Q-systems as cluster algebras

International Nuclear Information System (INIS)

Kedem, Rinat

2008-01-01

Q-systems first appeared in the analysis of the Bethe equations for the XXX model and generalized Heisenberg spin chains (Kirillov and Reshetikhin 1987 Zap. Nauchn. Sem. Leningr. Otd. Mat. Inst. Steklov. 160 211-21, 301). Such systems are known to exist for any simple Lie algebra and many other Kac-Moody algebras. We formulate the Q-system associated with any simple, simply-laced Lie algebras g in the language of cluster algebras (Fomin and Zelevinsky 2002 J. Am. Math. Soc. 15 497-529), and discuss the relation of the polynomiality property of the solutions of the Q-system in the initial variables, which follows from the representation-theoretical interpretation, to the Laurent phenomenon in cluster algebras (Fomin and Zelevinsky 2002 Adv. Appl. Math. 28 119-44)

MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters

Directory of Open Access Journals (Sweden)

Abreu Rui MV

2010-10-01

Full Text Available Abstract Background Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. Implementation MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. Conclusion MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a

Clustering execution in a processing system to increase power savings

Energy Technology Data Exchange (ETDEWEB)

Bose, Pradip; Buyuktosunoglu, Alper; Jacobson, Hans M.; Vega, Augusto J.

2018-04-03

Embodiments relate to clustering execution in a processing system. An aspect includes accessing a control flow graph that defines a data dependency and an execution sequence of a plurality of tasks of an application that executes on a plurality of system components. The execution sequence of the tasks in the control flow graph is modified as a clustered control flow graph that clusters active and idle phases of a system component while maintaining the data dependency. The clustered control flow graph is sent to an operating system, where the operating system utilizes the clustered control flow graph for scheduling the tasks.

Clustering execution in a processing system to increase power savings

Science.gov (United States)

Bose, Pradip; Buyuktosunoglu, Alper; Jacobson, Hans M.; Vega, Augusto J.

2018-03-20

Embodiments relate to clustering execution in a processing system. An aspect includes accessing a control flow graph that defines a data dependency and an execution sequence of a plurality of tasks of an application that executes on a plurality of system components. The execution sequence of the tasks in the control flow graph is modified as a clustered control flow graph that clusters active and idle phases of a system component while maintaining the data dependency. The clustered control flow graph is sent to an operating system, where the operating system utilizes the clustered control flow graph for scheduling the tasks.

A COMPUTER CLUSTER SYSTEM FOR PSEUDO-PARALLEL EXECUTION OF GEANT4 SERIAL APPLICATION

Directory of Open Access Journals (Sweden)

Memmo Federici

2013-12-01

Full Text Available Simulation of the interactions between particles and matter in studies for developing X-rays detectors generally requires very long calculation times (up to several days or weeks. These times are often a serious limitation for the success of the simulations and for the accuracy of the simulated models. One of the tools used by the scientific community to perform these simulations is Geant4 (Geometry And Tracking [2, 3]. On the best of experience in the design of the AVES cluster computing system, Federici et al. [1], the IAPS (Istituto di Astrofisica e Planetologia Spaziali INAF laboratories were able to develop a cluster computer system dedicated to Geant 4. The Cluster is easy to use and easily expandable, and thanks to the design criteria adopted it achieves an excellent compromise between performance and cost. The management software developed for the Cluster splits the single instance of simulation on the cores available, allowing the use of software written for serial computation to reach a computing speed similar to that obtainable from a native parallel software. The simulations carried out on the Cluster showed an increase in execution time by a factor of 20 to 60 compared to the times obtained with the use of a single PC of medium quality.

Dynamically Allocated Virtual Clustering Management System Users Guide

Science.gov (United States)

2016-11-01

ARL-SR-0366 ● NOV 2016 US Army Research Laboratory Dynamically Allocated Virtual Clustering Management System User’s Guide by... Clustering Management System User’s Guide by Kelvin M Marcus Computational and Information Sciences Directorate, ARL...

THE HST/ACS COMA CLUSTER SURVEY. IV. INTERGALACTIC GLOBULAR CLUSTERS AND THE MASSIVE GLOBULAR CLUSTER SYSTEM AT THE CORE OF THE COMA GALAXY CLUSTER

International Nuclear Information System (INIS)

Peng, Eric W.; Ferguson, Henry C.; Goudfrooij, Paul; Hammer, Derek; Lucey, John R.; Marzke, Ronald O.; Puzia, Thomas H.; Carter, David; Balcells, Marc; Bridges, Terry; Chiboucas, Kristin; Del Burgo, Carlos; Graham, Alister W.; Guzman, Rafael; Hudson, Michael J.; Matkovic, Ana

2011-01-01

Intracluster stellar populations are a natural result of tidal interactions in galaxy clusters. Measuring these populations is difficult, but important for understanding the assembly of the most massive galaxies. The Coma cluster of galaxies is one of the nearest truly massive galaxy clusters and is host to a correspondingly large system of globular clusters (GCs). We use imaging from the HST/ACS Coma Cluster Survey to present the first definitive detection of a large population of intracluster GCs (IGCs) that fills the Coma cluster core and is not associated with individual galaxies. The GC surface density profile around the central massive elliptical galaxy, NGC 4874, is dominated at large radii by a population of IGCs that extend to the limit of our data (R +4000 -5000 (systematic) IGCs out to this radius, and that they make up ∼70% of the central GC system, making this the largest GC system in the nearby universe. Even including the GC systems of other cluster galaxies, the IGCs still make up ∼30%-45% of the GCs in the cluster core. Observational limits from previous studies of the intracluster light (ICL) suggest that the IGC population has a high specific frequency. If the IGC population has a specific frequency similar to high-S N dwarf galaxies, then the ICL has a mean surface brightness of μ V ∼ 27 mag arcsec -2 and a total stellar mass of roughly 10 12 M sun within the cluster core. The ICL makes up approximately half of the stellar luminosity and one-third of the stellar mass of the central (NGC 4874+ICL) system. The color distribution of the IGC population is bimodal, with blue, metal-poor GCs outnumbering red, metal-rich GCs by a ratio of 4:1. The inner GCs associated with NGC 4874 also have a bimodal distribution in color, but with a redder metal-poor population. The fraction of red IGCs (20%), and the red color of those GCs, implies that IGCs can originate from the halos of relatively massive, L* galaxies, and not solely from the disruption of

Securing recommender systems against shilling attacks using social-based clustering

KAUST Repository

Zhang, Xiangliang

2013-07-01

Recommender systems (RS) have been found supportive and practical in e-commerce and been established as useful aiding services. Despite their great adoption in the user communities, RS are still vulnerable to unscrupulous producers who try to promote their products by shilling the systems. With the advent of social networks new sources of information have been made available which can potentially render RS more resistant to attacks. In this paper we explore the information provided in the form of social links with clustering for diminishing the impact of attacks. We propose two algorithms, CluTr and WCluTr, to combine clustering with "trust" among users. We demonstrate that CluTr and WCluTr enhance the robustness of RS by experimentally evaluating them on data from a public consumer recommender system Epinions.com. © 2013 Springer Science+Business Media New York & Science Press, China.

Subspace identification of distributed clusters of homogeneous systems

NARCIS (Netherlands)

Yu, C.; Verhaegen, M.H.G.

2017-01-01

This note studies the identification of a network comprised of interconnected clusters of LTI systems. Each cluster consists of homogeneous dynamical systems, and its interconnections with the rest of the network are unmeasurable. A subspace identification method is proposed for identifying a single

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems

Directory of Open Access Journals (Sweden)

Lili Shen

2018-06-01

Full Text Available The network real-time kinematic (RTK technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI, and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs, robotic equipment, etc. require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Performance Enhancement of a Web-Based Picture Archiving and Communication System Using Commercial Off-the-Shelf Server Clusters

Directory of Open Access Journals (Sweden)

Yan-Lin Liu

2014-01-01

Full Text Available The rapid development of picture archiving and communication systems (PACSs thoroughly changes the way of medical informatics communication and management. However, as the scale of a hospital’s operations increases, the large amount of digital images transferred in the network inevitably decreases system efficiency. In this study, a server cluster consisting of two server nodes was constructed. Network load balancing (NLB, distributed file system (DFS, and structured query language (SQL duplication services were installed. A total of 1 to 16 workstations were used to transfer computed radiography (CR, computed tomography (CT, and magnetic resonance (MR images simultaneously to simulate the clinical situation. The average transmission rate (ATR was analyzed between the cluster and noncluster servers. In the download scenario, the ATRs of CR, CT, and MR images increased by 44.3%, 56.6%, and 100.9%, respectively, when using the server cluster, whereas the ATRs increased by 23.0%, 39.2%, and 24.9% in the upload scenario. In the mix scenario, the transmission performance increased by 45.2% when using eight computer units. The fault tolerance mechanisms of the server cluster maintained the system availability and image integrity. The server cluster can improve the transmission efficiency while maintaining high reliability and continuous availability in a healthcare environment.

Properties of the disk system of globular clusters

International Nuclear Information System (INIS)

Armandroff, T.E.

1989-01-01

A large refined data sample is used to study the properties and origin of the disk system of globular clusters. A scale height for the disk cluster system of 800-1500 pc is found which is consistent with scale-height determinations for samples of field stars identified with the Galactic thick disk. A rotational velocity of 193 + or - 29 km/s and a line-of-sight velocity dispersion of 59 + or - 14 km/s have been found for the metal-rich clusters. 70 references

A Science Portal and Archive for Extragalactic Globular Cluster Systems Data

Science.gov (United States)

Young, Michael; Rhode, Katherine L.; Gopu, Arvind

2015-01-01

For several years we have been carrying out a wide-field imaging survey of the globular cluster populations of a sample of giant spiral, S0, and elliptical galaxies with distances of ~10-30 Mpc. We use mosaic CCD cameras on the WIYN 3.5-m and Kitt Peak 4-m telescopes to acquire deep BVR imaging of each galaxy and then analyze the data to derive global properties of the globular cluster system. In addition to measuring the total numbers, specific frequencies, spatial distributions, and color distributions for the globular cluster populations, we have produced deep, high-quality images and lists of tens to thousands of globular cluster candidates for the ~40 galaxies included in the survey.With the survey nearing completion, we have been exploring how to efficiently disseminate not only the overall results, but also all of the relevant data products, to the astronomical community. Here we present our solution: a scientific portal and archive for extragalactic globular cluster systems data. With a modern and intuitive web interface built on the same framework as the WIYN One Degree Imager Portal, Pipeline, and Archive (ODI-PPA), our system will provide public access to the survey results and the final stacked mosaic images of the target galaxies. In addition, the astrometric and photometric data for thousands of identified globular cluster candidates, as well as for all point sources detected in each field, will be indexed and searchable. Where available, spectroscopic follow-up data will be paired with the candidates. Advanced imaging tools will enable users to overlay the cluster candidates and other sources on the mosaic images within the web interface, while metadata charting tools will allow users to rapidly and seamlessly plot the survey results for each galaxy and the data for hundreds of thousands of individual sources. Finally, we will appeal to other researchers with similar data products and work toward making our portal a central repository for data

The signatures of the parental cluster on field planetary systems

Science.gov (United States)

Cai, Maxwell Xu; Portegies Zwart, Simon; van Elteren, Arjen

2018-03-01

Due to the high stellar densities in young clusters, planetary systems formed in these environments are likely to have experienced perturbations from encounters with other stars. We carry out direct N-body simulations of multiplanet systems in star clusters to study the combined effects of stellar encounters and internal planetary dynamics. These planetary systems eventually become part of the Galactic field population as the parental cluster dissolves, which is where most presently known exoplanets are observed. We show that perturbations induced by stellar encounters lead to distinct signatures in the field planetary systems, most prominently, the excited orbital inclinations and eccentricities. Planetary systems that form within the cluster's half-mass radius are more prone to such perturbations. The orbital elements are most strongly excited in the outermost orbit, but the effect propagates to the entire planetary system through secular evolution. Planet ejections may occur long after a stellar encounter. The surviving planets in these reduced systems tend to have, on average, higher inclinations and larger eccentricities compared to systems that were perturbed less strongly. As soon as the parental star cluster dissolves, external perturbations stop affecting the escaped planetary systems, and further evolution proceeds on a relaxation time-scale. The outer regions of these ejected planetary systems tend to relax so slowly that their state carries the memory of their last strong encounter in the star cluster. Regardless of the stellar density, we observe a robust anticorrelation between multiplicity and mean inclination/eccentricity. We speculate that the `Kepler dichotomy' observed in field planetary systems is a natural consequence of their early evolution in the parental cluster.

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data

Directory of Open Access Journals (Sweden)

Alessandro Manzi

2017-05-01

Full Text Available Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM, trained with Sequential Minimal Optimization (SMO. The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60 and the Telecommunication Systems Team (TST Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

Cluster Bulleticity

OpenAIRE

Massey, Richard; Kitching, Thomas; Nagai, Daisuke

2010-01-01

The unique properties of dark matter are revealed during collisions between clusters of galaxies, such as the bullet cluster (1E 0657−56) and baby bullet (MACS J0025−12). These systems provide evidence for an additional, invisible mass in the separation between the distributions of their total mass, measured via gravitational lensing, and their ordinary ‘baryonic’ matter, measured via its X-ray emission. Unfortunately, the information available from these systems is limited by their rarity. C...

QCS: a system for querying, clustering and summarizing documents.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M.; Schlesinger, Judith D. (Center for Computing Sciences, Bowie, MD); O' Leary, Dianne P. (University of Maryland, College Park, MD); Conroy, John M. (Center for Computing Sciences, Bowie, MD)

2006-10-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test sets from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence 'trimming', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of the design

QCS : a system for querying, clustering, and summarizing documents.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M.

2006-08-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test sets from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence ''trimming'', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of

Proposed Fuzzy-NN Algorithm with LoRaCommunication Protocol for Clustered Irrigation Systems

Directory of Open Access Journals (Sweden)

Sotirios Kontogiannis

2017-11-01

Full Text Available Modern irrigation systems utilize sensors and actuators, interconnected together as a single entity. In such entities, A.I. algorithms are implemented, which are responsible for the irrigation process. In this paper, the authors present an irrigation Open Watering System (OWS architecture that spatially clusters the irrigation process into autonomous irrigation sections. Authors’ OWS implementation includes a Neuro-Fuzzy decision algorithm called FITRA, which originates from the Greek word for seed. In this paper, the FITRA algorithm is described in detail, as are experimentation results that indicate significant water conservations from the use of the FITRA algorithm. Furthermore, the authors propose a new communication protocol over LoRa radio as an alternative low-energy and long-range OWS clusters communication mechanism. The experimental scenarios confirm that the FITRA algorithm provides more efficient irrigation on clustered areas than existing non-clustered, time scheduled or threshold adaptive algorithms. This is due to the FITRA algorithm’s frequent monitoring of environmental conditions, fuzzy and neural network adaptation as well as adherence to past irrigation preferences.

The properties of the disk system of globular clusters

Science.gov (United States)

Armandroff, Taft E.

1989-01-01

A large refined data sample is used to study the properties and origin of the disk system of globular clusters. A scale height for the disk cluster system of 800-1500 pc is found which is consistent with scale-height determinations for samples of field stars identified with the Galactic thick disk. A rotational velocity of 193 + or - 29 km/s and a line-of-sight velocity dispersion of 59 + or - 14 km/s have been found for the metal-rich clusters.

Performance enhancement of a web-based picture archiving and communication system using commercial off-the-shelf server clusters.

Science.gov (United States)

Liu, Yan-Lin; Shih, Cheng-Ting; Chang, Yuan-Jen; Chang, Shu-Jun; Wu, Jay

2014-01-01

The rapid development of picture archiving and communication systems (PACSs) thoroughly changes the way of medical informatics communication and management. However, as the scale of a hospital's operations increases, the large amount of digital images transferred in the network inevitably decreases system efficiency. In this study, a server cluster consisting of two server nodes was constructed. Network load balancing (NLB), distributed file system (DFS), and structured query language (SQL) duplication services were installed. A total of 1 to 16 workstations were used to transfer computed radiography (CR), computed tomography (CT), and magnetic resonance (MR) images simultaneously to simulate the clinical situation. The average transmission rate (ATR) was analyzed between the cluster and noncluster servers. In the download scenario, the ATRs of CR, CT, and MR images increased by 44.3%, 56.6%, and 100.9%, respectively, when using the server cluster, whereas the ATRs increased by 23.0%, 39.2%, and 24.9% in the upload scenario. In the mix scenario, the transmission performance increased by 45.2% when using eight computer units. The fault tolerance mechanisms of the server cluster maintained the system availability and image integrity. The server cluster can improve the transmission efficiency while maintaining high reliability and continuous availability in a healthcare environment.

Cluster Computing for Embedded/Real-Time Systems

Science.gov (United States)

Katz, D.; Kepner, J.

1999-01-01

Embedded and real-time systems, like other computing systems, seek to maximize computing power for a given price, and thus can significantly benefit from the advancing capabilities of cluster computing.

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.

Supra-galactic colour patterns in globular cluster systems

Science.gov (United States)

Forte, Juan C.

2017-07-01

An analysis of globular cluster systems associated with galaxies included in the Virgo and Fornax Hubble Space Telescope-Advanced Camera Surveys reveals distinct (g - z) colour modulation patterns. These features appear on composite samples of globular clusters and, most evidently, in galaxies with absolute magnitudes Mg in the range from -20.2 to -19.2. These colour modulations are also detectable on some samples of globular clusters in the central galaxies NGC 1399 and NGC 4486 (and confirmed on data sets obtained with different instruments and photometric systems), as well as in other bright galaxies in these clusters. After discarding field contamination, photometric errors and statistical effects, we conclude that these supra-galactic colour patterns are real and reflect some previously unknown characteristic. These features suggest that the globular cluster formation process was not entirely stochastic but included a fraction of clusters that formed in a rather synchronized fashion over large spatial scales, and in a tentative time lapse of about 1.5 Gy at redshifts z between 2 and 4. We speculate that the putative mechanism leading to that synchronism may be associated with large scale feedback effects connected with violent star-forming events and/or with supermassive black holes.

Implementasi Highly Available Website Dengan Distributed Replicated Block Device

Directory of Open Access Journals (Sweden)

Mulyanto Mulyanto

2016-07-01

Full Text Available As an important IT infrastructure, website is a system which requires high reliability and availability levels. Website meets the criteria as a highly available system because website must provide services to clients in real time, handle a large amount of data, and not lose data during transaction. A highly available system must meet the condition of being able to run continuously as well as guaranteeing consistency on data requests. This study designed a website with high availability. The approach was building network cluster with failover and replicated block device functions. Failover was built to provide service availability, while replicated block device provides data consistency during failure of service.  With failover cluster and replicated block device approaches, a cluster which is able to handle service failures of web server and database server on the website. The result of this study was the services of the website could run well if there was any failure in node members of the cluster. The system was able to provide 99,999 (five nines availability on database server services and 99,98  (three nines on web server services.

Traveling cluster approximation for uncorrelated amorphous systems

International Nuclear Information System (INIS)

Kaplan, T.; Sen, A.K.; Gray, L.J.; Mills, R.

1985-01-01

In this paper, the authors apply the TCA concepts to spatially disordered, uncorrelated systems (e.g., fluids or amorphous metals without short-range order). This is the first approximation scheme for amorphous systems that takes cluster effects into account while preserving the Herglotz property for any amount of disorder. They have performed some computer calculations for the pair TCA, for the model case of delta-function potentials on a one-dimensional random chain. These results are compared with exact calculations (which, in principle, taken into account all cluster effects) and with the CPA, which is the single-site TCA. The density of states for the pair TCA clearly shows some improvement over the CPA, and yet, apparently, the pair approximation distorts some of the features of the exact results. They conclude that the effects of large clusters are much more important in an uncorrelated liquid metal than in a substitutional alloy. As a result, the pair TCA, which does quite a nice job for alloys, is not adequate for the liquid. Larger clusters must be treated exactly, and therefore an n-TCA with n > 2 must be used

Integrated photometry of globular star clusters in the Vilnius system

International Nuclear Information System (INIS)

Zdanavichyus, K.V.

1983-01-01

Integrated colour indices in the Vilnius photometric system and newly determined colour excesses Esub(B-V) for 39 globular clusters are presented. It is shown that the coincidence of integrated spectral types are not a sufficient criterion for the identity of intrinsic colour indices of globular clusters. Relation of integrated colour indices with the slope of the giant branch S and with the horizontal branch morphological type D is investigated. Integrated colour indices of clusters with a blue horizontal branch show no correlation with either D or S. The increase of colour indices of the clusters of types D >= 4 correlates with the distribution of stars along the horizontal branch. Integrated photometry of globular star clusters in the Vilnius multicoloured photometric system permits to determine their colour excesses from some Q diagrams and normal colour index. Integral normal colour indexes and Q parameters for I globular star clusters of the Mironov group display small changes as compared to clusters of group 2. Colour indexes among star clusters having only red horizontal branches (D=7) change most considerably

B =5 Skyrmion as a two-cluster system

Science.gov (United States)

Gudnason, Sven Bjarke; Halcrow, Chris

2018-06-01

The classical B =5 Skyrmion can be approximated by a two-cluster system in which a B =1 Skyrmion is attached to a core B =4 Skyrmion. We quantize this system, allowing the B =1 to freely orbit the core. The configuration space is 11 dimensional but simplifies significantly after factoring out the overall spin and isospin degrees of freedom. We exactly solve the free quantum problem and then include an interaction potential between the Skyrmions numerically. The resulting energy spectrum is compared to the corresponding nuclei—the helium-5/lithium-5 isodoublet. We find approximate parity doubling not seen in the experimental data. In addition, we fail to obtain the correct ground-state spin. The framework laid out for this two-cluster system can readily be modified for other clusters and in particular for other B =4 n +1 nuclei, of which B =5 is the simplest example.

Effect of mesoscopic fluctuations on equation of state in cluster-forming systems

Directory of Open Access Journals (Sweden)

A. Ciach

2012-06-01

Full Text Available Equation of state for systems with particles self-assembling into aggregates is derived within a mesoscopic theory combining density functional and field-theoretic approaches. We focus on the effect of mesoscopic fluctuations in the disordered phase. The pressure - volume fraction isotherms are calculated explicitly for two forms of the short-range attraction long-range repulsion potential. Mesoscopic fluctuations lead to an increased pressure in each case, except for very small volume fractions. When large clusters are formed, the mechanical instability of the system is present at much higher temperature than found in mean-field approximation. In this case phase separation competes with the formation of periodic phases (colloidal crystals. In the case of small clusters, no mechanical instability associated with separation into dilute and dense phases appears.

AIDEN: A Density Conscious Artificial Immune System for Automatic Discovery of Arbitrary Shape Clusters in Spatial Patterns

Directory of Open Access Journals (Sweden)

Vishwambhar Pathak

2012-11-01

Full Text Available Recent efforts in modeling of dynamics of the natural immune cells leading to artificial immune systems (AIS have ignited contemporary research interest in finding out its analogies to real world problems. The AIS models have been vastly exploited to develop dependable robust
solutions to clustering. Most of the traditional clustering methods bear limitations in their capability to detect clusters of arbitrary shapes in a fully unsupervised manner. In this paper the recognition and communication dynamics of T Cell Receptors, the recognizing elements in innate immune
system, has been modeled with a kernel density estimation method. The model has been shown to successfully discover non spherical clusters in spatial patterns. Modeling the cohesion of the antibodies and pathogens with ‘local influence’ measure inducts comprehensive extension of the
antibody representation ball (ARB, which in turn corresponds to controlled expansion of clusters and prevents overfitting.

Proxmox high availability

CERN Document Server

Cheng, Simon MC

2014-01-01

If you want to know the secrets of virtualization and how to implement high availability on your services, this is the book for you. For those of you who are already using Proxmox, this book offers you the chance to build a high availability cluster with a distributed filesystem to further protect your system from failure.

Modeling the formation of globular cluster systems in the Virgo cluster

International Nuclear Information System (INIS)

Li, Hui; Gnedin, Oleg Y.

2014-01-01

The mass distribution and chemical composition of globular cluster (GC) systems preserve fossil record of the early stages of galaxy formation. The observed distribution of GC colors within massive early-type galaxies in the ACS Virgo Cluster Survey (ACSVCS) reveals a multi-modal shape, which likely corresponds to a multi-modal metallicity distribution. We present a simple model for the formation and disruption of GCs that aims to match the ACSVCS data. This model tests the hypothesis that GCs are formed during major mergers of gas-rich galaxies and inherit the metallicity of their hosts. To trace merger events, we use halo merger trees extracted from a large cosmological N-body simulation. We select 20 halos in the mass range of 2 × 10 12 to 7 × 10 13 M ☉ and match them to 19 Virgo galaxies with K-band luminosity between 3 × 10 10 and 3 × 10 11 L ☉ . To set the [Fe/H] abundances, we use an empirical galaxy mass-metallicity relation. We find that a minimal merger ratio of 1:3 best matches the observed cluster metallicity distribution. A characteristic bimodal shape appears because metal-rich GCs are produced by late mergers between massive halos, while metal-poor GCs are produced by collective merger activities of less massive hosts at early times. The model outcome is robust to alternative prescriptions for cluster formation rate throughout cosmic time, but a gradual evolution of the mass-metallicity relation with redshift appears to be necessary to match the observed cluster metallicities. We also affirm the age-metallicity relation, predicted by an earlier model, in which metal-rich clusters are systematically several billion younger than their metal-poor counterparts.

Search for Formation Criteria for Globular Cluster Systems

Science.gov (United States)

Nuritdinov, S. N.; Mirtadjieva, K. T.; Tadjibaev, I. U.

2005-01-01

Star cluster formation is a major mode of star formation in the extreme conditions of interacting galaxies and violent starbursts. By studying ages and metallicities of young metal-enhanced star clusters in mergers / merger remnants we can learn about the violent star formation history of these galaxies and eventually about galaxy formation and evolution. We will present a new set of evolutionary synthesis models of our GALEV code specially developed to account for the gaseous emission of presently forming star clusters and an advanced tool to compare large model grids with multi-color broad-band observations becoming presently available in large amounts. Such observations are an ecomonic way to determine the parameters of young star clusters as will be shown in the presentation. First results of newly-born clusters in mergers and starburst galaxies are presented and compared to the well-studied old globulars and interpreted in the framework of galaxy formation / evolution.

Attitude Estimation in Fractionated Spacecraft Cluster Systems

Science.gov (United States)

Hadaegh, Fred Y.; Blackmore, James C.

2011-01-01

An attitude estimation was examined in fractioned free-flying spacecraft. Instead of a single, monolithic spacecraft, a fractionated free-flying spacecraft uses multiple spacecraft modules. These modules are connected only through wireless communication links and, potentially, wireless power links. The key advantage of this concept is the ability to respond to uncertainty. For example, if a single spacecraft module in the cluster fails, a new one can be launched at a lower cost and risk than would be incurred with onorbit servicing or replacement of the monolithic spacecraft. In order to create such a system, however, it is essential to know what the navigation capabilities of the fractionated system are as a function of the capabilities of the individual modules, and to have an algorithm that can perform estimation of the attitudes and relative positions of the modules with fractionated sensing capabilities. Looking specifically at fractionated attitude estimation with startrackers and optical relative attitude sensors, a set of mathematical tools has been developed that specify the set of sensors necessary to ensure that the attitude of the entire cluster ( cluster attitude ) can be observed. Also developed was a navigation filter that can estimate the cluster attitude if these conditions are satisfied. Each module in the cluster may have either a startracker, a relative attitude sensor, or both. An extended Kalman filter can be used to estimate the attitude of all modules. A range of estimation performances can be achieved depending on the sensors used and the topology of the sensing network.

Classification Of Cluster Area Forsatellite Image

Directory of Open Access Journals (Sweden)

Thwe Zin Phyo

2015-06-01

Full Text Available Abstract This paper describes area classification for Landsat7 satellite image. The main purpose of this system is to classify the area of each cluster contained in a satellite image. To classify this image firstly need to clusterthe satellite image into different land cover types. Clustering is an unsupervised learning method that aimsto classify an image into homogeneous regions. This system is implemented based on color features with K-means clustering unsupervised algorithm. This method does not need to train image before clustering.The clusters of satellite image are grouped into a set of three clusters for Landsat7 satellite image. For this work the combined band 432 from Landsat7 satellite is used as an input. Satellite imageMandalay area in 2001 is chosen to test the segmentation method. After clustering a specific range for three clustered images must be defined in order to obtain greenland water and urbanbalance.This system is implemented by using MATLAB programming language.

Application of the dynamically allocated virtual clustering management system to emulated tactical network experimentation

Science.gov (United States)

Marcus, Kelvin

2014-06-01

The U.S Army Research Laboratory (ARL) has built a "Network Science Research Lab" to support research that aims to improve their ability to analyze, predict, design, and govern complex systems that interweave the social/cognitive, information, and communication network genres. Researchers at ARL and the Network Science Collaborative Technology Alliance (NS-CTA), a collaborative research alliance funded by ARL, conducted experimentation to determine if automated network monitoring tools and task-aware agents deployed within an emulated tactical wireless network could potentially increase the retrieval of relevant data from heterogeneous distributed information nodes. ARL and NS-CTA required the capability to perform this experimentation over clusters of heterogeneous nodes with emulated wireless tactical networks where each node could contain different operating systems, application sets, and physical hardware attributes. Researchers utilized the Dynamically Allocated Virtual Clustering Management System (DAVC) to address each of the infrastructure support requirements necessary in conducting their experimentation. The DAVC is an experimentation infrastructure that provides the means to dynamically create, deploy, and manage virtual clusters of heterogeneous nodes within a cloud computing environment based upon resource utilization such as CPU load, available RAM and hard disk space. The DAVC uses 802.1Q Virtual LANs (VLANs) to prevent experimentation crosstalk and to allow for complex private networks. Clusters created by the DAVC system can be utilized for software development, experimentation, and integration with existing hardware and software. The goal of this paper is to explore how ARL and the NS-CTA leveraged the DAVC to create, deploy and manage multiple experimentation clusters to support their experimentation goals.

MULTIAGENT IMITATION MODEL OF A REGIONAL CONSTRUCTION CLUSTER AS A HETERARCHICAL SYSTEM

Directory of Open Access Journals (Sweden)

Anufriev Dmitriy Petrovich

2018-01-01

Full Text Available Subject: a regional construction cluster, which is viewed as a complex system territorially localized within the region, consisting of interconnected and complementary enterprises of construction and related industries that are united with local institutions, authorities and cooperating enterprises by heterarchic relations. Research objectives: development of multi-agent simulation model that allows us to examine the business-processes in the regional construction cluster as a complex heterarchical system. Materials and methods: we formulate the mathematical problem for description of processes in a heterarchic system as in a special multi-agent queueing network. Conclusions: the article substantiates application of the decentralized approach which is based on the use of agent methodology. Several types of agents that model elementary organizational structures have been developed. We describe the functional core of the multi-agent simulation model characterizing the heterarchic organizational model. Using the Fishman-Kivia criterion, the adequacy of the logical functioning of the developed model was established.

The role of the Pauli principle in three-cluster systems composed of identical clusters

International Nuclear Information System (INIS)

Lashko, Yu.A.; Filippov, G.F.

