WorldWideScience

Sample records for cluster-based universal control

  1. Development and evaluation of the efficacy of a web-based 'social norms'-intervention for the prevention and reduction of substance use in a cluster-controlled trial conducted at eight German universities.

    Science.gov (United States)

    Helmer, Stefanie M; Muellmann, Saskia; Zeeb, Hajo; Pischke, Claudia R

    2016-03-11

    Previous research suggests that perceptions of peer substance use are associated with personal use. Specifically, overestimating use in the peer group is predictive of higher rates of personal substance use. 'Social norms'-interventions are based on the premise that changing these misperceived social norms regarding substance use by providing feedback on actual norms is associated with a reduction in personal substance use. Studies conducted in the U.S.A. suggest that 'social norms'-feedback is an effective strategy for reducing substance use among university students. It is unknown whether the effects of a 'social norms'-feedback on substance use can be replicated in a sample of German university students. The objective of this article is to describe the study design and aims of the 'INternet-based Social norms-Intervention for the prevention of substance use among Students' (INSIST)-study, a cluster-controlled trial examining the effects of a web-based 'social norms'- intervention in students enrolled at four intervention universities with those enrolled at four delayed intervention control universities. The INSIST-study is funded by the German Federal Ministry of Health. Eight universities in four regions in Germany will take part in the study, four serving as intervention and four as delayed intervention control universities (randomly selected within a geographic region). Six hundred students will be recruited at each university and will be asked to complete a web-based survey assessing personal and perceived substance use/attitudes towards substance use at baseline. These data will be used to develop the web-based 'social norms'-feedback tailored to gender and university. Three months after the baseline survey, students at intervention universities will receive the intervention. Two months after the launch of the intervention, students of all eight universities will be asked to complete the follow-up questionnaires to assess changes in perceptions of

  2. Universal Internet-based prevention for alcohol and cannabis use reduces truancy, psychological distress and moral disengagement: a cluster randomised controlled trial.

    Science.gov (United States)

    Newton, Nicola C; Andrews, Gavin; Champion, Katrina E; Teesson, Maree

    2014-08-01

    A universal Internet-based preventive intervention has been shown to reduce alcohol and cannabis use. The aim of this study was to examine if this program could also reduce risk-factors associated with substance use in adolescents. A cluster randomised controlled trial was conducted in Sydney, Australia in 2007-2008 to assess the effectiveness of the Internet-based Climate Schools: Alcohol and Cannabis course. The evidence-based course, aimed at reducing alcohol and cannabis use, consists of two sets of six lessons delivered approximately six months apart. A total of 764 students (mean 13.1years) from 10 secondary schools were randomly allocated to receive the preventive intervention (n=397, five schools), or their usual health classes (n=367, five schools) over the year. Participants were assessed at baseline, immediately post, and six and twelve months following the intervention on their levels of truancy, psychological distress and moral disengagement. Compared to the control group, students in the intervention group showed significant reductions in truancy, psychological distress and moral disengagement up to twelve months following completion of the intervention. These intervention effects indicate that Internet-based preventive interventions designed to prevent alcohol and cannabis use can concurrently reduce risk-factors associated with substance use in adolescents. Australian Clinical Trials Registry ACTRN: 012607000312448. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. A 10-Week Multimodal Nutrition Education Intervention Improves Dietary Intake among University Students: Cluster Randomised Controlled Trial

    Directory of Open Access Journals (Sweden)

    Mohd Razif Shahril

    2013-01-01

    Full Text Available The aim of the study was to evaluate the effectiveness of implementing multimodal nutrition education intervention (NEI to improve dietary intake among university students. The design of study used was cluster randomised controlled design at four public universities in East Coast of Malaysia. A total of 417 university students participated in the study. They were randomly selected and assigned into two arms, that is, intervention group (IG or control group (CG according to their cluster. The IG received 10-week multimodal intervention using three modes (conventional lecture, brochures, and text messages while CG did not receive any intervention. Dietary intake was assessed before and after intervention and outcomes reported as nutrient intakes as well as average daily servings of food intake. Analysis of covariance (ANCOVA and adjusted effect size were used to determine difference in dietary changes between groups and time. Results showed that, compared to CG, participants in IG significantly improved their dietary intake by increasing their energy intake, carbohydrate, calcium, vitamin C and thiamine, fruits and 100% fruit juice, fish, egg, milk, and dairy products while at the same time significantly decreased their processed food intake. In conclusion, multimodal NEI focusing on healthy eating promotion is an effective approach to improve dietary intakes among university students.

  4. Physical-depth architectural requirements for generating universal photonic cluster states

    Science.gov (United States)

    Morley-Short, Sam; Bartolucci, Sara; Gimeno-Segovia, Mercedes; Shadbolt, Pete; Cable, Hugo; Rudolph, Terry

    2018-01-01

    Most leading proposals for linear-optical quantum computing (LOQC) use cluster states, which act as a universal resource for measurement-based (one-way) quantum computation. In ballistic approaches to LOQC, cluster states are generated passively from small entangled resource states using so-called fusion operations. Results from percolation theory have previously been used to argue that universal cluster states can be generated in the ballistic approach using schemes which exceed the critical threshold for percolation, but these results consider cluster states with unbounded size. Here we consider how successful percolation can be maintained using a physical architecture with fixed physical depth, assuming that the cluster state is continuously generated and measured, and therefore that only a finite portion of it is visible at any one point in time. We show that universal LOQC can be implemented using a constant-size device with modest physical depth, and that percolation can be exploited using simple pathfinding strategies without the need for high-complexity algorithms.

  5. Cluster-based control of a separating flow over a smoothly contoured ramp

    Science.gov (United States)

    Kaiser, Eurika; Noack, Bernd R.; Spohn, Andreas; Cattafesta, Louis N.; Morzyński, Marek

    2017-12-01

    The ability to manipulate and control fluid flows is of great importance in many scientific and engineering applications. The proposed closed-loop control framework addresses a key issue of model-based control: The actuation effect often results from slow dynamics of strongly nonlinear interactions which the flow reveals at timescales much longer than the prediction horizon of any model. Hence, we employ a probabilistic approach based on a cluster-based discretization of the Liouville equation for the evolution of the probability distribution. The proposed methodology frames high-dimensional, nonlinear dynamics into low-dimensional, probabilistic, linear dynamics which considerably simplifies the optimal control problem while preserving nonlinear actuation mechanisms. The data-driven approach builds upon a state space discretization using a clustering algorithm which groups kinematically similar flow states into a low number of clusters. The temporal evolution of the probability distribution on this set of clusters is then described by a control-dependent Markov model. This Markov model can be used as predictor for the ergodic probability distribution for a particular control law. This probability distribution approximates the long-term behavior of the original system on which basis the optimal control law is determined. We examine how the approach can be used to improve the open-loop actuation in a separating flow dominated by Kelvin-Helmholtz shedding. For this purpose, the feature space, in which the model is learned, and the admissible control inputs are tailored to strongly oscillatory flows.

  6. A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

    Science.gov (United States)

    Gui, Jinsong; Zhou, Kai; Xiong, Naixue

    2016-09-25

    Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

  7. A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

    Science.gov (United States)

    Gui, Jinsong; Zhou, Kai; Xiong, Naixue

    2016-01-01

    Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

  8. A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jinsong Gui

    2016-09-01

    Full Text Available Multi-Input Multi-Output (MIMO can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs, clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO, which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

  9. Toward demonstrating controlled-X operation based on continuous-variable four-partite cluster states and quantum teleporters

    International Nuclear Information System (INIS)

    Wang Yu; Su Xiaolong; Shen Heng; Tan Aihong; Xie Changde; Peng Kunchi

    2010-01-01

    One-way quantum computation based on measurement and multipartite cluster entanglement offers the ability to perform a variety of unitary operations only through different choices of measurement bases. Here we present an experimental study toward demonstrating the controlled-X operation, a two-mode gate in which continuous variable (CV) four-partite cluster states of optical modes are utilized. Two quantum teleportation elements are used for achieving the gate operation of the quantum state transformation from input target and control states to output states. By means of the optical cluster state prepared off-line, the homodyne detection and electronic feeding forward, the information carried by the input control state is transformed to the output target state. The presented scheme of the controlled-X operation based on teleportation can be implemented nonlocally and deterministically. The distortion of the quantum information resulting from the imperfect cluster entanglement is estimated with the fidelity.

  10. Simultaneous gains tuning in boiler/turbine PID-based controller clusters using iterative feedback tuning methodology.

    Science.gov (United States)

    Zhang, Shu; Taft, Cyrus W; Bentsman, Joseph; Hussey, Aaron; Petrus, Bryan

    2012-09-01

    Tuning a complex multi-loop PID based control system requires considerable experience. In today's power industry the number of available qualified tuners is dwindling and there is a great need for better tuning tools to maintain and improve the performance of complex multivariable processes. Multi-loop PID tuning is the procedure for the online tuning of a cluster of PID controllers operating in a closed loop with a multivariable process. This paper presents the first application of the simultaneous tuning technique to the multi-input-multi-output (MIMO) PID based nonlinear controller in the power plant control context, with the closed-loop system consisting of a MIMO nonlinear boiler/turbine model and a nonlinear cluster of six PID-type controllers. Although simplified, the dynamics and cross-coupling of the process and the PID cluster are similar to those used in a real power plant. The particular technique selected, iterative feedback tuning (IFT), utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed-loop system. Based on the figure of merit for the control system performance, the IFT is shown to deliver performance favorably comparable to that attained through the empirical tuning carried out by an experienced control engineer. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  11. INCUBATORS WITHIN UNIVERSITY AND CLUSTERED CONTEXTS: CASES OF NATIONAL CHIAO TUNG UNIVERSITY (NCTU AND NATIONAL TSING HUA UNIVERSITY (NTHU INCUBATORS IN HSINCHU, TAIWAN

    Directory of Open Access Journals (Sweden)

    Khairul Akmaliah Adham

    2008-01-01

    Full Text Available Research literature on business incubators has highlighted the significance of clustered locational contexts and networking as key to an incubator's success. Using the case study approach, this study aimed to test the validity of this framework for explaining the level of success of the National Chiao Tung University (NCTU and National Tsing Hua University (NTHU Incubators in Hsinchu, Taiwan – both of which are highly-networked, cluster-centric and university-based. In-depth interviews were conducted with the managers of both incubators, and these were followed by information gathering on university patents and knowledge transfers from the research and development (R&D office at each university. Analysis found that the incubators' locational contexts determined the degree and manner of their networking, but their profitability and growth potential were influenced by many other factors working in combination. Satisfying their sponsors' requirements and serving their core functions through sound management and strategic planning appeared to be the key to achieving profitability and sustainability, with benefits for all stakeholders. These constructs provide directions for more research on the performance of incubators and other business entities that are located within university and clustered contexts.

  12. The CLIMATE schools combined study: a cluster randomised controlled trial of a universal Internet-based prevention program for youth substance misuse, depression and anxiety.

    Science.gov (United States)

    Teesson, Maree; Newton, Nicola C; Slade, Tim; Chapman, Cath; Allsop, Steve; Hides, Leanne; McBride, Nyanda; Mewton, Louise; Tonks, Zoe; Birrell, Louise; Brownhill, Louise; Andrews, Gavin

    2014-02-05

    Anxiety, depressive and substance use disorders account for three quarters of the disability attributed to mental disorders and frequently co-occur. While programs for the prevention and reduction of symptoms associated with (i) substance use and (ii) mental health disorders exist, research is yet to determine if a combined approach is more effective. This paper describes the study protocol of a cluster randomised controlled trial to evaluate the effectiveness of the CLIMATE Schools Combined intervention, a universal approach to preventing substance use and mental health problems among adolescents. Participants will consist of approximately 8400 students aged 13 to 14-years-old from 84 secondary schools in New South Wales, Western Australia and Queensland, Australia. The schools will be cluster randomised to one of four groups; (i) CLIMATE Schools Combined intervention; (ii) CLIMATE Schools - Substance Use; (iii) CLIMATE Schools - Mental Health, or (iv) Control (Health and Physical Education as usual). The primary outcomes of the trial will be the uptake and harmful use of alcohol and other drugs, mental health symptomatology and anxiety, depression and substance use knowledge. Secondary outcomes include substance use related harms, self-efficacy to resist peer pressure, general disability, and truancy. The link between personality and substance use will also be examined. Compared to students who receive the universal CLIMATE Schools - Substance Use, or CLIMATE Schools - Mental Health or the Control condition (who received usual Health and Physical Education), we expect students who receive the CLIMATE Schools Combined intervention to show greater delays to the initiation of substance use, reductions in substance use and mental health symptoms, and increased substance use and mental health knowledge. This trial is registered with the Australian and New Zealand Clinical Trials registry, ACTRN12613000723785.

  13. The CLIMATE schools combined study: a cluster randomised controlled trial of a universal Internet-based prevention program for youth substance misuse, depression and anxiety

    Science.gov (United States)

    2014-01-01

    Background Anxiety, depressive and substance use disorders account for three quarters of the disability attributed to mental disorders and frequently co-occur. While programs for the prevention and reduction of symptoms associated with (i) substance use and (ii) mental health disorders exist, research is yet to determine if a combined approach is more effective. This paper describes the study protocol of a cluster randomised controlled trial to evaluate the effectiveness of the CLIMATE Schools Combined intervention, a universal approach to preventing substance use and mental health problems among adolescents. Methods/design Participants will consist of approximately 8400 students aged 13 to 14-years-old from 84 secondary schools in New South Wales, Western Australia and Queensland, Australia. The schools will be cluster randomised to one of four groups; (i) CLIMATE Schools Combined intervention; (ii) CLIMATE Schools - Substance Use; (iii) CLIMATE Schools - Mental Health, or (iv) Control (Health and Physical Education as usual). The primary outcomes of the trial will be the uptake and harmful use of alcohol and other drugs, mental health symptomatology and anxiety, depression and substance use knowledge. Secondary outcomes include substance use related harms, self-efficacy to resist peer pressure, general disability, and truancy. The link between personality and substance use will also be examined. Discussion Compared to students who receive the universal CLIMATE Schools - Substance Use, or CLIMATE Schools - Mental Health or the Control condition (who received usual Health and Physical Education), we expect students who receive the CLIMATE Schools Combined intervention to show greater delays to the initiation of substance use, reductions in substance use and mental health symptoms, and increased substance use and mental health knowledge. Trial registration This trial is registered with the Australian and New Zealand Clinical Trials registry, ACTRN12613000723785

  14. Swarm controlled emergence for ant clustering

    DEFF Research Database (Denmark)

    Scheidler, Alexander; Merkle, Daniel; Middendorf, Martin

    2013-01-01

    .g. moving robots, and clustering algorithms. Design/methodology/approach: Different types of control agents for that ant clustering model are designed by introducing slight changes to the behavioural rules of the normal agents. The clustering behaviour of the resulting swarms is investigated by extensive...... for future research to investigate the application of the method in other swarm systems. Swarm controlled emergence might be applied to control emergent effects in computing systems that consist of many autonomous components which make decentralized decisions based on local information. Practical...... simulation studies. Findings: It is shown that complex behavior can emerge in systems with two types of agents (normal agents and control agents). For a particular behavior of the control agents, an interesting swarm size dependent effect was found. The behaviour prevents clustering when the number...

  15. Cluster-based adaptive power control protocol using Hidden Markov Model for Wireless Sensor Networks

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    Vinutha, C. B.; Nalini, N.; Nagaraja, M.

    2017-06-01

    This paper presents strategies for an efficient and dynamic transmission power control technique, in order to reduce packet drop and hence energy consumption of power-hungry sensor nodes operated in highly non-linear channel conditions of Wireless Sensor Networks. Besides, we also focus to prolong network lifetime and scalability by designing cluster-based network structure. Specifically we consider weight-based clustering approach wherein, minimum significant node is chosen as Cluster Head (CH) which is computed stemmed from the factors distance, remaining residual battery power and received signal strength (RSS). Further, transmission power control schemes to fit into dynamic channel conditions are meticulously implemented using Hidden Markov Model (HMM) where probability transition matrix is formulated based on the observed RSS measurements. Typically, CH estimates initial transmission power of its cluster members (CMs) from RSS using HMM and broadcast this value to its CMs for initialising their power value. Further, if CH finds that there are variations in link quality and RSS of the CMs, it again re-computes and optimises the transmission power level of the nodes using HMM to avoid packet loss due noise interference. We have demonstrated our simulation results to prove that our technique efficiently controls the power levels of sensing nodes to save significant quantity of energy for different sized network.

  16. On the clustering of particles in an expanding Universe

    International Nuclear Information System (INIS)

    Efstathiou, G.; Eastwood, J.W.

    1981-01-01

    The clustering of particles is investigated in Friedmann models of the Universe using 1000- and 20 000-body numerical simulations. The results of these computations are analysed in terms of the two- and three-point correlation functions, the mean relative peculiar velocity between particle pairs and the mean square peculiar velocity dispersion between pairs. In the case of Einstein-de Sitter models it is found that on scales corresponding to the transition region the results are in rough agreement with simple analytic treatments based on the homogeneous spherical cluster models for the collapse of protoclusters. The results are in conflict with the kinetic theory calculations of Davis and Peebles who studied the problem in the case of an Einstein-de Sitter Universe and found good agreement with observational data. These authors suggest that clusters develop substantial non-radial motions whilst they are still small density fluctuations, so that when a cluster fragments out of the general Hubble expansion, it is already virialized. This 'previrialization' effect does not appear to occur in the numerical models described here. The effects of particle discreteness and two-body relaxation, which are particularly important in the N-body models but neglected in the approach of Davis and Peebles are also examined. (author)

  17. The CAP study, evaluation of integrated universal and selective prevention strategies for youth alcohol misuse: study protocol of a cluster randomized controlled trial

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    Newton Nicola C

    2012-08-01

    Full Text Available Abstract Background Alcohol misuse amongst young people is a serious concern. The need for effective prevention is clear, yet there appear to be few evidenced-based programs that prevent alcohol misuse and none that target both high and low-risk youth. The CAP study addresses this gap by evaluating the efficacy of an integrated approach to alcohol misuse prevention, which combines the effective universal internet-based Climate Schools program with the effective selective personality-targeted Preventure program. This article describes the development and protocol of the CAP study which aims to prevent alcohol misuse and related harms in Australian adolescents. Methods/Design A cluster randomized controlled trial (RCT is being conducted with Year 8 students aged 13 to 14-years-old from 27 secondary schools in New South Wales and Victoria, Australia. Blocked randomisation was used to assign schools to one of four groups; Climate Schools only, Preventure only, CAP (Climate Schools and Preventure, or Control (alcohol, drug and health education as usual. The primary outcomes of the trial will be the uptake and harmful use of alcohol and alcohol related harms. Secondary outcomes will include alcohol and cannabis related knowledge, cannabis related harms, intentions to use, and mental health symptomatology. All participants will complete assessments on five occasions; baseline; immediately post intervention, and at 12, 24 and 36 months post baseline. Discussion This study protocol presents the design and current implementation of a cluster RCT to evaluate the efficacy of the CAP study; an integrated universal and selective approach to prevent alcohol use and related harms among adolescents. Compared to students who receive the stand-alone universal Climate Schools program or alcohol and drug education as usual (Controls, we expect the students who receive the CAP intervention to have significantly less uptake of alcohol use, a reduction in average

  18. Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

    International Nuclear Information System (INIS)

    Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

    2013-01-01

    This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network

  19. Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

    Science.gov (United States)

    Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

    2013-12-01

    This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.

  20. Performance Analysis of Quality-of-Service Controls in a Cell-Cluster-Based Wireless ATM Network

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Young Jong [Ajou University, Suwon (Korea, Republic of)

    1997-04-01

    In this paper, an efficient cell-cluster-based call control scheme with guaranteed quality-of-service(QoS) provision ing is presented for next generation wireless ATM networks and its performance is mathematically analyzed using the open queuing network. With the cell-cluster-based call control, at the time a mobile connection is admitted to the network, a virtual cell is constructed by choosing a group of neighboring base stations to which the call may probabilistic ally hand over and by assigning to the call a collection of virtual paths between the base stations. Within a micro cell/pico cell environment, it is seen that the cell-cluster-based call control can support effectively a very high rate of handovers, provides very high system capacity, and guarantees a high degree of frequency reuse over the same geographical region without requiring the intervention of the network call control processor each time a handover occurs. But since mobiles, once admitted, are free to roam within the virtual cell, congestion condition occurs in which the number of calls to be handled by one base station exceeds the cell sites` capacity of radio channel and consequently a predefined QoS provision cannot be guaranteed. So, there must be a call admission control function to limit the number of calls existing in a cell-cluster such that required QoS objectives are met. As call acceptance criteria for constant-bit-rate or realtime variable-bit-rate ATM connections, we define four mobile QoS metrics: new-call blocking probability, wireless channel utilization efficiency, congestion probability and normalized average congestion duration. In addition, for QoS provision ing to available-bit-rate, unspecified-bit-rate or non-realtime variable-bit-rate connections, we further define another QoS metric, the minimum threshold breaking probability. By using the open network queuing model, we derive closed form expressions for the five QoS metrics defined above and show that they can be

  1. ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster.

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    Stocker, Gernot; Rieder, Dietmar; Trajanoski, Zlatko

    2004-03-22

    ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions. http://genome.tugraz.at/Software/ClusterControl

  2. A Novel Cluster Head Selection Algorithm Based on Fuzzy Clustering and Particle Swarm Optimization.

    Science.gov (United States)

    Ni, Qingjian; Pan, Qianqian; Du, Huimin; Cao, Cen; Zhai, Yuqing

    2017-01-01

    An important objective of wireless sensor network is to prolong the network life cycle, and topology control is of great significance for extending the network life cycle. Based on previous work, for cluster head selection in hierarchical topology control, we propose a solution based on fuzzy clustering preprocessing and particle swarm optimization. More specifically, first, fuzzy clustering algorithm is used to initial clustering for sensor nodes according to geographical locations, where a sensor node belongs to a cluster with a determined probability, and the number of initial clusters is analyzed and discussed. Furthermore, the fitness function is designed considering both the energy consumption and distance factors of wireless sensor network. Finally, the cluster head nodes in hierarchical topology are determined based on the improved particle swarm optimization. Experimental results show that, compared with traditional methods, the proposed method achieved the purpose of reducing the mortality rate of nodes and extending the network life cycle.

  3. IMPLEMENTASI ALGORITMA K-MEANS CLUSTERING UNTUK MENENTUKAN STRATEGI MARKETING PRESIDENT UNIVERSITY

    Directory of Open Access Journals (Sweden)

    Johan Oscar Ong

    2013-06-01

    Full Text Available Information technology advances very rapidly at this time to generate thousands or even millions of data from various aspect of life. However, what can be done with that much data?. In this research, we start from calculation of data set of students who have graduated from President University using k-means clustering algorithm, namely by classifying the data of students into several clusters based on the characteristics of this data in order to discover the information hidden from the data set of student who have graduated from President University. The attribute data that is used in this study is hometown, major and GPA. The purpose of this study is to help the President University's marketing department in predicting promotion strategies undertaken in the cities in Indonesia. Information gained in this study can be used as a references in determining the proper strategy for marketing team in their promotion activities in the cities in Indonesia so that the campaign will be more effective and efficient.

  4. Data Mining of University Philanthropic Giving: Cluster-Discriminant Analysis and Pareto Effects

    Science.gov (United States)

    Le Blanc, Louis A.; Rucks, Conway T.

    2009-01-01

    A large sample of 33,000 university alumni records were cluster-analyzed to generate six groups relatively unique in their respective attribute values. The attributes used to cluster the former students included average gift to the university's foundation and to the alumni association for the same institution. Cluster detection is useful in this…

  5. The size of clusters in a neutrino-dominated universe

    International Nuclear Information System (INIS)

    White, S.D.M.; Davis, M.; Frenk, C.S.

    1984-01-01

    Quite soon after the first collapse of structure almost half the matter in a neutrino-dominated universe is expected to reside in clusters. The masses and binding energies of these neutrino clusters are too large for them to be identified with observed galaxy clusters. Even if such objects were able to suppress all galaxy formation, their X-ray emission would, however, make them highly visible if more than 2.5 per cent of their mass was in ordinary matter. Such a low baryon density leads to insufficient cooling for galaxies to form in pancakes. A neutrino-dominated universe appears to conflict with observation irrespective of the details of the processes which govern galaxy formation. (author)

  6. Can group-based reassuring information alter low back pain behavior? A cluster-randomized controlled trial

    DEFF Research Database (Denmark)

    Frederiksen, Pernille; Indahl, Aage; Andersen, Lars L

    2017-01-01

    -randomized controlled trial. METHODS: Publically employed workers (n = 505) from 11 Danish municipality centers were randomized at center-level (cluster) to either intervention (two 1-hour group-based talks at the workplace) or control. The talks provided reassuring information together with a simple non...

  7. Chaos control of ferroresonance system based on RBF-maximum entropy clustering algorithm

    International Nuclear Information System (INIS)

    Liu Fan; Sun Caixin; Sima Wenxia; Liao Ruijin; Guo Fei

    2006-01-01

    With regards to the ferroresonance overvoltage of neutral grounded power system, a maximum-entropy learning algorithm based on radial basis function neural networks is used to control the chaotic system. The algorithm optimizes the object function to derive learning rule of central vectors, and uses the clustering function of network hidden layers. It improves the regression and learning ability of neural networks. The numerical experiment of ferroresonance system testifies the effectiveness and feasibility of using the algorithm to control chaos in neutral grounded system

  8. Blind Quantum Signature with Controlled Four-Particle Cluster States

    Science.gov (United States)

    Li, Wei; Shi, Jinjing; Shi, Ronghua; Guo, Ying

    2017-08-01

    A novel blind quantum signature scheme based on cluster states is introduced. Cluster states are a type of multi-qubit entangled states and it is more immune to decoherence than other entangled states. The controlled four-particle cluster states are created by acting controlled-Z gate on particles of four-particle cluster states. The presented scheme utilizes the above entangled states and simplifies the measurement basis to generate and verify the signature. Security analysis demonstrates that the scheme is unconditional secure. It can be employed to E-commerce systems in quantum scenario.

  9. A study of hierarchical clustering of galaxies in an expanding universe

    Science.gov (United States)

    Porter, D. H.

    The nonlinear hierarchical clustering of galaxies in an Einstein-deSitter (Omega = 1), initially white noise mass fluctuations (n = 0) model universe is investigated and shown to be in contradiction with previous results. The model is done in terms of an 11,000-body numerical simulation. The independent statics of 0.72 million particles are used to simulte the boundary conditions. A new method for integrating the Newtonian N-body gravity equations, which has controllable accuracy, incorporates a recursive center of mass reduction, and regularizes two body encounters is used to do the simulation. The coordinate system used here is well suited for the investigation of galaxy clustering, incorporating the independent positions and velocities of an arbitrary number of particles into a logarithmic hierarchy of center of mass nodes. The boundary for the simulation is created by using this hierarchy to map the independent statics of 0.72 million particles into just 4,000 particles. This method for simulating the boundary conditions also has controllable accuracy.

  10. School-based suicide prevention programmes: the SEYLE cluster-randomised, controlled trial.

    Science.gov (United States)

    Wasserman, Danuta; Hoven, Christina W; Wasserman, Camilla; Wall, Melanie; Eisenberg, Ruth; Hadlaczky, Gergö; Kelleher, Ian; Sarchiapone, Marco; Apter, Alan; Balazs, Judit; Bobes, Julio; Brunner, Romuald; Corcoran, Paul; Cosman, Doina; Guillemin, Francis; Haring, Christian; Iosue, Miriam; Kaess, Michael; Kahn, Jean-Pierre; Keeley, Helen; Musa, George J; Nemes, Bogdan; Postuvan, Vita; Saiz, Pilar; Reiter-Theil, Stella; Varnik, Airi; Varnik, Peeter; Carli, Vladimir

    2015-04-18

    Suicidal behaviours in adolescents are a major public health problem and evidence-based prevention programmes are greatly needed. We aimed to investigate the efficacy of school-based preventive interventions of suicidal behaviours. The Saving and Empowering Young Lives in Europe (SEYLE) study is a multicentre, cluster-randomised controlled trial. The SEYLE sample consisted of 11,110 adolescent pupils, median age 15 years (IQR 14-15), recruited from 168 schools in ten European Union countries. We randomly assigned the schools to one of three interventions or a control group. The interventions were: (1) Question, Persuade, and Refer (QPR), a gatekeeper training module targeting teachers and other school personnel, (2) the Youth Aware of Mental Health Programme (YAM) targeting pupils, and (3) screening by professionals (ProfScreen) with referral of at-risk pupils. Each school was randomly assigned by random number generator to participate in one intervention (or control) group only and was unaware of the interventions undertaken in the other three trial groups. The primary outcome measure was the number of suicide attempt(s) made by 3 month and 12 month follow-up. Analysis included all pupils with data available at each timepoint, excluding those who had ever attempted suicide or who had shown severe suicidal ideation during the 2 weeks before baseline. This study is registered with the German Clinical Trials Registry, number DRKS00000214. Between Nov 1, 2009, and Dec 14, 2010, 168 schools (11,110 pupils) were randomly assigned to interventions (40 schools [2692 pupils] to QPR, 45 [2721] YAM, 43 [2764] ProfScreen, and 40 [2933] control). No significant differences between intervention groups and the control group were recorded at the 3 month follow-up. At the 12 month follow-up, YAM was associated with a significant reduction of incident suicide attempts (odds ratios [OR] 0·45, 95% CI 0·24-0·85; p=0·014) and severe suicidal ideation (0·50, 0·27-0·92; p=0·025

  11. Adaptive Marginal Costs-Based Distributed Economic Control of Microgrid Clusters Considering Line Loss

    Directory of Open Access Journals (Sweden)

    Xiaoqian Zhou

    2017-12-01

    Full Text Available When several microgrids (MG are interconnected into microgrid clusters (MGC, they have great potential to improve their reliability. Traditional droop control tends to make the total operating costs higher as the power is distributed by capacity ratios of distributed energy resources (DERs. This paper proposes an adaptive distributed economic control for islanded microgrids which considers line loss, specifically, an interesting marginal costs-based economic droop control is proposed, and consensus-based adaptive controller is applied, to deal with power limits and capacity constraints for storage. The whole expense can be effectively lowered by achieving identical marginal costs for DERs in MGC. Specially, the capacity constraints only for storages are also included to do further optimization. Moreover, consensus-based distributed secondary controllers are used to rapidly restore system frequency and voltage magnitudes. The above controllers only need to interact with neighbor DERs by a sparse communication network, eliminating the necessity of a central controller and enhancing the stability. A MGC, incorporating three microgrids, is used to verify the effectiveness of the proposed methods.

  12. Satellite cluster flight using on-off cyclic control

    Science.gov (United States)

    Zhang, Hao; Gurfil, Pini

    2015-01-01

    Nano-satellite clusters and disaggregated satellites are new concepts in the realm of distributed satellite systems, which require complex cluster management - mainly regulating the maximal and minimal inter-satellite distances on time scales of years - while utilizing simple on-off propulsion systems. The simple actuators and long time scales require judicious astrodynamical modeling coupled with specialized orbit control. This paper offers a satellite cluster orbit control law which works for long time scales in a perturbed environment while utilizing fixed-magnitude thrusters. The main idea is to design a distributed controller which balances the fuel consumption among the satellites, thus mitigating the effect of differential drag perturbations. The underlying methodology utilizes a cyclic control algorithm based on a mean orbital elements feedback. Stability properties of the closed-loop cyclic control system do not adhere to the classical Lyapunov stability theory, so an effort is made to define and implement a suitable stability theory of noncompact equilibria sets. A state selection scheme is proposed for efficiently establishing a low Earth orbit cluster. Several simulations, including a real mission study, and several comparative investigations, are performed to show the strengths of the proposed control law.

  13. Mindfulness-based prevention for eating disorders: A school-based cluster randomized controlled study.

    Science.gov (United States)

    Atkinson, Melissa J; Wade, Tracey D

    2015-11-01

    Successful prevention of eating disorders represents an important goal due to damaging long-term impacts on health and well-being, modest treatment outcomes, and low treatment seeking among individuals at risk. Mindfulness-based approaches have received early support in the treatment of eating disorders, but have not been evaluated as a prevention strategy. This study aimed to assess the feasibility, acceptability, and efficacy of a novel mindfulness-based intervention for reducing the risk of eating disorders among adolescent females, under both optimal (trained facilitator) and task-shifted (non-expert facilitator) conditions. A school-based cluster randomized controlled trial was conducted in which 19 classes of adolescent girls (N = 347) were allocated to a three-session mindfulness-based intervention, dissonance-based intervention, or classes as usual control. A subset of classes (N = 156) receiving expert facilitation were analyzed separately as a proxy for delivery under optimal conditions. Task-shifted facilitation showed no significant intervention effects across outcomes. Under optimal facilitation, students receiving mindfulness demonstrated significant reductions in weight and shape concern, dietary restraint, thin-ideal internalization, eating disorder symptoms, and psychosocial impairment relative to control by 6-month follow-up. Students receiving dissonance showed significant reductions in socio-cultural pressures. There were no statistically significant differences between the two interventions. Moderate intervention acceptability was reported by both students and teaching staff. Findings show promise for the application of mindfulness in the prevention of eating disorders; however, further work is required to increase both impact and acceptability, and to enable successful outcomes when delivered by less expert providers. © 2015 Wiley Periodicals, Inc.

  14. On the universality of MOG weak field approximation at galaxy cluster scale

    Directory of Open Access Journals (Sweden)

    Ivan De Martino

    2017-07-01

    Full Text Available In its weak field limit, Scalar-tensor-vector gravity theory introduces a Yukawa-correction to the gravitational potential. Such a correction depends on the two parameters, α which accounts for the modification of the gravitational constant, and μ⁎−1 which represents the scale length on which the scalar field propagates. These parameters were found to be universal when the modified gravitational potential was used to fit the galaxy rotation curves and the mass profiles of galaxy clusters, both without Dark Matter. We test the universality of these parameters using the temperature anisotropies due to the thermal Sunyaev–Zeldovich effect. In our model the intra-cluster gas is in hydrostatic equilibrium within the modified gravitational potential well and it is described by a polytropic equation of state. We predict the thermal Sunyaev–Zeldovich temperature anisotropies produced by Coma cluster, and we compare them with those obtained using the Planck 2013 Nominal maps. In our analysis, we find α and the scale length, respectively, to be consistent and to depart from their universal values. Our analysis points out that the assumption of the universality of the Yukawa-correction to the gravitational potential is ruled out at more than 3.5σ at galaxy clusters scale, while demonstrating that such a theory of gravity is capable to fit the cluster profile if the scale dependence of the gravitational potential is restored.

  15. A cluster randomized controlled trial testing the effectiveness of Houvast: A strengths-based intervention for homeless young adults

    NARCIS (Netherlands)

    Krabbenborg, M.A.M.; Boersma, S.N.; Veld, W.M. van der; Hulst, B. van; Vollebergh, W.A.M.; Wolf, J.R.L.M.

    2017-01-01

    Objective: To test the effectiveness of Houvast: a strengths-based intervention for homeless young adults. Method: A cluster randomized controlled trial was conducted with 10 Dutch shelter facilities randomly allocated to an intervention and a control group. Homeless young adults were interviewed

  16. The effectiveness of a clinically integrated e-learning course in evidence-based medicine: A cluster randomised controlled trial

    NARCIS (Netherlands)

    Kulier, Regina; Coppus, Sjors F. P. J.; Zamora, Javier; Hadley, Julie; Malick, Sadia; Das, Kausik; Weinbrenner, Susanne; Meyerrose, Berrit; Decsi, Tamas; Horvath, Andrea R.; Nagy, Eva; Emparanza, Jose I.; Arvanitis, Theodoros N.; Burls, Amanda; Cabello, Juan B.; Kaczor, Marcin; Zanrei, Gianni; Pierer, Karen; Stawiarz, Katarzyna; Kunz, Regina; Mol, Ben W. J.; Khan, Khalid S.

    2009-01-01

    ABSTRACT: BACKGROUND: To evaluate the educational effects of a clinically integrated e-learning course for teaching basic evidence-based medicine (EBM) among postgraduates compared to a traditional lecture-based course of equivalent content. METHODS: We conducted a cluster randomised controlled

  17. An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks.

    Science.gov (United States)

    Hosen, A S M Sanwar; Cho, Gi Hwan

    2018-05-11

    Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head's role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks' information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime.

  18. Gravitational Clustering of Galaxies in an Expanding Universe ...

    Indian Academy of Sciences (India)

    2006-12-08

    Dec 8, 2006 ... Abstract. We inquire the phenomena of clustering of galaxies in an expanding universe from a theoretical point of view on the basis of ther- modynamics and correlation functions. The partial differential equation is developed both for the point mass and extended mass structures of a two-point correlation ...

  19. Web-based consultation between general practitioners and nephrologists: a cluster randomized controlled trial.

    Science.gov (United States)

    van Gelder, Vincent A; Scherpbier-de Haan, Nynke D; van Berkel, Saskia; Akkermans, Reinier P; de Grauw, Inge S; Adang, Eddy M; Assendelft, Pim J; de Grauw, Wim J C; Biermans, Marion C J; Wetzels, Jack F M

    2017-08-01

    Consultation of a nephrologist is important in aligning care for patients with chronic kidney disease (CKD) at the primary-secondary care interface. However, current consultation methods come with practical difficulties that can lead to postponed consultation or patient referral instead. This study aimed to investigate whether a web-based consultation platform, telenephrology, led to a lower referral rate of indicated patients. Furthermore, we assessed consultation rate, quality of care, costs and general practitioner (GPs') experiences with telenephrology. Cluster randomized controlled trial with 47 general practices in the Netherlands was randomized to access to telenephrology or to enhanced usual care. A total of 3004 CKD patients aged 18 years or older who were under primary care were included (intervention group n = 1277, control group n = 1727) and 2693 completed the trial. All practices participated in a CKD management course and were given an overview of their CKD patients. The referral rates amounted to 2.3% (n = 29) in the intervention group and 3.0% (n = 52) in the control group, which was a non-significant difference, OR 0.61; 95% CI 0.31 to 1.23. The intervention group's consultation rate was 6.3% (n = 81) against 5.0% (n = 87) (OR 2.00; 95% CI 0.75-5.33). We found no difference in quality of care or costs. The majority of GPs had a positive opinion about telenephrology. The data in our study do not allow for conclusions on the effect of telenephrology on the rate of patient referrals and provider-to-provider consultations, compared to conventional methods. It was positively evaluated by GPs and was non-inferior in terms of quality of care and costs. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  20. Development of Universal Controller Architecture for SiC Based Power Electronic Building Blocks

    Science.gov (United States)

    2017-10-30

    SiC Based Power Electronic Building Blocks Award Number Title of Research 30 October 2017 SUBMITTED BY D R. HERBERT L. G INN, Pl DEPT. OF...Naval Research , Philadelphia PA, Aug. 2017. • Ginn, H.L. Bakos J., "Development of Universal Controller Architecture for SiC Based Power Electronic...Controller Implementation for MMC Converters", Workshop on Control Architectures for Modular Power Conversion Systems, Office of Naval Research , Arlington VA

  1. ASSESSMENT OF PROFESSIONAL SKILLS OF STUDENTS IN IT-BASED CONTROLLED EDUCATIONAL ENVIRONMENT OF A UNIVERSITY

    Directory of Open Access Journals (Sweden)

    Evgeiy Nikolaevich Boyarov

    2013-08-01

    Full Text Available The article looks at the problem of estimating professional skills of students, the process of their building and assessing their level in IT-based controlled educational environment of a university. The author presents research findings of professional skills level of future educational professionals in the field of Life Safety[1] based on their academic results.Goal: to develop and show by experiments efficiency of building professional skills of students in IT-based controlled educational environment of a university.Results: increasing the level of professional skills in IT-based controlled educational environment of a university.Scope of application of results: field of higher professional education.DOI: http://dx.doi.org/10.12731/2218-7405-2013-7-1[1] Life Safety or Fundamentals of Health and Safety is a secondary school subject, which involves teaching basic rules of how to act in dangerous situations in everyday life (natural disasters, fires, terrorist attacks, etc., provide first aid, etc.

  2. Probing the z > 6 Universe with the First Hubble Frontier Fields Cluster A2744

    Science.gov (United States)

    Atek, Hakim; Richard, Johan; Kneib, Jean-Paul; Clement, Benjamin; Egami, Eiichi; Ebeling, Harald; Jauzac, Mathilde; Jullo, Eric; Laporte, Nicolas; Limousin, Marceau; Natarajan, Priyamvada

    2014-05-01

    The Hubble Frontier Fields program combines the capabilities of the Hubble Space Telescope (HST) with the gravitational lensing of massive galaxy clusters to probe the distant universe to an unprecedented depth. Here, we present the results of the first combined HST and Spitzer observations of the cluster A-2744. We combine the full near-infrared data with ancillary optical images to search for gravitationally lensed high-redshift (z >~ 6) galaxies. We report the detection of 15 I 814 dropout candidates at z ~ 6-7 and one Y 105 dropout at z ~ 8 in a total survey area of 1.43 arcmin2 in the source plane. The predictions of our lens model also allow us to identify five multiply imaged systems lying at redshifts between z ~ 6 and z ~ 8. Thanks to constraints from the mass distribution in the cluster, we were able to estimate the effective survey volume corrected for completeness and magnification effects. This was in turn used to estimate the rest-frame ultraviolet luminosity function (LF) at z ~ 6-8. Our LF results are generally in agreement with the most recent blank field estimates, confirming the feasibility of surveys through lensing clusters. Although based on a shallower observations than what will be achieved in the final data set including the full Advanced Camera for Survey observations, the LF presented here goes down to M UV ~-18.5, corresponding to 0.2L sstarf at z ~ 7 with one identified object at M UV ~-15 thanks to the highly magnified survey areas. This early study forecasts the power of using massive galaxy clusters as cosmic telescopes and its complementarity to blank fields. Based on observations made with the NASA/ESA Hubble Space Telescope (HST), which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with programs 13495 and 11689. Based in part on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory

  3. True Green and Sustainable University Campuses? Toward a Clusters Approach

    Directory of Open Access Journals (Sweden)

    Giulia Sonetti

    2016-01-01

    Full Text Available Campus greening is often the first step universities take towards sustainability. However, the diffusion of sustainability reporting methodologies and rankings is still at an early stage, and is biased in mainly measuring energy efficiency indicators while omitting basic features enabling meaningful comparisons among centers or addressing social (users aspects related to long term sustainability transitions. This paper aims to introduce a critical perspective on sustainability university frameworks through: (i a review of current Campus Sustainability Assessments (CSAs; (ii performing and comparing the results obtained from the application of two internationally recognized CSAs (namely, Green Metric and ISCN to two case studies (the Politecnico di Torino, in Italy, and the Hokkaido University, In Japan and, finally, (iii proposing a new CSA approach that encompasses clusters of homogeneous campus typologies for meaningful comparisons and university rankings. The proposed clusters regard universities’ morphological structures (campuses nested within city centers versus outside of a city compact ones, climatic zones and functions. At the micro scale, the paper introduces the need for indicators beyond measuring pure energy efficiency, but which are attentive to local and societal constraints and provide long-term tracking of outcomes. This, better than a sheer record of sustainability priority actions, can help in building homogenous university case studies to find similar and scalable success strategies and practices, and also in self-monitoring progress toward achieving truly sustainable university campuses.

  4. Galaxy clusters in simulations of the local Universe: a matter of constraints

    Science.gov (United States)

    Sorce, Jenny G.; Tempel, Elmo

    2018-06-01

    To study the full formation and evolution history of galaxy clusters and their population, high-resolution simulations of the latter are flourishing. However, comparing observed clusters to the simulated ones on a one-to-one basis to refine the models and theories down to the details is non-trivial. The large variety of clusters limits the comparisons between observed and numerical clusters. Simulations resembling the local Universe down to the cluster scales permit pushing the limit. Simulated and observed clusters can be matched on a one-to-one basis for direct comparisons provided that clusters are well reproduced besides being in the proper large-scale environment. Comparing random and local Universe-like simulations obtained with differently grouped observational catalogues of peculiar velocities, this paper shows that the grouping scheme used to remove non-linear motions in the catalogues that constrain the simulations affects the quality of the numerical clusters. With a less aggressive grouping scheme - galaxies still falling on to clusters are preserved - combined with a bias minimization scheme, the mass of the dark matter haloes, simulacra for five local clusters - Virgo, Centaurus, Coma, Hydra, and Perseus - is increased by 39 per cent closing the gap with observational mass estimates. Simulacra are found on average in 89 per cent of the simulations, an increase of 5 per cent with respect to the previous grouping scheme. The only exception is Perseus. Since the Perseus-Pisces region is not well covered by the used peculiar velocity catalogue, the latest release lets us foresee a better simulacrum for Perseus in a near future.

  5. A Cluster Randomized Controlled Trial Testing the Effectiveness of Houvast: A Strengths-Based Intervention for Homeless Young Adults

    Science.gov (United States)

    Krabbenborg, Manon A. M.; Boersma, Sandra N.; van der Veld, William M.; van Hulst, Bente; Vollebergh, Wilma A. M.; Wolf, Judith R. L. M.

    2017-01-01

    Objective: To test the effectiveness of Houvast: a strengths-based intervention for homeless young adults. Method: A cluster randomized controlled trial was conducted with 10 Dutch shelter facilities randomly allocated to an intervention and a control group. Homeless young adults were interviewed when entering the facility and when care ended.…

  6. Ionized-cluster source based on high-pressure corona discharge

    International Nuclear Information System (INIS)

    Lokuliyanage, K.; Huber, D.; Zappa, F.; Scheier, P.

    2006-01-01

    Full text: It has been demonstrated that energetic beams of large clusters, with thousands of atoms, can be a powerful tool for surface modification. Normally ionized cluster beams are obtained by electron impact on neutral beams produced in a supersonic expansion. At the University of Innsbruck we are pursuing the realization of a high current cluster ion source based on the corona discharge.The idea in the present case is that the ionization should occur prior to the supersonic expansion, thus supersede the need of subsequent electron impact. In this contribution we present the project of our source in its initial stage. The intensity distribution of cluster sizes as a function of the source parameters, such as input pressure, temperature and gap voltage, are investigated with the aid of a custom-built time of flight mass spectrometer. (author)

  7. Cluster Based Hierarchical Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, Md. Golam; Kabir, M. Hasnat; Rahim, Muhammad Sajjadur; Ullah, Shaikh Enayet

    2012-01-01

    The efficient use of energy source in a sensor node is most desirable criteria for prolong the life time of wireless sensor network. In this paper, we propose a two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP). We introduce a new concept called head-set, consists of one active cluster head and some other associate cluster heads within a cluster. The head-set members are responsible for control and management of the network. Results show that t...

  8. Coordinated voltage control in offshore HVDC connected cluster of wind power plants

    DEFF Research Database (Denmark)

    Sakamuri, Jayachandra Naidu; Rather, Zakir Hussain; Rimez, Johan

    This paper presents a coordinated voltage control scheme (CVCS) for a cluster of offshore wind power plants connected to a voltage-source converter-based high-voltage direct current system. The primary control point of the proposed voltage control scheme is the introduced Pilot bus, which is having...... by dispatching reactive power references to each wind turbine (WT) in the wind power plant cluster based on their available reactive power margin and network sensitivity-based participation factors, which are derived from the dV/dQ sensitivity of a WT bus w.r.t. the Pilot bus. This method leads...

  9. Voting-based consensus clustering for combining multiple clusterings of chemical structures

    Directory of Open Access Journals (Sweden)

    Saeed Faisal

    2012-12-01

    Full Text Available Abstract Background Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster. Results The cumulative voting-based aggregation algorithm (CVAA, cluster-based similarity partitioning algorithm (CSPA and hyper-graph partitioning algorithm (HGPA were examined. The F-measure and Quality Partition Index method (QPI were used to evaluate the clusterings and the results were compared to the Ward’s clustering method. The MDL Drug Data Report (MDDR dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward’s method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward’s method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria. Conclusions The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA was the method of choice among consensus clustering methods.

  10. An exploratory cluster randomised trial of a university halls of residence based social norms marketing campaign to reduce alcohol consumption among 1st year students.

    Science.gov (United States)

    Moore, Graham F; Williams, Annie; Moore, Laurence; Murphy, Simon

    2013-04-18

    This exploratory trial examines the feasibility of implementing a social norms marketing campaign to reduce student drinking in universities in Wales, and evaluating it using cluster randomised trial methodology. Fifty residence halls in 4 universities in Wales were randomly assigned to intervention or control arms. Web and paper surveys were distributed to students within these halls (n = 3800), assessing exposure/contamination, recall of and evaluative responses to intervention messages, perceived drinking norms and personal drinking behaviour. Measures included the Drinking Norms Rating Form, the Daily Drinking Questionnaire and AUDIT-C. A response rate of 15% (n = 554) was achieved, varying substantially between sites. Intervention posters were seen by 80% and 43% of students in intervention and control halls respectively, with most remaining materials seen by a minority in both groups. Intervention messages were rated as credible and relevant by little more than half of students, though fewer felt they would influence their behaviour, with lighter drinkers more likely to perceive messages as credible. No differences in perceived norms were observed between intervention and control groups. Students reporting having seen intervention materials reported lower descriptive and injunctive norms than those who did not. Attention is needed to enhancing exposure, credibility and perceived relevance of intervention messages, particularly among heavier drinkers, before definitive evaluation can be recommended. A definitive evaluation would need to consider how it would achieve sufficient response rates, whilst hall-level cluster randomisation appears subject to a significant degree of contamination. ISRCTN: ISRCTN48556384.

  11. Text Clustering Algorithm Based on Random Cluster Core

    Directory of Open Access Journals (Sweden)

    Huang Long-Jun

    2016-01-01

    Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

  12. A cluster-based randomized controlled trial promoting community participation in arsenic mitigation efforts in Bangladesh

    OpenAIRE

    George, Christine Marie; van Geen, Alexander; Slavkovich, Vesna; Singha, Ashit; Levy, Diane; Islam, Tariqul; Ahmed, Kazi Matin; Moon-Howard, Joyce; Tarozzi, Alessandro; Liu, Xinhua; Factor-Litvak, Pam; Graziano, Joseph

    2012-01-01

    Abstract Objective To reduce arsenic (As) exposure, we evaluated the effectiveness of training community members to perform water arsenic (WAs) testing and provide As education compared to sending representatives from outside communities to conduct these tasks. Methods We conducted a cluster based randomized controlled trial of 20 villages in Singair, Bangladesh. Fifty eligible respondents were randomly selected in each village. In 10 villages, a community member provided As education and WAs...

  13. Normalization based K means Clustering Algorithm

    OpenAIRE

    Virmani, Deepali; Taneja, Shweta; Malhotra, Geetika

    2015-01-01

    K-means is an effective clustering technique used to separate similar data into groups based on initial centroids of clusters. In this paper, Normalization based K-means clustering algorithm(N-K means) is proposed. Proposed N-K means clustering algorithm applies normalization prior to clustering on the available data as well as the proposed approach calculates initial centroids based on weights. Experimental results prove the betterment of proposed N-K means clustering algorithm over existing...

  14. Behavioral Health Risk Profiles of Undergraduate University Students in England, Wales, and Northern Ireland: A Cluster Analysis.

    Science.gov (United States)

    El Ansari, Walid; Ssewanyana, Derrick; Stock, Christiane

    2018-01-01

    Limited research has explored clustering of lifestyle behavioral risk factors (BRFs) among university students. This study aimed to explore clustering of BRFs, composition of clusters, and the association of the clusters with self-rated health and perceived academic performance. We assessed (BRFs), namely tobacco smoking, physical inactivity, alcohol consumption, illicit drug use, unhealthy nutrition, and inadequate sleep, using a self-administered general Student Health Survey among 3,706 undergraduates at seven UK universities. A two-step cluster analysis generated: Cluster 1 (the high physically active and health conscious) with very high health awareness/consciousness, good nutrition, and physical activity (PA), and relatively low alcohol, tobacco, and other drug (ATOD) use. Cluster 2 (the abstinent) had very low ATOD use, high health awareness, good nutrition, and medium high PA. Cluster 3 (the moderately health conscious) included the highest regard for healthy eating, second highest fruit/vegetable consumption, and moderately high ATOD use. Cluster 4 (the risk taking) showed the highest ATOD use, were the least health conscious, least fruit consuming, and attached the least importance on eating healthy. Compared to the healthy cluster (Cluster 1), students in other clusters had lower self-rated health, and particularly, students in the risk taking cluster (Cluster 4) reported lower academic performance. These associations were stronger for men than for women. Of the four clusters, Cluster 4 had the youngest students. Our results suggested that prevention among university students should address multiple BRFs simultaneously, with particular focus on the younger students.

  15. A universal harm-minimisation approach to preventing psychostimulant and cannabis use in adolescents: a cluster randomised controlled trial.

    Science.gov (United States)

    Vogl, Laura Elise; Newton, Nicola Clare; Champion, Katrina Elizabeth; Teesson, Maree

    2014-06-18

    Psychostimulants and cannabis are two of the three most commonly used illicit drugs by young Australians. As such, it is important to deliver prevention for these substances to prevent their misuse and to reduce associated harms. The present study aims to evaluate the feasibility and effectiveness of the universal computer-based Climate Schools: Psychostimulant and Cannabis Module. A cluster randomised controlled trial was conducted with 1734 Year 10 students (mean age = 15.44 years; SD = 0.41) from 21 secondary schools in Australia. Schools were randomised to receive either the six lesson computer-based Climate Schools program or their usual health classes, including drug education, over the year. The Climate Schools program was shown to increase knowledge of cannabis and psychostimulants and decrease pro-drug attitudes. In the short-term the program was effective in subduing the uptake and plateauing the frequency of ecstasy use, however there were no changes in meth/amphetamine use. In addition, females who received the program used cannabis significantly less frequently than students who received drug education as usual. Finally, the Climate Schools program was related to decreasing students' intentions to use meth/amphetamine and ecstasy in the future, however these effects did not last over time. These findings provide support for the use of a harm-minimisation approach and computer technology as an innovative platform for the delivery of prevention education for illicit drugs in schools. The current study indicated that teachers and students enjoyed the program and that it is feasible to extend the successful Climate Schools model to the prevention of other drugs, namely cannabis and psychostimulants. Australian and New Zealand Clinical Trials Registry ACTRN12613000492752.

  16. Progressive Exponential Clustering-Based Steganography

    Directory of Open Access Journals (Sweden)

    Li Yue

    2010-01-01

    Full Text Available Cluster indexing-based steganography is an important branch of data-hiding techniques. Such schemes normally achieve good balance between high embedding capacity and low embedding distortion. However, most cluster indexing-based steganographic schemes utilise less efficient clustering algorithms for embedding data, which causes redundancy and leaves room for increasing the embedding capacity further. In this paper, a new clustering algorithm, called progressive exponential clustering (PEC, is applied to increase the embedding capacity by avoiding redundancy. Meanwhile, a cluster expansion algorithm is also developed in order to further increase the capacity without sacrificing imperceptibility.

  17. Scalable Density-Based Subspace Clustering

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

    2011-01-01

    For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering...... method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real...... and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well....

  18. Nonuniform Sparse Data Clustering Cascade Algorithm Based on Dynamic Cumulative Entropy

    Directory of Open Access Journals (Sweden)

    Ning Li

    2016-01-01

    Full Text Available A small amount of prior knowledge and randomly chosen initial cluster centers have a direct impact on the accuracy of the performance of iterative clustering algorithm. In this paper we propose a new algorithm to compute initial cluster centers for k-means clustering and the best number of the clusters with little prior knowledge and optimize clustering result. It constructs the Euclidean distance control factor based on aggregation density sparse degree to select the initial cluster center of nonuniform sparse data and obtains initial data clusters by multidimensional diffusion density distribution. Multiobjective clustering approach based on dynamic cumulative entropy is adopted to optimize the initial data clusters and the best number of the clusters. The experimental results show that the newly proposed algorithm has good performance to obtain the initial cluster centers for the k-means algorithm and it effectively improves the clustering accuracy of nonuniform sparse data by about 5%.

  19. Evaluating a community-based early childhood education and development program in Indonesia: study protocol for a pragmatic cluster randomized controlled trial with supplementary matched control group

    NARCIS (Netherlands)

    Pradhan, M.; Brinkman, S.A.; Beatty, A.; Maika, A.; Satriawan, E.; de Ree, J.; Hasan, A.

    2013-01-01

    Background This paper presents the study protocol for a pragmatic cluster randomized controlled trial (RCT) with a supplementary matched control group. The aim of the trial is to evaluate a community-based early education and development program launched by the Government of Indonesia. The program

  20. Evaluating a community-based early childhood education and development program in Indonesia: study protocol for a pragmatic cluster randomized controlled trial with supplementary matched control group

    NARCIS (Netherlands)

    Pradhan, M.P.; Brinkman, S.A.; Beatty, A.; Maika, A.; Satriawan, E.; de Ree, J.; Hasan, A.

    2013-01-01

    Background: This paper presents the study protocol for a pragmatic cluster randomized controlled trial (RCT) with a supplementary matched control group. The aim of the trial is to evaluate a community-based early education and development program launched by the Government of Indonesia. The program

  1. MAS-based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

    DEFF Research Database (Denmark)

    Han, Yang; Zhang, Ke; Hong, Li

    2018-01-01

    The increasing integration of the distributed renewable energy sources highlights the requirement to design various control strategies for microgrids (MGs) and microgrid clusters (MGCs). The multi-agent system (MAS)-based distributed coordinated control strategies shows the benefits to balance...... the power and energy, stabilize voltage and frequency, achieve economic and coordinated operation among the MGs and MGCs. However, the complex and diverse combinations of distributed generations in multi-agent system increase the complexity of system control and operation. In order to design the optimized...... configuration and control strategy using MAS, the topology models and mathematic models such as the graph topology model, non-cooperative game model, the genetic algorithm and particle swarm optimization algorithm are summarized. The merits and drawbacks of these control methods are compared. Moreover, since...

  2. Behavioral Health Risk Profiles of Undergraduate University Students in England, Wales, and Northern Ireland: A Cluster Analysis

    Directory of Open Access Journals (Sweden)

    Walid El Ansari

    2018-05-01

    Full Text Available BackgroundLimited research has explored clustering of lifestyle behavioral risk factors (BRFs among university students. This study aimed to explore clustering of BRFs, composition of clusters, and the association of the clusters with self-rated health and perceived academic performance.MethodWe assessed (BRFs, namely tobacco smoking, physical inactivity, alcohol consumption, illicit drug use, unhealthy nutrition, and inadequate sleep, using a self-administered general Student Health Survey among 3,706 undergraduates at seven UK universities.ResultsA two-step cluster analysis generated: Cluster 1 (the high physically active and health conscious with very high health awareness/consciousness, good nutrition, and physical activity (PA, and relatively low alcohol, tobacco, and other drug (ATOD use. Cluster 2 (the abstinent had very low ATOD use, high health awareness, good nutrition, and medium high PA. Cluster 3 (the moderately health conscious included the highest regard for healthy eating, second highest fruit/vegetable consumption, and moderately high ATOD use. Cluster 4 (the risk taking showed the highest ATOD use, were the least health conscious, least fruit consuming, and attached the least importance on eating healthy. Compared to the healthy cluster (Cluster 1, students in other clusters had lower self-rated health, and particularly, students in the risk taking cluster (Cluster 4 reported lower academic performance. These associations were stronger for men than for women. Of the four clusters, Cluster 4 had the youngest students.ConclusionOur results suggested that prevention among university students should address multiple BRFs simultaneously, with particular focus on the younger students.

  3. CoCMA: Energy-Efficient Coverage Control in Cluster-Based Wireless Sensor Networks Using a Memetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yung-Chung Wang

    2009-06-01

    Full Text Available Deployment of wireless sensor networks (WSNs has drawn much attention in recent years. Given the limited energy for sensor nodes, it is critical to implement WSNs with energy efficiency designs. Sensing coverage in networks, on the other hand, may degrade gradually over time after WSNs are activated. For mission-critical applications, therefore, energy-efficient coverage control should be taken into consideration to support the quality of service (QoS of WSNs. Usually, coverage-controlling strategies present some challenging problems: (1 resolving the conflicts while determining which nodes should be turned off to conserve energy; (2 designing an optimal wake-up scheme that avoids awakening more nodes than necessary. In this paper, we implement an energy-efficient coverage control in cluster-based WSNs using a Memetic Algorithm (MA-based approach, entitled CoCMA, to resolve the challenging problems. The CoCMA contains two optimization strategies: a MA-based schedule for sensor nodes and a wake-up scheme, which are responsible to prolong the network lifetime while maintaining coverage preservation. The MA-based schedule is applied to a given WSN to avoid unnecessary energy consumption caused by the redundant nodes. During the network operation, the wake-up scheme awakens sleeping sensor nodes to recover coverage hole caused by dead nodes. The performance evaluation of the proposed CoCMA was conducted on a cluster-based WSN (CWSN under either a random or a uniform deployment of sensor nodes. Simulation results show that the performance yielded by the combination of MA and wake-up scheme is better than that in some existing approaches. Furthermore, CoCMA is able to activate fewer sensor nodes to monitor the required sensing area.