2009-01-01

Within the microscopic model based on the algebraic version of the resonating group method the role of the Pauli principle in the formation of continuum wave function of nuclear systems composed of three identical s-clusters has been investigated. Emphasis is placed upon the study of the exchange effects contained in the genuine three-cluster norm kernel. Three-fermion, three-boson, three-dineutron (3d ' ) and 3α systems are considered in detail. Simple analytical method of constructing the norm kernel for 3α system is suggested. The Pauli-allowed basis functions for the 3α and 3d ' systems are given in an explicit form and asymptotic behavior of these functions is established. Complete classification of the eigenfunctions and the eigenvalues of the 12 C norm kernel by the 8 Be=α+α eigenvalues has been given for the first time. Spectrum of the 12 C norm kernel is compared to that of the 5 H system.

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.

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

Science.gov (United States)

Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

2017-05-11

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

Science.gov (United States)

Alexander, Nathan; Woetzel, Nils; Meiler, Jens

2011-02-01

Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

Schedulability-Driven Partitioning and Mapping for Multi-Cluster Real-Time Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2004-01-01

We present an approach to partitioning and mapping for multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. We have proposed a schedulability analysis for such systems, including a worst-case queuing delay analysis for the gateways...

NATO Advanced Research Workshop on Physics and Chemistry of Finite Systems : from Clusters to Crystals

CERN Document Server

Khanna, S; Rao, B

1992-01-01

Recent innovations in experimental techniques such as molecular and cluster beam epitaxy, supersonic jet expansion, matrix isolation and chemical synthesis are increasingly enabling researchers to produce materials by design and with atomic dimension. These materials constrained by sire, shape, and symmetry range from clusters containing as few as two atoms to nanoscale materials consisting of thousands of atoms. They possess unique structuraI, electronic, magnetic and optical properties that depend strongly on their size and geometry. The availability of these materials raises many fundamental questions as weIl as technological possibilities. From the academic viewpoint, the most pertinent question concerns the evolution of the atomic and electronic structure of the system as it grows from micro clusters to crystals. At what stage, for example, does the cluster look as if it is a fragment of the corresponding crystal. How do electrons forming bonds in micro-clusters transform to bands in solids? How do the s...

Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2004-01-01

We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2006-01-01

We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

Autonomic Cluster Management System (ACMS): A Demonstration of Autonomic Principles at Work

Science.gov (United States)

Baldassari, James D.; Kopec, Christopher L.; Leshay, Eric S.; Truszkowski, Walt; Finkel, David

2005-01-01

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of achieving significant computational capabilities for high-performance computing applications, while simultaneously affording the ability to. increase that capability simply by adding more (inexpensive) processors. However, the task of manually managing and con.guring a cluster quickly becomes impossible as the cluster grows in size. Autonomic computing is a relatively new approach to managing complex systems that can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Automatic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management.

GibbsCluster: unsupervised clustering and alignment of peptide sequences

DEFF Research Database (Denmark)

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-01-01

motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large......-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0....

Schedulability-Driven Frame Packing for Multi-Cluster Distributed Embedded Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2003-01-01

We present an approach to frame packing for multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In our approach, the application messages are packed into frames such that the application is schedulable. Thus, we have...... also proposed a schedulability analysis for applications consisting of mixed event-triggered and time-triggered processes and messages, and a worst case queuing delay analysis for the gateways, responsible for routing inter-cluster traffic. Optimization heuristics for frame packing aiming at producing...... a schedulable system have been proposed. Extensive experiments and a real-life example show the efficiency of our frame-packing approach....

Heterologous expression of pikromycin biosynthetic gene cluster using Streptomyces artificial chromosome system.

Science.gov (United States)

Pyeon, Hye-Rim; Nah, Hee-Ju; Kang, Seung-Hoon; Choi, Si-Sun; Kim, Eung-Soo

2017-05-31

Heterologous expression of biosynthetic gene clusters of natural microbial products has become an essential strategy for titer improvement and pathway engineering of various potentially-valuable natural products. A Streptomyces artificial chromosomal conjugation vector, pSBAC, was previously successfully applied for precise cloning and tandem integration of a large polyketide tautomycetin (TMC) biosynthetic gene cluster (Nah et al. in Microb Cell Fact 14(1):1, 2015), implying that this strategy could be employed to develop a custom overexpression scheme of natural product pathway clusters present in actinomycetes. To validate the pSBAC system as a generally-applicable heterologous overexpression system for a large-sized polyketide biosynthetic gene cluster in Streptomyces, another model polyketide compound, the pikromycin biosynthetic gene cluster, was preciously cloned and heterologously expressed using the pSBAC system. A unique HindIII restriction site was precisely inserted at one of the border regions of the pikromycin biosynthetic gene cluster within the chromosome of Streptomyces venezuelae, followed by site-specific recombination of pSBAC into the flanking region of the pikromycin gene cluster. Unlike the previous cloning process, one HindIII site integration step was skipped through pSBAC modification. pPik001, a pSBAC containing the pikromycin biosynthetic gene cluster, was directly introduced into two heterologous hosts, Streptomyces lividans and Streptomyces coelicolor, resulting in the production of 10-deoxymethynolide, a major pikromycin derivative. When two entire pikromycin biosynthetic gene clusters were tandemly introduced into the S. lividans chromosome, overproduction of 10-deoxymethynolide and the presence of pikromycin, which was previously not detected, were both confirmed. Moreover, comparative qRT-PCR results confirmed that the transcription of pikromycin biosynthetic genes was significantly upregulated in S. lividans containing tandem

Exploring the Dynamics of Exoplanetary Systems in a Young Stellar Cluster

Science.gov (United States)

Thornton, Jonathan Daniel; Glaser, Joseph Paul; Wall, Joshua Edward

2018-01-01

I describe a dynamical simulation of planetary systems in a young star cluster. One rather arbitrary aspect of cluster simulations is the choice of initial conditions. These are typically chosen from some standard model, such as Plummer or King, or from a “fractal” distribution to try to model young clumpy systems. Here I adopt the approach of realizing an initial cluster model directly from a detailed magnetohydrodynamical model of cluster formation from a 1000-solar-mass interstellar gas cloud, with magnetic fields and radiative and wind feedback from massive stars included self-consistently. The N-body simulation of the stars and planets starts once star formation is largely over and feedback has cleared much of the gas from the region where the newborn stars reside. It continues until the cluster dissolves in the galactic field. Of particular interest is what would happen to the free-floating planets created in the gas cloud simulation. Are they captured by a star or are they ejected from the cluster? This method of building a dynamical cluster simulation directly from the results of a cluster formation model allows us to better understand the evolution of young star clusters and enriches our understanding of extrasolar planet development in them. These simulations were performed within the AMUSE simulation framework, and combine N-body, multiples and background potential code.

Traveling-cluster approximation for uncorrelated amorphous systems

International Nuclear Information System (INIS)

Sen, A.K.; Mills, R.; Kaplan, T.; Gray, L.J.

1984-01-01

We have developed a formalism for including cluster effects in the one-electron Green's function for a positionally disordered (liquid or amorphous) system without any correlation among the scattering sites. This method is an extension of the technique known as the traveling-cluster approximation (TCA) originally obtained and applied to a substitutional alloy by Mills and Ratanavararaksa. We have also proved the appropriate fixed-point theorem, which guarantees, for a bounded local potential, that the self-consistent equations always converge upon iteration to a unique, Herglotz solution. To our knowledge, this is the only analytic theory for considering cluster effects. Furthermore, we have performed some computer calculations in the pair TCA, for the model case of delta-function potentials on a one-dimensional random chain. These results have been compared with ''exact calculations'' (which, in principle, take into account all cluster effects) and with the coherent-potential approximation (CPA), which is the single-site TCA. The density of states for the pair TCA clearly shows some improvement over the CPA and yet, apparently, the pair approximation distorts some of the features of the exact results

Advanced cluster methods for correlated-electron systems

Energy Technology Data Exchange (ETDEWEB)

Fischer, Andre

2015-04-27

In this thesis, quantum cluster methods are used to calculate electronic properties of correlated-electron systems. A special focus lies in the determination of the ground state properties of a 3/4 filled triangular lattice within the one-band Hubbard model. At this filling, the electronic density of states exhibits a so-called van Hove singularity and the Fermi surface becomes perfectly nested, causing an instability towards a variety of spin-density-wave (SDW) and superconducting states. While chiral d+id-wave superconductivity has been proposed as the ground state in the weak coupling limit, the situation towards strong interactions is unclear. Additionally, quantum cluster methods are used here to investigate the interplay of Coulomb interactions and symmetry-breaking mechanisms within the nematic phase of iron-pnictide superconductors. The transition from a tetragonal to an orthorhombic phase is accompanied by a significant change in electronic properties, while long-range magnetic order is not established yet. The driving force of this transition may not only be phonons but also magnetic or orbital fluctuations. The signatures of these scenarios are studied with quantum cluster methods to identify the most important effects. Here, cluster perturbation theory (CPT) and its variational extention, the variational cluster approach (VCA) are used to treat the respective systems on a level beyond mean-field theory. Short-range correlations are incorporated numerically exactly by exact diagonalization (ED). In the VCA, long-range interactions are included by variational optimization of a fictitious symmetry-breaking field based on a self-energy functional approach. Due to limitations of ED, cluster sizes are limited to a small number of degrees of freedom. For the 3/4 filled triangular lattice, the VCA is performed for different cluster symmetries. A strong symmetry dependence and finite-size effects make a comparison of the results from different clusters difficult

Clustering of resting state networks.

Directory of Open Access Journals (Sweden)

Megan H Lee

Full Text Available The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm.The fuzzy-c-means clustering algorithm was applied to resting state fMRI data in cortical and subcortical gray matter from two groups acquired separately, one of 17 healthy individuals and the second of 21 healthy individuals. Different numbers of clusters and different starting conditions were used. A cluster dispersion measure determined the optimal numbers of clusters. An inner product metric provided a measure of similarity between different clusters. The two cluster result found the task-negative and task-positive systems. The cluster dispersion measure was minimized with seven and eleven clusters. Each of the clusters in the seven and eleven cluster result was associated with either the task-negative or task-positive system. Applying the algorithm to find seven clusters recovered previously described resting state networks, including the default mode network, frontoparietal control network, ventral and dorsal attention networks, somatomotor, visual, and language networks. The language and ventral attention networks had significant subcortical involvement. This parcellation was consistently found in a large majority of algorithm runs under different conditions and was robust to different methods of initialization.The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results. This work reinforces the observation that resting state networks are hierarchically organized.

Management system of ELHEP cluster machine for FEL photonics design

Science.gov (United States)

Zysik, Jacek; Poźniak, Krzysztof; Romaniuk, Ryszard

2006-10-01

A multipurpose, distributed MatLab calculations oriented, cluster machine was assembled in PERG/ELHEP laboratory at ISE/WUT. It is predicted mainly for advanced photonics and FPGA/DSP based systems design for Free Electron Laser. It will be used also for student projects for superconducting accelerator and FEL. Here we present one specific side of cluster design. For an intense, distributed daily work with the cluster, it is important to have a good interface and practical access to all machine resources. A complex management system was implemented in PERG laboratory. It helps all registered users to work using all necessary applications, communicate with other logged in people, check all the news and gather all necessary information about what is going on in the system, how it is utilized, etc. The system is also very practical for administrator purposes, it helps to keep controlling who is using the resources and for how long. It provides different privileges for different applications and many more. The system is introduced as a freeware, using open source code and can be modified by system operators or super-users who are interested in nonstandard system configuration.

The research of the availability at cloud service systems

Science.gov (United States)

Demydov, Ivan; Klymash, Mykhailo; Kharkhalis, Zenoviy; Strykhaliuk, Bohdan; Komada, Paweł; Shedreyeva, Indira; Targeusizova, Aliya; Iskakova, Aigul

2017-08-01

This paper is devoted to the numerical investigation of the availability at cloud service systems. In this paper criteria and constraints calculations were performed and obtained results were analyzed for synthesis purposes of distributed service platforms based on the cloud service-oriented architecture such as availability and system performance index variations by defined set of the main parameters. The method of synthesis has been numerically generalized considering the type of service workload in statistical form by Hurst parameter application for each integrated service that requires implementation within the service delivery platform, which is synthesized by structural matching of virtual machines using combination of elementary servicing components up to functionality into a best-of-breed solution. As a result of restrictions from Amdahl's Law the necessity of cloud-networks clustering was shown, which makes it possible to break the complex dynamic network into separate segments that simplifies access to the resources of virtual machines and, in general, to the "clouds" and respectively simplifies complex topological structure, enhancing the overall system performance. In overall, proposed approaches and obtained results numerically justifying and algorithmically describing the process of structural and functional synthesis of efficient distributed service platforms, which under process of their configuring and exploitation provides an opportunity to act on the dynamic environment in terms of comprehensive services range and nomadic users' workload pulsing.

Optimal Sizing for Wind/PV/Battery System Using Fuzzy c-Means Clustering with Self-Adapted Cluster Number

Directory of Open Access Journals (Sweden)

Xin Liu

2017-01-01

Full Text Available Integrating wind generation, photovoltaic power, and battery storage to form hybrid power systems has been recognized to be promising in renewable energy development. However, considering the system complexity and uncertainty of renewable energies, such as wind and solar types, it is difficult to obtain practical solutions for these systems. In this paper, optimal sizing for a wind/PV/battery system is realized by trade-offs between technical and economic factors. Firstly, the fuzzy c-means clustering algorithm was modified with self-adapted parameters to extract useful information from historical data. Furthermore, the Markov model is combined to determine the chronological system states of natural resources and load. Finally, a power balance strategy is introduced to guide the optimization process with the genetic algorithm to establish the optimal configuration with minimized cost while guaranteeing reliability and environmental factors. A case of island hybrid power system is analyzed, and the simulation results are compared with the general FCM method and chronological method to validate the effectiveness of the mentioned method.

Clustervision: Visual Supervision of Unsupervised Clustering.

Science.gov (United States)

Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; De Filippi, Christopher; Stewart, Walter F; Perer, Adam

2018-01-01

Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.

Cluster-based bulk metallic glass formation in Fe-Si-B-Nb alloy systems

Energy Technology Data Exchange (ETDEWEB)

Zhu, C L; Wang, Q; Li, F W; Li, Y H; Wang, Y M; Dong, C [State Key Laboratory of Materials Modification, Dalian University of Technology (DUT), Dalian 116024 (China); Zhang, W; Inoue, A, E-mail: dong@dlut.edu.c [Institute for Materials Research (IMR), Tohoku University, Katahira 2-1-1, Aoba-Ku, Sendai 980-8577 (Japan)

2009-01-01

Bulk metallic glass formations have been explored in Fe-B-Si-Nb alloy system using the so-called atomic cluster line approach in combination with minor alloying guideline. The atomic cluster line refers to a straight line linking binary cluster to the third element in a ternary system. The basic ternary compositions in Fe-B-Si system are determined by the inetersection points of two cluster lines, namely Fe-B cluster to Si and Fe-Si cluster to B, and then further alloyed with 3-5 at. % Nb for enhancing glass forming abilities. BMG rods with a diameter of 3 mm are formed under the case of minor Nb alloying the basic intersecting compositions of Fe{sub 8}B{sub 3}-Si with Fe{sub 12}Si-B and Fe{sub 8}B{sub 2}-Si with Fe{sub 9}Si-B. The BMGs also exhibit high Vickers hardness (H{sub v}) of 1130-1164 and high Young's modulous (E) of 170-180 GPa

A Novel Clustering Algorithm Inspired by Membrane Computing

Directory of Open Access Journals (Sweden)

Hong Peng

2015-01-01

Full Text Available P systems are a class of distributed parallel computing models; this paper presents a novel clustering algorithm, which is inspired from mechanism of a tissue-like P system with a loop structure of cells, called membrane clustering algorithm. The objects of the cells express the candidate centers of clusters and are evolved by the evolution rules. Based on the loop membrane structure, the communication rules realize a local neighborhood topology, which helps the coevolution of the objects and improves the diversity of objects in the system. The tissue-like P system can effectively search for the optimal partitioning with the help of its parallel computing advantage. The proposed clustering algorithm is evaluated on four artificial data sets and six real-life data sets. Experimental results show that the proposed clustering algorithm is superior or competitive to k-means algorithm and several evolutionary clustering algorithms recently reported in the literature.

Mode 3 knowledge production: Systems and systems theory, clusters and networks

OpenAIRE

Carayannis, Elias G.; Campbell, David F. J.; Rehman, Scheherazade S.

2016-01-01

With the comprehensive term of "Mode 3," we want to draw a conceptual link between systems and systems theory and want to demonstrate further how this can be applied to knowledge in the next steps. Systems can be understood as being composed of "elements", which are tied together by a "self-rationale". For innovation, often innovation clusters and innovation networks are being regarded as important. By leveraging systems theory for innovation concepts, one can implement references between the...

The Innovation Clusters in the Developments by the Scandinavian School of Cluster Theory

Directory of Open Access Journals (Sweden)

Onipko Tetiana A.

2017-08-01

Full Text Available The article generalizes and analyzes the developments by the Scandinavian School of cluster theory (scientists from Sweden, Norway and Denmark on innovative clusters. It has been found that the Scandinavian scientists considered innovative clusters as an integral component of both the regional and the national innovation systems. It has been clarified that the efficiency of an innovative cluster depends largely on the «knowledge base». It was emphasized that innovative clusters, by facilitating interactive training and generating new ideas, stimulate the development of the «economy of training». It has been determined that the coordinating structures of innovative clusters are the institutions of cooperation that facilitate interaction between enterprises, scientific centres, and authorities. It has been specified that innovative clusters contribute to the emerging of benefits for participants, including the growing opportunities for innovation, improved conditions for establishing a business, and increased productivity. It has been concluded that the development of the inner environment of an innovative cluster depends largely on its relationships to the external environment.

Assessment of In-Cloud Enterprise Resource Planning System Performed in a Virtual Cluster

Directory of Open Access Journals (Sweden)

Bao Rong Chang

2015-01-01

Full Text Available This paper introduces a high-performed high-availability in-cloud enterprise resources planning (in-cloud ERP which has deployed in the virtual machine cluster. The proposed approach can resolve the crucial problems of ERP failure due to unexpected downtime and failover between physical hosts in enterprises, causing operation termination and hence data loss. Besides, the proposed one together with the access control authentication and network security is capable of preventing intrusion hacked and/or malicious attack via internet. Regarding system assessment, cost-performance (C-P ratio, a remarkable cost effectiveness evaluation, has been applied to several remarkable ERP systems. As a result, C-P ratio evaluated from the experiments shows that the proposed approach outperforms two well-known benchmark ERP systems, namely, in-house ECC 6.0 and in-cloud ByDesign.

Relativistic Binaries in Globular Clusters

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Matthew J. Benacquista

2013-03-01

Full Text Available Galactic globular clusters are old, dense star systems typically containing 10^4 – 10^6 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution that leads to relativistic binaries, and current and possible future observational evidence for this population. Our discussion of globular cluster evolution will focus on the processes that boost the production of tight binary systems and the subsequent interaction of these binaries that can alter the properties of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker–Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

Cluster Mean-Field Approach to the Steady-State Phase Diagram of Dissipative Spin Systems

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Jiasen Jin

2016-07-01

Full Text Available We show that short-range correlations have a dramatic impact on the steady-state phase diagram of quantum driven-dissipative systems. This effect, never observed in equilibrium, follows from the fact that ordering in the steady state is of dynamical origin, and is established only at very long times, whereas in thermodynamic equilibrium it arises from the properties of the (free energy. To this end, by combining the cluster methods extensively used in equilibrium phase transitions to quantum trajectories and tensor-network techniques, we extend them to nonequilibrium phase transitions in dissipative many-body systems. We analyze in detail a model of spin-1/2 on a lattice interacting through an XYZ Hamiltonian, each of them coupled to an independent environment that induces incoherent spin flips. In the steady-state phase diagram derived from our cluster approach, the location of the phase boundaries and even its topology radically change, introducing reentrance of the paramagnetic phase as compared to the single-site mean field where correlations are neglected. Furthermore, a stability analysis of the cluster mean field indicates a susceptibility towards a possible incommensurate ordering, not present if short-range correlations are ignored.

A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

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Bohui Zhu

2013-01-01

Full Text Available This paper presents a novel maximum margin clustering method with immune evolution (IEMMC for automatic diagnosis of electrocardiogram (ECG arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias.

Tourism Cluster Competitiveness and Sustainability: Proposal for a Systemic Model to Measure the Impact of Tourism on Local Development

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Sieglinde Kindl da Cunha

2005-07-01

Full Text Available This article proposes a model to measure tourism cluster impact on local development with a view to assessing tourism cluster interaction, competitiveness and sustainability impacts on the economy, society and the environment. The theoretical basis for this model is founded on cluster concept and typology adapting and integrating the systemic competitiveness and sustainability concepts within economic, social, cultural, environmental and political dimensions. The proposed model shows a holistic, multidisciplinary and multi-sector view of local development brought back through a systemic approach to the concepts of competitiveness, social equity and sustainability. Its results make possible strategic guidance to agents responsible for public sector tourism policies, as well as the strategies for competitiveness, competition, cooperation and sustainability in private companies and institutions.

Clustering analysis of water distribution systems: identifying critical components and community impacts.

Science.gov (United States)

Diao, K; Farmani, R; Fu, G; Astaraie-Imani, M; Ward, S; Butler, D

2014-01-01

Large water distribution systems (WDSs) are networks with both topological and behavioural complexity. Thereby, it is usually difficult to identify the key features of the properties of the system, and subsequently all the critical components within the system for a given purpose of design or control. One way is, however, to more explicitly visualize the network structure and interactions between components by dividing a WDS into a number of clusters (subsystems). Accordingly, this paper introduces a clustering strategy that decomposes WDSs into clusters with stronger internal connections than external connections. The detected cluster layout is very similar to the community structure of the served urban area. As WDSs may expand along with urban development in a community-by-community manner, the correspondingly formed distribution clusters may reveal some crucial configurations of WDSs. For verification, the method is applied to identify all the critical links during firefighting for the vulnerability analysis of a real-world WDS. Moreover, both the most critical pipes and clusters are addressed, given the consequences of pipe failure. Compared with the enumeration method, the method used in this study identifies the same group of the most critical components, and provides similar criticality prioritizations of them in a more computationally efficient time.

Modeling and estimating system availability

International Nuclear Information System (INIS)

Gaver, D.P.; Chu, B.B.

1976-11-01

Mathematical models to infer the availability of various types of more or less complicated systems are described. The analyses presented are probabilistic in nature and consist of three parts: a presentation of various analytic models for availability; a means of deriving approximate probability limits on system availability; and a means of statistical inference of system availability from sparse data, using a jackknife procedure. Various low-order redundant systems are used as examples, but extension to more complex systems is not difficult

Microsoft Hyper-V cluster design

CERN Document Server

Siron, Eric

2013-01-01

This book is written in a friendly and practical style with numerous tutorials centred on common as well as atypical Hyper-V cluster designs. This book also features a sample cluster design throughout to help you learn how to design a Hyper-V in a real-world scenario.Microsoft Hyper-V Cluster Design is perfect for the systems administrator who has a good understanding of Windows Server in an Active Directory domain and is ready to expand into a highly available virtualized environment. It only expects that you will be familiar with basic hypervisor terminology.

Cluster policy in Europe and Asia: A comparison using selected cluster policy characteristics

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Martina Sopoligová

2017-10-01

Full Text Available Currently, cluster concept is one of the most important tools for governments to enhance competitiveness and innovations through sectoral specialization and cooperation. The paper focuses on applications of the cluster policy in the distinct territorial context of Europe and Asia so that to perform a comparison between different approaches to the cluster concept application in real practice. The paper introduces a comparative study of the cluster policy concepts based on the characteristics defined by the authors, such as scope, approach, targeting, autonomy, institutional coordination, policy instruments and evaluation system studied for the selected European and Asian countries such as Denmark, France, Germany, China, Japan, and South Korea. The research draws upon processing the secondary data obtained through content analysis of the related literature, government documents and strategies, and also cluster funding programmes. The findings demonstrate the diversity of cluster policies implemented in the context of European and Asian conditions at the current stage of their development.

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

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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.

Clustering in Ethiopia

African Journals Online (AJOL)

Background: The importance of local variations in patterns of health and disease are increasingly recognised, but, particularly in the case of tropical infections, available methods and resources for characterising disease clusters in time and space are limited. Whilst the Global Positioning System. (GPS) allows accurate and ...

The use of a VAX cluster for the DIII-D data acquisition system

International Nuclear Information System (INIS)

McHarg, B.B. Jr.

1991-11-01

The DIII-D tokamak is a large fusion energy research experiment funded by the Department of Energy. The experiment currently collects nearly 40 Mbytes of data from each shot of the experiment. In the past, most of this data was acquired through the MODCOMP Classic data acquisition computers and then transferred to a DEC VAX computer system for permanent archiving and storage. A much smaller amount of data was acquired from a few MicroVAX based data acquisition systems. In the last two years, MicroVAX based systems have become the standard means for adding new diagnostic data and account for half the total data. There are now 17 VAX systems of various types at the DIII-D facility. As more diagnostics and data are added, it takes increasing of time to merge the data into the central shot file. The system management of so many systems has become increasingly time consuming as well. To improve the efficiency of the overall data acquisition system, a mixed interconnect VAX cluster has been formed consisting of 16 VAX computers. In the cluster, the software protocol for passing data around the cluster is much more efficient than using DECnet. The cluster has also greatly simplified the procedure of backing up disks. Another big improvement is the use of a VAX console system which ties all the console ports of the computers into one central computer system which then manages the entire cluster

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

Science.gov (United States)

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

A Binary System in the Hyades Cluster Hosting a Neptune-Sized Planet

Science.gov (United States)

Feinstein, Adina; Ciardi, David; Crossfield, Ian; Schlieder, Joshua; Petigura, Erik; David, Trevor J.; Bristow, Makennah; Patel, Rahul; Arnold, Lauren; Benneke, Björn; Christiansen, Jessie; Dressing, Courtney; Fulton, Benjamin; Howard, Andrew; Isaacson, Howard; Sinukoff, Evan; Thackeray, Beverly

2018-01-01

We report the discovery of a Neptune-size planet (Rp = 3.0Rearth) in the Hyades Cluster. The host star is in a binary system, comprising a K5V star and M7/8V star with a projected separation of 40 AU. The planet orbits the primary star with an orbital period of 17.3 days and a transit duration of 3 hours. The host star is bright (V = 11.2, J = 9.1) and so may be a good target for precise radial velocity measurements. The planet is the first Neptune-sized planet to be found orbiting in a binary system within an open cluster. The Hyades is the nearest star cluster to the Sun, has an age of 625-750 Myr, and forms one of the fundamental rungs in the distance ladder; understanding the planet population in such a well-studied cluster can help us understand and set contraints on the formation and evolution of planetary systems.

Phase correlation and clustering of a nearest neighbour coupled oscillators system

CERN Document Server

Ei-Nashar, H F

2002-01-01

We investigated the phases in a system of nearest neighbour coupled oscillators before complete synchronization in frequency occurs. We found that when oscillators under the influence of coupling form a cluster of the same time-average frequency, their phases start to correlate. An order parameter, which measures this correlation, starts to grow at this stage until it reaches maximum. This means that a time-average phase locked state is reached between the oscillators inside the cluster of the same time- average frequency. At this strength the cluster attracts individual oscillators or a cluster to join in. We also observe that clustering in averaged frequencies orders the phases of the oscillators. This behavior is found at all the transition points studied.

Phase correlation and clustering of a nearest neighbour coupled oscillators system

International Nuclear Information System (INIS)

EI-Nashar, Hassan F.

2002-09-01

We investigated the phases in a system of nearest neighbour coupled oscillators before complete synchronization in frequency occurs. We found that when oscillators under the influence of coupling form a cluster of the same time-average frequency, their phases start to correlate. An order parameter, which measures this correlation, starts to grow at this stage until it reaches maximum. This means that a time-average phase locked state is reached between the oscillators inside the cluster of the same time- average frequency. At this strength the cluster attracts individual oscillators or a cluster to join in. We also observe that clustering in averaged frequencies orders the phases of the oscillators. This behavior is found at all the transition points studied. (author)

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.

Nuclear clustering - a cluster core model study

International Nuclear Information System (INIS)

Paul Selvi, G.; Nandhini, N.; Balasubramaniam, M.

2015-01-01

Nuclear clustering, similar to other clustering phenomenon in nature is a much warranted study, since it would help us in understanding the nature of binding of the nucleons inside the nucleus, closed shell behaviour when the system is highly deformed, dynamics and structure at extremes. Several models account for the clustering phenomenon of nuclei. We present in this work, a cluster core model study of nuclear clustering in light mass nuclei

Pseudo-potential method for taking into account the Pauli principle in cluster systems

International Nuclear Information System (INIS)

Krasnopol'skii, V.M.; Kukulin, V.I.

1975-01-01

In order to take account of the Pauli principle in cluster systems (such as 3α, α + α + n) a convenient method of renormalization of the cluster-cluster deep attractive potentials with forbidden states is suggested. The renormalization consists of adding projectors upon the occupied states with an infinite coupling constant to the initial deep potential which means that we pass to pseudo-potentials. The pseudo-potential approach in projecting upon the noneigenstates is shown to be equivalent to the orthogonality condition model of Saito et al. The orthogonality of the many-particle wave function to the forbidden states of each two-cluster sub-system is clearly demonstrated

Cluster analysis in systems of magnetic spheres and cubes

Energy Technology Data Exchange (ETDEWEB)

Pyanzina, E.S., E-mail: elena.pyanzina@urfu.ru [Ural Federal University, Lenin Av. 51, Ekaterinburg (Russian Federation); Gudkova, A.V. [Ural Federal University, Lenin Av. 51, Ekaterinburg (Russian Federation); Donaldson, J.G. [University of Vienna, Sensengasse 8, Vienna (Austria); Kantorovich, S.S. [Ural Federal University, Lenin Av. 51, Ekaterinburg (Russian Federation); University of Vienna, Sensengasse 8, Vienna (Austria)

2017-06-01

In the present work we use molecular dynamics simulations and graph-theory based cluster analysis to compare self-assembly in systems of magnetic spheres, and cubes where the dipole moment is oriented along the side of the cube in the [001] crystallographic direction. We show that under the same conditions cubes aggregate far less than their spherical counterparts. This difference can be explained in terms of the volume of phase space in which the formation of the bond is thermodynamically advantageous. It follows that this volume is much larger for a dipolar sphere than for a dipolar cube. - Highlights: • A comparison of the degree of self-assembly in systems of magnetic spheres and cubes. • Spheres are more likely to form larger clusters than cubes. • Differences in microstructure will manifest in the magnetic response of each system.

Efficient Messaging through Cluster Coordinators in Decentralized Controlled Material Flow Systems

Directory of Open Access Journals (Sweden)

Lieberoth-Leden Christian

2016-01-01

Full Text Available The modularization of the hard- and software is one approach handling the demand for increasing flexibility and changeability of automated material flow systems. A control that is distributed across several different hardware controllers leads to a great demand for coordination between the modules while planning for example transports, especially if there is a mutual dependency between the modules on the executing tasks. Short-term changes in planning often initiate a rescheduling chain reaction, which causes a high communication load in the system. In the presented approach, module clusters with a centralized coordinator are automatically formed out of multiple modules and substitutional take over the surrounding communication for the modules. As a result, they minimize exchanged messages by focusing on the essential information.

Discovery of four gravitational lensing systems by clusters in the SDSS DR6

International Nuclear Information System (INIS)

Wen Zhonglue; Han Jinlin; Xu Xiangyang; Jiang Yunying; Guo Zhiqing; Wang Pengfei; Liu Fengshan

2009-01-01

We report the discovery of 4 strong gravitational lensing systems by visual inspections of the Sloan Digital Sky Survey images of galaxy clusters in Data Release 6 (SDSS DR6). Two of the four systems show Einstein rings while the others show tangential giant arcs. These arcs or rings have large angular separations (> 8) from the bright central galaxies and show bluer color compared with the red cluster galaxies. In addition, we found 5 probable and 4 possible lenses by galaxy clusters. (letters)

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.

Schedulability Analysis and Optimization for the Synthesis of Multi-Cluster Distributed Embedded Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2003-01-01

We present an approach to schedulability analysis for the synthesis of multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. We have also proposed a buffer size and worst case queuing delay analysis for the gateways......, responsible for routing inter-cluster traffic. Optimization heuristics for the priority assignment and synthesis of bus access parameters aimed at producing a schedulable system with minimal buffer needs have been proposed. Extensive experiments and a real-life example show the efficiency of our approaches....

Schedulability Analysis and Optimization for the Synthesis of Multi-Cluster Distributed Embedded Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2003-01-01

An approach to schedulability analysis for the synthesis of multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways, is presented. A buffer size and worst case queuing delay analysis for the gateways, responsible for routing...... inter-cluster traffic, is also proposed. Optimisation heuristics for the priority assignment and synthesis of bus access parameters aimed at producing a schedulable system with minimal buffer needs have been proposed. Extensive experiments and a real-life example show the efficiency of the approaches....

75 FR 17700 - Energy Efficient Building Systems Regional Innovation Cluster Initiative-Joint Federal Funding...

Science.gov (United States)

2010-04-07

... economically dynamic regional innovation cluster focused on energy efficient buildings technologies and systems...-risk, high-reward research that overcomes technology challenges through approaches that span basic... DEPARTMENT OF ENERGY Energy Efficient Building Systems Regional Innovation Cluster Initiative...

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.

Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

Science.gov (United States)

Mitra, Sunanda; Pemmaraju, Surya

1992-01-01

Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

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.

Test System Impact on System Availability

DEFF Research Database (Denmark)

Pau, L. F.

1987-01-01

The specifications are presented for an imperfect automatic test system (ATS) (test frequency distribution, reliability, false alarm rate, nondetection rate) in order to account for the availability, readiness, mean time between unscheduled repairs (MTBUR), reliability, and maintenance of the sys......The specifications are presented for an imperfect automatic test system (ATS) (test frequency distribution, reliability, false alarm rate, nondetection rate) in order to account for the availability, readiness, mean time between unscheduled repairs (MTBUR), reliability, and maintenance...... of the system subject to monitoring and test. A time-dependent Markov model is presented, and applied in three cases, with examples of numerical results provided for preventive maintenance decisions, design of an automatic test system, buffer testing in computers, and data communications....

Pitch Correlogram Clustering for Fast Speaker Identification

Directory of Open Access Journals (Sweden)

Nitin Jhanwar

2004-12-01

Full Text Available Gaussian mixture models (GMMs are commonly used in text-independent speaker identification systems. However, for large speaker databases, their high computational run-time limits their use in online or real-time speaker identification situations. Two-stage identification systems, in which the database is partitioned into clusters based on some proximity criteria and only a single-cluster GMM is run in every test, have been suggested in literature to speed up the identification process. However, most clustering algorithms used have shown limited success, apparently because the clustering and GMM feature spaces used are derived from similar speech characteristics. This paper presents a new clustering approach based on the concept of a pitch correlogram that captures frame-to-frame pitch variations of a speaker rather than short-time spectral characteristics like cepstral coefficient, spectral slopes, and so forth. The effectiveness of this two-stage identification process is demonstrated on the IVIE corpus of 110 speakers. The overall system achieves a run-time advantage of 500% as well as a 10% reduction of error in overall speaker identification.

Influence of system temperature on the micro-structures and dynamics of dust clusters in dusty plasmas

Energy Technology Data Exchange (ETDEWEB)

Song, Y. L.; Huang, F., E-mail: huangfeng@cau.edu.cn [College of Science, China Agricultural University, Beijing 100083 (China); He, Y. F.; Wu, L. [College of Information and Electrical Engineering, China Agricultural University, Beijing 100083 (China); Liu, Y. H. [School of Physics and Optoelectronic Engineering, Ludong University, Yantai 264025 (China); Chen, Z. Y. [Department of Physics, Beijing University of Chemical Technology, Beijing 100029 (China); Yu, M. Y. [Institute for Fusion Theory and Simulation, Zhejiang University, Hangzhou 310027 (China); Institute for Theoretical Physics I, Ruhr University, D-44801 Bochum (Germany)

2015-06-15

Influence of the system temperature on the micro-structures and dynamics of dust clusters in dusty plasmas is investigated through laboratory experiment and molecular dynamics simulation. The micro-structures, defect numbers, and pair correlation function of the dust clusters are studied for different system temperatures. The dust grains' trajectories, the mean square displacement, and the corresponding self-diffusion coefficient of the clusters are calculated for different temperatures for illustrating the phase properties of the dust clusters. The simulation results confirm that with the increase in system temperature, the micro-structures and dynamics of dust clusters are gradually changed, which qualitatively agree with experimental results.

FURTHER DEFINITION OF THE MASS-METALLICITY RELATION IN GLOBULAR CLUSTER SYSTEMS AROUND BRIGHTEST CLUSTER GALAXIES

International Nuclear Information System (INIS)

Cockcroft, Robert; Harris, William E.; Wehner, Elizabeth M. H.; Whitmore, Bradley C.; Rothberg, Barry

2009-01-01

We combine the globular cluster (GC) data for 15 brightest cluster galaxies and use this material to trace the mass-metallicity relations (MMRs) in their globular cluster systems (GCSs). This work extends previous studies which correlate the properties of the MMR with those of the host galaxy. Our combined data sets show a mean trend for the metal-poor subpopulation that corresponds to a scaling of heavy-element abundance with cluster mass Z ∼ M 0.30±0.05 . No trend is seen for the metal-rich subpopulation which has a scaling relation that is consistent with zero. We also find that the scaling exponent is independent of the GCS specific frequency and host galaxy luminosity, except perhaps for dwarf galaxies. We present new photometry in (g',i') obtained with Gemini/GMOS for the GC populations around the southern giant ellipticals NGC 5193 and IC 4329. Both galaxies have rich cluster populations which show up as normal, bimodal sequences in the color-magnitude diagram. We test the observed MMRs and argue that they are statistically real, and not an artifact caused by the method we used. We also argue against asymmetric contamination causing the observed MMR as our mean results are no different from other contamination-free studies. Finally, we compare our method to the standard bimodal fitting method (KMM or RMIX) and find our results are consistent. Interpretation of these results is consistent with recent models for GC formation in which the MMR is determined by GC self-enrichment during their brief formation period.

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.

Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

Science.gov (United States)

McIntosh, Dawn

2006-01-01

This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

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.

Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes

Science.gov (United States)

Satymbekov, M. N.; Pak, I. T.; Naizabayeva, L.; Nurzhanov, Ch. A.

2017-12-01

In this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.

The Development Of Red Chili Agribusiness Cluster With Soft System Methodology (Ssm Approach In Garut, West Java

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Sri Ayu Andayani

2016-12-01

Full Text Available Red chili is one of the commodities with high price fluctuation and gives influence to inflation. It happens due to the unsustainable supply of red chili from the central production centers to the market. Bank Indonesia (central bank initiates a cluster system to support price controlling and regional economic growth. In this regard, the study is conducted  in Garut regency, which is one of the centers of red chili plantation in West Java and uses as cluster development, and yet there are still many obstacles along the way. This paper has the objective to describe the problem which causes unsustainable production and affects industrial supplies systemically and also to analyze the existing partnerships in order to maintain the continuity of supply as an alternative solution.This study was designed qualitatively with case study method through a system approach namely soft system methodology (SSM. The results shows that the problems in the cluster of red chili are ranging from production planning to the delay of sales payment process which systemically interlinked and the collaboration of executors that have not been optimally implemented. This study offers solution for those problems accordance with change formulation of SSM and industrial emphasis on fairness, transparency and integrated optimization with the principle of production sustainability from all stakeholders through participative collaboration to maintain continuity of production.

Simulation bounds for system availability

International Nuclear Information System (INIS)

Tietjen, G.L.; Waller, R.A.

1976-01-01

System availability is a dominant factor in the practicality of nuclear power electrical generating plants. A proposed model for obtaining either lower bounds or interval estimates on availability uses observed data on ''n'' failure-to-repair cycles of the system to estimate the parameters in the time-to-failure and time-to-repair models. These estimates are then used in simulating failure/repair cycles of the system. The availability estimate is obtained for each of 5000 samples of ''n'' failure/repair cycles to form a distribution of estimates. Specific percentile points of those simulated distributions are selected as lower simulation bounds or simulation interval bounds for the system availability. The method is illustrated with operational data from two nuclear plants for which an exponential time-to-failure and a lognormal time-to-repair are assumed

Pendekatan Clustering untuk Ekstraksi Pengetahuan pada Pembangunan Sistem Manajemen Pengetahuan

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Dwinta Rahmallah Pulukadang

2016-01-01

Full Text Available The importance of knowledge management in any organization encourages the development of a knowledge management system with features that can facilitate knowledge management processes such as storing, organizing, filtering, searching, and most important is the transfer of knowledge. The purpose of this researchis to develop a knowledge management system with a clustering approach for knowledge extraction by using a knowledge of publication writing. This study uses clustering k-means method which is used for cluster knowledge feature where at the same time can help the process of organizing, filtering, browsing and searching knowledge. The results of this research showed that the clustering k-means can be used for knowledge management system with the best value of purity= 0,8454 which is found by using k = 20. Clustering approach in the system again can help the process for knowledge searching based on knowledge cluster. This can be proved by carried out 15 times experiments which result in average level of accuracy (precision about 89.13% and the average rate of completeness (recallabout 85.73 %.   Keywords : Knowledge Management System; Extraction; K-means; Clustering

Diametrical clustering for identifying anti-correlated gene clusters.

Science.gov (United States)

Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

2003-09-01

Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

On the incidence of close binary stars in globular clusters and the nature of the cluster X-ray sources

International Nuclear Information System (INIS)

Trimble, V.

1977-01-01

Recent calculations suggest that the globular clusters could not have formed with more than 20 per cent of the normal Population I fraction of their stars in binary systems. The fact that the clusters have more than their fair share of novae and U Geminorum stars (three each out of approximately 200 of each known, while the clusters contain only about 10 -4 of the mass and 10 -3 of the luminosity of the galaxy) therefore becomes surprising. The hypothesis of binary capture within cluster cores suggested to account for the clusters' high X-ray luminosity provides a few extra systems, but neither it nor any of the similar encounter or capture mechanisms suggested can account for the novae and U Gen stars, which remain puzzling. The number of Algol-type and W UMa eclipsing binaries predicted by these hypotheses do not conflict with data presently available, but careful searches for them would constitute a critical test of the theories. (author)

A Review of Subsequence Time Series Clustering

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Seyedjamal Zolhavarieh

2014-01-01

Full Text Available Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

THE ACS FORNAX CLUSTER SURVEY. X. COLOR GRADIENTS OF GLOBULAR CLUSTER SYSTEMS IN EARLY-TYPE GALAXIES

International Nuclear Information System (INIS)

Liu Chengze; Peng, Eric W.; Jordan, Andres; Ferrarese, Laura; Blakeslee, John P.; Cote, Patrick; Mei, Simona

2011-01-01

We use the largest homogeneous sample of globular clusters (GCs), drawn from the ACS Virgo Cluster Survey (ACSVCS) and ACS Fornax Cluster Survey (ACSFCS), to investigate the color gradients of GC systems in 76 early-type galaxies. We find that most GC systems possess an obvious negative gradient in (g-z) color with radius (bluer outward), which is consistent with previous work. For GC systems displaying color bimodality, both metal-rich and metal-poor GC subpopulations present shallower but significant color gradients on average, and the mean color gradients of these two subpopulations are of roughly equal strength. The field of view of ACS mainly restricts us to measuring the inner gradients of the studied GC systems. These gradients, however, can introduce an aperture bias when measuring the mean colors of GC subpopulations from relatively narrow central pointings. Inferred corrections to previous work imply a reduced significance for the relation between the mean color of metal-poor GCs and their host galaxy luminosity. The GC color gradients also show a dependence with host galaxy mass where the gradients are weakest at the ends of the mass spectrum-in massive galaxies and dwarf galaxies-and strongest in galaxies of intermediate mass, around a stellar mass of M * ∼10 10 M sun . We also measure color gradients for field stars in the host galaxies. We find that GC color gradients are systematically steeper than field star color gradients, but the shape of the gradient-mass relation is the same for both. If gradients are caused by rapid dissipational collapse and weakened by merging, these color gradients support a picture where the inner GC systems of most intermediate-mass and massive galaxies formed early and rapidly with the most massive galaxies having experienced greater merging. The lack of strong gradients in the GC systems of dwarfs, which probably have not experienced many recent major mergers, suggests that low-mass halos were inefficient at retaining

The Sustainable Development of Industry Clusters: Emergent Knowledge Networks and Socio Complex Adaptive Systems

Directory of Open Access Journals (Sweden)

Susu Nousala

2009-10-01

Full Text Available In a highly competitive global economy the development of sustainable, innovative responses from Industry is now vital. Many industries globally need to respond rather than react to current economic climate through sustainable (economically and environmentally development. The steel industry is a critical player in the urban landscape. Like many industries, small, medium enterprises (SMEs are vital players within the steel industry supply chain. The Australian SME steel housing sector (based in rural and regional areas are still developing systemic capabilities with the aim of realizing its full potential. The question of an effective sustainable industry is much larger than any one player. This paper aims to present a proposed methodological approach for sustainable cluster development based on previous industry wide investigations. Through the lens of scalability of a socio complex adaptive system, SME development becomes arguably the most significant player with regards to industry cluster development. By starting with SME development it's possible to build an understanding of a simultaneous two layered approach, "bottom up – top down" whilst including a very diversified group.

User and Document Group Approach of Clustering in Tagging Systems

DEFF Research Database (Denmark)

Pan, Rong; Xu, Guandong; Dolog, Peter

2010-01-01

In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optim...... amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group....

Cluster analysis of autoantibodies in 852 patients with systemic lupus erythematosus from a single center.

Science.gov (United States)

Artim-Esen, Bahar; Çene, Erhan; Şahinkaya, Yasemin; Ertan, Semra; Pehlivan, Özlem; Kamali, Sevil; Gül, Ahmet; Öcal, Lale; Aral, Orhan; Inanç, Murat

2014-07-01

Associations between autoantibodies and clinical features have been described in systemic lupus erythematosus (SLE). Herein, we aimed to define autoantibody clusters and their clinical correlations in a large cohort of patients with SLE. We analyzed 852 patients with SLE who attended our clinic. Seven autoantibodies were selected for cluster analysis: anti-DNA, anti-Sm, anti-RNP, anticardiolipin (aCL) immunoglobulin (Ig)G or IgM, lupus anticoagulant (LAC), anti-Ro, and anti-La. Two-step clustering and Kaplan-Meier survival analyses were used. Five clusters were identified. A cluster consisted of patients with only anti-dsDNA antibodies, a cluster of anti-Sm and anti-RNP, a cluster of aCL IgG/M and LAC, and a cluster of anti-Ro and anti-La antibodies. Analysis revealed 1 more cluster that consisted of patients who did not belong to any of the clusters formed by antibodies chosen for cluster analysis. Sm/RNP cluster had significantly higher incidence of pulmonary hypertension and Raynaud phenomenon. DsDNA cluster had the highest incidence of renal involvement. In the aCL/LAC cluster, there were significantly more patients with neuropsychiatric involvement, antiphospholipid syndrome, autoimmune hemolytic anemia, and thrombocytopenia. According to the Systemic Lupus International Collaborating Clinics damage index, the highest frequency of damage was in the aCL/LAC cluster. Comparison of 10 and 20 years survival showed reduced survival in the aCL/LAC cluster. This study supports the existence of autoantibody clusters with distinct clinical features in SLE and shows that forming clinical subsets according to autoantibody clusters may be useful in predicting the outcome of the disease. Autoantibody clusters in SLE may exhibit differences according to the clinical setting or population.

Performance comparison analysis library communication cluster system using merge sort

Science.gov (United States)

Wulandari, D. A. R.; Ramadhan, M. E.

2018-04-01

Begins by using a single processor, to increase the speed of computing time, the use of multi-processor was introduced. The second paradigm is known as parallel computing, example cluster. The cluster must have the communication potocol for processing, one of it is message passing Interface (MPI). MPI have many library, both of them OPENMPI and MPICH2. Performance of the cluster machine depend on suitable between performance characters of library communication and characters of the problem so this study aims to analyze the comparative performances libraries in handling parallel computing process. The case study in this research are MPICH2 and OpenMPI. This case research execute sorting’s problem to know the performance of cluster system. The sorting problem use mergesort method. The research method is by implementing OpenMPI and MPICH2 on a Linux-based cluster by using five computer virtual then analyze the performance of the system by different scenario tests and three parameters for to know the performance of MPICH2 and OpenMPI. These performances are execution time, speedup and efficiency. The results of this study showed that the addition of each data size makes OpenMPI and MPICH2 have an average speed-up and efficiency tend to increase but at a large data size decreases. increased data size doesn’t necessarily increased speed up and efficiency but only execution time example in 100000 data size. OpenMPI has a execution time greater than MPICH2 example in 1000 data size average execution time with MPICH2 is 0,009721 and OpenMPI is 0,003895 OpenMPI can customize communication needs.

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

clusterMaker: a multi-algorithm clustering plugin for Cytoscape

Directory of Open Access Journals (Sweden)

Morris John H

2011-11-01

Full Text Available Abstract Background In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view, k-means, k-medoid, SCPS, AutoSOME, and native (Java MCL. Results Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. Conclusions The Cytoscape plugin cluster

Hydrogen spillover on DV (555-777) graphene – vanadium cluster system: First principles study

Energy Technology Data Exchange (ETDEWEB)

Kumar, E. Mathan, E-mail: ranjit.t@res.srmuniv.ac.in, E-mail: mathanranjitha@gmail.com; Thapa, Ranjit, E-mail: ranjit.t@res.srmuniv.ac.in, E-mail: mathanranjitha@gmail.com [SRM Research Institute, SRM University, Kattankulathur, Tamil Nadu - 603203 (India); P, Sabarikirishwaran [Department of Physics and Nanotechnology, SRM University, Kattankulathur, Tamil Nadu - 603203 (India)

2015-06-24

Using dispersion corrected density functional theory (DFT+D), the interaction of Vanadium adatom and cluster with divacancy (555-777) defective graphene sheet has been studied elaborately. We explore the prospect of hydrogen storage on V{sub 4} cluster adsorbed divacancy graphene system. It has been observed that V{sub 4} cluster (acting as a catalyst) can dissociate the H{sub 2} molecule into H atoms with very low barrier energy. We introduce the spillover of the atomic hydrogen throughout the surface via external mediator gallane (GaH{sub 3}) to form a hydrogenated system.

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

2006-01-01

paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

2008-01-01

paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

Contribuição da Abordagem System Dynamics na Compreensão da Competitividade de Clusters de Negócios

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André Alarcon de Almeida Prado

2013-12-01

Full Text Available O presente trabalho teve como objetivo a constituição de um modelamento exploratório da operação de clusters de negócios por meio da abordagem System Dynamics, considerando, como fatores intervenientes do processo, os fundamentos da performance competitiva de clusters, proposto por Zaccarelli, Telles, Siqueira, Boaventura e Donaire (2008. Por meio da estruturação, segundo a metodologia system dynamics, da interação dos efeitos sistêmicos, responsáveis pelo estágio competitivo desses arranjos inter-organizacionais, segundo os autores, foram desenvolvidos diagramas causais para cada fundamento. Como principais resultados, o mapeamento das interações dinâmicas ofereceu uma nova perspectiva teórica e gerencial sobre operação e competitividade de clusters de negócios. DOI:10.5585/riae.v12i4.2011

Sparse Reconstruction of the Merging A520 Cluster System

Energy Technology Data Exchange (ETDEWEB)

Peel, Austin [Département d’Astrophysique, IRFU, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette (France); Lanusse, François [McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213 (United States); Starck, Jean-Luc, E-mail: austin.peel@cea.fr [Université Paris Diderot, AIM, Sorbonne Paris Cité, CEA, CNRS, F-91191 Gif-sur-Yvette (France)

2017-09-20

Merging galaxy clusters present a unique opportunity to study the properties of dark matter in an astrophysical context. These are rare and extreme cosmic events in which the bulk of the baryonic matter becomes displaced from the dark matter halos of the colliding subclusters. Since all mass bends light, weak gravitational lensing is a primary tool to study the total mass distribution in such systems. Combined with X-ray and optical analyses, mass maps of cluster mergers reconstructed from weak-lensing observations have been used to constrain the self-interaction cross-section of dark matter. The dynamically complex Abell 520 (A520) cluster is an exceptional case, even among merging systems: multi-wavelength observations have revealed a surprising high mass-to-light concentration of dark mass, the interpretation of which is difficult under the standard assumption of effectively collisionless dark matter. We revisit A520 using a new sparsity-based mass-mapping algorithm to independently assess the presence of the puzzling dark core. We obtain high-resolution mass reconstructions from two separate galaxy shape catalogs derived from Hubble Space Telescope observations of the system. Our mass maps agree well overall with the results of previous studies, but we find important differences. In particular, although we are able to identify the dark core at a certain level in both data sets, it is at much lower significance than has been reported before using the same data. As we cannot confirm the detection in our analysis, we do not consider A520 as posing a significant challenge to the collisionless dark matter scenario.

Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

Directory of Open Access Journals (Sweden)

Mohammad Nur Shodiq

2016-03-01

Full Text Available Spatio temporal data clustering is challenge task. The result of clustering data are utilized to investigate the seismic parameters. Seismic parameters are used to describe the characteristics of earthquake behavior. One of the effective technique to study multidimensional spatio temporal data is visualization. But, visualization of multidimensional data is complicated problem. Because, this analysis consists of observed data cluster and seismic parameters. In this paper, we propose a visualization system, called as IES (Indonesia Earthquake System, for cluster analysis, spatio temporal analysis, and visualize the multidimensional data of seismic parameters. We analyze the cluster analysis by using automatic clustering, that consists of get optimal number of cluster and Hierarchical K-means clustering. We explore the visual cluster and multidimensional data in low dimensional space visualization. We made experiment with observed data, that consists of seismic data around Indonesian archipelago during 2004 to 2014. Keywords: Clustering, visualization, multidimensional data, seismic parameters.

Balanced score card for cluster of building materials scrap recycling in Voronezh

Directory of Open Access Journals (Sweden)

Potekhi Igor

2018-01-01

Full Text Available In this article is described an effort to develop a new system of management and economy of building materials scrap recycling cluster. For this task is used conception “Management by Objective” by American legend Peter Drucker. Thus cluster participants have divergent purposes, but have common purpose, the present conception match the most for develop business strategy of uniting companies in this cluster. As result, it was developed a “Balanced Scorecard” for the cluster. This “Balanced Scorecard” take into account technological features of companies in cluster and developed common purpose system. In base of system structure of indicators there is exist model of cluster. This model can show capacity, output flows and throughput capacity of participants. During develop a system of cluster’s purposes it were learned priorities balance of economy efficiency and natural resource management. There are shown calculation of costs of reuse building recycled materials, located on solid waste landfill. Developed strategic system of purpose of cluster activity allows to get economical benefit all participants and for citizens to save environment from nature disaster.

Intrinsic Variability in Multiple Systems and Clusters: Open Questions

Science.gov (United States)

Lampens, P.

2006-04-01

It is most interesting and rewarding to probe the stellar structure of stars which belong to a system originating from the same parent cloud as this provides additional and more accurate constraints for the models. New results on pulsating components in multiple systems and clusters are beginning to emerge regularly. Based on concrete studies, I will present still unsolved problems and discuss some of the issues which may affect our understanding of the pulsation physics in such systems but also in general.

Evolution of the electronic and ionic structure of Mg clusters with increase in cluster size

DEFF Research Database (Denmark)

Lyalin, Andrey G.; Solov'yov, Ilia; Solov'yov, Andrey V.

2003-01-01

The optimized structure and electronic properties of neutral and singly charged magnesium clusters have been investigated using ab initio theoretical methods based on density-functional theory and systematic post–Hartree-Fock many-body perturbation theory accounting for all electrons in the system....... We have investigated the appearance of the elements of the hcp structure and metallic evolution of the magnesium clusters, as well as the stability of linear chains and rings of magnesium atoms. The results obtained are compared with the available experimental data and the results of other...

Аdaptive clustering algorithm for recommender systems

OpenAIRE

Stekh, Yu.; Artsibasov, V.

2012-01-01

In this article adaptive clustering algorithm for recommender systems is developed. Розроблено адаптивний алгоритм кластеризації для рекомендаційних систем.

Clustering of galaxies near damped Lyman-alpha systems with (z) = 2.6

Science.gov (United States)

Wolfe, A. M

1993-01-01

The galaxy two-point correlation function, xi, at (z) = 2.6 is determined by comparing the number of Ly-alpha-emitting galaxies in narrowband CCD fields selected for the presence of damped L-alpha absorption to their number in randomly selected control fields. Comparisons between the presented determination of (xi), a density-weighted volume average of xi, and model predictions for (xi) at large redshifts show that models in which the clustering pattern is fixed in proper coordinates are highly unlikely, while better agreement is obtained if the clustering pattern is fixed in comoving coordinates. Therefore, clustering of Ly-alpha-emitting galaxies around damped Ly-alpha systems at large redshifts is strong. It is concluded that the faint blue galaxies are drawn from a parent population different from normal galaxies, the presumed offspring of damped Ly-alpha systems.

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

Customized recommendations for production management clusters of North American automatic milking systems.

Science.gov (United States)

Tremblay, Marlène; Hess, Justin P; Christenson, Brock M; McIntyre, Kolby K; Smink, Ben; van der Kamp, Arjen J; de Jong, Lisanne G; Döpfer, Dörte

2016-07-01

Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is

Isolated ellipticals and their globular cluster systems. III. NGC 2271, NGC 2865, NGC 3962, NGC 4240, and IC 4889

Science.gov (United States)

Salinas, R.; Alabi, A.; Richtler, T.; Lane, R. R.

2015-05-01

As tracers of star formation, galaxy assembly, and mass distribution, globular clusters have provided important clues to our understanding of early-type galaxies. But their study has been mostly constrained to galaxy groups and clusters where early-type galaxies dominate, leaving the properties of the globular cluster systems (GCSs) of isolated ellipticals as a mostly uncharted territory. We present Gemini-South/GMOS g'i' observations of five isolated elliptical galaxies: NGC 3962, NGC 2865, IC 4889, NGC 2271, and NGC 4240. Photometry of their GCSs reveals clear color bimodality in three of them, but remains inconclusive for the other two. All the studied GCSs are rather poor with a mean specific frequency SN ~ 1.5, independently of the parent galaxy luminosity. Considering information from previous work as well, it is clear that bimodality and especially the presence of a significant, even dominant, population of blue clusters occurs at even the most isolated systems, which casts doubts on a possible accreted origin of metal-poor clusters, as suggested by some models. Additionally, we discuss the possible existence of ultra-compact dwarfs around the isolated elliptical NGC 3962. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the Science and Technology Facilities Council (United Kingdom), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência, Tecnologia e Inovação (Brazil) and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina).Globular cluster photometry is available in electronic form at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/577/A59Appendices are available in

Clusters - Tourism Activity Increase Competitiveness Support

Directory of Open Access Journals (Sweden)

Carmen IORDACHE

2010-05-01

Full Text Available Tourism represents one of those areas with the greatest potential of global expansion. Tourism development strategy in terms of maximizing its positive effects on regional economic increase and implicitly on the national one starts from the premise that in global economy value is created in regions which are defined as particular geographical entities, separated by geographical reasons and not as political-administrative structures, and economic increase is centrally cumulated and valued according to the economic policy and the national legal system.Regional economic system approach based on “cluster” concept is explained by the fact that the regional activities portfolio is based on an inter and intra-industry networking grouped by cluster, in which is created the value that increases as the activity results are leading to the final consumers.This type of communication aims to highlight the tourism role as a factor in regional development, the clustering process significance in obtaining some competitiveness advantages, clusters development in tourism beginnings, and also the identification methodology used to select one touristic area to create the cluster.

75 FR 7464 - Energy Efficient Building Systems Regional Innovation Cluster Initiative-Joint Federal Funding...

Science.gov (United States)

2010-02-19

... a regional innovation cluster focused on innovation in energy efficient building technologies and... technology challenges through approaches that span basic research to engineering development to... DEPARTMENT OF ENERGY Energy Efficient Building Systems Regional Innovation Cluster Initiative...

Novel Functions of MicroRNA-17-92 Cluster in the Endocrine System.

Science.gov (United States)

Wan, Shan; Chen, Xiang; He, Yuedong; Yu, Xijie

2018-01-01

MiR-17-92 cluster is coded by MIR17HG in chromosome 13, which is highly conserved in vertebrates. Published literatures have proved that miR-17-92 cluster critically regulates tumorigenesis and metastasis. Recent researches showed that the miR-17-92 cluster also plays novel functions in the endocrine system. To summarize recent findings on the physiological and pathological roles of miR-17-92 cluster in bone, lipid and glucose metabolisms. MiR-17-92 cluster plays significant regulatory roles in bone development and metabolism through regulating the differentiation and function of osteoblasts and osteoclasts. In addition, miR-17- 92 cluster is nearly involved in every aspect of lipid metabolism. Last but not the least, the miR-17-92 cluster is closely bound up with pancreatic beta cell function, development of type 1 diabetes and insulin resistance. However, whether miR-17-92 cluster is involved in the communication among bone, fat and glucose metabolisms remains unknown. Growing evidence indicates that miR-17-92 cluster plays significant roles in bone, lipid and glucose metabolisms through a variety of signaling pathways. Fully understanding its modulating mechanisms may necessarily facilitate to comprehend the clinical and molecule features of some metabolic disorders such as osteoporosis, arthrosclerosis and diabetes mellitus. It may provide new drug targets to prevent and cure these disorders. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Cluster electric spectroscopy of colloid chemical oxyhydrate systems

CERN Document Server

Sucharev, Yu I

2015-01-01

This monograph deals with the shape of Liesegang operator and its respective phase diagrams of spontaneous surges and analyzed properties of cluster attractors. It describes the influence of pulsation noise or self-organization current of gel systems in a magnetic field on singularities of optic parameters of yttrium oxyhydrate, as well as on kinetic curves of changes in optic density of oxyhydrate systems, sorptive properties of d- and f-elements, and the structural organization of their colloids. This monograph is meant for postgraduate students, magisters, researchers, and those interested

A Trajectory Regression Clustering Technique Combining a Novel Fuzzy C-Means Clustering Algorithm with the Least Squares Method

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Xiangbing Zhou

2018-04-01

Full Text Available Rapidly growing GPS (Global Positioning System trajectories hide much valuable information, such as city road planning, urban travel demand, and population migration. In order to mine the hidden information and to capture better clustering results, a trajectory regression clustering method (an unsupervised trajectory clustering method is proposed to reduce local information loss of the trajectory and to avoid getting stuck in the local optimum. Using this method, we first define our new concept of trajectory clustering and construct a novel partitioning (angle-based partitioning method of line segments; second, the Lagrange-based method and Hausdorff-based K-means++ are integrated in fuzzy C-means (FCM clustering, which are used to maintain the stability and the robustness of the clustering process; finally, least squares regression model is employed to achieve regression clustering of the trajectory. In our experiment, the performance and effectiveness of our method is validated against real-world taxi GPS data. When comparing our clustering algorithm with the partition-based clustering algorithms (K-means, K-median, and FCM, our experimental results demonstrate that the presented method is more effective and generates a more reasonable trajectory.