  4. Dynamic Characteristics Analysis and Stabilization of PV-Based Multiple Microgrid Clusters

    DEFF Research Database (Denmark)

    Zhao, Zhuoli; Yang, Ping; Wang, Yuewu

    2018-01-01

    -based multiple microgrid clusters. A detailed small-signal model for PV-based microgrid clusters considering local adaptive dynamic droop control mechanism of the voltage-source PV system is developed. The complete dynamic model is then used to access and compare the dynamic characteristics of the single...... microgrid and interconnected microgrids. In order to enhance system stability of the PV microgrid clusters, a tie-line flow and stabilization strategy is proposed to suppress the introduced interarea and local oscillations. Robustly selecting of the key control parameters is transformed to a multiobjective......As the penetration of PV generation increases, there is a growing operational demand on PV systems to participate in microgrid frequency regulation. It is expected that future distribution systems will consist of multiple microgrid clusters. However, interconnecting PV microgrids may lead to system...

  5. Clustering redshifts: a new window through the Universe

    International Nuclear Information System (INIS)

    Scottez, Vivien L.

    2015-01-01

    The main goals of this thesis are to validate, consolidate and develop a new method to measure the redshift distribution of a sample of galaxies. Where current methods - spectroscopic and photometric redshifts - rely on the study of the spectral energy distribution of extragalactic sources, the approach presented here is based on the clustering properties of galaxies. Indeed clustering of galaxies caused by gravity gives them a particular spatial - and angular - distribution. In this clustering redshift approach, we use this particular property between a galaxies sample of unknown redshifts and a galaxies sample of reference to reconstruct the redshift distribution of the unknown population. Thus, possible systematics in this approach should be independent of those existing in other methods. This new method responds to a real need from the scientific community in the context of large dark imaging experiments such as the Euclid mission of the European Space Agency (ESA). After introducing the general scientific context and having highlighted the crucial role of distance measurements in astronomy, I present the statistical tools generally used to study the large scale structure of the Universe as well as their modification to infer redshift distributions. After validating this approach on a particular type of extragalactic objects, I generalized its application to all types of galaxies. Then, I explored the precision and some systematic effects by conducting an ideal case study. Thus, I performed a real case study. I also pushed further this analysis and found that the reference sample used in the measurement does not need to have the same limiting magnitude than the population of unknown redshift. This property is a great advantage for the use of this approach in the context of large imaging dark energy experiments like the Euclid space mission. Finally, I summarize my main results and present some of my future projects. (author)

  6. Atomically precise cluster catalysis towards quantum controlled catalysts

    International Nuclear Information System (INIS)

    Watanabe, Yoshihide

    2014-01-01

    Catalysis of atomically precise clusters supported on a substrate is reviewed in relation to the type of reactions. The catalytic activity of supported clusters has generally been discussed in terms of electronic structure. Several lines of evidence have indicated that the electronic structure of clusters and the geometry of clusters on a support, including the accompanying cluster-support interaction, are strongly correlated with catalytic activity. The electronic states of small clusters would be easily affected by cluster–support interactions. Several studies have suggested that it is possible to tune the electronic structure through atomic control of the cluster size. It is promising to tune not only the number of cluster atoms, but also the hybridization between the electronic states of the adsorbed reactant molecules and clusters in order to realize a quantum-controlled catalyst. (review)

  7. The effectiveness of a clinically integrated e-learning course in evidence-based medicine: A cluster randomised controlled trial

    Directory of Open Access Journals (Sweden)

    Arvanitis Theodoros N

    2009-05-01

    Full Text Available Abstract Background To evaluate the educational effects of a clinically integrated e-learning course for teaching basic evidence-based medicine (EBM among postgraduates compared to a traditional lecture-based course of equivalent content. Methods We conducted a cluster randomised controlled trial in the Netherlands and the UK involving postgraduate trainees in six obstetrics and gynaecology departments. Outcomes (knowledge gain and change in attitude towards EBM were compared between the clinically integrated e-learning course (intervention and the traditional lecture based course (control. We measured change from pre- to post-intervention scores using a validated questionnaire assessing knowledge (primary outcome and attitudes (secondary outcome. Results There were six clusters involving teaching of 61 postgraduate trainees (28 in the intervention and 33 in the control group. The intervention group achieved slightly higher scores for knowledge gain compared to the control, but these results were not statistically significant (difference in knowledge gain: 3.5 points, 95% CI -2.7 to 9.8, p = 0.27. The attitudinal changes were similar for both groups. Conclusion A clinically integrated e-learning course was at least as effective as a traditional lecture based course and was well accepted. Being less costly than traditional teaching and allowing for more independent learning through materials that can be easily updated, there is a place for incorporating e-learning into postgraduate EBM curricula that offer on-the-job training for just-in-time learning. Trial registration Trial registration number: ACTRN12609000022268.

  8. Distributed controller clustering in software defined networks.

    Directory of Open Access Journals (Sweden)

    Ahmed Abdelaziz

    Full Text Available Software Defined Networking (SDN is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN SDN and Open Network Operating System (ONOS controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

  9. Distributed controller clustering in software defined networks.

    Science.gov (United States)

    Abdelaziz, Ahmed; Fong, Ang Tan; Gani, Abdullah; Garba, Usman; Khan, Suleman; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

    2017-01-01

    Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

  10. On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

    Science.gov (United States)

    Haneuse, Sebastien; Rivera-Rodriguez, Claudia

    2018-01-01

    In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

  11. Dividing traffic cluster into parts by signal control

    Science.gov (United States)

    Nagatani, Takashi

    2018-02-01

    When a cluster of vehicles with various speeds moves through the series of signals, the cluster breaks down by stopping at signals and results in smaller groups of vehicles. We present the nonlinear-map model of the motion of vehicles controlled by the signals. We study the breakup of a cluster of vehicles through the series of signals. The cluster of vehicles is divided into various groups by controlling the cycle time of signals. The vehicles within each group move with the same mean velocity. The breakup of the traffic cluster depends highly on the signal control. The dependence of dividing on both cycle time and vehicular speed is clarified. Also, we investigate the effect of the irregular interval between signals on dividing.

  12. The Children and Parents in Focus project: a population-based cluster-randomised controlled trial to prevent behavioural and emotional problems in children.

    Science.gov (United States)

    Salari, Raziye; Fabian, Helena; Prinz, Ron; Lucas, Steven; Feldman, Inna; Fairchild, Amanda; Sarkadi, Anna

    2013-10-16

    There is large body of knowledge to support the importance of early interventions to improve child health and development. Nonetheless, it is important to identify cost-effective blends of preventive interventions with adequate coverage and feasible delivery modes. The aim of the Children and Parents in Focus trial is to compare two levels of parenting programme intensity and rate of exposure, with a control condition to address impact and cost-effectiveness of a universally offered evidence-based parenting programme in the Swedish context. The trial has a cluster randomised controlled design comprising three arms: Universal arm (with access to participation in Triple P - Positive Parenting Program, level 2); Universal Plus arm (with access to participation in Triple P - Positive Parenting Program, level 2 as well as level 3, and level 4 group); and Services as Usual arm. The sampling frame is Uppsala municipality in Sweden. Child health centres consecutively recruit parents of children aged 3 to 5 years before their yearly check-ups (during the years 2013-2017). Outcomes will be measured annually. The primary outcome will be children's behavioural and emotional problems as rated by three informants: fathers, mothers and preschool teachers. The other outcomes will be parents' behaviour and parents' general health. Health economic evaluations will analyse cost-effectiveness of the interventions versus care as usual by comparing the costs and consequences in terms of impact on children's mental health, parent's mental health and health-related quality of life. This study addresses the need for comprehensive evaluation of the long-term effects, costs and benefits of early parenting interventions embedded within existing systems. In addition, the study will generate population-based data on the mental health and well-being of preschool aged children in Sweden. ISRCTN16513449.

  13. Effects of Mindfulness-Based Stress Reduction on the Mental Health of Clinical Clerkship Students: A Cluster-Randomized Controlled Trial

    NARCIS (Netherlands)

    Dijk, I. van; Lucassen, P.L.B.J.; Akkermans, R.P.; Engelen, B.G.M. van; Weel, C. van; Speckens, A.E.M.

    2017-01-01

    PURPOSE: To examine the effect of mindfulness-based stress reduction training (MBSR) on the mental health of medical students during clinical clerkships. METHOD: Between February 2011 and May 2014, the authors conducted a cluster-randomized controlled trial of clerkships as usual (CAU) and

  14. Membership determination of open clusters based on a spectral clustering method

    Science.gov (United States)

    Gao, Xin-Hua

    2018-06-01

    We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

  15. Consensus of satellite cluster flight using an energy-matching optimal control method

    Science.gov (United States)

    Luo, Jianjun; Zhou, Liang; Zhang, Bo

    2017-11-01

    This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

  16. Efficient clustering aggregation based on data fragments.

    Science.gov (United States)

    Wu, Ou; Hu, Weiming; Maybank, Stephen J; Zhu, Mingliang; Li, Bing

    2012-06-01

    Clustering aggregation, known as clustering ensembles, has emerged as a powerful technique for combining different clustering results to obtain a single better clustering. Existing clustering aggregation algorithms are applied directly to data points, in what is referred to as the point-based approach. The algorithms are inefficient if the number of data points is large. We define an efficient approach for clustering aggregation based on data fragments. In this fragment-based approach, a data fragment is any subset of the data that is not split by any of the clustering results. To establish the theoretical bases of the proposed approach, we prove that clustering aggregation can be performed directly on data fragments under two widely used goodness measures for clustering aggregation taken from the literature. Three new clustering aggregation algorithms are described. The experimental results obtained using several public data sets show that the new algorithms have lower computational complexity than three well-known existing point-based clustering aggregation algorithms (Agglomerative, Furthest, and LocalSearch); nevertheless, the new algorithms do not sacrifice the accuracy.

  17. A microgrid cluster structure and its autonomous coordination control strategy

    DEFF Research Database (Denmark)

    Zhou, Xiaoping; Zhou, Leming; Chen, Yandong

    2018-01-01

    This paper proposes a microgrid cluster structure and its autonomous coordination control strategy. Unlike existing microgrids that are purely AC or DC, the microgrid cluster studied here is an interconnected system with multiple AC and DC microgrids, which enables mutual power support among...... control method combining the normalized droop-based control and adaptive control is proposed for PEU, which can effectively realize mutual power support among microgrids and reduce the bus voltage or frequency deviation in microgrids. In addition, the adaptive control strategy of PEU can ensure...... that the bigger the normalized index of microgrid is, the larger the active power exchange coefficient is, which can make all of microgrids operate around the rated state as much as possible. Besides, EP is mainly used to balance the system power, and the hierarchical coordinated control method of EP is proposed...

  18. Simulation-based team training for multi-professional obstetric care teams to improve patient outcome : a multicentre, cluster randomised controlled trial

    NARCIS (Netherlands)

    Fransen, A F; van de Ven, J; Schuit, E; van Tetering, Aac; Mol, B W; Oei, S G

    OBJECTIVE: To investigate whether simulation-based obstetric team training in a simulation centre improves patient outcome. DESIGN: Multicentre, open, cluster randomised controlled trial. SETTING: Obstetric units in the Netherlands. POPULATION: Women with a singleton pregnancy beyond 24 weeks of

  19. The renewed HT-7 plasma control system based on real-time Linux cluster

    Energy Technology Data Exchange (ETDEWEB)

    Yuan, Q.P., E-mail: qpyuan@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei (China); Xiao, B.J.; Zhang, R.R. [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei (China); Walker, M.L.; Penaflor, B.G.; Piglowski, D.A.; Johnson, R.D. [General Atomics, DIII-D National Fusion Facility, San Diego, CA (United States)

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer The hardware and software structure of the new HT-7 plasma control system (HT-7 PCS) is reported. Black-Right-Pointing-Pointer All original systems were integrated in the new HT-7 PCS. And the implementation details of the control algorithms are given in the paper. Black-Right-Pointing-Pointer Different from EAST PCS, the AC operation mode is realized in HT-7 PCS. Black-Right-Pointing-Pointer The experiment results are discussed. Good control performance has been obtained. - Abstract: In order to improve the synchronization, flexibility and expansibility of the plasma control on HT-7, a new plasma control system (HT-7 PCS) was constructed. The HT-7 PCS was based on a real-time Linux cluster with a well-defined, robust and flexible software infrastructure which was adapted from DIII-D PCS. In this paper, the hardware structure and system customization details for HT-7 PCS are reported. The plasma position and current control, plasma density control and off-normal event detection, which were realized in separated systems originally, have been integrated and implemented in such HT-7 PCS. All these control algorithms have been successfully validated in the last several HT-7 experiment campaigns. Good control performance has been achieved and the experiment results are discussed in the paper.

  20. A Cluster- Based Secure Active Network Environment

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai

    2005-01-01

    We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

  1. Robust MST-Based Clustering Algorithm.

    Science.gov (United States)

    Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

    2018-06-01

    Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

  2. Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling.

    Science.gov (United States)

    Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

    2015-09-18

    This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.

  3. X-ray clusters from a high-resolution hydrodynamic PPM simulation of the cold dark matter universe

    Science.gov (United States)

    Bryan, Greg L.; Cen, Renyue; Norman, Michael L.; Ostriker, Jermemiah P.; Stone, James M.

    1994-01-01

    A new three-dimensional hydrodynamic code based on the piecewise parabolic method (PPM) is utilized to compute the distribution of hot gas in the standard Cosmic Background Explorer (COBE)-normalized cold dark matter (CDM) universe. Utilizing periodic boundary conditions, a box with size 85 h(exp-1) Mpc, having cell size 0.31 h(exp-1) Mpc, is followed in a simulation with 270(exp 3)=10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, Sigma(sub 8)=1.05, Omega(sub b)=0.06, we find the X-ray-emitting clusters, compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. The results, which are compared with those obtained in the preceding paper (Kang et al. 1994a), may be used in conjuction with ROSAT and other observational data sets. Overall, the results of the two computations are qualitatively very similar with regard to the trends of cluster properties, i.e., how the number density, radius, and temeprature depend on luminosity and redshift. The total luminosity from clusters is approximately a factor of 2 higher using the PPM code (as compared to the 'total variation diminishing' (TVD) code used in the previous paper) with the number of bright clusters higher by a similar factor. The primary conclusions of the prior paper, with regard to the power spectrum of the primeval density perturbations, are strengthened: the standard CDM model, normalized to the COBE microwave detection, predicts too many bright X-ray emitting clusters, by a factor probably in excess of 5. The comparison between observations and theoretical predictions for the evolution of cluster properties, luminosity functions, and size and temperature distributions should provide an important discriminator among competing scenarios for the development of structure in the universe.

  4. Bi-Level Decentralized Active Power Control for Large-Scale Wind Farm Cluster

    DEFF Research Database (Denmark)

    Huang, Shengli; Wu, Qiuwei; Guo, Yifei

    2018-01-01

    This paper presents a bi-level decentralized active power control (DAPC) for a large-scale wind farm cluster, consisting of several wind farms for better active power dispatch. In the upper level, a distributed active power control scheme based on the distributed consensus is designed to achieve...... fair active power sharing among multiple wind farms, which generates the power reference for each wind farm. A distributed estimator is used to estimate the total available power of all wind farms. In the lower level, a centralized control scheme based on the Model Predictive Control (MPC) is proposed...... to regulate active power outputs of all wind turbines (WTs) within a wind farm, which reduces the fatigue loads of WTs while tracking the power reference obtained from the upper level control. A wind farm cluster with 8 wind farms and totally 160 WTs, was used to test the control performance of the proposed...

  5. Use of machine learning methods to classify Universities based on the income structure

    Science.gov (United States)

    Terlyga, Alexandra; Balk, Igor

    2017-10-01

    In this paper we discuss use of machine learning methods such as self organizing maps, k-means and Ward’s clustering to perform classification of universities based on their income. This classification will allow us to quantitate classification of universities as teaching, research, entrepreneur, etc. which is important tool for government, corporations and general public alike in setting expectation and selecting universities to achieve different goals.

  6. A Data-origin Authentication Protocol Based on ONOS Cluster

    Directory of Open Access Journals (Sweden)

    Qin Hua

    2016-01-01

    Full Text Available This paper is aim to propose a data-origin authentication protocol based on ONOS cluster. ONOS is a SDN controller which can work under a distributed environment. However, the security of an ONOS cluster is seldom considered, and the communication in an ONOS cluster may suffer from lots of security threats. In this paper, we used a two-tier self-renewable hash chain for identity authentication and data-origin authentication. We analyse the security and overhead of our proposal and made a comparison with current security measure. It showed that with the help of our proposal, communication in an ONOS cluster could be protected from identity forging, replay attacks, data tampering, MITM attacks and repudiation, also the computational overhead would decrease apparently.

  7. The Ethical Behaviors of Educational Leaders in Ethiopian Public Universities: The Case of the Western Cluster Universities

    Science.gov (United States)

    Amsale, Frew; Bekele, Mitiku; Tafesse, Mebratu

    2016-01-01

    The purpose of this study was to assess the extent to which educational leaders in the western cluster public universities of Ethiopia are ethical. Ethical leadership variables such as fairness, equity, multicultural competence, modeling ethical behaviors and altruism are considered in describing the ethical behaviors of the leaders. Descriptive…

  8. CC_TRS: Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life

    Directory of Open Access Journals (Sweden)

    Musaab Riyadh

    2017-01-01

    Full Text Available The rapid spreading of positioning devices leads to the generation of massive spatiotemporal trajectories data. In some scenarios, spatiotemporal data are received in stream manner. Clustering of stream data is beneficial for different applications such as traffic management and weather forecasting. In this article, an algorithm for Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life is proposed. The algorithm consists of two phases. There is the online phase where temporal micro clusters are used to store summarized spatiotemporal information for each group of similar segments. The clustering task in online phase is based on temporal micro cluster lifetime instead of time window technique which divides stream data into time bins and clusters each bin separately. For offline phase, a density based clustering approach is used to generate macro clusters depending on temporal micro clusters. The evaluation of the proposed algorithm on real data sets shows the efficiency and the effectiveness of the proposed algorithm and proved it is efficient alternative to time window technique.

  9. Differential effect of exposure-based therapy and cognitive therapy on post-traumatic stress disorder symptom clusters: A randomized controlled trial.

    Science.gov (United States)

    Horesh, Danny; Qian, Meng; Freedman, Sara; Shalev, Arieh

    2017-06-01

    A question remains regarding differential effects of exposure-based versus non-exposure-based therapies on specific post-traumatic stress disorder (PTSD) symptom clusters. Traumatized emergency room patients were randomized to receive prolonged exposure (PE) or cognitive therapy (CT) without exposure. PE/CT had no differential effect on individual symptom clusters, and change in total PTSD score remained significant even after controlling for the reductions in all three symptom clusters. In addition, baseline levels of PTSD avoidance/intrusion/hyperarousal did not moderate the effects of PE and CT on total PTSD symptom scores. Taken together, these findings challenge the notion that PE and CT are specifically, and differentially, useful in treating one particular PTSD symptom cluster. Despite their different theoretical backgrounds and techniques, the notion that PE and CT (without exposure) target different PTSD symptoms was not confirmed in this study. Thus, both interventions may in fact be equally effective for treating intrusion, avoidance and hyperarousal symptoms. Baseline levels of avoidance, intrusion and hyperarousal may not be good a priori indicators for PTSD treatment selection. The effect of PE and CT on PTSD as a whole does not seem to depend on a reduction in any specific symptom cluster. These findings indicate that exposure and non-exposure interventions may lead to similar results in terms of reductions in specific PTSD symptoms. It is quite possible that individual PTSD clusters may respond to therapy in an inter-related fashion, with one cluster affecting the other. © 2016 The British Psychological Society.

  10. Self-similarity of temperature profiles in distant galaxy clusters: the quest for a universal law

    Science.gov (United States)

    Baldi, A.; Ettori, S.; Molendi, S.; Gastaldello, F.

    2012-09-01

    Context. We present the XMM-Newton temperature profiles of 12 bright (LX > 4 × 1044 erg s-1) clusters of galaxies at 0.4 high-redshift clusters, to investigate their properties, and to define a universal law to describe the temperature radial profiles in galaxy clusters as a function of both cosmic time and their state of relaxation. Methods: We performed a spatially resolved spectral analysis, using Cash statistics, to measure the temperature in the intracluster medium at different radii. Results: We extracted temperature profiles for the clusters in our sample, finding that all profiles are declining toward larger radii. The normalized temperature profiles (normalized by the mean temperature T500) are found to be generally self-similar. The sample was subdivided into five cool-core (CC) and seven non cool-core (NCC) clusters by introducing a pseudo-entropy ratio σ = (TIN/TOUT) × (EMIN/EMOUT)-1/3 and defining the objects with σ ratio σ is detected by fitting a function of r and σ, showing an indication that the outer part of the profiles becomes steeper for higher values of σ (i.e. transitioning toward the NCC clusters). No significant evidence of redshift evolution could be found within the redshift range sampled by our clusters (0.4 high-z sample with intermediate clusters at 0.1 0.4 has been attempted. We were able to define the closest possible relation to a universal law for the temperature profiles of galaxy clusters at 0.1 < z < 0.9, showing a dependence on both the relaxation state of the clusters and the redshift. Appendix A is only available in electronic form at http://www.aanda.org

  11. BioCluster: Tool for Identification and Clustering of Enterobacteriaceae Based on Biochemical Data

    Directory of Open Access Journals (Sweden)

    Ahmed Abdullah

    2015-06-01

    Full Text Available Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC and the Improved Hierarchical Clustering (IHC, a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1–47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/.

  12. Projection-based curve clustering

    International Nuclear Information System (INIS)

    Auder, Benjamin; Fischer, Aurelie

    2012-01-01

    This paper focuses on unsupervised curve classification in the context of nuclear industry. At the Commissariat a l'Energie Atomique (CEA), Cadarache (France), the thermal-hydraulic computer code CATHARE is used to study the reliability of reactor vessels. The code inputs are physical parameters and the outputs are time evolution curves of a few other physical quantities. As the CATHARE code is quite complex and CPU time-consuming, it has to be approximated by a regression model. This regression process involves a clustering step. In the present paper, the CATHARE output curves are clustered using a k-means scheme, with a projection onto a lower dimensional space. We study the properties of the empirically optimal cluster centres found by the clustering method based on projections, compared with the 'true' ones. The choice of the projection basis is discussed, and an algorithm is implemented to select the best projection basis among a library of orthonormal bases. The approach is illustrated on a simulated example and then applied to the industrial problem. (authors)

  13. Case-control geographic clustering for residential histories accounting for risk factors and covariates

    Science.gov (United States)

    2006-01-01

    Background Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Results Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. Conclusion These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case-control

  14. Case-control geographic clustering for residential histories accounting for risk factors and covariates

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2006-08-01

    Full Text Available Abstract Background Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Results Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters, Ingham (2 and Jackson (1 counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. Conclusion These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically

  15. DIMM-SC: a Dirichlet mixture model for clustering droplet-based single cell transcriptomic data.

    Science.gov (United States)

    Sun, Zhe; Wang, Ting; Deng, Ke; Wang, Xiao-Feng; Lafyatis, Robert; Ding, Ying; Hu, Ming; Chen, Wei

    2018-01-01

    Single cell transcriptome sequencing (scRNA-Seq) has become a revolutionary tool to study cellular and molecular processes at single cell resolution. Among existing technologies, the recently developed droplet-based platform enables efficient parallel processing of thousands of single cells with direct counting of transcript copies using Unique Molecular Identifier (UMI). Despite the technology advances, statistical methods and computational tools are still lacking for analyzing droplet-based scRNA-Seq data. Particularly, model-based approaches for clustering large-scale single cell transcriptomic data are still under-explored. We developed DIMM-SC, a Dirichlet Mixture Model for clustering droplet-based Single Cell transcriptomic data. This approach explicitly models UMI count data from scRNA-Seq experiments and characterizes variations across different cell clusters via a Dirichlet mixture prior. We performed comprehensive simulations to evaluate DIMM-SC and compared it with existing clustering methods such as K-means, CellTree and Seurat. In addition, we analyzed public scRNA-Seq datasets with known cluster labels and in-house scRNA-Seq datasets from a study of systemic sclerosis with prior biological knowledge to benchmark and validate DIMM-SC. Both simulation studies and real data applications demonstrated that overall, DIMM-SC achieves substantially improved clustering accuracy and much lower clustering variability compared to other existing clustering methods. More importantly, as a model-based approach, DIMM-SC is able to quantify the clustering uncertainty for each single cell, facilitating rigorous statistical inference and biological interpretations, which are typically unavailable from existing clustering methods. DIMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/∼wec47/singlecell.html. wei.chen@chp.edu or hum@ccf.org. Supplementary data are available at Bioinformatics online. © The Author

  16. Coordinated Voltage Control in Offshore HVDC Connected Cluster of Wind Power Plants

    DEFF Research Database (Denmark)

    Sakamuri, Jayachandra N.; Rather, Zakir Hussain; Rimez, Johan

    2016-01-01

    This paper presents a coordinated voltage control scheme (CVCS) for a cluster of offshore wind power plants (OWPPs) connected to a VSC HVDC system. The primary control point of the proposed voltage control scheme is the introduced Pilot bus, which is having the highest short circuit capacity...... in the offshore AC grid. The developed CVCS comprehends an optimization algorithm, aiming for minimum active power losses in the offshore grid, to generate voltage reference to the Pilot bus. During steady state operation, the Pilot bus voltage is controlled by dispatching reactive power references to each wind...... turbine (WT) in the WPP cluster based on their available reactive power margin and network sensitivity based participation factors, which are derived from the dV/dQ sensitivity of a WT bus w.r.t the Pilot bus. This method leads to minimization of the risk of undesired effects, particularly overvoltage...

  17. Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Gulnaz Ahmed

    2017-02-01

    Full Text Available The longer network lifetime of Wireless Sensor Networks (WSNs is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED clustering, Artificial Bee Colony (ABC, Zone Based Routing (ZBR, and Centralized Energy Efficient Clustering (CEEC using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput.

  18. Agent-based method for distributed clustering of textual information

    Science.gov (United States)

    Potok, Thomas E [Oak Ridge, TN; Reed, Joel W [Knoxville, TN; Elmore, Mark T [Oak Ridge, TN; Treadwell, Jim N [Louisville, TN

    2010-09-28

    A computer method and system for storing, retrieving and displaying information has a multiplexing agent (20) that calculates a new document vector (25) for a new document (21) to be added to the system and transmits the new document vector (25) to master cluster agents (22) and cluster agents (23) for evaluation. These agents (22, 23) perform the evaluation and return values upstream to the multiplexing agent (20) based on the similarity of the document to documents stored under their control. The multiplexing agent (20) then sends the document (21) and the document vector (25) to the master cluster agent (22), which then forwards it to a cluster agent (23) or creates a new cluster agent (23) to manage the document (21). The system also searches for stored documents according to a search query having at least one term and identifying the documents found in the search, and displays the documents in a clustering display (80) of similarity so as to indicate similarity of the documents to each other.

  19. Classical Music Clustering Based on Acoustic Features

    OpenAIRE

    Wang, Xindi; Haque, Syed Arefinul

    2017-01-01

    In this paper we cluster 330 classical music pieces collected from MusicNet database based on their musical note sequence. We use shingling and chord trajectory matrices to create signature for each music piece and performed spectral clustering to find the clusters. Based on different resolution, the output clusters distinctively indicate composition from different classical music era and different composing style of the musicians.

  20. Changing cluster composition in cluster randomised controlled trials: design and analysis considerations

    Science.gov (United States)

    2014-01-01

    Background There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. To illustrate this, we focus on the issue of cluster merging, considering the impact on the design, analysis and interpretation of trial outcomes. Methods We explored the effects of merging clusters on study power using standard methods of power calculation. We assessed the potential impacts on study findings of both homogeneous cluster merges (involving clusters randomised to the same arm of a trial) and heterogeneous merges (involving clusters randomised to different arms of a trial) by simulation. To determine the impact on bias and precision of treatment effect estimates, we applied standard methods of analysis to different populations under analysis. Results Cluster merging produced a systematic reduction in study power. This effect depended on the number of merges and was most pronounced when variability in cluster size was at its greatest. Simulations demonstrate that the impact on analysis was minimal when cluster merges were homogeneous, with impact on study power being balanced by a change in observed intracluster correlation coefficient (ICC). We found a decrease in study power when cluster merges were heterogeneous, and the estimate of treatment effect was attenuated. Conclusions Examples of cluster merges found in previously published reports of cluster randomised trials were typically homogeneous rather than heterogeneous. Simulations demonstrated that trial findings in such cases would be unbiased. However, simulations also showed that any heterogeneous cluster merges would introduce bias that would be hard to quantify, as well as having negative impacts on the precision of estimates obtained. Further methodological development is warranted to better determine how to analyse such trials appropriately. Interim recommendations

  1. Cluster Physics with Merging Galaxy Clusters

    Directory of Open Access Journals (Sweden)

    Sandor M. Molnar

    2016-02-01

    Full Text Available Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard LCDM model, where the total density is dominated by the cosmological constant ($Lambda$ and the matter density by cold dark matter (CDM, structure formation is hierarchical, and clusters grow mostly by merging.Mergers of two massive clusters are the most energetic events in the universe after the Big Bang,hence they provide a unique laboratory to study cluster physics.The two main mass components in clusters behave differently during collisions:the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulenceare developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thusour review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clustersis to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses.New high spatial and spectral resolution ground and space based telescopeswill come online in the near future. Motivated by these new opportunities,we briefly discuss methods which will be feasible in the near future in studying merging clusters.

  2. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  3. Weighted voting-based consensus clustering for chemical structure databases

    Science.gov (United States)

    Saeed, Faisal; Ahmed, Ali; Shamsir, Mohd Shahir; Salim, Naomie

    2014-06-01

    The cluster-based compound selection is used in the lead identification process of drug discovery and design. Many clustering methods have been used for chemical databases, but there is no clustering method that can obtain the best results under all circumstances. However, little attention has been focused on the use of combination methods for chemical structure clustering, which is known as consensus clustering. Recently, consensus clustering has been used in many areas including bioinformatics, machine learning and information theory. This process can improve the robustness, stability, consistency and novelty of clustering. For chemical databases, different consensus clustering methods have been used including the co-association matrix-based, graph-based, hypergraph-based and voting-based methods. In this paper, a weighted cumulative voting-based aggregation algorithm (W-CVAA) was developed. The MDL Drug Data Report (MDDR) benchmark chemical dataset was used in the experiments and represented by the AlogP and ECPF_4 descriptors. The results from the clustering methods were evaluated by the ability of the clustering to separate biologically active molecules in each cluster from inactive ones using different criteria, and the effectiveness of the consensus clustering was compared to that of Ward's method, which is the current standard clustering method in chemoinformatics. This study indicated that weighted voting-based consensus clustering can overcome the limitations of the existing voting-based methods and improve the effectiveness of combining multiple clusterings of chemical structures.

  4. Comparing clustering models in bank customers: Based on Fuzzy relational clustering approach

    Directory of Open Access Journals (Sweden)

    Ayad Hendalianpour

    2016-11-01

    Full Text Available Clustering is absolutely useful information to explore data structures and has been employed in many places. It organizes a set of objects into similar groups called clusters, and the objects within one cluster are both highly similar and dissimilar with the objects in other clusters. The K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms are the most popular clustering algorithms for their easy implementation and fast work, but in some cases we cannot use these algorithms. Regarding this, in this paper, a hybrid model for customer clustering is presented that is applicable in five banks of Fars Province, Shiraz, Iran. In this way, the fuzzy relation among customers is defined by using their features described in linguistic and quantitative variables. As follows, the customers of banks are grouped according to K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms and the proposed Fuzzy Relation Clustering (FRC algorithm. The aim of this paper is to show how to choose the best clustering algorithms based on density-based clustering and present a new clustering algorithm for both crisp and fuzzy variables. Finally, we apply the proposed approach to five datasets of customer's segmentation in banks. The result of the FCR shows the accuracy and high performance of FRC compared other clustering methods.

  5. WHERE ARE MOST OF THE GLOBULAR CLUSTERS IN TODAY’S UNIVERSE?

    Energy Technology Data Exchange (ETDEWEB)

    Harris, William E., E-mail: harris@physics.mcmaster.ca [Department of Physics and Astronomy, McMaster University, Hamilton, ON (Canada)

    2016-04-15

    The total number of globular clusters (GCs) in a galaxy rises continuously with the galaxy luminosity L, while the relative number of galaxies decreases with L following the Schechter function. The product of these two very nonlinear functions gives the relative number of GCs contained by all galaxies at a given L. It is shown that GCs, in this universal sense, are most commonly found in galaxies within a narrow range around L{sub ⋆}. In addition, blue (metal-poor) GCs outnumber the red (metal-richer) ones globally by 4 to 1 when all galaxies are added, pointing to the conclusion that the earliest stages of galaxy formation were especially favorable to forming massive, dense star clusters.

  6. A Clustering Based Approach for Observability and Controllability Analysis for Optimal Placement of PMU

    Science.gov (United States)

    Murthy, Ch; MIEEE; Mohanta, D. K.; SMIEE; Meher, Mahendra

    2017-08-01

    Continuous monitoring and control of the power system is essential for its healthy operation. This can be achieved by making the system observable as well as controllable. Many efforts have been made by several researchers to make the system observable by placing the Phasor Measurement Units (PMUs) at the optimal locations. But so far the idea of controllability with PMUs is not considered. This paper contributes how to check whether the system is controllable or not, if not then how make it controllable using a clustering approach. IEEE 14 bus system is considered to illustrate the concept of controllability.

  7. The CMS online cluster: IT for a large data acquisition and control cluster

    International Nuclear Information System (INIS)

    Bauer, G; Beccati, B; Cano, E; Ciganek, M; Cittolin, S; Deldicque, C; Erhan, S; Gigi, D; Glege, F; Gomez-Reino, R; Gutleber, J; Behrens, U; Hatton, D; Biery, K; Brett, A; Cheung, H; Branson, J; Coarasa, J A; Dusinberre, E; Rodrigues, F Fortes

    2010-01-01

    The CMS online cluster consists of more than 2000 computers running about 10000 application instances. These applications implement the control of the experiment, the event building, the high level trigger, the online database and the control of the buffering and transferring of data to the Central Data Recording at CERN. In this paper the IT solutions employed to fulfil the requirements of such a large cluster are revised. Details are given on the chosen network structure, configuration management system, monitoring infrastructure and on the implementation of the high availability for the services and infrastructure.

  8. Stigmergy based behavioural coordination for satellite clusters

    Science.gov (United States)

    Tripp, Howard; Palmer, Phil

    2010-04-01

    Multi-platform swarm/cluster missions are an attractive prospect for improved science return as they provide a natural capability for temporal, spatial and signal separation with further engineering and economic advantages. As spacecraft numbers increase and/or the round-trip communications delay from Earth lengthens, the traditional "remote-control" approach begins to break down. It is therefore essential to push control into space; to make spacecraft more autonomous. An autonomous group of spacecraft requires coordination, but standard terrestrial paradigms such as negotiation, require high levels of inter-spacecraft communication, which is nontrivial in space. This article therefore introduces the principals of stigmergy as a novel method for coordinating a cluster. Stigmergy is an agent-based, behavioural approach that allows for infrequent communication with decisions based on local information. Behaviours are selected dynamically using a genetic algorithm onboard. supervisors/ground stations occasionally adjust parameters and disseminate a "common environment" that is used for local decisions. After outlining the system, an analysis of some crucial parameters such as communications overhead and number of spacecraft is presented to demonstrate scalability. Further scenarios are considered to demonstrate the natural ability to deal with dynamic situations such as the failure of spacecraft, changing mission objectives and responding to sudden bursts of high priority tasks.

  9. Effectiveness of the universal prevention program 'Healthy School and Drugs': Study protocol of a randomized clustered trial

    Directory of Open Access Journals (Sweden)

    Malmberg Monique

    2010-09-01

    Full Text Available Abstract Background Substance use is highly prevalent among Dutch adolescents. The Healthy School and Drugs program is a nationally implemented school-based prevention program aimed at reducing early and excessive substance use among adolescents. Although the program's effectiveness was tested in a quasi-experimental design before, many program changes were made afterwards. The present study, therefore, aims to test the effects of this widely used, renewed universal prevention program. Methods/Design A randomized clustered trial will be conducted among 3,784 adolescents of 23 secondary schools in The Netherlands. The trial has three conditions; two intervention conditions (i.e., e-learning and integral and a control condition. The e-learning condition consists of three digital learning modules (i.e., about alcohol, tobacco, and marijuana that are sequentially offered over the course of three school years (i.e., grade 1, grade 2, and grade 3. The integral condition consists of parental participation in a parental meeting on substance use, regulation of substance use, and monitoring and counseling of students' substance use at school, over and above the three digital modules. The control condition is characterized as business as usual. Participating schools were randomly assigned to either an intervention or control condition. Participants filled out a digital questionnaire at baseline and will fill out the same questionnaire three more times at follow-up measurements (8, 20, and 32 months after baseline. Outcome variables included in the questionnaire are the percentage of binge drinking (more than five drinks per occasion, the average weekly number of drinks, and the percentage of adolescents who ever drunk a glass of alcohol and the percentage of adolescents who ever smoked a cigarette or a joint respectively for tobacco and marijuana. Discussion This study protocol describes the design of a randomized clustered trial that evaluates the

  10. Structure based alignment and clustering of proteins (STRALCP)

    Science.gov (United States)

    Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.

    2013-06-18

    Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

  11. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  12. Event-based cluster synchronization of coupled genetic regulatory networks

    Science.gov (United States)

    Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

    2017-09-01

    In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

  13. Conveyor Performance based on Motor DC 12 Volt Eg-530ad-2f using K-Means Clustering

    Science.gov (United States)

    Arifin, Zaenal; Artini, Sri DP; Much Ibnu Subroto, Imam

    2017-04-01

    To produce goods in industry, a controlled tool to improve production is required. Separation process has become a part of production process. Separation process is carried out based on certain criteria to get optimum result. By knowing the characteristics performance of a controlled tools in separation process the optimum results is also possible to be obtained. Clustering analysis is popular method for clustering data into smaller segments. Clustering analysis is useful to divide a group of object into a k-group in which the member value of the group is homogeny or similar. Similarity in the group is set based on certain criteria. The work in this paper based on K-Means method to conduct clustering of loading in the performance of a conveyor driven by a dc motor 12 volt eg-530-2f. This technique gives a complete clustering data for a prototype of conveyor driven by dc motor to separate goods in term of height. The parameters involved are voltage, current, time of travelling. These parameters give two clusters namely optimal cluster with center of cluster 10.50 volt, 0.3 Ampere, 10.58 second, and unoptimal cluster with center of cluster 10.88 volt, 0.28 Ampere and 40.43 second.

  14. Hybrid clustering based fuzzy structure for vibration control - Part 1: A novel algorithm for building neuro-fuzzy system

    Science.gov (United States)

    Nguyen, Sy Dzung; Nguyen, Quoc Hung; Choi, Seung-Bok

    2015-01-01

    This paper presents a new algorithm for building an adaptive neuro-fuzzy inference system (ANFIS) from a training data set called B-ANFIS. In order to increase accuracy of the model, the following issues are executed. Firstly, a data merging rule is proposed to build and perform a data-clustering strategy. Subsequently, a combination of clustering processes in the input data space and in the joint input-output data space is presented. Crucial reason of this task is to overcome problems related to initialization and contradictory fuzzy rules, which usually happen when building ANFIS. The clustering process in the input data space is accomplished based on a proposed merging-possibilistic clustering (MPC) algorithm. The effectiveness of this process is evaluated to resume a clustering process in the joint input-output data space. The optimal parameters obtained after completion of the clustering process are used to build ANFIS. Simulations based on a numerical data, 'Daily Data of Stock A', and measured data sets of a smart damper are performed to analyze and estimate accuracy. In addition, convergence and robustness of the proposed algorithm are investigated based on both theoretical and testing approaches.

  15. HUBBLE PINPOINTS WHITE DWARFS IN GLOBULAR CLUSTER

    Science.gov (United States)

    2002-01-01

    Peering deep inside a cluster of several hundred thousand stars, NASA's Hubble Space Telescope uncovered the oldest burned-out stars in our Milky Way Galaxy. Located in the globular cluster M4, these small, dying stars - called white dwarfs - are giving astronomers a fresh reading on one of the biggest questions in astronomy: How old is the universe? The ancient white dwarfs in M4 are about 12 to 13 billion years old. After accounting for the time it took the cluster to form after the big bang, astronomers found that the age of the white dwarfs agrees with previous estimates for the universe's age. In the top panel, a ground-based observatory snapped a panoramic view of the entire cluster, which contains several hundred thousand stars within a volume of 10 to 30 light-years across. The Kitt Peak National Observatory's 0.9-meter telescope took this picture in March 1995. The box at left indicates the region observed by the Hubble telescope. The Hubble telescope studied a small region of the cluster. A section of that region is seen in the picture at bottom left. A sampling of an even smaller region is shown at bottom right. This region is only about one light-year across. In this smaller region, Hubble pinpointed a number of faint white dwarfs. The blue circles pinpoint the dwarfs. It took nearly eight days of exposure time over a 67-day period to find these extremely faint stars. Globular clusters are among the oldest clusters of stars in the universe. The faintest and coolest white dwarfs within globular clusters can yield a globular cluster's age. Earlier Hubble observations showed that the first stars formed less than 1 billion years after the universe's birth in the big bang. So, finding the oldest stars puts astronomers within arm's reach of the universe's age. M4 is 7,000 light-years away in the constellation Scorpius. Hubble's Wide Field and Planetary Camera 2 made the observations from January through April 2001. These optical observations were combined to

  16. Universal block diagram based modeling and simulation schemes for fractional-order control systems.

    Science.gov (United States)

    Bai, Lu; Xue, Dingyü

    2017-05-08

    Universal block diagram based schemes are proposed for modeling and simulating the fractional-order control systems in this paper. A fractional operator block in Simulink is designed to evaluate the fractional-order derivative and integral. Based on the block, the fractional-order control systems with zero initial conditions can be modeled conveniently. For modeling the system with nonzero initial conditions, the auxiliary signal is constructed in the compensation scheme. Since the compensation scheme is very complicated, therefore the integrator chain scheme is further proposed to simplify the modeling procedures. The accuracy and effectiveness of the schemes are assessed in the examples, the computation results testify the block diagram scheme is efficient for all Caputo fractional-order ordinary differential equations (FODEs) of any complexity, including the implicit Caputo FODEs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  17. A Structural Equation Model of Knowledge Management Based On Organizational Climate in Universities

    OpenAIRE

    F. Nazem; M. Mozaiini; A. Seifi

    2014-01-01

    The purpose of the present study was to provide a structural model of knowledge management in universities based on organizational climate. The population of the research included all employees of Islamic Azad University (IAU). The sample consisted of 1590 employees selected using stratified and cluster random sampling method. The research instruments were two questionnaires which were administered in 78 IAU branches and education centers: Sallis and Jones’s (2002) Knowledge Management Questi...

  18. Cluster-based global firms' use of local capabilities

    DEFF Research Database (Denmark)

    Andersen, Poul Houman; Bøllingtoft, Anne

    2011-01-01

    Purpose – Despite growing interest in clusters role for the global competitiveness of firms, there has been little research into how globalization affects cluster-based firms’ (CBFs) use of local knowledge resources and the combination of local and global knowledge used. Using the cluster......’s knowledge base as a mediating variable, the purpose of this paper is to examine how globalization affected the studied firms’ use of local cluster-based knowledge, integration of local and global knowledge, and networking capabilities. Design/methodology/approach – Qualitative case studies of nine firms...... in three clusters strongly affected by increasing global division of labour. Findings – The paper suggests that globalization has affected how firms use local resources and combine local and global knowledge. Unexpectedly, clustered firms with explicit procedures and established global fora for exchanging...

  19. Percolation with multiple giant clusters

    International Nuclear Information System (INIS)

    Ben-Naim, E; Krapivsky, P L

    2005-01-01

    We study mean-field percolation with freezing. Specifically, we consider cluster formation via two competing processes: irreversible aggregation and freezing. We find that when the freezing rate exceeds a certain threshold, the percolation transition is suppressed. Below this threshold, the system undergoes a series of percolation transitions with multiple giant clusters ('gels') formed. Giant clusters are not self-averaging as their total number and their sizes fluctuate from realization to realization. The size distribution F k , of frozen clusters of size k, has a universal tail, F k ∼ k -3 . We propose freezing as a practical mechanism for controlling the gel size. (letter to the editor)

  20. Sparsity enabled cluster reduced-order models for control

    Science.gov (United States)

    Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

    2018-01-01

    Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

  1. blockcluster: An R Package for Model-Based Co-Clustering

    Directory of Open Access Journals (Sweden)

    Parmeet Singh Bhatia

    2017-02-01

    Full Text Available Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or block clustering, is an important technique in two way data analysis. A new standard and efficient approach has been recently proposed based on the latent block model (Govaert and Nadif 2003 which takes into account the block clustering problem on both the individual and variable sets. This article presents our R package blockcluster for co-clustering of binary, contingency and continuous data based on these very models. In this document, we will give a brief review of the model-based block clustering methods, and we will show how the R package blockcluster can be used for co-clustering.

  2. Dynamics of the baryonic component in hierarchical clustering universes

    Science.gov (United States)

    Navarro, Julio

    1993-01-01

    I present self-consistent 3-D simulations of the formation of virialized systems containing both gas and dark matter in a flat universe. A fully Lagrangian code based on the Smoothed Particle Hydrodynamics technique and a tree data structure has been used to evolve regions of comoving radius 2-3 Mpc. Tidal effects are included by coarse-sampling the density of the outer regions up to a radius approx. 20 Mpc. Initial conditions are set at high redshift (z greater than 7) using a standard Cold Dark Matter perturbation spectrum and a baryon mass fraction of 10 percent (omega(sub b) = 0.1). Simulations in which the gas evolves either adiabatically or radiates energy at a rate determined locally by its cooling function were performed. This allows us to investigate with the same set of simulations the importance of radiative losses in the formation of galaxies and the equilibrium structure of virialized systems where cooling is very inefficient. In the absence of radiative losses, the simulations can be rescaled to the density and radius typical of galaxy clusters. A summary of the main results is presented.

  3. Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

    International Nuclear Information System (INIS)

    Podestà, Alessandro; Borghi, Francesca; Indrieri, Marco; Bovio, Simone; Piazzoni, Claudio; Milani, Paolo

    2015-01-01

    Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO 2 ) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility

  4. Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

    Energy Technology Data Exchange (ETDEWEB)

    Podestà, Alessandro, E-mail: alessandro.podesta@mi.infn.it, E-mail: pmilani@mi.infn.it; Borghi, Francesca; Indrieri, Marco; Bovio, Simone; Piazzoni, Claudio; Milani, Paolo, E-mail: alessandro.podesta@mi.infn.it, E-mail: pmilani@mi.infn.it [Centro Interdisciplinare Materiali e Interfacce Nanostrutturati (C.I.Ma.I.Na.), Dipartimento di Fisica, Università degli Studi di Milano, via Celoria 16, 20133 Milano (Italy)

    2015-12-21

    Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO{sub 2}) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility.

  5. Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

    Science.gov (United States)

    Podestà, Alessandro; Borghi, Francesca; Indrieri, Marco; Bovio, Simone; Piazzoni, Claudio; Milani, Paolo

    2015-12-01

    Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO2) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility.

  6. Probing the z > 6 universe with the first Hubble frontier fields cluster A2744

    International Nuclear Information System (INIS)

    Atek, Hakim; Kneib, Jean-Paul; Richard, Johan; Clement, Benjamin; Egami, Eiichi; Ebeling, Harald; Jauzac, Mathilde; Jullo, Eric; Limousin, Marceau; Laporte, Nicolas; Natarajan, Priyamvada

    2014-01-01

    The Hubble Frontier Fields program combines the capabilities of the Hubble Space Telescope (HST) with the gravitational lensing of massive galaxy clusters to probe the distant universe to an unprecedented depth. Here, we present the results of the first combined HST and Spitzer observations of the cluster A-2744. We combine the full near-infrared data with ancillary optical images to search for gravitationally lensed high-redshift (z ≳ 6) galaxies. We report the detection of 15 I 814 dropout candidates at z ∼ 6-7 and one Y 105 dropout at z ∼ 8 in a total survey area of 1.43 arcmin 2 in the source plane. The predictions of our lens model also allow us to identify five multiply imaged systems lying at redshifts between z ∼ 6 and z ∼ 8. Thanks to constraints from the mass distribution in the cluster, we were able to estimate the effective survey volume corrected for completeness and magnification effects. This was in turn used to estimate the rest-frame ultraviolet luminosity function (LF) at z ∼ 6-8. Our LF results are generally in agreement with the most recent blank field estimates, confirming the feasibility of surveys through lensing clusters. Although based on a shallower observations than what will be achieved in the final data set including the full Advanced Camera for Survey observations, the LF presented here goes down to M UV ∼–18.5, corresponding to 0.2L * at z ∼ 7 with one identified object at M UV ∼–15 thanks to the highly magnified survey areas. This early study forecasts the power of using massive galaxy clusters as cosmic telescopes and its complementarity to blank fields.

  7. Probing the z > 6 universe with the first Hubble frontier fields cluster A2744

    Energy Technology Data Exchange (ETDEWEB)

    Atek, Hakim; Kneib, Jean-Paul [Laboratoire d' Astrophysique, Ecole Polytechnique Fédérale de Lausanne, Observatoire de Sauverny, CH-1290 Versoix (Switzerland); Richard, Johan [CRAL, Observatoire de Lyon, Université Lyon 1, 9 Avenue Ch. André, 69561 Saint Genis Laval Cedex (France); Clement, Benjamin; Egami, Eiichi [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ, 85721 (United States); Ebeling, Harald [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, Hawaii 96822 (United States); Jauzac, Mathilde [Astrophysics and Cosmology Research Unit, School of Mathematical Sciences, University of KwaZulu-Natal, Durban, 4041 South Africa (South Africa); Jullo, Eric; Limousin, Marceau [Aix Marseille Université, CNRS, LAM (Laboratoire d' Astrophysique de Marseille) UMR 7326, 13388, Marseille (France); Laporte, Nicolas [Instituto de Astrofisica de Canarias (IAC), E-38200 La Laguna, Tenerife (Spain); Natarajan, Priyamvada [Department of Astronomy, Yale University, 260 Whitney Avenue, New Haven, CT 06511 (United States)

    2014-05-01

    The Hubble Frontier Fields program combines the capabilities of the Hubble Space Telescope (HST) with the gravitational lensing of massive galaxy clusters to probe the distant universe to an unprecedented depth. Here, we present the results of the first combined HST and Spitzer observations of the cluster A-2744. We combine the full near-infrared data with ancillary optical images to search for gravitationally lensed high-redshift (z ≳ 6) galaxies. We report the detection of 15 I {sub 814} dropout candidates at z ∼ 6-7 and one Y {sub 105} dropout at z ∼ 8 in a total survey area of 1.43 arcmin{sup 2} in the source plane. The predictions of our lens model also allow us to identify five multiply imaged systems lying at redshifts between z ∼ 6 and z ∼ 8. Thanks to constraints from the mass distribution in the cluster, we were able to estimate the effective survey volume corrected for completeness and magnification effects. This was in turn used to estimate the rest-frame ultraviolet luminosity function (LF) at z ∼ 6-8. Our LF results are generally in agreement with the most recent blank field estimates, confirming the feasibility of surveys through lensing clusters. Although based on a shallower observations than what will be achieved in the final data set including the full Advanced Camera for Survey observations, the LF presented here goes down to M {sub UV} ∼–18.5, corresponding to 0.2L {sup *} at z ∼ 7 with one identified object at M {sub UV} ∼–15 thanks to the highly magnified survey areas. This early study forecasts the power of using massive galaxy clusters as cosmic telescopes and its complementarity to blank fields.

  8. A cluster randomized control field trial of the ABRACADABRA web-based literacy intervention: Replication and extension of basic findings.

    Directory of Open Access Journals (Sweden)

    Noella Angele Piquette

    2014-12-01

    Full Text Available The present paper reports a cluster randomized control trial evaluation of teaching using ABRACADABRA (ABRA, an evidence-based and web-based literacy intervention (http://abralite.concordia.ca with 107 kindergarten and 96 grade 1 children in 24 classes (12 intervention 12 control classes from all 12 elementary schools in one school district in Canada. Children in the intervention condition received 10-12 hours of whole class instruction using ABRA between pre- and post-test. Hierarchical linear modeling of post-test results showed significant gains in letter-sound knowledge for intervention classrooms over control classrooms. In addition, medium effect sizes were evident for three of five outcome measures favoring the intervention: letter-sound knowledge (d = +.66, phonological blending (d = +.52, and word reading (d = +.52, over effect sizes for regular teaching. It is concluded that regular teaching with ABRA technology adds significantly to literacy in the early elementary years.

  9. Hierarchical Control for Multiple DC Microgrids Clusters

    DEFF Research Database (Denmark)

    Shafiee, Qobad; Dragicevic, Tomislav; Vasquez, Juan Carlos

    2014-01-01

    This paper presents a distributed hierarchical control framework to ensure reliable operation of dc Microgrid (MG) clusters. In this hierarchy, primary control is used to regulate the common bus voltage inside each MG locally. An adaptive droop method is proposed for this level which determines...

  10. A first packet processing subdomain cluster model based on SDN

    Science.gov (United States)

    Chen, Mingyong; Wu, Weimin

    2017-08-01

    For the current controller cluster packet processing performance bottlenecks and controller downtime problems. An SDN controller is proposed to allocate the priority of each device in the SDN (Software Defined Network) network, and the domain contains several network devices and Controller, the controller is responsible for managing the network equipment within the domain, the switch performs data delivery based on the load of the controller, processing network equipment data. The experimental results show that the model can effectively solve the risk of single point failure of the controller, and can solve the performance bottleneck of the first packet processing.

  11. A primary-school-based study to reduce prevalence of childhood obesity in Catalunya (Spain)--EDAL-Educació en alimentació: study protocol for a randomised controlled trial.

    Science.gov (United States)

    Giralt, Montse; Albaladejo, Rosa; Tarro, Lucia; Moriña, David; Arija, Victoria; Solà, Rosa

    2011-02-27

    The EdAL (Educació en Alimentació) study is a long-term, nutrition educational, primary-school-based program designed to prevent obesity by promoting a healthy lifestyle that includes dietary recommendations and physical activity.The aims are: 1) to evaluate the effects of a 3-year school-based life-style improvement program on the prevalence of obesity in an area of north-west Mediterranean 2) To design a health-promotion program to be implemented by health-promoter agents (university students) in primary schools. 1) The intervention study is a randomised, controlled, school-based program performed by university-student health-promoter agents. Initial pupil enrolment was in 2006 and continued for 3 years. We considered two clusters (designated as cluster A and cluster B) as the units for randomisation. The first cluster involved 24 schools from Reus and the second involved 14 schools from surrounding towns Cambrils, Salou and Vilaseca combined in order to obtain comparable groups. There are very good communications between schools in each town, and to avoid cross influence of the programs resulting from inter-school dialogue, the towns themselves were the unit for randomisation. Data collected included name, gender, date and place of birth at the start of the program and, subsequently, weight, height, body mass index (BMI) and waist circumference every year for 3 years. Questionnaires on eating and physical activity habits are filled-in by the parents at the start and end of the study and, providing that informed consent is given, the data are analysed on the intention-to-treat basis.The interventions are based on 8 nutritional and physical activity objectives. They are implemented by university students as part of the university curriculum in training health-promoter agents. These 8 objectives are developed in 4 educational activities/year for 3 years (a total of 12 activities; 1 h/activity) performed by the health-promoter agents in primary schools. Control

  12. Coma cluster of galaxies

    Science.gov (United States)

    1999-01-01

    Atlas Image mosaic, covering 34' x 34' on the sky, of the Coma cluster, aka Abell 1656. This is a particularly rich cluster of individual galaxies (over 1000 members), most prominently the two giant ellipticals, NGC 4874 (right) and NGC 4889 (left). The remaining members are mostly smaller ellipticals, but spiral galaxies are also evident in the 2MASS image. The cluster is seen toward the constellation Coma Berenices, but is actually at a distance of about 100 Mpc (330 million light years, or a redshift of 0.023) from us. At this distance, the cluster is in what is known as the 'Hubble flow,' or the overall expansion of the Universe. As such, astronomers can measure the Hubble Constant, or the universal expansion rate, based on the distance to this cluster. Large, rich clusters, such as Coma, allow astronomers to measure the 'missing mass,' i.e., the matter in the cluster that we cannot see, since it gravitationally influences the motions of the member galaxies within the cluster. The near-infrared maps the overall luminous mass content of the member galaxies, since the light at these wavelengths is dominated by the more numerous older stellar populations. Galaxies, as seen by 2MASS, look fairly smooth and homogeneous, as can be seen from the Hubble 'tuning fork' diagram of near-infrared galaxy morphology. Image mosaic by S. Van Dyk (IPAC).

  13. Universality and clustering in 1 + 1 dimensional superstring-bit models

    International Nuclear Information System (INIS)

    Bergman, O.; Thorn, C.B.

    1996-01-01

    We construct a 1+1 dimensional superstring-bit model for D=3 Type IIB superstring. This low dimension model escapes the problem encountered in higher dimension models: (1) It possesses full Galilean supersymmetry; (2) For noninteracting Polymers of bits, the exactly soluble linear superpotential describing bit interactions is in a large universality class of superpotentials which includes ones bounded at spatial infinity; (3) The latter are used to construct a superstring-bit model with the clustering properties needed to define an S-matrix for closed polymers of superstring-bits

  14. The effectiveness of educational interventions to enhance the adoption of fee-based arsenic testing in Bangladesh: a cluster randomized controlled trial.

    Science.gov (United States)

    George, Christine Marie; Inauen, Jennifer; Rahman, Sheikh Masudur; Zheng, Yan

    2013-07-01

    Arsenic (As) testing could help 22 million people, using drinking water sources that exceed the Bangladesh As standard, to identify safe sources. A cluster randomized controlled trial was conducted to evaluate the effectiveness of household education and local media in the increasing demand for fee-based As testing. Randomly selected households (N = 452) were divided into three interventions implemented by community workers: 1) fee-based As testing with household education (HE); 2) fee-based As testing with household education and a local media campaign (HELM); and 3) fee-based As testing alone (Control). The fee for the As test was US$ 0.28, higher than the cost of the test (US$ 0.16). Of households with untested wells, 93% in both intervention groups HE and HELM purchased an As test, whereas only 53% in the control group. In conclusion, fee-based As testing with household education is effective in the increasing demand for As testing in rural Bangladesh.

  15. Effective Social Relationship Measurement and Cluster Based Routing in Mobile Opportunistic Networks.

    Science.gov (United States)

    Zeng, Feng; Zhao, Nan; Li, Wenjia

    2017-05-12

    In mobile opportunistic networks, the social relationship among nodes has an important impact on data transmission efficiency. Motivated by the strong share ability of "circles of friends" in communication networks such as Facebook, Twitter, Wechat and so on, we take a real-life example to show that social relationships among nodes consist of explicit and implicit parts. The explicit part comes from direct contact among nodes, and the implicit part can be measured through the "circles of friends". We present the definitions of explicit and implicit social relationships between two nodes, adaptive weights of explicit and implicit parts are given according to the contact feature of nodes, and the distributed mechanism is designed to construct the "circles of friends" of nodes, which is used for the calculation of the implicit part of social relationship between nodes. Based on effective measurement of social relationships, we propose a social-based clustering and routing scheme, in which each node selects the nodes with close social relationships to form a local cluster, and the self-control method is used to keep all cluster members always having close relationships with each other. A cluster-based message forwarding mechanism is designed for opportunistic routing, in which each node only forwards the copy of the message to nodes with the destination node as a member of the local cluster. Simulation results show that the proposed social-based clustering and routing outperforms the other classic routing algorithms.