Open source clustering software.

Science.gov (United States)

de Hoon, M J L; Imoto, S; Nolan, J; Miyano, S

2004-06-12

We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C. The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

The HectoMAP Cluster Survey. I. redMaPPer Clusters

Science.gov (United States)

Sohn, Jubee; Geller, Margaret J.; Rines, Kenneth J.; Hwang, Ho Seong; Utsumi, Yousuke; Diaferio, Antonaldo

2018-04-01

We use the dense HectoMAP redshift survey to explore the properties of 104 redMaPPer cluster candidates. The redMaPPer systems in HectoMAP cover the full range of richness and redshift (0.08 systems included in the Subaru/Hyper Suprime-Cam public data release are bona fide clusters. The median number of spectroscopic members per cluster is ∼20. We include redshifts of 3547 member candidates listed in the redMaPPer catalog whether they are cluster members or not. We evaluate the redMaPPer membership probability spectroscopically. The purity (number of real systems) in redMaPPer exceeds 90% even at the lowest richness. Three massive galaxy clusters (M ∼ 2 × 1013 M ⊙) associated with X-ray emission in the HectoMAP region are not included in the public redMaPPer catalog with λ rich > 20, because they lie outside the cuts for this catalog.

Folksonomies and clustering in the collaborative system CiteULike

Science.gov (United States)

Capocci, Andrea; Caldarelli, Guido

2008-06-01

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags.

Folksonomies and clustering in the collaborative system CiteULike

International Nuclear Information System (INIS)

Capocci, Andrea; Caldarelli, Guido

2008-01-01

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags

Folksonomies and clustering in the collaborative system CiteULike

Energy Technology Data Exchange (ETDEWEB)

Capocci, Andrea [Dip. di Informatica e Sistemistica Universita ' Sapienza' , via Ariosto, 25 00185 Rome (Italy); Caldarelli, Guido [SMC Centre, CNR-INFM, Dip. di Fisica, Universita ' Sapienza' , P.le A. Moro 5, 00185-Rome (Italy)

2008-06-06

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags.

Globular Clusters - Guides to Galaxies

CERN Document Server

Richtler, Tom; Joint ESO-FONDAP Workshop on Globular Clusters

2009-01-01

The principal question of whether and how globular clusters can contribute to a better understanding of galaxy formation and evolution is perhaps the main driving force behind the overall endeavour of studying globular cluster systems. Naturally, this splits up into many individual problems. The objective of the Joint ESO-FONDAP Workshop on Globular Clusters - Guides to Galaxies was to bring together researchers, both observational and theoretical, to present and discuss the most recent results. Topics covered in these proceedings are: internal dynamics of globular clusters and interaction with host galaxies (tidal tails, evolution of cluster masses), accretion of globular clusters, detailed descriptions of nearby cluster systems, ultracompact dwarfs, formations of massive clusters in mergers and elsewhere, the ACS Virgo survey, galaxy formation and globular clusters, dynamics and kinematics of globular cluster systems and dark matter-related problems. With its wide coverage of the topic, this book constitute...

Cluster consensus in discrete-time networks of multiagents with inter-cluster nonidentical inputs.

Science.gov (United States)

Han, Yujuan; Lu, Wenlian; Chen, Tianping

2013-04-01

In this paper, cluster consensus of multiagent systems is studied via inter-cluster nonidentical inputs. Here, we consider general graph topologies, which might be time-varying. The cluster consensus is defined by two aspects: intracluster synchronization, the state at which differences between each pair of agents in the same cluster converge to zero, and inter-cluster separation, the state at which agents in different clusters are separated. For intra-cluster synchronization, the concepts and theories of consensus, including the spanning trees, scramblingness, infinite stochastic matrix product, and Hajnal inequality, are extended. As a result, it is proved that if the graph has cluster spanning trees and all vertices self-linked, then the static linear system can realize intra-cluster synchronization. For the time-varying coupling cases, it is proved that if there exists T > 0 such that the union graph across any T-length time interval has cluster spanning trees and all graphs has all vertices self-linked, then the time-varying linear system can also realize intra-cluster synchronization. Under the assumption of common inter-cluster influence, a sort of inter-cluster nonidentical inputs are utilized to realize inter-cluster separation, such that each agent in the same cluster receives the same inputs and agents in different clusters have different inputs. In addition, the boundedness of the infinite sum of the inputs can guarantee the boundedness of the trajectory. As an application, we employ a modified non-Bayesian social learning model to illustrate the effectiveness of our results.

AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

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Cooper James B

2010-03-01

Full Text Available Abstract Background Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. Results We integrated strategies from machine learning, cartography, and graph theory into a new informatics method for automatically clustering self-organizing map ensembles of high-dimensional data. Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data. Visualization of AutoSOME output using network diagrams and differential heat maps reveals unexpected variation among well-characterized cancer cell lines. Co-expression analysis of data from human embryonic and induced pluripotent stem cells using AutoSOME identifies >3400 up-regulated genes associated with pluripotency, and indicates that a recently identified protein-protein interaction network characterizing pluripotency was underestimated by a factor of four. Conclusions By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome.

Fluorescent Thiol-Derivatized Gold Clusters Embedded in Polymers

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G. Carotenuto

2013-01-01

Full Text Available Owing to aurophilic interactions, linear and/or planar Au(I-thiolate molecules spontaneously aggregate, leading to molecular gold clusters passivated by a thiolate monolayer coating. Differently from the thiolate precursors, such cluster compounds show very intensive visible fluorescence characteristics that can be tuned by alloying the gold clusters with silver atoms or by conjugating the electronic structure of the metallic core with unsaturated electronic structures in the organic ligand through the sulphur atom. Here, the photoluminescence features of some examples of these systems are shortly described.

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

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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.

European BWR R and D cluster for innovative passive safety systems

International Nuclear Information System (INIS)

Hicken, E.F.; Lensa, W. von

1996-01-01

The main technological innovation trends for future nuclear power plants tend towards a broader use of passive safety systems for the prevention, mitigation and managing of severe accident scenarios. Several approaches have been undertaken in a number of European countries to study and demonstrate the feasibility and charateristics of innovative passive safety systems. The European BWR R and D Cluster combines those experimental and analytical efforts that are mainly directed to the introduction of passive safety systems into boiling water reactor technology. The Cluster is grouped around thermohydraulic test facilities in Europe for the qualification of innovative BWR safety systems, also taking into account especially the operating experience of the nuclear power plant Dodewaard and other BWRs, which already incorporated some passive safety features. The background, the objectives, the structure of the project and the work programme are presented in this paper as well as an outline of the significance of the expected results. (orig.) [de

Support Policies in Clusters: Prioritization of Support Needs by Cluster Members According to Cluster Life Cycle

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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.

Genome-Wide Analysis of Type VI System Clusters and Effectors in Burkholderia Species

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Thao Thi Nguyen

2018-02-01

Full Text Available Type VI secretion system (T6SS has been discovered in a variety of gram-negative bacteria as a versatile weapon to stimulate the killing of eukaryotic cells or prokaryotic competitors. Type VI secretion effectors (T6SEs are well known as key virulence factors for important pathogenic bacteria. In many Burkholderia species, T6SS has evolved as the most complicated secretion pathway with distinguished types to translocate diverse T6SEs, suggesting their essential roles in this genus. Here we attempted to detect and characterize T6SSs and potential T6SEs in target genomes of plant-associated and environmental Burkholderia species based on computational analyses. In total, 66 potential functional T6SS clusters were found in 30 target Burkholderia bacterial genomes, of which 33% possess three or four clusters. The core proteins in each cluster were specified and phylogenetic trees of three components (i.e., TssC, TssD, TssL were constructed to elucidate the relationship among the identified T6SS clusters. Next, we identified 322 potential T6SEs in the target genomes based on homology searches and explored the important domains conserved in effector candidates. In addition, using the screening approach based on the profile hidden Markov model (pHMM of T6SEs that possess markers for type VI effectors (MIX motif (MIX T6SEs, 57 revealed proteins that were not included in training datasets were recognized as novel MIX T6SE candidates from the Burkholderia species. This approach could be useful to identify potential T6SEs from other bacterial genomes.

Correlations in clusters and related systems. New perspectives on the many-body problem

International Nuclear Information System (INIS)

Connerade, J.P.

1996-01-01

The contents of the present volume are the proceedings of an Adriatico Research Conference, held at the International Centre for Theoretical Physics in Trieste from 26 to 29 July 1994. The theme of the conference covered many aspects of cooperative effects, beginning with giant resonances in many-electron systems, and particularly in new objects such as metallic clusters, in which collective electron dynamics are a novel feature. The relationship of these resonances with comparable features in nuclear and solid state physics was extensively discussed. Related effects, such as instabilities of valence both in clusters and in solids were explored. Clusters allow one to track the evolution of certain properties from the free atom to the solid state limits as a function of size. The giant resonances concerned not only intra-atomic excitations, but also correlated motions of all delocalized electrons within the cluster. Other systems with unusual properties, such as negative ions, in which correlations play an important role, were also considered. Finally, dynamical effects and the possible interactions between electron-electron correlations and high laser fields were envisaged

Directed clustering coefficient as a measure of systemic risk in complex banking networks

Science.gov (United States)

Tabak, Benjamin M.; Takami, Marcelo; Rocha, Jadson M. C.; Cajueiro, Daniel O.; Souza, Sergio R. S.

2014-01-01

Recent literature has focused on the study of systemic risk in complex networks. It is clear now, after the crisis of 2008, that the aggregate behavior of the interaction among agents is not straightforward and it is very difficult to predict. Contributing to this debate, this paper shows that the directed clustering coefficient may be used as a measure of systemic risk in complex networks. Furthermore, using data from the Brazilian interbank network, we show that the directed clustering coefficient is negatively correlated with domestic interest rates.

Reduced-dimension power allocation over clustered channels in cognitive radios system under co-channel interference

KAUST Repository

Ben Ghorbel, Mahdi

2014-05-12

The objective of this paper is to propose a reduceddimension resource allocation scheme in the context of cognitive radio system in presence of co-channel interference between users. We assume a multicarrier transmission for both the primary and secondary systems. Instead of optimizing the powers over all sub-carriers, the sub-carriers are grouped into clusters of sub-carriers, where the power of each sub-carrier is directly related to the power of the correspondent cluster. The power optimization is done only over the set of clusters instead of all sub-carriers which can significantly reduce the complexity of the resource allocation problem. The performance loss of the reduced dimension solution with respect to the optimal solution, where the optimization is carried over all active sub-carriers, allows trading-off complexity versus performance. Numerical evaluation indeed revealed that a limited performance loss occurs by optimizing over a reduced set of clusters instead of the full optimization in the context of cognitive radio systems.

High-Performance, Multi-Node File Copies and Checksums for Clustered File Systems

Science.gov (United States)

Kolano, Paul Z.; Ciotti, Robert B.

2012-01-01

Modern parallel file systems achieve high performance using a variety of techniques, such as striping files across multiple disks to increase aggregate I/O bandwidth and spreading disks across multiple servers to increase aggregate interconnect bandwidth. To achieve peak performance from such systems, it is typically necessary to utilize multiple concurrent readers/writers from multiple systems to overcome various singlesystem limitations, such as number of processors and network bandwidth. The standard cp and md5sum tools of GNU coreutils found on every modern Unix/Linux system, however, utilize a single execution thread on a single CPU core of a single system, and hence cannot take full advantage of the increased performance of clustered file systems. Mcp and msum are drop-in replacements for the standard cp and md5sum programs that utilize multiple types of parallelism and other optimizations to achieve maximum copy and checksum performance on clustered file systems. Multi-threading is used to ensure that nodes are kept as busy as possible. Read/write parallelism allows individual operations of a single copy to be overlapped using asynchronous I/O. Multinode cooperation allows different nodes to take part in the same copy/checksum. Split-file processing allows multiple threads to operate concurrently on the same file. Finally, hash trees allow inherently serial checksums to be performed in parallel. Mcp and msum provide significant performance improvements over standard cp and md5sum using multiple types of parallelism and other optimizations. The total speed-ups from all improvements are significant. Mcp improves cp performance over 27x, msum improves md5sum performance almost 19x, and the combination of mcp and msum improves verified copies via cp and md5sum by almost 22x. These improvements come in the form of drop-in replacements for cp and md5sum, so are easily used and are available for download as open source software at http://mutil.sourceforge.net.

THE M33 GLOBULAR CLUSTER SYSTEM WITH PAndAS DATA: THE LAST OUTER HALO CLUSTER?

International Nuclear Information System (INIS)

Cockcroft, Robert; Harris, William E.; Ferguson, Annette M. N.

2011-01-01

We use CFHT/MegaCam data to search for outer halo star clusters in M33 as part of the Pan-Andromeda Archaeological Survey. This work extends previous studies out to a projected radius of 50 kpc and covers over 40 deg 2 . We find only one new unambiguous star cluster in addition to the five previously known in the M33 outer halo (10 kpc ≤ r ≤ 50 kpc). Although we identify 2440 cluster candidates of various degrees of confidence from our objective image search procedure, almost all of these are likely background contaminants, mostly faint unresolved galaxies. We measure the luminosity, color, and structural parameters of the new cluster in addition to the five previously known outer halo clusters. At a projected radius of 22 kpc, the new cluster is slightly smaller, fainter, and redder than all but one of the other outer halo clusters, and has g' ∼ 19.9, (g' - i') ∼ 0.6, concentration parameter c ∼ 1.0, a core radius r c ∼ 3.5 pc, and a half-light radius r h ∼ 5.5 pc. For M33 to have so few outer halo clusters compared to M31 suggests either tidal stripping of M33's outer halo clusters by M31, or a very different, much calmer accretion history of M33.

Performance Analysis of Cluster Formation in Wireless Sensor Networks

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Edgar Romo Montiel

2017-12-01

Full Text Available Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes.

Research on the method of information system risk state estimation based on clustering particle filter

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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.

Spatial and color clustering on an FPGA-based computer system

Science.gov (United States)

Leeser, Miriam E.; Kitaryeva, Natalya V.; Crisman, Jill D.

1998-10-01

We are mapping an image clustering algorithm onto an FPGA- based computer system. Our approach processes raw pixel data in the red, green, blue color space and generates an output image where all pixels are assigned to classes. A class is a group of pixels with similar color and location. These classes are then used as the basis of further processing to generate tags. The tags, in turn, are used to generate queries for searching libraries of digital images. We run our image tagging approach on an FPGA-based computing machine. The image clustering algorithm is run on an FPGA board, and only the classified image is communicated to the host PC. Further processing is run on the host. Our experimental system consists of an Annapolis Wildforce board with four Xilinx XC4000 chips and a PCI connection to a host PC. Our implementation allows the raw image data to stay local to the FPGAs, and only the class image is communicated to the host PC. The classified pixels are then used to generate tags which can be used for searching a digital library. This approach allows us to parallelize the image processing on the FPGA board, and to minimize the data handled by the PC. FPGA platforms are ideally suited for this sort of initial processing of images. The large amount of image data can be preprocessed by exploiting the inherent parallelism available in FPGA architectures, keeping unnecessary data off the host processor. The result of our algorithm is a reduction by up to a factor of six in the number of bits required to represent each pixel. The output data is passed to the host PC, thus reducing the processing and memory resources needed compared to handling the raw data on the PC. The process of generating tags of images is simplified by first classifying pixels on an FPGA-based system, and digital library search is accelerated.

Cluster Physics with Merging Galaxy Clusters

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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.

A scalable and practical one-pass clustering algorithm for recommender system

Science.gov (United States)

Khalid, Asra; Ghazanfar, Mustansar Ali; Azam, Awais; Alahmari, Saad Ali

2015-12-01

KMeans clustering-based recommendation algorithms have been proposed claiming to increase the scalability of recommender systems. One potential drawback of these algorithms is that they perform training offline and hence cannot accommodate the incremental updates with the arrival of new data, making them unsuitable for the dynamic environments. From this line of research, a new clustering algorithm called One-Pass is proposed, which is a simple, fast, and accurate. We show empirically that the proposed algorithm outperforms K-Means in terms of recommendation and training time while maintaining a good level of accuracy.

Neutrosophic Hierarchical Clustering Algoritms

Directory of Open Access Journals (Sweden)

Rıdvan Şahin

2014-03-01

Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

Properties of an ionised-cluster beam from a vaporised-cluster ion source

International Nuclear Information System (INIS)

Takagi, T.; Yamada, I.; Sasaki, A.

1978-01-01

A new type of ion source vaporised-metal cluster ion source, has been developed for deposition and epitaxy. A cluster consisting of 10 2 to 10 3 atoms coupled loosely together is formed by adiabatic expansion ejecting the vapour of materials into a high-vacuum region through the nozzle of a heated crucible. The clusters are ionised by electron bombardment and accelerated with neutral clusters toward a substrate. In this paper, mechanisms of cluster formation experimental results of the cluster size (atoms/cluster) and its distribution, and characteristics of the cluster ion beams are reported. The size is calculated from the kinetic equation E = (1/2)mNVsub(ej) 2 , where E is the cluster beam energy, Vsub(ej) is the ejection velocity, m is the mass of atom and N is the cluster size. The energy and the velocity of the cluster are measured by an electrostatic 127 0 energy analyser and a rotating disc system, respectively. The cluster size obtained for Ag is about 5 x 10 2 to 2 x 10 3 atoms. The retarding potential method is used to confirm the results for Ag. The same dependence on cluster size for metals such as Ag, Cu and Pb has been obtained in previous experiments. In the cluster state the cluster ion beam is easily produced by electron bombardment. About 50% of ionised clusters are obtained under typical operation conditions, because of the large ionisation cross sections of the clusters. To obtain a uniform spatial distribution, the ionising electrode system is also discussed. The new techniques are termed ionised-cluster beam deposition (ICBD) and epitaxy (ICBE). (author)

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.

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

Analytical system availability techniques

NARCIS (Netherlands)

Brouwers, J.J.H.; Verbeek, P.H.J.; Thomson, W.R.

1987-01-01

Analytical techniques are presented to assess the probability distributions and related statistical parameters of loss of production from equipment networks subject to random failures and repairs. The techniques are based on a theoretical model for system availability, which was further developed

The sluggs survey: HST/ACS mosaic imaging of the NGC 3115 globular cluster system

Energy Technology Data Exchange (ETDEWEB)

Jennings, Zachary G.; Romanowsky, Aaron J.; Brodie, Jean P.; Arnold, Jacob A. [University of California Observatories, Santa Cruz, CA 95064 (United States); Strader, Jay [Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, MI 48824 (United States); Lin, Dacheng; Irwin, Jimmy A.; Wong, Ka-Wah [Department of Physics and Astronomy, University of Alabama, Box 870324, Tuscaloosa, AL 35487 (United States); Sivakoff, Gregory R., E-mail: zgjennin@ucsc.edu [Department of Physics, University of Alberta, Edmonton, Alberta T6G 2E1 (Canada)

2014-08-01

We present Hubble Space Telescope/Advanced Camera for Surveys (HST/ACS) g and z photometry and half-light radii R {sub h} measurements of 360 globular cluster (GC) candidates around the nearby S0 galaxy NGC 3115. We also include Subaru/Suprime-Cam g, r, and i photometry of 421 additional candidates. The well-established color bimodality of the GC system is obvious in the HST/ACS photometry. We find evidence for a 'blue tilt' in the blue GC subpopulation, wherein the GCs in the blue subpopulation get redder as luminosity increases, indicative of a mass-metallicity relationship. We find a color gradient in both the red and blue subpopulations, with each group of clusters becoming bluer at larger distances from NGC 3115. The gradient is of similar strength in both subpopulations, but is monotonic and more significant for the blue clusters. On average, the blue clusters have ∼10% larger R {sub h} than the red clusters. This average difference is less than is typically observed for early-type galaxies but does match that measured in the literature for the Sombrero Galaxy (M104), suggesting that morphology and inclination may affect the measured size difference between the red and blue clusters. However, the scatter on the R {sub h} measurements is large. We also identify 31 clusters more extended than typical GCs, which we term ultra-compact dwarf (UCD) candidates. Many of these objects are actually considerably fainter than typical UCDs. While it is likely that a significant number will be background contaminants, six of these UCD candidates are spectroscopically confirmed as NGC 3115 members. To explore the prevalence of low-mass X-ray binaries in the GC system, we match our ACS and Suprime-Cam detections to corresponding Chandra X-ray sources. We identify 45 X-ray-GC matches: 16 among the blue subpopulation and 29 among the red subpopulation. These X-ray/GC coincidence fractions are larger than is typical for most GC systems, probably due to the increased

Marketing research cluster analysis

Directory of Open Access Journals (Sweden)

Marić Nebojša

2002-01-01

Full Text Available One area of applications of cluster analysis in marketing is identification of groups of cities and towns with similar demographic profiles. This paper considers main aspects of cluster analysis by an example of clustering 12 cities with the use of Minitab software.

Molecular depth profiling of multi-layer systems with cluster ion sources

Energy Technology Data Exchange (ETDEWEB)

Cheng, Juan [Department of Chemistry, Penn State University, University Park, PA 16802 (United States); Winograd, Nicholas [Department of Chemistry, Penn State University, University Park, PA 16802 (United States)]. E-mail: nxw@psu.edu

2006-07-30

Cluster bombardment of molecular films has created new opportunities for SIMS research. To more quantitatively examine the interaction of cluster beams with organic materials, we have developed a reproducible platform consisting of a well-defined sugar film (trehalose) doped with peptides. Molecular depth profiles have been acquired with these systems using C{sub 60} {sup +} bombardment. In this study, we utilize this platform to determine the feasibility of examining buried interfaces for multi-layer systems. Using C{sub 60} {sup +} at 20 keV, several systems have been tested including Al/trehalose/Si, Al/trehalose/Al/Si, Ag/trehalose/Si and ice/trehalose/Si. The results show that there can be interactions between the layers during the bombardment process that prevent a simple interpretation of the depth profile. We find so far that the best results are obtained when the mass of the overlayer atoms is less than or nearly equal to the mass of the atoms in buried molecules. In general, these observations suggest that C{sub 60} {sup +} bombardment can be successfully applied to interface characterization of multi-layer systems if the systems are carefully chosen.

Cluster management.

Science.gov (United States)

Katz, R

1992-11-01

Cluster management is a management model that fosters decentralization of management, develops leadership potential of staff, and creates ownership of unit-based goals. Unlike shared governance models, there is no formal structure created by committees and it is less threatening for managers. There are two parts to the cluster management model. One is the formation of cluster groups, consisting of all staff and facilitated by a cluster leader. The cluster groups function for communication and problem-solving. The second part of the cluster management model is the creation of task forces. These task forces are designed to work on short-term goals, usually in response to solving one of the unit's goals. Sometimes the task forces are used for quality improvement or system problems. Clusters are groups of not more than five or six staff members, facilitated by a cluster leader. A cluster is made up of individuals who work the same shift. For example, people with job titles who work days would be in a cluster. There would be registered nurses, licensed practical nurses, nursing assistants, and unit clerks in the cluster. The cluster leader is chosen by the manager based on certain criteria and is trained for this specialized role. The concept of cluster management, criteria for choosing leaders, training for leaders, using cluster groups to solve quality improvement issues, and the learning process necessary for manager support are described.

Issues of branch clusters development: from theory to practice

Directory of Open Access Journals (Sweden)

Bondarenko N. E.

2016-07-01

Full Text Available the article deals with objective preconditions of forming stable bases of the cluster theory and its specific features, the attention is paid to historical aspects of dialectical development of the cluster theory. The authors highlighted the main tasks, accomplishment of which is necessary for achieving an effective cluster policy in the system of the national economy. The opportunity of using the advantages and potential opportunities of clusters in respect of the agricultural sphere of the national economy is grounded. The model of agro-industrial clusters is considered as one of the ways to increase competitive advantage of the agro-industrial complex, to achieve reproduction on an enlarged scale and to solve tasks of the national victualling. An algorithm of analyzing factors of forming clusters in the agricultural sector of russian economy is proposed.

Effect of Policy Analysis on Indonesia’s Maritime Cluster Development Using System Dynamics Modeling

Science.gov (United States)

Nursyamsi, A.; Moeis, A. O.; Komarudin

2018-03-01

As an archipelago with two third of its territory consist of water, Indonesia should address more attention to its maritime industry development. One of the catalyst to fasten the maritime industry growth is by developing a maritime cluster. The purpose of this research is to gain understanding of the effect if Indonesia implement maritime cluster policy to the growth of maritime economic and its role to enhance the maritime cluster performance, hence enhancing Indonesia’s maritime industry as well. The result of the constructed system dynamic model simulation shows that with the effect of maritime cluster, the growth of employment rate and maritime economic is much bigger that the business as usual case exponentially. The result implies that the government should act fast to form a legitimate cluster maritime organizer institution so that there will be a synergize, sustainable, and positive maritime cluster environment that will benefit the performance of Indonesia’s maritime industry.

Output ordering and prioritisation system (OOPS): ranking biosynthetic gene clusters to enhance bioactive metabolite discovery.

Science.gov (United States)

Peña, Alejandro; Del Carratore, Francesco; Cummings, Matthew; Takano, Eriko; Breitling, Rainer

2017-12-18

The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.

Super computer made with Linux cluster

International Nuclear Information System (INIS)

Lee, Jeong Hun; Oh, Yeong Eun; Kim, Jeong Seok

2002-01-01

This book consists of twelve chapters, which introduce super computer made with Linux cluster. The contents of this book are Linux cluster, the principle of cluster, design of Linux cluster, general things for Linux, building up terminal server and client, Bear wolf cluster by Debian GNU/Linux, cluster system with red hat, Monitoring system, application programming-MPI, on set-up and install application programming-PVM, with PVM programming and XPVM application programming-open PBS with composition and install and set-up and GRID with GRID system, GSI, GRAM, MDS, its install and using of tool kit

MANAGING THE DEVELOPMENT OF AGRO-INDUSTRIAL CLUSTERS

Directory of Open Access Journals (Sweden)

D. V. Zavyalov

2018-01-01

Full Text Available Purpose: the purpose of the research is to design a concept of management system for agro-industrial clusters as self-organizing systems. The transition to a new technological way was marked not only by breakthrough solutions in the organization of production of goods, works and services, but also by the emergence of new (in some cases unique forms of inter-firm cooperation and interaction of economic agents in the real and financial sector of the economy. The concept of "digital economy" becomes the most important in economic research, and moreover - from a practical point of view, modern digitalization technologies in managing the activities of economic entities form new information and communication platforms for economic and scientific exchange. The penetration of digital technologies into life is one of the characteristic features of the future world. Not an exception is the agro-industrial sector, which is both strategically important for ensuring food security and has a high export potential. The article presents the concept of managing the development of agro-industrial clusters as self-organizing systems capable of integrating the activities of small and medium-sized businesses into the value-added chain based on modern information technologies. The obligatory and providing tools, mechanisms for implementing the concept, aimed at eliminating existing problems on the way of forming agro-industrial clusters, are disclosed.Methods: the agro-industrial cluster management model is developed using the methods of economic analysis and synthesis, and functional modelling.Results: conceptual model of cluster development management is presented to be used for the nascent clusters and the development of existing agro-industrial clusters.Conclusions and Relevance: as a result of the conducted research the reasons interfering development of cluster approach in the agroindustrial sector of economy are defined. Among them the main are: lack of

Stimulation of the sphenopalatine ganglion in intractable cluster headache

DEFF Research Database (Denmark)

Jürgens, Tim P; Schoenen, Jean; Rostgaard, Jørgen

2014-01-01

, but only very few randomized controlled studies exist in the field of neuromodulation for the treatment of drug-refractory headaches. Based on the prominent role of the cranial parasympathetic system in acute cluster headache attacks, high-frequency sphenopalatine ganglion (SPG) stimulation has been shown...... patients and the first commercially available CE-marked SPG neurostimulator system has been introduced for cluster headache, patient selection and care should be standardized to ensure maximal efficacy and safety. As only limited data have been published on SPG stimulation, standards of care based...

Clustering of near clusters versus cluster compactness

International Nuclear Information System (INIS)

Yu Gao; Yipeng Jing

1989-01-01

The clustering properties of near Zwicky clusters are studied by using the two-point angular correlation function. The angular correlation functions for compact and medium compact clusters, for open clusters, and for all near Zwicky clusters are estimated. The results show much stronger clustering for compact and medium compact clusters than for open clusters, and that open clusters have nearly the same clustering strength as galaxies. A detailed study of the compactness-dependence of correlation function strength is worth investigating. (author)

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.

Reduced-dimension power allocation over clustered channels in cognitive radios system under co-channel interference

KAUST Repository

Ben Ghorbel, Mahdi; Guenach, Mamoun; Alouini, Mohamed-Slim

2014-01-01

and secondary systems. Instead of optimizing the powers over all sub-carriers, the sub-carriers are grouped into clusters of sub-carriers, where the power of each sub-carrier is directly related to the power of the correspondent cluster. The power optimization

Availability analysis of supervised protective systems

International Nuclear Information System (INIS)

Kontoleon, N.; Kontoleon, J.M.; Chrysochoides, N.G.

1975-01-01

The behaviour in time of a nuclear reactor supervised protective system is modelled mathematically by a Markov process, continuous in time and with three discrete states. Failure and repair rates are assumed to be exponentially distributed. An analytical expression of system availability as a function of failure and repair rates as well as the inspection intervals and duration is derived. An optimization problem is then discussed in order to maximize system availability with respect to imposed cost constraints. Finally, an example of a supervised protective system with short inactive times is given, which may be found in many practical situations of modern protective systems. (author)

Mainshock-Aftershocks Clustering Detection in Volcanic Regions

Science.gov (United States)

Garza Giron, R.; Brodsky, E. E.; Prejean, S. G.

2017-12-01

Crustal earthquakes tend to break their general Poissonean process behavior by gathering into two main kinds of seismic bursts: swarms and mainshock-aftershocks sequences. The former is commonly related to volcanic or geothermal processes whereas the latter is a characteristic feature of tectonically driven seismicity. We explore the mainshock-aftershock clustering behavior of different active volcanic regions in Japan and its comparison to non-volcanic regions. We find that aftershock production in volcanoes shows mainshock-aftershocks clustering similar to what is observed in non-volcanic areas. The ratio of volanic areas that cluster in mainshock-aftershocks sequences vs the areas that do not is comparable to the ratio of non-volcanic regions that show clustering vs the ones that do not. Furthermore, the level of production of aftershocks for most volcanic areas where clustering is present seems to be of the same order of magnitude, or slightly higher, as the median of the non-volcanic regions. An interesting example of highly aftershock-productive volcanoes emerges from the 2000 Miyakejima dike intrusion. A big seismic cluster started to build up rapidly in the south-west flank of Miyakejima to later propagate to the north-west towards the Kozushima and Niijima volcanoes. In Miyakejima the seismicity showed a swarm-like signature with a constant earthquake rate, whereas Kozushima and Niijima both had expressions of highly productive mainshock-aftershocks sequences. These findings are surprising given the alternative mechanisms available in volcanic systems for releasing deviatoric strain. We speculate that aftershock behavior might hold a relationship with the rheological properties of the rocks of each system and with the capacity of a system to accumulate or release the internal pressures caused by magmatic or hydrothermal systems.

Star clusters and K2

Science.gov (United States)

Dotson, Jessie; Barentsen, Geert; Cody, Ann Marie

2018-01-01

The K2 survey has expanded the Kepler legacy by using the repurposed spacecraft to observe over 20 star clusters. The sample includes open and globular clusters at all ages, including very young (1-10 Myr, e.g. Taurus, Upper Sco, NGC 6530), moderately young (0.1-1 Gyr, e.g. M35, M44, Pleiades, Hyades), middle-aged (e.g. M67, Ruprecht 147, NGC 2158), and old globular clusters (e.g. M9, M19, Terzan 5). K2 observations of stellar clusters are exploring the rotation period-mass relationship to significantly lower masses than was previously possible, shedding light on the angular momentum budget and its dependence on mass and circumstellar disk properties, and illuminating the role of multiplicity in stellar angular momentum. Exoplanets discovered by K2 in stellar clusters provides planetary systems ripe for modeling given the extensive information available about their ages and environment. I will review the star clusters sampled by K2 across 16 fields so far, highlighting several characteristics, caveats, and unexplored uses of the public data set along the way. With fuel expected to run out in 2018, I will discuss the closing Campaigns, highlight the final target selection opportunities, and explain the data archive and TESS-compatible software tools the K2 mission intends to leave behind for posterity.

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.

Cluster-cluster clustering

International Nuclear Information System (INIS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

Quantization State of Baryonic Mass in Clusters of Galaxies

Directory of Open Access Journals (Sweden)

Potter F.

2007-01-01

Full Text Available The rotational velocity curves for clusters of galaxies cannot be explained by Newtonian gravitation using the baryonic mass nor does MOND succeed in reducing this discrepancy to acceptable differences. The dark matter hypothesis appears to offer a solution; however, non-baryonic dark matter has never been detected. As an alternative approach, quantum celestial mechanics (QCM predicts that galactic clusters are in quantization states determined solely by the total baryonic mass of the cluster and its total angular momentum. We find excellent agreement with QCM for ten galactic clusters, demonstrating that dark matter is not needed to explain the rotation velocities and providing further support to the hypothesis that all gravitationally bound systems have QCM quantization states.

Availability of periodically tested systems

International Nuclear Information System (INIS)

Signoret, J.P.

1979-01-01

There is at the present time a need in accurate models to asess the availability of periodically tested stand-by systems. This paper shows how to improve the well known 'saw-tooth curve' model in order to take into account various reliability parameters. A model is developed to assess the pointwise and the mean availabilities of periodically tested stand-by systems. Exact and approxination formulae are given. In addition, the model developed herein leads to optimize the test interval in order to minimize the mean unavailability. A safety diesel in a nuclear power plant is given as an example

Resistance–temperature relation and atom cluster estimation of In–Bi system melts

International Nuclear Information System (INIS)

Geng, Haoran; Wang Zhiming; Zhou Yongzhi; Li Cancan

2012-01-01

Highlights: ► A testing device was adopted to measure the electrical resistivity of In–Bi system melts. ► A basically linear relation exists between the resistivity and temperature of In x Bi 100−x melts in measured temperature range. ► Based on Novakovic's assumption, the content of InBi atomic cluster in In x Bi 100−x melt is estimated with ρ ≈ ρ InBi x InBi + ρ m (1 − x InBi ) equation. - Abstract: A testing device for the resistivity of high-temperature melt was adopted to measure the l resistivity of In–Bi system melts at different temperatures. It can be concluded from the analysis and calculation of the experimental results that the resistivity of In x Bi 100−x (x = 0–100) melt is in linear relationship with temperature within the experiment temperature range. The resistivity of the melt decreases with the increasing content of In. The fair consistency of resistivity of In–Bi system melt is found in the heating and cooling processes. On the basis of Novakovic's assumption, we approximately estimated the content of InBi atom clusters in In x Bi 100−x melts with the resistivity data by equation ρ ≈ ρ InBi x InBi + ρ m (1 − x InBi ). In the whole components interval, the content corresponds well with the mole fraction of InBi clusters calculated by Novakovic in the thermodynamic approach. The mole fraction of InBi type atom clusters in the melts reaches the maximum at the point of stoichiometric composition In 50 Bi 50 .

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

Science.gov (United States)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

International Nuclear Information System (INIS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-01-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system. (paper)

Merged consensus clustering to assess and improve class discovery with microarray data

Directory of Open Access Journals (Sweden)

Jarman Andrew P

2010-12-01

Full Text Available Abstract Background One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a large number of methods available to perform clustering, but it is often unclear which method is best suited to the data and how to quantify the quality of the classifications produced. Results Here we describe an R package containing methods to analyse the consistency of clustering results from any number of different clustering methods using resampling statistics. These methods allow the identification of the the best supported clusters and additionally rank cluster members by their fidelity within the cluster. These metrics allow us to compare the performance of different clustering algorithms under different experimental conditions and to select those that produce the most reliable clustering structures. We show the application of this method to simulated data, canonical gene expression experiments and our own novel analysis of genes involved in the specification of the peripheral nervous system in the fruitfly, Drosophila melanogaster. Conclusions Our package enables users to apply the merged consensus clustering methodology conveniently within the R programming environment, providing both analysis and graphical display functions for exploring clustering approaches. It extends the basic principle of consensus clustering by allowing the merging of results between different methods to provide an averaged clustering robustness. We show that this extension is useful in correcting for the tendency of clustering algorithms to treat outliers differently within datasets. The R package, clusterCons, is freely available at CRAN and sourceforge under the GNU public licence.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states.

Science.gov (United States)

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Modulated modularity clustering as an exploratory tool for functional genomic inference.

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Eric A Stone

2009-05-01

Full Text Available In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC, seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation.

Plasma Physics Calculations on a Parallel Macintosh Cluster

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Decyk, Viktor; Dauger, Dean; Kokelaar, Pieter

2000-03-01

We have constructed a parallel cluster consisting of 16 Apple Macintosh G3 computers running the MacOS, and achieved very good performance on numerically intensive, parallel plasma particle-in-cell simulations. A subset of the MPI message-passing library was implemented in Fortran77 and C. This library enabled us to port code, without modification, from other parallel processors to the Macintosh cluster. For large problems where message packets are large and relatively few in number, performance of 50-150 MFlops/node is possible, depending on the problem. This is fast enough that 3D calculations can be routinely done. Unlike Unix-based clusters, no special expertise in operating systems is required to build and run the cluster. Full details are available on our web site: http://exodus.physics.ucla.edu/appleseed/.

Information and methodological support of the cluster of children wellness recreation

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Ivanova Svetlana

2016-02-01

Full Text Available The article considers the instrument of transfer of pedagogical experience of the staff at children's health camps, which can be used as one of the components of the cluster to ensure the functioning of the health-educational system children's health camps. The transformation of the notion "cluster" from economic category in social and pedagogical is shown

Extracting Aggregation Free Energies of Mixed Clusters from Simulations of Small Systems: Application to Ionic Surfactant Micelles.

Science.gov (United States)

Zhang, X; Patel, L A; Beckwith, O; Schneider, R; Weeden, C J; Kindt, J T

2017-11-14

Micelle cluster distributions from molecular dynamics simulations of a solvent-free coarse-grained model of sodium octyl sulfate (SOS) were analyzed using an improved method to extract equilibrium association constants from small-system simulations containing one or two micelle clusters at equilibrium with free surfactants and counterions. The statistical-thermodynamic and mathematical foundations of this partition-enabled analysis of cluster histograms (PEACH) approach are presented. A dramatic reduction in computational time for analysis was achieved through a strategy similar to the selector variable method to circumvent the need for exhaustive enumeration of the possible partitions of surfactants and counterions into clusters. Using statistics from a set of small-system (up to 60 SOS molecules) simulations as input, equilibrium association constants for micelle clusters were obtained as a function of both number of surfactants and number of associated counterions through a global fitting procedure. The resulting free energies were able to accurately predict micelle size and charge distributions in a large (560 molecule) system. The evolution of micelle size and charge with SOS concentration as predicted by the PEACH-derived free energies and by a phenomenological four-parameter model fit, along with the sensitivity of these predictions to variations in cluster definitions, are analyzed and discussed.

Evolution of highly compact binary stellar systems in globular clusters

International Nuclear Information System (INIS)

Krolik, J.H.; Meiksin, A.; Joss, P.C.

1984-01-01

We have calculated the secular evolution of a highly compact binary stellar system, composed of a collapsed object and a low-mass secondary star, in the core of a globular cluster. The binary evolves under the combined influences of (i) gravitational radiation losses from the system, (ii) the evolution of the secondary star, (iii) the resultant gradual mass transfer, if any, from the secondary to the collapsed object, and (iv) occasional encounters with passing field stars. We calculate all these effects in detail, utilizing some simplifying approximations appropriate to low-mass secondaries. The times of encounters with field stars, and the initial parameter specifying those encounters, were chosen by use of a Monte Carlo technique; the subsequent gravitational interactions were calculated utilzing a three-body integrator, and the changes in the binary orbital parmeters were thereby determined. We carried out a total of 20 such evolutionary calculations for each of two cluster core densities (1 and 3 x 10 3 stars pc -3 ). Each calculation was continued until the binary was disrupted or until 2 x 10 10 yr had elapsed

A new Self-Adaptive disPatching System for local clusters

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Kan, Bowen; Shi, Jingyan; Lei, Xiaofeng

2015-12-01

The scheduler is one of the most important components of a high performance cluster. This paper introduces a self-adaptive dispatching system (SAPS) based on Torque[1] and Maui[2]. It promotes cluster resource utilization and improves the overall speed of tasks. It provides some extra functions for administrators and users. First of all, in order to allow the scheduling of GPUs, a GPU scheduling module based on Torque and Maui has been developed. Second, SAPS analyses the relationship between the number of queueing jobs and the idle job slots, and then tunes the priority of users’ jobs dynamically. This means more jobs run and fewer job slots are idle. Third, integrating with the monitoring function, SAPS excludes nodes in error states as detected by the monitor, and returns them to the cluster after the nodes have recovered. In addition, SAPS provides a series of function modules including a batch monitoring management module, a comprehensive scheduling accounting module and a real-time alarm module. The aim of SAPS is to enhance the reliability and stability of Torque and Maui. Currently, SAPS has been running stably on a local cluster at IHEP (Institute of High Energy Physics, Chinese Academy of Sciences), with more than 12,000 cpu cores and 50,000 jobs running each day. Monitoring has shown that resource utilization has been improved by more than 26%, and the management work for both administrator and users has been reduced greatly.

The high performance cluster computing system for BES offline data analysis

International Nuclear Information System (INIS)

Sun Yongzhao; Xu Dong; Zhang Shaoqiang; Yang Ting

2004-01-01

A high performance cluster computing system (EPCfarm) is introduced, which used for BES offline data analysis. The setup and the characteristics of the hardware and software of EPCfarm are described. The PBS, a queue management package, and the performance of EPCfarm is presented also. (authors)

Explicitly-correlated ring-coupled-cluster-doubles theory: Including exchange for computations on closed-shell systems

Energy Technology Data Exchange (ETDEWEB)

Hehn, Anna-Sophia; Holzer, Christof; Klopper, Wim, E-mail: klopper@kit.edu

2016-11-10

Highlights: • Ring-coupled-cluster-doubles approach now implemented with exchange terms. • Ring-coupled-cluster-doubles approach now implemented with F12 functions. • Szabo–Ostlund scheme (SO2) implemented for use in SAPT. • Fast convergence to the limit of a complete basis. • Implementation in the TURBOMOLE program system. - Abstract: Random-phase-approximation (RPA) methods have proven to be powerful tools in electronic-structure theory, being non-empirical, computationally efficient and broadly applicable to a variety of molecular systems including small-gap systems, transition-metal compounds and dispersion-dominated complexes. Applications are however hindered due to the slow basis-set convergence of the electron-correlation energy with the one-electron basis. As a remedy, we present approximate explicitly-correlated RPA approaches based on the ring-coupled-cluster-doubles formulation including exchange contributions. Test calculations demonstrate that the basis-set convergence of correlation energies is drastically accelerated through the explicitly-correlated approach, reaching 99% of the basis-set limit with triple-zeta basis sets. When implemented in close analogy to early work by Szabo and Ostlund [36], the new explicitly-correlated ring-coupled-cluster-doubles approach including exchange has the perspective to become a valuable tool in the framework of symmetry-adapted perturbation theory (SAPT) for the computation of dispersion energies of molecular complexes of weakly interacting closed-shell systems.

EVIDENCE FOR AN ACCRETION ORIGIN FOR THE OUTER HALO GLOBULAR CLUSTER SYSTEM OF M31

International Nuclear Information System (INIS)

Mackey, A. D.; Huxor, A. P.; Ferguson, A. M. N.; Irwin, M. J.; Chapman, S. C.; Tanvir, N. R.; McConnachie, A. W.; Ibata, R. A.; Lewis, G. F.

2010-01-01

We use a sample of newly discovered globular clusters from the Pan-Andromeda Archaeological Survey (PAndAS) in combination with previously cataloged objects to map the spatial distribution of globular clusters in the M31 halo. At projected radii beyond ∼30 kpc, where large coherent stellar streams are readily distinguished in the field, there is a striking correlation between these features and the positions of the globular clusters. Adopting a simple Monte Carlo approach, we test the significance of this association by computing the probability that it could be due to the chance alignment of globular clusters smoothly distributed in the M31 halo. We find that the likelihood of this possibility is low, below 1%, and conclude that the observed spatial coincidence between globular clusters and multiple tidal debris streams in the outer halo of M31 reflects a genuine physical association. Our results imply that the majority of the remote globular cluster system of M31 has been assembled as a consequence of the accretion of cluster-bearing satellite galaxies. This constitutes the most direct evidence to date that the outer halo globular cluster populations in some galaxies are largely accreted.

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.

An Application of Fuzzy Inference System by Clustering Subtractive Fuzzy Method for Estimating of Product Requirement

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Fajar Ibnu Tufeil

2009-06-01

Full Text Available Model fuzzy memiliki kemampuan untuk menjelaskan secara linguistik suatu sistem yang terlalu kompleks. Aturan-aturan dalam model fuzzy pada umumnya dibangun berdasarkan keahlian manusia dan pengetahuan heuristik dari sistem yang dimodelkan. Teknik ini selanjutnya dikembangkan menjadi teknik yang dapat mengidentifikasi aturan-aturan dari suatu basis data yang telah dikelompokkan berdasarkan persamaan strukturnya. Dalam hal ini metode pengelompokan fuzzy berfungsi untuk mencari kelompok-kelompok data. Informasi yang dihasilkan dari metode pengelompokan ini, yaitu informasi tentang pusat kelompok, digunakan untuk membentuk aturan-aturan dalam sistem penalaran fuzzy. Dalam skripsi ini dibahas mengenai penerapan fuzzy infereance system dengan metode pengelompokan fuzzy subtractive clustering, yaitu untuk membentuk sistem penalaran fuzzy dengan menggunakan model fuzzy Takagi-Sugeno orde satu. Selanjutnya, metode pengelompokan fuzzy subtractive clustering diterapkan dalam memodelkan masalah dibidang pemasaran, yaitu untuk memprediksi permintaan pasar terhadap suatu produk susu. Aplikasi ini dibangun menggunakan Borland Delphi 6.0. Dari hasil pengujian diperoleh tingkat error prediksi terkecil yaitu dengan Error Average 0.08%.

Exploitation of Clustering Techniques in Transactional Healthcare Data

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Naeem Ahmad Mahoto

2014-03-01

Full Text Available Healthcare service centres equipped with electronic health systems have improved their resources as well as treatment processes. The dynamic nature of healthcare data of each individual makes it complex and difficult for physicians to manually mediate them; therefore, automatic techniques are essential to manage the quality and standardization of treatment procedures. Exploratory data analysis, patternanalysis and grouping of data is managed using clustering techniques, which work as an unsupervised classification. A number of healthcare applications are developed that use several data mining techniques for classification, clustering and extracting useful information from healthcare data. The challenging issue in this domain is to select adequate data mining algorithm for optimal results. This paper exploits three different clustering algorithms: DBSCAN (Density-Based Clustering, agglomerative hierarchical and k-means in real transactional healthcare data of diabetic patients (taken as case study to analyse their performance in large and dispersed healthcare data. The best solution of cluster sets among the exploited algorithms is evaluated using clustering quality indexes and is selected to identify the possible subgroups of patients having similar treatment patterns

Clustering by reordering of similarity and Laplacian matrices: Application to galaxy clusters

Science.gov (United States)

Mahmoud, E.; Shoukry, A.; Takey, A.

2018-04-01

Similarity metrics, kernels and similarity-based algorithms have gained much attention due to their increasing applications in information retrieval, data mining, pattern recognition and machine learning. Similarity Graphs are often adopted as the underlying representation of similarity matrices and are at the origin of known clustering algorithms such as spectral clustering. Similarity matrices offer the advantage of working in object-object (two-dimensional) space where visualization of clusters similarities is available instead of object-features (multi-dimensional) space. In this paper, sparse ɛ-similarity graphs are constructed and decomposed into strong components using appropriate methods such as Dulmage-Mendelsohn permutation (DMperm) and/or Reverse Cuthill-McKee (RCM) algorithms. The obtained strong components correspond to groups (clusters) in the input (feature) space. Parameter ɛi is estimated locally, at each data point i from a corresponding narrow range of the number of nearest neighbors. Although more advanced clustering techniques are available, our method has the advantages of simplicity, better complexity and direct visualization of the clusters similarities in a two-dimensional space. Also, no prior information about the number of clusters is needed. We conducted our experiments on two and three dimensional, low and high-sized synthetic datasets as well as on an astronomical real-dataset. The results are verified graphically and analyzed using gap statistics over a range of neighbors to verify the robustness of the algorithm and the stability of the results. Combining the proposed algorithm with gap statistics provides a promising tool for solving clustering problems. An astronomical application is conducted for confirming the existence of 45 galaxy clusters around the X-ray positions of galaxy clusters in the redshift range [0.1..0.8]. We re-estimate the photometric redshifts of the identified galaxy clusters and obtain acceptable values

Linked cluster expansions for open quantum systems on a lattice

Science.gov (United States)

Biella, Alberto; Jin, Jiasen; Viyuela, Oscar; Ciuti, Cristiano; Fazio, Rosario; Rossini, Davide

2018-01-01

We propose a generalization of the linked-cluster expansions to study driven-dissipative quantum lattice models, directly accessing the thermodynamic limit of the system. Our method leads to the evaluation of the desired extensive property onto small connected clusters of a given size and topology. We first test this approach on the isotropic spin-1/2 Hamiltonian in two dimensions, where each spin is coupled to an independent environment that induces incoherent spin flips. Then we apply it to the study of an anisotropic model displaying a dissipative phase transition from a magnetically ordered to a disordered phase. By means of a Padé analysis on the series expansions for the average magnetization, we provide a viable route to locate the phase transition and to extrapolate the critical exponent for the magnetic susceptibility.

Infrared Multiple Photon Dissociation Spectroscopy Of Metal Cluster-Adducts

Science.gov (United States)

Cox, D. M.; Kaldor, A.; Zakin, M. R.

1987-01-01

Recent development of the laser vaporization technique combined with mass-selective detection has made possible new studies of the fundamental chemical and physical properties of unsupported transition metal clusters as a function of the number of constituent atoms. A variety of experimental techniques have been developed in our laboratory to measure ionization threshold energies, magnetic moments, and gas phase reactivity of clusters. However, studies have so far been unable to determine the cluster structure or the chemical state of chemisorbed species on gas phase clusters. The application of infrared multiple photon dissociation IRMPD to obtain the IR absorption properties of metal cluster-adsorbate species in a molecular beam is described here. Specifically using a high power, pulsed CO2 laser as the infrared source, the IRMPD spectrum for methanol chemisorbed on small iron clusters is measured as a function of the number of both iron atoms and methanols in the complex for different methanol isotopes. Both the feasibility and potential utility of IRMPD for characterizing metal cluster-adsorbate interactions are demonstrated. The method is generally applicable to any cluster or cluster-adsorbate system dependent only upon the availability of appropriate high power infrared sources.

Semi-supervised clustering methods.

Science.gov (United States)

Bair, Eric

2013-01-01

Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as "semi-supervised clustering" methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided.

Spatial clustering of pixels of a multispectral image

Science.gov (United States)

Conger, James Lynn

2014-08-19

A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

Galaxy CloudMan: delivering cloud compute clusters.

Science.gov (United States)

Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

2010-12-21

Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

Emergent and multiplicative effect in a cluster

Directory of Open Access Journals (Sweden)

I. V. Linev

2016-01-01

Full Text Available The concept “Cluster” of domestic and foreign literature traditionally is considered as administrative and organizational education. At the same time he represents the social and economic object created for life support of the person. The cluster is considered as system object. The main signs are defined and his life cycle is considered. Cluster self-organization takes place stages: growth of organizational weight and effects, market threats and restrictions interfering growth of organizational weight. Development of clusters requires the state support in various forms which is offered to be carried out at various stages depending on his type. The cluster is considered as the economic system possessing an emergent which dynamic aspect is the synergy, the receiving multiplicative effect causing an opportunity. The quantitative assessment of size of the listed effects represents rather complex challenge, at the same time there is a number of the factors which are with her in directly proportional dependence. The synergy which is present at a cluster allows to gain social and economic effect of his functioning by means of integration of effects of all structural elements bigger, than their simple sum. The emergent in a cluster causes increase of productivity at the expense of innovations in technological and organizational spheres and stimulations of the birth of new businesses. The multiplicative effect arising in a cluster provides incremental nature of economic results. It is possible to refer the following to the main economic results received from creation and development of clusters: decrease in transactional and transformational expenses and costs of formation and further use of infrastructure, economy of costs of introduction and development of the high and innovative technologies, optimization of logistic and information expenses, increase of business reputation and investment appeal.

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.

Macroeconomic Dimensions in the Clusterization Processes: Lithuanian Biomass Cluster Case

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Navickas Valentinas

2017-03-01

Full Text Available The Future production systems’ increasing significance will impose work, which maintains not a competitive, but a collaboration basis, with concentrated resources and expertise, which can help to reach the general purpose. One form of collaboration among medium-size business organizations is work in clusters. Clusterization as a phenomenon has been known from quite a long time, but it offers simple benefits to researches at micro and medium levels. The clusterization process evaluation in macroeconomic dimensions has been comparatively little investigated. Thereby, in this article, the clusterization processes is analysed by concentrating our attention on macroeconomic factor researches. The authors analyse clusterization’s influence on country’s macroeconomic growth; they apply a structure research methodology for clusterization’s macroeconomic influence evaluation and propose that clusterization processes benefit macroeconomic analysis. The theoretical model of clusterization processes was validated by referring to a biomass cluster case. Because biomass cluster case is a new phenomenon, currently there are no other scientific approaches to them. The authors’ accomplished researches show that clusterization allows the achievement of a large positive slip in macroeconomics, which proves to lead to a high value added to creation, a faster country economic growth, and social situation amelioration.

The Peculiarities of Cluster Formation in the Russian Nanotechnology Industry

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Kurchenkov Vladimir Viktorovich

2015-05-01

Full Text Available The innovative development of the Russian economy in modern conditions should be based on the development of advanced nanotechnology. The formation of the nanotechnology industry in Russia requires optimal organization, the development of networking, the search for new forms of integrating the primary and secondary productions. The cluster organization in nanotech industry is based on high-tech production and has a number of advantages: uncertainty elimination, restriction of the competition by monopolization of supply with raw materials and semi-finished products, improvement of quality and decrease in expenses. The main forms of interaction of the enterprises and organizations which are a part of a nanoindustrial cluster are allocated. The article describes the peculiarities of the Russian nanoidustry formation, determines the significance of the cluster policy in this sphere. The author develops the criteria for identifying the nanoclusters on the basis of the basic nanotechnology and the nomenclature of final product. The author also proposes the approach to the analysis of cluster interaction and determines the boundaries of the cluster based on the difference between system and quasisystem cluster interaction. In this regard it is necessary to consider possibilities of the analysis of both system, and quasisystem interaction of the main participants of a nanoindustrial cluster.

Relationship between damage clustering and mortality in systemic lupus erythematosus in early and late stages of the disease: cluster analyses in a large cohort from the Spanish Society of Rheumatology Lupus Registry.

Science.gov (United States)

Pego-Reigosa, José María; Lois-Iglesias, Ana; Rúa-Figueroa, Íñigo; Galindo, María; Calvo-Alén, Jaime; de Uña-Álvarez, Jacobo; Balboa-Barreiro, Vanessa; Ibáñez Ruan, Jesús; Olivé, Alejandro; Rodríguez-Gómez, Manuel; Fernández Nebro, Antonio; Andrés, Mariano; Erausquin, Celia; Tomero, Eva; Horcada Rubio, Loreto; Uriarte Isacelaya, Esther; Freire, Mercedes; Montilla, Carlos; Sánchez-Atrio, Ana I; Santos-Soler, Gregorio; Zea, Antonio; Díez, Elvira; Narváez, Javier; Blanco-Alonso, Ricardo; Silva-Fernández, Lucía; Ruiz-Lucea, María Esther; Fernández-Castro, Mónica; Hernández-Beriain, José Ángel; Gantes-Mora, Marian; Hernández-Cruz, Blanca; Pérez-Venegas, José; Pecondón-Español, Ángela; Marras Fernández-Cid, Carlos; Ibáñez-Barcelo, Mónica; Bonilla, Gema; Torrente-Segarra, Vicenç; Castellví, Iván; Alegre, Juan José; Calvet, Joan; Marenco de la Fuente, José Luis; Raya, Enrique; Vázquez-Rodríguez, Tomás Ramón; Quevedo-Vila, Víctor; Muñoz-Fernández, Santiago; Otón, Teresa; Rahman, Anisur; López-Longo, Francisco Javier

2016-07-01

To identify patterns (clusters) of damage manifestations within a large cohort of SLE patients and evaluate the potential association of these clusters with a higher risk of mortality. This is a multicentre, descriptive, cross-sectional study of a cohort of 3656 SLE patients from the Spanish Society of Rheumatology Lupus Registry. Organ damage was ascertained using the Systemic Lupus International Collaborating Clinics Damage Index. Using cluster analysis, groups of patients with similar patterns of damage manifestations were identified. Then, overall clusters were compared as well as the subgroup of patients within every cluster with disease duration shorter than 5 years. Three damage clusters were identified. Cluster 1 (80.6% of patients) presented a lower amount of individuals with damage (23.2 vs 100% in clusters 2 and 3, P Cluster 2 (11.4% of patients) was characterized by musculoskeletal damage in all patients. Cluster 3 (8.0% of patients) was the only group with cardiovascular damage, and this was present in all patients. The overall mortality rate of patients in clusters 2 and 3 was higher than that in cluster 1 (P clusters. Both in early and late stages of the disease, there was a significant association of these clusters with an increased risk of mortality. Physicians should pay special attention to the early prevention of damage in these two systems. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Self-consistent cluster theory for systems with off-diagonal disorder

International Nuclear Information System (INIS)

Kaplan, T.; Leath, P.L.; Gray, L.J.; Diehl, H.W.

1980-01-01

A self-consistent cluster theory for elementary excitations in systems with diagonal, off-diagonal, and environmental disorder is presented. The theory is developed in augmented space where the configurational average over the disorder is replaced by a ground-state matrix element in a translationally invariant system. The analyticity of the resulting approximate Green's function is proved. Numerical results for the self-consistent single-site and pair approximations are presented for the vibrational and electronic properties of disordered linear chains with diagonal, off-diagonal, and environmental disorder

Web service availability-impact of error recovery and traffic model

International Nuclear Information System (INIS)

Martinello, Magnos; Kaa-hat niche, Mohamed; Kanoun, Karama

2005-01-01

Internet is often used for transaction based applications such as online banking, stock trading and shopping, where the service interruption or outages are unacceptable. Therefore, it is important for designers of such applications to analyze how hardware, software and performance related failures affect the quality of service delivered to the users. This paper presents analytical models for evaluating the service availability of web cluster architectures. A composite performance and availability modeling approach is defined considering various causes of service unavailability. In particular, web cluster systems are modeled taking into account: two error recovery strategies (client transparent and non-client-transparent) as well as two traffic models (Poisson and modulated Poisson). Sensitivity analysis results are presented to show their impact on the web service availability. The obtained results provide useful guidelines to web designers

New Heterogeneous Clustering Protocol for Prolonging Wireless Sensor Networks Lifetime

Directory of Open Access Journals (Sweden)

Md. Golam Rashed

2014-06-01

Full Text Available Clustering in wireless sensor networks is one of the crucial methods for increasing of network lifetime. The network characteristics of existing classical clustering protocols for wireless sensor network are homogeneous. Clustering protocols fail to maintain the stability of the system, especially when nodes are heterogeneous. We have seen that the behavior of Heterogeneous-Hierarchical Energy Aware Routing Protocol (H-HEARP becomes very unstable once the first node dies, especially in the presence of node heterogeneity. In this paper we assume a new clustering protocol whose network characteristics is heterogeneous for prolonging of network lifetime. The computer simulation results demonstrate that the proposed clustering algorithm outperforms than other clustering algorithms in terms of the time interval before the death of the first node (we refer to as stability period. The simulation results also show the high performance of the proposed clustering algorithm for higher values of extra energy brought by more powerful nodes.

Exploring biological network structure with clustered random networks

Directory of Open Access Journals (Sweden)

Bansal Shweta

2009-12-01

Full Text Available Abstract Background Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions and the extent of clustering (the tendency for a set of three nodes to be interconnected are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics. Results Here we develop and implement a new Markov chain simulation algorithm to generate simple, connected random graphs that have a specified degree sequence and level of clustering, but are random in all other respects. The implementation of the algorithm (ClustRNet: Clustered Random Networks provides the generation of random graphs optimized according to a local or global, and relative or absolute measure of clustering. We compare our algorithm to other similar methods and show that ours more successfully produces desired network characteristics. Finding appropriate null models is crucial in bioinformatics research, and is often difficult, particularly for biological networks. As we demonstrate, the networks generated by ClustRNet can serve as random controls when investigating the impacts of complex network features beyond the byproduct of degree and clustering in empirical networks. Conclusion ClustRNet generates ensembles of graphs of specified edge structure and clustering. These graphs allow for systematic study of the impacts of connectivity and redundancies on network function and dynamics. This process is a key step in

Assessing Centralized Governance in a Software Cluster

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João Paulo Leonardo Oliveira

2014-04-01

Full Text Available Increasing attention has been paid to the creation of spatially concentrated environments (industrial agglomerations or clusters that aim at fostering firm-level competitiveness. However, while much has been said about clusters in general, less attention has been paid to structural governance within these agglomerations. This paper discusses the economic dynamics of clusters in the presence of centralized formal body of governance regarding internal and external relationships. We have carried out a case study of the key players in the software industry of Ribeirão Preto, which relies on an institutional arrangement called PISO. PISO arises as an economic institution in the context of Ribeirão Preto’s software cluster that structures collective action within the system, interfering in the regional policymaking processes and fostering an environment that improves overall capabilities that allow firms to take full advantage of the externalities in order to create and consolidate competitive local advantages.