  16. Protocol for a Cluster Randomised Controlled Trial to Compare the “Taste & See” Programme—A Church-Based Programme to Develop a Healthy Relationship with Food—With a Wait-List Control

    Directory of Open Access Journals (Sweden)

    Deborah Lycett

    2018-03-01

    Full Text Available (1 Background: Obesity is strongly associated with poor mental-health. Spiritual and religious wellbeing is associated with improved mental well-being and reduced emotional eating. “Taste & See”, a church based programme to help develop a healthy relationship with food has been successfully tested for feasibility in the UK but an adequately powered randomised controlled trial is needed to test efficacy. This paper reports on the protocol for such a trial; (2 Method: A cluster, randomised controlled trial where Christian churches (any denomination are the unit of randomisation. 150 overweight adults will be recruited from approximately 15 churches (clusters in the UK, each church (cluster will recruit approximately 10 participants. Churches will be randomised 2:1 to either begin the “Taste & See” programme immediately or in 10 weeks’ time. Data on eating habits, mental and spiritual health will be collected online before and after the intervention and control period and follow-up will continue until 2 years; (3 Implication of Results: Should the programme prove effective it will provide strong clinical evidence of the role of churches in improving the health and well-being of those struggling with food and weight issues.

  17. NetCDF based data archiving system applied to ITER Fast Plant System Control prototype

    International Nuclear Information System (INIS)

    Castro, R.; Vega, J.; Ruiz, M.; De Arcas, G.; Barrera, E.; López, J.M.; Sanz, D.; Gonçalves, B.; Santos, B.; Utzel, N.; Makijarvi, P.

    2012-01-01

    Highlights: ► Implementation of a data archiving solution for a Fast Plant System Controller (FPSC) for ITER CODAC. ► Data archiving solution based on scientific NetCDF-4 file format and Lustre storage clustering. ► EPICS control based solution. ► Tests results and detailed analysis of using NetCDF-4 and clustering technologies on fast acquisition data archiving. - Abstract: EURATOM/CIEMAT and Technical University of Madrid (UPM) have been involved in the development of a FPSC (Fast Plant System Control) prototype for ITER, based on PXIe (PCI eXtensions for Instrumentation). One of the main focuses of this project has been data acquisition and all the related issues, including scientific data archiving. Additionally, a new data archiving solution has been developed to demonstrate the obtainable performances and possible bottlenecks of scientific data archiving in Fast Plant System Control. The presented system implements a fault tolerant architecture over a GEthernet network where FPSC data are reliably archived on remote, while remaining accessible to be redistributed, within the duration of a pulse. The storing service is supported by a clustering solution to guaranty scalability, so that FPSC management and configuration may be simplified, and a unique view of all archived data provided. All the involved components have been integrated under EPICS (Experimental Physics and Industrial Control System), implementing in each case the necessary extensions, state machines and configuration process variables. The prototyped solution is based on the NetCDF-4 (Network Common Data Format) file format in order to incorporate important features, such as scientific data models support, huge size files management, platform independent codification, or single-writer/multiple-readers concurrency. In this contribution, a complete description of the above mentioned solution is presented, together with the most relevant results of the tests performed, while focusing in the

  18. Cluster Control of Offshore Wind Power Plants Connected to a Common HVDC Station

    DEFF Research Database (Denmark)

    Göksu, Ömer; Sakamuri, Jayachandra N.; Rapp, C. Andrea

    2016-01-01

    of offshore AC grid voltage control and onshore ancillary services provision, i.e. POD by the active power modulation of the cluster. The two cases are simulated using DIgSILENT PowerFactory, where the IEC 61400-27-1 wind turbine and WPP control models and a generic offshore layout with cluster of three WPPs......In this paper a coordinated control for cluster of offshore WPPs connected to the same HVDC connection is being implemented and analyzed. The study is targeting two cases as; coordination of reactive power flow between HVDC converter and the WPP cluster while providing offshore AC grid voltage...... control, and coordinated closed loop control between the HVDC and the WPPs while the cluster is providing Power Oscillation Damping ( POD) via active power modulation. It is shown that the coordinated cluster control helps to improve the steady-state and dynamic response of the offshore AC grid in case...

  19. Universal Prevention for Anxiety and Depressive Symptoms in Children: A Meta-analysis of Randomized and Cluster-Randomized Trials.

    Science.gov (United States)

    Ahlen, Johan; Lenhard, Fabian; Ghaderi, Ata

    2015-12-01

    Although under-diagnosed, anxiety and depression are among the most prevalent psychiatric disorders in children and adolescents, leading to severe impairment, increased risk of future psychiatric problems, and a high economic burden to society. Universal prevention may be a potent way to address these widespread problems. There are several benefits to universal relative to targeted interventions because there is limited knowledge as to how to screen for anxiety and depression in the general population. Earlier meta-analyses of the prevention of depression and anxiety symptoms among children suffer from methodological inadequacies such as combining universal, selective, and indicated interventions in the same analyses, and comparing cluster-randomized trials with randomized trials without any correction for clustering effects. The present meta-analysis attempted to determine the effectiveness of universal interventions to prevent anxiety and depressive symptoms after correcting for clustering effects. A systematic search of randomized studies in PsychINFO, Cochrane Library, and Google Scholar resulted in 30 eligible studies meeting inclusion criteria, namely peer-reviewed, randomized or cluster-randomized trials of universal interventions for anxiety and depressive symptoms in school-aged children. Sixty-three percent of the studies reported outcome data regarding anxiety and 87 % reported outcome data regarding depression. Seventy percent of the studies used randomization at the cluster level. There were small but significant effects regarding anxiety (.13) and depressive (.11) symptoms as measured at immediate posttest. At follow-up, which ranged from 3 to 48 months, effects were significantly larger than zero regarding depressive (.07) but not anxiety (.11) symptoms. There was no significant moderation effect of the following pre-selected variables: the primary aim of the intervention (anxiety or depression), deliverer of the intervention, gender distribution

  20. Effectiveness of a multifaceted implementation strategy on physicians? referral behavior to an evidence-based psychosocial intervention in dementia: a cluster randomized controlled trial

    OpenAIRE

    D?pp, Carola ME; Graff, Maud JL; Teerenstra, Steven; Nijhuis-van der Sanden, Maria WG; Olde Rikkert, Marcel GM; Vernooij-Dassen, Myrra JFJ

    2013-01-01

    BACKGROUND: To evaluate the effectiveness of a multifaceted implementation strategy on physicians' referral rate to and knowledge on the community occupational therapy in dementia program (COTiD program). METHODS: A cluster randomized controlled trial with 28 experimental and 17 control clusters was conducted. Cluster included a minimum of one physician, one manager, and two occupational therapists. In the control group physicians and managers received no interventions and occupational therap...

  1. A cluster-randomised controlled trial integrating a community-based water, sanitation and hygiene programme, with mass distribution of albendazole to reduce intestinal parasites in Timor-Leste: the WASH for WORMS research protocol.

    Science.gov (United States)

    Nery, Susana Vaz; McCarthy, James S; Traub, Rebecca; Andrews, Ross M; Black, Jim; Gray, Darren; Weking, Edmund; Atkinson, Jo-An; Campbell, Suzy; Francis, Naomi; Vallely, Andrew; Williams, Gail; Clements, Archie

    2015-12-30

    There is limited evidence demonstrating the benefits of community-based water, sanitation and hygiene (WASH) programmes on infections with soil-transmitted helminths (STH) and intestinal protozoa. Our study aims to contribute to that evidence base by investigating the effectiveness of combining two complementary approaches for control of STH: periodic mass administration of albendazole, and delivery of a community-based WASH programme. WASH for WORMS is a cluster-randomised controlled trial to test the hypothesis that a community-based WASH intervention integrated with periodic mass distribution of albendazole will be more effective in reducing infections with STH and protozoa than mass deworming alone. All 18 participating rural communities in Timor-Leste receive mass chemotherapy every 6 months. Half the communities also receive the community-based WASH programme. Primary outcomes are the cumulative incidence of infection with STH. Secondary outcomes include the prevalence of protozoa; intensity of infection with STH; as well as morbidity indicators (anaemia, stunting and wasting). Each of the trial outcomes will be compared between control and intervention communities. End points will be measured 2 years after the first albendazole distribution; and midpoints are measured at 6 months intervals (12 months for haemoglobin and anthropometric indexes). Mixed-methods research will also be conducted in order to identify barriers and enablers associated with the acceptability and uptake of the WASH programme. Ethics approval was obtained from the human ethics committees at the University of Queensland, Australian National University, Timorese Ministry of Health, and University of Melbourne. The results of the trial will be published in peer-reviewed journals presented at national and international conferences, and disseminated to relevant stakeholders in health and WASH programmes. This study is funded by a Partnership for Better Health--Project grant from the National

  2. A cluster-randomised controlled trial integrating a community-based water, sanitation and hygiene programme, with mass distribution of albendazole to reduce intestinal parasites in Timor-Leste: the WASH for WORMS research protocol

    Science.gov (United States)

    Nery, Susana Vaz; McCarthy, James S; Traub, Rebecca; Andrews, Ross M; Black, Jim; Gray, Darren; Weking, Edmund; Atkinson, Jo-An; Campbell, Suzy; Francis, Naomi; Vallely, Andrew; Williams, Gail; Clements, Archie

    2015-01-01

    Introduction There is limited evidence demonstrating the benefits of community-based water, sanitation and hygiene (WASH) programmes on infections with soil-transmitted helminths (STH) and intestinal protozoa. Our study aims to contribute to that evidence base by investigating the effectiveness of combining two complementary approaches for control of STH: periodic mass administration of albendazole, and delivery of a community-based WASH programme. Methods and analysis WASH for WORMS is a cluster-randomised controlled trial to test the hypothesis that a community-based WASH intervention integrated with periodic mass distribution of albendazole will be more effective in reducing infections with STH and protozoa than mass deworming alone. All 18 participating rural communities in Timor-Leste receive mass chemotherapy every 6 months. Half the communities also receive the community-based WASH programme. Primary outcomes are the cumulative incidence of infection with STH. Secondary outcomes include the prevalence of protozoa; intensity of infection with STH; as well as morbidity indicators (anaemia, stunting and wasting). Each of the trial outcomes will be compared between control and intervention communities. End points will be measured 2 years after the first albendazole distribution; and midpoints are measured at 6 months intervals (12 months for haemoglobin and anthropometric indexes). Mixed-methods research will also be conducted in order to identify barriers and enablers associated with the acceptability and uptake of the WASH programme. Ethics and dissemination Ethics approval was obtained from the human ethics committees at the University of Queensland, Australian National University, Timorese Ministry of Health, and University of Melbourne. The results of the trial will be published in peer-reviewed journals presented at national and international conferences, and disseminated to relevant stakeholders in health and WASH programmes. This study is funded

  3. Scaffold Architecture Controls Insulinoma Clustering, Viability, and Insulin Production

    Science.gov (United States)

    Blackstone, Britani N.; Palmer, Andre F.; Rilo, Horacio R.

    2014-01-01

    Recently, in vitro diagnostic tools have shifted focus toward personalized medicine by incorporating patient cells into traditional test beds. These cell-based platforms commonly utilize two-dimensional substrates that lack the ability to support three-dimensional cell structures seen in vivo. As monolayer cell cultures have previously been shown to function differently than cells in vivo, the results of such in vitro tests may not accurately reflect cell response in vivo. It is therefore of interest to determine the relationships between substrate architecture, cell structure, and cell function in 3D cell-based platforms. To investigate the effect of substrate architecture on insulinoma organization and function, insulinomas were seeded onto 2D gelatin substrates and 3D fibrous gelatin scaffolds with three distinct fiber diameters and fiber densities. Cell viability and clustering was assessed at culture days 3, 5, and 7 with baseline insulin secretion and glucose-stimulated insulin production measured at day 7. Small, closely spaced gelatin fibers promoted the formation of large, rounded insulinoma clusters, whereas monolayer organization and large fibers prevented cell clustering and reduced glucose-stimulated insulin production. Taken together, these data show that scaffold properties can be used to control the organization and function of insulin-producing cells and may be useful as a 3D test bed for diabetes drug development. PMID:24410263

  4. Cluster-based DBMS Management Tool with High-Availability

    Directory of Open Access Journals (Sweden)

    Jae-Woo Chang

    2005-02-01

    Full Text Available A management tool which is needed for monitoring and managing cluster-based DBMSs has been little studied. So, we design and implement a cluster-based DBMS management tool with high-availability that monitors the status of nodes in a cluster system as well as the status of DBMS instances in a node. The tool enables users to recognize a single virtual system image and provides them with the status of all the nodes and resources in the system by using a graphic user interface (GUI. By using a load balancer, our management tool can increase the performance of a cluster-based DBMS as well as can overcome the limitation of the existing parallel DBMSs.

  5. The impact of collaborations between universities and private organizations on cluster development and competitiveness in Romania

    Science.gov (United States)

    Stoicovici, D.; Bănică, M.; Ungureanu, M.; Stoicovici, M.

    2017-05-01

    While the European Union has put a lot of emphasis on cluster development due to their inherent advantages such as lower transaction costs, technological transfer and regional development, little is known about how clusters emerge and what can facilitate their competitiveness. This paper aims to study the impact of public-private cooperation between universities and organizations on cluster development and competitiveness. A literature review is employed to develop the model while 4 qualitative case studies provide the initial test of its validity. The analysis suggests that cooperating with research institutions impacts cluster development first through education of industrial staff, but also by developing innovation processes through the facilitation of the appearance of innovative ideas and also of knowledge sharing among organizations. The research has several implications both for organizations and for government officials. First of all, R&D and top management should actively seek to cooperate with research institutions both for training of their staff but also in seeking new ideas and as a way of collaborating with other organizations within the field without fear of losing competitive advantage. Second, government officials should try to create more incentives both for organizations (through for example tax returns) and for universities (extra funding or salary incentives) that can increase collaboration between these actors. This paper is the first one to asses empirically how cooperation with research institutions affect cluster competitiveness and development, especially within the developing region of Eastern Europe, Romania.

  6. Probing the large-scale structure of the universe: an analysis of 55 bright southern clusters of galaxies

    International Nuclear Information System (INIS)

    Olowin, R.P.

    1985-01-01

    This dissertation presents the description of 55 bright, close (Z less than or equal to 0.1) clusters of galaxies as a homogeneous sample taken from a new effort to catalog galaxy clusters in the Southern Hemisphere. The positions of some 21,000 galaxies in clusters were cataloged along with visual magnitudes, morphological types, position angles of extended objects and pertinent remarks. For all of the clusters, various cluster parameters were determined and form the basis of comparative studies for these fundamental aggregates of matter in the universe. The aims of this study are to produce a homogeneous sample of galaxy clusters measured to a uniform limiting magnitude of m/sub v/ = 19.0 by means of a calibrated stepscale: catalogued with accurate positions relative to nearby astrometric standard stars; morphologically classified and population typed; and statistically analyzed in a uniform fashion to deduce certain cluster parameters. The cluster parameters of interest include an estimate of cluster distance, cluster center and cluster richness; galaxy distributions as a function of morphological type, magnitude distribution and core radius as determined by an isothermal gas sphere model

  7. Generation of clusters in complex dynamical networks via pinning control

    International Nuclear Information System (INIS)

    Li Kezan; Fu Xinchu; Small, Michael

    2008-01-01

    Many real-world networks show community structure, i.e., groups (or clusters) of nodes that have a high density of links within them but with a lower density of links between them. In this paper, by applying feedback injections to a fraction of network nodes, various clusters are synchronized independently according to the community structure generated by the group partition of the network (cluster synchronization). This control is achieved by pinning (i.e. applying linear feedback control) to a subset of the network nodes. Those pinned nodes are selected not randomly but according to the topological structure of communities of a given network. Specifically, for a given group partition of a network, those nodes with direct connections between groups must be pinned in order to achieve cluster synchronization. Both the local stability and global stability of cluster synchronization are investigated. Taking the tree-shaped network and the most modular network as two particular examples, we illustrate in detail how the pinning strategy influences the generation of clusters. The simulations verify the efficiency of the pinning schemes used in this paper

  8. A Flocking Based algorithm for Document Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Gao, Jinzhu [ORNL; Potok, Thomas E [ORNL

    2006-01-01

    Social animals or insects in nature often exhibit a form of emergent collective behavior known as flocking. In this paper, we present a novel Flocking based approach for document clustering analysis. Our Flocking clustering algorithm uses stochastic and heuristic principles discovered from observing bird flocks or fish schools. Unlike other partition clustering algorithm such as K-means, the Flocking based algorithm does not require initial partitional seeds. The algorithm generates a clustering of a given set of data through the embedding of the high-dimensional data items on a two-dimensional grid for easy clustering result retrieval and visualization. Inspired by the self-organized behavior of bird flocks, we represent each document object with a flock boid. The simple local rules followed by each flock boid result in the entire document flock generating complex global behaviors, which eventually result in a clustering of the documents. We evaluate the efficiency of our algorithm with both a synthetic dataset and a real document collection that includes 100 news articles collected from the Internet. Our results show that the Flocking clustering algorithm achieves better performance compared to the K- means and the Ant clustering algorithm for real document clustering.

  9. Profiling physical activity motivation based on self-determination theory: a cluster analysis approach.

    Science.gov (United States)

    Friederichs, Stijn Ah; Bolman, Catherine; Oenema, Anke; Lechner, Lilian

    2015-01-01

    In order to promote physical activity uptake and maintenance in individuals who do not comply with physical activity guidelines, it is important to increase our understanding of physical activity motivation among this group. The present study aimed to examine motivational profiles in a large sample of adults who do not comply with physical activity guidelines. The sample for this study consisted of 2473 individuals (31.4% male; age 44.6 ± 12.9). In order to generate motivational profiles based on motivational regulation, a cluster analysis was conducted. One-way analyses of variance were then used to compare the clusters in terms of demographics, physical activity level, motivation to be active and subjective experience while being active. Three motivational clusters were derived based on motivational regulation scores: a low motivation cluster, a controlled motivation cluster and an autonomous motivation cluster. These clusters differed significantly from each other with respect to physical activity behavior, motivation to be active and subjective experience while being active. Overall, the autonomous motivation cluster displayed more favorable characteristics compared to the other two clusters. The results of this study provide additional support for the importance of autonomous motivation in the context of physical activity behavior. The three derived clusters may be relevant in the context of physical activity interventions as individuals within the different clusters might benefit most from different intervention approaches. In addition, this study shows that cluster analysis is a useful method for differentiating between motivational profiles in large groups of individuals who do not comply with physical activity guidelines.

  10. A Clustering-Oriented Closeness Measure Based on Neighborhood Chain and Its Application in the Clustering Ensemble Framework Based on the Fusion of Different Closeness Measures

    Directory of Open Access Journals (Sweden)

    Shaoyi Liang

    2017-09-01

    Full Text Available Closeness measures are crucial to clustering methods. In most traditional clustering methods, the closeness between data points or clusters is measured by the geometric distance alone. These metrics quantify the closeness only based on the concerned data points’ positions in the feature space, and they might cause problems when dealing with clustering tasks having arbitrary clusters shapes and different clusters densities. In this paper, we first propose a novel Closeness Measure between data points based on the Neighborhood Chain (CMNC. Instead of using geometric distances alone, CMNC measures the closeness between data points by quantifying the difficulty for one data point to reach another through a chain of neighbors. Furthermore, based on CMNC, we also propose a clustering ensemble framework that combines CMNC and geometric-distance-based closeness measures together in order to utilize both of their advantages. In this framework, the “bad data points” that are hard to cluster correctly are identified; then different closeness measures are applied to different types of data points to get the unified clustering results. With the fusion of different closeness measures, the framework can get not only better clustering results in complicated clustering tasks, but also higher efficiency.

  11. Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

    Science.gov (United States)

    Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

    2017-09-01

    Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

  12. Beyond Apprenticeship: Knowledge Brokers and Sustainability of Apprentice-Based Clusters

    Directory of Open Access Journals (Sweden)

    Huasheng Zhu

    2016-12-01

    Full Text Available Knowledge learning and diffusion have long been discussed in the literature on the dynamics of industrial clusters, but recent literature provides little evidence for how different actors serve as knowledge brokers in the upgrading process of apprentice-based clusters, and does not dynamically consider how to preserve the sustainability of these clusters. This paper uses empirical evidence from an antique furniture manufacturing cluster in Xianyou, Fujian Province, in southeastern China, to examine the growth trajectory of the knowledge learning system of an antique furniture manufacturing cluster. It appears that the apprentice-based learning system is crucial during early stages of the cluster evolution, but later becomes complemented and relatively substituted by the role of both local governments and focal outsiders. This finding addresses the context of economic transformation and provides empirical insights into knowledge acquisition in apprentice-based clusters to question the rationality based on European and North American cases, and to provide a broader perspective for policy makers to trigger and sustain the development of apprentice-based clusters.

  13. Cluster-based analysis of multi-model climate ensembles

    Science.gov (United States)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

  14. Managing distance and covariate information with point-based clustering

    Directory of Open Access Journals (Sweden)

    Peter A. Whigham

    2016-09-01

    Full Text Available Abstract Background Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley’s K and applied to the problem of clustering with deliberate self-harm (DSH, is presented. Methods Point-based Monte-Carlo simulation of Ripley’s K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years’ emergency hospital presentations (n = 136 in a New Zealand town (population ~50,000. Study area was defined by residential (housing land parcels representing a finite set of possible point addresses. Results Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Conclusions Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley’s K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for

  15. Effective Social Relationship Measurement and Cluster Based Routing in Mobile Opportunistic Networks †

    Science.gov (United States)

    Zeng, Feng; Zhao, Nan; Li, Wenjia

    2017-01-01

    In mobile opportunistic networks, the social relationship among nodes has an important impact on data transmission efficiency. Motivated by the strong share ability of “circles of friends” in communication networks such as Facebook, Twitter, Wechat and so on, we take a real-life example to show that social relationships among nodes consist of explicit and implicit parts. The explicit part comes from direct contact among nodes, and the implicit part can be measured through the “circles of friends”. We present the definitions of explicit and implicit social relationships between two nodes, adaptive weights of explicit and implicit parts are given according to the contact feature of nodes, and the distributed mechanism is designed to construct the “circles of friends” of nodes, which is used for the calculation of the implicit part of social relationship between nodes. Based on effective measurement of social relationships, we propose a social-based clustering and routing scheme, in which each node selects the nodes with close social relationships to form a local cluster, and the self-control method is used to keep all cluster members always having close relationships with each other. A cluster-based message forwarding mechanism is designed for opportunistic routing, in which each node only forwards the copy of the message to nodes with the destination node as a member of the local cluster. Simulation results show that the proposed social-based clustering and routing outperforms the other classic routing algorithms. PMID:28498309

  16. Gravitational clustering in the expanding universe - Controlled high-resolution studies in two dimensions

    Science.gov (United States)

    Beacom, John Francis; Dominik, Kurt G.; Melott, Adrian L.; Perkins, Sam P.; Shandarin, Sergei F.

    1991-01-01

    Results are presented from a series of gravitational clustering simulations in two dimensions. These simulations are a significant departure from previous work, since in two dimensions one can have large dynamic range in both length scale and mass using present computer technology. Controlled experiments were conducted by varying the slope of power-law initial density fluctuation spectra and varying cutoffs at large k, while holding constant the phases of individual Fourier components and the scale of nonlinearity. Filaments are found in many different simulations, even with pure power-law initial conditions. By direct comparison, filaments, called 'second-generation pancakes' are shown to arise as a consequence of mild nonlinearity on scales much larger than the correlation length and are not relics of an initial lattice or due to sparse sampling of the Fourier components. Bumps of low amplitude in the two-point correlation are found to be generic but usually only statistical fluctuations. Power spectra are much easier to relate to initial conditions, and seem to follow a simple triangular shape (on log-log plot) in the nonlinear regime. The rms density fluctuation with Gaussian smoothing is the most stable indicator of nonlinearity.

  17. Simulation-Based Training for Residents in the Management of Acute Agitation: A Cluster Randomized Controlled Trial.

    Science.gov (United States)

    Vestal, Heather S; Sowden, Gillian; Nejad, Shamim; Stoklosa, Joseph; Valcourt, Stephanie C; Keary, Christopher; Caminis, Argyro; Huffman, Jeff

    2017-02-01

    Simulations are used extensively in medicine to train clinicians to manage high-risk situations. However, to our knowledge, no studies have determined whether this is an effective means of teaching residents to manage acutely agitated patients. This study aimed to determine whether simulation-based training in the management of acute agitation improves resident knowledge and performance, as compared to didactic-based instruction. Following a standard lecture on the management of agitated patients, first-year psychiatry residents were randomized (in clusters of three to four residents) to either the intervention (n = 15) or control arm (n = 11). Residents in the intervention arm then received simulation-based training on the management of acute agitation using a scenario with an agitated standardized patient. Those in the control arm received simulation-based training on a clinical topic unrelated to the management of agitation using a scenario with a non-agitated standardized patient who had suffered a fall. Baseline confidence and knowledge were assessed using pre-intervention self-assessment questionnaires and open-ended clinical case vignettes. Efficacy of the intervention as a teaching tool was assessed with post-intervention open-ended clinical case vignettes and videotaped simulation-based assessment, using a different scenario of an agitated standardized patient. Residents who received the agitation simulation-based training showed significantly greater improvement in knowledge (intervention = 3.0 vs. control = 0.3, p = 0.007, Cohen's d = 1.2) and performance (intervention = 39.6 vs control = 32.5, p = 0.001, Cohen's d = 1.6). Change in self-perceived confidence did not differ significantly between groups. In this study, simulation-based training appeared to be more effective at teaching knowledge and skills necessary for the management of acutely agitated patients, as compared to didactic-based instruction alone

  18. Energy Aware Cluster Based Routing Scheme For Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Roy Sohini

    2015-09-01

    Full Text Available Wireless Sensor Network (WSN has emerged as an important supplement to the modern wireless communication systems due to its wide range of applications. The recent researches are facing the various challenges of the sensor network more gracefully. However, energy efficiency has still remained a matter of concern for the researches. Meeting the countless security needs, timely data delivery and taking a quick action, efficient route selection and multi-path routing etc. can only be achieved at the cost of energy. Hierarchical routing is more useful in this regard. The proposed algorithm Energy Aware Cluster Based Routing Scheme (EACBRS aims at conserving energy with the help of hierarchical routing by calculating the optimum number of cluster heads for the network, selecting energy-efficient route to the sink and by offering congestion control. Simulation results prove that EACBRS performs better than existing hierarchical routing algorithms like Distributed Energy-Efficient Clustering (DEEC algorithm for heterogeneous wireless sensor networks and Energy Efficient Heterogeneous Clustered scheme for Wireless Sensor Network (EEHC.

  19. Dynamic clustering scheme based on the coordination of management and control in multi-layer and multi-region intelligent optical network

    Science.gov (United States)

    Niu, Xiaoliang; Yuan, Fen; Huang, Shanguo; Guo, Bingli; Gu, Wanyi

    2011-12-01

    A Dynamic clustering scheme based on coordination of management and control is proposed to reduce network congestion rate and improve the blocking performance of hierarchical routing in Multi-layer and Multi-region intelligent optical network. Its implement relies on mobile agent (MA) technology, which has the advantages of efficiency, flexibility, functional and scalability. The paper's major contribution is to adjust dynamically domain when the performance of working network isn't in ideal status. And the incorporation of centralized NMS and distributed MA control technology migrate computing process to control plane node which releases the burden of NMS and improves process efficiently. Experiments are conducted on Multi-layer and multi-region Simulation Platform for Optical Network (MSPON) to assess the performance of the scheme.

  20. Cluster-based Data Gathering in Long-Strip Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    FANG, W.

    2012-02-01

    Full Text Available This paper investigates a special class of wireless sensor networks that are different from traditional ones in that the sensor nodes in this class of networks are deployed along narrowly elongated geographical areas and form a long-strip topology. According to hardware capabilities of current sensor nodes, a cluster-based protocol for reliable and efficient data gathering in long-strip wireless sensor networks (LSWSN is proposed. A well-distributed cluster-based architecture is first formed in the whole network through contention-based cluster head election. Cluster heads are responsible for coordination among the nodes within their clusters and aggregation of their sensory data, as well as transmission the data to the sink node on behalf of their own clusters. The intra-cluster coordination is based on the traditional TDMA schedule, in which the inter-cluster interference caused by the border nodes is solved by the multi-channel communication technique. The cluster reporting is based on the CSMA contention, in which a connected overlay network is formed by relay nodes to forward the data from the cluster heads through multi-hops to the sink node. The relay nodes are non-uniformly deployed to resolve the energy-hole problem which is extremely serious in the LSWSN. Extensive simulation results illuminate the distinguished performance of the proposed protocol.

  1. Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

    Science.gov (United States)

    Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

    2018-02-01

    A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method

  2. CORECLUSTER: A Degeneracy Based Graph Clustering Framework

    OpenAIRE

    Giatsidis , Christos; Malliaros , Fragkiskos; Thilikos , Dimitrios M. ,; Vazirgiannis , Michalis

    2014-01-01

    International audience; Graph clustering or community detection constitutes an important task forinvestigating the internal structure of graphs, with a plethora of applications in several domains. Traditional tools for graph clustering, such asspectral methods, typically suffer from high time and space complexity. In thisarticle, we present \\textsc{CoreCluster}, an efficient graph clusteringframework based on the concept of graph degeneracy, that can be used along withany known graph clusteri...

  3. Integrated analysis of CFD data with K-means clustering algorithm and extreme learning machine for localized HVAC control

    International Nuclear Information System (INIS)

    Zhou, Hongming; Soh, Yeng Chai; Wu, Xiaoying

    2015-01-01

    Maintaining a desired comfort level while minimizing the total energy consumed is an interesting optimization problem in Heating, ventilating and air conditioning (HVAC) system control. This paper proposes a localized control strategy that uses Computational Fluid Dynamics (CFD) simulation results and K-means clustering algorithm to optimally partition an air-conditioned room into different zones. The temperature and air velocity results from CFD simulation are combined in two ways: 1) based on the relationship indicated in predicted mean vote (PMV) formula; 2) based on the relationship extracted from ASHRAE RP-884 database using extreme learning machine (ELM). Localized control can then be effected in which each of the zones can be treated individually and an optimal control strategy can be developed based on the partitioning result. - Highlights: • The paper provides a visual guideline for thermal comfort analysis. • CFD, K-means, PMV and ELM are used to analyze thermal conditions within a room. • Localized control strategy could be developed based on our clustering results

  4. A primary-school-based study to reduce prevalence of childhood obesity in Catalunya (Spain - EDAL-Educació en alimentació: study protocol for a randomised controlled trial

    Directory of Open Access Journals (Sweden)

    Moriña David

    2011-02-01

    Full Text Available Abstract Background The EdAL (Educació en Alimentació study is a long-term, nutrition educational, primary-school-based program designed to prevent obesity by promoting a healthy lifestyle that includes dietary recommendations and physical activity. The aims are: 1 to evaluate the effects of a 3-year school-based life-style improvement program on the prevalence of obesity in an area of north-west Mediterranean 2 To design a health-promotion program to be implemented by health-promoter agents (university students in primary schools. Methods/Design 1 The intervention study is a randomised, controlled, school-based program performed by university-student health-promoter agents. Initial pupil enrolment was in 2006 and continued for 3 years. We considered two clusters (designated as cluster A and cluster B as the units for randomisation. The first cluster involved 24 schools from Reus and the second involved 14 schools from surrounding towns Cambrils, Salou and Vilaseca combined in order to obtain comparable groups. There are very good communications between schools in each town, and to avoid cross influence of the programs resulting from inter-school dialogue, the towns themselves were the unit for randomisation. Data collected included name, gender, date and place of birth at the start of the program and, subsequently, weight, height, body mass index (BMI and waist circumference every year for 3 years. Questionnaires on eating and physical activity habits are filled-in by the parents at the start and end of the study and, providing that informed consent is given, the data are analysed on the intention-to-treat basis. The interventions are based on 8 nutritional and physical activity objectives. They are implemented by university students as part of the university curriculum in training health-promoter agents. These 8 objectives are developed in 4 educational activities/year for 3 years (a total of 12 activities; 1 h/activity performed by the

  5. Effects of Mindfulness-Based Stress Reduction on the Mental Health of Clinical Clerkship Students: A Cluster-Randomized Controlled Trial.

    Science.gov (United States)

    van Dijk, Inge; Lucassen, Peter L B J; Akkermans, Reinier P; van Engelen, Baziel G M; van Weel, Chris; Speckens, Anne E M

    2017-07-01

    To examine the effect of mindfulness-based stress reduction training (MBSR) on the mental health of medical students during clinical clerkships. Between February 2011 and May 2014, the authors conducted a cluster-randomized controlled trial of clerkships as usual (CAU) and clerkships with additional MBSR in medical students during their first year of clinical clerkships at a Dutch university medical center. MBSR consisted of eight weekly two-hour sessions, comprising didactic teaching, meditation exercises, and group dialogues. Students completed online assessments at baseline and after 3, 7, 12, 15, and 20 months. Outcome measures were psychological distress, positive mental health, life satisfaction, physician empathy, mindfulness skills, and dysfunctional cognitions as measured by validated tools. Of 232 eligible students, 167 students (72%) participated and were randomized by clerkship group into MBSR (n = 83) or CAU (n = 84). The MBSR group reported a small reduction of psychological distress (P = .03, Cohen's d = 0.20) and dysfunctional cognitions (P = .05, Cohen's d = 0.18) and a moderate increase of positive mental health (P = .002, Cohen's d = 0.44), life satisfaction (P = .01, Cohen's d = 0.51), and mindfulness skills (P = .05, Cohen's d = 0.35) compared with CAU during the 20-month follow-up. The authors detected no significant effect on physician empathy (P = .18, Cohen's d = 0.27). MBSR appeared feasible and acceptable to medical clerkship students and resulted in a small to moderate improvement of mental health compared with CAU over the 20-month follow-up.

  6. Flowbca : A flow-based cluster algorithm in Stata

    NARCIS (Netherlands)

    Meekes, J.; Hassink, W.H.J.

    In this article, we introduce the Stata implementation of a flow-based cluster algorithm written in Mata. The main purpose of the flowbca command is to identify clusters based on relational data of flows. We illustrate the command by providing multiple applications, from the research fields of

  7. Controlled clustering of carboxylated SPIONs through polyethylenimine

    Energy Technology Data Exchange (ETDEWEB)

    Nesztor, Dániel; Bali, Krisztina; Tóth, Ildikó Y.; Szekeres, Márta; Tombácz, Etelka, E-mail: tombacz@chem.u-szeged.hu

    2015-04-15

    Clusters of magnetite nanoparticles (MNPs) were synthesized using poly(acrylic acid-co-maleic acid) coated MNPs (PAM@MNP) and branched polyethylenimine (PEI). Materials were characterized by potentiometric titration, zeta potential and dynamic light scattering (DLS) measurements. PEI and PAM@MNP are oppositely charged as characterized by zeta potential measurements (+8, −34 mV respectively) and titration (10.30 mmol −NH{sub 3}{sup +}/g PEI; 0.175 mmol −COO{sup −}/g PAM@MNP) at pH 6.5±0.2; therefore magnetic clusters are formed by electrostatic adhesion. Two different preparation methods and the effect of PEI and electrolyte (NaCl) concentration on the cluster formation was studied. Choosing an optimal concentration of PEI (charge ratio of PEI to PAM@MNP: 0.17) and electrolyte (10 mM), a concentrated (10 g MNP/L) product containing PEI–PAM@MNP nanoclusters with size of 165±10 nm was prepared. Its specific absorption rate (SAR) measured in AC magnetic field (110 kHz, 25 mT) is 12 W/g Fe. The clustered product is expected to have enhanced contrast efficiency in MRI. - Highlights: • SPION clusters of controlled size were prepared by means of electrostatic adhesion. • Nanocluster formation optimum was at 0.17 charge ratio of PEI to PAM@MNP. • Huge aggregates form at higher PEI to PAM@MNP charge ratio. • Higher ionic strength promotes the formation of clusters at lower PEI concentrations.

  8. University-based user facilities: lessons from Tantalus and Aladdin

    International Nuclear Information System (INIS)

    Huber, D.L.

    1985-01-01

    The establishment of university-based user facilities is a relatively new development in the federal funding of research in condensed matter science. Because the Synchrotron Radiation Center (SRC) has been a pioneer user facility, a certain degree of experience, both good and bad, has been acquired in the construction and operation of university-based facilities for synchrotron-related research. The history of SRC is discussed and some of the general lessons learned in the area of advanced planning are outlined. No attempt is made to be either definitive or exhaustive. In the present context, a university-based user facility is understood to be a dedicated facility under direct university control where a majority of the users come from outside the local university community

  9. Effectiveness of a multifaceted implementation strategy on physicians' referral behavior to an evidence-based psychosocial intervention in dementia: a cluster randomized controlled trial

    NARCIS (Netherlands)

    Dopp, C.M.E.; Graff, M.J.L.; Teerenstra, S.; Nijhuis-Van der Sanden, M.W.; Olde Rikkert, M.G.M.; Vernooij-Dassen, M.J.F.J.

    2013-01-01

    BACKGROUND: To evaluate the effectiveness of a multifaceted implementation strategy on physicians' referral rate to and knowledge on the community occupational therapy in dementia program (COTiD program). METHODS: A cluster randomized controlled trial with 28 experimental and 17 control clusters was

  10. CBHRP: A Cluster Based Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, M. G.; Kabir, M. Hasnat; Rahim, M. Sajjadur; Ullah, Sk. Enayet

    2012-01-01

    A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to collect information from target field. On rotation basis, a head-set member receives data from the neighbor nodes and transmits the aggregated results to the distance base station. This protocol ...

  11. Exponential cluster synchronization in directed community networks via adaptive nonperiodically intermittent pinning control

    Science.gov (United States)

    Zhou, Peipei; Cai, Shuiming; Jiang, Shengqin; Liu, Zengrong

    2018-02-01

    In this paper, the problem of exponential cluster synchronization for a class of directed community networks is investigated via adaptive nonperiodically intermittent pinning control. By constructing a novel piecewise continuous Lyapunov function, some sufficient conditions to guarantee globally exponential cluster synchronization are derived. It is noted that the derived cluster synchronization criteria rely on the control rates, but not the control widths or the control periods, which facilitates the choice of the control periods in practical applications. A numerical example is finally presented to show the effectiveness of the obtained theoretical results.

  12. Canonical PSO Based K-Means Clustering Approach for Real Datasets.

    Science.gov (United States)

    Dey, Lopamudra; Chakraborty, Sanjay

    2014-01-01

    "Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.

  13. Collagen attachment to the substrate controls cell clustering through migration

    International Nuclear Information System (INIS)

    Hou, Yue; Rodriguez, Laura Lara; Wang, Juan; Schneider, Ian C

    2014-01-01

    Cell clustering and scattering play important roles in cancer progression and tissue engineering. While the extracellular matrix (ECM) is known to control cell clustering, much of the quantitative work has focused on the analysis of clustering between cells with strong cell–cell junctions. Much less is known about how the ECM regulates cells with weak cell–cell contact. Clustering characteristics were quantified in rat adenocarcinoma cells, which form clusters on physically adsorbed collagen substrates, but not on covalently attached collagen substrates. Covalently attaching collagen inhibited desorption of collagen from the surface. While changes in proliferation rate could not explain differences seen in the clustering, changes in cell motility could. Cells plated under conditions that resulted in more clustering had a lower persistence time and slower migration rate than those under conditions that resulted in less clustering. Understanding how the ECM regulates clustering will not only impact the fundamental understanding of cancer progression, but also will guide the design of tissue engineered constructs that allow for the clustering or dissemination of cells throughout the construct. (paper)

  14. A Cluster Based Group Signature Mechanism For Secure Vanet Communication

    Directory of Open Access Journals (Sweden)

    Navjot Kaur

    2015-08-01

    Full Text Available Vehicular adhoc network is one of the recent area of research to administer safety to human lives controlling of messages and in disposal of messages to users and passengers. VANETs allows communication of moving vehicular nodes. Movement of nodes leads in changing network size and scenario. Whenever a new node joins the network there is a threat of malicious node attack. So we need an environment that is secure and trust worthy. Therefore a new cluster based secure technique is proposed where cluster head is responsible for providing communication between the vehicular nodes. Performance parameters used in this paper are message drop ratio packet delay ratio and verification time.

  15. Core Web Sites of Universities of Islamic world Countries Capitals

    Directory of Open Access Journals (Sweden)

    Farshid Danesh

    2012-07-01

    Full Text Available In order to serve the Islamic researchers, providing a web site is inevitable for Islamic Universities which are in transition from the real to the virtual world and. Today, almost all the major universities in Islamic community have websites. But, in the realization of their mission, it is not clear to what extant these universities were successful in terms of information dissemination. The aim of this paper was to determine the core web sites and evaluate the effectiveness, ranking and collaboration rate among these websites. The formulas of core website determination, co-links and in-links analysis and revised web impact factor were used beside cluster and multidimensional analysis methods in this study. Results showed that "King Saud University" website in Saudi Arabia had the highest visibility and the most authoritative website among all university websites. Also, co-link analysis showed that major Islamic university websites had collaboration in 12 clusters based on clustering analysis and in 11 clusters based on multidimensional analysis, where two of them (Iran and Turkey were national clusters in cluster analysis method. Results analysis indicated that web designers in these universities must identify how to attract links and web traffic in order to promote the quality and content of websites. However, the ultimate success of a website was dependent upon factors such as quality, size, language, and the approximate age of a website which was not limited to one or two factors.

  16. Implementation of evidence-based treatment protocols to manage fever, hyperglycaemia, and swallowing dysfunction in acute stroke (QASC): a cluster randomised controlled trial.

    Science.gov (United States)

    Middleton, Sandy; McElduff, Patrick; Ward, Jeanette; Grimshaw, Jeremy M; Dale, Simeon; D'Este, Catherine; Drury, Peta; Griffiths, Rhonda; Cheung, N Wah; Quinn, Clare; Evans, Malcolm; Cadilhac, Dominique; Levi, Christopher

    2011-11-12

    We assessed patient outcomes 90 days after hospital admission for stroke following a multidisciplinary intervention targeting evidence-based management of fever, hyperglycaemia, and swallowing dysfunction in acute stroke units (ASUs). In the Quality in Acute Stroke Care (QASC) study, a single-blind cluster randomised controlled trial, we randomised ASUs (clusters) in New South Wales, Australia, with immediate access to CT and on-site high dependency units, to intervention or control group. Patients were eligible if they spoke English, were aged 18 years or older, had had an ischaemic stroke or intracerebral haemorrhage, and presented within 48 h of onset of symptoms. Intervention ASUs received treatment protocols to manage fever, hyperglycaemia, and swallowing dysfunction with multidisciplinary team building workshops to address implementation barriers. Control ASUs received only an abridged version of existing guidelines. We recruited pre-intervention and post-intervention patient cohorts to compare 90-day death or dependency (modified Rankin scale [mRS] ≥2), functional dependency (Barthel index), and SF-36 physical and mental component summary scores. Research assistants, the statistician, and patients were masked to trial groups. All analyses were done by intention to treat. This trial is registered at the Australia New Zealand Clinical Trial Registry (ANZCTR), number ACTRN12608000563369. 19 ASUs were randomly assigned to intervention (n=10) or control (n=9). Of 6564 assessed for eligibility, 1696 patients' data were obtained (687 pre-intervention; 1009 post-intervention). Results showed that, irrespective of stroke severity, intervention ASU patients were significantly less likely to be dead or dependent (mRS ≥2) at 90 days than control ASU patients (236 [42%] of 558 patients in the intervention group vs 259 [58%] of 449 in the control group, p=0·002; number needed to treat 6·4; adjusted absolute difference 15·7% [95% CI 5·8-25·4]). They also had a

  17. Control of entanglement transitions in quantum spin clusters

    Science.gov (United States)

    Irons, Hannah R.; Quintanilla, Jorge; Perring, Toby G.; Amico, Luigi; Aeppli, Gabriel

    2017-12-01

    Quantum spin clusters provide a platform for the experimental study of many-body entanglement. Here we address a simple model of a single-molecule nanomagnet featuring N interacting spins in a transverse field. The field can control an entanglement transition (ET). We calculate the magnetization, low-energy gap, and neutron-scattering cross section and find that the ET has distinct signatures, detectable at temperatures as high as 5% of the interaction strength. The signatures are stronger for smaller clusters.

  18. Cluster Ion Implantation in Graphite and Diamond

    DEFF Research Database (Denmark)

    Popok, Vladimir

    2014-01-01

    Cluster ion beam technique is a versatile tool which can be used for controllable formation of nanosize objects as well as modification and processing of surfaces and shallow layers on an atomic scale. The current paper present an overview and analysis of data obtained on a few sets of graphite...... and diamond samples implanted by keV-energy size-selected cobalt and argon clusters. One of the emphases is put on pinning of metal clusters on graphite with a possibility of following selective etching of graphene layers. The other topic of concern is related to the development of scaling law for cluster...... implantation. Implantation of cobalt and argon clusters into two different allotropic forms of carbon, namely, graphite and diamond is analysed and compared in order to approach universal theory of cluster stopping in matter....

  19. A valence-universal coupled-cluster single- and double-excitations method for atoms: Pt. 3

    International Nuclear Information System (INIS)

    Jankowski, K.; Malinowski, P.

    1994-01-01

    To better understand the problems met when solving the equations of VU-CC approaches in the presence of intruder states, we are concerned with the following aspects of the solvability problem for sets of non-linear equations: the existence and properties of multiple solutions and the attainability of these solutions by means of various numerical methods. Our study is concentrated on the equations obtained for Be within the framework of the recently formulated atomically oriented form of the valence-universal coupled-cluster theory accounting for one- and two-electron excitations (VU-CCSD/R) and based on the complete model space (2s 2 , 2p 2 ). Six pairs of multiple solutions representing four 1 S states are found and discussed. Three of these solutions provide amplitudes describing the 2p 2 1 S state for which the intruder state problem has been considered as extremely serious. Several known numerical methods have been applied to solve the same set of non-linear equations for the two-valence cluster amplitudes. It is shown that these methods perform quite differently in the presence of intruder states, which seems to indicate that the intruder state problem for VU-CC methods is partly caused by the commonly used methods of solving the non-linear equations. (author)

  20. [Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

    Science.gov (United States)

    Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

    2013-12-01

    To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

  1. Improving preventive service delivery at adult complete health check-ups: the Preventive health Evidence-based Recommendation Form (PERFORM cluster randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Moineddin Rahim

    2006-07-01

    Full Text Available Abstract Background To determine the effectiveness of a single checklist reminder form to improve the delivery of preventive health services at adult health check-ups in a family practice setting. Methods A prospective cluster randomized controlled trial was conducted at four urban family practice clinics among 38 primary care physicians affiliated with the University of Toronto. Preventive Care Checklist Forms© were created to be used by family physicians at adult health check-ups over a five-month period. The sex-specific forms incorporate evidence-based recommendations on preventive health services and documentation space for routine procedures such as physical examination. The forms were used in two intervention clinics and two control clinics. Rates and relative risks (RR of the performance of 13 preventive health maneuvers at baseline and post-intervention and the percentage of up-to-date preventive health services delivered per patient were compared between the two groups. Results Randomly-selected charts were reviewed at baseline (n = 509 and post-intervention (n = 608. Baseline rates for provision of preventive health services ranged from 3% (fecal occult blood testing to 93% (blood pressure measurement, similar to other settings. The percentage of up-to-date preventive health services delivered per patient at the end of the intervention was 48.9% in the control group and 71.7% in the intervention group. This is an overall 22.8% absolute increase (p = 0.0001, and 46.6% relative increase in the delivery of preventive health services per patient in the intervention group compared to controls. Eight of thirteen preventive health services showed a statistically significant change (p Conclusion This simple, low cost, clinically relevant intervention improves the delivery of preventive health services by prompting physicians of evidence-based recommendations in a checklist format that incorporates existing practice patterns. Periodic updates

  2. Hierarchical video summarization based on context clustering

    Science.gov (United States)

    Tseng, Belle L.; Smith, John R.

    2003-11-01

    A personalized video summary is dynamically generated in our video personalization and summarization system based on user preference and usage environment. The three-tier personalization system adopts the server-middleware-client architecture in order to maintain, select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. In this paper, the metadata includes visual semantic annotations and automatic speech transcriptions. Our personalization and summarization engine in the middleware selects the optimal set of desired video segments by matching shot annotations and sentence transcripts with user preferences. Besides finding the desired contents, the objective is to present a coherent summary. There are diverse methods for creating summaries, and we focus on the challenges of generating a hierarchical video summary based on context information. In our summarization algorithm, three inputs are used to generate the hierarchical video summary output. These inputs are (1) MPEG-7 metadata descriptions of the contents in the server, (2) user preference and usage environment declarations from the user client, and (3) context information including MPEG-7 controlled term list and classification scheme. In a video sequence, descriptions and relevance scores are assigned to each shot. Based on these shot descriptions, context clustering is performed to collect consecutively similar shots to correspond to hierarchical scene representations. The context clustering is based on the available context information, and may be derived from domain knowledge or rules engines. Finally, the selection of structured video segments to generate the hierarchical summary efficiently balances between scene representation and shot selection.

  3. Microassembly using a Cluster of Paramagnetic Microparticles

    NARCIS (Netherlands)

    Khalil, I.S.M.; Brink, F.V; Sardan Sukas, Ö.; Misra, Sarthak

    2013-01-01

    We use a cluster of paramagnetic microparticles to carry out a wireless two-dimensional microassembly operation. A magnetic-based manipulation system is used to control the motion of the cluster under the influence of the applied magnetic fields. Wireless motion control of the cluster is implemented

  4. APPECT: An Approximate Backbone-Based Clustering Algorithm for Tags

    DEFF Research Database (Denmark)

    Zong, Yu; Xu, Guandong; Jin, Pin

    2011-01-01

    algorithm for Tags (APPECT). The main steps of APPECT are: (1) we execute the K-means algorithm on a tag similarity matrix for M times and collect a set of tag clustering results Z={C1,C2,…,Cm}; (2) we form the approximate backbone of Z by executing a greedy search; (3) we fix the approximate backbone...... as the initial tag clustering result and then assign the rest tags into the corresponding clusters based on the similarity. Experimental results on three real world datasets namely MedWorm, MovieLens and Dmoz demonstrate the effectiveness and the superiority of the proposed method against the traditional...... Agglomerative Clustering on tagging data, which possess the inherent drawbacks, such as the sensitivity of initialization. In this paper, we instead make use of the approximate backbone of tag clustering results to find out better tag clusters. In particular, we propose an APProximate backbonE-based Clustering...

  5. Cost/Performance Ratio Achieved by Using a Commodity-Based Cluster

    Science.gov (United States)

    Lopez, Isaac

    2001-01-01

    Researchers at the NASA Glenn Research Center acquired a commodity cluster based on Intel Corporation processors to compare its performance with a traditional UNIX cluster in the execution of aeropropulsion applications. Since the cost differential of the clusters was significant, a cost/performance ratio was calculated. After executing a propulsion application on both clusters, the researchers demonstrated a 9.4 cost/performance ratio in favor of the Intel-based cluster. These researchers utilize the Aeroshark cluster as one of the primary testbeds for developing NPSS parallel application codes and system software. The Aero-shark cluster provides 64 Intel Pentium II 400-MHz processors, housed in 32 nodes. Recently, APNASA - a code developed by a Government/industry team for the design and analysis of turbomachinery systems was used for a simulation on Glenn's Aeroshark cluster.

  6. Molecular-based rapid inventories of sympatric diversity: a comparison of DNA barcode clustering methods applied to geography-based vs clade-based sampling of amphibians.

    Science.gov (United States)

    Paz, Andrea; Crawford, Andrew J

    2012-11-01

    Molecular markers offer a universal source of data for quantifying biodiversity. DNA barcoding uses a standardized genetic marker and a curated reference database to identify known species and to reveal cryptic diversity within wellsampled clades. Rapid biological inventories, e.g. rapid assessment programs (RAPs), unlike most barcoding campaigns, are focused on particular geographic localities rather than on clades. Because of the potentially sparse phylogenetic sampling, the addition of DNA barcoding to RAPs may present a greater challenge for the identification of named species or for revealing cryptic diversity. In this article we evaluate the use of DNA barcoding for quantifying lineage diversity within a single sampling site as compared to clade-based sampling, and present examples from amphibians. We compared algorithms for identifying DNA barcode clusters (e.g. species, cryptic species or Evolutionary Significant Units) using previously published DNA barcode data obtained from geography-based sampling at a site in Central Panama, and from clade-based sampling in Madagascar. We found that clustering algorithms based on genetic distance performed similarly on sympatric as well as clade-based barcode data, while a promising coalescent-based method performed poorly on sympatric data. The various clustering algorithms were also compared in terms of speed and software implementation. Although each method has its shortcomings in certain contexts, we recommend the use of the ABGD method, which not only performs fairly well under either sampling method, but does so in a few seconds and with a user-friendly Web interface.

  7. Centroid based clustering of high throughput sequencing reads based on n-mer counts.

    Science.gov (United States)

    Solovyov, Alexander; Lipkin, W Ian

    2013-09-08

    Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering. We study several centroid based algorithms for clustering sequences based on word counts. Study of their performance shows that using k-means algorithm with or without the data whitening is efficient from the computational point of view. A higher clustering accuracy can be achieved using the soft expectation maximization method, whereby each sequence is attributed to each cluster with a specific probability. We implement an open source tool for alignment-free clustering. It is publicly available from github: https://github.com/luscinius/afcluster. We show the utility of alignment-free sequence clustering for high throughput sequencing analysis despite its limitations. In particular, it allows one to perform assembly with reduced resources and a minimal loss of quality. The major factor affecting performance of alignment-free read clustering is the length of the read.

  8. Web-based Quality Control Tool used to validate CERES products on a cluster of Linux servers

    Science.gov (United States)

    Chu, C.; Sun-Mack, S.; Heckert, E.; Chen, Y.; Mlynczak, P.; Mitrescu, C.; Doelling, D.

    2014-12-01

    There have been a few popular desktop tools used in the Earth Science community to validate science data. Because of the limitation on the capacity of desktop hardware such as disk space and CPUs, those softwares are not able to display large amount of data from files.This poster will talk about an in-house developed web-based software built on a cluster of Linux servers. That allows users to take advantage of a few Linux servers working in parallel to generate hundreds images in a short period of time. The poster will demonstrate:(1) The hardware and software architecture is used to provide high throughput of images. (2) The software structure that can incorporate new products and new requirement quickly. (3) The user interface about how users can manipulate the data and users can control how the images are displayed.

  9. Comparisons of Belief-Based Personality Constructs in Polish and American University Students: Paranormal Beliefs, Locus of Control, Irrational Beliefs, and Social Interest.

    Science.gov (United States)

    Tobacyk, Jerome J.; Tobacyk, Zofia Socha

    1992-01-01

    Uses Social Learning Theory to compare 149 university students from Poland with 136 university students from the southern United States for belief-based personality constructs and personality correlates of paranormal beliefs. As hypothesized, Poles reported a more external locus of control and significantly greater endorsement of irrational…

  10. Space-Time Analysis of Testicular Cancer Clusters Using Residential Histories: A Case-Control Study in Denmark

    Science.gov (United States)

    Sloan, Chantel D.; Nordsborg, Rikke B.; Jacquez, Geoffrey M.; Raaschou-Nielsen, Ole; Meliker, Jaymie R.

    2015-01-01

    Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population. PMID

  11. Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.

    Directory of Open Access Journals (Sweden)

    Chantel D Sloan

    Full Text Available Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297 were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs. Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish

  12. Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.

    Science.gov (United States)

    Sloan, Chantel D; Nordsborg, Rikke B; Jacquez, Geoffrey M; Raaschou-Nielsen, Ole; Meliker, Jaymie R

    2015-01-01

    Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population.

  13. Cluster-based spectrum sensing for cognitive radios with imperfect channel to cluster-head

    KAUST Repository

    Ben Ghorbel, Mahdi

    2012-04-01

    Spectrum sensing is considered as the first and main step for cognitive radio systems to achieve an efficient use of spectrum. Cooperation and clustering among cognitive radio users are two techniques that can be employed with spectrum sensing in order to improve the sensing performance by reducing miss-detection and false alarm. In this paper, within the framework of a clustering-based cooperative spectrum sensing scheme, we study the effect of errors in transmitting the local decisions from the secondary users to the cluster heads (or the fusion center), while considering non-identical channel conditions between the secondary users. Closed-form expressions for the global probabilities of detection and false alarm at the cluster head are derived. © 2012 IEEE.

  14. Cluster-based spectrum sensing for cognitive radios with imperfect channel to cluster-head

    KAUST Repository

    Ben Ghorbel, Mahdi; Nam, Haewoon; Alouini, Mohamed-Slim

    2012-01-01

    Spectrum sensing is considered as the first and main step for cognitive radio systems to achieve an efficient use of spectrum. Cooperation and clustering among cognitive radio users are two techniques that can be employed with spectrum sensing in order to improve the sensing performance by reducing miss-detection and false alarm. In this paper, within the framework of a clustering-based cooperative spectrum sensing scheme, we study the effect of errors in transmitting the local decisions from the secondary users to the cluster heads (or the fusion center), while considering non-identical channel conditions between the secondary users. Closed-form expressions for the global probabilities of detection and false alarm at the cluster head are derived. © 2012 IEEE.

  15. Sliding Window Based Feature Extraction and Traffic Clustering for Green Mobile Cyberphysical Systems

    Directory of Open Access Journals (Sweden)

    Jiao Zhang

    2017-01-01

    Full Text Available Both the densification of small base stations and the diversity of user activities bring huge challenges for today’s heterogeneous networks, either heavy burdens on base stations or serious energy waste. In order to ensure coverage of the network while reducing the total energy consumption, we adopt a green mobile cyberphysical system (MCPS to handle this problem. In this paper, we propose a feature extraction method using sliding window to extract the distribution feature of mobile user equipment (UE, and a case study is presented to demonstrate that the method is efficacious in reserving the clustering distribution feature. Furthermore, we present traffic clustering analysis to categorize collected traffic distribution samples into a limited set of traffic patterns, where the patterns and corresponding optimized control strategies are used to similar traffic distributions for the rapid control of base station state. Experimental results show that the sliding window is more superior in enabling higher UE coverage over the grid method. Besides, the optimized control strategy obtained from the traffic pattern is capable of achieving a high coverage that can well serve over 98% of all mobile UE for similar traffic distributions.

  16. Structuring communication relationships for interprofessional teamwork (SCRIPT): a cluster randomized controlled trial

    OpenAIRE

    Zwarenstein, Merrick; Reeves, Scott; Russell, Ann; Kenaszchuk, Chris; Conn, Lesley Gotlib; Miller, Karen-Lee; Lingard, Lorelei; Thorpe, Kevin E

    2007-01-01

    Abstract Background Despite a burgeoning interest in using interprofessional approaches to promote effective collaboration in health care, systematic reviews find scant evidence of benefit. This protocol describes the first cluster randomized controlled trial (RCT) to design and evaluate an intervention intended to improve interprofessional collaborative communication and patient-centred care. Objectives The objective is to evaluate the effects of a four-component, hospital-based staff commun...

  17. Graph-based clustering and data visualization algorithms

    CERN Document Server

    Vathy-Fogarassy, Ágnes

    2013-01-01

    This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on

  18. Improved Density Based Spatial Clustering of Applications of Noise Clustering Algorithm for Knowledge Discovery in Spatial Data

    Directory of Open Access Journals (Sweden)

    Arvind Sharma

    2016-01-01

    Full Text Available There are many techniques available in the field of data mining and its subfield spatial data mining is to understand relationships between data objects. Data objects related with spatial features are called spatial databases. These relationships can be used for prediction and trend detection between spatial and nonspatial objects for social and scientific reasons. A huge data set may be collected from different sources as satellite images, X-rays, medical images, traffic cameras, and GIS system. To handle this large amount of data and set relationship between them in a certain manner with certain results is our primary purpose of this paper. This paper gives a complete process to understand how spatial data is different from other kinds of data sets and how it is refined to apply to get useful results and set trends to predict geographic information system and spatial data mining process. In this paper a new improved algorithm for clustering is designed because role of clustering is very indispensable in spatial data mining process. Clustering methods are useful in various fields of human life such as GIS (Geographic Information System, GPS (Global Positioning System, weather forecasting, air traffic controller, water treatment, area selection, cost estimation, planning of rural and urban areas, remote sensing, and VLSI designing. This paper presents study of various clustering methods and algorithms and an improved algorithm of DBSCAN as IDBSCAN (Improved Density Based Spatial Clustering of Application of Noise. The algorithm is designed by addition of some important attributes which are responsible for generation of better clusters from existing data sets in comparison of other methods.

  19. Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

    Science.gov (United States)

    Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

    2018-05-03

    Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

  20. Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks

    Directory of Open Access Journals (Sweden)

    Farhan Aadil

    2018-05-01

    Full Text Available Flying ad-hoc networks (FANETs are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

  1. An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

    Science.gov (United States)

    Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

    2013-05-01

    Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

  2. REFOCUS Trial: protocol for a cluster randomised controlled trial of a pro-recovery intervention within community based mental health teams.

    Science.gov (United States)

    Slade, Mike; Bird, Victoria; Le Boutillier, Clair; Williams, Julie; McCrone, Paul; Leamy, Mary

    2011-11-23

    There is a consensus about the importance of 'recovery' in mental health services, but the evidence base is limited. A two centre, cluster randomised controlled trial. Participants are community-based mental health teams, and service users aged 18-65 years with a primary clinical diagnosis of psychosis. In relation to the REFOCUS Manual researchintorecovery.com/refocus, which describes a 12-month, pro-recovery intervention based on the REFOCUS Model, the objectives are: (1) To establish the effectiveness of the intervention described in the REFOCUS Manual; (2) To validate the REFOCUS Model; (3) To establish and optimise trial parameters for the REFOCUS Manual; and (4) To understand the relationship between clinical outcomes and recovery outcomes. The hypothesis for the main study is that service users in the intervention arm will experience significantly greater increases in measures of personal recovery (as measured by the QPR) compared to service users receiving care from control teams. The hypothesis for the secondary study is that black service users in the intervention arm will experience significantly greater increases in measures of personal recovery (as measured by the QPR) and client satisfaction (as measured by the CSQ) compared to Black service users receiving care from control teams. The intervention comprises treatment as usual plus two components: recovery-promoting relationships and working practices. The control condition is treatment as usual. The primary outcme is the Process of Recovery Questionnaire (QPR). Secondary outcomes are satisfaction, Goal setting - Personal Primary Outcome, hope, well-being, empowerment, and quality of life. Primary outcomes for the secondary study will be QPR and satisfaction. Cost data will be estimated, and clinical outcomes will also be reported (symptomatology, need, social disability, functioning). 29 teams (15 intervention and 14 control) will be randomised. Within each team, 15 services users will be randomly

  3. Map-based trigonometric parallaxes of open clusters - The Pleiades

    Science.gov (United States)

    Gatewood, George; Castelaz, Michael; Han, Inwoo; Persinger, Timothy; Stein, John

    1990-01-01

    The multichannel astrometric photometer and Thaw refractor of the University of Pittsburgh's Allegheny Observatory have been used to determine the trigonometric parallax of the Pleiades star cluster. The distance determined, 150 with a standard error of 18 parsecs, places the cluster slightly farther away than generally accepted. This suggests that the basis of many estimations of the cosmic distance scale is approximately 20 percent short. The accuracy of the determination is limited by the number and choice of reference stars. With careful attention to the selection of reference stars in several Pleiades regions, it should be possible to examine differences in the photometric and trigonometric modulus at a precision of 0.1 magnitudes.

  4. Microgrid central controller development and hierarchical control implemetation in the intelligent microgrid lab of Aalborg University

    OpenAIRE

    Meng, Lexuan; Savaghebi, Mehdi; Andrade, Fabio; Vasquez Quintero, Juan Carlos; Guerrero, Josep M.; Graells Sobré, Moisès

    2015-01-01

    This paper presents the development of a microgrid central controller in an inverter-based intelligent microgrid (iMG) lab in Aalborg University, Denmark. The iMG lab aims to provide a flexible experimental platform for comprehensive studies of microgrids. The complete control system applied in this lab is based on the hierarchical control scheme for microgrids and includes primary, secondary and tertiary control. The structure of the lab, including the lab facilities, configurations and comm...

  5. Density-Based Clustering with Geographical Background Constraints Using a Semantic Expression Model

    Directory of Open Access Journals (Sweden)

    Qingyun Du

    2016-05-01

    Full Text Available A semantics-based method for density-based clustering with constraints imposed by geographical background knowledge is proposed. In this paper, we apply an ontological approach to the DBSCAN (Density-Based Geospatial Clustering of Applications with Noise algorithm in the form of knowledge representation for constraint clustering. When used in the process of clustering geographic information, semantic reasoning based on a defined ontology and its relationships is primarily intended to overcome the lack of knowledge of the relevant geospatial data. Better constraints on the geographical knowledge yield more reasonable clustering results. This article uses an ontology to describe the four types of semantic constraints for geographical backgrounds: “No Constraints”, “Constraints”, “Cannot-Link Constraints”, and “Must-Link Constraints”. This paper also reports the implementation of a prototype clustering program. Based on the proposed approach, DBSCAN can be applied with both obstacle and non-obstacle constraints as a semi-supervised clustering algorithm and the clustering results are displayed on a digital map.

  6. Ontology-based topic clustering for online discussion data

    Science.gov (United States)

    Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

    2013-03-01

    With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.

  7. Two-year impact of community-based health screening and parenting groups on child development in Zambia: Follow-up to a cluster-randomized controlled trial.

    Science.gov (United States)

    Rockers, Peter C; Zanolini, Arianna; Banda, Bowen; Chipili, Mwaba Moono; Hughes, Robert C; Hamer, Davidson H; Fink, Günther

    2018-04-01

    Early childhood interventions have potential to offset the negative impact of early adversity. We evaluated the impact of a community-based parenting group intervention on child development in Zambia. We conducted a non-masked cluster-randomized controlled trial in Southern Province, Zambia. Thirty clusters of villages were matched based on population density and distance from the nearest health center, and randomly assigned to intervention (15 clusters, 268 caregiver-child dyads) or control (15 clusters, 258 caregiver-child dyads). Caregivers were eligible if they had a child 6 to 12 months old at baseline. In intervention clusters, caregivers were visited twice per month during the first year of the study by child development agents (CDAs) and were invited to attend fortnightly parenting group meetings. Parenting groups selected "head mothers" from their communities who were trained by CDAs to facilitate meetings and deliver a diverse parenting curriculum. The parenting group intervention, originally designed to run for 1 year, was extended, and households were visited for a follow-up assessment at the end of year 2. The control group did not receive any intervention. Intention-to-treat analysis was performed for primary outcomes measured at the year 2 follow-up: stunting and 5 domains of neurocognitive development measured using the Bayley Scales of Infant and Toddler Development-Third Edition (BSID-III). In order to show Cohen's d estimates, BSID-III composite scores were converted to z-scores by standardizing within the study population. In all, 195/268 children (73%) in the intervention group and 182/258 children (71%) in the control group were assessed at endline after 2 years. The intervention significantly reduced stunting (56/195 versus 72/182; adjusted odds ratio 0.45, 95% CI 0.22 to 0.92; p = 0.028) and had a significant positive impact on language (β 0.14, 95% CI 0.01 to 0.27; p = 0.039). The intervention did not significantly impact cognition (β 0

  8. Two-year impact of community-based health screening and parenting groups on child development in Zambia: Follow-up to a cluster-randomized controlled trial.

    Directory of Open Access Journals (Sweden)

    Peter C Rockers

    2018-04-01

    Full Text Available Early childhood interventions have potential to offset the negative impact of early adversity. We evaluated the impact of a community-based parenting group intervention on child development in Zambia.We conducted a non-masked cluster-randomized controlled trial in Southern Province, Zambia. Thirty clusters of villages were matched based on population density and distance from the nearest health center, and randomly assigned to intervention (15 clusters, 268 caregiver-child dyads or control (15 clusters, 258 caregiver-child dyads. Caregivers were eligible if they had a child 6 to 12 months old at baseline. In intervention clusters, caregivers were visited twice per month during the first year of the study by child development agents (CDAs and were invited to attend fortnightly parenting group meetings. Parenting groups selected "head mothers" from their communities who were trained by CDAs to facilitate meetings and deliver a diverse parenting curriculum. The parenting group intervention, originally designed to run for 1 year, was extended, and households were visited for a follow-up assessment at the end of year 2. The control group did not receive any intervention. Intention-to-treat analysis was performed for primary outcomes measured at the year 2 follow-up: stunting and 5 domains of neurocognitive development measured using the Bayley Scales of Infant and Toddler Development-Third Edition (BSID-III. In order to show Cohen's d estimates, BSID-III composite scores were converted to z-scores by standardizing within the study population. In all, 195/268 children (73% in the intervention group and 182/258 children (71% in the control group were assessed at endline after 2 years. The intervention significantly reduced stunting (56/195 versus 72/182; adjusted odds ratio 0.45, 95% CI 0.22 to 0.92; p = 0.028 and had a significant positive impact on language (β 0.14, 95% CI 0.01 to 0.27; p = 0.039. The intervention did not significantly impact

  9. Case clustering in pityriasis rosea: a multicenter epidemiologic study in primary care settings in Hong Kong.

    Science.gov (United States)

    Chuh, Antonio A T; Lee, Albert; Molinari, Nicolas

    2003-04-01

    To investigate the epidemiology of pityriasis rosea in primary care settings in Hong Kong and to analyze for temporal clustering. Retrospective epidemiologic study. Six primary care teaching practices affiliated with a university. Patients Forty-one patients with pityriasis rosea, 564 patients with atopic dermatitis (negative control condition), and 35 patients with scabies (positive control condition). We retrieved all records of patients with pityriasis rosea, atopic dermatitis, or scabies diagnosed in 3 years. We analyzed temporal clustering by a method based on a regression model. The monthly incidence of pityriasis rosea is negatively but insignificantly correlated with mean air temperature (gamma s = -0.41, P =.19) and mean total rainfall (gamma s = -0.34, P =.27). Three statistically significant clusters with 7, 6, and 7 cases were identified (P =.03), occurring in the second coldest month in the year (February), the second hottest month (July), and a temperate month (April), respectively. For atopic dermatitis (negative control condition), the nonclustering regression model was selected by Akaike information criteria. For scabies (positive control condition), 1 cluster of 20 cases was detected (P =.03). Significant temporal clustering independent of seasonal variation occurred in our series of patients with pityriasis rosea. This may be indicative of an infectious cause.

  10. Cluster-guided imaging-based CFD analysis of airflow and particle deposition in asthmatic human lungs

    Science.gov (United States)

    Choi, Jiwoong; Leblanc, Lawrence; Choi, Sanghun; Haghighi, Babak; Hoffman, Eric; Lin, Ching-Long

    2017-11-01

    The goal of this study is to assess inter-subject variability in delivery of orally inhaled drug products to small airways in asthmatic lungs. A recent multiscale imaging-based cluster analysis (MICA) of computed tomography (CT) lung images in an asthmatic cohort identified four clusters with statistically distinct structural and functional phenotypes associating with unique clinical biomarkers. Thus, we aimed to address inter-subject variability via inter-cluster variability. We selected a representative subject from each of the 4 asthma clusters as well as 1 male and 1 female healthy controls, and performed computational fluid and particle simulations on CT-based airway models of these subjects. The results from one severe and one non-severe asthmatic cluster subjects characterized by segmental airway constriction had increased particle deposition efficiency, as compared with the other two cluster subjects (one non-severe and one severe asthmatics) without airway constriction. Constriction-induced jets impinging on distal bifurcations led to excessive particle deposition. The results emphasize the impact of airway constriction on regional particle deposition rather than disease severity, demonstrating the potential of using cluster membership to tailor drug delivery. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837. XSEDE.

  11. Result Diversification Based on Query-Specific Cluster Ranking

    NARCIS (Netherlands)

    J. He (Jiyin); E. Meij; M. de Rijke (Maarten)

    2011-01-01

    htmlabstractResult diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking,

  12. Microgrids Real-Time Pricing Based on Clustering Techniques

    Directory of Open Access Journals (Sweden)

    Hao Liu

    2018-05-01

    Full Text Available Microgrids are widely spreading in electricity markets worldwide. Besides the security and reliability concerns for these microgrids, their operators need to address consumers’ pricing. Considering the growth of smart grids and smart meter facilities, it is expected that microgrids will have some level of flexibility to determine real-time pricing for at least some consumers. As such, the key challenge is finding an optimal pricing model for consumers. This paper, accordingly, proposes a new pricing scheme in which microgrids are able to deploy clustering techniques in order to understand their consumers’ load profiles and then assign real-time prices based on their load profile patterns. An improved weighted fuzzy average k-means is proposed to cluster load curve of consumers in an optimal number of clusters, through which the load profile of each cluster is determined. Having obtained the load profile of each cluster, real-time prices are given to each cluster, which is the best price given to all consumers in that cluster.

  13. Motion control in double-walled carbon nanotube systems using a Stone-Thrower-Wales defect cluster

    International Nuclear Information System (INIS)

    Liu Ping; Zhang Yongwei

    2010-01-01

    The ability to control the motion of a single molecule will have an important impact in nano-mechanical systems. Multi-walled carbon nanotube systems, which have extremely low intertube friction and strong motion confinement, can form the basis for mechanically based motion control. We devise two molecular motion control units based on double-walled carbon nanotubes embedded with a Stone-Thrower-Wales defect cluster, and perform molecular dynamics simulations to determine the characteristics of these two control units. We show that one of the molecular control units is able to perform a logic operation on one logic input and produce three logic outputs, while the other is able to produce two logic outputs. Potential applications of the motion control units include molecular switches, shuttles and mechanically based logic devices.

  14. Cluster-specific small airway modeling for imaging-based CFD analysis of pulmonary air flow and particle deposition in COPD smokers

    Science.gov (United States)

    Haghighi, Babak; Choi, Jiwoong; Choi, Sanghun; Hoffman, Eric A.; Lin, Ching-Long

    2017-11-01

    Accurate modeling of small airway diameters in patients with chronic obstructive pulmonary disease (COPD) is a crucial step toward patient-specific CFD simulations of regional airflow and particle transport. We proposed to use computed tomography (CT) imaging-based cluster membership to identify structural characteristics of airways in each cluster and use them to develop cluster-specific airway diameter models. We analyzed 284 COPD smokers with airflow limitation, and 69 healthy controls. We used multiscale imaging-based cluster analysis (MICA) to classify smokers into 4 clusters. With representative cluster patients and healthy controls, we performed multiple regressions to quantify variation of airway diameters by generation as well as by cluster. The cluster 2 and 4 showed more diameter decrease as generation increases than other clusters. The cluster 4 had more rapid decreases of airway diameters in the upper lobes, while cluster 2 in the lower lobes. We then used these regression models to estimate airway diameters in CT unresolved regions to obtain pressure-volume hysteresis curves using a 1D resistance model. These 1D flow solutions can be used to provide the patient-specific boundary conditions for 3D CFD simulations in COPD patients. Support for this study was provided, in part, by NIH Grants U01-HL114494, R01-HL112986 and S10-RR022421.

  15. A LOOP-BASED APPROACH IN CLUSTERING AND ROUTING IN MOBILE AD HOC NETWORKS

    Institute of Scientific and Technical Information of China (English)

    Li Yanping; Wang Xin; Xue Xiangyang; C.K. Toh

    2006-01-01

    Although clustering is a convenient framework to enable traffic control and service support in Mobile Ad hoc NETworks (MANETs), it is seldom adopted in practice due to the additional traffic overhead it leads to for the resource limited ad hoc network. In order to address this problem, we proposed a loop-based approach to combine clustering and routing. By employing loop topologies, topology information is disseminated with a loop instead of a single node, which provides better robustness, and the nature of a loop that there are two paths between each pair of nodes within a loop suggests smart route recovery strategy. Our approach is composed of setup procedure, regular procedure and recovery procedure to achieve clustering, routing and emergent route recovering.

  16. Proactive palliative care for patients with COPD (PROLONG: a pragmatic cluster controlled trial

    Directory of Open Access Journals (Sweden)

    Duenk RG

    2017-09-01

    Full Text Available RG Duenk,1 C Verhagen,1 EM Bronkhorst,2 PJWB van Mierlo,3,4 MEAC Broeders,5 SM Collard,6 PNR Dekhuijzen,7 KCP Vissers,1 Y Heijdra,7,* Y Engels1,* 1Department of Anesthesiology, Pain and Palliative Medicine, 2Department of Health Evidence, Radboud University Medical Center, Nijmegen, 3Department of Supportive and Palliative Medicine, 4Department of Geriatric Medicine, Rijnstate Hospital, Arnhem, 5Department of Pulmonary Diseases, Jeroen Bosch Hospital, ‘s-Hertogenbosch, 6Department of Pulmonary Diseases, Meander Medical Center, Amersfoort, 7Department of Pulmonary Diseases, Radboud University Medical Center, Nijmegen, the Netherlands *These authors contributed equally to this work Background and aim: Patients with advanced chronic obstructive pulmonary disease (COPD have poor quality of life. The aim of this study was to assess the effects of proactive palliative care on the well-being of these patients.Trial registration: This trial is registered with the Netherlands Trial Register, NTR4037.Patients and methods: A pragmatic cluster controlled trial (quasi-experimental design was performed with hospitals as cluster (three intervention and three control and a pretrial assessment was performed. Hospitals were selected for the intervention group based on the presence of a specialized palliative care team (SPCT. To control for confounders, a pretrial assessment was performed in which hospitals were compared on baseline characteristics. Patients with COPD with poor prognosis were recruited during hospitalization for acute exacerbation. All patients received usual care while patients in the intervention group received additional proactive palliative care in monthly meetings with an SPCT. Our primary outcome was change in quality of life score after 3 months, which was measured using the St George Respiratory Questionnaire (SGRQ. Secondary outcomes were, among others, quality of life at 6, 9 and 12 months; readmissions: survival; and having made

  17. Likelihood-based inference for clustered line transect data

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus Plenge; Schweder, Tore

    The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

  18. Result diversification based on query-specific cluster ranking

    NARCIS (Netherlands)

    He, J.; Meij, E.; de Rijke, M.

    2011-01-01

    Result diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking, in which diversification

  19. Likelihood-based inference for clustered line transect data

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Schweder, Tore

    2006-01-01

    The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

  20. Analyzing Dynamic Probabilistic Risk Assessment Data through Topology-Based Clustering

    Energy Technology Data Exchange (ETDEWEB)

    Diego Mandelli; Dan Maljovec; BeiWang; Valerio Pascucci; Peer-Timo Bremer

    2013-09-01

    We investigate the use of a topology-based clustering technique on the data generated by dynamic event tree methodologies. The clustering technique we utilizes focuses on a domain-partitioning algorithm based on topological structures known as the Morse-Smale complex, which partitions the data points into clusters based on their uniform gradient flow behavior. We perform both end state analysis and transient analysis to classify the set of nuclear scenarios. We demonstrate our methodology on a dataset generated for a sodium-cooled fast reactor during an aircraft crash scenario. The simulation tracks the temperature of the reactor as well as the time for a recovery team to fix the passive cooling system. Combined with clustering results obtained previously through mean shift methodology, we present the user with complementary views of the data that help illuminate key features that may be otherwise hidden using a single methodology. By clustering the data, the number of relevant test cases to be selected for further analysis can be drastically reduced by selecting a representative from each cluster. Identifying the similarities of simulations within a cluster can also aid in the drawing of important conclusions with respect to safety analysis.

  1. Fuzzy Weight Cluster-Based Routing Algorithm for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Teng Gao

    2015-01-01

    Full Text Available Cluster-based protocol is a kind of important routing in wireless sensor networks. However, due to the uneven distribution of cluster heads in classical clustering algorithm, some nodes may run out of energy too early, which is not suitable for large-scale wireless sensor networks. In this paper, a distributed clustering algorithm based on fuzzy weighted attributes is put forward to ensure both energy efficiency and extensibility. On the premise of a comprehensive consideration of all attributes, the corresponding weight of each parameter is assigned by using the direct method of fuzzy engineering theory. Then, each node works out property value. These property values will be mapped to the time axis and be triggered by a timer to broadcast cluster headers. At the same time, the radio coverage method is adopted, in order to avoid collisions and to ensure the symmetrical distribution of cluster heads. The aggregated data are forwarded to the sink node in the form of multihop. The simulation results demonstrate that clustering algorithm based on fuzzy weighted attributes has a longer life expectancy and better extensibility than LEACH-like algorithms.

  2. Getting better at chronic care in remote communities: study protocol for a pragmatic cluster randomised controlled of community based management.

    Science.gov (United States)

    Schmidt, Barbara; Wenitong, Mark; Esterman, Adrian; Hoy, Wendy; Segal, Leonie; Taylor, Sean; Preece, Cilla; Sticpewich, Alex; McDermott, Robyn

    2012-11-21

    Prevalence and incidence of diabetes and other common comorbid conditions (hypertension, coronary heart disease, renal disease and chronic lung disease) are extremely high among Indigenous Australians. Recent measures to improve quality of preventive care in Indigenous community settings, while apparently successful at increasing screening and routine check-up rates, have shown only modest or little improvements in appropriate care such as the introduction of insulin and other scaled-up drug regimens in line with evidence-based guidelines, together with support for risk factor reduction. A new strategy is required to ensure high quality integrated family-centred care is available locally, with continuity and cultural safety, by community-based care coordinators with appropriate system supports. The trial design is open parallel cluster randomised controlled trial. The objective of this pragmatic trial is to test the effectiveness of a model of health service delivery that facilitates integrated community-based, intensive chronic condition management, compared with usual care, in rural and remote Indigenous primary health care services in north Queensland. Participants are Indigenous adults (aged 18-65 years) with poorly controlled diabetes (HbA1c>=8.5) and at least one other chronic condition. The intervention is to employ an Indigenous Health Worker to case manage the care of a maximum caseload of 30 participants. The Indigenous Health Workers receive intensive clinical training initially, and throughout the study, to ensure they are competent to coordinate care for people with chronic conditions. The Indigenous Health Workers, supported by the local primary health care (PHC) team and an Indigenous Clinical Support Team, will manage care, including coordinating access to multidisciplinary team care based on best practice standards. Allocation by cluster to the intervention and control groups is by simple randomisation after participant enrolment. Participants in

  3. Effects of a guided web-based smoking cessation program with telephone counseling: a cluster randomized controlled trial.

    Science.gov (United States)

    Mehring, Michael; Haag, Max; Linde, Klaus; Wagenpfeil, Stefan; Schneider, Antonius

    2014-09-24

    Preliminary findings suggest that Web-based interventions may be effective in achieving significant smoking cessation. To date, very few findings are available for primary care patients, and especially for the involvement of general practitioners. Our goal was to examine the short-term effectiveness of a fully automated Web-based coaching program in combination with accompanied telephone counseling in smoking cessation in a primary care setting. The study was an unblinded cluster-randomized trial with an observation period of 12 weeks. Individuals recruited by general practitioners randomized to the intervention group participated in a Web-based coaching program based on education, motivation, exercise guidance, daily short message service (SMS) reminding, weekly feedback through Internet, and active monitoring by general practitioners. All components of the program are fully automated. Participants in the control group received usual care and advice from their practitioner without the Web-based coaching program. The main outcome was the biochemically confirmed smoking status after 12 weeks. We recruited 168 participants (86 intervention group, 82 control group) into the study. For 51 participants from the intervention group and 70 participants from the control group, follow-up data were available both at baseline and 12 weeks. Very few patients (9.8%, 5/51) from the intervention group and from the control group (8.6%, 6/70) successfully managed smoking cessation (OR 0.86, 95% CI 0.25-3.0; P=.816). Similar results were found within the intent-to-treat analysis: 5.8% (5/86) of the intervention group and 7.3% (6/82) of the control group (OR 1.28, 95% CI 0.38-4.36; P=.694). The number of smoked cigarettes per day decreased on average by 9.3 in the intervention group and by 6.6 in the control group (2.7 mean difference; 95% CI -5.33 to -0.58; P=.045). After adjustment for the baseline value, age, gender, and height, this significance decreases (mean difference 2.2; 95

  4. Effect of workplace- versus home-based physical exercise on pain in healthcare workers: study protocol for a single blinded cluster randomized controlled trial.

    Science.gov (United States)

    Jakobsen, Markus D; Sundstrup, Emil; Brandt, Mikkel; Kristensen, Anne Zoëga; Jay, Kenneth; Stelter, Reinhard; Lavendt, Ebbe; Aagaard, Per; Andersen, Lars L

    2014-04-07

    The prevalence and consequences of musculoskeletal pain is considerable among healthcare workers, allegedly due to high physical work demands of healthcare work. Previous investigations have shown promising results of physical exercise for relieving pain among different occupational groups, but the question remains whether such physical exercise should be performed at the workplace or conducted as home-based exercise. Performing physical exercise at the workplace together with colleagues may be more motivating for some employees and thus increase adherence. On the other hand, physical exercise performed during working hours at the workplace may be costly for the employers in terms of time spend. Thus, it seems relevant to compare the efficacy of workplace- versus home-based training on musculoskeletal pain. This study is intended to investigate the effect of workplace-based versus home-based physical exercise on musculoskeletal pain among healthcare workers. This study was designed as a cluster randomized controlled trial performed at 3 hospitals in Copenhagen, Denmark. Clusters are hospital departments and hospital units. Cluster randomization was chosen to increase adherence and avoid contamination between interventions. Two hundred healthcare workers from 18 departments located at three different hospitals is allocated to 10 weeks of 1) workplace based physical exercise performed during working hours (using kettlebells, elastic bands and exercise balls) for 5 × 10 minutes per week and up to 5 group-based coaching sessions, or 2) home based physical exercise performed during leisure time (using elastic bands and body weight exercises) for 5 × 10 minutes per week. Both intervention groups will also receive ergonomic instructions on patient handling and use of lifting aides etc. Inclusion criteria are female healthcare workers working at a hospital. Average pain intensity (VAS scale 0-10) of the back, neck and shoulder (primary outcome) and physical

  5. Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

    Science.gov (United States)

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2014-05-01

    This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

    Science.gov (United States)

    Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure

    2018-01-01

    Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257

  7. Fatigue Feature Extraction Analysis based on a K-Means Clustering Approach

    Directory of Open Access Journals (Sweden)

    M.F.M. Yunoh

    2015-06-01

    Full Text Available This paper focuses on clustering analysis using a K-means approach for fatigue feature dataset extraction. The aim of this study is to group the dataset as closely as possible (homogeneity for the scattered dataset. Kurtosis, the wavelet-based energy coefficient and fatigue damage are calculated for all segments after the extraction process using wavelet transform. Kurtosis, the wavelet-based energy coefficient and fatigue damage are used as input data for the K-means clustering approach. K-means clustering calculates the average distance of each group from the centroid and gives the objective function values. Based on the results, maximum values of the objective function can be seen in the two centroid clusters, with a value of 11.58. The minimum objective function value is found at 8.06 for five centroid clusters. It can be seen that the objective function with the lowest value for the number of clusters is equal to five; which is therefore the best cluster for the dataset.

  8. Galaxy clusters in the cosmic web

    Science.gov (United States)

    Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

    2014-12-01

    Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4DAFT/FADA survey, which combines deep large field multi-band imaging and spectroscopic data, in order to detect filaments and/or structures around these clusters. Based on colour-magnitude diagrams, we have selected the galaxies likely to be in the cluster redshift range and studied their spatial distribution. We detect a number of structures and filaments around several clusters, proving that colour-magnitude diagrams are a reliable method to detect filaments around galaxy clusters. Since this method excludes blue (spiral) galaxies at the cluster redshift, we also apply the LePhare software to compute photometric redshifts from BVRIZ images to select galaxy cluster members and study their spatial distribution. We then find that, if only galaxies classified as early-type by LePhare are considered, we obtain the same distribution than with a red sequence selection, while taking into account late-type galaxies just pollutes the background level and deteriorates our detections. The photometric redshift based method therefore does not provide any additional information.

  9. Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

    Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

  10. Impact evaluation for University-Business Cooperation and Technology Transfer in higher education systems: cluster analysis

    Directory of Open Access Journals (Sweden)

    Tomoe Daniela Hamanaka Gusberti

    2017-09-01

    Full Text Available Abstract Higher education systems evolved in recent decades. Universities must not only provide society with capable professionals but also act in the market for technologies, knowledge, and ideas to promote technological development. This paper discusses the motivational performance evaluation system for technology transfer process, specifically the patterns’ evaluation of academic units considering micro-cultures and idiosyncrasies’ analysis, in the academic context of autonomy. Based on action research, the existing performance evaluation system was assessed, and multivariate cluster analysis was proposed and tested as a method to enable micro cultures’ identification and evaluation. The analysis proposed enabled a tool for reflexive discussion regarding the effectiveness of the institutional innovation system in academic units and Engineering Education, and its implications for social and technological development of industry and society enabled action proposals for improvement in the university’s technology transfer management process.

  11. Density control of dodecamanganese clusters anchored on silicon(100).

    Science.gov (United States)

    Condorelli, Guglielmo G; Motta, Alessandro; Favazza, Maria; Nativo, Paola; Fragalà, Ignazio L; Gatteschi, Dante

    2006-04-24

    A synthetic strategy to control the density of Mn12 clusters anchored on silicon(100) was investigated. Diluted monolayers suitable for Mn12 anchoring were prepared by Si-grafting mixtures of the methyl 10-undecylenoate precursor ligand with 1-decene spectator spacers. Different ratios of these mixtures were tested. The grafted surfaces were hydrolyzed to reveal the carboxylic groups available for the subsequent exchange with the [Mn12O12(OAc)16(H2O)4]4 H2O2 AcOH cluster. Modified surfaces were analyzed by attenuated total reflection (ATR)-FTIR spectroscopy, X-ray photoemission spectroscopy (XPS), and AFM imaging. Results of XPS and ATR-FTIR spectroscopy show that the surface mole ratio between grafted ester and decene is higher than in the source solution. The surface density of the Mn12 cluster is, in turn, strictly proportional to the ester mole fraction. Well-resolved and isolated clusters were observed by AFM, using a diluted ester/decene 1:1 solution.

  12. Enhancing evidence-based diabetes and chronic disease control among local health departments: a multi-phase dissemination study with a stepped-wedge cluster randomized trial component.

    Science.gov (United States)

    Parks, Renee G; Tabak, Rachel G; Allen, Peg; Baker, Elizabeth A; Stamatakis, Katherine A; Poehler, Allison R; Yan, Yan; Chin, Marshall H; Harris, Jenine K; Dobbins, Maureen; Brownson, Ross C

    2017-10-18

    The rates of diabetes and prediabetes in the USA are growing, significantly impacting the quality and length of life of those diagnosed and financially burdening society. Premature death and disability can be prevented through implementation of evidence-based programs and policies (EBPPs). Local health departments (LHDs) are uniquely positioned to implement diabetes control EBPPs because of their knowledge of, and focus on, community-level needs, contexts, and resources. There is a significant gap, however, between known diabetes control EBPPs and actual diabetes control activities conducted by LHDs. The purpose of this study is to determine how best to support the use of evidence-based public health for diabetes (and related chronic diseases) control among local-level public health practitioners. This paper describes the methods for a two-phase study with a stepped-wedge cluster randomized trial that will evaluate dissemination strategies to increase the uptake of public health knowledge and EBPPs for diabetes control among LHDs. Phase 1 includes development of measures to assess practitioner views on and organizational supports for evidence-based public health, data collection using a national online survey of LHD chronic disease practitioners, and a needs assessment of factors influencing the uptake of diabetes control EBPPs among LHDs within one state in the USA. Phase 2 involves conducting a stepped-wedge cluster randomized trial to assess effectiveness of dissemination strategies with local-level practitioners at LHDs to enhance capacity and organizational support for evidence-based diabetes prevention and control. Twelve LHDs will be selected and randomly assigned to one of the three groups that cross over from usual practice to receive the intervention (dissemination) strategies at 8-month intervals; the intervention duration for groups ranges from 8 to 24 months. Intervention (dissemination) strategies may include multi-day in-person workshops, electronic

  13. The Efficacy of a Universal School-Based Prevention Program for Eating Disorders among German Adolescents: Results from a Randomized-Controlled Trial.

    Science.gov (United States)

    Warschburger, Petra; Zitzmann, Jana

    2018-04-10

    Disordered eating is highly prevalent during adolescence and has a detrimental effect on further development. Effective prevention programs are needed to prevent unhealthy developmental trajectories. This study evaluated the efficacy of the POPS-program (POtsdam Prevention at Schools), a universal school-based eating disorder prevention program for adolescents. In a cluster-randomized design, we compared the intervention group receiving the prevention program to a waiting control group. Outcomes included indicators of disordered eating and relevant risk factors for eating disorders (body dissatisfaction, internalization of the thin ideal, perceived media pressure, perfectionism, emotional element of exercise, social comparison, and perceived teasing). Questionnaires were administered at the start of the intervention, 3 and 12 months post intervention. At baseline, 1112 adolescents aged 10 to 16 years participated (49% girls; 51% intervention group). Intention-to-treat analyses with the complete data set and per-protocol analyses as a completer analysis were performed. The intervention group showed a more favorable course compared to the control group regarding all observed risk factors for eating disorders except for perceived teasing. Effect sizes were small but comparable to other primary prevention programs. At 1-year follow-up, a small but significant effect on disordered eating was observed. Results of the per-protocol analyses were mostly confirmed by the intention-to-treat analyses. Results were promising for both genders although girls benefited more regarding disordered eating and internalization of the thin ideal. Further studies are warranted examining successful program elements and whether gender-specific programs are needed.

  14. Control of Phlebotomus argentipes (Diptera: Psychodidae sand fly in Bangladesh: A cluster randomized controlled trial.

    Directory of Open Access Journals (Sweden)

    Rajib Chowdhury

    2017-09-01

    Full Text Available A number of studies on visceral leishmaniasis (VL vector control have been conducted during the past decade, sometimes came to very different conclusion. The present study on a large sample investigated different options which are partially unexplored including: (1 indoor residual spraying (IRS with alpha cypermethrin 5WP; (2 long lasting insecticide impregnated bed-net (LLIN; (3 impregnation of local bed-nets with slow release insecticide K-O TAB 1-2-3 (KOTAB; (4 insecticide spraying in potential breeding sites outside of house using chlorpyrifos 20EC (OUT and different combinations of the above.The study was a cluster randomized controlled trial where 3089 houses from 11 villages were divided into 10 sections, each section with 6 clusters and each cluster having approximately 50 houses. Based on vector density (males plus females during baseline survey, the 60 clusters were categorized into 3 groups: (1 high, (2 medium and (3 low. Each group had 20 clusters. From these three groups, 6 clusters (about 300 households were randomly selected for each type of intervention and control arms. Vector density was measured before and 2, 4, 5, 7, 11, 14, 15, 18 and 22 months after intervention using CDC light traps. The impact of interventions was measured by using the difference-in-differences regression model.A total of 17,434 sand flies were collected at baseline and during the surveys conducted over 9 months following the baseline measurements. At baseline, the average P. argentipes density per household was 10.6 (SD = 11.5 in the control arm and 7.3 (SD = 8.46 to 11.5 (SD = 20.2 in intervention arms. The intervention results presented as the range of percent reductions of sand flies (males plus females and rate ratios in 9 measurements over 22 months. Among single type interventions, the effect of IRS with 2 rounds of spraying (applied by the research team ranged from 13% to 75% reduction of P. argentipes density compared to the control arm (rate

  15. Analyzing the factors affecting network lifetime cluster-based wireless sensor network

    International Nuclear Information System (INIS)

    Malik, A.S.; Qureshi, A.

    2010-01-01

    Cluster-based wireless sensor networks enable the efficient utilization of the limited energy resources of the deployed sensor nodes and hence prolong the node as well as network lifetime. Low Energy Adaptive Clustering Hierarchy (Leach) is one of the most promising clustering protocol proposed for wireless sensor networks. This paper provides the energy utilization and lifetime analysis for cluster-based wireless sensor networks based upon LEACH protocol. Simulation results identify some important factors that induce unbalanced energy utilization between the sensor nodes and hence affect the network lifetime in these types of networks. These results highlight the need for a standardized, adaptive and distributed clustering technique that can increase the network lifetime by further balancing the energy utilization among sensor nodes. (author)

  16. Photo-induced transformation process at gold clusters-semiconductor interface: Implications for the complexity of gold clusters-based photocatalysis

    Science.gov (United States)

    Liu, Siqi; Xu, Yi-Jun

    2016-03-01

    The recent thrust in utilizing atomically precise organic ligands protected gold clusters (Au clusters) as photosensitizer coupled with semiconductors for nano-catalysts has led to the claims of improved efficiency in photocatalysis. Nonetheless, the influence of photo-stability of organic ligands protected-Au clusters at the Au/semiconductor interface on the photocatalytic properties remains rather elusive. Taking Au clusters-TiO2 composites as a prototype, we for the first time demonstrate the photo-induced transformation of small molecular-like Au clusters to larger metallic Au nanoparticles under different illumination conditions, which leads to the diverse photocatalytic reaction mechanism. This transformation process undergoes a diffusion/aggregation mechanism accompanied with the onslaught of Au clusters by active oxygen species and holes resulting from photo-excited TiO2 and Au clusters. However, such Au clusters aggregation can be efficiently inhibited by tuning reaction conditions. This work would trigger rational structural design and fine condition control of organic ligands protected-metal clusters-semiconductor composites for diverse photocatalytic applications with long-term photo-stability.

  17. Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial.

    Science.gov (United States)

    Rapoport, Mark J; Zucchero Sarracini, Carla; Kiss, Alex; Lee, Linda; Byszewski, Anna; Seitz, Dallas P; Vrkljan, Brenda; Molnar, Frank; Herrmann, Nathan; Tang-Wai, David F; Frank, Christopher; Henry, Blair; Pimlott, Nicholas; Masellis, Mario; Naglie, Gary

    2018-05-25

    Physicians often find significant challenges in assessing automobile driving in persons with mild cognitive impairment and mild dementia and deciding when to report to transportation administrators. Care must be taken to balance the safety of patients and other road users with potential negative effects of issuing such reports. The aim of this study was to assess whether a computer-based Driving in Dementia Decision Tool (DD-DT) increased appropriate reporting of patients with mild dementia or mild cognitive impairment to transportation administrators. The study used a parallel-group cluster nonblinded randomized controlled trial design to test a multifaceted knowledge translation intervention. The intervention included a computer-based decision support system activated by the physician-user, which provides a recommendation about whether to report patients with mild dementia or mild cognitive impairment to transportation administrators, based on an algorithm derived from earlier work. The intervention also included a mailed educational package and Web-based specialized reporting forms. Specialists and family physicians with expertise in dementia or care of the elderly were stratified by sex and randomized to either use the DD-DT or a control version of the tool that required identical data input as the intervention group, but instead generated a generic reminder about the reporting legislation in Ontario, Canada. The trial ran from September 9, 2014 to January 29, 2016, and the primary outcome was the number of reports made to the transportation administrators concordant with the algorithm. A total of 69 participating physicians were randomized, and 36 of these used the DD-DT; 20 of the 35 randomized to the intervention group used DD-DT with 114 patients, and 16 of the 34 randomized to the control group used it with 103 patients. The proportion of all assessed patients reported to the transportation administrators concordant with recommendation did not differ

  18. Effects of the X:IT smoking intervention: a school-based cluster randomized trial.

    Science.gov (United States)

    Andersen, Anette; Krølner, Rikker; Bast, Lotus Sofie; Thygesen, Lau Caspar; Due, Pernille

    2015-12-01

    Uptake of smoking in adolescence is still of major public health concern. Evaluations of school-based programmes for smoking prevention show mixed results. The aim of this study was to examine the effect of X:IT, a multi-component school-based programme to prevent adolescent smoking. Data from a Danish cluster randomized trial included 4041 year-7 students (mean age: 12.5) from 51 intervention and 43 control schools. Outcome measure 'current smoking' was dichotomized into smoking daily, weekly, monthly or more seldom vs do not smoke. Analyses were adjusted for baseline covariates: sex, family socioeconomic position (SEP), best friend's smoking and parental smoking. We performed multilevel, logistic regression analyses of available cases and intention-to-treat (ITT) analyses, replacing missing outcome values by multiple imputation. At baseline, 4.7% and 6.8% of the students at the intervention and the control schools smoked, respectively. After 1 year of the intervention, the prevalence was 7.9% and 10.7%, respectively. At follow-up, 553 students (13.7%) did not answer the question on smoking. Available case analyses: crude odds ratios (OR) for smoking at intervention schools compared with control schools: 0.65 (0.48-0.88) and adjusted: 0.70 (0.47-1.04). ITT analyses: crude OR for smoking at intervention schools compared with control schools: 0.67 (0.50-0.89) and adjusted: 0.61 (0.45-0.82). Students at intervention schools had a lower risk of smoking after a year of intervention in year 7. This multi-component intervention involving educational, parental and context-related intervention components seems to be efficient in lowering or postponing smoking uptake in Danish adolescents. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

  19. REFOCUS Trial: protocol for a cluster randomised controlled trial of a pro-recovery intervention within community based mental health teams

    Directory of Open Access Journals (Sweden)

    Slade Mike

    2011-11-01

    Full Text Available Abstract Background There is a consensus about the importance of 'recovery' in mental health services, but the evidence base is limited. Methods/Design A two centre, cluster randomised controlled trial. Participants are community-based mental health teams, and service users aged 18-65 years with a primary clinical diagnosis of psychosis. In relation to the REFOCUS Manual researchintorecovery.com/refocus, which describes a 12-month, pro-recovery intervention based on the REFOCUS Model, the objectives are: (1 To establish the effectiveness of the intervention described in the REFOCUS Manual; (2 To validate the REFOCUS Model; (3 To establish and optimise trial parameters for the REFOCUS Manual; and (4 To understand the relationship between clinical outcomes and recovery outcomes. The hypothesis for the main study is that service users in the intervention arm will experience significantly greater increases in measures of personal recovery (as measured by the QPR compared to service users receiving care from control teams. The hypothesis for the secondary study is that black service users in the intervention arm will experience significantly greater increases in measures of personal recovery (as measured by the QPR and client satisfaction (as measured by the CSQ compared to Black service users receiving care from control teams. The intervention comprises treatment as usual plus two components: recovery-promoting relationships and working practices. The control condition is treatment as usual. The primary outcme is the Process of Recovery Questionnaire (QPR. Secondary outcomes are satisfaction, Goal setting - Personal Primary Outcome, hope, well-being, empowerment, and quality of life. Primary outcomes for the secondary study will be QPR and satisfaction. Cost data will be estimated, and clinical outcomes will also be reported (symptomatology, need, social disability, functioning. 29 teams (15 intervention and 14 control will be randomised. Within

  20. Cluster algebras in mathematical physics

    International Nuclear Information System (INIS)

    Francesco, Philippe Di; Gekhtman, Michael; Kuniba, Atsuo; Yamazaki, Masahito

    2014-01-01

    This special issue of Journal of Physics A: Mathematical and Theoretical contains reviews and original research articles on cluster algebras and their applications to mathematical physics. Cluster algebras were introduced by S Fomin and A Zelevinsky around 2000 as a tool for studying total positivity and dual canonical bases in Lie theory. Since then the theory has found diverse applications in mathematics and mathematical physics. Cluster algebras are axiomatically defined commutative rings equipped with a distinguished set of generators (cluster variables) subdivided into overlapping subsets (clusters) of the same cardinality subject to certain polynomial relations. A cluster algebra of rank n can be viewed as a subring of the field of rational functions in n variables. Rather than being presented, at the outset, by a complete set of generators and relations, it is constructed from the initial seed via an iterative procedure called mutation producing new seeds successively to generate the whole algebra. A seed consists of an n-tuple of rational functions called cluster variables and an exchange matrix controlling the mutation. Relations of cluster algebra type can be observed in many areas of mathematics (Plücker and Ptolemy relations, Stokes curves and wall-crossing phenomena, Feynman integrals, Somos sequences and Hirota equations to name just a few examples). The cluster variables enjoy a remarkable combinatorial pattern; in particular, they exhibit the Laurent phenomenon: they are expressed as Laurent polynomials rather than more general rational functions in terms of the cluster variables in any seed. These characteristic features are often referred to as the cluster algebra structure. In the last decade, it became apparent that cluster structures are ubiquitous in mathematical physics. Examples include supersymmetric gauge theories, Poisson geometry, integrable systems, statistical mechanics, fusion products in infinite dimensional algebras, dilogarithm

  1. Concept design and cluster control of advanced space connectable intelligent microsatellite

    Science.gov (United States)

    Wang, Xiaohui; Li, Shuang; She, Yuchen

    2017-12-01

    In this note, a new type of advanced space connectable intelligent microsatellite is presented to extend the range of potential application of microsatellite and improve the efficiency of cooperation. First, the overall concept of the micro satellite cluster is described, which is characterized by autonomously connecting with each other and being able to realize relative rotation through the external interfaces. Second, the multi-satellite autonomous assembly algorithm and control algorithm of the cluster motion are developed to make the cluster system combine into a variety of configurations in order to achieve different types of functionality. Finally, the design of the satellite cluster system is proposed, and the possible applications are discussed.

  2. Vote Stuffing Control in IPTV-based Recommender Systems

    Science.gov (United States)

    Bhatt, Rajen

    Vote stuffing is a general problem in the functioning of the content rating-based recommender systems. Currently IPTV viewers browse various contents based on the program ratings. In this paper, we propose a fuzzy clustering-based approach to remove the effects of vote stuffing and consider only the genuine ratings for the programs over multiple genres. The approach requires only one authentic rating, which is generally available from recommendation system administrators or program broadcasters. The entire process is automated using fuzzy c-means clustering. Computational experiments performed over one real-world program rating database shows that the proposed approach is very efficient for controlling vote stuffing.

  3. Policy of Innovation Clustering Based on the Public-Private Partnership in Contemporary Russia

    Directory of Open Access Journals (Sweden)

    Oleg Vasilyevich Inshakov

    2016-10-01

    Full Text Available The article presents an analysis of trends in organizational, industrial and infrastructural development of innovative territorial clusters (ITC in the Russian Federation. Parameters and characteristics of subsidies allocated from various sources for these purposes in 2013-2015 are disclosed. The study of the conducted ITC’s support policies reflects the concentration of clusters’ control levers by the regional authorities, that causes certain risks of clustering processes containment in general. The spatial and temporal unevenness of clusters’ organizational development process, the instability of their financial support and strengthening the vertical channels of influence that could give rise to corruption, stagnation and ignoring the views of cluster participants when making strategic decisions are revealed. The authors reveal the necessity of conceptual enrichment of the methods and tools of formation and implementation of ITC’s strategies aimed at achieving high feasibility and concretization of their goals and means, providing strong link between tactical measures and ongoing projects, and balancing the interests of stakeholders. It is proved in the article that the urgent task of enhancing the state of clustering policy in Russia has become a framework to improve the quality of ITC’s projects initiated and creating an adequate system for monitoring the effectiveness of their implementation. While assessing the ITC projects it is proposed to take into account the investment effectiveness, associated with the home region development strategy, sectoral strategies, profile programs of companies’ innovative development on the public-private partnership basis, regional universities development programs, as well as the similar projects implemented in other regions of Russia.

  4. School-based intervention to improve the mental health of low-income, secondary school students in Santiago, Chile (YPSA: study protocol for a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Cova Felix

    2011-02-01

    Full Text Available Abstract Background Depression is common and can have devastating effects on the life of adolescents. Psychological interventions are the first-line for treating or preventing depression among adolescents. This proposal aims to evaluate a school-based, universal psychological intervention to reduce depressive symptoms among student's aged 13-14 attending municipal state secondary schools in Santiago, Chile. Study design This is a cluster randomised controlled trial with schools as the main clusters. We compared this intervention with a control group in a study involving 22 schools, 66 classes and approximately 2,600 students. Students in the active schools attended 11 weekly and 3 booster sessions of an intervention based on cognitive-behavioural models. The control schools received their usual but enhanced counselling sessions currently included in their curriculum. Mean depression scores and indicators of levels of functioning were assessed at 3 and 12 months after the completion of the intervention in order to assess the effectiveness of the intervention. Direct and indirect costs were measured in both groups to assess the cost-effectiveness of this intervention. Discussion As far as we are aware this is the first cluster randomised controlled trial of a school intervention for depression among adolescents outside the Western world. Trial Registration ISRCTN19466209

  5. A fast density-based clustering algorithm for real-time Internet of Things stream.

    Science.gov (United States)

    Amini, Amineh; Saboohi, Hadi; Wah, Teh Ying; Herawan, Tutut

    2014-01-01

    Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.

  6. Irie Classroom Toolbox: a study protocol for a cluster-randomised trial of a universal violence prevention programme in Jamaican preschools.

    Science.gov (United States)

    Baker-Henningham, Helen; Vera-Hernández, Marcos; Alderman, Harold; Walker, Susan

    2016-05-10

    We aim to determine the effectiveness of a school-based violence prevention programme implemented in Jamaican preschools, on reducing the levels of aggression among children at school, and violence against children by teachers. This is a 2-arm, single-blind, cluster-randomised controlled trial with parallel assignment. Clusters are 76 preschools in Kingston, and all teachers and classrooms in the selected schools are included in the study. In addition, a random sample of up to 12 children in the 4-year-old classes have been selected for evaluation of child-level outcomes. The intervention involves training teachers in classroom behaviour management and in strategies to promote children's social-emotional competence. Training is delivered through five full-day workshops, monthly in-class coaching over 2 school terms, and weekly text messages. The primary outcome measures are: (1) observed levels of child aggression and (2) observed violence against children by teachers. Secondary outcomes include observations of the levels of children's prosocial behaviour and the quality of the classroom environment, teachers' reports of their mental health, teacher-reported child mental health, direct tests of children's self-regulation and child attendance. If this intervention were effective at improving the caregiving environment of young children in school, this would have significant implications for the prevention of child mental health problems, and prevention of violence against children in low and middle-income countries where services are often limited. The intervention is integrated into the school system and involves training existing staff, and thus, represents an appropriate strategy for large-scale implementation and benefits at the population level. Ethical consent for the study was given by the School of Psychology Ethics and Research Committee, Bangor University (ref: 2014-14167), and by the University of the West Indies Ethics Committee (ref: ECP 50

  7. Walking Away from Type 2 diabetes: a cluster randomized controlled trial.

    Science.gov (United States)

    Yates, T; Edwardson, C L; Henson, J; Gray, L J; Ashra, N B; Troughton, J; Khunti, K; Davies, M J

    2017-05-01

    This study aimed to investigate whether an established behavioural intervention, Walking Away from Type 2 Diabetes, is effective at promoting and sustaining increased walking activity when delivered within primary care. Cluster randomized controlled trial involving 10 general practices recruited from Leicestershire, UK, in 2009-2010. Eight hundred and eight (36% female) individuals with a high risk of Type 2 diabetes mellitus, identified through a validated risk score, were included. Participants in five practices were randomized to Walking Away from Type 2 Diabetes, a pragmatic 3-h group-based structured education programme incorporating pedometer use with annual follow-on refresher sessions. The primary outcome was accelerometer assessed ambulatory activity (steps/day) at 12 months. Longer term maintenance was assessed at 24 and 36 months. Results were analysed using generalized estimating equation models, accounting for clustering. Complete accelerometer data for the primary outcome were available for 571 (71%) participants. Increases in ambulatory activity of 411 steps/day [95% confidence interval (CI): 117, 704] and self-reported vigorous-intensity physical activity of 218 metabolic equivalent min/week (95% CI: 6, 425) at 12 months were observed in the intervention group compared with control; differences between groups were not sustained at 36 months. No differences between groups were observed for markers of cardiometabolic health. Replacing missing data with multiple imputation did not affect the results. A pragmatic low-resource group-based structured education programme with pedometer use resulted in modest increases in ambulatory activity compared with control conditions after 12 months when implemented within a primary care setting to those at high risk of Type 2 diabetes mellitus; however, the results were not maintained over 36 months. © 2016 Diabetes UK.

  8. Cluster Ensemble-Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  9. Selection bias and subject refusal in a cluster-randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Rochelle Yang

    2017-07-01

    Full Text Available Abstract Background Selection bias and non-participation bias are major methodological concerns which impact external validity. Cluster-randomized controlled trials are especially prone to selection bias as it is impractical to blind clusters to their allocation into intervention or control. This study assessed the impact of selection bias in a large cluster-randomized controlled trial. Methods The Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE study examined the impact of a remote pharmacist-led intervention in twelve medical offices. To assess eligibility, a standardized form containing patient demographics and medical information was completed for each screened patient. Eligible patients were approached by the study coordinator for recruitment. Both the study coordinator and the patient were aware of the site’s allocation prior to consent. Patients who consented or declined to participate were compared across control and intervention arms for differing characteristics. Statistical significance was determined using a two-tailed, equal variance t-test and a chi-square test with adjusted Bonferroni p-values. Results were adjusted for random cluster variation. Results There were 2749 completed screening forms returned to research staff with 461 subjects who had either consented or declined participation. Patients with poorly controlled diabetes were found to be significantly more likely to decline participation in intervention sites compared to those in control sites. A higher mean diastolic blood pressure was seen in patients with uncontrolled hypertension who declined in the control sites compared to those who declined in the intervention sites. However, these findings were no longer significant after adjustment for random variation among the sites. After this adjustment, females were now found to be significantly more likely to consent than males (odds ratio = 1.41; 95% confidence interval = 1.03, 1

  10. Topology control algorithm for wireless sensor networks based on Link forwarding

    Science.gov (United States)

    Pucuo, Cairen; Qi, Ai-qin

    2018-03-01

    The research of topology control could effectively save energy and increase the service life of network based on wireless sensor. In this paper, a arithmetic called LTHC (link transmit hybrid clustering) based on link transmit is proposed. It decreases expenditure of energy by changing the way of cluster-node’s communication. The idea is to establish a link between cluster and SINK node when the cluster is formed, and link-node must be non-cluster. Through the link, cluster sends information to SINK nodes. For the sake of achieving the uniform distribution of energy on the network, prolongate the network survival time, and improve the purpose of communication, the communication will cut down much more expenditure of energy for cluster which away from SINK node. In the two aspects of improving the traffic and network survival time, we find that the LTCH is far superior to the traditional LEACH by experiments.

  11. Student profiling on university co-curricular activities using cluster analysis

    Science.gov (United States)

    Rajenthran, Hemabegai A./P.; Shaharanee, Izwan Nizal Mohd; Jamil, Jastini Mohd.

    2017-11-01

    In higher learning institutions, the co-curricular programs are needed for the graduation besides the standard academic programs. By actively participating in co-curricular, students can attain many of soft skills and proficiencies besides learning and adopting campus environment, community and traditions. Co-curricular activities are implemented by universities mainly for the refinement of the academic achievement along with the social development. This studies aimed to analyse the academic profile of the co-curricular students among uniform units. The main objective of study is to develop a profile of student co-curricular activities in uniform units. Additionally, several variables has been selected to serve as the characteristics for student co-curricular profile. The findings of this study demonstrate the practicality of clustering technique to investigate student's profiles and allow for a better understanding of student's behavior and co-curriculum activities.

  12. Interplay between experiments and calculations for organometallic clusters and caged clusters

    International Nuclear Information System (INIS)

    Nakajima, Atsushi

    2015-01-01

    Clusters consisting of 10-1000 atoms exhibit size-dependent electronic and geometric properties. In particular, composite clusters consisting of several elements and/or components provide a promising way for a bottom-up approach for designing functional advanced materials, because the functionality of the composite clusters can be optimized not only by the cluster size but also by their compositions. In the formation of composite clusters, their geometric symmetry and dimensionality are emphasized to control the physical and chemical properties, because selective and anisotropic enhancements for optical, chemical, and magnetic properties can be expected. Organometallic clusters and caged clusters are demonstrated as a representative example of designing the functionality of the composite clusters. Organometallic vanadium-benzene forms a one dimensional sandwich structure showing ferromagnetic behaviors and anomalously large HOMO-LUMO gap differences of two spin orbitals, which can be regarded as spin-filter components for cluster-based spintronic devices. Caged clusters of aluminum (Al) are well stabilized both geometrically and electronically at Al 12 X, behaving as a “superatom”

  13. XML documents cluster research based on frequent subpatterns

    Science.gov (United States)

    Ding, Tienan; Li, Wei; Li, Xiongfei

    2015-12-01

    XML data is widely used in the information exchange field of Internet, and XML document data clustering is the hot research topic. In the XML document clustering process, measure differences between two XML documents is time costly, and impact the efficiency of XML document clustering. This paper proposed an XML documents clustering method based on frequent patterns of XML document dataset, first proposed a coding tree structure for encoding the XML document, and translate frequent pattern mining from XML documents into frequent pattern mining from string. Further, using the cosine similarity calculation method and cohesive hierarchical clustering method for XML document dataset by frequent patterns. Because of frequent patterns are subsets of the original XML document data, so the time consumption of XML document similarity measure is reduced. The experiment runs on synthetic dataset and the real datasets, the experimental result shows that our method is efficient.

  14. Local Community Detection Algorithm Based on Minimal Cluster

    Directory of Open Access Journals (Sweden)

    Yong Zhou

    2016-01-01

    Full Text Available In order to discover the structure of local community more effectively, this paper puts forward a new local community detection algorithm based on minimal cluster. Most of the local community detection algorithms begin from one node. The agglomeration ability of a single node must be less than multiple nodes, so the beginning of the community extension of the algorithm in this paper is no longer from the initial node only but from a node cluster containing this initial node and nodes in the cluster are relatively densely connected with each other. The algorithm mainly includes two phases. First it detects the minimal cluster and then finds the local community extended from the minimal cluster. Experimental results show that the quality of the local community detected by our algorithm is much better than other algorithms no matter in real networks or in simulated networks.

  15. Cluster Synchronization of Diffusively Coupled Nonlinear Systems: A Contraction-Based Approach

    Science.gov (United States)

    Aminzare, Zahra; Dey, Biswadip; Davison, Elizabeth N.; Leonard, Naomi Ehrich

    2018-04-01

    Finding the conditions that foster synchronization in networked nonlinear systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in nonlinear systems with linear coupling, such as has been used to model neuronal networks, are in general not strict enough to accurately determine the system behavior. We leverage contraction theory to derive new sufficient conditions for cluster synchronization in terms of the network structure, for a network where the intrinsic nonlinear dynamics of each node may differ. Our result requires that network connections satisfy a cluster-input-equivalence condition, and we explore the influence of this requirement on network dynamics. For application to networks of nodes with FitzHugh-Nagumo dynamics, we show that our new sufficient condition is tighter than those found in previous analyses that used smooth or nonsmooth Lyapunov functions. Improving the analytical conditions for when cluster synchronization will occur based on network configuration is a significant step toward facilitating understanding and control of complex networked systems.

  16. Fault-tolerant measurement-based quantum computing with continuous-variable cluster states.

    Science.gov (United States)

    Menicucci, Nicolas C

    2014-03-28

    A long-standing open question about Gaussian continuous-variable cluster states is whether they enable fault-tolerant measurement-based quantum computation. The answer is yes. Initial squeezing in the cluster above a threshold value of 20.5 dB ensures that errors from finite squeezing acting on encoded qubits are below the fault-tolerance threshold of known qubit-based error-correcting codes. By concatenating with one of these codes and using ancilla-based error correction, fault-tolerant measurement-based quantum computation of theoretically indefinite length is possible with finitely squeezed cluster states.

  17. Community-based intermittent mass testing and treatment for malaria in an area of high transmission intensity, western Kenya: study design and methodology for a cluster randomized controlled trial.

    Science.gov (United States)

    Samuels, Aaron M; Awino, Nobert; Odongo, Wycliffe; Abong'o, Benard; Gimnig, John; Otieno, Kephas; Shi, Ya Ping; Were, Vincent; Allen, Denise Roth; Were, Florence; Sang, Tony; Obor, David; Williamson, John; Hamel, Mary J; Patrick Kachur, S; Slutsker, Laurence; Lindblade, Kim A; Kariuki, Simon; Desai, Meghna

    2017-06-07

    Most human Plasmodium infections in western Kenya are asymptomatic and are believed to contribute importantly to malaria transmission. Elimination of asymptomatic infections requires active treatment approaches, such as mass testing and treatment (MTaT) or mass drug administration (MDA), as infected persons do not seek care for their infection. Evaluations of community-based approaches that are designed to reduce malaria transmission require careful attention to study design to ensure that important effects can be measured accurately. This manuscript describes the study design and methodology of a cluster-randomized controlled trial to evaluate a MTaT approach for malaria transmission reduction in an area of high malaria transmission. Ten health facilities in western Kenya were purposively selected for inclusion. The communities within 3 km of each health facility were divided into three clusters of approximately equal population size. Two clusters around each health facility were randomly assigned to the control arm, and one to the intervention arm. Three times per year for 2 years, after the long and short rains, and again before the long rains, teams of community health volunteers visited every household within the intervention arm, tested all consenting individuals with malaria rapid diagnostic tests, and treated all positive individuals with an effective anti-malarial. The effect of mass testing and treatment on malaria transmission was measured through population-based longitudinal cohorts, outpatient visits for clinical malaria, periodic population-based cross-sectional surveys, and entomological indices.