CLOSE STELLAR ENCOUNTERS IN YOUNG, SUBSTRUCTURED, DISSOLVING STAR CLUSTERS: STATISTICS AND EFFECTS ON PLANETARY SYSTEMS

International Nuclear Information System (INIS)

Craig, Jonathan; Krumholz, Mark R.

2013-01-01

Both simulations and observations indicate that stars form in filamentary, hierarchically clustered associations, most of which disperse into their galactic field once feedback destroys their parent clouds. However, during their early evolution in these substructured environments, stars can undergo close encounters with one another that might have significant impacts on their protoplanetary disks or young planetary systems. We perform N-body simulations of the early evolution of dissolving, substructured clusters with a wide range of properties, with the aim of quantifying the expected number and orbital element distributions of encounters as a function of cluster properties. We show that the presence of substructure both boosts the encounter rate and modifies the distribution of encounter velocities compared to what would be expected for a dynamically relaxed cluster. However, the boost only lasts for a dynamical time, and as a result the overall number of encounters expected remains low enough that gravitational stripping is unlikely to be a significant effect for the vast majority of star-forming environments in the Galaxy. We briefly discuss the implications of this result for models of the origin of the solar system, and of free-floating planets. We also provide tabulated encounter rates and orbital element distributions suitable for inclusion in population synthesis models of planet formation in a clustered environment.

CLOSE STELLAR ENCOUNTERS IN YOUNG, SUBSTRUCTURED, DISSOLVING STAR CLUSTERS: STATISTICS AND EFFECTS ON PLANETARY SYSTEMS

Energy Technology Data Exchange (ETDEWEB)

Craig, Jonathan; Krumholz, Mark R., E-mail: krumholz@ucolick.org [Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States)

2013-06-01

Both simulations and observations indicate that stars form in filamentary, hierarchically clustered associations, most of which disperse into their galactic field once feedback destroys their parent clouds. However, during their early evolution in these substructured environments, stars can undergo close encounters with one another that might have significant impacts on their protoplanetary disks or young planetary systems. We perform N-body simulations of the early evolution of dissolving, substructured clusters with a wide range of properties, with the aim of quantifying the expected number and orbital element distributions of encounters as a function of cluster properties. We show that the presence of substructure both boosts the encounter rate and modifies the distribution of encounter velocities compared to what would be expected for a dynamically relaxed cluster. However, the boost only lasts for a dynamical time, and as a result the overall number of encounters expected remains low enough that gravitational stripping is unlikely to be a significant effect for the vast majority of star-forming environments in the Galaxy. We briefly discuss the implications of this result for models of the origin of the solar system, and of free-floating planets. We also provide tabulated encounter rates and orbital element distributions suitable for inclusion in population synthesis models of planet formation in a clustered environment.

Close Stellar Encounters in Young, Substructured, Dissolving Star Clusters: Statistics and Effects on Planetary Systems

Science.gov (United States)

Craig, Jonathan; Krumholz, Mark R.

2013-06-01

Both simulations and observations indicate that stars form in filamentary, hierarchically clustered associations, most of which disperse into their galactic field once feedback destroys their parent clouds. However, during their early evolution in these substructured environments, stars can undergo close encounters with one another that might have significant impacts on their protoplanetary disks or young planetary systems. We perform N-body simulations of the early evolution of dissolving, substructured clusters with a wide range of properties, with the aim of quantifying the expected number and orbital element distributions of encounters as a function of cluster properties. We show that the presence of substructure both boosts the encounter rate and modifies the distribution of encounter velocities compared to what would be expected for a dynamically relaxed cluster. However, the boost only lasts for a dynamical time, and as a result the overall number of encounters expected remains low enough that gravitational stripping is unlikely to be a significant effect for the vast majority of star-forming environments in the Galaxy. We briefly discuss the implications of this result for models of the origin of the solar system, and of free-floating planets. We also provide tabulated encounter rates and orbital element distributions suitable for inclusion in population synthesis models of planet formation in a clustered environment.

Determining characteristic principal clusters in the “cluster-plus-glue-atom” model

International Nuclear Information System (INIS)

Du, Jinglian; Wen, Bin; 2NeT Lab, Wilfrid Laurier University, Waterloo, 75 University Ave West, Ontario N2L 3C5 (Canada))" data-affiliation=" (M2NeT Lab, Wilfrid Laurier University, Waterloo, 75 University Ave West, Ontario N2L 3C5 (Canada))" >Melnik, Roderick; Kawazoe, Yoshiyuki

2014-01-01

The “cluster-plus-glue-atom” model can easily describe the structure of complex metallic alloy phases. However, the biggest obstacle limiting the application of this model is that it is difficult to determine the characteristic principal cluster. In the case when interatomic force constants (IFCs) inside the cluster lead to stronger interaction than the interaction between the clusters, a new rule for determining the characteristic principal cluster in the “cluster-plus-glue-atom” model has been proposed on the basis of IFCs. To verify this new rule, the alloy phases in Cu–Zr and Al–Ni–Zr systems have been tested, and our results indicate that the present new rule for determining characteristic principal clusters is effective and reliable

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

Science.gov (United States)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Density functional study of structural and electronic properties of bimetallic silver-gold clusters: Comparison with pure gold and silver clusters

Science.gov (United States)

Bonacic-Koutecky, Vlasta; Burda, Jaroslav; Mitric, Roland; Ge, Maofa; Zampella, Giuseppe; Fantucci, Piercarlo

2002-08-01

Bimetallic silver-gold clusters offer an excellent opportunity to study changes in metallic versus "ionic" properties involving charge transfer as a function of the size and the composition, particularly when compared to pure silver and gold clusters. We have determined structures, ionization potentials, and vertical detachment energies for neutral and charged bimetallic AgmAun 3[less-than-or-equal](m+n)[less-than-or-equal]5 clusters. Calculated VDE values compare well with available experimental data. In the stable structures of these clusters Au atoms assume positions which favor the charge transfer from Ag atoms. Heteronuclear bonding is usually preferred to homonuclear bonding in clusters with equal numbers of hetero atoms. In fact, stable structures of neutral Ag2Au2, Ag3Au3, and Ag4Au4 clusters are characterized by the maximum number of hetero bonds and peripheral positions of Au atoms. Bimetallic tetramer as well as hexamer are planar and have common structural properties with corresponding one-component systems, while Ag4Au4 and Ag8 have 3D forms in contrast to Au8 which assumes planar structure. At the density functional level of theory we have shown that this is due to participation of d electrons in bonding of pure Aun clusters while s electrons dominate bonding in pure Agm as well as in bimetallic clusters. In fact, Aun clusters remain planar for larger sizes than Agm and AgnAun clusters. Segregation between two components in bimetallic systems is not favorable, as shown in the example of Ag5Au5 cluster. We have found that the structures of bimetallic clusters with 20 atoms Ag10Au10 and Ag12Au8 are characterized by negatively charged Au subunits embedded in Ag environment. In the latter case, the shape of Au8 is related to a pentagonal bipyramid capped by one atom and contains three exposed negatively charged Au atoms. They might be suitable for activating reactions relevant to catalysis. According to our findings the charge transfer in bimetallic

Instrument air system - Aging impact on system availability

International Nuclear Information System (INIS)

Villaran, M.; Subudhi, M.

1989-01-01

As part of ongoing efforts to understand and manage the effects of aging in nuclear power plants, an aging assessment was performed for the Instrument Air (IA) system, a system that has been the subject of much scrutiny in recent years. Despite its non-safety classification, instrument air has been a factor in a number of potentially serious events. This report presents the results of the assessment and discusses the impact of instrument air system aging on system availability and plant safety. This work was performed for the US Nuclear Regulatory Commission (NRC) as part of the Nuclear Plant Aging Research (NPAR) program. To perform the complex task of analyzing an entire system, the Aging and Life Extension Assessment Program (ALEAP) System Level Plan was developed by Brookhaven National Laboratory and applied successfully in previous system aging studies. The work presented herein was performed using two parallel work paths, as described in the ALEAP plant. One path used deterministic techniques to assess the impact of aging on compressed air system performance, while the second path used probabilistic methods. Results from both paths then were used to characterize aging in the instrument air system. Some conclusions from this work are: compressors, air system valves, and air dryers were found to make up the majority of failures; the effectiveness and quantity of preventive maintenance devoted to a component significantly affected the amount of failures experienced; review of compressed air system designs and studies using a PRA-based system model revealed that the redundancy of key components (compressors, dryers, IA/SA crossconnect valve) was an important factor in system availability; total loss of air events are uncommon

Cluster as a Service for Disaster Recovery in Intercloud Systems: Design and Modeling

OpenAIRE

Mohammad Ali Khoshkholghi

2014-01-01

Nowadays, all modern IT technologies aim to create dynamic and flexible environments. For this reason, InterCloud has been designed to provide a vast and flexible virtualized environment in which many clouds can interact with one another in a dynamic way. Disaster recovery is one of the main applications of InterCloud which can be supported by Cluster as a Service. However, the previous studies addressed disaster recovery and Cluster as a Service separately. In addition, system backup and dis...

Dynamical processes in space: Cluster results

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C. P. Escoubet

2013-06-01

Full Text Available After 12 years of operations, the Cluster mission continues to successfully fulfil its scientific objectives. The main goal of the Cluster mission, comprised of four identical spacecraft, is to study in three dimensions small-scale plasma structures in key plasma regions of the Earth's environment: solar wind and bow shock, magnetopause, polar cusps, magnetotail, plasmasphere and auroral zone. During the course of the mission, the relative distance between the four spacecraft has been varied from 20 km to 36 000 km to study the scientific regions of interest at different scales. Since summer 2005, new multi-scale constellations have been implemented, wherein three spacecraft (C1, C2, C3 are separated by 10 000 km, while the fourth one (C4 is at a variable distance ranging between 20 km and 10 000 km from C3. Recent observations were conducted in the auroral acceleration region with the spacecraft separated by 1000s km. We present highlights of the results obtained during the last 12 years on collisionless shocks, magnetopause waves, magnetotail dynamics, plasmaspheric structures, and the auroral acceleration region. In addition, we highlight Cluster results on understanding the impact of Coronal Mass Ejections (CME on the Earth environment. We will also present Cluster data accessibility through the Cluster Science Data System (CSDS, and the Cluster Active Archive (CAA, which was implemented to provide a permanent and public archive of high resolution Cluster data from all instruments.

Application of Fuzzy Clustering in Modeling of a Water Hydraulics System

DEFF Research Database (Denmark)

Zhou, Jianjun; Kroszynski, Uri

2000-01-01

This article presents a case study of applying fuzzy modeling techniques for a water hydraulics system. The obtained model is intended to provide a basis for model-based control of the system. Fuzzy clustering is used for classifying measured input-output data points into partitions. The fuzzy...... model is extracted from the obtained partitions. The identified model has been evaluated by comparing measurements with simulation results. The evaluation shows that the identified model is capable of describing the system dynamics over a reasonably wide frequency range....

Hubble Space Telescope Observations of cD Galaxies and Their Globular Cluster Systems

Science.gov (United States)

Jordán, Andrés; Côté, Patrick; West, Michael J.; Marzke, Ronald O.; Minniti, Dante; Rejkuba, Marina

2004-01-01

We have used WFPC2 on the Hubble Space Telescope (HST) to obtain F450W and F814W images of four cD galaxies (NGC 541 in Abell 194, NGC 2832 in Abell 779, NGC 4839 in Abell 1656, and NGC 7768 in Abell 2666) in the range 5400 km s-1cluster (GC) systems reveals no anomalies in terms of specific frequencies, metallicity gradients, average metallicities, or the metallicity offset between the globular clusters and the host galaxy. We show that the latter offset appears roughly constant at Δ[Fe/H]~0.8 dex for early-type galaxies spanning a luminosity range of roughly 4 orders of magnitude. We combine the globular cluster metallicity distributions with an empirical technique described in a series of earlier papers to investigate the form of the protogalactic mass spectrum in these cD galaxies. We find that the observed GC metallicity distributions are consistent with those expected if cD galaxies form through the cannibalism of numerous galaxies and protogalactic fragments that formed their stars and globular clusters before capture and disruption. However, the properties of their GC systems suggest that dynamical friction is not the primary mechanism by which these galaxies are assembled. We argue that cD's instead form rapidly, via hierarchical merging, prior to cluster virialization. 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 Based in part on observations obtained at the European Southern Observatory, for VLT program 68.D-0130(A).

Adaptive Scaling of Cluster Boundaries for Large-Scale Social Media Data Clustering.

Science.gov (United States)

Meng, Lei; Tan, Ah-Hwee; Wunsch, Donald C

2016-12-01

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the clustering mechanism of Fuzzy ART, and discover the vigilance region (VR) that essentially determines how a cluster in the Fuzzy ART system recognizes similar patterns in the feature space. The VR gives an intrinsic interpretation of the clustering mechanism and limitations of Fuzzy ART. Second, we introduce the idea of allowing different clusters in the Fuzzy ART system to have different vigilance levels in order to meet the diverse nature of the pattern distribution of social media data. To this end, we propose three vigilance adaptation methods, namely, the activation maximization (AM) rule, the confliction minimization (CM) rule, and the hybrid integration (HI) rule. With an initial vigilance value, the resulting clustering algorithms, namely, the AM-ART, CM-ART, and HI-ART, can automatically adapt the vigilance values of all clusters during the learning epochs in order to produce better cluster boundaries. Experiments on four social media data sets show that AM-ART, CM-ART, and HI-ART are more robust than Fuzzy ART to the initial vigilance value, and they usually achieve better or comparable performance and much faster speed than the state-of-the-art clustering algorithms that also do not require a predefined number of clusters.

FLOCK cluster analysis of mast cell event clustering by high-sensitivity flow cytometry predicts systemic mastocytosis.

Science.gov (United States)

Dorfman, David M; LaPlante, Charlotte D; Pozdnyakova, Olga; Li, Betty

2015-11-01

In our high-sensitivity flow cytometric approach for systemic mastocytosis (SM), we identified mast cell event clustering as a new diagnostic criterion for the disease. To objectively characterize mast cell gated event distributions, we performed cluster analysis using FLOCK, a computational approach to identify cell subsets in multidimensional flow cytometry data in an unbiased, automated fashion. FLOCK identified discrete mast cell populations in most cases of SM (56/75 [75%]) but only a minority of non-SM cases (17/124 [14%]). FLOCK-identified mast cell populations accounted for 2.46% of total cells on average in SM cases and 0.09% of total cells on average in non-SM cases (P < .0001) and were predictive of SM, with a sensitivity of 75%, a specificity of 86%, a positive predictive value of 76%, and a negative predictive value of 85%. FLOCK analysis provides useful diagnostic information for evaluating patients with suspected SM, and may be useful for the analysis of other hematopoietic neoplasms. Copyright© by the American Society for Clinical Pathology.

A Collaboration Service Model for a Global Port Cluster

Directory of Open Access Journals (Sweden)

Keith K.T. Toh

2010-03-01

Full Text Available The importance of port clusters to a global city may be viewed from a number of perspectives. The development of port clusters and economies of agglomeration and their contribution to a regional economy is underpinned by information and physical infrastructure that facilitates collaboration between business entities within the cluster. The maturity of technologies providing portals, web and middleware services provides an opportunity to push the boundaries of contemporary service reference models and service catalogues to what the authors propose to be "collaboration services". Servicing port clusters, portal engineers of the future must consider collaboration services to benefit a region. Particularly, service orchestration through a "public user portal" must gain better utilisation of publically owned infrastructure, to share knowledge and collaborate among organisations through information systems.

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...

The globular cluster system of NGC 1316. II. The extraordinary object SH2

Science.gov (United States)

Richtler, T.; Kumar, B.; Bassino, L. P.; Dirsch, B.; Romanowsky, A. J.

2012-07-01

Context. SH2 has been described as an isolated HII-region, located about 6.5' south of the nucleus of NGC 1316 (Fornax A), a merger remnant in the the outskirts of the Fornax cluster of galaxies. Aims: We give a first, preliminary description of the stellar content and environment of this remarkable object. Methods: We used photometric data in the Washington system and HST photometry from the Hubble Legacy Archive for a morphological description and preliminary aperture photometry. Low-resolution spectroscopy provides radial velocities of the brightest star cluster in SH2 and a nearby intermediate-age cluster. Results: SH2 is not a normal HII-region, ionized by very young stars. It contains a multitude of star clusters with ages of approximately 108 yr. A ring-like morphology is striking. SH2 seems to be connected to an intermediate-age massive globular cluster with a similar radial velocity, which itself is the main object of a group of fainter clusters. Metallicity estimates from emission lines remain ambiguous. Conclusions: The present data do not yet allow firm conclusions about the nature or origin of SH2. It might be a dwarf galaxy that has experienced a burst of extremely clustered star formation. We may witness how globular clusters are donated to a parent galaxy. Based on observations taken at the European Southern Observatory, Cerro Paranal, Chile, under the programmes 082.B-0680, on observations taken at the Interamerican Observatory, Cerro Tololo, Chile. Furthermore based on observations made with the NASA/ESA Hubble Space Telescope (HST, PI: A. Sandage, Prop.ID: 7504), and obtained from the Hubble Legacy Archive, which is a collaboration between the Space Telescope Science Institute (STScI/NASA), the Space Telescope European Coordinating Facility (ST-ECF/ESA) and the Canadian Astronomy Data Centre (CADC/NRC/CSA).

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

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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.

Cluster expansion for ground states of local Hamiltonians

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Alvise Bastianello

2016-08-01

Full Text Available A central problem in many-body quantum physics is the determination of the ground state of a thermodynamically large physical system. We construct a cluster expansion for ground states of local Hamiltonians, which naturally incorporates physical requirements inherited by locality as conditions on its cluster amplitudes. Applying a diagrammatic technique we derive the relation of these amplitudes to thermodynamic quantities and local observables. Moreover we derive a set of functional equations that determine the cluster amplitudes for a general Hamiltonian, verify the consistency with perturbation theory and discuss non-perturbative approaches. Lastly we verify the persistence of locality features of the cluster expansion under unitary evolution with a local Hamiltonian and provide applications to out-of-equilibrium problems: a simplified proof of equilibration to the GGE and a cumulant expansion for the statistics of work, for an interacting-to-free quantum quench.

Probing cluster structures through sub-barrier transfer reactions

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Rafferty D. C.

2016-01-01

Full Text Available Multinucleon transfer probabilities and excitation energy distributions have been measured in 16,18O, 19F + 208Pb at energies between 90% - 100% of the Coulomb barrier. A strong 2p2n enhancement is observed for all reactions, though most spectacularly in the 18O induced reaction. Results are interpreted in terms of the Semiclassical model, which seems to suggest α-cluster transfer in all studied systems. The relation to cluster-states in the projectile is discussed, with the experimental results consistent with previous structure studies. Dissipation of energy in the collisions of 18O is compared between different reaction modes, with cluster transfer associated with dissipation over a large number of internal states. Cluster transfer is shown to be a long range dissipation mechanism, which will inform the development of future models to treat these dynamic processes in reactions.

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.

Interfacial spin cluster effects in exchange bias systems

Energy Technology Data Exchange (ETDEWEB)

Carpenter, R., E-mail: rc548@york.ac.uk; Vallejo-Fernandez, G.; O' Grady, K. [Department of Physics, The University of York, York YO10 5DD (United Kingdom)

2014-05-07

In this work, the effect of exchange bias on the hysteresis loop of CoFe is observed. The evolution of the coercivities and the shift of the hysteresis loop during the annealing process has been measured for films deposited on NiCr and Cu seed layers. Through comparison of the as deposited and field annealed loops, it is clear that for an exchange biased material, the two coercivities are due to different reversal processes. This behaviour is attributed to spin clusters at the ferromagnet/antiferromagnet interface, which behave in a similar manner to a fine particle system.

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.

Symmetries of cluster configurations

International Nuclear Information System (INIS)

Kramer, P.

1975-01-01

A deeper understanding of clustering phenomena in nuclei must encompass at least two interrelated aspects of the subject: (A) Given a system of A nucleons with two-body interactions, what are the relevant and persistent modes of clustering involved. What is the nature of the correlated nucleon groups which form the clusters, and what is their mutual interaction. (B) Given the cluster modes and their interaction, what systematic patterns of nuclear structure and reactions emerge from it. Are there, for example, families of states which share the same ''cluster parents''. Which cluster modes are compatible or exclude each other. What quantum numbers could characterize cluster configurations. There is no doubt that we can learn a good deal from the experimentalists who have discovered many of the features relevant to aspect (B). Symmetries specific to cluster configurations which can throw some light on both aspects of clustering are discussed

Atomic size effect on the formation of ionized cluster beam epitaxy in Lennard-Jones systems

International Nuclear Information System (INIS)

Hsieh Horngming; Averback, R.S.

1991-01-01

Ionized cluster beam deposition is studied by molecular dynamics simulations in which the atomic size of incident cluster atoms is different from the size of substrate atoms. Lennard-Jones interatomic potentials are used for the two-component system. The results provide the morphologies of the overlayers for various atomic sizes and are compared to simulation results of molecular beam epitaxy. (orig.)

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

Directory of Open Access Journals (Sweden)

Ujjwal Maulik

Full Text Available Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request.sarkar@labri.fr.

The globular cluster systems of 54 Coma ultra-diffuse galaxies: statistical constraints from HST data

Science.gov (United States)

Amorisco, N. C.; Monachesi, A.; Agnello, A.; White, S. D. M.

2018-04-01

We use data from the HST Coma Cluster Treasury program to assess the richness of the globular cluster systems (GCSs) of 54 Coma ultra-diffuse galaxies (UDGs), 18 of which have a half-light radius exceeding 1.5 kpc. We use a hierarchical Bayesian method tested on a large number of mock data sets to account consistently for the high and spatially varying background counts in Coma. These include both background galaxies and intra-cluster globular clusters (ICGCs), which are disentangled from the population of member globular clusters (GCs) in a probabilistic fashion. We find no candidate for a GCS as rich as that of the Milky Way, our sample has GCSs typical of dwarf galaxies. For the standard relation between GCS richness and halo mass, 33 galaxies have a virial mass Mvir ≤ 1011 M⊙ at 90 per cent probability. Only three have Mvir > 1011 M⊙ with the same confidence. The mean colour and spread in colour of the UDG GCs are indistinguishable from those of the abundant population of ICGCs. The majority of UDGs in our sample are consistent with the relation between stellar mass and GC richness of `normal' dwarf galaxies. Nine systems, however, display GCSs that are richer by a factor of 3 or more (at 90 per cent probability). Six of these have sizes ≲1.4 kpc. Our results imply that the physical mechanisms responsible for the extended size of the UDGs and for the enhanced GC richness of some cluster dwarfs are at most weakly correlated.

Distant Galaxy Clusters Hosting Extreme Central Galaxies

Science.gov (United States)

McDonald, Michael

2014-09-01

The recently-discovered Phoenix cluster harbors the most star-forming central cluster galaxy of any cluster in the known Universe, by nearly a factor of 10. This extreme system appears to be fulfilling early cooling flow predictions, although the lack of similar systems makes any interpretation difficult. In an attempt to find other "Phoenix-like" clusters, we have cross-correlated archival all-sky surveys (in which Phoenix was detected) and isolated 4 similarly-extreme systems which are also coincident in position and redshift with an overdensity of red galaxies. We propose here to obtain Chandra observations of these extreme, Phoenix-like systems, in order to confirm them as relaxed, rapidly-cooling galaxy clusters.

Dynamical evolution of galaxies in clusters

International Nuclear Information System (INIS)

Ostriker, J.P.

1977-01-01

In addition to the processes involved in the evolution of star clusters, there are three kinds of processes that are peculiar to, or far more important in, galaxy clusters than in star clusters: galaxy interactions with gas, high-velocity tidal interactions, and accretion and cannibalism. The latter is discussed at some length; analytical calculations for the apparent luminosity evolution of the first brightest galaxy and the apparent luminosity evolution of M 12 are described, along with the numerical simulation of cluster evolution. It appears that many of the notable features of centrally condensed clusters of galaxies, particularly the presence of very luminous but low-surface-brightness central cD systems, can be understood in terms of a straightforward dynamical theory of galactic cannibalism. It is possible to maintain the hypothesis that dynamical evolution gradually transforms Bautz--Morgan III clusters to type II systems or type I systems. 36 references, 5 figures

CLUSTERS AS A MODEL OF ECONOMIC DEVELOPMENT OF SERBIA

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Marko Laketa

2013-12-01

Full Text Available Insufficient competitiveness of small and medium enterprises in Serbia can be significantly improved by a system of business associations through clusters, business incubators and technology parks. This connection contributes to the growth and development of not only the cluster members, but has a regional and national dimension as well because without it there is no significant breakthrough on the international market. The process of association of small and medium enterprises in clusters and other forms of interconnection in Serbia is far from the required and potential level.The awareness on the importance of clusters in a local economic development through contributions to the advancement of small and medium sized enterprises is not yet sufficiently mature. Support to associating into clusters and usage of their benefits after the model of highly developed countries is the basis for leading a successful economic policy and in Serbia there are all necessary prerequisites for it.

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

Semi-supervised clustering methods

Science.gov (United States)

Bair, Eric

2013-01-01

Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as “semi-supervised clustering” methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided. PMID:24729830

Reduct Driven Pattern Extraction from Clusters

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Shuchita Upadhyaya

2009-03-01

Full Text Available Clustering algorithms give general description of clusters, listing number of clusters and member entities in those clusters. However, these algorithms lack in generating cluster description in the form of pattern. From data mining perspective, pattern learning from clusters is as important as cluster finding. In the proposed approach, reduct derived from rough set theory is employed for pattern formulation. Further, reduct are the set of attributes which distinguishes the entities in a homogenous cluster, hence these can be clear cut removed from the same. Remaining attributes are then ranked for their contribution in the cluster. Pattern is formulated with the conjunction of most contributing attributes such that pattern distinctively describes the cluster with minimum error.

Clustering Dycom

KAUST Repository

Minku, Leandro L.

2017-10-06

Background: Software Effort Estimation (SEE) can be formulated as an online learning problem, where new projects are completed over time and may become available for training. In this scenario, a Cross-Company (CC) SEE approach called Dycom can drastically reduce the number of Within-Company (WC) projects needed for training, saving the high cost of collecting such training projects. However, Dycom relies on splitting CC projects into different subsets in order to create its CC models. Such splitting can have a significant impact on Dycom\\'s predictive performance. Aims: This paper investigates whether clustering methods can be used to help finding good CC splits for Dycom. Method: Dycom is extended to use clustering methods for creating the CC subsets. Three different clustering methods are investigated, namely Hierarchical Clustering, K-Means, and Expectation-Maximisation. Clustering Dycom is compared against the original Dycom with CC subsets of different sizes, based on four SEE databases. A baseline WC model is also included in the analysis. Results: Clustering Dycom with K-Means can potentially help to split the CC projects, managing to achieve similar or better predictive performance than Dycom. However, K-Means still requires the number of CC subsets to be pre-defined, and a poor choice can negatively affect predictive performance. EM enables Dycom to automatically set the number of CC subsets while still maintaining or improving predictive performance with respect to the baseline WC model. Clustering Dycom with Hierarchical Clustering did not offer significant advantage in terms of predictive performance. Conclusion: Clustering methods can be an effective way to automatically generate Dycom\\'s CC subsets.

Data Clustering

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Wagstaff, Kiri L.

2012-03-01

clustering, in which some partial information about item assignments or other components of the resulting output are already known and must be accommodated by the solution. Some algorithms seek a partition of the data set into distinct clusters, while others build a hierarchy of nested clusters that can capture taxonomic relationships. Some produce a single optimal solution, while others construct a probabilistic model of cluster membership. More formally, clustering algorithms operate on a data set X composed of items represented by one or more features (dimensions). These could include physical location, such as right ascension and declination, as well as other properties such as brightness, color, temporal change, size, texture, and so on. Let D be the number of dimensions used to represent each item, xi ∈ RD. The clustering goal is to produce an organization P of the items in X that optimizes an objective function f : P -> R, which quantifies the quality of solution P. Often f is defined so as to maximize similarity within a cluster and minimize similarity between clusters. To that end, many algorithms make use of a measure d : X x X -> R of the distance between two items. A partitioning algorithm produces a set of clusters P = {c1, . . . , ck} such that the clusters are nonoverlapping (c_i intersected with c_j = empty set, i != j) subsets of the data set (Union_i c_i=X). Hierarchical algorithms produce a series of partitions P = {p1, . . . , pn }. For a complete hierarchy, the number of partitions n’= n, the number of items in the data set; the top partition is a single cluster containing all items, and the bottom partition contains n clusters, each containing a single item. For model-based clustering, each cluster c_j is represented by a model m_j , such as the cluster center or a Gaussian distribution. The wide array of available clustering algorithms may seem bewildering, and covering all of them is beyond the scope of this chapter. Choosing among them for a

Clustering methods and visualization algorithms to aid nuclear reactor operative diagnostics

International Nuclear Information System (INIS)

Pepelyshev, Yu.N.; Dzwinel, W.

1990-01-01

The software system developed plays the role of the aid to an operator for nuclear reactor diagnostics. The noise analysis of the reactor parameters such as power, temperature and coolant flow rate constitutes the basis of the system. Combination of data acquisition, data preprocessing, clustering and cluster visualization algorithms with heuristic techniques of results analysis, determine the way of its implementation. Two regimes are available. The first one - extended - is recommended for a long term investigations and the second - suppressed for the aid to the reactor operation monitoring. The system has been tested and developed at the JINR IBR-2 pulsed reactor. 13 refs.; 4 figs.; 2 tabs

Operational Numerical Weather Prediction systems based on Linux cluster architectures

International Nuclear Information System (INIS)

Pasqui, M.; Baldi, M.; Gozzini, B.; Maracchi, G.; Giuliani, G.; Montagnani, S.

2005-01-01

The progress in weather forecast and atmospheric science has been always closely linked to the improvement of computing technology. In order to have more accurate weather forecasts and climate predictions, more powerful computing resources are needed, in addition to more complex and better-performing numerical models. To overcome such a large computing request, powerful workstations or massive parallel systems have been used. In the last few years, parallel architectures, based on the Linux operating system, have been introduced and became popular, representing real high performance-low cost systems. In this work the Linux cluster experience achieved at the Laboratory far Meteorology and Environmental Analysis (LaMMA-CNR-IBIMET) is described and tips and performances analysed

A new physical performance classification system for elite handball players: cluster analysis

Directory of Open Access Journals (Sweden)

Bautista Iker J.

2016-06-01

Full Text Available The aim of the present study was to identify different cluster groups of handball players according to their physical performance level assessed in a series of physical assessments, which could then be used to design a training program based on individual strengths and weaknesses, and to determine which of these variables best identified elite performance in a group of under-19 [U19] national level handball players. Players of the U19 National Handball team (n=16 performed a set of tests to determine: 10 m (ST10 and 20 m (ST20 sprint time, ball release velocity (BRv, countermovement jump (CMJ height and squat jump (SJ height. All players also performed an incremental-load bench press test to determine the 1 repetition maximum (1RMest, the load corresponding to maximum mean power (LoadMP, the mean propulsive phase power at LoadMP (PMPPMP and the peak power at LoadMP (PPEAKMP. Cluster analyses of the test results generated four groupings of players. The variables best able to discriminate physical performance were BRv, ST20, 1RMest, PPEAKMP and PMPPMP. These variables could help coaches identify talent or monitor the physical performance of athletes in their team. Each cluster of players has a particular weakness related to physical performance and therefore, the cluster results can be applied to a specific training programmed based on individual needs.

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

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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.

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.)