  18. Probing dark energy via galaxy cluster outskirts

    Science.gov (United States)

    Morandi, Andrea; Sun, Ming

    2016-04-01

    We present a Bayesian approach to combine Planck data and the X-ray physical properties of the intracluster medium in the virialization region of a sample of 320 galaxy clusters (0.056 definition of cluster boundary radius is more tenable, namely based on a fixed overdensity with respect to the critical density of the Universe. This novel cosmological test has the capacity to provide a generational leap forward in our understanding of the equation of state of dark energy.

  19. Getting better at chronic care in remote communities: study protocol for a pragmatic cluster randomised controlled of community based management

    Directory of Open Access Journals (Sweden)

    Schmidt Barbara

    2012-11-01

    Full Text Available Abstract Background Prevalence and incidence of diabetes and other common comorbid conditions (hypertension, coronary heart disease, renal disease and chronic lung disease are extremely high among Indigenous Australians. Recent measures to improve quality of preventive care in Indigenous community settings, while apparently successful at increasing screening and routine check-up rates, have shown only modest or little improvements in appropriate care such as the introduction of insulin and other scaled-up drug regimens in line with evidence-based guidelines, together with support for risk factor reduction. A new strategy is required to ensure high quality integrated family-centred care is available locally, with continuity and cultural safety, by community-based care coordinators with appropriate system supports. Methods/design The trial design is open parallel cluster randomised controlled trial. The objective of this pragmatic trial is to test the effectiveness of a model of health service delivery that facilitates integrated community-based, intensive chronic condition management, compared with usual care, in rural and remote Indigenous primary health care services in north Queensland. Participants are Indigenous adults (aged 18–65 years with poorly controlled diabetes (HbA1c>=8.5 and at least one other chronic condition. The intervention is to employ an Indigenous Health Worker to case manage the care of a maximum caseload of 30 participants. The Indigenous Health Workers receive intensive clinical training initially, and throughout the study, to ensure they are competent to coordinate care for people with chronic conditions. The Indigenous Health Workers, supported by the local primary health care (PHC team and an Indigenous Clinical Support Team, will manage care, including coordinating access to multidisciplinary team care based on best practice standards. Allocation by cluster to the intervention and control groups is by simple

  20. Carbon based nanostructures: diamond clusters structured with nanotubes

    Directory of Open Access Journals (Sweden)

    O.A. Shenderova

    2003-01-01

    Full Text Available Feasibility of designing composites from carbon nanotubes and nanodiamond clusters is discussed based on atomistic simulations. Depending on nanotube size and morphology, some types of open nanotubes can be chemically connected with different facets of diamond clusters. The geometrical relation between different types of nanotubes and different diamond facets for construction of mechanically stable composites with all bonds saturated is summarized. Potential applications of the suggested nanostructures are briefly discussed based on the calculations of their electronic properties using environment dependent self-consistent tight-binding approach.

  1. Communication Base Station Log Analysis Based on Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Zhang Shao-Hua

    2017-01-01

    Full Text Available Communication base stations generate massive data every day, these base station logs play an important value in mining of the business circles. This paper use data mining technology and hierarchical clustering algorithm to group the scope of business circle for the base station by recording the data of these base stations.Through analyzing the data of different business circle based on feature extraction and comparing different business circle category characteristics, which can choose a suitable area for operators of commercial marketing.

  2. A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream

    Science.gov (United States)

    Ying Wah, Teh

    2014-01-01

    Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets. PMID:25110753

  3. Effect of workplace- versus home-based physical exercise on pain in healthcare workers: study protocol for a single blinded cluster randomized controlled trial

    Science.gov (United States)

    2014-01-01

    Background The prevalence and consequences of musculoskeletal pain is considerable among healthcare workers, allegedly due to high physical work demands of healthcare work. Previous investigations have shown promising results of physical exercise for relieving pain among different occupational groups, but the question remains whether such physical exercise should be performed at the workplace or conducted as home-based exercise. Performing physical exercise at the workplace together with colleagues may be more motivating for some employees and thus increase adherence. On the other hand, physical exercise performed during working hours at the workplace may be costly for the employers in terms of time spend. Thus, it seems relevant to compare the efficacy of workplace- versus home-based training on musculoskeletal pain. This study is intended to investigate the effect of workplace-based versus home-based physical exercise on musculoskeletal pain among healthcare workers. Methods/Design This study was designed as a cluster randomized controlled trial performed at 3 hospitals in Copenhagen, Denmark. Clusters are hospital departments and hospital units. Cluster randomization was chosen to increase adherence and avoid contamination between interventions. Two hundred healthcare workers from 18 departments located at three different hospitals is allocated to 10 weeks of 1) workplace based physical exercise performed during working hours (using kettlebells, elastic bands and exercise balls) for 5 × 10 minutes per week and up to 5 group-based coaching sessions, or 2) home based physical exercise performed during leisure time (using elastic bands and body weight exercises) for 5 × 10 minutes per week. Both intervention groups will also receive ergonomic instructions on patient handling and use of lifting aides etc. Inclusion criteria are female healthcare workers working at a hospital. Average pain intensity (VAS scale 0-10) of the back, neck and shoulder

  4. Variable selection in multivariate calibration based on clustering of variable concept.

    Science.gov (United States)

    Farrokhnia, Maryam; Karimi, Sadegh

    2016-01-01

    Recently we have proposed a new variable selection algorithm, based on clustering of variable concept (CLoVA) in classification problem. With the same idea, this new concept has been applied to a regression problem and then the obtained results have been compared with conventional variable selection strategies for PLS. The basic idea behind the clustering of variable is that, the instrument channels are clustered into different clusters via clustering algorithms. Then, the spectral data of each cluster are subjected to PLS regression. Different real data sets (Cargill corn, Biscuit dough, ACE QSAR, Soy, and Tablet) have been used to evaluate the influence of the clustering of variables on the prediction performances of PLS. Almost in the all cases, the statistical parameter especially in prediction error shows the superiority of CLoVA-PLS respect to other variable selection strategies. Finally the synergy clustering of variable (sCLoVA-PLS), which is used the combination of cluster, has been proposed as an efficient and modification of CLoVA algorithm. The obtained statistical parameter indicates that variable clustering can split useful part from redundant ones, and then based on informative cluster; stable model can be reached. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Minimizing Broadcast Expenses in Clustered Ad-hoc Networks

    Directory of Open Access Journals (Sweden)

    S. Zeeshan Hussain

    2018-01-01

    Full Text Available One way to minimize the broadcast expenses of routing protocols is to cluster the network. In clustered ad-hoc networks, all resources can be managed easily by resolving scalability issues. However, blind query broadcast is a major issue that leads to the broadcast storm problem in clustered ad-hoc networks. This query broadcast is done to carry out the route-search task that leads to the unnecessary propagation of route-query even after route has been found. Hence, this query propagation poses the problem of congestion in the network. In particular this motivates us to propose a query-control technique in such networks which works based on broadcast repealing. A huge amount of work has been devoted to propose the query control broadcasting techniques. However, such techniques used in traditional broadcasting mechanisms need to be properly extended for use in the cluster based routing architecture. In this paper, query-control technique is proposed for cluster based routing technique to reduce the broadcast expenses. Finally, we report some experiments which compare the proposed technique to other commonly used techniques including standard one-class AODV that follows TTL-sequence based broadcasting technique.

  6. Price Formation Based on Particle-Cluster Aggregation

    Science.gov (United States)

    Wang, Shijun; Zhang, Changshui

    In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

  7. Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

    Directory of Open Access Journals (Sweden)

    Yimei Wang

    2018-04-01

    Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

  8. Spanning Tree Based Attribute Clustering

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Jorge, Cordero Hernandez

    2009-01-01

    Attribute clustering has been previously employed to detect statistical dependence between subsets of variables. We propose a novel attribute clustering algorithm motivated by research of complex networks, called the Star Discovery algorithm. The algorithm partitions and indirectly discards...... inconsistent edges from a maximum spanning tree by starting appropriate initial modes, therefore generating stable clusters. It discovers sound clusters through simple graph operations and achieves significant computational savings. We compare the Star Discovery algorithm against earlier attribute clustering...

  9. Net-zero Building Cluster Simulations and On-line Energy Forecasting for Adaptive and Real-Time Control and Decisions

    Science.gov (United States)

    Li, Xiwang

    this thesis can be used for building cluster energy forecasting model development and model based control and operation optimization. The thesis concludes with a summary of the key outcomes of this research, as well as a list of recommendations for future work.

  10. Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm.

    Science.gov (United States)

    Kamali, Tahereh; Stashuk, Daniel

    2016-10-01

    Robust and accurate segmentation of brain white matter (WM) fiber bundles assists in diagnosing and assessing progression or remission of neuropsychiatric diseases such as schizophrenia, autism and depression. Supervised segmentation methods are infeasible in most applications since generating gold standards is too costly. Hence, there is a growing interest in designing unsupervised methods. However, most conventional unsupervised methods require the number of clusters be known in advance which is not possible in most applications. The purpose of this study is to design an unsupervised segmentation algorithm for brain white matter fiber bundles which can automatically segment fiber bundles using intrinsic diffusion tensor imaging data information without considering any prior information or assumption about data distributions. Here, a new density based clustering algorithm called neighborhood distance entropy consistency (NDEC), is proposed which discovers natural clusters within data by simultaneously utilizing both local and global density information. The performance of NDEC is compared with other state of the art clustering algorithms including chameleon, spectral clustering, DBSCAN and k-means using Johns Hopkins University publicly available diffusion tensor imaging data. The performance of NDEC and other employed clustering algorithms were evaluated using dice ratio as an external evaluation criteria and density based clustering validation (DBCV) index as an internal evaluation metric. Across all employed clustering algorithms, NDEC obtained the highest average dice ratio (0.94) and DBCV value (0.71). NDEC can find clusters with arbitrary shapes and densities and consequently can be used for WM fiber bundle segmentation where there is no distinct boundary between various bundles. NDEC may also be used as an effective tool in other pattern recognition and medical diagnostic systems in which discovering natural clusters within data is a necessity. Copyright

  11. Chandra Finds Ghosts Of Eruption In Galaxy Cluster

    Science.gov (United States)

    2002-01-01

    gas. "Ghost cavities may be the vessels that transport magnetic fields generated in a disk surrounding a giant black hole to the cluster gas that is spread over a region a billion times larger," said McNamara. If dozens of these cavities were created over the life of the cluster, they could explain the surprisingly strong magnetic field of the multimillion-degree gas that pervades the cluster. Galaxy clusters are the largest known gravitationally bound structures in the universe. Hundreds of galaxies swarm in giant reservoirs of multimillion-degree gas that radiates most of its energy in X-rays. Over the course of billions of years some of the gas should cool and sink toward a galaxy in the center of the cluster where it could trigger an outburst in the vicinity of the central massive black hole. Chandra observed Abell 2597 on July 28, 2000,for 40,000 seconds with the Advanced CCD Imaging Spectrometer (ACIS) instrument. Pennsylvania State University, University Park, and MIT developed the instrument for NASA. In addition to a group of astronomers from the Space Telescope Science Institute, Baltimore, and the University of Virginia, Charlottesville, the team included: Paul Nulsen, University of Wollagong, Australia; Larry David, Harvard-Smithsonian Center for Astrophysics, Cambridge, Mass.; Chris Carilli, National Radio Astronomy Observatory, Socorro, N.M.; and Craig Sarazin, University of Virginia. NASA's Marshall Space Flight Center in Huntsville, Ala., manages the Chandra program, and TRW, Inc., Redondo Beach, Calif., is the prime contractor for the spacecraft. The Smithsonian's Chandra X-ray Center controls science and flight operations from Cambridge, Mass.

  12. Short message service (SMS)-based intervention targeting alcohol consumption among university students: study protocol of a randomized controlled trial.

    Science.gov (United States)

    Thomas, Kristin; Bendtsen, Marcus; Linderoth, Catharina; Karlsson, Nadine; Bendtsen, Preben; Müssener, Ulrika

    2017-04-04

    Despite significant health risks, heavy drinking of alcohol among university students is a widespread problem; excessive drinking is part of the social norm. A growing number of studies indicate that short message service (SMS)-based interventions are cost-effective, accessible, require limited effort by users, and can enable continuous, real-time, brief support in real-world settings. Although there is emerging evidence for the effect of SMS-based interventions in reducing alcohol consumption, more research is needed. This study aims to test the effectiveness of a newly developed SMS-based intervention targeting excessive alcohol consumption among university and college students in Sweden. The study is a two-arm randomized controlled trial with an intervention (SMS programme) and a control (treatment as usual) group. Outcome measures will be investigated at baseline and at 3-month follow up. The primary outcome is total weekly alcohol consumption. Secondary outcomes are frequency of heavy episodic drinking, highest estimated blood alcohol concentration and number of negative consequences due to excessive drinking. This study contributes knowledge on the effect of automatized SMS support to reduce excessive drinking among students compared with existing support such as Student Health Centres. ISRCTN.com, ISRCTN95054707 . Registered on 31 August 2016.

  13. Fuzzy clustering-based segmented attenuation correction in whole-body PET

    CERN Document Server

    Zaidi, H; Boudraa, A; Slosman, DO

    2001-01-01

    Segmented-based attenuation correction is now a widely accepted technique to reduce noise contribution of measured attenuation correction. In this paper, we present a new method for segmenting transmission images in positron emission tomography. This reduces the noise on the correction maps while still correcting for differing attenuation coefficients of specific tissues. Based on the Fuzzy C-Means (FCM) algorithm, the method segments the PET transmission images into a given number of clusters to extract specific areas of differing attenuation such as air, the lungs and soft tissue, preceded by a median filtering procedure. The reconstructed transmission image voxels are therefore segmented into populations of uniform attenuation based on the human anatomy. The clustering procedure starts with an over-specified number of clusters followed by a merging process to group clusters with similar properties and remove some undesired substructures using anatomical knowledge. The method is unsupervised, adaptive and a...

  14. Massive Star Clusters in Ongoing Galaxy Interactions: Clues to Cluster Formation

    Science.gov (United States)

    Keel, William C.; Borne, Kirk D.

    2003-09-01

    We present HST WFPC2 observations, supplemented by ground-based Hα data, of the star-cluster populations in two pairs of interacting galaxies selected for being in very different kinds of encounters seen at different stages. Dynamical information and n-body simulations provide the details of encounter geometry, mass ratio, and timing. In NGC 5752/4 we are seeing a weak encounter, well past closest approach, after about 2.5×108 yr. The large spiral NGC 5754 has a normal population of disk clusters, while the fainter companion NGC 5752 exhibits a rich population of luminous clusters with a flatter luminosity function. The strong, ongoing encounter in NGC 6621/2, seen about 1.0×108 yr past closest approach between roughly equal-mass galaxies, has produced an extensive population of luminous clusters, particularly young and luminous in a small region between the two nuclei. This region is dynamically interesting, with such a strong perturbation in the velocity field that the rotation curve reverses sign. From these results, in comparison with other strongly interacting systems discussed in the literature, cluster formation requires a threshold level of perturbation, with stage of the interaction a less important factor. The location of the most active star formation in NGC 6621/2 draws attention to a possible role for the Toomre stability threshold in shaping star formation in interacting galaxies. The rich cluster populations in NGC 5752 and NGC 6621 show that direct contact between gas-rich galaxy disks is not a requirement to form luminous clusters and that they can be triggered by processes happening within a single galaxy disk (albeit triggered by external perturbations). Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

  15. Cluster ion beam facilities

    International Nuclear Information System (INIS)

    Popok, V.N.; Prasalovich, S.V.; Odzhaev, V.B.; Campbell, E.E.B.

    2001-01-01

    A brief state-of-the-art review in the field of cluster-surface interactions is presented. Ionised cluster beams could become a powerful and versatile tool for the modification and processing of surfaces as an alternative to ion implantation and ion assisted deposition. The main effects of cluster-surface collisions and possible applications of cluster ion beams are discussed. The outlooks of the Cluster Implantation and Deposition Apparatus (CIDA) being developed in Guteborg University are shown

  16. ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    T. SHANKAR

    2014-04-01

    Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.

  17. KM-FCM: A fuzzy clustering optimization algorithm based on Mahalanobis distance

    Directory of Open Access Journals (Sweden)

    Zhiwen ZU

    2018-04-01

    Full Text Available The traditional fuzzy clustering algorithm uses Euclidean distance as the similarity criterion, which is disadvantageous to the multidimensional data processing. In order to solve this situation, Mahalanobis distance is used instead of the traditional Euclidean distance, and the optimization of fuzzy clustering algorithm based on Mahalanobis distance is studied to enhance the clustering effect and ability. With making the initialization means by Heuristic search algorithm combined with k-means algorithm, and in terms of the validity function which could automatically adjust the optimal clustering number, an optimization algorithm KM-FCM is proposed. The new algorithm is compared with FCM algorithm, FCM-M algorithm and M-FCM algorithm in three standard data sets. The experimental results show that the KM-FCM algorithm is effective. It has higher clustering accuracy than FCM, FCM-M and M-FCM, recognizing high-dimensional data clustering well. It has global optimization effect, and the clustering number has no need for setting in advance. The new algorithm provides a reference for the optimization of fuzzy clustering algorithm based on Mahalanobis distance.

  18. Seminal Quality Prediction Using Clustering-Based Decision Forests

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-08-01

    Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

  19. Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

    Science.gov (United States)

    Hendrix, Val; Benjamin, Doug; Yao, Yushu

    2012-12-01

    Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

  20. A similarity based agglomerative clustering algorithm in networks

    Science.gov (United States)

    Liu, Zhiyuan; Wang, Xiujuan; Ma, Yinghong

    2018-04-01

    The detection of clusters is benefit for understanding the organizations and functions of networks. Clusters, or communities, are usually groups of nodes densely interconnected but sparsely linked with any other clusters. To identify communities, an efficient and effective community agglomerative algorithm based on node similarity is proposed. The proposed method initially calculates similarities between each pair of nodes, and form pre-partitions according to the principle that each node is in the same community as its most similar neighbor. After that, check each partition whether it satisfies community criterion. For the pre-partitions who do not satisfy, incorporate them with others that having the biggest attraction until there are no changes. To measure the attraction ability of a partition, we propose an attraction index that based on the linked node's importance in networks. Therefore, our proposed method can better exploit the nodes' properties and network's structure. To test the performance of our algorithm, both synthetic and empirical networks ranging in different scales are tested. Simulation results show that the proposed algorithm can obtain superior clustering results compared with six other widely used community detection algorithms.

  1. Finite-Time and Fixed-Time Cluster Synchronization With or Without Pinning Control.

    Science.gov (United States)

    Liu, Xiwei; Chen, Tianping

    2018-01-01

    In this paper, the finite-time and fixed-time cluster synchronization problem for complex networks with or without pinning control are discussed. Finite-time (or fixed-time) synchronization has been a hot topic in recent years, which means that the network can achieve synchronization in finite-time, and the settling time depends on the initial values for finite-time synchronization (or the settling time is bounded by a constant for any initial values for fixed-time synchronization). To realize the finite-time and fixed-time cluster synchronization, some simple distributed protocols with or without pinning control are designed and the effectiveness is rigorously proved. Several sufficient criteria are also obtained to clarify the effects of coupling terms for finite-time and fixed-time cluster synchronization. Especially, when the cluster number is one, the cluster synchronization becomes the complete synchronization problem; when the network has only one node, the coupling term between nodes will disappear, and the synchronization problem becomes the simplest master-slave case, which also includes the stability problem for nonlinear systems like neural networks. All these cases are also discussed. Finally, numerical simulations are presented to demonstrate the correctness of obtained theoretical results.

  2. Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

    Directory of Open Access Journals (Sweden)

    Olszewski Kellen L

    2007-07-01

    Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

  3. Universal quantum computation with temporal-mode bilayer square lattices

    Science.gov (United States)

    Alexander, Rafael N.; Yokoyama, Shota; Furusawa, Akira; Menicucci, Nicolas C.

    2018-03-01

    We propose an experimental design for universal continuous-variable quantum computation that incorporates recent innovations in linear-optics-based continuous-variable cluster state generation and cubic-phase gate teleportation. The first ingredient is a protocol for generating the bilayer-square-lattice cluster state (a universal resource state) with temporal modes of light. With this state, measurement-based implementation of Gaussian unitary gates requires only homodyne detection. Second, we describe a measurement device that implements an adaptive cubic-phase gate, up to a random phase-space displacement. It requires a two-step sequence of homodyne measurements and consumes a (non-Gaussian) cubic-phase state.

  4. Efficacy of community-based physiotherapy networks for patients with Parkinson's disease: a cluster-randomised trial.

    Science.gov (United States)

    Munneke, Marten; Nijkrake, Maarten J; Keus, Samyra Hj; Kwakkel, Gert; Berendse, Henk W; Roos, Raymund Ac; Borm, George F; Adang, Eddy M; Overeem, Sebastiaan; Bloem, Bastiaan R

    2010-01-01

    Many patients with Parkinson's disease are treated with physiotherapy. We have developed a community-based professional network (ParkinsonNet) that involves training of a selected number of expert physiotherapists to work according to evidence-based recommendations, and structured referrals to these trained physiotherapists to increase the numbers of patients they treat. We aimed to assess the efficacy of this approach for improving health-care outcomes. Between February, 2005, and August, 2007, we did a cluster-randomised trial with 16 clusters (defined as community hospitals and their catchment area). Clusters were randomly allocated by use of a variance minimisation algorithm to ParkinsonNet care (n=8) or usual care (n=8). Patients were assessed at baseline and at 8, 16, and 24 weeks of follow-up. The primary outcome was a patient preference disability score, the patient-specific index score, at 16 weeks. Health secondary outcomes were functional mobility, mobility-related quality of life, and total societal costs over 24 weeks. Analysis was by intention to treat. This trial is registered, number NCT00330694. We included 699 patients. Baseline characteristics of the patients were comparable between the ParkinsonNet clusters (n=358) and usual-care clusters (n=341). The primary endpoint was similar for patients within the ParkinsonNet clusters (mean 47.7, SD 21.9) and control clusters (48.3, 22.4). Health secondary endpoints were also similar for patients in both study groups. Total costs over 24 weeks were lower in ParkinsonNet clusters compared with usual-care clusters (difference euro727; 95% CI 56-1399). Implementation of ParkinsonNet networks did not change health outcomes for patients living in ParkinsonNet clusters. However, health-care costs were reduced in ParkinsonNet clusters compared with usual-care clusters. ZonMw; Netherlands Organisation for Scientific Research; Dutch Parkinson's Disease Society; National Parkinson Foundation; Stichting Robuust

  5. Cluster Approach to Network Interaction in Pedagogical University

    Science.gov (United States)

    Chekaleva, Nadezhda V.; Makarova, Natalia S.; Drobotenko, Yulia B.

    2016-01-01

    The study presented in the article is devoted to the analysis of theory and practice of network interaction within the framework of education clusters. Education clusters are considered to be a novel form of network interaction in pedagogical education in Russia. The aim of the article is to show the advantages and disadvantages of the cluster…

  6. Close Binaries in the Orion Nebula Cluster: On the Universality of Stellar Multiplicity and the Origin of Field Stars

    Science.gov (United States)

    Duchene, Gaspard; Lacour, Sylvestre; Moraux, Estelle; Bouvier, Jerome; Goodwin, Simon

    2018-01-01

    While stellar multiplicity is an ubiquitous outcome of star formation, there is a clear dichotomy between the multiplicity properties of young (~1 Myr-old) stellar clusters, like the ONC, which host a mostly field-like population of visual binaries, and those of equally young sparse populations, like the Taurus-Auriga region, which host twice as many stellar companions. Two distinct scenarios can account for this observation: one in which different star-forming regions form different number of stars, and one in which multiplicity properties are universal at birth but where internal cluster dynamics destroy many wide binaries. To solve this ambiguity, one must probe binaries that are sufficiently close so as not to be destroyed through interactions with other cluster members. To this end, we have conducted a survey for 10-100 au binaries in the ONC using the aperture masking technique with the VLT adaptive optics system. Among our sample of the 42 ONC members, we discovered 13 companions in this range of projected separations. This is consistent with the companion frequency observed in the Taurus population and twice as high as that observed among field stars. This survey thus strongly supports the idea that stellar multiplicity is characterized by near-universal initial properties that can later be dynamically altered. On the other hand, this exacerbates the question of the origin of field stars, since only clusters much denser than the ONC can effectively destroyed binaries closer than 100 au.

  7. A Clustering-Based Automatic Transfer Function Design for Volume Visualization

    Directory of Open Access Journals (Sweden)

    Tianjin Zhang

    2016-01-01

    Full Text Available The two-dimensional transfer functions (TFs designed based on intensity-gradient magnitude (IGM histogram are effective tools for the visualization and exploration of 3D volume data. However, traditional design methods usually depend on multiple times of trial-and-error. We propose a novel method for the automatic generation of transfer functions by performing the affinity propagation (AP clustering algorithm on the IGM histogram. Compared with previous clustering algorithms that were employed in volume visualization, the AP clustering algorithm has much faster convergence speed and can achieve more accurate clustering results. In order to obtain meaningful clustering results, we introduce two similarity measurements: IGM similarity and spatial similarity. These two similarity measurements can effectively bring the voxels of the same tissue together and differentiate the voxels of different tissues so that the generated TFs can assign different optical properties to different tissues. Before performing the clustering algorithm on the IGM histogram, we propose to remove noisy voxels based on the spatial information of voxels. Our method does not require users to input the number of clusters, and the classification and visualization process is automatic and efficient. Experiments on various datasets demonstrate the effectiveness of the proposed method.

  8. DCE: A Distributed Energy-Efficient Clustering Protocol for Wireless Sensor Network Based on Double-Phase Cluster-Head Election.

    Science.gov (United States)

    Han, Ruisong; Yang, Wei; Wang, Yipeng; You, Kaiming

    2017-05-01

    Clustering is an effective technique used to reduce energy consumption and extend the lifetime of wireless sensor network (WSN). The characteristic of energy heterogeneity of WSNs should be considered when designing clustering protocols. We propose and evaluate a novel distributed energy-efficient clustering protocol called DCE for heterogeneous wireless sensor networks, based on a Double-phase Cluster-head Election scheme. In DCE, the procedure of cluster head election is divided into two phases. In the first phase, tentative cluster heads are elected with the probabilities which are decided by the relative levels of initial and residual energy. Then, in the second phase, the tentative cluster heads are replaced by their cluster members to form the final set of cluster heads if any member in their cluster has more residual energy. Employing two phases for cluster-head election ensures that the nodes with more energy have a higher chance to be cluster heads. Energy consumption is well-distributed in the proposed protocol, and the simulation results show that DCE achieves longer stability periods than other typical clustering protocols in heterogeneous scenarios.

  9. Semantic based cluster content discovery in description first clustering algorithm

    International Nuclear Information System (INIS)

    Khan, M.W.; Asif, H.M.S.

    2017-01-01

    In the field of data analytics grouping of like documents in textual data is a serious problem. A lot of work has been done in this field and many algorithms have purposed. One of them is a category of algorithms which firstly group the documents on the basis of similarity and then assign the meaningful labels to those groups. Description first clustering algorithm belong to the category in which the meaningful description is deduced first and then relevant documents are assigned to that description. LINGO (Label Induction Grouping Algorithm) is the algorithm of description first clustering category which is used for the automatic grouping of documents obtained from search results. It uses LSI (Latent Semantic Indexing); an IR (Information Retrieval) technique for induction of meaningful labels for clusters and VSM (Vector Space Model) for cluster content discovery. In this paper we present the LINGO while it is using LSI during cluster label induction and cluster content discovery phase. Finally, we compare results obtained from the said algorithm while it uses VSM and Latent semantic analysis during cluster content discovery phase. (author)

  10. Simulation-based marginal likelihood for cluster strong lensing cosmology

    Science.gov (United States)

    Killedar, M.; Borgani, S.; Fabjan, D.; Dolag, K.; Granato, G.; Meneghetti, M.; Planelles, S.; Ragone-Figueroa, C.

    2018-01-01

    Comparisons between observed and predicted strong lensing properties of galaxy clusters have been routinely used to claim either tension or consistency with Λ cold dark matter cosmology. However, standard approaches to such cosmological tests are unable to quantify the preference for one cosmology over another. We advocate approximating the relevant Bayes factor using a marginal likelihood that is based on the following summary statistic: the posterior probability distribution function for the parameters of the scaling relation between Einstein radii and cluster mass, α and β. We demonstrate, for the first time, a method of estimating the marginal likelihood using the X-ray selected z > 0.5 Massive Cluster Survey clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We investigate the uncertainty in this estimate and consequential ability to compare competing cosmologies, which arises from incomplete descriptions of baryonic processes, discrepancies in cluster selection criteria, redshift distribution and dynamical state. The relation between triaxial cluster masses at various overdensities provides a promising alternative to the strong lensing test.

  11. Evolution of galaxy cluster scaling and structural properties from XMM observations: probing the physics of structure formation

    International Nuclear Information System (INIS)

    Anokhin, Sergey

    2008-01-01

    Clusters of galaxies are the largest gravitationally bound objects in the Universe. It is possible to study the hierarchical structure formation based on these youngest objects in the Universe. In order to complete the results found with hot clusters, we choose the cold distant galaxy clusters selected from The Southern SHARC catalogue. In the same time, we studied archived galaxy clusters to test the theory and treatment analysis. To study these weak cluster of galaxies, we optimized our treatment analysis: in particular, searching for the best background subtraction and modeling it for our surface brightness profile and spectra. Our results are in a good agreement with Scaling Relation obtained from hot galaxy clusters. (author) [fr

  12. Cluster synchronization of community network with distributed time delays via impulsive control

    International Nuclear Information System (INIS)

    Leng Hui; Wu Zhao-Yan

    2016-01-01

    Cluster synchronization is an important dynamical behavior in community networks and deserves further investigations. A community network with distributed time delays is investigated in this paper. For achieving cluster synchronization, an impulsive control scheme is introduced to design proper controllers and an adaptive strategy is adopted to make the impulsive controllers unified for different networks. Through taking advantage of the linear matrix inequality technique and constructing Lyapunov functions, some synchronization criteria with respect to the impulsive gains, instants, and system parameters without adaptive strategy are obtained and generalized to the adaptive case. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results. (paper)

  13. Review on Control of DC Microgrids and Multiple Microgrid Clusters

    DEFF Research Database (Denmark)

    Meng, Lexuan; Shafiee, Qobad; Ferrari-Trecate, Giancarlo

    2017-01-01

    This paper performs an extensive review on control schemes and architectures applied to DC microgrids. It covers multi-layer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active damping aspects as well as nonlinear control algorithms....... Islanding detection, protection and microgrid clusters control are also briefly summarized. All the mentioned issues are discussed with the goal of providing control design guidelines for DC microgrids. The future research challenges, from the authors’ point of view, are also provided in the final...

  14. Collaborative Filtering Based on Sequential Extraction of User-Item Clusters

    Science.gov (United States)

    Honda, Katsuhiro; Notsu, Akira; Ichihashi, Hidetomo

    Collaborative filtering is a computational realization of “word-of-mouth” in network community, in which the items prefered by “neighbors” are recommended. This paper proposes a new item-selection model for extracting user-item clusters from rectangular relation matrices, in which mutual relations between users and items are denoted in an alternative process of “liking or not”. A technique for sequential co-cluster extraction from rectangular relational data is given by combining the structural balancing-based user-item clustering method with sequential fuzzy cluster extraction appraoch. Then, the tecunique is applied to the collaborative filtering problem, in which some items may be shared by several user clusters.

  15. Cluster decay of 218U isotope

    International Nuclear Information System (INIS)

    Shivakumaraswamy, G.; Umesh, T.K.

    2012-01-01

    The phenomenon of spontaneous emission of charged particles heavier than alpha particle and lighter than a fission fragment from radioactive nuclei without accompanied by the emission of neutrons is known as cluster radioactivity or exotic radioactivity. The process of emission of charged particles heavier than alpha particle and lighter than a fission fragment is called exotic decay or cluster decay. The phenomenon of cluster radioactivity was first predicted theoretically by Sandulescu et al in 1980. Rose and Jones made first experimental observations of 14 C emission from 223 Ra in 1984. Several cluster decay modes in trans-lead region have been experimentally observed. The half-life values for different modes of cluster decay from different isotopes of uranium have been calculated using different theoretical models such as the analytical super asymmetric model (ASAFM), Preformed cluster model (PCM) and Coulomb and Proximity potential model (CPPM) etc. Recently some semi-empirical formulae, i.e, single line of universal curve (UNIV), Universal decay law (UDL) for both alpha and cluster radioactivity have also been proposed to explain cluster decay data. The alpha decay half-life of 218-219 U isotopes has been experimentally measured in 2007. The half-life values for different cluster decay modes of 218 U isotopes have been calculated PCM model. Recently in 2011, the half-life values have also been calculated for some cluster decay modes of 222-236 U isotopes using the effective liquid drop description with the varying mass asymmetry (VMAS) shape and effective inertial coefficient. In the light of this, in the present work we have studied the cluster radioactivity of 218 U isotope. The logarithmic half-lives for few cluster decay modes from 218 U isotope have been calculated by using three different approaches, i.e, UNIV proposed by Poenaru et al in 2011, UDL proposed by Qi et al in 2009 and the CPPM model proposed by Santhosh et al in 2002. The CPPM based

  16. Long-term mother and child mental health effects of a population-based infant sleep intervention: cluster-randomized, controlled trial.

    Science.gov (United States)

    Hiscock, Harriet; Bayer, Jordana K; Hampton, Anne; Ukoumunne, Obioha C; Wake, Melissa

    2008-09-01

    Maternal depression is an established risk for adverse child development. Two thirds of clinically significant depressive symptoms occur in mothers reporting an infant sleep problem. We aimed to determine the long-term effects of a behavioral intervention for infant sleep problems on maternal depression and parenting style, as well as on child mental health and sleep, when the children reached 2 years of age. We conducted a cluster-randomized trial in well-child centers across 6 government areas of Melbourne, Australia. Participants included 328 mothers reporting an infant sleep problem at 7 months, drawn from a population sample (N = 739) recruited at 4 months. We compared the usual well-child care (n = 154) versus a brief behavior-modification program designed to improve infant sleep (n = 174) delivered by well-child nurses at ages 8 to 10 months and measured maternal depression symptoms (Edinburgh Postnatal Depression Scale); parenting practices (Parent Behavior Checklist); child mental health (Child Behavior Checklist); and maternal report of a sleep problem (yes or no). At 2 years, mothers in the intervention group were less likely than control mothers to report clinical depression symptoms: 15.4% vs 26.4% (Edinburgh Postnatal Depression Scale community cut point) and 4.2% vs 13.2% (Edinburgh Postnatal Depression Scale clinical cut point). Neither parenting style nor child mental health differed markedly between the intervention and control groups. A total of 27.3% of children in the intervention group versus 32.6% of control children had a sleep problem. The sleep intervention in infancy resulted in sustained positive effects on maternal depression symptoms and found no evidence of longer-term adverse effects on either mothers' parenting practices or children's mental health. This intervention demonstrated the capacity of a functioning primary care system to deliver effective, universally offered secondary prevention.

  17. Testing dark energy and dark matter cosmological models with clusters of galaxies

    Energy Technology Data Exchange (ETDEWEB)

    Boehringer, Hans [Max-Planck-Institut fuer Extraterrestrische Physik, Garching (Germany)

    2008-07-01

    Galaxy clusters are, as the largest building blocks of our Universe, ideal probes to study the large-scale structure and to test cosmological models. The principle approach und the status of this research is reviewed. Clusters lend themselves for tests in serveral ways: the cluster mass function, the spatial clustering, the evolution of both functions with reshift, and the internal composition can be used to constrain cosmological parameters. X-ray observations are currently the best means of obtaining the relevant data on the galaxy cluster population. We illustrate in particular all the above mentioned methods with our ROSAT based cluster surveys. The mass calibration of clusters is an important issue, that is currently solved with XMM-Newton and Chandra studies. Based on the current experience we provide an outlook for future research, especially with eROSITA.

  18. Scientific Cluster Deployment and Recovery – Using puppet to simplify cluster management

    International Nuclear Information System (INIS)

    Hendrix, Val; Yao Yushu; Benjamin, Doug

    2012-01-01

    Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

  19. Objective Classification of Rainfall in Northern Europe for Online Operation of Urban Water Systems Based on Clustering Techniques

    DEFF Research Database (Denmark)

    Löwe, Roland; Madsen, Henrik; McSharry, Patrick

    2016-01-01

    operators to change modes of control of their facilities. A k-means clustering technique was applied to group events retrospectively and was able to distinguish events with clearly different temporal and spatial correlation properties. For online applications, techniques based on k-means clustering...... and quadratic discriminant analysis both provided a fast and reliable identification of rain events of "high" variability, while the k-means provided the smallest number of rain events falsely identified as being of "high" variability (false hits). A simple classification method based on a threshold...

  20. Motivational Interviewing for Workers with Disabling Musculoskeletal Disorders: Results of a Cluster Randomized Control Trial.

    Science.gov (United States)

    Park, Joanne; Esmail, Shaniff; Rayani, Fahreen; Norris, Colleen M; Gross, Douglas P

    2018-06-01

    Purpose Although functional restoration programs appear effective in assisting injured workers to return-to-work (RTW) after a work related musculoskeletal (MSK) disorder, the addition of Motivational Interviewing (MI) to these programs may result in higher RTW. Methods We conducted a cluster randomized controlled trial with claimants attending an occupational rehabilitation facility from November 17, 2014 to June 30, 2015. Six clinicians provided MI in addition to the standard functional restoration program and formed an intervention group. Six clinicians continued to provide the standard functional restoration program based on graded activity, therapeutic exercise, and workplace accommodations. Independent t tests and chi square analysis were used to compare groups. Multivariable logistic regression was used to obtain the odds ratio of claimants' confirmed RTW status at time of program discharge. Results 728 workers' compensation claimants with MSK disorders were entered into 1 of 12 therapist clusters (MI group = 367, control group = 361). Claimants were predominantly employed (72.7%), males (63.2%), with moderate levels of pain and disability (mean pain VAS = 5.0/10 and mean Pain Disability Index = 48/70). Claimants were stratified based on job attachment status. The proportion of successful RTW at program discharge was 12.1% higher for unemployed workers in the intervention group (intervention group 21.6 vs. 9.5% in control, p = 0.03) and 3.0% higher for job attached workers compared to the control group (intervention group 97.1 vs. 94.1% in control, p = 0.10). Adherence to MI was mixed, but RTW was significantly higher among MI-adherent clinicians. The odds ratio for unemployed claimants was 2.64 (0.69-10.14) and 2.50 (0.68-9.14) for employed claimants after adjusting for age, sex, pain intensity, perceived disability, and therapist cluster. Conclusion MI in addition to routine functional restoration is more effective than routine

  1. Information Clustering Based on Fuzzy Multisets.

    Science.gov (United States)

    Miyamoto, Sadaaki

    2003-01-01

    Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…

  2. The Eclipse system for surveying the guide tubes of control rod clusters

    International Nuclear Information System (INIS)

    Pace, Y.M.

    2008-01-01

    Eclipse is a new system developed by Areva to assess the wear of the guide tubes of control rod clusters. This system is based on the projection of a shadow on a light plan in order to record the profile and the internal diameter of a hollow tube. This system allows us to quantify the wear and it can be included in a program dedicated to monitor the wear and master its kinetics. This system has been validated on the guide tubes from the Ringhals units. (A.C.)

  3. Effectiveness and Cost-Effectiveness of Occupation-Based Occupational Therapy Using the Aid for Decision Making in Occupation Choice (ADOC) for Older Residents: Pilot Cluster Randomized Controlled Trial

    Science.gov (United States)

    Nagayama, Hirofumi; Tomori, Kounosuke; Ohno, Kanta; Takahashi, Kayoko; Ogahara, Kakuya; Sawada, Tatsunori; Uezu, Sei; Nagatani, Ryutaro; Yamauchi, Keita

    2016-01-01

    Background Care-home residents are mostly inactive, have little interaction with staff, and are dependent on staff to engage in daily occupations. We recently developed an iPad application called the Aid for Decision-making in Occupation Choice (ADOC) to promote shared decision-making in activities and occupation-based goal setting by choosing from illustrations describing daily activities. This study aimed to evaluate if interventions based on occupation-based goal setting using the ADOC could focus on meaningful activities to improve quality of life and independent activities of daily living, with greater cost-effectiveness than an impairment-based approach as well as to evaluate the feasibility of conducting a large cluster, randomized controlled trial. Method In this single (assessor)-blind pilot cluster randomized controlled trial, the intervention group (ADOC group) received occupational therapy based on occupation-based goal setting using the ADOC, and the interventions were focused on meaningful occupations. The control group underwent an impairment-based approach focused on restoring capacities, without goal setting tools. In both groups, the 20-minute individualized intervention sessions were conducted twice a week for 4 months. Main Outcome Measures Short Form-36 (SF-36) score, SF-6D utility score, quality adjusted life years (QALY), Barthel Index, and total care cost. Results We randomized and analyzed 12 facilities (44 participants, 18.5% drop-out rate), with 6 facilities each allocated to the ADOC (n = 23) and control (n = 21) groups. After the 4-month intervention, the ADOC group had a significantly greater change in the BI score, with improved scores (P = 0.027, 95% CI 0.41 to 6.87, intracluster correlation coefficient = 0.14). No other outcome was significantly different. The incremental cost-effectiveness ratio, calculated using the change in BI score, was $63.1. Conclusion The results suggest that occupational therapy using the ADOC for older

  4. Parallel Density-Based Clustering for Discovery of Ionospheric Phenomena

    Science.gov (United States)

    Pankratius, V.; Gowanlock, M.; Blair, D. M.

    2015-12-01

    Ionospheric total electron content maps derived from global networks of dual-frequency GPS receivers can reveal a plethora of ionospheric features in real-time and are key to space weather studies and natural hazard monitoring. However, growing data volumes from expanding sensor networks are making manual exploratory studies challenging. As the community is heading towards Big Data ionospheric science, automation and Computer-Aided Discovery become indispensable tools for scientists. One problem of machine learning methods is that they require domain-specific adaptations in order to be effective and useful for scientists. Addressing this problem, our Computer-Aided Discovery approach allows scientists to express various physical models as well as perturbation ranges for parameters. The search space is explored through an automated system and parallel processing of batched workloads, which finds corresponding matches and similarities in empirical data. We discuss density-based clustering as a particular method we employ in this process. Specifically, we adapt Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This algorithm groups geospatial data points based on density. Clusters of points can be of arbitrary shape, and the number of clusters is not predetermined by the algorithm; only two input parameters need to be specified: (1) a distance threshold, (2) a minimum number of points within that threshold. We discuss an implementation of DBSCAN for batched workloads that is amenable to parallelization on manycore architectures such as Intel's Xeon Phi accelerator with 60+ general-purpose cores. This manycore parallelization can cluster large volumes of ionospheric total electronic content data quickly. Potential applications for cluster detection include the visualization, tracing, and examination of traveling ionospheric disturbances or other propagating phenomena. Acknowledgments. We acknowledge support from NSF ACI-1442997 (PI V. Pankratius).

  5. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.

    Science.gov (United States)

    Inano, Rika; Oishi, Naoya; Kunieda, Takeharu; Arakawa, Yoshiki; Yamao, Yukihiro; Shibata, Sumiya; Kikuchi, Takayuki; Fukuyama, Hidenao; Miyamoto, Susumu

    2014-01-01

    Gliomas are the most common intra-axial primary brain tumour; therefore, predicting glioma grade would influence therapeutic strategies. Although several methods based on single or multiple parameters from diagnostic images exist, a definitive method for pre-operatively determining glioma grade remains unknown. We aimed to develop an unsupervised method using multiple parameters from pre-operative diffusion tensor images for obtaining a clustered image that could enable visual grading of gliomas. Fourteen patients with low-grade gliomas and 19 with high-grade gliomas underwent diffusion tensor imaging and three-dimensional T1-weighted magnetic resonance imaging before tumour resection. Seven features including diffusion-weighted imaging, fractional anisotropy, first eigenvalue, second eigenvalue, third eigenvalue, mean diffusivity and raw T2 signal with no diffusion weighting, were extracted as multiple parameters from diffusion tensor imaging. We developed a two-level clustering approach for a self-organizing map followed by the K-means algorithm to enable unsupervised clustering of a large number of input vectors with the seven features for the whole brain. The vectors were grouped by the self-organizing map as protoclusters, which were classified into the smaller number of clusters by K-means to make a voxel-based diffusion tensor-based clustered image. Furthermore, we also determined if the diffusion tensor-based clustered image was really helpful for predicting pre-operative glioma grade in a supervised manner. The ratio of each class in the diffusion tensor-based clustered images was calculated from the regions of interest manually traced on the diffusion tensor imaging space, and the common logarithmic ratio scales were calculated. We then applied support vector machine as a classifier for distinguishing between low- and high-grade gliomas. Consequently, the sensitivity, specificity, accuracy and area under the curve of receiver operating characteristic

  6. Clusters and the new economics of competition.

    Science.gov (United States)

    Porter, M E

    1998-01-01

    Economic geography in an era of global competition poses a paradox. In theory, location should no longer be a source of competitive advantage. Open global markets, rapid transportation, and high-speed communications should allow any company to source any thing from any place at any time. But in practice, Michael Porter demonstrates, location remains central to competition. Today's economic map of the world is characterized by what Porter calls clusters: critical masses in one place of linked industries and institutions--from suppliers to universities to government agencies--that enjoy unusual competitive success in a particular field. The most famous example are found in Silicon Valley and Hollywood, but clusters dot the world's landscape. Porter explains how clusters affect competition in three broad ways: first, by increasing the productivity of companies based in the area; second, by driving the direction and pace of innovation; and third, by stimulating the formation of new businesses within the cluster. Geographic, cultural, and institutional proximity provides companies with special access, closer relationships, better information, powerful incentives, and other advantages that are difficult to tap from a distance. The more complex, knowledge-based, and dynamic the world economy becomes, the more this is true. Competitive advantage lies increasingly in local things--knowledge, relationships, and motivation--that distant rivals cannot replicate. Porter challenges the conventional wisdom about how companies should be configured, how institutions such as universities can contribute to competitive success, and how governments can promote economic development and prosperity.

  7. Mindfulness-Based Stress Release Program for University Employees: A Pilot, Waitlist-Controlled Trial and Implementation Replication.

    Science.gov (United States)

    Koncz, Rebecca; Wolfenden, Fiona; Hassed, Craig; Chambers, Richard; Cohen, Julia; Glozier, Nicholas

    2016-10-01

    The aim of this study was to evaluate the effectiveness of a 6-week mindfulness-based stress release program (SRP) on stress and work engagement in fulltime university employees. Perceived stress, workplace wellbeing, and engagement were measured at baseline and within 1 week of the SRP completion, and contemporaneously 6 weeks apart for a waitlist control group. A second program was implemented to examine reproducibility of results. Fifty participants undertook the SRPs, and 29 participants were waitlisted. A significant improvement in distress, workplace wellbeing, and vigor was observed within the first SRP group, when compared with the control group. The improvement in distress and wellbeing was reproduced in the second SRP group. This study adds to the growing body of research that mindfulness may be an effective method for reducing workplace stress, improving employee wellbeing, and enhancing work engagement.

  8. Supporting recovery in patients with psychosis through care by community-based adult mental health teams (REFOCUS): a multisite, cluster, randomised, controlled trial.

    Science.gov (United States)

    Slade, Mike; Bird, Victoria; Clarke, Eleanor; Le Boutillier, Clair; McCrone, Paul; Macpherson, Rob; Pesola, Francesca; Wallace, Genevieve; Williams, Julie; Leamy, Mary

    2015-06-01

    Mental health policy in many countries is oriented around recovery, but the evidence base for service-level recovery-promotion interventions is lacking. We did a cluster, randomised, controlled trial in two National Health Service Trusts in England. REFOCUS is a 1-year team-level intervention targeting staff behaviour to increase focus on values, preferences, strengths, and goals of patients with psychosis, and staff-patient relationships, through coaching and partnership. Between April, 2011, and May, 2012, community-based adult mental health teams were randomly allocated to provide usual treatment plus REFOCUS or usual treatment alone (control). Baseline and 1-year follow-up outcomes were assessed in randomly selected patients. The primary outcome was recovery and was assessed with the Questionnaire about Processes of Recovery (QPR). We also calculated overall service costs. We used multiple imputation to estimate missing data, and the imputation model captured clustering at the team level. Analysis was by intention to treat. This trial is registered, number ISRCTN02507940. 14 teams were included in the REFOCUS group and 13 in the control group. Outcomes were assessed in 403 patients (88% of the target sample) at baseline and in 297 at 1 year. Mean QPR total scores did not differ between the two groups (REFOCUS group 40·6 [SD 10·1] vs control 40·0 [10·2], adjusted difference 0·68, 95% CI -1·7 to 3·1, p=0·58). High team participation was associated with higher staff-rated scores for recovery-promotion behaviour change (adjusted difference -0·4, 95% CI -0·7 to -0·2, p=0·001) and patient-rated QPR interpersonal scores (-1·6, -2·7 to -0·5, p=0·005) at follow-up than low participation. Patients treated in the REFOCUS group incurred £1062 (95% CI -1103 to 3017) lower adjusted costs than those in the control group. Although the primary endpoint was negative, supporting recovery might, from the staff perspective, improve functioning and reduce needs

  9. An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt

    Directory of Open Access Journals (Sweden)

    Qingming Zhan

    2017-08-01

    Full Text Available An adaptive spatial clustering (ASC algorithm is proposed in this present study, which employs sweep-circle techniques and a dynamic threshold setting based on the Gestalt theory to detect spatial clusters. The proposed algorithm can automatically discover clusters in one pass, rather than through the modification of the initial model (for example, a minimal spanning tree, Delaunay triangulation, or Voronoi diagram. It can quickly identify arbitrarily-shaped clusters while adapting efficiently to non-homogeneous density characteristics of spatial data, without the need for prior knowledge or parameters. The proposed algorithm is also ideal for use in data streaming technology with dynamic characteristics flowing in the form of spatial clustering in large data sets.

  10. Cross-layer cluster-based energy-efficient protocol for wireless sensor networks.

    Science.gov (United States)

    Mammu, Aboobeker Sidhik Koyamparambil; Hernandez-Jayo, Unai; Sainz, Nekane; de la Iglesia, Idoia

    2015-04-09

    Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).

  11. Management of Energy Consumption on Cluster Based Routing Protocol for MANET

    Science.gov (United States)

    Hosseini-Seno, Seyed-Amin; Wan, Tat-Chee; Budiarto, Rahmat; Yamada, Masashi

    The usage of light-weight mobile devices is increasing rapidly, leading to demand for more telecommunication services. Consequently, mobile ad hoc networks and their applications have become feasible with the proliferation of light-weight mobile devices. Many protocols have been developed to handle service discovery and routing in ad hoc networks. However, the majority of them did not consider one critical aspect of this type of network, which is the limited of available energy in each node. Cluster Based Routing Protocol (CBRP) is a robust/scalable routing protocol for Mobile Ad hoc Networks (MANETs) and superior to existing protocols such as Ad hoc On-demand Distance Vector (AODV) in terms of throughput and overhead. Therefore, based on this strength, methods to increase the efficiency of energy usage are incorporated into CBRP in this work. In order to increase the stability (in term of life-time) of the network and to decrease the energy consumption of inter-cluster gateway nodes, an Enhanced Gateway Cluster Based Routing Protocol (EGCBRP) is proposed. Three methods have been introduced by EGCBRP as enhancements to the CBRP: improving the election of cluster Heads (CHs) in CBRP which is based on the maximum available energy level, implementing load balancing for inter-cluster traffic using multiple gateways, and implementing sleep state for gateway nodes to further save the energy. Furthermore, we propose an Energy Efficient Cluster Based Routing Protocol (EECBRP) which extends the EGCBRP sleep state concept into all idle member nodes, excluding the active nodes in all clusters. The experiment results show that the EGCBRP decreases the overall energy consumption of the gateway nodes up to 10% and the EECBRP reduces the energy consumption of the member nodes up to 60%, both of which in turn contribute to stabilizing the network.

  12. Cross-Layer Cluster-Based Energy-Efficient Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Aboobeker Sidhik Koyamparambil Mammu

    2015-04-01

    Full Text Available Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs. One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs and a cluster head (CH. The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH and hybrid energy-efficient distributed clustering (HEED.

  13. Construction and application of Red5 cluster based on OpenStack

    Science.gov (United States)

    Wang, Jiaqing; Song, Jianxin

    2017-08-01

    With the application and development of cloud computing technology in various fields, the resource utilization rate of the data center has been improved obviously, and the system based on cloud computing platform has also improved the expansibility and stability. In the traditional way, Red5 cluster resource utilization is low and the system stability is poor. This paper uses cloud computing to efficiently calculate the resource allocation ability, and builds a Red5 server cluster based on OpenStack. Multimedia applications can be published to the Red5 cloud server cluster. The system achieves the flexible construction of computing resources, but also greatly improves the stability of the cluster and service efficiency.

  14. Fault detection of flywheel system based on clustering and principal component analysis

    Directory of Open Access Journals (Sweden)

    Wang Rixin

    2015-12-01

    Full Text Available Considering the nonlinear, multifunctional properties of double-flywheel with closed-loop control, a two-step method including clustering and principal component analysis is proposed to detect the two faults in the multifunctional flywheels. At the first step of the proposed algorithm, clustering is taken as feature recognition to check the instructions of “integrated power and attitude control” system, such as attitude control, energy storage or energy discharge. These commands will ask the flywheel system to work in different operation modes. Therefore, the relationship of parameters in different operations can define the cluster structure of training data. Ordering points to identify the clustering structure (OPTICS can automatically identify these clusters by the reachability-plot. K-means algorithm can divide the training data into the corresponding operations according to the reachability-plot. Finally, the last step of proposed model is used to define the relationship of parameters in each operation through the principal component analysis (PCA method. Compared with the PCA model, the proposed approach is capable of identifying the new clusters and learning the new behavior of incoming data. The simulation results show that it can effectively detect the faults in the multifunctional flywheels system.

  15. Task shifting of frontline community health workers for cardiovascular risk reduction: design and rationale of a cluster randomised controlled trial (DISHA study) in India.

    Science.gov (United States)

    Jeemon, Panniyammakal; Narayanan, Gitanjali; Kondal, Dimple; Kahol, Kashvi; Bharadwaj, Ashok; Purty, Anil; Negi, Prakash; Ladhani, Sulaiman; Sanghvi, Jyoti; Singh, Kuldeep; Kapoor, Deksha; Sobti, Nidhi; Lall, Dorothy; Manimunda, Sathyaprakash; Dwivedi, Supriya; Toteja, Gurudyal; Prabhakaran, Dorairaj

    2016-03-15

    Effective task-shifting interventions targeted at reducing the global cardiovascular disease (CVD) epidemic in low and middle-income countries (LMICs) are urgently needed. DISHA is a cluster randomised controlled trial conducted across 10 sites (5 in phase 1 and 5 in phase 2) in India in 120 clusters. At each site, 12 clusters were randomly selected from a district. A cluster is defined as a small village with 250-300 households and well defined geographical boundaries. They were then randomly allocated to intervention and control clusters in a 1:1 allocation sequence. If any of the intervention and control clusters were workers (mainly Anganwadi workers and ASHA workers) and a post intervention survey in a representative sample. The study staff had no information on intervention allocation until the completion of the baseline survey. In order to ensure comparability of data across sites, the DISHA study follows a common protocol and manual of operation with standardized measurement techniques. Our study is the largest community based cluster randomised trial in low and middle-income country settings designed to test the effectiveness of 'task shifting' interventions involving frontline health workers for cardiovascular risk reduction. CTRI/2013/10/004049 . Registered 7 October 2013.

  16. Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks.

    Science.gov (United States)

    Arunraja, Muruganantham; Malathi, Veluchamy; Sakthivel, Erulappan

    2015-11-01

    Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  17. SDN‐Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra‐Dense Small Cell Networks

    Directory of Open Access Journals (Sweden)

    Guang Yang

    2018-04-01

    Full Text Available Ultra‐dense small cell networks (UD‐SCNs have been identified as a promising scheme for next‐generation wireless networks capable of meeting the ever‐increasing demand for higher transmission rates and better quality of service. However, UD‐SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software‐defined networking (SDN‐based hierarchical agglomerative clustering (SDN‐HAC framework, which leverages SDN to centrally control all sub‐channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non‐cooperative scenarios, respectively.

  18. Multi scales based sparse matrix spectral clustering image segmentation

    Science.gov (United States)

    Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

    2018-04-01

    In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

  19. A lightweight universe?

    Science.gov (United States)

    Bahcall, Neta A.; Fan, Xiaohui

    1998-01-01

    How much matter is there in the universe? Does the universe have the critical density needed to stop its expansion, or is the universe underweight and destined to expand forever? We show that several independent measures, especially those utilizing the largest bound systems known—clusters of galaxies—all indicate that the mass-density of the universe is insufficient to halt the expansion. A promising new method, the evolution of the number density of clusters with time, provides the most powerful indication so far that the universe has a subcritical density. We show that different techniques reveal a consistent picture of a lightweight universe with only ∼20–30% of the critical density. Thus, the universe may expand forever. PMID:9600898

  20. A novel clustering algorithm based on quantum games

    International Nuclear Information System (INIS)

    Li Qiang; He Yan; Jiang Jingping

    2009-01-01

    Enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum game with the problem of data clustering, and then develop a quantum-game-based clustering algorithm, in which data points in a dataset are considered as players who can make decisions and implement quantum strategies in quantum games. After each round of a quantum game, each player's expected payoff is calculated. Later, he uses a link-removing-and-rewiring (LRR) function to change his neighbors and adjust the strength of links connecting to them in order to maximize his payoff. Further, algorithms are discussed and analyzed in two cases of strategies, two payoff matrixes and two LRR functions. Consequently, the simulation results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms have fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach.

  1. Cluster size matters: Size-driven performance of subnanometer clusters in catalysis, electrocatalysis and Li-air batteries

    Science.gov (United States)

    Vajda, Stefan

    2015-03-01

    This paper discusses the strongly size-dependent performance of subnanometer cluster based catalysts in 1) heterogeneous catalysis, 2) electrocatalysis and 3) Li-air batteries. The experimental studies are based on I. fabrication of ultrasmall clusters with atomic precision control of particle size and their deposition on oxide and carbon based supports; II. test of performance, III. in situand ex situ X-ray characterization of cluster size, shape and oxidation state; and IV.electron microscopies. Heterogeneous catalysis. The pronounced effect of cluster size and support on the performance of the catalyst (catalyst activity and the yield of Cn products) will be illustrated on the example of nickel and cobalt clusters in Fischer-Tropsch reaction. Electrocatalysis. The study of the oxygen evolution reaction (OER) on size-selected palladium clusters supported on ultrananocrystalline diamond show pronounced size effects. While Pd4 clusters show no reaction, Pd6 and Pd17 clusters are among the most active catalysts known (in in terms of turnover rate per Pd atom). The system (soft-landed Pd4, Pd6, or Pd17 clusters on an UNCD Si coated electrode) shows stable electrochemical potentials over several cycles, and the characterization of the electrodes show no evidence for evolution or dissolution of either the support Theoretical calculations suggest that this striking difference may be a demonstration that bridging Pd-Pd sites, which are only present in three-dimensional clusters, are active for the oxygen evolution reaction in Pd6O6. Li-air batteries. The studies show that sub-nm silver clusters have dramatic size-dependent effect on the lowering of the overpotential, charge capacity, morphology of the discharge products, as well as on the morphology of the nm size building blocks of the discharge products. The results suggest that by precise control of the active surface sites on the cathode, the performance of Li-air cells can be significantly improved

  2. Green Clustering Implementation Based on DPS-MOPSO

    Directory of Open Access Journals (Sweden)

    Yang Lu

    2014-01-01

    Full Text Available A green clustering implementation is proposed to be as the first method in the framework of an energy-efficient strategy for centralized enterprise high-density WLANs. Traditionally, to maintain the network coverage, all of the APs within the WLAN have to be powered on. Nevertheless, the new algorithm can power off a large proportion of APs while the coverage is maintained as the always-on counterpart. The proposed algorithm is composed of two parallel and concurrent procedures, which are the faster procedure based on K-means and the more accurate procedure based on Dynamic Population Size Multiple Objective Particle Swarm Optimization (DPS-MOPSO. To implement green clustering efficiently and accurately, dynamic population size and mutational operators are introduced as complements for the classical MOPSO. In addition to the function of AP selection, the new green clustering algorithm has another new function as the reference and guidance for AP deployment. This paper also presents simulations in scenarios modeled with ray-tracing method and FDTD technique, and the results show that about 67% up to 90% of energy consumption can be saved while the original network coverage is maintained during periods when few users are online or when the traffic load is low.

  3. Structuring communication relationships for interprofessional teamwork (SCRIPT: a cluster randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Kenaszchuk Chris

    2007-09-01

    Full Text Available Abstract Background Despite a burgeoning interest in using interprofessional approaches to promote effective collaboration in health care, systematic reviews find scant evidence of benefit. This protocol describes the first cluster randomized controlled trial (RCT to design and evaluate an intervention intended to improve interprofessional collaborative communication and patient-centred care. Objectives The objective is to evaluate the effects of a four-component, hospital-based staff communication protocol designed to promote collaborative communication between healthcare professionals and enhance patient-centred care. Methods The study is a multi-centre mixed-methods cluster randomized controlled trial involving twenty clinical teaching teams (CTTs in general internal medicine (GIM divisions of five Toronto tertiary-care hospitals. CTTs will be randomly assigned either to receive an intervention designed to improve interprofessional collaborative communication, or to continue usual communication practices. Non-participant naturalistic observation, shadowing, and semi-structured, qualitative interviews were conducted to explore existing patterns of interprofessional collaboration in the CTTs, and to support intervention development. Interviews and shadowing will continue during intervention delivery in order to document interactions between the intervention settings and adopters, and changes in interprofessional communication. The primary outcome is the rate of unplanned hospital readmission. Secondary outcomes are length of stay (LOS; adherence to evidence-based prescription drug therapy; patients' satisfaction with care; self-report surveys of CTT staff perceptions of interprofessional collaboration; and frequency of calls to paging devices. Outcomes will be compared on an intention-to-treat basis using adjustment methods appropriate for data from a cluster randomized design. Discussion Pre-intervention qualitative analysis revealed that a

  4. A quasiparticle-based multi-reference coupled-cluster method.

    Science.gov (United States)

    Rolik, Zoltán; Kállay, Mihály

    2014-10-07

    The purpose of this paper is to introduce a quasiparticle-based multi-reference coupled-cluster (MRCC) approach. The quasiparticles are introduced via a unitary transformation which allows us to represent a complete active space reference function and other elements of an orthonormal multi-reference (MR) basis in a determinant-like form. The quasiparticle creation and annihilation operators satisfy the fermion anti-commutation relations. On the basis of these quasiparticles, a generalization of the normal-ordered operator products for the MR case can be introduced as an alternative to the approach of Mukherjee and Kutzelnigg [Recent Prog. Many-Body Theor. 4, 127 (1995); Mukherjee and Kutzelnigg, J. Chem. Phys. 107, 432 (1997)]. Based on the new normal ordering any quasiparticle-based theory can be formulated using the well-known diagram techniques. Beyond the general quasiparticle framework we also present a possible realization of the unitary transformation. The suggested transformation has an exponential form where the parameters, holding exclusively active indices, are defined in a form similar to the wave operator of the unitary coupled-cluster approach. The definition of our quasiparticle-based MRCC approach strictly follows the form of the single-reference coupled-cluster method and retains several of its beneficial properties. Test results for small systems are presented using a pilot implementation of the new approach and compared to those obtained by other MR methods.

  5. Cosmological analysis of galaxy clusters surveys in X-rays

    International Nuclear Information System (INIS)

    Clerc, N.

    2012-01-01

    Clusters of galaxies are the most massive objects in equilibrium in our Universe. Their study allows to test cosmological scenarios of structure formation with precision, bringing constraints complementary to those stemming from the cosmological background radiation, supernovae or galaxies. They are identified through the X-ray emission of their heated gas, thus facilitating their mapping at different epochs of the Universe. This report presents two surveys of galaxy clusters detected in X-rays and puts forward a method for their cosmological interpretation. Thanks to its multi-wavelength coverage extending over 10 sq. deg. and after one decade of expertise, the XMM-LSS allows a systematic census of clusters in a large volume of the Universe. In the framework of this survey, the first part of this report describes the techniques developed to the purpose of characterizing the detected objects. A particular emphasis is placed on the most distant ones (z ≥ 1) through the complementarity of observations in X-ray, optical and infrared bands. Then the X-CLASS survey is fully described. Based on XMM archival data, it provides a new catalogue of 800 clusters detected in X-rays. A cosmological analysis of this survey is performed thanks to 'CR-HR' diagrams. This new method self-consistently includes selection effects and scaling relations and provides a means to bypass the computation of individual cluster masses. Propositions are made for applying this method to future surveys as XMM-XXL and eRosita. (author) [fr

  6. Moscow University race-track microtron control system: ideas and development

    International Nuclear Information System (INIS)

    Chepurnov, A.S.; Gribov, I.V.; Morozov, S.Yu.; Shumakov, A.V.; Zinoviev, S.V.

    1992-01-01

    Moscow University race-track microtron (RTM) control system is a star-shape network of LSI-11 compatible microcomputers. Each of them is connected with RTM systems via CAMAC; optical fiber coupling is also used. Control system software is designed on Pascal-1, supplemented with real time modules and Macro. A unified real time technique and reenterable data acquisition drivers allow to simplify development of control drivers and algorithms. Among the latter three main types are used: DDC methods, those, based on optimization technique and algorithms, applying models of microtron's systems. Man-machine interface is based on concept of the 'world of accelerator'. It supports means to design, within hardware possibilities, various computer images of the RTM. (author)

  7. Formal And Informal Macro-Regional Transport Clusters As A Primary Step In The Design And Implementation Of Cluster-Based Strategies

    Directory of Open Access Journals (Sweden)

    Nežerenko Olga

    2015-09-01

    Full Text Available The aim of the study is the identification of a formal macro-regional transport and logistics cluster and its development trends on a macro-regional level in 2007-2011 by means of the hierarchical cluster analysis. The central approach of the study is based on two concepts: 1 the concept of formal and informal macro-regions, and 2 the concept of clustering which is based on the similarities shared by the countries of a macro-region and tightly related to the concept of macro-region. The authors seek to answer the question whether the formation of a formal transport cluster could provide the BSR a stable competitive position in the global transportation and logistics market.

  8. Substructures in DAFT/FADA survey clusters based on XMM and optical data

    Science.gov (United States)

    Durret, F.; DAFT/FADA Team

    2014-07-01

    The DAFT/FADA survey was initiated to perform weak lensing tomography on a sample of 90 massive clusters in the redshift range [0.4,0.9] with HST imaging available. The complementary deep multiband imaging constitutes a high quality imaging data base for these clusters. In X-rays, we have analysed the XMM-Newton and/or Chandra data available for 32 clusters, and for 23 clusters we fit the X-ray emissivity with a beta-model and subtract it to search for substructures in the X-ray gas. This study was coupled with a dynamical analysis for the 18 clusters with at least 15 spectroscopic galaxy redshifts in the cluster range, based on a Serna & Gerbal (SG) analysis. We detected ten substructures in eight clusters by both methods (X-rays and SG). The percentage of mass included in substructures is found to be roughly constant with redshift, with values of 5-15%. Most of the substructures detected both in X-rays and with the SG method are found to be relatively recent infalls, probably at their first cluster pericenter approach.

  9. Space-time clustering of non-hodgkin lymphoma using residential histories in a Danish case-control study.

    Directory of Open Access Journals (Sweden)

    Rikke Baastrup Nordsborg

    Full Text Available Non-Hodgkin lymphoma (NHL is a frequent cancer and incidence rates have increased markedly during the second half of the 20(th century; however, the few established risk factors cannot explain this rise and still little is known about the aetiology of NHL. Spatial analyses have been applied in an attempt to identify environmental risk factors, but most studies do not take human mobility into account. The aim of this study was to identify clustering of NHL in space and time in Denmark, using 33 years of residential addresses. We utilised the nation-wide Danish registers and unique personal identification number that all Danish citizens have to conduct a register-based case-control study of 3210 NHL cases and two independent control groups of 3210 each. Cases were identified in the Danish Cancer Registry and controls were matched by age and sex and randomly selected from the Civil Registration System. Residential addresses of cases and controls from 1971 to 2003 were collected from the Civil Registration System and geocoded. Data on pervious hospital diagnoses and operations were obtained from the National Patient Register. We applied the methods of the newly developed Q-statistics to identify space-time clustering of NHL. All analyses were conducted with each of the two control groups, and we adjusted for previous history of autoimmune disease, HIV/AIDS or organ transplantation. Some areas with statistically significant clustering were identified; however, results were not consistent across the two control groups; thus we interpret the results as chance findings. We found no evidence for clustering of NHL in space and time using 33 years of residential histories, suggesting that if the rise in incidence of NHL is a result of risk factors that vary across space and time, the spatio-temporal variation of such factors in Denmark is too small to be detected with the applied method.

  10. Effectiveness of a pragmatic school-based universal intervention targeting student resilience protective factors in reducing mental health problems in adolescents.

    Science.gov (United States)

    Dray, Julia; Bowman, Jenny; Campbell, Elizabeth; Freund, Megan; Hodder, Rebecca; Wolfenden, Luke; Richards, Jody; Leane, Catherine; Green, Sue; Lecathelinais, Christophe; Oldmeadow, Christopher; Attia, John; Gillham, Karen; Wiggers, John

    2017-06-01

    Worldwide, 10-20% of adolescents experience mental health problems. Strategies aimed at strengthening resilience protective factors provide a potential approach for reducing mental health problems in adolescents. This study evaluated the effectiveness of a universal, school-based intervention targeting resilience protective factors in reducing mental health problems in adolescents. A cluster randomised controlled trial was conducted in 20 intervention and 12 control secondary schools located in socio-economically disadvantaged areas of NSW, Australia. Data were collected from 3115 students at baseline (Grade 7, 2011), of whom 2149 provided data at follow up (Grade 10, 2014; enrolments in Grades 7 to 10 typically aged 12-16 years; 50% male; 69.0% retention). There were no significant differences between groups at follow-up for three mental health outcomes: total SDQ, internalising problems, and prosocial behaviour. A small statistically significant difference in favour of the control group was found for externalising problems. Findings highlight the continued difficulties in developing effective, school-based prevention programs for mental health problems in adolescents. ANZCTR (Ref no: ACTRN12611000606987). Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  11. Providing NHS staff with height-adjustable workstations and behaviour change strategies to reduce workplace sitting time: protocol for the Stand More AT (SMArT) Work cluster randomised controlled trial.

    Science.gov (United States)

    O'Connell, S E; Jackson, B R; Edwardson, C L; Yates, T; Biddle, S J H; Davies, M J; Dunstan, D; Esliger, D; Gray, L; Miller, P; Munir, F

    2015-12-09

    High levels of sedentary behaviour (i.e., sitting) are a risk factor for poor health. With high levels of sitting widespread in desk-based office workers, office workplaces are an appropriate setting for interventions aimed at reducing sedentary behaviour. This paper describes the development processes and proposed intervention procedures of Stand More AT (SMArT) Work, a multi-component randomised control (RCT) trial which aims to reduce occupational sitting time in desk-based office workers within the National Health Service (NHS). SMArT Work consists of 2 phases: 1) intervention development: The development of the SMArT Work intervention takes a community-based participatory research approach using the Behaviour Change Wheel. Focus groups will collect detailed information to gain a better understanding of the most appropriate strategies, to sit alongside the provision of height-adjustable workstations, at the environmental, organisational and individual level that support less occupational sitting. 2) intervention delivery and evaluation: The 12 month cluster RCT aims to reduce workplace sitting in the University Hospitals of Leicester NHS Trust. Desk-based office workers (n = 238) will be randomised to control or intervention clusters, with the intervention group receiving height-adjustable workstations and supporting techniques based on the feedback received from the development phase. Data will be collected at four time points; baseline, 3, 6 and 12 months. The primary outcome is a reduction in sitting time, measured by the activPAL(TM) micro at 12 months. Secondary outcomes include objectively measured physical activity and a variety of work-related health and psycho-social measures. A process evaluation will also take place. This study will be the first long-term, evidence-based, multi-component cluster RCT aimed at reducing occupational sitting within the NHS. This study will help form a better understanding and knowledge base of facilitators and

  12. Adaptive density trajectory cluster based on time and space distance

    Science.gov (United States)

    Liu, Fagui; Zhang, Zhijie

    2017-10-01

    There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

  13. Microgrid Central Controller Development and Hierarchical Control Implementation in the Intelligent MicroGrid Lab of Aalborg University

    DEFF Research Database (Denmark)

    Meng, Lexuan; Savaghebi, Mehdi; Andrade, Fabio

    2015-01-01

    This paper presents the development of a microgrid central controller in an inverter-based intelligent microgrid (iMG) lab in Aalborg University, Denmark. The iMG lab aims to provide a flexible experimental platform for comprehensive studies of microgrids. The complete control system applied...... in this lab is based on the hierarchical control scheme for microgrids and includes primary, secondary and tertiary control. The structure of the lab, including the lab facilities, configurations and communication network, is first introduced. Primary control loops are developed in MATLAB....../Simulink and compiled to dSPACEs for local control purposes. In order to realize system supervision and proper secondary and tertiary management, a LabVIEW-based microgrid central controller is also developed. The software and hardware schemes are described. An example case is introduced and tested in the iMG lab...

  14. Load management: Model-based control of aggregate power for populations of thermostatically controlled loads

    International Nuclear Information System (INIS)

    Perfumo, Cristian; Kofman, Ernesto; Braslavsky, Julio H.; Ward, John K.

    2012-01-01

    Highlights: ► Characterisation of power response of a population of air conditioners. ► Implementation of demand side management on a group of air conditioners. ► Design of a controller for the power output of a group of air conditioners. ► Quantification of comfort impact of demand side management. - Abstract: Large groups of electrical loads can be controlled as a single entity to reduce their aggregate power demand in the electricity network. This approach, known as load management (LM) or demand response, offers an alternative to the traditional paradigm in the electricity market, where matching supply and demand is achieved solely by regulating how much generation is dispatched. Thermostatically controlled loads (TCLs), such as air conditioners (ACs) and fridges, are particularly suitable for LM, which can be implemented using feedback control techniques to regulate their aggregate power. To achieve high performance, such feedback control techniques require an accurate mathematical model of the TCL aggregate dynamics. Although such models have been developed, they appear too complex to be effectively used in control design. In this paper we develop a mathematical model aimed at the design of a model-based feedback control strategy. The proposed model analytically characterises the aggregate power response of a population of ACs to a simultaneous step change in temperature set points. Based on this model, we then derive, and completely parametrise in terms of the ACs ensemble properties, a reduced-order mathematical model to design an internal-model controller that regulates aggregate power by broadcasting temperature set-point offset changes. The proposed controller achieves high LM performance provided the ACs are equipped with high resolution thermostats. With coarser resolution thermostats, which are typical in present commercial and residential ACs, performance deteriorates significantly. This limitation is overcome by subdividing the population

  15. A Universal Motor Performance Test System Based on Virtual Instrument

    Directory of Open Access Journals (Sweden)

    Wei Li

    2014-09-01

    Full Text Available With the development of technology universal motors play a more and more important role in daily life and production, they have been used in increasingly wide field and the requirements increase gradually. How to control the speed and monitor the real-time temperature of motors are key issues. The cost of motor testing system based on traditional technology platform is very high in many reasons. In the paper a universal motor performance test system which based on virtual instrument is provided. The system achieves the precise control of the current motor speed and completes the measurement of real-time temperature of motor bearing support in order to realize the testing of general-purpose motor property. Experimental result shows that the system can work stability in controlling the speed and monitoring the real-time temperature. It has advantages that traditional using of SCM cannot match in speed, stability, cost and accuracy aspects. Besides it is easy to expand and reconfigure.

  16. Personalized PageRank Clustering: A graph clustering algorithm based on random walks

    Science.gov (United States)

    A. Tabrizi, Shayan; Shakery, Azadeh; Asadpour, Masoud; Abbasi, Maziar; Tavallaie, Mohammad Ali

    2013-11-01

    Graph clustering has been an essential part in many methods and thus its accuracy has a significant effect on many applications. In addition, exponential growth of real-world graphs such as social networks, biological networks and electrical circuits demands clustering algorithms with nearly-linear time and space complexity. In this paper we propose Personalized PageRank Clustering (PPC) that employs the inherent cluster exploratory property of random walks to reveal the clusters of a given graph. We combine random walks and modularity to precisely and efficiently reveal the clusters of a graph. PPC is a top-down algorithm so it can reveal inherent clusters of a graph more accurately than other nearly-linear approaches that are mainly bottom-up. It also gives a hierarchy of clusters that is useful in many applications. PPC has a linear time and space complexity and has been superior to most of the available clustering algorithms on many datasets. Furthermore, its top-down approach makes it a flexible solution for clustering problems with different requirements.

  17. Novel Clustering Method Based on K-Medoids and Mobility Metric

    Directory of Open Access Journals (Sweden)

    Y. Hamzaoui

    2018-06-01

    Full Text Available The structure and constraint of MANETS influence negatively the performance of QoS, moreover the main routing protocols proposed generally operate in flat routing. Hence, this structure gives the bad results of QoS when the network becomes larger and denser. To solve this problem we use one of the most popular methods named clustering. The present paper comes within the frameworks of research to improve the QoS in MANETs. In this paper we propose a new algorithm of clustering based on the new mobility metric and K-Medoid to distribute the nodes into several clusters. Intuitively our algorithm can give good results in terms of stability of the cluster, and can also extend life time of cluster head.

  18. Clustering economies based on multiple criteria decision making techniques

    Directory of Open Access Journals (Sweden)

    Mansour Momeni

    2011-10-01

    Full Text Available One of the primary concerns on many countries is to determine different important factors affecting economic growth. In this paper, we study some factors such as unemployment rate, inflation ratio, population growth, average annual income, etc to cluster different countries. The proposed model of this paper uses analytical hierarchy process (AHP to prioritize the criteria and then uses a K-mean technique to cluster 59 countries based on the ranked criteria into four groups. The first group includes countries with high standards such as Germany and Japan. In the second cluster, there are some developing countries with relatively good economic growth such as Saudi Arabia and Iran. The third cluster belongs to countries with faster rates of growth compared with the countries located in the second group such as China, India and Mexico. Finally, the fourth cluster includes countries with relatively very low rates of growth such as Jordan, Mali, Niger, etc.

  19. Psychosocial benefits of workplace physical exercise: cluster randomized controlled trial.

    Science.gov (United States)

    Jakobsen, Markus D; Sundstrup, Emil; Brandt, Mikkel; Andersen, Lars L

    2017-10-10

    While benefits of workplace physical exercise on physical health is well known, little is known about the psychosocial effects of such initiatives. This study evaluates the effect of workplace versus home-based physical exercise on psychosocial factors among healthcare workers. A total of 200 female healthcare workers (Age: 42.0, BMI: 24.1) from 18 departments at three hospitals were cluster-randomized to 10 weeks of: 1) home-based physical exercise (HOME) performed alone during leisure time for 10 min 5 days per week or 2) workplace physical exercise (WORK) performed in groups during working hours for 10 min 5 days per week and up to 5 group-based coaching sessions on motivation for regular physical exercise. Vitality and mental health (SF-36, scale 0-100), psychosocial work environment (COPSOQ, scale 0-100), work- and leisure disability (DASH, 0-100), control- (Bournemouth, scale 0-10) and concern about pain (Pain Catastrophizing Scale, scale 0-10) were assessed at baseline and at 10-week follow-up. Vitality as well as control and concern about pain improved more following WORK than HOME (all p health remained unchanged. Between-group differences at follow-up (WORK vs. HOME) were 7 [95% confidence interval (95% CI) 3 to 10] for vitality, -0.8 [95% CI -1.3 to -0.3] for control of pain and -0.9 [95% CI -1.4 to -0.5] for concern about pain, respectively. Performing physical exercise together with colleagues during working hours was more effective than home-based exercise in improving vitality and concern and control of pain among healthcare workers. These benefits occurred in spite of increased work pace. NCT01921764 at ClinicalTrials.gov . Registered 10 August 2013.

  20. Bipartite entanglement in continuous variable cluster states

    Energy Technology Data Exchange (ETDEWEB)

    Cable, Hugo; Browne, Daniel E, E-mail: cqthvc@nus.edu.s, E-mail: d.browne@ucl.ac.u [Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543 (Singapore)

    2010-11-15

    A study of the entanglement properties of Gaussian cluster states, proposed as a universal resource for continuous variable (CV) quantum computing is presented in this paper. The central aim is to compare mathematically idealized cluster states defined using quadrature eigenstates, which have infinite squeezing and cannot exist in nature, with Gaussian approximations that are experimentally accessible. Adopting widely used definitions, we first review the key concepts, by analysing a process of teleportation along a CV quantum wire in the language of matrix product states. Next we consider the bipartite entanglement properties of the wire, providing analytic results. We proceed to grid cluster states, which are universal for the qubit case. To extend our analysis of the bipartite entanglement, we adopt the entropic-entanglement width, a specialized entanglement measure introduced recently by Van den Nest et al (2006 Phys. Rev. Lett. 97 150504), adapting their definition to the CV context. Finally, we consider the effects of photonic loss, extending our arguments to mixed states. Cumulatively our results point to key differences in the properties of idealized and Gaussian cluster states. Even modest loss rates are found to strongly limit the amount of entanglement. We discuss the implications for the potential of CV analogues for measurement-based quantum computation.

  1. Explaining the effects of an intervention designed to promote evidence-based diabetes care: a theory-based process evaluation of a pragmatic cluster randomised controlled trial

    Directory of Open Access Journals (Sweden)

    Kaner Eileen FS

    2008-11-01

    Full Text Available Abstract Background The results of randomised controlled trials can be usefully illuminated by studies of the processes by which they achieve their effects. The Theory of Planned Behaviour (TPB offers a framework for conducting such studies. This study used TPB to explore the observed effects in a pragmatic cluster randomised controlled trial of a structured recall and prompting intervention to increase evidence-based diabetes care that was conducted in three Primary Care Trusts in England. Methods All general practitioners and nurses in practices involved in the trial were sent a postal questionnaire at the end of the intervention period, based on the TPB (predictor variables: attitude; subjective norm; perceived behavioural control, or PBC. It focussed on three clinical behaviours recommended in diabetes care: measuring blood pressure; inspecting feet; and prescribing statins. Multivariate analyses of variance and multiple regression analyses were used to explore changes in cognitions and thereby better understand trial effects. Results Fifty-nine general medical practitioners and 53 practice nurses (intervention: n = 55, 41.98% of trial participants; control: n = 57, 38.26% of trial participants completed the questionnaire. There were no differences between groups in mean scores for attitudes, subjective norms, PBC or intentions. Control group clinicians had 'normatively-driven' intentions (i.e., related to subjective norm scores, whereas intervention group clinicians had 'attitudinally-driven' intentions (i.e., related to attitude scores for foot inspection and statin prescription. After controlling for effects of the three predictor variables, this group difference was significant for foot inspection behaviour (trial group × attitude interaction, beta = 0.72, p Conclusion Attitudinally-driven intentions are proposed to be more consistently translated into action than normatively-driven intentions. This proposition was supported by the

  2. A novel intrusion detection method based on OCSVM and K-means recursive clustering

    Directory of Open Access Journals (Sweden)

    Leandros A. Maglaras

    2015-01-01

    Full Text Available In this paper we present an intrusion detection module capable of detecting malicious network traffic in a SCADA (Supervisory Control and Data Acquisition system, based on the combination of One-Class Support Vector Machine (OCSVM with RBF kernel and recursive k-means clustering. Important parameters of OCSVM, such as Gaussian width o and parameter v affect the performance of the classifier. Tuning of these parameters is of great importance in order to avoid false positives and over fitting. The combination of OCSVM with recursive k- means clustering leads the proposed intrusion detection module to distinguish real alarms from possible attacks regardless of the values of parameters o and v, making it ideal for real-time intrusion detection mechanisms for SCADA systems. Extensive simulations have been conducted with datasets extracted from small and medium sized HTB SCADA testbeds, in order to compare the accuracy, false alarm rate and execution time against the base line OCSVM method.

  3. Power Flow Control through a Multi-Level H-Bridge-based Power Converter for Universal and Flexible Power Management in Future Electrical Grids

    DEFF Research Database (Denmark)

    Iov, Florin; Bifaretti, Steffano; Zanchetta, Pericle

    2008-01-01

    The paper proposes a novel power conversion system for Universal and Flexible Power Management (UNIFLEX-PM) in Future Electricity Network. The structure is based on three AC-DC converters each one connected to a different grid, (representing the main grid and/or various distributed generation...... systems) on the AC side, and linked together at DC side by suitable DC isolation modules. Each port of the UNIFLEX-PM system employs a conversion structure based on a three-phase 7-level AC-DC cascaded converter. Effective and accurate power flow control is demonstrated through simulation in Matlab...... and Simulink environment on a simplified model based on a two-port structure and using a Stationery Reference Frame based control solution. Control of different Power flow profiles has been successfully tested in numerous network conditions such as voltage unbalance, frequency excursions and harmonic...

  4. Unsupervised active learning based on hierarchical graph-theoretic clustering.

    Science.gov (United States)

    Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

    2009-10-01

    Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

  5. A robust approach based on Weibull distribution for clustering gene expression data

    Directory of Open Access Journals (Sweden)

    Gong Binsheng

    2011-05-01

    Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

  6. Depression in university students: associations with impulse control disorders.

    Science.gov (United States)

    Leppink, Eric W; Lust, Katherine; Grant, Jon E

    2016-09-01

    The purpose of this study was to assess the implications of depression in a sample of university students, particularly relating to impulse control disorders. While previous studies have shown high rates of depression among university students, no study to date has assessed whether levels of depression show associations with the incidence of impulse control disorders in this population. In all, 6000 students participated in the College Student Computer Use Survey. A total of 1717 students completed the scales of interest for this analysis. Participants were assigned to groups based on depression scores: severe (N = 75), mild/moderate (N = 647) and none (N = 995). The three groups were assessed using analysis of variance (ANOVA) or chi-square test. A multinomial logistic regression analysis was used to elucidate associations between depression and impulse control disorder diagnoses. Groups differed across demographic, health and academic variables. The severe depression group reported higher rates of skin-picking disorder, compulsive sexual behaviour and compulsive buying. Results suggest a significant association between depression and impulse control disorders. One possibility is that a facet of impulsivity contributes to both problems, which could be important information for clinicians. Future studies will need to clarify the exact nature of the relationship between depression and impulse control disorders.

  7. MCBT: Multi-Hop Cluster Based Stable Backbone Trees for Data Collection and Dissemination in WSNs

    Directory of Open Access Journals (Sweden)

    Tae-Jin Lee

    2009-07-01

    Full Text Available We propose a stable backbone tree construction algorithm using multi-hop clusters for wireless sensor networks (WSNs. The hierarchical cluster structure has advantages in data fusion and aggregation. Energy consumption can be decreased by managing nodes with cluster heads. Backbone nodes, which are responsible for performing and managing multi-hop communication, can reduce the communication overhead such as control traffic and minimize the number of active nodes. Previous backbone construction algorithms, such as Hierarchical Cluster-based Data Dissemination (HCDD and Multicluster, Mobile, Multimedia radio network (MMM, consume energy quickly. They are designed without regard to appropriate factors such as residual energy and degree (the number of connections or edges to other nodes of a node for WSNs. Thus, the network is quickly disconnected or has to reconstruct a backbone. We propose a distributed algorithm to create a stable backbone by selecting the nodes with higher energy or degree as the cluster heads. This increases the overall network lifetime. Moreover, the proposed method balances energy consumption by distributing the traffic load among nodes around the cluster head. In the simulation, the proposed scheme outperforms previous clustering schemes in terms of the average and the standard deviation of residual energy or degree of backbone nodes, the average residual energy of backbone nodes after disseminating the sensed data, and the network lifetime.

  8. A Cluster-based Approach Towards Detecting and Modeling Network Dictionary Attacks

    Directory of Open Access Journals (Sweden)

    A. Tajari Siahmarzkooh

    2016-12-01

    Full Text Available In this paper, we provide an approach to detect network dictionary attacks using a data set collected as flows based on which a clustered graph is resulted. These flows provide an aggregated view of the network traffic in which the exchanged packets in the network are considered so that more internally connected nodes would be clustered. We show that dictionary attacks could be detected through some parameters namely the number and the weight of clusters in time series and their evolution over the time. Additionally, the Markov model based on the average weight of clusters,will be also created. Finally, by means of our suggested model, we demonstrate that artificial clusters of the flows are created for normal and malicious traffic. The results of the proposed approach on CAIDA 2007 data set suggest a high accuracy for the model and, therefore, it provides a proper method for detecting the dictionary attack.

  9. IDENTIFICAÇÃO DE CLUSTERS INTERNACIONAIS COM BASE NAS DIMENSÕES CULTURAIS DE HOFSTEDE. / Identification of international clusters based on the hofstede’s cultural dimensions

    Directory of Open Access Journals (Sweden)

    Valderí de Castro Alcântara1

    2012-08-01

    Full Text Available Haja vista que a cultura de um país influencia a cultura organizacional das empresas nele presente e ainda é fator determinante no processo de internacionalização, torna-se relevante compreender e mensurar as características culturais de cada país. Os estudos de Hofstede (1984 apresentam uma metodologia útil para comparação entre culturas. Tal metodologia leva em consideração as características deuma cultura que possibilita diferenciar um país de outro. Dessa forma, é possível observar que determinados países compartilham certos traços culturais e, assim, é possível agrupá-los segundo critérios pré-estabelecidos. O presente trabalho objetiva utilizar-se de procedimentos estatísticos multivariados Clusters Analyses, K-Means Cluster Analysis e Análise Discriminante para determinar e validar agrupamentos de países, com base nas dimensões culturais de Hofstede (Distance Index, Individualism, Masculinity e Uncertainty Avoidance Index. Os resultados determinaram quatro clusters: Cluster 1 - países com cultura masculina e individualista; Cluster 2 - cultura coletivista e aversa à incerteza; Cluster 3 - cultura feminina e com baixa distância hierárquica; e Cluster 4 - cultura com elevada distância hierárquica e propensão à incerteza./ Considering that the culture of a country influences the organizational culture of this company and it is still a determining factor in the internationalization process becomes important to understand and measure the cultural characteristics of each country. The studies of Hofstede (1984 present a useful methodology for comparing cultures, this methodology takes into account the characteristics of a culturethat allows to differentiate one from another country. Thus one can observe that certain countries share certain cultural traits and so it is possible grouping them according to predetermined criteria. The present work aims to utilize multivariate statistical procedures Cluster Analyses

  10. A school-based intervention incorporating smartphone technology to improve health-related fitness among adolescents: rationale and study protocol for the NEAT and ATLAS 2.0 cluster randomised controlled trial and dissemination study.

    Science.gov (United States)

    Lubans, David R; Smith, Jordan J; Peralta, Louisa R; Plotnikoff, Ronald C; Okely, Anthony D; Salmon, Jo; Eather, Narelle; Dewar, Deborah L; Kennedy, Sarah; Lonsdale, Chris; Hilland, Toni A; Estabrooks, Paul; Finn, Tara L; Pollock, Emma; Morgan, Philip J

    2016-06-27

    Physical inactivity has been described as a global pandemic. Interventions aimed at developing skills in lifelong physical activities may provide the foundation for an active lifestyle into adulthood. In general, school-based physical activity interventions targeting adolescents have produced modest results and few have been designed to be 'scaled-up' and disseminated. This study aims to: (1) assess the effectiveness of two physical activity promotion programmes (ie, NEAT and ATLAS) that have been modified for scalability; and (2) evaluate the dissemination of these programmes throughout government funded secondary schools. The study will be conducted in two phases. In the first phase (cluster randomised controlled trial), 16 schools will be randomly allocated to the intervention or a usual care control condition. In the second phase, the Reach, Effectiveness, Adoption, Implementation and Maintenance (Re-AIM) framework will be used to guide the design and evaluation of programme dissemination throughout New South Wales (NSW), Australia. In both phases, teachers will be trained to deliver the NEAT and ATLAS programmes, which will include: (1) interactive student seminars; (2) structured physical activity programmes; (3) lunch-time fitness sessions; and (4) web-based smartphone apps. In the cluster RCT, study outcomes will be assessed at baseline, 6 months (primary end point) and 12-months. Muscular fitness will be the primary outcome and secondary outcomes will include: objectively measured body composition, cardiorespiratory fitness, flexibility, resistance training skill competency, physical activity, self-reported recreational screen-time, sleep, sugar-sweetened beverage and junk food snack consumption, self-esteem and well-being. This study has received approval from the University of Newcastle (H-2014-0312) and the NSW Department of Education (SERAP: 2012121) human research ethics committees. This study is funded by the Australian Research Council (FT

  11. Galaxy clusters and cosmology

    CERN Document Server

    White, S

    1994-01-01

    Galaxy clusters are the largest coherent objects in Universe. It has been known since 1933 that their dynamical properties require either a modification of the theory of gravity, or the presence of a dominant component of unseen material of unknown nature. Clusters still provide the best laboratories for studying the amount and distribution of this dark matter relative to the material which can be observed directly -- the galaxies themselves and the hot,X-ray-emitting gas which lies between them.Imaging and spectroscopy of clusters by satellite-borne X -ray telescopes has greatly improved our knowledge of the structure and composition of this intergalactic medium. The results permit a number of new approaches to some fundamental cosmological questions,but current indications from the data are contradictory. The observed irregularity of real clusters seems to imply recent formation epochs which would require a universe with approximately the critical density. On the other hand, the large baryon fraction observ...

  12. Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback

    Directory of Open Access Journals (Sweden)

    Haoting Liu

    2017-02-01

    Full Text Available An imaging sensor-based intelligent Light Emitting Diode (LED lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes.

  13. PROSPECTS OF THE REGIONAL INTEGRATION POLICY BASED ON CLUSTER FORMATION

    Directory of Open Access Journals (Sweden)

    Elena Tsepilova

    2018-01-01

    Full Text Available The purpose of this article is to develop the theoretical foundations of regional integration policy and to determine its prospects on the basis of cluster formation. The authors use such research methods as systematization, comparative and complex analysis, synthesis, statistical method. Within the framework of the research, the concept of regional integration policy is specified, and its integration core – cluster – is allocated. The authors work out an algorithm of regional clustering, which will ensure the growth of economy and tax income. Measures have been proposed to optimize the organizational mechanism of interaction between the participants of the territorial cluster and the authorities that allow to ensure the effective functioning of clusters, including taxation clusters. Based on the results of studying the existing methods for assessing the effectiveness of cluster policy, the authors propose their own approach to evaluating the consequences of implementing the regional integration policy, according to which the list of quantitative and qualitative indicators is defined. The present article systematizes the experience and results of the cluster policy of certain European countries, that made it possible to determine the prospects and synergetic effect from the development of clusters as an integration foundation of regional policy in the Russian Federation. The authors carry out the analysis of activity of cluster formations using the example of the Rostov region – a leader in the formation of conditions for the cluster policy development in the Southern Federal District. 11 clusters and cluster initiatives are developing in this region. As a result, the authors propose measures for support of the already existing clusters and creation of the new ones.

  14. A Web service substitution method based on service cluster nets

    Science.gov (United States)

    Du, YuYue; Gai, JunJing; Zhou, MengChu

    2017-11-01

    Service substitution is an important research topic in the fields of Web services and service-oriented computing. This work presents a novel method to analyse and substitute Web services. A new concept, called a Service Cluster Net Unit, is proposed based on Web service clusters. A service cluster is converted into a Service Cluster Net Unit. Then it is used to analyse whether the services in the cluster can satisfy some service requests. Meanwhile, the substitution methods of an atomic service and a composite service are proposed. The correctness of the proposed method is proved, and the effectiveness is shown and compared with the state-of-the-art method via an experiment. It can be readily applied to e-commerce service substitution to meet the business automation needs.

  15. TRUSTWORTHY OPTIMIZED CLUSTERING BASED TARGET DETECTION AND TRACKING FOR WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    C. Jehan

    2016-06-01

    Full Text Available In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN. The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the identification of clusters and cluster heads using OGSAFCM. Here, kernel fuzzy c-means (KFCM and gravitational search algorithm (GSA are combined to create clusters. At first, oppositional gravitational search algorithm (OGSA is used to optimize the initial clustering center and then the KFCM algorithm is availed to guide the classification and the cluster formation process. In the OGSA, the concept of the opposition based population initialization in the basic GSA to improve the convergence profile. The identified clusters are changed dynamically. The second step deals with the data transmission to the cluster heads. The third step deals with the transmission of aggregated data to the base station as well as the detection of target. From the experimental results, the proposed scheme efficiently and efficiently identifies the target. As a result the tracking error is minimized.

  16. Effect of Seizure Clustering on Epilepsy Outcome

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2008-05-01

    Full Text Available A prospective, long-term population-based study was performed to determine whether seizure clustering (3 or more afebrile seizures during a 24 hour period is associated with drug resistance and increased mortality in childhood-onset epilepsy, in a study at University of Turku, Finland, and the Epilepsy Research Group, Berlin, Germany.

  17. An improved initialization center k-means clustering algorithm based on distance and density

    Science.gov (United States)

    Duan, Yanling; Liu, Qun; Xia, Shuyin

    2018-04-01

    Aiming at the problem of the random initial clustering center of k means algorithm that the clustering results are influenced by outlier data sample and are unstable in multiple clustering, a method of central point initialization method based on larger distance and higher density is proposed. The reciprocal of the weighted average of distance is used to represent the sample density, and the data sample with the larger distance and the higher density are selected as the initial clustering centers to optimize the clustering results. Then, a clustering evaluation method based on distance and density is designed to verify the feasibility of the algorithm and the practicality, the experimental results on UCI data sets show that the algorithm has a certain stability and practicality.

  18. Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

    Science.gov (United States)

    Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

    2017-07-01

    Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

  19. Inhomogeneity of epidemic spreading with entropy-based infected clusters.

    Science.gov (United States)

    Wen-Jie, Zhou; Xing-Yuan, Wang

    2013-12-01

    Considering the difference in the sizes of the infected clusters in the dynamic complex networks, the normalized entropy based on infected clusters (δ*) is proposed to characterize the inhomogeneity of epidemic spreading. δ* gives information on the variability of the infected clusters in the system. We investigate the variation in the inhomogeneity of the distribution of the epidemic with the absolute velocity v of moving agent, the infection density ρ, and the interaction radius r. By comparing δ* in the dynamic networks with δH* in homogeneous mode, the simulation experiments show that the inhomogeneity of epidemic spreading becomes smaller with the increase of v, ρ, r.

  20. Effectiveness and feasibility of long-lasting insecticide-treated curtains and water container covers for dengue vector control in Colombia: a cluster randomised trial.

    Science.gov (United States)

    Quintero, Juliana; García-Betancourt, Tatiana; Cortés, Sebastian; García, Diana; Alcalá, Lucas; González-Uribe, Catalina; Brochero, Helena; Carrasquilla, Gabriel

    2015-02-01

    Long-lasting insecticide-treated net (LLIN) window and door curtains alone or in combination with LLIN water container covers were analysed regarding effectiveness in reducing dengue vector density, and feasibility of the intervention. A cluster randomised trial was conducted in an urban area of Colombia comparing 10 randomly selected control and 10 intervention clusters. In control clusters, routine vector control activities were performed. The intervention delivered first, LLIN curtains (from July to August 2013) and secondly, water container covers (from October to March 2014). Cross-sectional entomological surveys were carried out at baseline (February 2013 to June 2013), 9 weeks after the first intervention (August to October 2013), and 4-6 weeks after the second intervention (March to April 2014). Curtains were installed in 922 households and water container covers in 303 households. The Breteau index (BI) fell from 14 to 6 in the intervention group and from 8 to 5 in the control group. The additional intervention with LLIN covers for water containers showed a significant reduction in pupae per person index (PPI) (p=0.01). In the intervention group, the PPI index showed a clear decline of 71% compared with 25% in the control group. Costs were high but options for cost savings were identified. Short term impact evaluation indicates that the intervention package can reduce dengue vector density but sustained effect will depend on multiple factors. © The author 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.

  1. A community-based cluster randomized controlled trial (cRCT) to evaluate the impact and operational assessment of "safe motherhood and newborn health promotion package": study protocol.

    Science.gov (United States)

    Hoque, Dewan Md Emdadul; Chowdhury, Mohiuddin Ahsanul Kabir; Rahman, Ahmed Ehsanur; Billah, Sk Masum; Bari, Sanwarul; Tahsina, Tazeen; Hasan, Mohammad Mehedi; Islam, Sajia; Islam, Tajul; Mori, Rintaro; Arifeen, Shams El

    2018-05-03

    Despite considerable progress in reduction of both under-five and maternal mortality in recent decades, Bangladesh is still one of the low and middle income countries with high burden of maternal and neonatal mortality. The primary objective of the current study is to measure the impact of a comprehensive package of interventions on maternal and neonatal mortality. In addition, changes in coverage, quality and utilization of maternal and newborn health (MNH) services, social capital, and cost effectiveness of the interventions will be measured. A community-based, cluster randomized controlled trial design will be adopted and implemented in 30 unions of three sub-districts of Chandpur district of Bangladesh. Every union, the lowest administrative unit of the local government with population of around 20,000-30,000, will be considered a cluster. Based on the baseline estimates, 15 clusters will be paired for random assignment as intervention and comparison clusters. The primary outcome measure is neonatal mortality, and secondary outcomes are coverage of key interventions like ANC, PNC, facility and skilled provider delivery. Baseline, midterm and endline household survey will be conducted to assess the key coverage of interventions. Health facility assessment surveys will be conducted periodically to assess facility readiness and utilization of MNH services in the participating health facilities. The current study is expected to provide essential strong evidences on the impact of a comprehensive package of interventions to the Bangladesh government, and other developmental partners. The study results may help in prioritizing, planning, and scaling-up of Safe Motherhood Promotional interventions in other geographical areas of Bangladesh as well as to inform other developing countries of similar settings. NCT03032276 .

  2. A cluster randomised controlled trial to determine the clinical effectiveness and cost-effectiveness of classroom-based cognitive-behavioural therapy (CBT) in reducing symptoms of depression in high-risk adolescents.

    Science.gov (United States)

    Stallard, P; Phillips, R; Montgomery, A A; Spears, M; Anderson, R; Taylor, J; Araya, R; Lewis, G; Ukoumunne, O C; Millings, A; Georgiou, L; Cook, E; Sayal, K

    2013-10-01

    Depression in adolescents is a significant problem that impairs everyday functioning and increases the risk of severe mental health disorders in adulthood. Although this is a major problem, relatively few adolescents with, or at risk of developing, depression are identified and referred for treatment. This suggests the need to investigate alternative approaches whereby preventative interventions are made widely available in schools. To investigate the clinical effectiveness and cost-effectiveness of classroom-based cognitive-behavioural therapy (CBT) in reducing symptoms of depression in high-risk adolescents. Cluster randomised controlled trial. Year groups ( n = 28) randomly allocated on a 1 : 1 : 1 basis to one of three trial arms once all schools were recruited and balanced for number of classes, number of students, Personal, Social and Health Education (PSHE) lesson frequency, and scheduling of PSHE. Year groups 8 to 11 (ages 12-16 years) in mixed-sex secondary schools in the UK. Data were collected between 2009 and 2011. Young people who attended PSHE at participating schools were eligible ( n = 5503). Of the 5030 who agreed to participate, 1064 (21.2%) were classified as 'high risk': 392 in the classroom-based CBT arm, 374 in the attention control PSHE arm and 298 in the usual PSHE arm. Primary outcome data on the high-risk group at 12 months were available for classroom-based CBT ( n = 296), attention control PSHE ( n = 308) and usual PSHE ( n = 242). The Resourceful Adolescent Programme (RAP) is a focused CBT-based intervention adapted for the UK (RAP-UK) and delivered by two facilitators external to the school. Control groups were usual PSHE (usual school curriculum delivered by teachers) and attention control (usual school PSHE with additional support from two facilitators). Interventions were delivered universally to whole classes. Clinical effectiveness: symptoms of depression [Short Mood and Feelings Questionnaire (SMFQ)] in adolescents at high risk

  3. COMPARISON AND EVALUATION OF CLUSTER BASED IMAGE SEGMENTATION TECHNIQUES

    OpenAIRE

    Hetangi D. Mehta*, Daxa Vekariya, Pratixa Badelia

    2017-01-01

    Image segmentation is the classification of an image into different groups. Numerous algorithms using different approaches have been proposed for image segmentation. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. A review is done on different types of clustering methods used for image segmentation. Also a methodology is proposed to classify and quantify different clustering algorithms based on their consistency in different...

  4. A Coupled User Clustering Algorithm Based on Mixed Data for Web-Based Learning Systems

    Directory of Open Access Journals (Sweden)

    Ke Niu

    2015-01-01

    Full Text Available In traditional Web-based learning systems, due to insufficient learning behaviors analysis and personalized study guides, a few user clustering algorithms are introduced. While analyzing the behaviors with these algorithms, researchers generally focus on continuous data but easily neglect discrete data, each of which is generated from online learning actions. Moreover, there are implicit coupled interactions among the data but are frequently ignored in the introduced algorithms. Therefore, a mass of significant information which can positively affect clustering accuracy is neglected. To solve the above issues, we proposed a coupled user clustering algorithm for Wed-based learning systems by taking into account both discrete and continuous data, as well as intracoupled and intercoupled interactions of the data. The experiment result in this paper demonstrates the outperformance of the proposed algorithm.

  5. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    The cluster theory attributed to Michael Porter has significantly influenced industrial policies in countries across Europe and North America since the beginning of the 1990s. Institutions such as the EU, OECD and the World Bank and governments in countries such as the UK, France, The Netherlands...... or management. Both the Accelerate Wales and the Accelerate Cluster programmes target this issue by trying to establish networks between companies that can be used to supply knowledge from research institutions to manufacturing companies. The paper concludes that public sector interventions can make...... businesses. The universities were not considered by the participating companies to be important parts of the local business environment and inputs from universities did not appear to be an important source to access knowledge about new product development or new techniques in production, distribution...

  6. The Most Distant Mature Galaxy Cluster - Young, but surprisingly grown-up

    Science.gov (United States)

    2011-03-01

    Astronomers have used an armada of telescopes on the ground and in space, including the Very Large Telescope at ESO's Paranal Observatory in Chile to discover and measure the distance to the most remote mature cluster of galaxies yet found. Although this cluster is seen when the Universe was less than one quarter of its current age it looks surprisingly similar to galaxy clusters in the current Universe. "We have measured the distance to the most distant mature cluster of galaxies ever found", says the lead author of the study in which the observations from ESO's VLT have been used, Raphael Gobat (CEA, Paris). "The surprising thing is that when we look closely at this galaxy cluster it doesn't look young - many of the galaxies have settled down and don't resemble the usual star-forming galaxies seen in the early Universe." Clusters of galaxies are the largest structures in the Universe that are held together by gravity. Astronomers expect these clusters to grow through time and hence that massive clusters would be rare in the early Universe. Although even more distant clusters have been seen, they appear to be young clusters in the process of formation and are not settled mature systems. The international team of astronomers used the powerful VIMOS and FORS2 instruments on ESO's Very Large Telescope (VLT) to measure the distances to some of the blobs in a curious patch of very faint red objects first observed with the Spitzer space telescope. This grouping, named CL J1449+0856 [1], had all the hallmarks of being a very remote cluster of galaxies [2]. The results showed that we are indeed seeing a galaxy cluster as it was when the Universe was about three billion years old - less than one quarter of its current age [3]. Once the team knew the distance to this very rare object they looked carefully at the component galaxies using both the NASA/ESA Hubble Space Telescope and ground-based telescopes, including the VLT. They found evidence suggesting that most of the

  7. Network-based landscape of research strengths of universities in Mainland China

    Science.gov (United States)

    Liu, Zihua; Xiao, Qin; Zhan, Qian; Gu, Changgui; Yang, Huijie

    2017-07-01

    A landscape of a complex system presents a quantitative measure of its global state. The profile of research strength in Mainland China is investigated in detail, by which we illustrate a complex network based framework to extract a landscape from detailed records. First, a measure analogous to the Jaccard similarity is proposed to calculate from the presided funds similarities between the top-ranked universities. The neighbor threshold method is employed to reconstruct the similarity network of the universities. Second, the network is divided into communities. In each community the node with the largest degree and the smallest average shortest path length is taken as the representative of the community, called central node. The node bridging each pair of communities is defined to be a boundary. The central nodes and boundaries cooperatively give us a picture of the research strength landscape. Third, the evolutionary behavior is monitored by the fission and fusion probability matrices, elements of which are the percentage of a community at present time that joins into every community at the next time, and the percentage of a community at next time that comes from every present community, respectively. The landscapes in three successive 4-year durations are identified. It was found that some types of universities, such as the medicine&pharmacy and the finance&economy, conserve in single communities in the more than ten years, respectively. The agriculture&forest universities tend to cluster into one community. Meanwhile the engineering type distributes in different communities and tends to mix with the comprehension type. This framework can be used straightforwardly to analyze temporal networks. It provides also a new network-based method for multivariate time series analysis.

  8. Universal CNC platform motion control technology for industrial CT

    International Nuclear Information System (INIS)

    Cheng Senlin; Wang Yang

    2011-01-01

    According to the more scanning methods and the higher speed of industrial CT, the higher precision of the motion location and the data collection sync-control is required at present, a new motion control technology was proposed, which was established based on the universal CNC system with high precision of multi-axis control. Aiming at the second and the third generation of CT scanning motion, a control method was researched, and achieved the demands of the changeable parameters and network control, Through the simulation of the second and the third generation of CT scanning motion process, the control precision of the rotation axis reached 0.001° and the linear axis reached 0.002 mm, Practical tests showed this system can meet the requirements of the multi-axis motion integration and the sync signal control, it also have advantages in the control precision and the performance. (authors)

  9. Model-based Clustering of Categorical Time Series with Multinomial Logit Classification

    Science.gov (United States)

    Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Winter-Ebmer, Rudolf; Weber, Andrea

    2010-09-01

    A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance-based clustering methods cannot easily be extended to time series data, where an appropriate distance-measure is rather difficult to define, particularly for discrete-valued time series. Markov chain clustering, proposed by Pamminger and Frühwirth-Schnatter [6], is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This model-based clustering method is based on finite mixtures of first-order time-homogeneous Markov chain models. In order to further explain group membership we present an extension to the approach of Pamminger and Frühwirth-Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model. The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov chain Monte Carlo (MCMC) sampling scheme representing a (full) Gibbs-type sampler which involves only draws from standard distributions. Finally, an application to a panel of Austrian wage mobility data is presented which leads to an interesting segmentation of the Austrian labour market.

  10. Predictor-Year Subspace Clustering Based Ensemble Prediction of Indian Summer Monsoon

    Directory of Open Access Journals (Sweden)

    Moumita Saha

    2016-01-01

    Full Text Available Forecasting the Indian summer monsoon is a challenging task due to its complex and nonlinear behavior. A large number of global climatic variables with varying interaction patterns over years influence monsoon. Various statistical and neural prediction models have been proposed for forecasting monsoon, but many of them fail to capture variability over years. The skill of predictor variables of monsoon also evolves over time. In this article, we propose a joint-clustering of monsoon years and predictors for understanding and predicting the monsoon. This is achieved by subspace clustering algorithm. It groups the years based on prevailing global climatic condition using statistical clustering technique and subsequently for each such group it identifies significant climatic predictor variables which assist in better prediction. Prediction model is designed to frame individual cluster using random forest of regression tree. Prediction of aggregate and regional monsoon is attempted. Mean absolute error of 5.2% is obtained for forecasting aggregate Indian summer monsoon. Errors in predicting the regional monsoons are also comparable in comparison to the high variation of regional precipitation. Proposed joint-clustering based ensemble model is observed to be superior to existing monsoon prediction models and it also surpasses general nonclustering based prediction models.

  11. An improvement of speed control performances of a two-mass system using a universal approximator

    DEFF Research Database (Denmark)

    Lee, Kyo Beum; Blåbjerg, Frede

    2007-01-01

    A new control scheme using a universal approximator based on a radial basis ti.tnction network (RBFN) is proposed and investigated for improving the control characteristics of the high-performance motion control system. This control method presents better performance in the corresponding speed vi...

  12. Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments

    Directory of Open Access Journals (Sweden)

    Wen Liu

    2016-12-01

    Full Text Available Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS. Due to the absence of satellite signal in Global Navigation Satellite System (GNSS, various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP, which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC, is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1 and the XiDan Joy City (Floors 1 and 2, as Test-bed 2, and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

  13. Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments.

    Science.gov (United States)

    Liu, Wen; Fu, Xiao; Deng, Zhongliang

    2016-12-02

    Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

  14. Clustering of 18 Local Black Rice Base on Total Anthocyanin

    Directory of Open Access Journals (Sweden)

    Kristamtini Kristamtini

    2017-10-01

    Full Text Available Black rice has a high anthocyanin content in the pericarp layer, which provides a dark purple color. Anthocyanin serve as an antioxidant that control cholesterol level in the blood, prevent anemia, potentially improve the body's resistance to disease, improve damage to liver cells (hepatitis and chirrosis, prevent impaired kidney function, prevent cancer/tumors, slows down antiaging, and prevent atherosclerosis and cardiovascular disease. Exploration results at AIAT Yogyakarta, Indonesia from 2011 to 2014 obtained 18 cultivar of local black rice Indonesia. The names of the rice are related to the color (black, red or purple formed by anthocyanin deposits in the pericarp layer, seed coat or aleuron. The objective of the study was to classify several types of local black rice from explorations based on the total anthocyanin content. The study was conducted by clustering analyzing the total anthocyanin content of 18 local black rice cultivars in Indonesia. Cluster analysis of total anthocyanin content were done using SAS ver. 9.2. Clustering dendogram shows that there were 4 groups of black rice cultivars based on the total anthocyanin content. Group I consists of Melik black rice, Patalan black rice, Yunianto black rice, Muharjo black rice, Ngatijo black rice, short life of Tugiyo black rice, Andel hitam 1, Jlitheng, and Sragen black rice. Group II consists of Pari ireng, Magelang black hairy rice, Banjarnegara-Wonosobo black rice, and Banjarnegara black rice. Group III consists of NTT black rice, Magelang non hairy black rice, Sembada hitam, and longevity Tugiyo black rice. Group IV consist only one type of black rice namely Cempo ireng. The grouping result indicate the existence of duplicate names among the black rice namely Patalan with Yunianto black rice, and short life Tugiyo with Andel hitam 1 black rice.

  15. Enacs Survey of Southern Galaxies Indicates Open Universe

    Science.gov (United States)

    1996-02-01

    hundreds, in some cases even thousands of galaxies (each with many billions of stars and much interstellar matter), they also contain hot gas (with a temperature of several million degrees) which is best visible in X-rays, as well as the invisible dark matter just mentioned. In fact, these clusters are the largest and most massive objects that are known today, and a detailed study of their properties can therefore provide insight into the way in which large-scale structures in the Universe have formed. This unique information is encoded into the distribution of the clusters' total masses, of their physical shapes, and not the least in the way they are distributed in space. The need for a `complete' cluster sample Several of these fundamental questions can be studied by observing a few, or at the most several tens of well-chosen clusters. However, if the goal is to discriminate between the various proposed theories of formation of their spatial distribution and thus the Universe's large-scale structure, it is essential that uniform data is collected for a sample of clusters that is complete in a statistical sense. Only then will it be possible to determine reliably the distribution of cluster masses and shapes, etc. For such comprehensive investigations, `complete' samples of clusters (that is, brighter than a certain magnitude and located within a given area in the sky) can be compiled either by means of catalogues like the one published by Abell and his collaborators and based on the distribution of optically selected galaxies, or from large-scale surveys of X-ray sources. However, in both cases, it is of paramount importance to verify the physical reality of the presumed clusters. Sometimes several galaxies are seen in nearly the same direction and therefore appear to form a cluster, but it later turns out that they are at very different distances and do not form a physical entity. This control must be performed through spectroscopic observations of the galaxies in the

  16. Comparison of Skin Moisturizer: Consumer-Based Brand Equity (CBBE Factors in Clusters Based on Consumer Ethnocentrism

    Directory of Open Access Journals (Sweden)

    Yossy Hanna Garlina

    2014-09-01

    Full Text Available This research aims to analyze relevant factors contributing to the four dimensions of consumer-based brand equity in skin moisturizer industry. It is then followed by the clustering of female consumers of skin moisturizer based on ethnocentrism and differentiating each cluster’s consumer-based brand equity dimensions towards a domestic skin moisturizer brand Mustika Ratu, skin moisturizer. Research used descriptive survey method analysis. Primary data was obtained through questionnaire distribution to 70 female respondents for factor analysis and 120 female respondents for cluster analysis and one way analysis of variance (ANOVA. This research employed factor analysis to obtain relevant factors contributing to the five dimensions of consumer-based brand equity in skin moisturizer industry. Cluster analysis and one way analysis of variance (ANOVA were to see the difference of consumer-based brand equity between highly ethnocentric consumer and low ethnocentric consumer towards the same skin moisturizer domestic brand, Mustika Ratu skin moisturizer. Research found in all individual dimension analysis, all variable means and individual means show distinct difference between the high ethnocentric consumer and the low ethnocentric consumer. The low ethnocentric consumer cluster tends to be lower in mean score of Brand Loyalty, Perceived Quality, Brand Awareness, Brand Association, and Overall Brand Equity than the high ethnocentric consumer cluster. Research concludes consumer ethnocentrism is positively correlated with preferences towards domestic products and negatively correlated with foreign-made product preference. It is, then, highly ethnocentric consumers have positive perception towards domestic product.

  17. FRCA: A Fuzzy Relevance-Based Cluster Head Selection Algorithm for Wireless Mobile Ad-Hoc Sensor Networks

    Directory of Open Access Journals (Sweden)

    Taegwon Jeong

    2011-05-01

    Full Text Available Clustering is an important mechanism that efficiently provides information for mobile nodes and improves the processing capacity of routing, bandwidth allocation, and resource management and sharing. Clustering algorithms can be based on such criteria as the battery power of nodes, mobility, network size, distance, speed and direction. Above all, in order to achieve good clustering performance, overhead should be minimized, allowing mobile nodes to join and leave without perturbing the membership of the cluster while preserving current cluster structure as much as possible. This paper proposes a Fuzzy Relevance-based Cluster head selection Algorithm (FRCA to solve problems found in existing wireless mobile ad hoc sensor networks, such as the node distribution found in dynamic properties due to mobility and flat structures and disturbance of the cluster formation. The proposed mechanism uses fuzzy relevance to select the cluster head for clustering in wireless mobile ad hoc sensor networks. In the simulation implemented on the NS-2 simulator, the proposed FRCA is compared with algorithms such as the Cluster-based Routing Protocol (CBRP, the Weighted-based Adaptive Clustering Algorithm (WACA, and the Scenario-based Clustering Algorithm for Mobile ad hoc networks (SCAM. The simulation results showed that the proposed FRCA achieves better performance than that of the other existing mechanisms.

  18. FRCA: a fuzzy relevance-based cluster head selection algorithm for wireless mobile ad-hoc sensor networks.

    Science.gov (United States)

    Lee, Chongdeuk; Jeong, Taegwon

    2011-01-01

    Clustering is an important mechanism that efficiently provides information for mobile nodes and improves the processing capacity of routing, bandwidth allocation, and resource management and sharing. Clustering algorithms can be based on such criteria as the battery power of nodes, mobility, network size, distance, speed and direction. Above all, in order to achieve good clustering performance, overhead should be minimized, allowing mobile nodes to join and leave without perturbing the membership of the cluster while preserving current cluster structure as much as possible. This paper proposes a Fuzzy Relevance-based Cluster head selection Algorithm (FRCA) to solve problems found in existing wireless mobile ad hoc sensor networks, such as the node distribution found in dynamic properties due to mobility and flat structures and disturbance of the cluster formation. The proposed mechanism uses fuzzy relevance to select the cluster head for clustering in wireless mobile ad hoc sensor networks. In the simulation implemented on the NS-2 simulator, the proposed FRCA is compared with algorithms such as the Cluster-based Routing Protocol (CBRP), the Weighted-based Adaptive Clustering Algorithm (WACA), and the Scenario-based Clustering Algorithm for Mobile ad hoc networks (SCAM). The simulation results showed that the proposed FRCA achieves better performance than that of the other existing mechanisms.

  19. Dynamical aspects of galaxy clustering

    International Nuclear Information System (INIS)

    Fall, S.M.