A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis

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Shaoning Li

2017-01-01

Full Text Available In the fields of geographic information systems (GIS and remote sensing (RS, the clustering algorithm has been widely used for image segmentation, pattern recognition, and cartographic generalization. Although clustering analysis plays a key role in geospatial modelling, traditional clustering methods are limited due to computational complexity, noise resistant ability and robustness. Furthermore, traditional methods are more focused on the adjacent spatial context, which makes it hard for the clustering methods to be applied to multi-density discrete objects. In this paper, a new method, cell-dividing hierarchical clustering (CDHC, is proposed based on convex hull retraction. The main steps are as follows. First, a convex hull structure is constructed to describe the global spatial context of geospatial objects. Then, the retracting structure of each borderline is established in sequence by setting the initial parameter. The objects are split into two clusters (i.e., “sub-clusters” if the retracting structure intersects with the borderlines. Finally, clusters are repeatedly split and the initial parameter is updated until the terminate condition is satisfied. The experimental results show that CDHC separates the multi-density objects from noise sufficiently and also reduces complexity compared to the traditional agglomerative hierarchical clustering algorithm.

Applications of Cluster Analysis to the Creation of Perfectionism Profiles: A Comparison of two Clustering Approaches

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Jocelyn H Bolin

2014-04-01

Full Text Available Although traditional clustering methods (e.g., K-means have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Trimming and clustering sugarcane ESTs

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Guilherme P. Telles

2001-12-01

Full Text Available The original clustering procedure adopted in the Sugarcane Expressed Sequence Tag project (SUCEST had many problems, for instance too many clusters, the presence of ribosomal sequences, etc. We therefore redesigned the clustering procedure entirely, including a much more careful initial trimming of the reads. In this paper the new trimming and clustering strategies are described in detail and we give the new official figures for the project, 237,954 expressed sequence tags and 43,141 clusters.O método de clustering adotado no Projeto SUCEST (Sugarcane EST Project tinha vários problemas (muitos clusters, presença de seqüências de ribossomo etc. Nós assumimos a tarefa de reprojetar todo o processo de clustering, propondo uma "limpeza" inicial mais cuidadosa das seqüências. Neste artigo as estratégias de limpeza das seqüências e de clustering são descritas em detalhe, incluindo os números oficiais do projeto (237,954 ESTs e 43,141 clusters.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

Science.gov (United States)

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

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

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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.

Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

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Bilal Jan

2017-01-01

Full Text Available Wireless sensor networks (WSN are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

The integration of Workload Management Systems for the ProtoDUNE Software and Computing cluster

CERN Document Server

Oniciuc, Oriana-Maria

2017-01-01

The protoDUNE experimental program is designed to test and validate the technologies for DUNE. All of the many elements in the chain of data acquisition, storage, distribution and processing are critically important to derive physics results from the data. To achieve these, a software stack has been chosen to implement automatic propagation of configurations across all the nodes in the NP cluster. This report presents the architecture of the system and the operations through which the cluster features can be scaled.

Availability Analysis of the Ventilation Stack CAM Interlock System

CERN Document Server

Young, J

2000-01-01

Ventilation Stack Continuous Air Monitor (CAM) Interlock System failure modes, failure frequencies, and system availability have been evaluated for the RPP. The evaluation concludes that CAM availability is as high as assumed in the safety analysis and that the current routine system surveillance is adequate to maintain this availability credited in the safety analysis, nor is such an arrangement predicted to significantly improve system availability.

Coarse cluster enhancing collaborative recommendation for social network systems

Science.gov (United States)

Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng

2017-10-01

Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.

Structure and bonding in clusters

International Nuclear Information System (INIS)

Kumar, V.

1991-10-01

We review here the recent progress made in the understanding of the electronic and atomic structure of small clusters of s-p bonded materials using the density functional molecular dynamics technique within the local density approximation. Starting with a brief description of the method, results are presented for alkali metal clusters, clusters of divalent metals such as Mg and Be which show a transition from van der Waals or weak chemical bonding to metallic behaviour as the cluster size grows and clusters of Al, Sn and Sb. In the case of semiconductors, we discuss results for Si, Ge and GaAs clusters. Clusters of other materials such as P, C, S, and Se are also briefly discussed. From these and other available results we suggest the possibility of unique structures for the magic clusters. (author). 69 refs, 7 figs, 1 tab

Cluster strategies in the regional economy development: legal aspects

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Irina V. Mikheeva

2016-09-01

Full Text Available Objective to study the state of legal support of the cluster strategies implementation to identify the problems and possible directions for improving the legal support of cluster development in the regions. Methods systemic structuralfunctional induction and deduction analysis and synthesis formal legal. Results the paper formulates the definition of cluster as a form of cooperative interaction of organizations interacting in some economic sphere due to functional dependence complementing each other and reinforcing the competitive advantages of individual companies. The hypothesis is proposed that the organizational and management structure of clusters should be unified and obtain normative fixation so that the same type of bodies including executive bodies and the structure of the different clusters deliberative specialized organizations organizationcoordinator etc. had similar competence and position in the management hierarchy. Scientific novelty following the most general conception of a cluster as interacting institutions in a specific area one can see that the lack of clarity in the legal support of the clusters functioning does not allow to determine the status of authoritative and nonauthoritative subjects of economic activities their organizationallegal forms and the procedure of their interaction. Practical significance the identified problems of legal support of the cluster strategies implementation can help in the improvement of state regulation of cluster relations in the regions and their implementation.

Globular clusters and galaxy halos

International Nuclear Information System (INIS)

Van Den Bergh, S.

1984-01-01

Using semipartial correlation coefficients and bootstrap techniques, a study is made of the important features of globular clusters with respect to the total number of galaxy clusters and dependence of specific galaxy cluster on parent galaxy type, cluster radii, luminosity functions and cluster ellipticity. It is shown that the ellipticity of LMC clusters correlates significantly with cluster luminosity functions, but not with cluster age. The cluter luminosity value above which globulars are noticeably flattened may differ by a factor of about 100 from galaxy to galaxy. Both in the Galaxy and in M31 globulars with small core radii have a Gaussian distribution over luminosity, whereas clusters with large core radii do not. In the cluster systems surrounding the Galaxy, M31 and NGC 5128 the mean radii of globular clusters was found to increase with the distance from the nucleus. Central galaxies in rich clusters have much higher values for specific globular cluster frequency than do other cluster ellipticals, suggesting that such central galaxies must already have been different from normal ellipticals at the time they were formed

A Hybrid Fuzzy Multi-hop Unequal Clustering Algorithm for Dense Wireless Sensor Networks

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Shawkat K. Guirguis

2017-01-01

Full Text Available Clustering is carried out to explore and solve power dissipation problem in wireless sensor network (WSN. Hierarchical network architecture, based on clustering, can reduce energy consumption, balance traffic load, improve scalability, and prolong network lifetime. However, clustering faces two main challenges: hotspot problem and searching for effective techniques to perform clustering. This paper introduces a fuzzy unequal clustering technique for heterogeneous dense WSNs to determine both final cluster heads and their radii. Proposed fuzzy system blends three effective parameters together which are: the distance to the base station, the density of the cluster, and the deviation of the noders residual energy from the average network energy. Our objectives are achieving gain for network lifetime, energy distribution, and energy consumption. To evaluate the proposed algorithm, WSN clustering based routing algorithms are analyzed, simulated, and compared with obtained results. These protocols are LEACH, SEP, HEED, EEUC, and MOFCA.

Monitoring evolving urban cluster systems using DMSP/OLS nighttime light data: a case study of the Yangtze River Delta region, China

Science.gov (United States)

Wang, Zhao; Yang, Shan; Wang, Shuguang; Shen, Yan

2017-10-01

The assessment of the dynamic urban structure has been affected by lack of timely and accurate spatial information for a long period, which has hindered the measurements of structural continuity at the macroscale. Defense meteorological satellite program's operational linescan system (DMSP/OLS) nighttime light (NTL) data provide an ideal source for urban information detection with a long-time span, short-time interval, and wide coverage. In this study, we extracted the physical boundaries of urban clusters from corrected NTL images and quantitatively analyzed the structure of the urban cluster system based on rank-size distribution, spatial metrics, and Mann-Kendall trend test. Two levels of urban cluster systems in the Yangtze River Delta region (YRDR) were examined. We found that (1) in the entire YRDR, the urban cluster system showed a periodic process, with a significant trend of even distribution before 2007 but an unequal growth pattern after 2007, and (2) at the metropolitan level, vast disparities exist in four metropolitan areas for the fluctuations of Pareto's exponent, the speed of cluster expansion, and the dominance of core cluster. The results suggest that the extracted urban cluster information from NTL data effectively reflect the evolving nature of regional urbanization, which in turn can aid in the planning of cities and help achieve more sustainable regional development.

The coupled cluster theory of quantum lattice systems

International Nuclear Information System (INIS)

Bishop, R.; Xian, Yang

1994-01-01

The coupled cluster method is widely recognized nowadays as providing an ab initio method of great versatility, power, and accuracy for handling in a fully microscopic and systematic way the correlations between particles in quantum many-body systems. The number of successful applications made to date within both chemistry and physics is impressive. In this article, the authors review recent extensions of the method which now provide a unifying framework for also dealing with strongly interacting infinite quantum lattice systems described by a Hamiltonian. Such systems include both spin-lattice models (such as the anisotropic Heisenberg or XXZ model) exhibiting interesting magnetic properties, and electron lattice models (such as the tJ and Hubbard models), where the spins or fermions are localized on the sites of a regular lattice; as well as lattice gauge theories [such as the Abelian U(1) model of quantum electrodynamics and non-Abelian SU(n) models]. Illustrative results are given for both the XXZ spin lattice model and U(1) lattice gauge theory

Cluster emission at pre-equilibrium stage in Heavy Nuclear Reactions. A Model considering the Thermodynamics of Small Systems

International Nuclear Information System (INIS)

Bermudez Martinez, A.; Damiani, D.; Guzman Martinez, F.; Rodriguez Hoyos, O.; Rodriguez Manso, A.

2015-01-01

Cluster emission at pre-equilibrium stage, in heavy ion fusion reactions of 12 C and 16 O nuclei with 116 Sn, 208 Pb, 238 U are studied. the energy of the projectile nuclei was chosen at 0.25GeV, 0.5GeV and 1GeV. A cluster formation model is developed in order to calculate the cluster size. Thermodynamics of small systems was used in order to examine the cluster behavior inside the nuclear media. This model is based on considering two phases inside the compound nucleus, on one hand the nuclear media phase, and on the other hand the cluster itself. The cluster acts like an instability inside the compound nucleus, provoking an exchange of nucleons with the nuclear media through its surface. The processes were simulated using Monte Carlo methods. We obtained that the cluster emission probability shows great dependence on the cluster size. This project is aimed to implement cluster emission processes, during the pre-equilibrium stage, in the frame of CRISP code (Collaboration Rio-Sao Paulo). (Author)

Rack Aware Data Placement for Network Consumption in Erasure-Coded Clustered Storage Systems

Directory of Open Access Journals (Sweden)

Bilin Shao

2018-06-01

Full Text Available The amount of encoded data replication in an erasure-coded clustered storage system has a great impact on the bandwidth consumption and network latency, mostly during data reconstruction. Aimed at the reasons that lead to the excess data transmission between racks, a rack aware data block placement method is proposed. In order to ensure rack-level fault tolerance and reduce the frequency and amount of the cross-rack data transmission during data reconstruction, the method deploys partial data block concentration to store the data blocks of a file in fewer racks. Theoretical analysis and simulation results show that our proposed strategy greatly reduces the frequency and data volume of the cross-rack transmission during data reconstruction. At the same time, it has better performance than the typical random distribution method in terms of network usage and data reconstruction efficiency.

Cluster growth kinetics

International Nuclear Information System (INIS)

Dubovik, V.M.; Gal'perin, A.G.; Rikhvitskij, V.S.; Lushnikov, A.A.

2000-01-01

Processes of some traffic blocking coming into existence are considered as probabilistic ones. We study analytic solutions for models for the dynamics of both cluster growth and cluster growth with fragmentation in the systems of finite number of objects. Assuming rates constancy of both coalescence and fragmentation, the models under consideration are linear on the probability functions

Reliability Evaluation for Clustered WSNs under Malware Propagation

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Shigen Shen

2016-06-01

Full Text Available We consider a clustered wireless sensor network (WSN under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node’s MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN.

Defining objective clusters for rabies virus sequences using affinity propagation clustering.

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Susanne Fischer

2018-01-01

Full Text Available Rabies is caused by lyssaviruses, and is one of the oldest known zoonoses. In recent years, more than 21,000 nucleotide sequences of rabies viruses (RABV, from the prototype species rabies lyssavirus, have been deposited in public databases. Subsequent phylogenetic analyses in combination with metadata suggest geographic distributions of RABV. However, these analyses somewhat experience technical difficulties in defining verifiable criteria for cluster allocations in phylogenetic trees inviting for a more rational approach. Therefore, we applied a relatively new mathematical clustering algorythm named 'affinity propagation clustering' (AP to propose a standardized sub-species classification utilizing full-genome RABV sequences. Because AP has the advantage that it is computationally fast and works for any meaningful measure of similarity between data samples, it has previously been applied successfully in bioinformatics, for analysis of microarray and gene expression data, however, cluster analysis of sequences is still in its infancy. Existing (516 and original (46 full genome RABV sequences were used to demonstrate the application of AP for RABV clustering. On a global scale, AP proposed four clusters, i.e. New World cluster, Arctic/Arctic-like, Cosmopolitan, and Asian as previously assigned by phylogenetic studies. By combining AP with established phylogenetic analyses, it is possible to resolve phylogenetic relationships between verifiably determined clusters and sequences. This workflow will be useful in confirming cluster distributions in a uniform transparent manner, not only for RABV, but also for other comparative sequence analyses.

Neuro-fuzzy system modeling based on automatic fuzzy clustering

Institute of Scientific and Technical Information of China (English)

Yuangang TANG; Fuchun SUN; Zengqi SUN

2005-01-01

A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

K-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system.

Science.gov (United States)

Zhang, Junfeng; Chen, Wei; Gao, Mingyi; Shen, Gangxiang

2017-10-30

In this work, we proposed two k-means-clustering-based algorithms to mitigate the fiber nonlinearity for 64-quadrature amplitude modulation (64-QAM) signal, the training-sequence assisted k-means algorithm and the blind k-means algorithm. We experimentally demonstrated the proposed k-means-clustering-based fiber nonlinearity mitigation techniques in 75-Gb/s 64-QAM coherent optical communication system. The proposed algorithms have reduced clustering complexity and low data redundancy and they are able to quickly find appropriate initial centroids and select correctly the centroids of the clusters to obtain the global optimal solutions for large k value. We measured the bit-error-ratio (BER) performance of 64-QAM signal with different launched powers into the 50-km single mode fiber and the proposed techniques can greatly mitigate the signal impairments caused by the amplified spontaneous emission noise and the fiber Kerr nonlinearity and improve the BER performance.

Availability Analysis of the Ventilation Stack CAM Interlock System

International Nuclear Information System (INIS)

YOUNG, J.

2000-01-01

Ventilation Stack Continuous Air Monitor (CAM) Interlock System failure modes, failure frequencies and system availability have been evaluated for the RPP. The evaluation concludes that CAM availability is as high as assumed in the safety analysis and that the current routine system surveillance is adequate to maintain this availability. Further, requiring an alarm to actuate upon CAM failure is not necessary to maintain the availability credited in the safety analysis, nor is such an arrangement predicted to significantly improve system availability. However, if CAM failures were only detected by the 92-day functional tests required in the Authorization Basis (AB), CAM availability would be much less than that credited in the safety analysis. Therefore it is recommended that the current surveillance practice of daily simple system checks, 30-day source checks and 92-day functional tests be continued in order to maintain CAM availability

Study of Cluster-size Effect on Damage Formation

International Nuclear Information System (INIS)

Aoki, Takaaki; Seki, Toshio; Nakai, Atsuko; Matsuo, Jiro; Takaoka, Gikan

2003-01-01

Computer simulation and experiments were performed in order to understand the effect of cluster size on damage formation. Results of molecular dynamics simulations of cluster impact on solid targets derived the model function, which explains the relationship among cluster size, incident energy and number of displacements. On the other hand, time of flight mass measurement system was installed a cluster irradiation system, so that cluster ion beam which cluster size distribution is well known can be irradiated on the target. The damage properties under various cluster irradiation conditions were examined using RBS. The results from computer simulations and experiments showed good agreements with each other, which suggests that irradiation damage by cluster ion beam can be controlled by selecting cluster size distribution and incident energy

Framework for Optimizing Cluster Selection using Geo-assisted Movement Prediction

DEFF Research Database (Denmark)

Kristensen, Thomas Sander; Madsen, Jacob Theilgaard; Pedersen, Michael Sølvkjær

2012-01-01

Due to the availability of satellite- and radio-based location systems in most new devices, it is possible to use geographical location of a node for network management and communication protocol optimization. It is a common belief that usage of location information can bring performance benefits...... movement prediction and inaccurate location estimation on its performance. The proposed algorithm is compared with two reference algorithms: when a considered node associates with either the first discovered cluster or the nearest cluster. Evaluation shows significant performance benefits in terms...

Mass spectrometric production of heterogeneous metal clusters using Knudsen cell

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Veljković Filip M.

2016-01-01

Full Text Available Knudsen effusion mass spectrometry or high-temperature method of mass spectrometry for decades gives new information about saturated vapor of hardly volatile compounds and it is an important method in the discovery of many new molecules, radicals, ions and clusters present in the gas phase. Since pioneering works until now, this method has been successfully applied to a large number of systems (ores, oxides, ceramics, glass materials, borides, carbides, sulfides, nitrates, metals, fullerenes, etc which led to the establishment of various research branches such as chemistry of clusters. This paper describes the basic principles of Knudsen cell use for both identification of chemical species created in the process of evaporation and determination of their ionization energies. Depending on detected ions intensities and the partial pressure of each gaseous component, as well as on changes in partial pressure with temperature, Knudsen cell mass spectrometry enables the determination of thermodynamic parameters of the tested system. A special attention is paid to its application in the field of small heterogeneous and homogeneous clusters of alkali metals. Furthermore, experimental results for thermodynamic parameters of some clusters, as well as capabilities of non-standard ways of using Knudsen cells in the process of synthesis of new clusters are presented herein. [Projekat Ministarstva nauke Republike Srbije, br. 172019

Influence of Energy and Temperature in Cluster Coalescence Induced by Deposition

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J. C. Jiménez-Sáez

2012-01-01

Full Text Available Coalescence induced by deposition of different Cu clusters on an epitaxial Co cluster supported on a Cu(001 substrate is studied by constant-temperature molecular dynamics simulations. The degree of epitaxy of the final system increases with increasing separation between the centres of mass of the projectile and target clusters during the collision. Structure, roughness, and epitaxial order of the supported cluster also influence the degree of epitaxy. The effect of energy and temperature is determinant on the epitaxial condition of the coalesced cluster, especially both factors modify the generation, growth and interaction among grains. A higher temperature favours the epitaxial growth for low impact parameters. A higher energy contributes to the epitaxial coalescence for any initial separation between the projectile and target clusters. The influence of projectile energy is notably greater than the influence of temperature since higher energies allow greater and instantaneous atomic reorganizations, so that the number of arisen grains just after the collision becomes smaller. The appearance of grain boundary dislocations is, therefore, a decisive factor in the epitaxial growth of the coalesced cluster.

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review.

Science.gov (United States)

Kristunas, Caroline; Morris, Tom; Gray, Laura

2017-11-15

To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Any, not limited to healthcare settings. Any taking part in an SW-CRT published up to March 2016. The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Cluster algorithms with empahsis on quantum spin systems

International Nuclear Information System (INIS)

Gubernatis, J.E.; Kawashima, Naoki

1995-01-01

The purpose of this lecture is to discuss in detail the generalized approach of Kawashima and Gubernatis for the construction of cluster algorithms. We first present a brief refresher on the Monte Carlo method, describe the Swendsen-Wang algorithm, show how this algorithm follows from the Fortuin-Kastelyn transformation, and re=interpret this transformation in a form which is the basis of the generalized approach. We then derive the essential equations of the generalized approach. This derivation is remarkably simple if done from the viewpoint of probability theory, and the essential assumptions will be clearly stated. These assumptions are implicit in all useful cluster algorithms of which we are aware. They lead to a quite different perspective on cluster algorithms than found in the seminal works and in Ising model applications. Next, we illustrate how the generalized approach leads to a cluster algorithm for world-line quantum Monte Carlo simulations of Heisenberg models with S = 1/2. More succinctly, we also discuss the generalization of the Fortuin- Kasetelyn transformation to higher spin models and illustrate the essential steps for a S = 1 Heisenberg model. Finally, we summarize how to go beyond S = 1 to a general spin, XYZ model

Launching large computing applications on a disk-less cluster

International Nuclear Information System (INIS)

Schwemmer, Rainer; Caicedo Carvajal, Juan Manuel; Neufeld, Niko

2011-01-01

The LHCb Event Filter Farm system is based on a cluster of the order of 1.500 disk-less Linux nodes. Each node runs one instance of the filtering application per core. The amount of cores in our current production environment is 8 per machine for the old cluster and 12 per machine on extension of the cluster. Each instance has to load about 1.000 shared libraries, weighting 200 MB from several directory locations from a central repository. The repository is currently hosted on a SAN and exported via NFS. The libraries are all available in the local file system cache on every node. Loading a library still causes a huge number of requests to the server though, because the loader will try to probe every available path. Measurements show there are between 100.000-200.000 calls per application instance start up. Multiplied by the numbers of cores in the farm, this translates into a veritable DDoS attack on the servers, which lasts several minutes. Since the application is being restarted frequently, a better solution had to be found.scp Rolling out the software to the nodes is out of the question, because they have no disks and the software in it's entirety is too large to put into a ram disk. To solve this problem we developed a FUSE based file systems which acts as a permanent, controllable cache that keeps the essential files that are necessary in stock.

Evaluating the Efficiency of Banking Systems During a Pre-Crisis and Crisis Period by Using Cluster Analysis (2004-2009

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Serhiy Reverchuk

2013-10-01

Full Text Available The proposed study, by using cluster analysis, presents the unique methodology for determining the level of efficiency of banking systems in terms of crisis. It identifies a cause and relationship of various derivatives when applying the specialized tools to regulate the level of stability of the banking system. The proposed methodology assists in applying the presented studies to track the trends of governmental strategies in regulating the banking market applying the financial and performance indicators. Furthermore, this article presents the innovative methodology when assessing the level of effectiveness of national banking systems in relation to other countries, by carrying out the evaluation of the efficiency of governmental regulations compared with various international banking systems during the period of 2004-2009, and the implementation of the results by received economic interpretations.

Research on Bridge Sensor Validation Based on Correlation in Cluster

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Huang Xiaowei

2016-01-01

Full Text Available In order to avoid the false alarm and alarm failure caused by sensor malfunction or failure, it has been critical to diagnose the fault and analyze the failure of the sensor measuring system in major infrastructures. Based on the real time monitoring of bridges and the study on the correlation probability distribution between multisensors adopted in the fault diagnosis system, a clustering algorithm based on k-medoid is proposed, by dividing sensors of the same type into k clusters. Meanwhile, the value of k is optimized by a specially designed evaluation function. Along with the further study of the correlation of sensors within the same cluster, this paper presents the definition and corresponding calculation algorithm of the sensor’s validation. The algorithm is applied to the analysis of the sensor data from an actual health monitoring system. The result reveals that the algorithm can not only accurately measure the failure degree and orientate the malfunction in time domain but also quantitatively evaluate the performance of sensors and eliminate error of diagnosis caused by the failure of the reference sensor.

Overlapping Open Clusters NGC 1750 and NGC 1758 behind the Taurus Dark Clouds. II. CCD Photometry in the Vilnius System

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Straižys V.

2003-09-01

Full Text Available Seven-color photometry in the Vilnius system has been obtained for 420 stars down to V = 16 mag in the area containing the overlapping open clusters NGC 1750 and NGC 1758 in Taurus. Spectral and luminosity classes, color excesses, interstellar extinctions and distances are given for 287 stars. The classification of stars is based on their reddening-free Q-parameters. 18 stars observed photoelectrically were used as standards. The extinction vs. distance diagram exhibits the presence of one dust cloud at a distance of 175 pc which almost coincides with a distance of other dust clouds in the Taurus complex. The clusters NGC 1750 and NGC 1758 are found to be at the same distance of ~760 pc and may penetrate each other. Their interstellar extinction AV is 1.06 mag which corresponds to EB-V = 0.34 mag.

THE STAR CLUSTER SYSTEM IN THE NEARBY STARBURST GALAXY M82

International Nuclear Information System (INIS)

Lim, Sungsoon; Lee, Myung Gyoon; Hwang, Narae

2013-01-01

We present a photometric study of star clusters in the nearby starburst galaxy M82 based on the UBVI-, YJ- and H-band Hubble Space Telescope images. We find 1105 star clusters with V 0 ≈ 0.45, and a weaker red population. The luminosity function of the disk clusters shows a power-law distribution with a power-law index α = –2.04 ± 0.03, and the scale height of their distribution is h z = 9.''64 ± 0.''40 (164 ± 7 pc), similar to that of the stellar thin disk of M82. We have derived the ages of ∼630 star clusters using the spectral energy distribution fit method by comparing UBVI(YJ)H-band photometric data with the simple stellar population models. The age distribution of the disk clusters shows that the most dominant cluster population has ages ranging from 100 Myr to 1 Gyr, with a peak at about 500 Myr. This suggests that M82 has undergone a disk-wide star formation about 500 Myr ago, probably through the interaction with M81. The brightest star clusters in the nuclear region are much brighter than those in other regions, indicating that more massive star clusters are formed in the denser environments. On the other hand, the colors of the halo clusters are similar to those of globular clusters in the Milky Way, and their ages are estimated to be older than 1 Gyr. These are probably genuine old globular clusters in M82.

Merging history of three bimodal clusters

Science.gov (United States)

Maurogordato, S.; Sauvageot, J. L.; Bourdin, H.; Cappi, A.; Benoist, C.; Ferrari, C.; Mars, G.; Houairi, K.

2011-01-01

We present a combined X-ray and optical analysis of three bimodal galaxy clusters selected as merging candidates at z ~ 0.1. These targets are part of MUSIC (MUlti-Wavelength Sample of Interacting Clusters), which is a general project designed to study the physics of merging clusters by means of multi-wavelength observations. Observations include spectro-imaging with XMM-Newton EPIC camera, multi-object spectroscopy (260 new redshifts), and wide-field imaging at the ESO 3.6 m and 2.2 m telescopes. We build a global picture of these clusters using X-ray luminosity and temperature maps together with galaxy density and velocity distributions. Idealized numerical simulations were used to constrain the merging scenario for each system. We show that A2933 is very likely an equal-mass advanced pre-merger ~200 Myr before the core collapse, while A2440 and A2384 are post-merger systems (~450 Myr and ~1.5 Gyr after core collapse, respectively). In the case of A2384, we detect a spectacular filament of galaxies and gas spreading over more than 1 h-1 Mpc, which we infer to have been stripped during the previous collision. The analysis of the MUSIC sample allows us to outline some general properties of merging clusters: a strong luminosity segregation of galaxies in recent post-mergers; the existence of preferential axes - corresponding to the merging directions - along which the BCGs and structures on various scales are aligned; the concomitance, in most major merger cases, of secondary merging or accretion events, with groups infalling onto the main cluster, and in some cases the evidence of previous merging episodes in one of the main components. These results are in good agreement with the hierarchical scenario of structure formation, in which clusters are expected to form by successive merging events, and matter is accreted along large-scale filaments. Based on data obtained with the European Southern Observatory, Chile (programs 072.A-0595, 075.A-0264, and 079.A-0425

Monitoring by Use of Clusters of Sensor-Data Vectors

Science.gov (United States)

Iverson, David L.

2007-01-01

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean

Color Gradient in the King Type Globular Cluster NGC 7089

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Young-Jong Sohn

1999-12-01

Full Text Available We use BV CCD images to investigate the reality of the color gradient within a King type globular cluster NGC 7089. Surface photometry shows that there is a strong radial color gradient in the central region of the cluster in the sense of bluer center with the amplitude of -0.39 +/- 0.07 mag/arcsec2 in (B - V. In the outer region of the cluster, however, the radial color gradient shows a reverse case, i.e., redder toward the center. (B - V color profile which was derived from resolved stars in VGC 7089 field also shows a significant color gradient in the central region of the clusters, indicating that lights from the combination of red giant stars and blue horizontal branch stars cause the radial color gradient. Color gradient of the outer region of NGC 7089 may be due to the unresolved background of the cluster. Similar color gradients in the central area of clusters have been previously observed exserved exclusively in highly concentrated systems classified as post core collapse clusters. We caution, however, to confirm the reality of the color gradient from resolved stars, we need more accurate imaging data of the cluster with exceptional seeing condition because the effect of completeness correlates with local density of stars.

A WEB-BASED SOLUTION TO VISUALIZE OPERATIONAL MONITORING LINUX CLUSTER FOR THE PROTODUNE DATA QUALITY MONITORING CLUSTER

CERN Document Server

Mosesane, Badisa

2017-01-01

The Neutrino computing cluster made of 300 Dell PowerEdge 1950 U1 nodes serves an integral role to the CERN Neutrino Platform (CENF). It represents an effort to foster fundamental research in the field of Neutrino physics as it provides data processing facility. We cannot begin to over emphasize the need for data quality monitoring coupled with automating system configurations and remote monitoring of the cluster. To achieve these, a software stack has been chosen to implement automatic propagation of configurations across all the nodes in the cluster. The bulk of these discusses and delves more into the automated configuration management system on this cluster to enable the fast online data processing and Data Quality (DQM) process for the Neutrino Platform cluster (npcmp.cern.ch).

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

A highly accurate positioning and orientation system based on the usage of four-cluster fibre optic gyros

International Nuclear Information System (INIS)

Zhang, Xiaoyue; Lin, Zhili; Zhang, Chunxi

2013-01-01

A highly accurate positioning and orientation technique based on four-cluster fibre optic gyros (FOGs) is presented. The four-cluster FOG inertial measurement unit (IMU) comprises three low-precision FOGs, one static high-precision FOG and three accelerometers. To realize high-precision positioning and orientation, the static alignment (north-seeking) before vehicle manoeuvre was divided into a low-precision self-alignment phase and a high-precision north-seeking (online calibration) phase. The high-precision FOG measurement information was introduced to obtain high-precision azimuth alignment (north-seeking) result and achieve online calibration of the low-precision three-cluster FOG. The results of semi-physical simulation were presented to validate the availability and utility of the highly accurate positioning and orientation technique based on the four-cluster FOGs. (paper)

Wave failure at strong coupling in intracellular C a2 + signaling system with clustered channels

Science.gov (United States)

Li, Xiang; Wu, Yuning; Gao, Xuejuan; Cai, Meichun; Shuai, Jianwei

2018-01-01

As an important intracellular signal, C a2 + ions control diverse cellular functions. In this paper, we discuss the C a2 + signaling with a two-dimensional model in which the inositol 1,4,5-trisphosphate (I P3 ) receptor channels are distributed in clusters on the endoplasmic reticulum membrane. The wave failure at large C a2 + diffusion coupling is discussed in detail in the model. We show that with varying model parameters the wave failure is a robust behavior with either deterministic or stochastic channel dynamics. We suggest that the wave failure should be a general behavior in inhomogeneous diffusing systems with clustered excitable regions and may occur in biological C a2 + signaling systems.