    1980-01-01

    Some recent work on the origin and evolution of galaxy clustering is reviewed, particularly within the context of the gravitational instability theory and the hot big-bang cosmological model. Statistical measures of clustering, including correlation functions and multiplicity functions, are explained and discussed. The close connection between galaxy formation and clustering is emphasized. Additional topics include the dependence of galaxy clustering on the spectrum of primordial density fluctuations and the mean mass density of the Universe. (author)

  20. Hierarchical MAS based control strategy for microgrid

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Z.; Li, T.; Huang, M.; Shi, J.; Yang, J.; Yu, J. [School of Information Science and Engineering, Yunnan University, Kunming 650091 (China); Xiao, Z. [School of Electrical and Electronic Engineering, Nanyang Technological University, Western Catchment Area, 639798 (Singapore); Wu, W. [Communication Branch of Yunnan Power Grid Corporation, Kunming, Yunnan 650217 (China)

    2010-09-15

    Microgrids have become a hot topic driven by the dual pressures of environmental protection concerns and the energy crisis. In this paper, a challenge for the distributed control of a modern electric grid incorporating clusters of residential microgrids is elaborated and a hierarchical multi-agent system (MAS) is proposed as a solution. The issues of how to realize the hierarchical MAS and how to improve coordination and control strategies are discussed. Based on MATLAB and ZEUS platforms, bilateral switching between grid-connected mode and island mode is performed under control of the proposed MAS to enhance and support its effectiveness. (authors)

  1. AES based secure low energy adaptive clustering hierarchy for WSNs

    Science.gov (United States)

    Kishore, K. R.; Sarma, N. V. S. N.

    2013-01-01

    Wireless sensor networks (WSNs) provide a low cost solution in diversified application areas. The wireless sensor nodes are inexpensive tiny devices with limited storage, computational capability and power. They are being deployed in large scale in both military and civilian applications. Security of the data is one of the key concerns where large numbers of nodes are deployed. Here, an energy-efficient secure routing protocol, secure-LEACH (Low Energy Adaptive Clustering Hierarchy) for WSNs based on the Advanced Encryption Standard (AES) is being proposed. This crypto system is a session based one and a new session key is assigned for each new session. The network (WSN) is divided into number of groups or clusters and a cluster head (CH) is selected among the member nodes of each cluster. The measured data from the nodes is aggregated by the respective CH's and then each CH relays this data to another CH towards the gateway node in the WSN which in turn sends the same to the Base station (BS). In order to maintain confidentiality of data while being transmitted, it is necessary to encrypt the data before sending at every hop, from a node to the CH and from the CH to another CH or to the gateway node.

  2. REGIONAL DEVELOPMENT BASED ON CLUSTER IN LIVESTOCK DEVELOPMENT. CLUSTER IN LIVESTOCK SECTOR IN THE KYRGYZ REPUBLIC

    Directory of Open Access Journals (Sweden)

    Meerim SYDYKOVA

    2014-11-01

    Full Text Available In most developing countries, where agriculture is the main economical source, clusters have been found as a booster to develop their economy. The Asian countries are now starting to implement agro-food clusters into the mainstream of changes in agriculture, farming and food industry. The long-term growth of meat production in the Kyrgyz Republic during the last decade, as well as the fact that agriculture has become one of the prioritized sectors of the economy, proved the importance of livestock sector in the economy of the Kyrgyz Republic. The research question is “Does the Kyrgyz Republic has strong economic opportunities and prerequisites in agriculture in order to implement an effective agro cluster in the livestock sector?” Paper focuses on describing the prerequisites of the Kyrgyz Republic in agriculture to implement livestock cluster. The main objective of the paper is to analyse the livestock sector of the Kyrgyz Republic and observe the capacity of this sector to implement agro-cluster. The study focuses on investigating livestock sector and a complex S.W.O.T. The analysis was carried out based on local and regional database and official studies. The results of research demonstrate the importance of livestock cluster for national economy. It can be concluded that cluster implementation could provide to its all members with benefits if they could build strong collaborative relationship in order to facilitate the access to the labour market and implicitly, the access to exchange of good practices. Their ability of potential cluster members to act as a convergence pole is critical for acquiring practical skills necessary for the future development of the livestock sector.

  3. Feature Selection and Kernel Learning for Local Learning-Based Clustering.

    Science.gov (United States)

    Zeng, Hong; Cheung, Yiu-ming

    2011-08-01

    The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.

  4. Effectiveness of home-based nutritional counselling and support on exclusive breastfeeding in urban poor settings in Nairobi: a cluster randomized controlled trial.

    Science.gov (United States)

    Kimani-Murage, Elizabeth W; Griffiths, Paula L; Wekesah, Frederick Murunga; Wanjohi, Milka; Muhia, Nelson; Muriuki, Peter; Egondi, Thaddaeus; Kyobutungi, Catherine; Ezeh, Alex C; McGarvey, Stephen T; Musoke, Rachel N; Norris, Shane A; Madise, Nyovani J

    2017-12-19

    Exclusive breastfeeding (EBF) improves infant health and survival. We tested the effectiveness of a home-based intervention using Community Health Workers (CHWs) on EBF for six months in urban poor settings in Kenya. We conducted a cluster-randomized controlled trial in Korogocho and Viwandani slums in Nairobi. We recruited pregnant women and followed them until the infant's first birthday. Fourteen community clusters were randomized to intervention or control arm. The intervention arm received home-based nutritional counselling during scheduled visits by CHWs trained to provide specific maternal infant and young child nutrition (MIYCN) messages and standard care. The control arm was visited by CHWs who were not trained in MIYCN and they provided standard care (which included aspects of ante-natal and post-natal care, family planning, water, sanitation and hygiene, delivery with skilled attendance, immunization and community nutrition). CHWs in both groups distributed similar information materials on MIYCN. Differences in EBF by intervention status were tested using chi square and logistic regression, employing intention-to-treat analysis. A total of 1110 mother-child pairs were involved, about half in each arm. At baseline, demographic and socioeconomic factors were similar between the two arms. The rates of EBF for 6 months increased from 2% pre-intervention to 55.2% (95% CI 50.4-59.9) in the intervention group and 54.6% (95% CI 50.0-59.1) in the control group. The adjusted odds of EBF (after adjusting for baseline characteristics) were slightly higher in the intervention arm compared to the control arm but not significantly different: for 0-2 months (OR 1.27, 95% CI 0.55 to 2.96; p = 0.550); 0-4 months (OR 1.15; 95% CI 0.54 to 2.42; p = 0.696), and 0-6 months (OR 1.11, 95% CI 0.61 to 2.02; p = 0.718). EBF for six months significantly increased in both arms indicating potential effectiveness of using CHWs to provide home-based counselling to

  5. Galaxy clusters in the SDSS Stripe 82 based on photometric redshifts

    International Nuclear Information System (INIS)

    Durret, F.; Adami, C.; Bertin, E.; Hao, J.; Márquez, I.

    2015-01-01

    Based on a recent photometric redshift galaxy catalogue, we have searched for galaxy clusters in the Stripe ~82 region of the Sloan Digital Sky Survey by applying the Adami & MAzure Cluster FInder (AMACFI). Extensive tests were made to fine-tune the AMACFI parameters and make the cluster detection as reliable as possible. The same method was applied to the Millennium simulation to estimate our detection efficiency and the approximate masses of the detected clusters. Considering all the cluster galaxies (i.e. within a 1 Mpc radius of the cluster to which they belong and with a photoz differing by less than 0.05 from that of the cluster), we stacked clusters in various redshift bins to derive colour-magnitude diagrams and galaxy luminosity functions (GLFs). For each galaxy with absolute magnitude brighter than -19.0 in the r band, we computed the disk and spheroid components by applying SExtractor, and by stacking clusters we determined how the disk-to-spheroid flux ratio varies with cluster redshift and mass. We also detected 3663 clusters in the redshift range 0.15< z<0.70, with estimated mean masses between 10"1"3 and a few 10"1"4 solar masses. Furthermore, by stacking the cluster galaxies in various redshift bins, we find a clear red sequence in the (g'-r') versus r' colour-magnitude diagrams, and the GLFs are typical of clusters, though with a possible contamination from field galaxies. The morphological analysis of the cluster galaxies shows that the fraction of late-type to early-type galaxies shows an increase with redshift (particularly in high mass clusters) and a decrease with detection level, i.e. cluster mass. From the properties of the cluster galaxies, the majority of the candidate clusters detected here seem to be real clusters with typical cluster properties.

  6. Clusters of Galaxies

    Science.gov (United States)

    Huchtmeier, W. K.; Richter, O. G.; Materne, J.

    1981-09-01

    The large-scale structure of the universe is dominated by clustering. Most galaxies seem to be members of pairs, groups, clusters, and superclusters. To that degree we are able to recognize a hierarchical structure of the universe. Our local group of galaxies (LG) is centred on two large spiral galaxies: the Andromeda nebula and our own galaxy. Three sr:naller galaxies - like M 33 - and at least 23 dwarf galaxies (KraanKorteweg and Tammann, 1979, Astronomische Nachrichten, 300, 181) can be found in the evironment of these two large galaxies. Neighbouring groups have comparable sizes (about 1 Mpc in extent) and comparable numbers of bright members. Small dwarf galaxies cannot at present be observed at great distances.

  7. Cluster-based localization and tracking in ubiquitous computing systems

    CERN Document Server

    Martínez-de Dios, José Ramiro; Torres-González, Arturo; Ollero, Anibal

    2017-01-01

    Localization and tracking are key functionalities in ubiquitous computing systems and techniques. In recent years a very high variety of approaches, sensors and techniques for indoor and GPS-denied environments have been developed. This book briefly summarizes the current state of the art in localization and tracking in ubiquitous computing systems focusing on cluster-based schemes. Additionally, existing techniques for measurement integration, node inclusion/exclusion and cluster head selection are also described in this book.

  8. Support Policies in Clusters: Prioritization of Support Needs by Cluster Members According to Cluster Life Cycle

    Directory of Open Access Journals (Sweden)

    Gulcin Salıngan

    2012-07-01

    Full Text Available Economic development has always been a moving target. Both the national and local governments have been facing the challenge of implementing the effective and efficient economic policy and program in order to best utilize their limited resources. One of the recent approaches in this area is called cluster-based economic analysis and strategy development. This study reviews key literature and some of the cluster based economic policies adopted by different governments. Based on this review, it proposes “the cluster life cycle” as a determining factor to identify the support requirements of clusters. A survey, designed based on literature review of International Cluster support programs, was conducted with 30 participants from 3 clusters with different maturity stage. This paper discusses the results of this study conducted among the cluster members in Eskişehir- Bilecik-Kütahya Region in Turkey on the requirement of the support to foster the development of related clusters.

  9. FPGA cluster for high-performance AO real-time control system

    Science.gov (United States)

    Geng, Deli; Goodsell, Stephen J.; Basden, Alastair G.; Dipper, Nigel A.; Myers, Richard M.; Saunter, Chris D.

    2006-06-01

    Whilst the high throughput and low latency requirements for the next generation AO real-time control systems have posed a significant challenge to von Neumann architecture processor systems, the Field Programmable Gate Array (FPGA) has emerged as a long term solution with high performance on throughput and excellent predictability on latency. Moreover, FPGA devices have highly capable programmable interfacing, which lead to more highly integrated system. Nevertheless, a single FPGA is still not enough: multiple FPGA devices need to be clustered to perform the required subaperture processing and the reconstruction computation. In an AO real-time control system, the memory bandwidth is often the bottleneck of the system, simply because a vast amount of supporting data, e.g. pixel calibration maps and the reconstruction matrix, need to be accessed within a short period. The cluster, as a general computing architecture, has excellent scalability in processing throughput, memory bandwidth, memory capacity, and communication bandwidth. Problems, such as task distribution, node communication, system verification, are discussed.

  10. Statistical Significance for Hierarchical Clustering

    Science.gov (United States)

    Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

    2017-01-01

    Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

  11. Clustering-based analysis for residential district heating data

    DEFF Research Database (Denmark)

    Gianniou, Panagiota; Liu, Xiufeng; Heller, Alfred

    2018-01-01

    The wide use of smart meters enables collection of a large amount of fine-granular time series, which can be used to improve the understanding of consumption behavior and used for consumption optimization. This paper presents a clustering-based knowledge discovery in databases method to analyze r....... These findings will be valuable for district heating utilities and energy planners to optimize their operations, design demand-side management strategies, and develop targeting energy-efficiency programs or policies.......The wide use of smart meters enables collection of a large amount of fine-granular time series, which can be used to improve the understanding of consumption behavior and used for consumption optimization. This paper presents a clustering-based knowledge discovery in databases method to analyze...... residential heating consumption data and evaluate information included in national building databases. The proposed method uses the K-means algorithm to segment consumption groups based on consumption intensity and representative patterns and ranks the groups according to daily consumption. This paper also...

  12. The OGCleaner: filtering false-positive homology clusters.

    Science.gov (United States)

    Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Snell, Quinn; Bybee, Seth M

    2017-01-01

    Detecting homologous sequences in organisms is an essential step in protein structure and function prediction, gene annotation and phylogenetic tree construction. Heuristic methods are often employed for quality control of putative homology clusters. These heuristics, however, usually only apply to pairwise sequence comparison and do not examine clusters as a whole. We present the Orthology Group Cleaner (the OGCleaner), a tool designed for filtering putative orthology groups as homology or non-homology clusters by considering all sequences in a cluster. The OGCleaner relies on high-quality orthologous groups identified in OrthoDB to train machine learning algorithms that are able to distinguish between true-positive and false-positive homology groups. This package aims to improve the quality of phylogenetic tree construction especially in instances of lower-quality transcriptome assemblies. https://github.com/byucsl/ogcleaner CONTACT: sfujimoto@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. A semantics-based method for clustering of Chinese web search results

    Science.gov (United States)

    Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

    2014-01-01

    Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

  14. A clustering approach to segmenting users of internet-based risk calculators.

    Science.gov (United States)

    Harle, C A; Downs, J S; Padman, R

    2011-01-01

    Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

  15. Trial for the Prevention of Depression (TriPoD) in final-year secondary students: study protocol for a cluster randomised controlled trial.

    Science.gov (United States)

    Perry, Yael; Calear, Alison L; Mackinnon, Andrew; Batterham, Philip J; Licinio, Julio; King, Catherine; Thomsen, Noel; Scott, Jan; Donker, Tara; Merry, Sally; Fleming, Theresa; Stasiak, Karolina; Werner-Seidler, Aliza; Christensen, Helen

    2015-10-12

    Evidence suggests that current treatments cannot fully alleviate the burden of disease associated with depression but that prevention approaches offer a promising opportunity to further reduce this burden. Adolescence is a critical period in the development of mental illness, and final school examinations are a significant and nearly universal stressor that may act as a trigger for mental health difficulties such as depression. The aim of the present trial is to investigate the impact of SPARX-R, an online, gamified intervention based on cognitive behavioural principles, on the prevention of depression in secondary school students before their final examinations. Government, independent and Catholic secondary schools in New South Wales, Australia, will be recruited to participate in the trial. All students enrolled in their final year of high school (year 12) in participating schools will be invited to participate. To account for possible attrition, the target sample size was set at 1600 participants across 30 schools. Participating schools will be cluster randomised at the school level to receive either SPARX-R or lifeSTYLE, an attention-controlled placebo comparator. The control intervention is an online program aimed at maintaining a healthy lifestyle. The primary outcome will be symptoms of depression, and secondary outcomes will include symptoms of anxiety, suicidal ideation and behaviours, stigma and academic performance. Additional measures of cost-effectiveness, as well as process variables (e.g., adherence, acceptability) and potential predictors of response to treatment, will be collected. Consenting parents will be invited to complete measures regarding their own mental health and expectations for their child. Assessments will be conducted pre- and post-intervention and at 6- and 18-month follow-up. Primary analyses will compare changes in levels of depressive symptomatology for the intervention group relative to the attention control condition using

  16. The nanocoherer: an electrically and mechanically resettable resistive switching device based on gold clusters assembled on paper

    Science.gov (United States)

    Minnai, Chloé; Mirigliano, Matteo; Brown, Simon A.; Milani, Paolo

    2018-03-01

    We report the realization of a resettable resistive switching device based on a nanostructured film fabricated by supersonic cluster beam deposition of gold clusters on plain paper substrates. Through the application of suitable voltage ramps, we obtain, in the same device, either a complex pattern of resistive switchings, or reproducible and stable switchings between low resistance and high resistance states, with an amplitude up to five orders of magnitude. Our device retains a state of internal resistance following the history of the applied voltage similar to that reported for memristors. The two different switching regimes in the same device are both stable, the transition between them is reversible, and it can be controlled by applying voltage ramps or by mechanical deformation of the substrate. The device behavior can be related to the formation, growth and breaking of junctions between the loosely aggregated gold clusters forming the nanostructured films. The fact that our cluster-assembled device is mechanically resettable suggests that it can be considered as the analog of the coherer: a switching device based on metallic powders used for the first radio communication system.

  17. FORMATION OF A INNOVATION REGIONAL CLUSTER MODEL

    Directory of Open Access Journals (Sweden)

    G. S. Merzlikina

    2015-01-01

    Full Text Available Summary. As a result of investigation of science and methodical approaches related problems of building and development of innovation clusters there were some issues in functional assignments of innovation and production clusters. Because of those issues, article’s authors differ conceptions of innovation cluster and production cluster, as they explain notion of innovation-production cluster. The main goal of this article is to reveal existing organizational issues in cluster building and its successful development. Based on regional clusters building analysis carried out there was typical practical structure of cluster members interaction revealed. This structure also have its cons, as following: absence cluster orientation to marketing environment, lack of members’ prolonged relations’ building and development system, along with ineffective management of information, financial and material streams within cluster, narrow competence difference and responsibility zones between cluster members, lack of transparence of cluster’s action, low environment changes adaptivity, hard to use cluster members’ intellectual property, and commercialization of hi-tech products. When all those issues listed above come together, it reduces life activity of existing models of innovative cluster-building along with practical opportunity of cluster realization. Because of that, authors offer an upgraded innovative-productive cluster building model with more efficient business processes management system, which includes advanced innovative cluster structure, competence matrix and subcluster responsibility zone. Suggested model differs from other ones by using unified innovative product development control center, which also controls production and marketing realization.

  18. On Two Mixture-Based Clustering Approaches Used in Modeling an Insurance Portfolio

    Directory of Open Access Journals (Sweden)

    Tatjana Miljkovic

    2018-05-01

    Full Text Available We review two complementary mixture-based clustering approaches for modeling unobserved heterogeneity in an insurance portfolio: the generalized linear mixed cluster-weighted model (CWM and mixture-based clustering for an ordered stereotype model (OSM. The latter is for modeling of ordinal variables, and the former is for modeling losses as a function of mixed-type of covariates. The article extends the idea of mixture modeling to a multivariate classification for the purpose of testing unobserved heterogeneity in an insurance portfolio. The application of both methods is illustrated on a well-known French automobile portfolio, in which the model fitting is performed using the expectation-maximization (EM algorithm. Our findings show that these mixture-based clustering methods can be used to further test unobserved heterogeneity in an insurance portfolio and as such may be considered in insurance pricing, underwriting, and risk management.

  19. A novel artificial bee colony based clustering algorithm for categorical data.

    Science.gov (United States)

    Ji, Jinchao; Pang, Wei; Zheng, Yanlin; Wang, Zhe; Ma, Zhiqiang

    2015-01-01

    Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data.

  20. Clustering of galaxies with f(R) gravity

    Science.gov (United States)

    Capozziello, Salvatore; Faizal, Mir; Hameeda, Mir; Pourhassan, Behnam; Salzano, Vincenzo; Upadhyay, Sudhaker

    2018-02-01

    Based on thermodynamics, we discuss the galactic clustering of expanding Universe by assuming the gravitational interaction through the modified Newton's potential given by f(R) gravity. We compute the corrected N-particle partition function analytically. The corrected partition function leads to more exact equations of state of the system. By assuming that the system follows quasi-equilibrium, we derive the exact distribution function that exhibits the f(R) correction. Moreover, we evaluate the critical temperature and discuss the stability of the system. We observe the effects of correction of f(R) gravity on the power-law behaviour of particle-particle correlation function also. In order to check the feasibility of an f(R) gravity approach to the clustering of galaxies, we compare our results with an observational galaxy cluster catalogue.

  1. Academic Quality Control in Nigerian Universities: Exploring Lecturers' Perceptions

    Science.gov (United States)

    Obiekezie, E. O.; Ejemot-Nwadiaro, R. I.; Essien, M. I.; Timothy, A. Essien

    2014-01-01

    The level of job performance, international comparability and competitiveness of Nigerian university graduates are burning issues. Consequently, the academic quality of Nigerian universities has come under severe criticism. Since university lecturers are key players in quality control in universities, this study explored their perceptions of…

  2. Beverages-Food Industry Cluster Development Based on Value Chain in Indonesia

    OpenAIRE

    Lasmono Tri Sunaryanto; Gatot Sasongko; Ira Yumastuti

    2014-01-01

    This study wants to develop the cluster-based food and beverage industry value chain that corresponds to the potential in the regions in Java Economic Corridor. Targeted research: a description of SME development strategies that have been implemented, composed, and can be applied to an SME cluster development strategy of food and beverage, as well as a proven implementation strategy of SME cluster development of food and beverage. To achieve these objectives, implemented descriptive methods, ...

  3. Controllable irregular melting induced by atomic segregation in bimetallic clusters with fabricating different initial configurations

    International Nuclear Information System (INIS)

    Li Guojian; Liu Tie; Wang Qiang; Lue Xiao; Wang Kai; He Jicheng

    2010-01-01

    The melting process of Co, Co-Cu and Co-Ni clusters with different initial configurations is studied in molecular dynamics by a general embedded atom method. An irregular melting, at which energy decreases as the temperature increase near the melting point, is found in the onion-like Co-Cu-Co clusters, but not in the mixed Co-Cu and onion-like Co-Ni-Co clusters. From the analysis of atomic distributions and energy variation, the results indicate the irregular melting is induced by Cu atomic segregation. Furthermore, this melting can be controlled by doping hetero atoms with different surface energies and controlling their distributions.

  4. INTERSECTION DETECTION BASED ON QUALITATIVE SPATIAL REASONING ON STOPPING POINT CLUSTERS

    Directory of Open Access Journals (Sweden)

    S. Zourlidou

    2016-06-01

    Full Text Available The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location – thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

  5. Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

    Science.gov (United States)

    Chen, Xin; Liu, Li; Zhou, Sida; Yue, Zhenjiang

    2016-09-01

    Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.

  6. Reducing child conduct problems and promoting social skills in a middle-income country: cluster randomised controlled trial.

    Science.gov (United States)

    Baker-Henningham, Helen; Scott, Stephen; Jones, Kelvyn; Walker, Susan

    2012-08-01

    There is an urgent need for effective, affordable interventions to prevent child mental health problems in low- and middle-income countries. To determine the effects of a universal pre-school-based intervention on child conduct problems and social skills at school and at home. In a cluster randomised design, 24 community pre-schools in inner-city areas of Kingston, Jamaica, were randomly assigned to receive the Incredible Years Teacher Training intervention (n = 12) or to a control group (n = 12). Three children from each class with the highest levels of teacher-reported conduct problems were selected for evaluation, giving 225 children aged 3-6 years. The primary outcome was observed child behaviour at school. Secondary outcomes were child behaviour by parent and teacher report, child attendance and parents' attitude to school. The study is registered as ISRCTN35476268. Children in intervention schools showed significantly reduced conduct problems (effect size (ES) = 0.42) and increased friendship skills (ES = 0.74) through observation, significant reductions to teacher-reported (ES = 0.47) and parent-reported (ES = 0.22) behaviour difficulties and increases in teacher-reported social skills (ES = 0.59) and child attendance (ES = 0.30). Benefits to parents' attitude to school were not significant. A low-cost, school-based intervention in a middle-income country substantially reduces child conduct problems and increases child social skills at home and at school.

  7. Developing a Clustering-Based Empirical Bayes Analysis Method for Hotspot Identification

    Directory of Open Access Journals (Sweden)

    Yajie Zou

    2017-01-01

    Full Text Available Hotspot identification (HSID is a critical part of network-wide safety evaluations. Typical methods for ranking sites are often rooted in using the Empirical Bayes (EB method to estimate safety from both observed crash records and predicted crash frequency based on similar sites. The performance of the EB method is highly related to the selection of a reference group of sites (i.e., roadway segments or intersections similar to the target site from which safety performance functions (SPF used to predict crash frequency will be developed. As crash data often contain underlying heterogeneity that, in essence, can make them appear to be generated from distinct subpopulations, methods are needed to select similar sites in a principled manner. To overcome this possible heterogeneity problem, EB-based HSID methods that use common clustering methodologies (e.g., mixture models, K-means, and hierarchical clustering to select “similar” sites for building SPFs are developed. Performance of the clustering-based EB methods is then compared using real crash data. Here, HSID results, when computed on Texas undivided rural highway cash data, suggest that all three clustering-based EB analysis methods are preferred over the conventional statistical methods. Thus, properly classifying the road segments for heterogeneous crash data can further improve HSID accuracy.

  8. Stabilizing ultrasmall Au clusters for enhanced photoredox catalysis.

    Science.gov (United States)

    Weng, Bo; Lu, Kang-Qiang; Tang, Zichao; Chen, Hao Ming; Xu, Yi-Jun

    2018-04-18

    Recently, loading ligand-protected gold (Au) clusters as visible light photosensitizers onto various supports for photoredox catalysis has attracted considerable attention. However, the efficient control of long-term photostability of Au clusters on the metal-support interface remains challenging. Herein, we report a simple and efficient method for enhancing the photostability of glutathione-protected Au clusters (Au GSH clusters) loaded on the surface of SiO 2 sphere by utilizing multifunctional branched poly-ethylenimine (BPEI) as a surface charge modifying, reducing and stabilizing agent. The sequential coating of thickness controlled TiO 2 shells can further significantly improve the photocatalytic efficiency, while such structurally designed core-shell SiO 2 -Au GSH clusters-BPEI@TiO 2 composites maintain high photostability during longtime light illumination conditions. This joint strategy via interfacial modification and composition engineering provides a facile guideline for stabilizing ultrasmall Au clusters and rational design of Au clusters-based composites with improved activity toward targeting applications in photoredox catalysis.

  9. The Performance-based Funding Scheme of Universities

    Directory of Open Access Journals (Sweden)

    Juha KETTUNEN

    2016-05-01

    Full Text Available The purpose of this study is to analyse the effectiveness of the performance-based funding scheme of the Finnish universities that was adopted at the beginning of 2013. The political decision-makers expect that the funding scheme will create incentives for the universities to improve performance, but these funding schemes have largely failed in many other countries, primarily because public funding is only a small share of the total funding of universities. This study is interesting because Finnish universities have no tuition fees, unlike in many other countries, and the state allocates funding based on the objectives achieved. The empirical evidence of the graduation rates indicates that graduation rates increased when a new scheme was adopted, especially among male students, who have more room for improvement than female students. The new performance-based funding scheme allocates the funding according to the output-based indicators and limits the scope of strategic planning and the autonomy of the university. The performance-based funding scheme is transformed to the strategy map of the balanced scorecard. The new funding scheme steers universities in many respects but leaves the research and teaching skills to the discretion of the universities. The new scheme has also diminished the importance of the performance agreements between the university and the Ministry. The scheme increases the incentives for universities to improve the processes and structures in order to attain as much public funding as possible. It is optimal for the central administration of the university to allocate resources to faculties and other organisational units following the criteria of the performance-based funding scheme. The new funding scheme has made the universities compete with each other, because the total funding to the universities is allocated to each university according to the funding scheme. There is a tendency that the funding schemes are occasionally

  10. A Cluster-Based Fuzzy Fusion Algorithm for Event Detection in Heterogeneous Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    ZiQi Hao

    2015-01-01

    Full Text Available As limited energy is one of the tough challenges in wireless sensor networks (WSN, energy saving becomes important in increasing the lifecycle of the network. Data fusion enables combining information from several sources thus to provide a unified scenario, which can significantly save sensor energy and enhance sensing data accuracy. In this paper, we propose a cluster-based data fusion algorithm for event detection. We use k-means algorithm to form the nodes into clusters, which can significantly reduce the energy consumption of intracluster communication. Distances between cluster heads and event and energy of clusters are fuzzified, thus to use a fuzzy logic to select the clusters that will participate in data uploading and fusion. Fuzzy logic method is also used by cluster heads for local decision, and then the local decision results are sent to the base station. Decision-level fusion for final decision of event is performed by base station according to the uploaded local decisions and fusion support degree of clusters calculated by fuzzy logic method. The effectiveness of this algorithm is demonstrated by simulation results.

  11. Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

    Science.gov (United States)

    Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

    2016-01-01

    Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

  12. Reversible light-controlled conductance switching of azobenzene-based metal/polymer nanocomposites

    International Nuclear Information System (INIS)

    Pakula, Christina; Zaporojtchenko, Vladimir; Strunskus, Thomas; Faupel, Franz; Zargarani, Dordaneh; Herges, Rainer

    2010-01-01

    We present a new concept of light-controlled conductance switching based on metal/polymer nanocomposites with dissolved chromophores that do not have intrinsic current switching ability. Photoswitchable metal/PMMA nanocomposites were prepared by physical vapor deposition of Au and Pt clusters, respectively, onto spin-coated thin poly(methylmethacrylate) films doped with azo-dye molecules. High dye concentrations were achieved by functionalizing the azo groups with tails and branches, thus enhancing solubility. The composites show completely reversible optical switching of the absorption bands upon alternating irradiation with UV and blue light. We also demonstrate reversible light-controlled conductance switching. This is attributed to changes in the metal cluster separation upon isomerization based on model experiments where analogous conductance changes were induced by swelling of the composite films in organic vapors and by tensile stress.

  13. Orbit Clustering Based on Transfer Cost

    Science.gov (United States)

    Gustafson, Eric D.; Arrieta-Camacho, Juan J.; Petropoulos, Anastassios E.

    2013-01-01

    We propose using cluster analysis to perform quick screening for combinatorial global optimization problems. The key missing component currently preventing cluster analysis from use in this context is the lack of a useable metric function that defines the cost to transfer between two orbits. We study several proposed metrics and clustering algorithms, including k-means and the expectation maximization algorithm. We also show that proven heuristic methods such as the Q-law can be modified to work with cluster analysis.

  14. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Science.gov (United States)

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  15. OMERACT-based fibromyalgia symptom subgroups: an exploratory cluster analysis.

    Science.gov (United States)

    Vincent, Ann; Hoskin, Tanya L; Whipple, Mary O; Clauw, Daniel J; Barton, Debra L; Benzo, Roberto P; Williams, David A

    2014-10-16

    The aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains. Female patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire-Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria. A total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P FIQ-R total scores (P = 0.0004)). In our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.

  16. A store-based intervention to increase fruit and vegetable consumption: The El Valor de Nuestra Salud cluster randomized controlled trial.

    Science.gov (United States)

    Ayala, Guadalupe X; Baquero, Barbara; Pickrel, Julie L; Mayer, Joni; Belch, George; Rock, Cheryl L; Linnan, Laura; Gittelsohn, Joel; Sanchez-Flack, Jennifer; Elder, John P

    2015-05-01

    Most evidence-based interventions to improve fruit and vegetable (FV) consumption target individual behaviors and family systems; however, these changes are difficult to sustain without environmental support. This paper describes an innovative social and structural food store-based intervention to increase availability and accessibility of FVs in tiendas (small- to medium-sized Latino food stores) and purchasing and consumption of FVs among tienda customers. Using a cluster randomized controlled trial with 16 tiendas pair-matched and randomized to an intervention or wait-list control condition, this study will evaluate a 2-month intervention directed at tiendas, managers, and employees followed by a 4-month customer-directed food marketing campaign. The intervention involves social (e.g., employee trainings) and structural (e.g., infrastructure) environmental changes. Three hundred sixty-nine customers (approximately 23 per tienda) serve on an evaluation cohort and complete assessments (interviews and measurements of weight) at 3 time points: baseline, 6-months post-baseline, and 12-months post-baseline. The primary study outcome is customer-reported daily consumption of FVs. Manager interviews and monthly tienda audits and collection of sales data will provide evidence of tienda-level intervention effects, our secondary outcomes. Process evaluation methods assess dose delivered, dose received, and fidelity. Recruitment of tiendas, managers, employees, and customers is complete. Demographic data shows that 30% of the customers are males, thus providing a unique opportunity to examine the effects of a tienda-based intervention on Latino men. Determining whether a tienda-based intervention can improve customers' FV purchasing and consumption will provide key evidence for how to create healthier consumer food environments. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. A store-based intervention to increase fruit and vegetable consumption: The El Valor de Nuestra Salud cluster randomized controlled trial

    Science.gov (United States)

    Ayala, Guadalupe X.; Baquero, Barbara; Pickrel, Julie L.; Mayer, Joni; Belch, George; Rock, Cheryl L.; Linnan, Laura; Gittelsohn, Joel; Sanchez-Flack, Jennifer; Elder, John P.

    2015-01-01

    Introduction Most evidence-based interventions to improve fruit and vegetable (FV) consumption target individual behaviors and family systems; however, these changes are difficult to sustain without environmental support. This paper describes an innovative social and structural food store-based intervention to increase availability and accessibility of FVs in tiendas (small-to medium-sized Latino food stores) and purchasing and consumption of FVs among tienda customers. Methods Using a cluster randomized controlled trial with 16 tiendas pair-matched and randomized to an intervention or wait-list control condition, this study will evaluate a 2-month intervention directed at tiendas, managers, and employees followed by a 4-month customer-directed food marketing campaign. The intervention involves social (e.g., employee trainings) and structural (e.g., infrastructure) environmental changes. Three hundred sixty-nine customers (approximately 23 per tienda) serve on an evaluation cohort and complete assessments (interviews and measurements of weight) at 3 time points: baseline, 6-months post-baseline, and 12-months post-baseline. The primary study outcome is customer-reported daily consumption of FVs. Manager interviews and monthly tienda audits and collection of sales data will provide evidence of tienda-level intervention effects, our secondary outcomes. Process evaluation methods assess dose delivered, dose received, and fidelity. Results Recruitment of tiendas, managers, employees, and customers is complete. Demographic data shows that 30% of the customers are males, thus providing a unique opportunity to examine the effects of a tienda-based intervention on Latino men. Conclusions Determining whether a tienda-based intervention can improve customers’ FV purchasing and consumption will provide key evidence for how to create healthier consumer food environments. PMID:25924592

  18. Classification via Clustering for Predicting Final Marks Based on Student Participation in Forums

    Science.gov (United States)

    Lopez, M. I.; Luna, J. M.; Romero, C.; Ventura, S.

    2012-01-01

    This paper proposes a classification via clustering approach to predict the final marks in a university course on the basis of forum data. The objective is twofold: to determine if student participation in the course forum can be a good predictor of the final marks for the course and to examine whether the proposed classification via clustering…

  19. Man, Controller of the Universe

    Science.gov (United States)

    Olowin, R. P.

    2011-06-01

    The Man, Controller of the Universe painted by the renowned Mexican artist Diego Rivera in the gigantic mural of the Palace of Fine Arts in Mexico City is overlooked by a telescope. We acknowledge this instrument as the Plaskett Telescope at the Dominion Astrophysical Observatory in Victoria, Canada.

  20. Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

    Science.gov (United States)

    Wang, James Z.; Du, Yanping

    Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

  1. Unusual clustering of coefficients of variation in published articles from a medical biochemistry department in India.

    Science.gov (United States)

    Hudes, Mark L; McCann, Joyce C; Ames, Bruce N

    2009-03-01

    A simple statistical method is described to test whether data are consistent with minimum statistical variability expected in a biological experiment. The method is applied to data presented in data tables in a subset of 84 articles among more than 200 published by 3 investigators in a small medical biochemistry department at a major university in India and to 29 "control" articles selected by key word PubMed searches. Major conclusions include: 1) unusual clustering of coefficients of variation (CVs) was observed for data from the majority of articles analyzed that were published by the 3 investigators from 2000-2007; unusual clustering was not observed for data from any of their articles examined that were published between 1992 and 1999; and 2) among a group of 29 control articles retrieved by PubMed key word, title, or title/abstract searches, unusually clustered CVs were observed in 3 articles. Two of these articles were coauthored by 1 of the 3 investigators, and 1 was from the same university but a different department. We are unable to offer a statistical or biological explanation for the unusual clustering observed.

  2. Cluster Validity Classification Approaches Based on Geometric Probability and Application in the Classification of Remotely Sensed Images

    Directory of Open Access Journals (Sweden)

    LI Jian-Wei

    2014-08-01

    Full Text Available On the basis of the cluster validity function based on geometric probability in literature [1, 2], propose a cluster analysis method based on geometric probability to process large amount of data in rectangular area. The basic idea is top-down stepwise refinement, firstly categories then subcategories. On all clustering levels, use the cluster validity function based on geometric probability firstly, determine clusters and the gathering direction, then determine the center of clustering and the border of clusters. Through TM remote sensing image classification examples, compare with the supervision and unsupervised classification in ERDAS and the cluster analysis method based on geometric probability in two-dimensional square which is proposed in literature 2. Results show that the proposed method can significantly improve the classification accuracy.

  3. A Survey on the Taxonomy of Cluster-Based Routing Protocols for Homogeneous Wireless Sensor Networks

    Science.gov (United States)

    Naeimi, Soroush; Ghafghazi, Hamidreza; Chow, Chee-Onn; Ishii, Hiroshi

    2012-01-01

    The past few years have witnessed increased interest among researchers in cluster-based protocols for homogeneous networks because of their better scalability and higher energy efficiency than other routing protocols. Given the limited capabilities of sensor nodes in terms of energy resources, processing and communication range, the cluster-based protocols should be compatible with these constraints in either the setup state or steady data transmission state. With focus on these constraints, we classify routing protocols according to their objectives and methods towards addressing the shortcomings of clustering process on each stage of cluster head selection, cluster formation, data aggregation and data communication. We summarize the techniques and methods used in these categories, while the weakness and strength of each protocol is pointed out in details. Furthermore, taxonomy of the protocols in each phase is given to provide a deeper understanding of current clustering approaches. Ultimately based on the existing research, a summary of the issues and solutions of the attributes and characteristics of clustering approaches and some open research areas in cluster-based routing protocols that can be further pursued are provided. PMID:22969350

  4. A novel grain cluster-based homogenization scheme

    International Nuclear Information System (INIS)

    Tjahjanto, D D; Eisenlohr, P; Roters, F

    2010-01-01

    An efficient homogenization scheme, termed the relaxed grain cluster (RGC), for elasto-plastic deformations of polycrystals is presented. The scheme is based on a generalization of the grain cluster concept. A volume element consisting of eight (= 2 × 2 × 2) hexahedral grains is considered. The kinematics of the RGC scheme is formulated within a finite deformation framework, where the relaxation of the local deformation gradient of each individual grain is connected to the overall deformation gradient by the, so-called, interface relaxation vectors. The set of relaxation vectors is determined by the minimization of the constitutive energy (or work) density of the overall cluster. An additional energy density associated with the mismatch at the grain boundaries due to relaxations is incorporated as a penalty term into the energy minimization formulation. Effectively, this penalty term represents the kinematical condition of deformation compatibility at the grain boundaries. Simulations have been performed for a dual-phase grain cluster loaded in uniaxial tension. The results of the simulations are presented and discussed in terms of the effective stress–strain response and the overall deformation anisotropy as functions of the penalty energy parameters. In addition, the prediction of the RGC scheme is compared with predictions using other averaging schemes, as well as to the result of direct finite element (FE) simulation. The comparison indicates that the present RGC scheme is able to approximate FE simulation results of relatively fine discretization at about three orders of magnitude lower computational cost

  5. a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

    Science.gov (United States)

    Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

    2017-09-01

    Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

  6. Camino Verde (The Green Way: evidence-based community mobilisation for dengue control in Nicaragua and Mexico: feasibility study and study protocol for a randomised controlled trial

    Directory of Open Access Journals (Sweden)

    Neil Andersson

    2017-05-01

    Full Text Available Abstract Background Since the Aedes aegypti mosquitoes that transmit dengue virus can breed in clean water, WHO-endorsed vector control strategies place sachets of organophosphate pesticide, temephos (Abate, in household water storage containers. These and other pesticide-dependent approaches have failed to curb the spread of dengue and multiple dengue virus serotypes continue to spread throughout tropical and subtropical regions worldwide. A feasibility study in Managua, Nicaragua, generated instruments, intervention protocols, training schedules and impact assessment tools for a cluster randomised controlled trial of community-based approaches to vector control comprising an alternative strategy for dengue prevention and control in Nicaragua and Mexico. Methods/Design The Camino Verde (Green Way is a pragmatic parallel group trial of pesticide-free dengue vector control, adding effectiveness to the standard government dengue control. A random sample from the most recent census in three coastal regions of Guerrero state in Mexico will generate 90 study clusters and the equivalent sampling frame in Managua, Nicaragua will generate 60 clusters, making a total of 150 clusters each of 137–140 households. After a baseline study, computer-driven randomisation will allocate to intervention one half of the sites, stratified by country, evidence of recent dengue virus infection in children aged 3–9 years and, in Nicaragua, level of community organisation. Following a common evidence-based education protocol, each cluster will develop and implement its own collective interventions including house-to-house visits, school-based programmes and inter-community visits. After 18 months, a follow-up study will compare dengue history, serological evidence of recent dengue virus infection (via measurement of anti-dengue virus antibodies in saliva samples and entomological indices between intervention and control sites. Discussion Our hypothesis is that

  7. Camino Verde (The Green Way): evidence-based community mobilisation for dengue control in Nicaragua and Mexico: feasibility study and study protocol for a randomised controlled trial.

    Science.gov (United States)

    Andersson, Neil; Arostegui, Jorge; Nava-Aguilera, Elizabeth; Harris, Eva; Ledogar, Robert J

    2017-05-30

    Since the Aedes aegypti mosquitoes that transmit dengue virus can breed in clean water, WHO-endorsed vector control strategies place sachets of organophosphate pesticide, temephos (Abate), in household water storage containers. These and other pesticide-dependent approaches have failed to curb the spread of dengue and multiple dengue virus serotypes continue to spread throughout tropical and subtropical regions worldwide. A feasibility study in Managua, Nicaragua, generated instruments, intervention protocols, training schedules and impact assessment tools for a cluster randomised controlled trial of community-based approaches to vector control comprising an alternative strategy for dengue prevention and control in Nicaragua and Mexico. The Camino Verde (Green Way) is a pragmatic parallel group trial of pesticide-free dengue vector control, adding effectiveness to the standard government dengue control. A random sample from the most recent census in three coastal regions of Guerrero state in Mexico will generate 90 study clusters and the equivalent sampling frame in Managua, Nicaragua will generate 60 clusters, making a total of 150 clusters each of 137-140 households. After a baseline study, computer-driven randomisation will allocate to intervention one half of the sites, stratified by country, evidence of recent dengue virus infection in children aged 3-9 years and, in Nicaragua, level of community organisation. Following a common evidence-based education protocol, each cluster will develop and implement its own collective interventions including house-to-house visits, school-based programmes and inter-community visits. After 18 months, a follow-up study will compare dengue history, serological evidence of recent dengue virus infection (via measurement of anti-dengue virus antibodies in saliva samples) and entomological indices between intervention and control sites. Our hypothesis is that informed community mobilisation adds effectiveness in controlling

  8. Effectiveness of school dental screening on dental visits and untreated caries among primary schoolchildren: study protocol for a cluster randomised controlled trial.

    Science.gov (United States)

    Alayadi, Haya; Sabbah, Wael; Bernabé, Eduardo

    2018-04-13

    Dental caries is one of the most common diseases affecting children in Saudi Arabia despite the availability of free dental services. School-based dental screening could be a potential intervention that impacts uptake of dental services, and subsequently, dental caries' levels. The purpose of this study is to evaluate the effectiveness of two alternative approaches for school-based dental screening in promoting dental attendance and reducing untreated dental caries among primary schoolchildren. This is a cluster randomised controlled trial comparing referral of screened-positive children to a specific treatment facility (King Saud University Dental College) against conventional referral (information letter advising parents to take their child to a dentist). A thousand and ten children in 16 schools in Riyadh, Saudi Arabia, will be recruited for the trial. Schools (clusters) will be randomly selected and allocated to either group. Clinical assessment for dental caries will be conducted at baseline and after 12 months by dentists using the World Health Organisation (WHO) criteria. Data on sociodemographic, behavioural factors and children's dental visits will be collected through structured questionnaires at baseline and follow-up. The primary outcome is the change in number of teeth with untreated dental caries 12 months after referral. Secondary outcomes are the changes in the proportions of children having untreated caries and of those who visited the dentist over the trial period. This project should provide high level of evidence on the clinical benefits of school dental screening. The findings should potentially inform policies related to the continuation/implementation of school-based dental screening in Saudi Arabia. ClinicalTrials.gov , ID: NCT03345680 . Registered on 17 November 2017.

  9. Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods.

    Science.gov (United States)

    Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

    2016-01-01

    Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community.

  10. Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods

    Science.gov (United States)

    Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

    2016-01-01

    Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community. PMID:27124610

  11. An ant colony based resilience approach to cascading failures in cluster supply network

    Science.gov (United States)

    Wang, Yingcong; Xiao, Renbin

    2016-11-01

    Cluster supply chain network is a typical complex network and easily suffers cascading failures under disruption events, which is caused by the under-load of enterprises. Improving network resilience can increase the ability of recovery from cascading failures. Social resilience is found in ant colony and comes from ant's spatial fidelity zones (SFZ). Starting from the under-load failures, this paper proposes a resilience method to cascading failures in cluster supply chain network by leveraging on social resilience of ant colony. First, the mapping between ant colony SFZ and cluster supply chain network SFZ is presented. Second, a new cascading model for cluster supply chain network is constructed based on under-load failures. Then, the SFZ-based resilience method and index to cascading failures are developed according to ant colony's social resilience. Finally, a numerical simulation and a case study are used to verify the validity of the cascading model and the resilience method. Experimental results show that, the cluster supply chain network becomes resilient to cascading failures under the SFZ-based resilience method, and the cluster supply chain network resilience can be enhanced by improving the ability of enterprises to recover and adjust.

  12. Research on the method of information system risk state estimation based on clustering particle filter

    Directory of Open Access Journals (Sweden)

    Cui Jia

    2017-05-01

    Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  13. Research on the method of information system risk state estimation based on clustering particle filter

    Science.gov (United States)

    Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

    2017-05-01

    With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  14. Regenerative Medicine as an Emergent Cluster in Tampere Region

    Directory of Open Access Journals (Sweden)

    Tuomo Heinonen

    2015-01-01

    Full Text Available Clusters are important for regional economies and emergent clusters are in a key position, as a means of adding more diversification to the current economic activity by involving new technologies and industries. Science-based industries may be the most promising in this regard since they are encouraged to develop and enhance the economic imaginaries of territories under the umbrella of radical innovations or in the name of broadening the current economic model based on mostly traditional industries. Regenerative medicine (RM could be an example of these so-called emergent clusters. Regenerative medicine is highly dependent on academic research, which means that local territories must fund the research in this field and, hence, they expect some returns as well. As territories do not typically have existing industries specifically in RM, these industries must emerge or expand from existing ones. Regenerative medicine involves a wide spectrum of different technologies and industries that are likely to form a cluster and benefit from it if successfully developed. The first aim of this paper is to show how some obstacles eventually impede the proper development of these emergent clusters. The second aim is to shed light on how innovations emerge in the cluster and what are the main implications for the territory. In this study, existing literature is used in order to describe the technology market and commercial aspects of the RM sector. Empirically this study is based on the emergent RM cluster in the region of Tampere in Finland. Analysis of 24 conducted interviews helps to contextualize the emergence of the RM cluster in Tampere, where academia is both the booster and the driver of the emergent RM cluster. Commercialization of research in the RM field is one of the goals at the university, even though there are no commercial outcomes yet available. This study contributes to the understanding of emergent cluster development in science-based

  15. Cluster synchronization for directed community networks via pinning partial schemes

    International Nuclear Information System (INIS)

    Hu Cheng; Jiang Haijun

    2012-01-01

    Highlights: ► Cluster synchronization for directed community networks is proposed by pinning partial schemes. ► Each community is considered as a whole. ► Several novel pinning criteria are derived based on the information of communities. ► A numerical example with simulation is provided. - Abstract: In this paper, we focus on driving a class of directed networks to achieve cluster synchronization by pinning schemes. The desired cluster synchronization states are no longer decoupled orbits but a set of un-decoupled trajectories. Each community is considered as a whole and the synchronization criteria are derived based on the information of communities. Several pinning schemes including feedback control and adaptive strategy are proposed to select controlled communities by analyzing the information of each community such as indegrees and outdegrees. In all, this paper answers several challenging problems in pinning control of directed community networks: (1) What communities should be chosen as controlled candidates? (2) How many communities are needed to be controlled? (3) How large should the control gains be used in a given community network to achieve cluster synchronization? Finally, an example with numerical simulations is given to demonstrate the effectiveness of the theoretical results.

  16. Semi-supervised weighted kernel clustering based on gravitational search for fault diagnosis.

    Science.gov (United States)

    Li, Chaoshun; Zhou, Jianzhong

    2014-09-01

    Supervised learning method, like support vector machine (SVM), has been widely applied in diagnosing known faults, however this kind of method fails to work correctly when new or unknown fault occurs. Traditional unsupervised kernel clustering can be used for unknown fault diagnosis, but it could not make use of the historical classification information to improve diagnosis accuracy. In this paper, a semi-supervised kernel clustering model is designed to diagnose known and unknown faults. At first, a novel semi-supervised weighted kernel clustering algorithm based on gravitational search (SWKC-GS) is proposed for clustering of dataset composed of labeled and unlabeled fault samples. The clustering model of SWKC-GS is defined based on wrong classification rate of labeled samples and fuzzy clustering index on the whole dataset. Gravitational search algorithm (GSA) is used to solve the clustering model, while centers of clusters, feature weights and parameter of kernel function are selected as optimization variables. And then, new fault samples are identified and diagnosed by calculating the weighted kernel distance between them and the fault cluster centers. If the fault samples are unknown, they will be added in historical dataset and the SWKC-GS is used to partition the mixed dataset and update the clustering results for diagnosing new fault. In experiments, the proposed method has been applied in fault diagnosis for rotatory bearing, while SWKC-GS has been compared not only with traditional clustering methods, but also with SVM and neural network, for known fault diagnosis. In addition, the proposed method has also been applied in unknown fault diagnosis. The results have shown effectiveness of the proposed method in achieving expected diagnosis accuracy for both known and unknown faults of rotatory bearing. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  17. The luminosity function of star clusters in 20 star-forming galaxies based on Hubble legacy archive photometry

    International Nuclear Information System (INIS)

    Whitmore, Bradley C.; Bowers, Ariel S.; Lindsay, Kevin; Ansari, Asna; Evans, Jessica; Chandar, Rupali; Larsen, Soeren

    2014-01-01

    Luminosity functions (LFs) have been determined for star cluster populations in 20 nearby (4-30 Mpc), star-forming galaxies based on Advanced Camera for Surveys source lists generated by the Hubble Legacy Archive (HLA). These cluster catalogs provide one of the largest sets of uniform, automatically generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster LF can be approximated by a power law, dN/dL∝L α , with an average value for α of –2.37 and rms scatter = 0.18 when using the F814W ('I') band. A comparison of fitting results based on methods that use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum likelihood) method to give slightly more negative values of α for galaxies with steeper LFs. We find that galaxies with high rates of star formation (or equivalently, with the brightest or largest numbers of clusters) have a slight tendency to have shallower values of α. In particular, the Antennae galaxy (NGC 4038/39), a merging system with a relatively high star formation rate (SFR), has the second flattest LF in the sample. A tentative correlation may also be present between Hubble type and values of α, in the sense that later type galaxies (i.e., Sd and Sm) appear to have flatter LFs. Hence, while there do appear to be some weak correlations, the relative similarity in the values of α for a large number of star-forming galaxies suggests that, to first order, the LFs are fairly universal. We examine the bright end of the LFs and find evidence for a downturn, although it only pertains to about 1% of the clusters. Our uniform database results in a small scatter (≈0.4 to 0.5 mag) in the correlation between the magnitude of the brightest cluster (M brightest ) and log of the number

  18. School-Based Nutrition Education Intervention Using Social Cognitive Theory for Overweight and Obese Iranian Adolescent Girls: A Cluster Randomized Controlled Trial.

    Science.gov (United States)

    Bagherniya, Mohammad; Sharma, Manoj; Mostafavi Darani, Firoozeh; Maracy, Mohammad Reza; Safarian, Mohammad; Allipour Birgani, Ramesh; Bitarafan, Vida; Keshavarz, Seyed Ali

    2017-10-01

    Background Nowadays childhood obesity has become one the most challenging issue which is considered as a principle public health problem all around the world. This study was conducted with the aim of evaluating the impact of a 7-month school-based nutrition education intervention using social cognitive theory (SCT) to prevent obesity among overweight and obese adolescent girls. Method In this cluster randomized community trial after choosing schools, a total of 172 overweight and obese girl students participated in the study (87 in the intervention and 85 in the control group). A 7-month intervention based on SCT for students, their parents, and teachers was conducted. At baseline and end of the study, body mass index (BMI), waist circumstances (WCs), dietary intake, and psychological questionnaires regarding the SCT constructs were obtained. Results After 7 months, the mean of BMI and WCs reduced in the intervention group from 29.47 (4.05) to 28.5 (4.35) and from 89.65 (8.15) to 86.54 (9.76), respectively, but in comparison to the control group, they were not statistically significant ( p values .127 and .504, respectively). In the intervention group, nutritional behaviors and most of the psychological variables (self-efficacy, social support, intention, and situation) were improved in favor of the study and they were significant in comparison to the control group ( p < .05). Conclusion Although school-based nutrition education intervention using SCT did not change significantly BMI and WCs among the targeted population in this study, dietary habits as well as psychological factors improved significantly in the intervention group. This trial was registered in Iranian Registry of Clinical Trials, www.irct.ir (IRCT2013103115211N1).

  19. Performance of the cluster-jet target for PANDA

    Energy Technology Data Exchange (ETDEWEB)

    Hergemoeller, Ann-Katrin; Bonaventura, Daniel; Grieser, Silke; Hetz, Benjamin; Koehler, Esperanza; Khoukaz, Alfons [Institut fuer Kernphysik, Westfaelische Wilhelms-Universitaet Muenster, 48149 Muenster (Germany)

    2016-07-01

    The success of storage ring experiments strongly depends on the choice of the target. For this purpose, a very appropriate internal target for such an experiment is a cluster-jet target, which will be the first operated target at the PANDA experiment at FAIR. In this kind of target the cluster beam itself is formed due to the expansion of pre-cooled gases within a Laval nozzle and is prepared afterwards via two orifices, the skimmer and the collimator. The target prototype, operating successfully for years at the University of Muenster, provides routinely target thicknesses of more than 2 x 10{sup 15} (atoms)/(cm{sup 2}) in a distance of 2.1 m behind the nozzle. Based on the results of the performance of the cluster target prototype the final cluster-jet target source was designed and set into operation in Muenster as well. Besides the monitoring of the cluster beam itself and the thickness with two different monitoring systems at this target, investigations on the cluster mass via Mie scattering will be performed. In this presentation an overview of the cluster target design, its performance and the Mie scattering method are presented and discussed.

  20. Fast gene ontology based clustering for microarray experiments.

    Science.gov (United States)

    Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

    2008-11-21

    Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

  1. Message Passing Framework for Globally Interconnected Clusters

    International Nuclear Information System (INIS)

    Hafeez, M; Riaz, N; Asghar, S; Malik, U A; Rehman, A

    2011-01-01

    In prevailing technology trends it is apparent that the network requirements and technologies will advance in future. Therefore the need of High Performance Computing (HPC) based implementation for interconnecting clusters is comprehensible for scalability of clusters. Grid computing provides global infrastructure of interconnecting clusters consisting of dispersed computing resources over Internet. On the other hand the leading model for HPC programming is Message Passing Interface (MPI). As compared to Grid computing, MPI is better suited for solving most of the complex computational problems. MPI itself is restricted to a single cluster. It does not support message passing over the internet to use the computing resources of different clusters in an optimal way. We propose a model that provides message passing capabilities between parallel applications over the internet. The proposed model is based on Architecture for Java Universal Message Passing (A-JUMP) framework and Enterprise Service Bus (ESB) named as High Performance Computing Bus. The HPC Bus is built using ActiveMQ. HPC Bus is responsible for communication and message passing in an asynchronous manner. Asynchronous mode of communication offers an assurance for message delivery as well as a fault tolerance mechanism for message passing. The idea presented in this paper effectively utilizes wide-area intercluster networks. It also provides scheduling, dynamic resource discovery and allocation, and sub-clustering of resources for different jobs. Performance analysis and comparison study of the proposed framework with P2P-MPI are also presented in this paper.

  2. Large-Scale Multi-Dimensional Document Clustering on GPU Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Mueller, Frank [North Carolina State University; Zhang, Yongpeng [ORNL; Potok, Thomas E [ORNL

    2010-01-01

    Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulation resembling the flocking behavior of birds in nature. This method is superior to other clustering algorithms, including k-means, in the sense that the outcome is not sensitive to the initial state. One limitation of this approach is that the algorithmic complexity is inherently quadratic in the number of documents. As a result, execution time becomes a bottleneck with large number of documents. In this paper, we assess the benefits of exploiting the computational power of Beowulf-like clusters equipped with contemporary Graphics Processing Units (GPUs) as a means to significantly reduce the runtime of flocking-based document clustering. Our framework scales up to over one million documents processed simultaneously in a sixteennode GPU cluster. Results are also compared to a four-node cluster with higher-end GPUs. On these clusters, we observe 30X-50X speedups, which demonstrates the potential of GPU clusters to efficiently solve massive data mining problems. Such speedups combined with the scalability potential and accelerator-based parallelization are unique in the domain of document-based data mining, to the best of our knowledge.

  3. A time-series approach for clustering farms based on slaughterhouse health aberration data.

    Science.gov (United States)

    Hulsegge, B; de Greef, K H

    2018-05-01

    A large amount of data is collected routinely in meat inspection in pig slaughterhouses. A time series clustering approach is presented and applied that groups farms based on similar statistical characteristics of meat inspection data over time. A three step characteristic-based clustering approach was used from the idea that the data contain more info than the incidence figures. A stratified subset containing 511,645 pigs was derived as a study set from 3.5 years of meat inspection data. The monthly averages of incidence of pleuritis and of pneumonia of 44 Dutch farms (delivering 5149 batches to 2 pig slaughterhouses) were subjected to 1) derivation of farm level data characteristics 2) factor analysis and 3) clustering into groups of farms. The characteristic-based clustering was able to cluster farms for both lung aberrations. Three groups of data characteristics were informative, describing incidence, time pattern and degree of autocorrelation. The consistency of clustering similar farms was confirmed by repetition of the analysis in a larger dataset. The robustness of the clustering was tested on a substantially extended dataset. This confirmed the earlier results, three data distribution aspects make up the majority of distinction between groups of farms and in these groups (clusters) the majority of the farms was allocated comparable to the earlier allocation (75% and 62% for pleuritis and pneumonia, respectively). The difference between pleuritis and pneumonia in their seasonal dependency was confirmed, supporting the biological relevance of the clustering. Comparison of the identified clusters of statistically comparable farms can be used to detect farm level risk factors causing the health aberrations beyond comparison on disease incidence and trend alone. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Cloud computing-based energy optimization control framework for plug-in hybrid electric bus

    International Nuclear Information System (INIS)

    Yang, Chao; Li, Liang; You, Sixiong; Yan, Bingjie; Du, Xian

    2017-01-01

    Considering the complicated characteristics of traffic flow in city bus route and the nonlinear vehicle dynamics, optimal energy management integrated with clustering and recognition of driving conditions in plug-in hybrid electric bus is still a challenging problem. Motivated by this issue, this paper presents an innovative energy optimization control framework based on the cloud computing for plug-in hybrid electric bus. This framework, which includes offline part and online part, can realize the driving conditions clustering in offline part, and the energy management in online part. In offline part, utilizing the operating data transferred from a bus to the remote monitoring center, K-means algorithm is adopted to cluster the driving conditions, and then Markov probability transfer matrixes are generated to predict the possible operating demand of the bus driver. Next in online part, the current driving condition is real-time identified by a well-trained support vector machine, and Markov chains-based driving behaviors are accordingly selected. With the stochastic inputs, stochastic receding horizon control method is adopted to obtain the optimized energy management of hybrid powertrain. Simulations and hardware-in-loop test are carried out with the real-world city bus route, and the results show that the presented strategy could greatly improve the vehicle fuel economy, and as the traffic flow data feedback increases, the fuel consumption of every plug-in hybrid electric bus running in a specific bus route tends to be a stable minimum. - Highlights: • Cloud computing-based energy optimization control framework is proposed. • Driving cycles are clustered into 6 types by K-means algorithm. • Support vector machine is employed to realize the online recognition of driving condition. • Stochastic receding horizon control-based energy management strategy is designed for plug-in hybrid electric bus. • The proposed framework is verified by simulation and hard

  5. Efficacy of infant simulator programmes to prevent teenage pregnancy: a school-based cluster randomised controlled trial in Western Australia.

    Science.gov (United States)

    Brinkman, Sally A; Johnson, Sarah E; Codde, James P; Hart, Michael B; Straton, Judith A; Mittinty, Murthy N; Silburn, Sven R

    2016-11-05

    Infant simulator-based programmes, which aim to prevent teenage pregnancy, are used in high-income as well as low-income and middle-income countries but, despite growing popularity, no published evidence exists of their long-term effect. The aim of this trial was to investigate the effect of such a programme, the Virtual Infant Parenting (VIP) programme, on pregnancy outcomes of birth and induced abortion in Australia. In this school-based pragmatic cluster randomised controlled trial, eligible schools in Perth, Western Australia, were enrolled and randomised 1:1 to the intervention and control groups. Randomisation using a table of random numbers without blocking, stratification, or matching was done by a researcher who was masked to the identity of the schools. Between 2003 and 2006, the VIP programme was administered to girls aged 13-15 years in the intervention schools, while girls of the same age in the control schools received the standard health education curriculum. Participants were followed until they reached 20 years of age via data linkage to hospital medical and abortion clinic records. The primary endpoint was the occurrence of pregnancy during the teenage years. Binomial and Cox proportional hazards regression was used to test for differences in pregnancy rates between study groups. This study is registered as an international randomised controlled trial, number ISRCTN24952438. 57 (86%) of 66 eligible schools were enrolled into the trial and randomly assigned 1:1 to the intervention (28 schools) or the control group (29 schools). Then, between Feb 1, 2003, and May 31, 2006, 1267 girls in the intervention schools received the VIP programme while 1567 girls in the control schools received the standard health education curriculum. Compared with girls in the control group, a higher proportion of girls in the intervention group recorded at least one birth (97 [8%] of 1267 in the intervention group vs 67 [4%] of 1567 in the control group) or at least one

  6. Seniority-based coupled cluster theory

    International Nuclear Information System (INIS)

    Henderson, Thomas M.; Scuseria, Gustavo E.; Bulik, Ireneusz W.; Stein, Tamar

    2014-01-01

    Doubly occupied configuration interaction (DOCI) with optimized orbitals often accurately describes strong correlations while working in a Hilbert space much smaller than that needed for full configuration interaction. However, the scaling of such calculations remains combinatorial with system size. Pair coupled cluster doubles (pCCD) is very successful in reproducing DOCI energetically, but can do so with low polynomial scaling (N 3 , disregarding the two-electron integral transformation from atomic to molecular orbitals). We show here several examples illustrating the success of pCCD in reproducing both the DOCI energy and wave function and show how this success frequently comes about. What DOCI and pCCD lack are an effective treatment of dynamic correlations, which we here add by including higher-seniority cluster amplitudes which are excluded from pCCD. This frozen pair coupled cluster approach is comparable in cost to traditional closed-shell coupled cluster methods with results that are competitive for weakly correlated systems and often superior for the description of strongly correlated systems

  7. Performance Analysis of a Cluster-Based MAC Protocol for Wireless Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Jesús Alonso-Zárate

    2010-01-01

    Full Text Available An analytical model to evaluate the non-saturated performance of the Distributed Queuing Medium Access Control Protocol for Ad Hoc Networks (DQMANs in single-hop networks is presented in this paper. DQMAN is comprised of a spontaneous, temporary, and dynamic clustering mechanism integrated with a near-optimum distributed queuing Medium Access Control (MAC protocol. Clustering is executed in a distributed manner using a mechanism inspired by the Distributed Coordination Function (DCF of the IEEE 802.11. Once a station seizes the channel, it becomes the temporary clusterhead of a spontaneous cluster and it coordinates the peer-to-peer communications between the clustermembers. Within each cluster, a near-optimum distributed queuing MAC protocol is executed. The theoretical performance analysis of DQMAN in single-hop networks under non-saturation conditions is presented in this paper. The approach integrates the analysis of the clustering mechanism into the MAC layer model. Up to the knowledge of the authors, this approach is novel in the literature. In addition, the performance of an ad hoc network using DQMAN is compared to that obtained when using the DCF of the IEEE 802.11, as a benchmark reference.

  8. How Clusters Work

    Science.gov (United States)

    Technology innovation clusters are geographic concentrations of interconnected companies, universities, and other organizations with a focus on environmental technology. They play a key role in addressing the nation’s pressing environmental problems.

  9. Statistical measures of galaxy clustering

    International Nuclear Information System (INIS)

    Porter, D.H.

    1988-01-01

    Consideration is given to the large-scale distribution of galaxies and ways in which this distribution may be statistically measured. Galaxy clustering is hierarchical in nature, so that the positions of clusters of galaxies are themselves spatially clustered. A simple identification of groups of galaxies would be an inadequate description of the true richness of galaxy clustering. Current observations of the large-scale structure of the universe and modern theories of cosmology may be studied with a statistical description of the spatial and velocity distributions of galaxies. 8 refs

  10. A Clustered Randomized Controlled Trial of the Positive Prevention PLUS Adolescent Pregnancy Prevention Program.

    Science.gov (United States)

    LaChausse, Robert G

    2016-09-01

    To determine the impact of Positive Prevention PLUS, a school-based adolescent pregnancy prevention program on delaying sexual intercourse, birth control use, and pregnancy. I randomly assigned a diverse sample of ninth grade students in 21 suburban public high schools in California into treatment (n = 2483) and control (n = 1784) groups that participated in a clustered randomized controlled trial. Between October 2013 and May 2014, participants completed baseline and 6-month follow-up surveys regarding sexual behavior and pregnancy. Participants in the treatment group were offered Positive Prevention PLUS, an 11-lesson adolescent pregnancy prevention program. The program had statistically significant impacts on delaying sexual intercourse and increasing the use of birth control. However, I detected no program effect on pregnancy rates at 6-month follow-up. The Positive Prevention PLUS program demonstrated positive impacts on adolescent sexual behavior. This suggests that programs that focus on having students practice risk reduction skills may delay sexual activity and increase birth control use.

  11. Multifaceted intervention to enhance the screening and care of hospitalised malnourished children: study protocol for the PREDIRE cluster randomized controlled trial

    Science.gov (United States)

    2013-01-01

    Background Hospital malnutrition is an underestimated problem and as many as half of malnourished patients do not receive appropriate treatment. In order to extend the management of malnutrition in health care facilities, multidisciplinary teams focusing on clinical nutrition were established in France. The establishment of such teams within hospital facilities remains nonetheless difficult. We have consequently developed a multifaceted intervention coordinated by a Nutritional Support Team (NST). Our study aims to evaluate the impact of this multifaceted intervention coordinated by a NST, in adherence to recommended practices for the care of malnourished children, among health care workers of a paediatric university hospital. Methods/design We carried out 1) a six-month observational phase focusing on the medical care procedures relative to malnourished children followed by 2) a cluster randomised controlled trial phase to evaluate the impact of a multidisciplinary nutrition team over an 18 month time frame. Based on power analyses and assuming a conservative intracluster correlation coefficient, 1289 children were needed to detect a 25% difference in rates between the two groups of the cluster trial. The implementation of our intervention was coordinated by the NST and had three major components: a) access to a computerised malnutrition screening system associated with an automatic alert system, b) an awareness campaign directed toward the health care workers and c) a leadership based strategy. Main outcomes included the number of daily weighings during hospitalisation, the investigation of malnutrition etiology and the management of malnutrition by a dietician and/or the NST. Due to the clustered nature of the data with children nested in departments, a generalized estimated equations approach will be used to analyse the impact of the multifaceted intervention on primary and secondary outcomes. Discussion Our results will provide an overall response regarding

  12. JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

    Science.gov (United States)

    Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

    2015-01-01

    Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

  13. JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

    Directory of Open Access Journals (Sweden)

    David K Brown

    Full Text Available Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS, a workflow management system and web interface for high performance computing (HPC. JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

  14. JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

    Science.gov (United States)

    Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

    2015-01-01

    Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

  15. Universal real-time control framework and Internet of Things for fast-paced research and development based production environments

    KAUST Repository

    Chaoui, Hicham

    2017-05-13

    This paper introduces a universal real-time control platform for complex research and development (R&D) based products design. The inherent complexity in R&D projects makes products development a difficult task to undertake. The use of state of the art development tools for modeling, simulation, and hardware-in-the-loop (HIL) validation contributes to a complexity reduction. However, R&D projects still require significant development time since many design iterations are usually necessary before final solution, which increases the cost. In most R&D processes, these tools are not used beyond rapid prototyping since development for mass production is usually performed in another environment, using different tools. This paper presents a fast and cost effective way of R&D-based products development, speeding-up time to market.

  16. Universal real-time control framework and Internet of Things for fast-paced research and development based production environments

    KAUST Repository

    Chaoui, Hicham; Aljarboua, Abdullah Abdulaziz; Miah, Suruz

    2017-01-01

    This paper introduces a universal real-time control platform for complex research and development (R&D) based products design. The inherent complexity in R&D projects makes products development a difficult task to undertake. The use of state of the art development tools for modeling, simulation, and hardware-in-the-loop (HIL) validation contributes to a complexity reduction. However, R&D projects still require significant development time since many design iterations are usually necessary before final solution, which increases the cost. In most R&D processes, these tools are not used beyond rapid prototyping since development for mass production is usually performed in another environment, using different tools. This paper presents a fast and cost effective way of R&D-based products development, speeding-up time to market.

  17. Evaluating a Web-Based Social Anxiety Intervention Among University Students: Randomized Controlled Trial.

    Science.gov (United States)

    McCall, Hugh Cameron; Richardson, Chris G; Helgadottir, Fjola Dogg; Chen, Frances S

    2018-03-21

    Treatment rates for social anxiety, a prevalent and potentially debilitating condition, remain among the lowest of all major mental disorders today. Although computer-delivered interventions are well poised to surmount key barriers to the treatment of social anxiety, most are only marginally effective when delivered as stand-alone treatments. A new, Web-based cognitive behavioral therapy (CBT) intervention called Overcome Social Anxiety was recently created to address the limitations of prior computer-delivered interventions. Users of Overcome Social Anxiety are self-directed through various CBT modules incorporating cognitive restructuring and behavioral experiments. The intervention is personalized to each user's symptoms, and automatic email reminders and time limits are used to encourage adherence. The purpose of this study was to conduct a randomized controlled trial to investigate the effectiveness of Overcome Social Anxiety in reducing social anxiety symptoms in a nonclinical sample of university students. As a secondary aim, we also investigated whether Overcome Social Anxiety would increase life satisfaction in this sample. Following eligibility screening, participants were randomly assigned to a treatment condition or a wait-list control condition. Only those assigned to the treatment condition were given access to Overcome Social Anxiety; they were asked to complete the program within 4 months. The social interaction anxiety scale (SIAS), the fear of negative evaluation scale (FNE), and the quality of life enjoyment and satisfaction questionnaire-short form (Q-LES-Q-SF) were administered to participants from both conditions during baseline and 4-month follow-up lab visits. Over the course of the study, participants assigned to the treatment condition experienced a significant reduction in social anxiety (SIAS: Psocial anxiety in the 2 conditions over the course of the study showed that those assigned to the treatment condition experienced significantly

  18. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Science.gov (United States)

    Tokuda, Tomoki; Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  19. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Directory of Open Access Journals (Sweden)

    Tomoki Tokuda

    Full Text Available We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  20. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

    Science.gov (United States)

    Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

  1. An effective trust-based recommendation method using a novel graph clustering algorithm

    Science.gov (United States)

    Moradi, Parham; Ahmadian, Sajad; Akhlaghian, Fardin

    2015-10-01

    Recommender systems are programs that aim to provide personalized recommendations to users for specific items (e.g. music, books) in online sharing communities or on e-commerce sites. Collaborative filtering methods are important and widely accepted types of recommender systems that generate recommendations based on the ratings of like-minded users. On the other hand, these systems confront several inherent issues such as data sparsity and cold start problems, caused by fewer ratings against the unknowns that need to be predicted. Incorporating trust information into the collaborative filtering systems is an attractive approach to resolve these problems. In this paper, we present a model-based collaborative filtering method by applying a novel graph clustering algorithm and also considering trust statements. In the proposed method first of all, the problem space is represented as a graph and then a sparsest subgraph finding algorithm is applied on the graph to find the initial cluster centers. Then, the proposed graph clustering algorithm is performed to obtain the appropriate users/items clusters. Finally, the identified clusters are used as a set of neighbors to recommend unseen items to the current active user. Experimental results based on three real-world datasets demonstrate that the proposed method outperforms several state-of-the-art recommender system methods.

  2. The role of repetition and reinforcement in school-based oral health education-a cluster randomized controlled trial.

    Science.gov (United States)

    Haleem, Abdul; Khan, Muhammad Khalil; Sufia, Shamta; Chaudhry, Saima; Siddiqui, Muhammad Irfanullah; Khan, Ayyaz Ali

    2016-01-04

    Repetition and reinforcement have been shown to play a crucial role in the sustainability of the effect of Oral Health Education (OHE) programs. However, its relevance to school-based OHE imparted by different personnel is not depicted by the existing dental literature. The present study was undertaken to determine the effectiveness of the repeated and reinforced OHE (RR-OHE) compared to one-time OHE intervention and to assess its role in school-based OHE imparted by dentist, teachers and peers. The study was a cluster randomized controlled trial that involved 935 adolescents aged 10-11 years. Twenty four boys' and girls' schools selected at random in two towns of Karachi, Pakistan were randomly assigned to three groups to receive OHE by dentist (DL), teachers (TL) and peer-leaders (PL). The groups received a single OHE session and were evaluated post-intervention and 6 months after. The three groups were then exposed to OHE for 6 months followed by 1 year of no OHE activity. Two further evaluations at 6-month and 12-month intervals were conducted. The data were collected by a self-administered questionnaire preceded by a structured interview and followed by oral examination of participants. The adolescents' oral health knowledge (OHK) in the DL and PL groups increased significantly by a single OHE session compared to their baseline knowledge (p strategy. Although the OHK scores of the DL and PL groups decreased significantly at 12-month evaluation of RR-OHE (p play a key role in school-based OHE irrespective of educators. The trained teachers and peers can play a complementary role in RR-OHE.

  3. X-ray clusters in a cold dark matter + lambda universe: A direct, large-scale, high-resolution, hydrodynamic simulation

    Science.gov (United States)

    Cen, Renyue; Ostriker, Jeremiah P.

    1994-01-01

    A new, three-dimensional, shock-capturing, hydrodynamic code is utilized to determine the distribution of hot gas in a cold dark matter (CDM) + lambda model universe. Periodic boundary conditions are assumed: a box with size 85/h Mpc, having cell size 0.31/h Mpc, is followed in a simulation with 270(exp 3) = 10(exp 7.3) cells. We adopt omega = 0.45, lambda = 0.55, h identically equal to H/100 km/s/Mpc = 0.6, and then, from the cosmic background explorer (COBE) and light element nucleosynthesis, sigma(sub 8) = 0.77, omega(sub b) = 0.043. We identify the X-ray emitting clusters in the simulation box, compute the luminosity function at several wavelength bands, the temperature function and estimated sizes, as well as the evolution of these quantities with redshift. This open model succeeds in matching local observations of clusters in contrast to the standard omega = 1, CDM model, which fails. It predicts an order of magnitude decline in the number density of bright (h nu = 2-10 keV) clusters from z = 0 to z = 2 in contrast to a slight increase in the number density for standard omega = 1, CDM model. This COBE-normalized CDM + lambda model produces approximately the same number of X-ray clusters having L(sub x) greater than 10(exp 43) erg/s as observed. The background radiation field at 1 keV due to clusters is approximately the observed background which, after correction for numerical effects, again indicates that the model is consistent with observations.

  4. Participatory women's groups and counselling through home visits to improve child growth in rural eastern India: protocol for a cluster randomised controlled trial.

    Science.gov (United States)

    Nair, Nirmala; Tripathy, Prasanta; Sachdev, Harshpal S; Bhattacharyya, Sanghita; Gope, Rajkumar; Gagrai, Sumitra; Rath, Shibanand; Rath, Suchitra; Sinha, Rajesh; Roy, Swati Sarbani; Shewale, Suhas; Singh, Vijay; Srivastava, Aradhana; Pradhan, Hemanta; Costello, Anthony; Copas, Andrew; Skordis-Worrall, Jolene; Haghparast-Bidgoli, Hassan; Saville, Naomi; Prost, Audrey

    2015-04-15

    Child stunting (low height-for-age) is a marker of chronic undernutrition and predicts children's subsequent physical and cognitive development. Around one third of the world's stunted children live in India. Our study aims to assess the impact, cost-effectiveness, and scalability of a community intervention with a government-proposed community-based worker to improve growth in children under two in rural India. The study is a cluster randomised controlled trial in two rural districts of Jharkhand and Odisha (eastern India). The intervention tested involves a community-based worker carrying out two activities: (a) one home visit to all pregnant women in the third trimester, followed by subsequent monthly home visits to all infants aged 0-24 months to support appropriate feeding, infection control, and care-giving; (b) a monthly women's group meeting using participatory learning and action to catalyse individual and community action for maternal and child health and nutrition. Both intervention and control clusters also receive an intervention to strengthen Village Health Sanitation and Nutrition Committees. The unit of randomisation is a purposively selected cluster of approximately 1000 population. A total of 120 geographical clusters covering an estimated population of 121,531 were randomised to two trial arms: 60 clusters in the intervention arm receive home visits, group meetings, and support to Village Health Sanitation and Nutrition Committees; 60 clusters in the control arm receive support to Committees only. The study participants are pregnant women identified in the third trimester of pregnancy and their children (n = 2520). Mothers and their children are followed up at seven time points: during pregnancy, within 72 hours of delivery, and at 3, 6, 9, 12 and 18 months after birth. The trial's primary outcome is children's mean length-for-age Z scores at 18 months. Secondary outcomes include wasting and underweight at all time points, birth weight, growth

  5. Clustered tuberculosis in a low-burden country

    DEFF Research Database (Denmark)

    Kamper-Jørgensen, Z; Andersen, A B; Kok-Jensen, A

    2012-01-01

    Molecular genotyping of Mycobacterium tuberculosis has proved to be a powerful tool in tuberculosis surveillance, epidemiology, and control. Based on results obtained through 15 years of nationwide IS6110 restriction fragment length polymorphism (RFLP) genotyping of M. tuberculosis cases in Denmark......, a country on the way toward tuberculosis elimination, we discuss M. tuberculosis transmission dynamics and point to areas for control interventions. Cases with 100% identical genotypes (RFLP patterns) were defined as clustered, and a cluster was defined as cases with an identical genotype. Of 4,601 included...... cases, corresponding to 76% of reported and 97% of culture-verified tuberculosis cases in the country, 56% were clustered, of which 69% were Danes. Generally, Danes were more often in large clusters (= 50 persons), older (mean age, 45 years), and male (male/female ratio, 2.5). Also, Danes had a higher...

  6. Cluster chain based energy efficient routing protocol for moblie WSN

    Directory of Open Access Journals (Sweden)

    WU Ziyu

    2016-04-01

    Full Text Available With the ubiquitous smart devices acting as mobile sensor nodes in the wireless sensor networks(WSNs to sense and transmit physical information,routing protocols should be designed to accommodate the mobility issues,in addition to conventional considerations on energy efficiency.However,due to frequent topology change,traditional routing schemes cannot perform well.Moreover,existence of mobile nodes poses new challenges on energy dissipation and packet loss.In this paper,a novel routing scheme called cluster chain based routing protocol(CCBRP is proposed,which employs a combination of cluster and chain structure to accomplish data collection and transmission and thereafter selects qualified cluster heads as chain leaders to transmit data to the sink.Furthermore,node mobility is handled based on periodical membership update of mobile nodes.Simulation results demonstrate that CCBRP has a good performance in terms of network lifetime and packet delivery,also strikes a better balance between successful packet reception and energy consumption.

  7. Innovation Cluster and Economic Development in Bucharest Ilfov Region

    Directory of Open Access Journals (Sweden)

    Ana Cristina Adumitroaei

    2013-08-01

    Full Text Available Simultaneous globalisation tendencies have created policy challenges for national and local governments. One response to these challenges has been a dramatic proliferation of development policies based on clusters of firms and industries. In EU Strategy 2020 – COM 546/6.10.2010 Initiative “An Union of Innovation”, COM 614/27.10.2010 Initiative “Industrial Policy in the Globalization Era” innovative clusters were considered the “engine” of economic development. They represent a framework for business development, collaboration between companies, universities, research institutions, suppliers, customers and competitors located in the same geographical area. Clusters of small and medium sized firms in developing economies are coming under increased pressure from competition as products mature, technology becomes widely available, and companies seek lower cost locations for production. In this paper, we consider that the cluster is an engine for economic development in our region and we need to have a regional strategy for clusters in Bucharest Ilfov Regional Development Plan for 2014-2020.

  8. Informing resource-poor populations and the delivery of entitled health and social services in rural India: a cluster randomized controlled trial.

    Science.gov (United States)

    Pandey, Priyanka; Sehgal, Ashwini R; Riboud, Michelle; Levine, David; Goyal, Madhav

    2007-10-24

    A lack of awareness about entitled health and social services may contribute to poor delivery of such services in developing countries, especially among individuals of low socioeconomic status. To determine the impact of informing resource-poor rural populations about entitled services. Community-based, cluster randomized controlled trial conducted from May 2004 to May 2005 in 105 randomly selected village clusters in Uttar Pradesh state in India. Households (548 intervention and 497 control) were selected by a systematic sampling design, including both low-caste and mid- to high-caste households. Four to 6 public meetings were held in each intervention village cluster to disseminate information on entitled health services, entitled education services, and village governance requirements. No intervention took place in control village clusters. Visits by nurse midwife; prenatal examinations, tetanus vaccinations, and prenatal supplements received by pregnant women; vaccinations received by infants; excess school fees charged; occurrence of village council meetings; and development work in villages. At baseline, there were no significant differences in self-reported delivery of health and social services. After 1 year, intervention villagers reported better delivery of several services compared with control villagers: in a multivariate analysis, 30% more prenatal examinations (95% confidence interval [CI], 17%-43%; P India about entitled services enhanced the delivery of health and social services among both low- and mid- to high-caste households. Interventions that emphasize educating resource-poor populations about entitled services may improve the delivery of such services. clinicaltrials.gov Identifier: NCT00421291.

  9. Targeted Prevention of Common Mental Health Disorders in University Students: Randomised Controlled Trial of a Transdiagnostic Trait-Focused Web-Based Intervention

    Science.gov (United States)

    Musiat, Peter; Conrod, Patricia; Treasure, Janet; Tylee, Andre; Williams, Chris; Schmidt, Ulrike

    2014-01-01

    Background A large proportion of university students show symptoms of common mental disorders, such as depression, anxiety, substance use disorders and eating disorders. Novel interventions are required that target underlying factors of multiple disorders. Aims To evaluate the efficacy of a transdiagnostic trait-focused web-based intervention aimed at reducing symptoms of common mental disorders in university students. Method Students were recruited online (n = 1047, age: M = 21.8, SD = 4.2) and categorised into being at high or low risk for mental disorders based on their personality traits. Participants were allocated to a cognitive-behavioural trait-focused (n = 519) or a control intervention (n = 528) using computerised simple randomisation. Both interventions were fully automated and delivered online (trial registration: ISRCTN14342225). Participants were blinded and outcomes were self-assessed at baseline, at 6 weeks and at 12 weeks after registration. Primary outcomes were current depression and anxiety, assessed on the Patient Health Questionnaire (PHQ9) and Generalised Anxiety Disorder Scale (GAD7). Secondary outcome measures focused on alcohol use, disordered eating, and other outcomes. Results Students at high risk were successfully identified using personality indicators and reported poorer mental health. A total of 520 students completed the 6-week follow-up and 401 students completed the 12-week follow-up. Attrition was high across intervention groups, but comparable to other web-based interventions. Mixed effects analyses revealed that at 12-week follow up the trait-focused intervention reduced depression scores by 3.58 (pstudents at high risk. In high-risk students, between group effect sizes were 0.58 (depression) and 0.42 (anxiety). In addition, self-esteem was improved. No changes were observed regarding the use of alcohol or disordered eating. Conclusions This study suggests that a transdiagnostic web-based intervention for

  10. The effectiveness of non-pyrethroid insecticide-treated durable wall lining to control malaria in rural Tanzania: study protocol for a two-armed cluster randomized trial

    Directory of Open Access Journals (Sweden)

    George Mtove

    2016-07-01

    Full Text Available Abstract Background Despite considerable reductions in malaria achieved by scaling-up long-lasting insecticidal nets (LLINs and indoor residual spraying (IRS, maintaining sustained community protection remains operationally challenging. Increasing insecticide resistance also threatens to jeopardize the future of both strategies. Non-pyrethroid insecticide­treated wall lining (ITWL may represent an alternate or complementary control method and a potential tool to manage insecticide resistance. To date no study has demonstrated whether ITWL can reduce malaria transmission nor provide additional protection beyond the current best practice of universal coverage (UC of LLINs and prompt case management. Methods/design A two-arm cluster randomized controlled trial will be conducted in rural Tanzania to assess whether non-pyrethroid ITWL and UC of LLINs provide added protection against malaria infection in children, compared to UC of LLINs alone. Stratified randomization based on malaria prevalence will be used to select 22 village clusters per arm. All 44 clusters will receive LLINs and half will also have ITWL installed on interior house walls. Study children, aged 6 months to 11 years old, will be enrolled from each cluster and followed monthly to estimate cumulative incidence of malaria parasitaemia (primary endpoint, time to first malaria episode and prevalence of anaemia before and after intervention. Entomological inoculation rate will be estimated using indoor CDC light traps and outdoor tent traps followed by detection of Anopheles gambiae species, sporozoite infection, insecticide resistance and blood meal source. ITWL bioefficacy and durability will be monitored using WHO cone bioassays and household surveys, respectively. Social and cultural factors influencing community and household ITWL acceptability will be explored through focus-group discussions and in-depth interviews. Cost-effectiveness, compared between study arms, will be

  11. Preventing Weight Gain in Women in Rural Communities: A Cluster Randomised Controlled Trial.

    Directory of Open Access Journals (Sweden)

    Catherine Lombard

    2016-01-01

    Full Text Available Obesity is reaching epidemic proportions in both developed and developing countries. Even modest weight gain increases the risk for chronic illness, yet evidence-based interventions to prevent weight gain are rare. This trial will determine if a simple low-intensity intervention can prevent weight gain in women compared to general health information.We conducted a 1-yr pragmatic, cluster randomised controlled trial in 41 Australian towns (clusters randomised using a computer-generated randomisation list for intervention (n = 21 or control (n = 20. Women aged 18 to 50 yr were recruited from the general population to receive a 1-yr self-management lifestyle intervention (HeLP-her consisting of one group session, monthly SMS text messages, one phone coaching session, and a program manual, or to a control group receiving one general women's health education session. From October 2012 to April 2014 we studied 649 women, mean age 39.6 yr (+/- SD 6.7 and BMI of 28.8 kg/m(2 (+/- SD 6.9 with the primary outcome weight change between groups at 1 yr. The mean change in the control was +0.44 kg (95% CI -0.09 to 0.97 and in the intervention group -0.48 kg (95% CI -0.99 to 0.03 with an unadjusted between group difference of -0.92 kg (95% CI -1.67 to -0.16 or -0.87 kg (95% CI -1.62 to -0.13 adjusted for baseline values and clustering. Secondary outcomes included improved diet quality and greater self-management behaviours. The intervention appeared to be equally efficacious across all age, BMI, income, and education subgroups. Loss to follow-up included 23.8% in the intervention group and 21.8% in the control group and was within the anticipated range. Limitations include lack of sensitive tools to measure the small changes to energy intake and physical activity. Those who gained weight may have been less inclined to return for 1 yr weight measures.A low intensity lifestyle program can prevent the persistent weight gain observed in women. Key features included

  12. Half-lives of cluster decay of neutron rich nuclei in trans-tin region

    International Nuclear Information System (INIS)

    Swamy, G.S.; Umesh, T.K.

    2011-01-01

    In this work, the logarithmic half-life [log 10 (T 1/2 )] values have been reported for the exotic decay of some neutron rich even–even parent nuclei (56≤Z≤64) accompanied by the emission of alpha-like and non-alpha-like clusters in the trans-tin region. These values were calculated by using the single line of universal curve (UNIV) for alpha and cluster radioactive decay as well as the universal decay law (UDL). The half-life values were also separately calculated by considering the interacting nuclear potential barrier as the sum of Coulomb and proximity potentials. The half-life values based on the three calculations mentioned above, were found to agree with one another within a few orders of magnitude. Possible conclusions are drawn based on the present study. (author)

  13. DOOCS environment for FPGA-based cavity control system and control algorithms development

    International Nuclear Information System (INIS)

    Pucyk, P.; Koprek, W.; Kaleta, P.; Szewinski, J.; Pozniak, K.T.; Czarski, T.; Romaniuk, R.S.

    2005-01-01

    The paper describes the concept and realization of the DOOCS control software for FPGAbased TESLA cavity controller and simulator (SIMCON). It bases on universal software components, created for laboratory purposes and used in MATLAB based control environment. These modules have been recently adapted to the DOOCS environment to ensure a unified software to hardware communication model. The presented solution can be also used as a general platform for control algorithms development. The proposed interfaces between MATLAB and DOOCS modules allow to check the developed algorithm in the operation environment before implementation in the FPGA. As the examples two systems have been presented. (orig.)

  14. Multi-wavelength study of young and massive galaxy clusters

    International Nuclear Information System (INIS)

    Lemonon, Ludovic

    1999-01-01

    Clusters of galaxies are the most massive objects gravitationally bound observed. They are the consequence of the evolution of most important perturbations in the cosmological microwave background. Their formation depends strongly of the cosmology, so they represent key objects to understand the Universe. The aim of this thesis is to study the processes of formation in clusters of galaxies well far away than previous studies clone, by high-resolution observations obtained by using most powerful telescope in each studied wavelength: X-ray, visible, infrared and radio. After data reductions of 12 clusters located at 0.1; z; 0.3, I was able to classified them in three categories: dynamically perturbed clusters, with substructures in their X-ray/optical image or velocity distribution of galaxies; cooling flows clusters, more relaxed than previous, with huge amount of gas cooling in their center; AGN contaminated, where the central dominant galaxy is an AGN which contaminate considerably the X-ray emission. I have obtained a measurement of the baryonic fraction of the Universe mass, and an estimation of the Universe matter density parameter at the mega-parsec scale, claiming for a low density universe. The ISOCAM data showed the effect of the ICM interactions on the star formation in cluster galaxies, and demonstrated that optical and mid-IR deduced star-formation are not basically compatible. They also showed how IR-emitting galaxies distribute in clusters, most noticeably how 15 um galaxies are located preferably on the edge of clusters. X-ray and radio data showed that clusters at z 0.25 could be find in several dynamical state, similarly with nearby ones, from relaxed to severely perturbed. All clusters present signs of past or present merging, in agreement with hierarchical structure formation scenario. This clusters database is an excellent starting point to study process of merging in clusters since they showed different aspect of this evolution. (author) [fr

  15. Efficacy of an internet-based learning module and small-group debriefing on trainees' attitudes and communication skills toward patients with substance use disorders: results of a cluster randomized controlled trial.

    Science.gov (United States)

    Lanken, Paul N; Novack, Dennis H; Daetwyler, Christof; Gallop, Robert; Landis, J Richard; Lapin, Jennifer; Subramaniam, Geetha A; Schindler, Barbara A

    2015-03-01

    To examine whether an Internet-based learning module and small-group debriefing can improve medical trainees' attitudes and communication skills toward patients with substance use disorders (SUDs). In 2011-2012, 129 internal and family medicine residents and 370 medical students at two medical schools participated in a cluster randomized controlled trial, which assessed the effect of adding a two-part intervention to the SUDs curricula. The intervention included a self-directed, media-rich Internet-based learning module and a small-group, faculty-led debriefing. Primary study outcomes were changes in self-assessed attitudes in the intervention group (I-group) compared with those in the control group (C-group) (i.e., a difference of differences). For residents, the authors used real-time, Web-based interviews of standardized patients to assess changes in communication skills. Statistical analyses, conducted separately for residents and students, included hierarchical linear modeling, adjusted for site, participant type, cluster, and individual scores at baseline. The authors found no significant differences between the I- and C-groups in attitudes for residents or students at baseline. Compared with those in the C-group, residents, but not students, in the I-group had more positive attitudes toward treatment efficacy and self-efficacy at follow-up (Pcommunication skills toward patients with SUDs among residents. Enhanced attitudes and skills may result in improved care for these patients.

  16. An adaptive clustering algorithm for image matching based on corner feature

    Science.gov (United States)

    Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

    2018-04-01

    The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

  17. Generating clustered scale-free networks using Poisson based localization of edges

    Science.gov (United States)

    Türker, İlker

    2018-05-01

    We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach.

  18. Galaxy Clusters, Near and Far, Have a Lot in Common

    Science.gov (United States)

    2005-04-01

    Using two orbiting X-ray telescopes, a team of international astronomers has examined distant galaxy clusters in order to compare them with their counterparts that are relatively close by. Speaking today at the RAS National Astronomy Meeting in Birmingham, Dr. Ben Maughan (Harvard-Smithsonian Center for Astrophysics), presented the results of this new analysis. The observations indicate that, despite the great expansion that the Universe has undergone since the Big Bang, galaxy clusters both local and distant have a great deal in common. This discovery could eventually lead to a better understanding of how to "weigh" these enormous structures, and, in so doing, answer important questions about the nature and structure of the Universe. Clusters of galaxies, the largest known gravitationally-bound objects, are the knots in the cosmic web of structure that permeates the Universe. Theoretical models make predictions about the number, distribution and properties of these clusters. Scientists can test and improve models of the Universe by comparing these predictions with observations. The most powerful way of doing this is to measure the masses of galaxy clusters, particularly those in the distant Universe. However, weighing galaxy clusters is extremely difficult. One relatively easy way to weigh a galaxy cluster is to use simple laws ("scaling relations") to estimate its weight from properties that are easy to observe, like its luminosity (brightness) or temperature. This is like estimating someone's weight from their height if you didn't have any scales. Over the last 3 years, a team of researchers, led by Ben Maughan, has observed 11 distant galaxy clusters with ESA's XMM-Newton and NASA's Chandra X-ray Observatory. The clusters have redshifts of z = 0.6-1.0, which corresponds to distances of 6 to 8 billion light years. This means that we see them as they were when the Universe was half its present age. The survey included two unusual systems, one in which two massive

  19. TreeCluster: Massively scalable transmission clustering using phylogenetic trees

    OpenAIRE

    Moshiri, Alexander

    2018-01-01

    Background: The ability to infer transmission clusters from molecular data is critical to designing and evaluating viral control strategies. Viral sequencing datasets are growing rapidly, but standard methods of transmission cluster inference do not scale well beyond thousands of sequences. Results: I present TreeCluster, a cross-platform tool that performs transmission cluster inference on a given phylogenetic tree orders of magnitude faster than existing inference methods and supports multi...

  20. Unsupervised Performance Evaluation Strategy for Bridge Superstructure Based on Fuzzy Clustering and Field Data

    Directory of Open Access Journals (Sweden)

    Yubo Jiao

    2013-01-01

    Full Text Available Performance evaluation of a bridge is critical for determining the optimal maintenance strategy. An unsupervised bridge superstructure state assessment method is proposed in this paper based on fuzzy clustering and bridge field measured data. Firstly, the evaluation index system of bridge is constructed. Secondly, a certain number of bridge health monitoring data are selected as clustering samples to obtain the fuzzy similarity matrix and fuzzy equivalent matrix. Finally, different thresholds are selected to form dynamic clustering maps and determine the best classification based on statistic analysis. The clustering result is regarded as a sample base, and the bridge state can be evaluated by calculating the fuzzy nearness between the unknown bridge state data and the sample base. Nanping Bridge in Jilin Province is selected as the engineering project to verify the effectiveness of the proposed method.

  1. Improvement of perinatal and newborn care in rural Pakistan through community-based strategies: a cluster-randomised effectiveness trial.

    Science.gov (United States)

    Bhutta, Zulfiqar A; Soofi, Sajid; Cousens, Simon; Mohammad, Shah; Memon, Zahid A; Ali, Imran; Feroze, Asher; Raza, Farrukh; Khan, Amanullah; Wall, Steve; Martines, Jose

    2011-01-29

    Newborn deaths account for 57% of deaths in children younger than 5 years in Pakistan. Although a large programme of trained lady health workers (LHWs) exists, the effectiveness of this training on newborn outcomes has not been studied. We aimed to evaluate the effectiveness of a community-based intervention package, principally delivered through LHWs working with traditional birth attendants and community health committees, for reduction of perinatal and neonatal mortality in a rural district of Pakistan. We undertook a cluster randomised trial between February, 2006, and March, 2008, in Hala and Matiari subdistricts, Pakistan. Catchment areas of primary care facilities and all affiliated LHWs were used to define clusters, which were allocated to intervention and control groups by restricted, stratified randomisation. The intervention package delivered by LHWs through group sessions consisted of promotion of antenatal care and maternal health education, use of clean delivery kits, facility births, immediate newborn care, identification of danger signs, and promotion of careseeking; control clusters received routine care. Independent data collectors undertook quarterly household surveillance to capture data for births, deaths, and household practices related to maternal and newborn care. Data collectors were masked to cluster allocation; those analysing data were not. The primary outcome was perinatal and all-cause neonatal mortality. Analysis was by intention to treat. This trial is registered, ISRCTN16247511. 16 clusters were assigned to intervention (23,353 households, 12,391 total births) and control groups (23,768 households, 11,443 total births). LHWs in the intervention clusters were able to undertake 4428 (63%) of 7084 planned group sessions, but were only able to visit 2943 neonates (24%) of a total 12,028 livebirths in their catchment villages. Stillbirths were reduced in intervention clusters (39·1 stillbirths per 1000 total births) compared with

  2. Recognition of genetically modified product based on affinity propagation clustering and terahertz spectroscopy

    Science.gov (United States)

    Liu, Jianjun; Kan, Jianquan

    2018-04-01

    In this paper, based on the terahertz spectrum, a new identification method of genetically modified material by support vector machine (SVM) based on affinity propagation clustering is proposed. This algorithm mainly uses affinity propagation clustering algorithm to make cluster analysis and labeling on unlabeled training samples, and in the iterative process, the existing SVM training data are continuously updated, when establishing the identification model, it does not need to manually label the training samples, thus, the error caused by the human labeled samples is reduced, and the identification accuracy of the model is greatly improved.

  3. Biological consequences of potential repair intermediates of clustered base damage site in Escherichia coli

    Energy Technology Data Exchange (ETDEWEB)

    Shikazono, Naoya, E-mail: shikazono.naoya@jaea.go.jp [Japan Atomic Energy Agency, Advanced Research Science Center, 2-4 Shirakata-Shirane, Tokai-mura, Naka-gun, Ibaraki 319-1195 (Japan); O' Neill, Peter [Gray Institute for Radiation Oncology and Biology, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ (United Kingdom)

    2009-10-02

    Clustered DNA damage induced by a single radiation track is a unique feature of ionizing radiation. Using a plasmid-based assay in Escherichia coli, we previously found significantly higher mutation frequencies for bistranded clusters containing 7,8-dihydro-8-oxoguanine (8-oxoG) and 5,6-dihydrothymine (DHT) than for either a single 8-oxoG or a single DHT in wild type and in glycosylase-deficient strains of E. coli. This indicates that the removal of an 8-oxoG from a clustered damage site is most likely retarded compared to the removal of a single 8-oxoG. To gain further insights into the processing of bistranded base lesions, several potential repair intermediates following 8-oxoG removal were assessed. Clusters, such as DHT + apurinic/apyrimidinic (AP) and DHT + GAP have relatively low mutation frequencies, whereas clusters, such as AP + AP or GAP + AP, significantly reduce the number of transformed colonies, most probably through formation of a lethal double strand break (DSB). Bistranded AP sites placed 3' to each other with various interlesion distances also blocked replication. These results suggest that bistranded base lesions, i.e., single base lesions on each strand, but not clusters containing only AP sites and strand breaks, are repaired in a coordinated manner so that the formation of DSBs is avoided. We propose that, when either base lesion is initially excised from a bistranded base damage site, the remaining base lesion will only rarely be converted into an AP site or a single strand break in vivo.

  4. Biological consequences of potential repair intermediates of clustered base damage site in Escherichia coli

    International Nuclear Information System (INIS)

    Shikazono, Naoya; O'Neill, Peter

    2009-01-01

    Clustered DNA damage induced by a single radiation track is a unique feature of ionizing radiation. Using a plasmid-based assay in Escherichia coli, we previously found significantly higher mutation frequencies for bistranded clusters containing 7,8-dihydro-8-oxoguanine (8-oxoG) and 5,6-dihydrothymine (DHT) than for either a single 8-oxoG or a single DHT in wild type and in glycosylase-deficient strains of E. coli. This indicates that the removal of an 8-oxoG from a clustered damage site is most likely retarded compared to the removal of a single 8-oxoG. To gain further insights into the processing of bistranded base lesions, several potential repair intermediates following 8-oxoG removal were assessed. Clusters, such as DHT + apurinic/apyrimidinic (AP) and DHT + GAP have relatively low mutation frequencies, whereas clusters, such as AP + AP or GAP + AP, significantly reduce the number of transformed colonies, most probably through formation of a lethal double strand break (DSB). Bistranded AP sites placed 3' to each other with various interlesion distances also blocked replication. These results suggest that bistranded base lesions, i.e., single base lesions on each strand, but not clusters containing only AP sites and strand breaks, are repaired in a coordinated manner so that the formation of DSBs is avoided. We propose that, when either base lesion is initially excised from a bistranded base damage site, the remaining base lesion will only rarely be converted into an AP site or a single strand break in vivo.

  5. Universally applicable design concept of stably controlling an HTGR-hydrogen production system

    International Nuclear Information System (INIS)

    Hada, Kazuhiko; Shibata, Taiju; Nishihara, Tetsuo; Shiozawa, Shusaku

    1996-01-01

    An HTGR-hydrogen production system should be designed to have stable controllability because of a large difference in thermal dynamics between reactor and hydrogen production system and such a control design concept should be universally applicable to a variety of hydrogen production processes by the use of nuclear heat from HTGR. A transient response analysis of an HTGR-steam reforming hydrogen production system showed that a steam generator installed in a helium circuit for cooling the nuclear reactor provides stable controllability of the total system, resulting in avoiding a reactor scram. A survey of control design-related characteristics among several hydrogen production processes revealed the similarity of endothermic chemical reactions by the use of high temperature heat and that steam is required as a reactant of the endothermic reaction or for preheating a reactant. Based on these findings, a system design concept with stable controllability and universal applicability was proposed to install a steam generator as a downstream cooler of an endothermic reactor in the helium circuit of an HTGR-hydrogen production system. (author)

  6. Size and composition dependence of the frozen structures in Co-based bimetallic clusters

    International Nuclear Information System (INIS)

    Li, Guojian; Wang, Qiang; Cao, Yongze; Du, Jiaojiao; He, Jicheng

    2012-01-01

    This Letter studies the size-dependent freezing of Co, Co–Ni, and Co–Cu clusters by using molecular dynamics with embedded atom method. Size effect occurs in these three types of clusters. The clusters with large sizes always freeze to form their bulk-like structures. However, the frozen structures for small sizes are generally related to their compositions. The icosahedral clusters are formed for Co clusters (for ⩽3.2 nm diameter) and also for Co–Ni clusters but at a larger size range (for ⩽4.08 nm). Upon the Co–Cu clusters, decahedral structure is obtained for small size (for 2.47 nm). The released energy induced the structural transformation plays a key role in the frozen structures. These results indicate that the preformed clusters with special structures can be tuned by controlling their compositions and sizes. -- Highlights: ► The size effect occurs in the Co, Co–Ni, and Co–Cu clusters. ► The clusters with large sizes always freeze to form their bulk-like structures. ► The frozen structures for small sizes are generally related to their compositions. ► Icosahedron is formed for Co and also for Co–Ni but at a larger size range. ► Upon the Co–Cu clusters, decahedral structure is obtained for small size.

  7. Galaxy and cluster formation in a universe dominated by cold dark matter

    International Nuclear Information System (INIS)

    Primack, J.R.

    1984-07-01

    The dark matter (DM) that appears to be gravitationally dominant on all astronomical scales larger than the cores of galaxies can be classified, on the basis of its characteristic free-streaming damping mass M/sub D/, as hot (M/sub D/ approx. 10 15 M/sub mass/), warm (M/sub D/ approx. 10 11 M/sub mass/), or cold (M/sub D 8 M/sub mass/). For the case of cold DM, the shape of the DM fluctuation spectrum is determined by (a) the primordial spectrum (on scales larger than the horizon), and (b) stagspansion, the stagnation of the growth of DM fluctuations that enter the horizon while the universe is still radiation-dominated. An attractive feature of the cold dark matter hypothesis is its considerable predictive power: the post-recombination fluctuation spectrum is calculable, and it in turn governs the formation of galaxies and clusters. Good agreement with the data is obtained for a Zeldovich spectrum of primordial fluctuations

  8. Galaxy and cluster formation in a universe dominated by cold dark matter

    Energy Technology Data Exchange (ETDEWEB)

    Primack, J.R.

    1984-07-01

    The dark matter (DM) that appears to be gravitationally dominant on all astronomical scales larger than the cores of galaxies can be classified, on the basis of its characteristic free-streaming damping mass M/sub D/, as hot (M/sub D/ approx. 10/sup 15/ M/sub mass/), warm (M/sub D/ approx. 10/sup 11/ M/sub mass/), or cold (M/sub D < 10/sup 8/ M/sub mass/). For the case of cold DM, the shape of the DM fluctuation spectrum is determined by (a) the primordial spectrum (on scales larger than the horizon), and (b) stagspansion, the stagnation of the growth of DM fluctuations that enter the horizon while the universe is still radiation-dominated. An attractive feature of the cold dark matter hypothesis is its considerable predictive power: the post-recombination fluctuation spectrum is calculable, and it in turn governs the formation of galaxies and clusters. Good agreement with the data is obtained for a Zeldovich spectrum of primordial fluctuations.

  9. Photometric redshifts as a tool for studying the Coma cluster galaxy populations

    Science.gov (United States)

    Adami, C.; Ilbert, O.; Pelló, R.; Cuillandre, J. C.; Durret, F.; Mazure, A.; Picat, J. P.; Ulmer, M. P.

    2008-12-01

    Aims: We apply photometric redshift techniques to an investigation of the Coma cluster galaxy luminosity function (GLF) at faint magnitudes, in particular in the u* band where basically no studies are presently available at these magnitudes. Methods: Cluster members were selected based on probability distribution function from photometric redshift calculations applied to deep u^*, B, V, R, I images covering a region of almost 1 deg2 (completeness limit R ~ 24). In the area covered only by the u* image, the GLF was also derived after a statistical background subtraction. Results: Global and local GLFs in the B, V, R, and I bands obtained with photometric redshift selection are consistent with our previous results based on a statistical background subtraction. The GLF in the u* band shows an increase in the faint end slope towards the outer regions of the cluster. The analysis of the multicolor type spatial distribution reveals that late type galaxies are distributed in clumps in the cluster outskirts, where X-ray substructures are also detected and where the GLF in the u* band is steeper. Conclusions: We can reproduce the GLFs computed with classical statistical subtraction methods by applying a photometric redshift technique. The u* GLF slope is steeper in the cluster outskirts, varying from α ~ -1 in the cluster center to α ~ -2 in the cluster periphery. The concentrations of faint late type galaxies in the cluster outskirts could explain these very steep slopes, assuming a short burst of star formation in these galaxies when entering the cluster. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is also partly based on data products produced at

  10. Impact of a school-based intervention on nutritional education and physical activity in primary public schools in Chile (KIND programme study protocol: cluster randomised controlled trial

    Directory of Open Access Journals (Sweden)

    Nelly Bustos

    2016-12-01

    Full Text Available Abstract Background Chile has suffered a fast increase in childhood obesity in the last 10 years. As a result, several school programmes have been implemented, however the effectiveness of these needs to be evaluated to identify and prioritize strategies to curve this trend. Methods Cluster randomized controlled trial. Twelve primary public schools chosen at random over three regions of the country will take part in this study. The sample size consisted of a total of 1,655 children. For each region one school will be selected for each of the three nutritional intervention modes and one school will be selected as the control group. The intervention modes consist of the following: Healthy Kiosk and nutritional education (KSEAN; Optimized physical activity (AFSO; Healthy Kiosk and nutritional education (KSEAN + optimized physical activity (AFSO; Control group. The effectiveness of each intervention will be evaluated by determining the nutritional condition of each child by measuring percentage of body fat, BMI and the z-score of the BMI. This study will also identify the eating behaviours, nutritional knowledge and fitness of each child, along with the effective time of moderate activity during physical education classes. Discussion A protocol to evaluate the effectiveness of a school based intervention to control and/or reduce the rates of childhood obesity for children between 6 and 10 years of age was developed. The protocol was developed in line with the Declaration of Helsinski, the Nüremberg Code and the University of Chile Guidelines for ethical committees, and was approved by the INTA, Universidad de Chile ethical committee on Wednesday 12 March 2014. There is consensus among researchers and health and education personnel that schools are a favourable environment for actions to prevent and/or control childhood obesity. However a lack of evidence on the effectiveness of interventions to date has led some to question the wisdom of

  11. Impact of a school-based intervention on nutritional education and physical activity in primary public schools in Chile (KIND) programme study protocol: cluster randomised controlled trial.

    Science.gov (United States)

    Bustos, Nelly; Olivares, Sonia; Leyton, Bárbara; Cano, Marcelo; Albala, Cecilia

    2016-12-03

    Chile has suffered a fast increase in childhood obesity in the last 10 years. As a result, several school programmes have been implemented, however the effectiveness of these needs to be evaluated to identify and prioritize strategies to curve this trend. Cluster randomized controlled trial. Twelve primary public schools chosen at random over three regions of the country will take part in this study. The sample size consisted of a total of 1,655 children. For each region one school will be selected for each of the three nutritional intervention modes and one school will be selected as the control group. The intervention modes consist of the following: Healthy Kiosk and nutritional education (KSEAN); Optimized physical activity (AFSO); Healthy Kiosk and nutritional education (KSEAN) + optimized physical activity (AFSO); Control group. The effectiveness of each intervention will be evaluated by determining the nutritional condition of each child by measuring percentage of body fat, BMI and the z-score of the BMI. This study will also identify the eating behaviours, nutritional knowledge and fitness of each child, along with the effective time of moderate activity during physical education classes. A protocol to evaluate the effectiveness of a school based intervention to control and/or reduce the rates of childhood obesity for children between 6 and 10 years of age was developed. The protocol was developed in line with the Declaration of Helsinski, the Nüremberg Code and the University of Chile Guidelines for ethical committees, and was approved by the INTA, Universidad de Chile ethical committee on Wednesday 12 March 2014. There is consensus among researchers and health and education personnel that schools are a favourable environment for actions to prevent and/or control childhood obesity. However a lack of evidence on the effectiveness of interventions to date has led some to question the wisdom of allocating resources to programmes. This is the first study

  12. Reconstructing galaxy histories from globular clusters.

    Science.gov (United States)

    West, Michael J; Côté, Patrick; Marzke, Ronald O; Jordán, Andrés

    2004-01-01

    Nearly a century after the true nature of galaxies as distant 'island universes' was established, their origin and evolution remain great unsolved problems of modern astrophysics. One of the most promising ways to investigate galaxy formation is to study the ubiquitous globular star clusters that surround most galaxies. Globular clusters are compact groups of up to a few million stars. They generally formed early in the history of the Universe, but have survived the interactions and mergers that alter substantially their parent galaxies. Recent advances in our understanding of the globular cluster systems of the Milky Way and other galaxies point to a complex picture of galaxy genesis driven by cannibalism, collisions, bursts of star formation and other tumultuous events.

  13. Particle Swarm Optimization and harmony search based clustering and routing in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Veena Anand

    2017-01-01

    Full Text Available Wireless Sensor Networks (WSN has the disadvantage of limited and non-rechargeable energy resource in WSN creates a challenge and led to development of various clustering and routing algorithms. The paper proposes an approach for improving network lifetime by using Particle swarm optimization based clustering and Harmony Search based routing in WSN. So in this paper, global optimal cluster head are selected and Gateway nodes are introduced to decrease the energy consumption of the CH while sending aggregated data to the Base station (BS. Next, the harmony search algorithm based Local Search strategy finds best routing path for gateway nodes to the Base Station. Finally, the proposed algorithm is presented.

  14. Cluster computing for lattice QCD simulations

    International Nuclear Information System (INIS)

    Coddington, P.D.; Williams, A.G.

    2000-01-01

    Full text: Simulations of lattice quantum chromodynamics (QCD) require enormous amounts of compute power. In the past, this has usually involved sharing time on large, expensive machines at supercomputing centres. Over the past few years, clusters of networked computers have become very popular as a low-cost alternative to traditional supercomputers. The dramatic improvements in performance (and more importantly, the ratio of price/performance) of commodity PCs, workstations, and networks have made clusters of off-the-shelf computers an attractive option for low-cost, high-performance computing. A major advantage of clusters is that since they can have any number of processors, they can be purchased using any sized budget, allowing research groups to install a cluster for their own dedicated use, and to scale up to more processors if additional funds become available. Clusters are now being built for high-energy physics simulations. Wuppertal has recently installed ALiCE, a cluster of 128 Alpha workstations running Linux, with a peak performance of 158 G flops. The Jefferson Laboratory in the US has a 16 node Alpha cluster and plans to upgrade to a 256 processor machine. In Australia, several large clusters have recently been installed. Swinburne University of Technology has a cluster of 64 Compaq Alpha workstations used for astrophysics simulations. Early this year our DHPC group constructed a cluster of 116 dual Pentium PCs (i.e. 232 processors) connected by a Fast Ethernet network, which is used by chemists at Adelaide University and Flinders University to run computational chemistry codes. The Australian National University has recently installed a similar PC cluster with 192 processors. The Centre for the Subatomic Structure of Matter (CSSM) undertakes large-scale high-energy physics calculations, mainly lattice QCD simulations. The choice of the computer and network hardware for a cluster depends on the particular applications to be run on the machine. Our

  15. Fast Gene Ontology based clustering for microarray experiments

    Directory of Open Access Journals (Sweden)

    Ovaska Kristian

    2008-11-01

    Full Text Available Abstract Background Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. Results We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Conclusion Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

  16. Family-Based Cluster Randomized Controlled Trial Enhancing Physical Activity and Motor Competence in 4-7-Year-Old Children.

    Directory of Open Access Journals (Sweden)

    Arto Laukkanen

    Full Text Available Little is known of how to involve families in physical activity (PA interventions for children. In this cluster randomized controlled trial, we recruited families with four- to seven-year-old children to participate in a year-long study where parents in the intervention group families (n = 46 received tailored counseling to increase children’s PA. Structured PA was not served. Control group families (n = 45 did not receive any counseling. PA in all children (n = 91; mean age 6.16 ± 1.13 years at the baseline was measured by accelerometers at the baseline and after three, six, nine and 12 months. Motor competence (MC (n = 89 was measured at the baseline and after six and 12 months by a KTK (KörperkoordinationsTest für Kinder and throwing and catching a ball (TCB protocols. The effect of parental counseling on study outcomes was analyzed by a linear mixed-effects model fit by REML and by a Mann-Whitney U test in the case of the TCB. As season was hypothesized to affect counseling effect, an interaction of season on the study outcomes was examined. The results show significant decrease of MVPA in the intervention group when compared to the control group (p < .05. The TCB showed a nearly significant improvement at six months in the intervention group compared to the controls (p = .051, but not at 12 months. The intervention group had a steadier development of the KTK when the interaction of season was taken into account. In conclusion, more knowledge of family constructs associating with the effectiveness of counseling is needed for understanding how to enhance PA in children by parents. However, a hypothesis may be put forward that family-based counseling during an inactive season rather than an active season may provide a more lasting effect on the development of KTK in children.Controlled-Trials.com ISRCTN28668090.

  17. Environment-based selection effects of Planck clusters

    Energy Technology Data Exchange (ETDEWEB)

    Kosyra, R.; Gruen, D.; Seitz, S.; Mana, A.; Rozo, E.; Rykoff, E.; Sanchez, A.; Bender, R.

    2015-07-24

    We investigate whether the large-scale structure environment of galaxy clusters imprints a selection bias on Sunyaev–Zel'dovich (SZ) catalogues. Such a selection effect might be caused by line of sight (LoS) structures that add to the SZ signal or contain point sources that disturb the signal extraction in the SZ survey. We use the Planck PSZ1 union catalogue in the Sloan Digital Sky Survey (SDSS) region as our sample of SZ-selected clusters. We calculate the angular two-point correlation function (2pcf) for physically correlated, foreground and background structure in the RedMaPPer SDSS DR8 catalogue with respect to each cluster. We compare our results with an optically selected comparison cluster sample and with theoretical predictions. In contrast to the hypothesis of no environment-based selection, we find a mean 2pcf for background structures of -0.049 on scales of ≲40 arcmin, significantly non-zero at ~4σ, which means that Planck clusters are more likely to be detected in regions of low background density. We hypothesize this effect arises either from background estimation in the SZ survey or from radio sources in the background. We estimate the defect in SZ signal caused by this effect to be negligibly small, of the order of ~10-4 of the signal of a typical Planck detection. Analogously, there are no implications on X-ray mass measurements. However, the environmental dependence has important consequences for weak lensing follow up of Planck galaxy clusters: we predict that projection effects account for half of the mass contained within a 15 arcmin radius of Planck galaxy clusters. We did not detect a background underdensity of CMASS LRGs, which also leaves a spatially varying redshift dependence of the Planck SZ selection function as a possible cause for our findings.

  18. Investigating role stress in frontline bank employees: A cluster based approach

    Directory of Open Access Journals (Sweden)

    Arti Devi

    2013-09-01

    Full Text Available An effective role stress management programme would benefit from a segmentation of employees based on their experience of role stressors. This study explores role stressor based segments of frontline bank employees towards providing a framework for designing such a programme. Cluster analysis on a random sample of 501 frontline employees of commercial banks in Jammu and Kashmir (India revealed three distinct segments – “overloaded employees”, “unclear employees”, and “underutilised employees”, based on their experience of role stressors. The findings suggest a customised approach to role stress management, with the role stress management programme designed to address cluster specific needs.

  19. Hopping models and ac universality

    DEFF Research Database (Denmark)

    Dyre, Jeppe; Schrøder, Thomas

    2002-01-01

    Some general relations for hopping models are established. We proceed to discuss the universality of the ac conductivity which arises in the extreme disorder limit of the random barrier model. It is shown that the relevant dimension entering into the diffusion cluster approximation (DCA) is the h......Some general relations for hopping models are established. We proceed to discuss the universality of the ac conductivity which arises in the extreme disorder limit of the random barrier model. It is shown that the relevant dimension entering into the diffusion cluster approximation (DCA......) is the harmonic (fracton) dimension of the diffusion cluster. The temperature scaling of the dimensionless frequency entering into the DCA is discussed. Finally, some open problems regarding ac universality are listed....

  20. Distribution-based fuzzy clustering of electrical resistivity tomography images for interface detection

    Science.gov (United States)

    Ward, W. O. C.; Wilkinson, P. B.; Chambers, J. E.; Oxby, L. S.; Bai, L.

    2014-04-01

    A novel method for the effective identification of bedrock subsurface elevation from electrical resistivity tomography images is described. Identifying subsurface boundaries in the topographic data can be difficult due to smoothness constraints used in inversion, so a statistical population-based approach is used that extends previous work in calculating isoresistivity surfaces. The analysis framework involves a procedure for guiding a clustering approach based on the fuzzy c-means algorithm. An approximation of resistivity distributions, found using kernel density estimation, was utilized as a means of guiding the cluster centroids used to classify data. A fuzzy method was chosen over hard clustering due to uncertainty in hard edges in the topography data, and a measure of clustering uncertainty was identified based on the reciprocal of cluster membership. The algorithm was validated using a direct comparison of known observed bedrock depths at two 3-D survey sites, using real-time GPS information of exposed bedrock by quarrying on one site, and borehole logs at the other. Results show similarly accurate detection as a leading isosurface estimation method, and the proposed algorithm requires significantly less user input and prior site knowledge. Furthermore, the method is effectively dimension-independent and will scale to data of increased spatial dimensions without a significant effect on the runtime. A discussion on the results by automated versus supervised analysis is also presented.