Studies of the charge instabilities in the complex nano-objects: clusters and bio-molecular systems

International Nuclear Information System (INIS)

Manil, B.

2007-11-01

For the last 6 years, my main research works focused on i) the Coulomb instabilities and the fragmentation processes of fullerenes and clusters of fullerenes ii) the stability and the reactivity of complex bio-molecular systems. Concerning the clusters of fullerenes, which are van der Waals type clusters, we have shown that the multiply charged species, obtained in collisions with slow highly charged ions, keep their structural properties but become very good electric conductor. In another hand, with the aim to understand the role of the biologic environment at the molecular scale in the irradiation damage of complex biomolecules, we have studied the charge stabilities of clusters of small biomolecules and the dissociation processes of larger nano-hydrated biomolecules. Theses studies have shown that first, specific molecular recognition mechanisms continue to exist in gas phase and secondly, a small and very simple biochemical environment is enough to change the dynamics of instabilities. (author)

Cluster analysis in systems of magnetic spheres and cubes

Science.gov (United States)

Pyanzina, E. S.; Gudkova, A. V.; Donaldson, J. G.; Kantorovich, S. S.

2017-06-01

In the present work we use molecular dynamics simulations and graph-theory based cluster analysis to compare self-assembly in systems of magnetic spheres, and cubes where the dipole moment is oriented along the side of the cube in the [001] crystallographic direction. We show that under the same conditions cubes aggregate far less than their spherical counterparts. This difference can be explained in terms of the volume of phase space in which the formation of the bond is thermodynamically advantageous. It follows that this volume is much larger for a dipolar sphere than for a dipolar cube.

Distributed controller clustering in software defined networks.

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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.

Applying Stochastic Metaheuristics to the Problem of Data Management in a Multi-Tenant Database Cluster

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E. A. Boytsov

2014-01-01

Full Text Available A multi-tenant database cluster is a concept of a data-storage subsystem for cloud applications with the multi-tenant architecture. The cluster is a set of relational database servers with the single entry point, combined into one unit with a cluster controller. This system is aimed to be used by applications developed according to Software as a Service (SaaS paradigm and allows to place tenants at database servers so that providing their isolation, data backup and the most effective usage of available computational power. One of the most important problems about such a system is an effective distribution of data into servers, which affects the degree of individual cluster nodes load and faulttolerance. This paper considers the data-management approach, based on the usage of a load-balancing quality measure function. This function is used during initial placement of new tenants and also during placement optimization steps. Standard schemes of metaheuristic optimization such as simulated annealing and tabu search are used to find a better tenant placement.

Projected coupled cluster theory.

Science.gov (United States)

Qiu, Yiheng; Henderson, Thomas M; Zhao, Jinmo; Scuseria, Gustavo E

2017-08-14

Coupled cluster theory is the method of choice for weakly correlated systems. But in the strongly correlated regime, it faces a symmetry dilemma, where it either completely fails to describe the system or has to artificially break certain symmetries. On the other hand, projected Hartree-Fock theory captures the essential physics of many kinds of strong correlations via symmetry breaking and restoration. In this work, we combine and try to retain the merits of these two methods by applying symmetry projection to broken symmetry coupled cluster wave functions. The non-orthogonal nature of states resulting from the application of symmetry projection operators furnishes particle-hole excitations to all orders, thus creating an obstacle for the exact evaluation of overlaps. Here we provide a solution via a disentanglement framework theory that can be approximated rigorously and systematically. Results of projected coupled cluster theory are presented for molecules and the Hubbard model, showing that spin projection significantly improves unrestricted coupled cluster theory while restoring good quantum numbers. The energy of projected coupled cluster theory reduces to the unprojected one in the thermodynamic limit, albeit at a much slower rate than projected Hartree-Fock.

Preconditions for Emergence of Lithuanian Clusters: from Informal Cooperation to Its Legitimation

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Grumadaitė Kristina

2017-06-01

Full Text Available This paper reveals preconditions for the emergence of clusters as self-organisation based industrial systems in a context, in which cooperation traditions are insufficiently developed. These preconditions reflect the principles of the emergence of self-organising complex adaptive systems that are analysed in the complexity theory. Those principles are based on the initiation of non-equilibrium and its purposeful direction into the creation of a new order. This paper highlights the main external and internal tensions that influence informal or formal clustering of enterprises, while various change agents perform different roles making self-organising processes to occur.

Design and reliability, availability, maintainability, and safety analysis of a high availability quadruple vital computer system

Institute of Scientific and Technical Information of China (English)

Ping TAN; Wei-ting HE; Jia LIN; Hong-ming ZHAO; Jian CHU

2011-01-01

With the development of high-speed railways in China,more than 2000 high-speed trains will be put into use.Safety and efficiency of railway transportation is increasingly important.We have designed a high availability quadruple vital computer (HAQVC) system based on the analysis of the architecture of the traditional double 2-out-of-2 system and 2-out-of-3 system.The HAQVC system is a system with high availability and safety,with prominent characteristics such as fire-new internal architecture,high efficiency,reliable data interaction mechanism,and operation state change mechanism.The hardware of the vital CPU is based on ARM7 with the real-time embedded safe operation system (ES-OS).The Markov modeling method is designed to evaluate the reliability,availability,maintainability,and safety (RAMS) of the system.In this paper,we demonstrate that the HAQVC system is more reliable than the all voting triple modular redundancy (AVTMR) system and double 2-out-of-2 system.Thus,the design can be used for a specific application system,such as an airplane or high-speed railway system.

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...

Diskless Linux Cluster How-To

National Research Council Canada - National Science Library

Shumaker, Justin L

2005-01-01

Diskless linux clustering is not yet a turn-key solution. The process of configuring a cluster of diskless linux machines requires many modifications to the stock linux operating system before they can boot cleanly...

VEGAS-SSS. II. Comparing the globular cluster systems in NGC 3115 and NGC 1399 using VEGAS and FDS survey data. The quest for a common genetic heritage of globular cluster systems

Science.gov (United States)

Cantiello, Michele; D'Abrusco, Raffaele; Spavone, Marilena; Paolillo, Maurizio; Capaccioli, Massimo; Limatola, Luca; Grado, Aniello; Iodice, Enrica; Raimondo, Gabriella; Napolitano, Nicola; Blakeslee, John P.; Brocato, Enzo; Forbes, Duncan A.; Hilker, Michael; Mieske, Steffen; Peletier, Reynier; van de Ven, Glenn; Schipani, Pietro

2018-04-01

We analyze the globular cluster (GC) systems in two very different galaxies, NGC 3115 and NGC 1399. With the papers of this series, we aim at highlighting common and different properties in the GC systems in galaxies covering a wide range of parameter space. We compare the GCs in NGC 3115 and NGC 1399 as derived from the analysis of one square degree u-, g-, and i-band images taken with the VST telescope as part of the VST early-type galaxy survey (VEGAS) and Fornax deep survey (FDS). We selected GC candidates using as reference the morpho-photometric and color properties of confirmed GCs. The surface density maps of GCs in NGC 3115 reveal a morphology similar to the light profile of field stars; the same is true when blue and red GCs are taken separately. The GC maps for NGC 1399 are richer in structure and confirm the existence of an intra-cluster GC component. We confirm the presence of a spatial offset in the NGC 1399 GC centroid and find that the centroid of the GCs for NGC 3115 coincides well with the galaxy center. Both GC systems show unambiguous color bimodality in (g - i) and (u - i); the color-color relations of the two GC systems are slightly different with NGC 3115 appearing more linear than NGC 1399. The azimuthal average of the radial density profiles in both galaxies reveals a larger spatial extent for the total GCs population with respect to the galaxy surface brightness profile. For both galaxies, the red GCs have radial density profiles compatible with the galaxy light profile, while the radial profiles for blue GCs are shallower. As for the specific frequency of GCs, SN, we find it is a factor of two higher in NGC 1399 than for NGC 3115; this is mainly the result of extra blue GCs. By inspecting the radial behavior of the specific frequency, SN(

Scaling of cluster growth for coagulating active particles

Science.gov (United States)

Cremer, Peet; Löwen, Hartmut

2014-02-01

Cluster growth in a coagulating system of active particles (such as microswimmers in a solvent) is studied by theory and simulation. In contrast to passive systems, the net velocity of a cluster can have various scalings dependent on the propulsion mechanism and alignment of individual particles. Additionally, the persistence length of the cluster trajectory typically increases with size. As a consequence, a growing cluster collects neighboring particles in a very efficient way and thus amplifies its growth further. This results in unusual large growth exponents for the scaling of the cluster size with time and, for certain conditions, even leads to "explosive" cluster growth where the cluster becomes macroscopic in a finite amount of time.

The Assessment of Hydrogen Energy Systems for Fuel Cell Vehicles Using Principal Componenet Analysis and Cluster Analysis

DEFF Research Database (Denmark)

Ren, Jingzheng; Tan, Shiyu; Dong, Lichun

2012-01-01

and analysis of the hydrogen systems is meaningful for decision makers to select the best scenario. principal component analysis (PCA) has been used to evaluate the integrated performance of different hydrogen energy systems and select the best scenario, and hierarchical cluster analysis (CA) has been used...... for transportation of hydrogen, hydrogen gas tank for the storage of hydrogen at refueling stations, and gaseous hydrogen as power energy for fuel cell vehicles has been recognized as the best scenario. Also, the clustering results calculated by CA are consistent with those determined by PCA, denoting...

Availability model of stand-alone photovoltaic system

Science.gov (United States)

Mazurek, G.

2017-08-01

In this paper we present a simple, empirical model of stand-alone photovoltaic power system availability. The model is a final result of five-year long studies and ground measurements of solar irradiation carried out in Central Europe. The obtained results facilitate sizing of PV modules that have to be installed with taking into account system's availability level in each month of a year. The model can be extended to different geographical locations, with help of local meteorological data or solar irradiation datasets derived from satellite measurements.

Cataloging the Praesepe Cluster: Identifying Interlopers and Binary Systems

Science.gov (United States)

Lucey, Madeline R.; Gosnell, Natalie M.; Mann, Andrew; Douglas, Stephanie

2018-01-01

We present radial velocity measurements from an ongoing survey of the Praesepe open cluster using the WIYN 3.5m Telescope. Our target stars include 229 early-K to mid-M dwarfs with proper motion memberships that have been observed by the repurposed Kepler mission, K2. With this survey, we will provide a well-constrained membership list of the cluster. By removing interloping stars and determining the cluster binary frequency we can avoid systematic errors in our analysis of the K2 findings and more accurately determine exoplanet properties in the Praesepe cluster. Obtaining accurate exoplanet parameters in open clusters allows us to study the temporal dimension of exoplanet parameter space. We find Praesepe to have a mean radial velocity of 34.09 km/s and a velocity dispersion of 1.13 km/s, which is consistent with previous studies. We derive radial velocity membership probabilities for stars with ≥3 radial velocity measurements and compare against published membership probabilities. We also identify radial velocity variables and potential double-lined spectroscopic binaries. We plan to obtain more observations to determine the radial velocity membership of all the stars in our sample, as well as follow up on radial velocity variables to determine binary orbital solutions.

THE MASSIVE DISTANT CLUSTERS OF WISE SURVEY: THE FIRST DISTANT GALAXY CLUSTER DISCOVERED BY WISE

International Nuclear Information System (INIS)

Gettings, Daniel P.; Gonzalez, Anthony H.; Mancone, Conor; Stanford, S. Adam; Eisenhardt, Peter R. M.; Stern, Daniel; Brodwin, Mark; Zeimann, Gregory R.; Masci, Frank J.; Papovich, Casey; Tanaka, Ichi; Wright, Edward L.

2012-01-01

We present spectroscopic confirmation of a z = 0.99 galaxy cluster discovered using data from the Wide-field Infrared Survey Explorer (WISE). This is the first z ∼ 1 cluster candidate from the Massive Distant Clusters of WISE Survey to be confirmed. It was selected as an overdensity of probable z ∼> 1 sources using a combination of WISE and Sloan Digital Sky Survey DR8 photometric catalogs. Deeper follow-up imaging data from Subaru and WIYN reveal the cluster to be a rich system of galaxies, and multi-object spectroscopic observations from Keck confirm five cluster members at z = 0.99. The detection and confirmation of this cluster represents a first step toward constructing a uniformly selected sample of distant, high-mass galaxy clusters over the full extragalactic sky using WISE data.

Electronic laboratory system reduces errors in National Tuberculosis Program: a cluster randomized controlled trial.

Science.gov (United States)

Blaya, J A; Shin, S S; Yale, G; Suarez, C; Asencios, L; Contreras, C; Rodriguez, P; Kim, J; Cegielski, P; Fraser, H S F

2010-08-01

To evaluate the impact of the e-Chasqui laboratory information system in reducing reporting errors compared to the current paper system. Cluster randomized controlled trial in 76 health centers (HCs) between 2004 and 2008. Baseline data were collected every 4 months for 12 months. HCs were then randomly assigned to intervention (e-Chasqui) or control (paper). Further data were collected for the same months the following year. Comparisons were made between intervention and control HCs, and before and after the intervention. Intervention HCs had respectively 82% and 87% fewer errors in reporting results for drug susceptibility tests (2.1% vs. 11.9%, P = 0.001, OR 0.17, 95%CI 0.09-0.31) and cultures (2.0% vs. 15.1%, P Chasqui users sent on average three electronic error reports per week to the laboratories. e-Chasqui reduced the number of missing laboratory results at point-of-care health centers. Clinical users confirmed viewing electronic results not available on paper. Reporting errors to the laboratory using e-Chasqui promoted continuous quality improvement. The e-Chasqui laboratory information system is an important part of laboratory infrastructure improvements to support multidrug-resistant tuberculosis care in Peru.

Perceptions of firms within a cluster regarding the cluster's function and success: Amish furniture manufacturing in Ohio

Science.gov (United States)

Matthew S. Bumgardner; Gary W. Graham; P. Charles Goebel; Robert L. Romig

2011-01-01

The Amish-based furniture manufacturing cluster in and around Holmes County, OH, is home to some 400 shops and has become an important regional driver of demand for hardwood products. The cluster has expanded even as the broader domestic furniture industry has declined. Clustering dynamics are seen as important to the success, but little information has been available...

Cluster Analysis of Maize Inbred Lines

Directory of Open Access Journals (Sweden)

Jiban Shrestha

2016-12-01

Full Text Available The determination of diversity among inbred lines is important for heterosis breeding. Sixty maize inbred lines were evaluated for their eight agro morphological traits during winter season of 2011 to analyze their genetic diversity. Clustering was done by average linkage method. The inbred lines were grouped into six clusters. Inbred lines grouped into Clusters II had taller plants with maximum number of leaves. The cluster III was characterized with shorter plants with minimum number of leaves. The inbred lines categorized into cluster V had early flowering whereas the group into cluster VI had late flowering time. The inbred lines grouped into the cluster III were characterized by higher value of anthesis silking interval (ASI and those of cluster VI had lower value of ASI. These results showed that the inbred lines having widely divergent clusters can be utilized in hybrid breeding programme.

Remarks on stellar clusters

International Nuclear Information System (INIS)

Teller, E.

1985-01-01

In the following, a few simple remarks on the evolution and properties of stellar clusters will be collected. In particular, globular clusters will be considered. Though details of such clusters are often not known, a few questions can be clarified with the help of primitive arguments. These are:- why are spherical clusters spherical, why do they have high densities, why do they consist of approximately a million stars, how may a black hole of great mass form within them, may they be the origin of gamma-ray bursts, may their invisible remnants account for the missing mass of our galaxy. The available data do not warrant a detailed evaluation. However, it is remarkable that exceedingly simple models can shed some light on the questions enumerated above. (author)

ABOUT THE TYPES OF REGIONAL INNOVATION CLUSTERS

Directory of Open Access Journals (Sweden)

Aleksandr S. Voronov

2016-01-01

Full Text Available This article describes the main characteristics of innovation clusters, analyzed the develop-ment plans of the cluster areas of growth on the basis of innovation in the various subjects of the federation, it proposed the principle of clustering of the «nuclear» type, dened by problems in the functioning of specialized distributed clusters on the basis of the organi-zational and marketing innovations, proposed scheme for sustainable innovation develop-ment of specialized distributed cluster.

The globular cluster system of NGC 1316. IV. Nature of the star cluster complex SH2

Science.gov (United States)

Richtler, T.; Husemann, B.; Hilker, M.; Puzia, T. H.; Bresolin, F.; Gómez, M.

2017-05-01

Context. The light of the merger remnant NGC 1316 (Fornax A) is dominated by old and intermediate-age stars. The only sign of current star formation in this big galaxy is the Hii region SH2, an isolated star cluster complex with a ring-like morphology and an estimated age of 0.1 Gyr at a galactocentric distance of about 35 kpc. A nearby intermediate-age globular cluster, surrounded by weak line emission and a few more young star clusters, is kinematically associated. The origin of this complex is enigmatic. Aims: We want to investigate the nature of this star cluster complex. The nebular emission lines permit a metallicity determination which can discriminate between a dwarf galaxy or other possible precursors. Methods: We used the Integral Field Unit (IFU) of the VIMOS instrument at the Very Large Telescope of the European Southern Observatory in high dispersion mode to study the morphology, kinematics, and metallicity employing line maps, velocity maps, and line diagnostics of a few characteristic spectra. Results: The line ratios of different spectra vary, indicating highly structured Hii regions, but define a locus of uniform metallicity. The strong-line diagnostic diagrams and empirical calibrations point to a nearly solar or even super-solar oxygen abundance. The velocity dispersion of the gas is highest in the region offset from the bright clusters. Star formation may be active on a low level. There is evidence for a large-scale disk-like structure in the region of SH2, which would make the similar radial velocity of the nearby globular cluster easier to understand. Conclusions: The high metallicity does not fit to a dwarf galaxy as progenitor. We favour the scenario of a free-floating gaseous complex having its origin in the merger 2 Gyr ago. Over a long period the densities increased secularly until finally the threshold for star formation was reached. SH2 illustrates how massive star clusters can form outside starbursts and without a considerable field

Epidemiology Analysis of Streptococcus pyogenes in a Hospital in Southern Taiwan by Use of the Updated emm Cluster Typing System.

Science.gov (United States)

Chiang-Ni, Chuan; Zheng, Po-Xing; Wang, Shu-Ying; Tsai, Pei-Jane; Chuang, Woei-Jer; Lin, Yee-Shin; Liu, Ching-Chuan; Wu, Jiunn-Jong

2016-01-01

emm typing is the most widely used molecular typing method for the human pathogen Streptococcus pyogenes (group A streptococcus [GAS]). emm typing is based on a small variable region of the emm gene; however, the emm cluster typing system defines GAS types according to the nearly complete sequence of the emm gene. Therefore, emm cluster typing is considered to provide more information regarding the functional and structural properties of M proteins in different emm types of GAS. In the present study, 677 isolates collected between 1994 and 2008 in a hospital in southern Taiwan were analyzed by the emm cluster typing system. emm clusters A-C4, E1, E6, and A-C3 were the most prevalent emm cluster types and accounted for 67.4% of total isolates. emm clusters A-C4 and E1 were associated with noninvasive diseases, whereas E6 was significantly associated with both invasive and noninvasive manifestations. In addition, emm clusters D4, E2, and E3 were significantly associated with invasive manifestations. Furthermore, we found that the functional properties of M protein, including low fibrinogen-binding and high IgG-binding activities, were correlated significantly with invasive manifestations. In summary, the present study provides updated epidemiological information on GAS emm cluster types in southern Taiwan. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Function and Regulation of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR / CRISPR Associated (Cas Systems

Directory of Open Access Journals (Sweden)

Peter C. Fineran

2012-10-01

Full Text Available Phages are the most abundant biological entities on earth and pose a constant challenge to their bacterial hosts. Thus, bacteria have evolved numerous ‘innate’ mechanisms of defense against phage, such as abortive infection or restriction/modification systems. In contrast, the clustered regularly interspaced short palindromic repeats (CRISPR systems provide acquired, yet heritable, sequence-specific ‘adaptive’ immunity against phage and other horizontally-acquired elements, such as plasmids. Resistance is acquired following viral infection or plasmid uptake when a short sequence of the foreign genome is added to the CRISPR array. CRISPRs are then transcribed and processed, generally by CRISPR associated (Cas proteins, into short interfering RNAs (crRNAs, which form part of a ribonucleoprotein complex. This complex guides the crRNA to the complementary invading nucleic acid and targets this for degradation. Recently, there have been rapid advances in our understanding of CRISPR/Cas systems. In this review, we will present the current model(s of the molecular events involved in both the acquisition of immunity and interference stages and will also address recent progress in our knowledge of the regulation of CRISPR/Cas systems.

Using Clustering Techniques To Detect Usage Patterns in a Web-based Information System.

Science.gov (United States)

Chen, Hui-Min; Cooper, Michael D.

2001-01-01

This study developed an analytical approach to detecting groups with homogenous usage patterns in a Web-based information system. Principal component analysis was used for data reduction, cluster analysis for categorizing usage into groups. The methodology was demonstrated and tested using two independent samples of user sessions from the…

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/.

A Novel Artificial Immune Algorithm for Spatial Clustering with Obstacle Constraint and Its Applications

Directory of Open Access Journals (Sweden)

Liping Sun

2014-01-01

Full Text Available An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

Implementing parallel elliptic solver on a Beowulf cluster

Directory of Open Access Journals (Sweden)

Marcin Paprzycki

1999-12-01

Full Text Available In a recent paper cite{zara} a parallel direct solver for the linear systems arising from elliptic partial differential equations has been proposed. The aim of this note is to present the initial evaluation of the performance characteristics of this algorithm on Beowulf-type cluster. In this context the performance of PVM and MPI based implementations is compared.

Fermion cluster algorithms

International Nuclear Information System (INIS)

Chandrasekharan, Shailesh

2000-01-01

Cluster algorithms have been recently used to eliminate sign problems that plague Monte-Carlo methods in a variety of systems. In particular such algorithms can also be used to solve sign problems associated with the permutation of fermion world lines. This solution leads to the possibility of designing fermion cluster algorithms in certain cases. Using the example of free non-relativistic fermions we discuss the ideas underlying the algorithm

Cluster Statistics of BTW Automata

International Nuclear Information System (INIS)

Ajanta Bhowal Acharyya

2011-01-01

The cluster statistics of BTW automata in the SOC states are obtained by extensive computer simulation. Various moments of the clusters are calculated and few results are compared with earlier available numerical estimates and exact results. Reasonably good agreement is observed. An extended statistical analysis has been made. (author)

SOS System Induction Inhibits the Assembly of Chemoreceptor Signaling Clusters in Salmonella enterica.

Science.gov (United States)

Irazoki, Oihane; Mayola, Albert; Campoy, Susana; Barbé, Jordi

2016-01-01

Swarming, a flagellar-driven multicellular form of motility, is associated with bacterial virulence and increased antibiotic resistance. In this work we demonstrate that activation of the SOS response reversibly inhibits swarming motility by preventing the assembly of chemoreceptor-signaling polar arrays. We also show that an increase in the concentration of the RecA protein, generated by SOS system activation, rather than another function of this genetic network impairs chemoreceptor polar cluster formation. Our data provide evidence that the molecular balance between RecA and CheW proteins is crucial to allow polar cluster formation in Salmonella enterica cells. Thus, activation of the SOS response by the presence of a DNA-injuring compound increases the RecA concentration, thereby disturbing the equilibrium between RecA and CheW and resulting in the cessation of swarming. Nevertheless, when the DNA-damage decreases and the SOS response is no longer activated, basal RecA levels and thus polar cluster assembly are reestablished. These results clearly show that bacterial populations moving over surfaces make use of specific mechanisms to avoid contact with DNA-damaging compounds.

CHEMODYNAMICS OF COMPACT STELLAR SYSTEMS IN NGC 5128: HOW SIMILAR ARE GLOBULAR CLUSTERS, ULTRA-COMPACT DWARFS, AND DWARF GALAXIES?

International Nuclear Information System (INIS)

Taylor, Matthew A.; Puzia, Thomas H.; Harris, Gretchen L.; Harris, William E.; Kissler-Patig, Markus; Hilker, Michael

2010-01-01

Velocity dispersion measurements are presented for several of the most luminous globular clusters (GCs) in NGC 5128 (Centaurus A) derived from high-resolution spectra obtained with the UVES echelle spectrograph on the 8.2 m ESO/Very Large Telescope. The measurements are made utilizing a penalized pixel-fitting method that parametrically recovers line-of-sight velocity dispersions. Combining the measured velocity dispersions with surface photometry and structural parameter data from the Hubble Space Telescope enables both dynamical masses and mass-to-light ratios to be derived. The properties of these massive stellar systems are similar to those of both massive GCs contained within the Local Group and nuclear star clusters and ultra-compact dwarf galaxies (UCDs). The fundamental plane relations of these clusters are investigated in order to fill the apparent gap between the relations of Local Group GCs and more massive early-type galaxies. It is found that the properties of these massive stellar systems match those of nuclear clusters in dwarf elliptical galaxies and UCDs better than those of Local Group GCs, and that all objects share similarly old (∼>8 Gyr) ages, suggesting a possible link between the formation and evolution of nuclear star clusters in dwarf elliptical galaxies (dE,Ns), UCDs, and massive GCs. We find a very steep correlation between dynamical mass-to-light ratio and dynamical mass of the form Υ V dyn ∝ M dyn 0.24±0.02 above M dyn ∼ 2x10 6 M sun . Formation scenarios are investigated with a chemical abundance analysis using absorption-line strengths calibrated to the Lick/IDS index system. The results lend support to two scenarios contained within a single general formation scheme. Old, massive, super-solar [α/Fe] systems are formed on short (∼ 13 -10 15 M sun potential wells of massive galaxies and galaxy clusters.

Data-Driven Packet Loss Estimation for Node Healthy Sensing in Decentralized Cluster

Directory of Open Access Journals (Sweden)

Hangyu Fan

2018-01-01

Full Text Available Decentralized clustering of modern information technology is widely adopted in various fields these years. One of the main reason is the features of high availability and the failure-tolerance which can prevent the entire system form broking down by a failure of a single point. Recently, toolkits such as Akka are used by the public commonly to easily build such kind of cluster. However, clusters of such kind that use Gossip as their membership managing protocol and use link failure detecting mechanism to detect link failures cannot deal with the scenario that a node stochastically drops packets and corrupts the member status of the cluster. In this paper, we formulate the problem to be evaluating the link quality and finding a max clique (NP-Complete in the connectivity graph. We then proposed an algorithm that consists of two models driven by data from application layer to respectively solving these two problems. Through simulations with statistical data and a real-world product, we demonstrate that our algorithm has a good performance.

Star clusters in evolving galaxies

Science.gov (United States)

Renaud, Florent

2018-04-01

Their ubiquity and extreme densities make star clusters probes of prime importance of galaxy evolution. Old globular clusters keep imprints of the physical conditions of their assembly in the early Universe, and younger stellar objects, observationally resolved, tell us about the mechanisms at stake in their formation. Yet, we still do not understand the diversity involved: why is star cluster formation limited to 105M⊙ objects in the Milky Way, while some dwarf galaxies like NGC 1705 are able to produce clusters 10 times more massive? Why do dwarfs generally host a higher specific frequency of clusters than larger galaxies? How to connect the present-day, often resolved, stellar systems to the formation of globular clusters at high redshift? And how do these links depend on the galactic and cosmological environments of these clusters? In this review, I present recent advances on star cluster formation and evolution, in galactic and cosmological context. The emphasis is put on the theory, formation scenarios and the effects of the environment on the evolution of the global properties of clusters. A few open questions are identified.

A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks.

Science.gov (United States)

Xu, Lina; O'Hare, Gregory M P; Collier, Rem

2017-07-05

Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work-Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity.

Energy Efficient Clustering Based Network Protocol Stack for 3D Airborne Monitoring System

Directory of Open Access Journals (Sweden)

Abhishek Joshi

2017-01-01

Full Text Available Wireless Sensor Network consists of large number of nodes densely deployed in ad hoc manner. Usually, most of the application areas of WSNs require two-dimensional (2D topology. Various emerging application areas such as airborne networks and underwater wireless sensor networks are usually deployed using three-dimensional (3D network topology. In this paper, a static 3D cluster-based network topology has been proposed for airborne networks. A network protocol stack consisting of various protocols such as TDMA MAC and dynamic routing along with services such as time synchronization, Cluster Head rotation, and power level management has been proposed for this airborne network. The proposed protocol stack has been implemented on the hardware platform consisting of number of TelosB nodes. This 3D airborne network architecture can be used to measure Air Quality Index (AQI in an area. Various parameters of network such as energy consumption, Cluster Head rotation, time synchronization, and Packet Delivery Ratio (PDR have been analyzed. Detailed description of the implementation of the protocol stack along with results of implementation has been provided in this paper.

Reactivity of Monolayer Protected Silver Clusters Towards Excess Ligand: A Calorimetric Study

KAUST Repository

Baksi, Ananya

2017-10-31

Reactivity of monolayer protected atomically precise clusters of noble metals is of significant research interest. Till date very few experimental data are available on the reaction thermodynamics of such clusters. Here we report a calorimetric study of the reaction of glutathione (GSH) protected silver clusters in presence of excess ligand, GSH using isothermal titration calorimetry (ITC). We have studied Ag11(SG)7 and Ag32(SG)19 clusters and compared their reactivity with GSH protected silver nanoparticles (AgNPs) and silver ions. Clusters show intermediate reactivity towards excess ligand com-pared to nanoparticles and silver ions. Several control experiments were performed to understand the degradation mech-anism of these silver clusters and nanoparticles. Effect of dissolved oxygen in the degradation process was studied in de-tail and found that it did not have a significant role, although alternate pathways of degradation with the involvement of oxygen cannot be ruled out. Direct confirmation of the fact that functionalized metal clusters fall in-between NPs and atomic systems in their stability is obtained experimentally for the first time. Several other thermophysical parameters of these clusters were also determined including, density, speed of sound, isentropic compressibility and coefficient of thermal expansion.

Clusters of Adolescent and Young Adult Thyroid Cancer in Florida Counties

Directory of Open Access Journals (Sweden)

Raid Amin

2014-01-01

Full Text Available Background. Thyroid cancer is a common cancer in adolescents and young adults ranking 4th in frequency. Thyroid cancer has captured the interest of epidemiologists because of its strong association to environmental factors. The goal of this study is to identify thyroid cancer clusters in Florida for the period 2000–2008. This will guide further discovery of potential risk factors within areas of the cluster compared to areas not in cluster. Methods. Thyroid cancer cases for ages 15–39 were obtained from the Florida Cancer Data System. Next, using the purely spatial Poisson analysis function in SaTScan, the geographic distribution of thyroid cancer cases by county was assessed for clusters. The reference population was obtained from the Census Bureau 2010, which enabled controlling for population age, sex, and race. Results. Two statistically significant clusters of thyroid cancer clusters were found in Florida: one in southern Florida (SF (relative risk of 1.26; P value of <0.001 and the other in northwestern Florida (NWF (relative risk of 1.71; P value of 0.012. These clusters persisted after controlling for demographics including sex, age, race. Conclusion. In summary, we found evidence of thyroid cancer clustering in South Florida and North West Florida for adolescents and young adult.

Special resonances in two- and three-cluster systems

International Nuclear Information System (INIS)

Orlowski, M.

1979-01-01

In the framework of Schmid's N-cluster theory the resonance theory of Wildermuth-Benoehr is extended to three clusters. This three-cluster resonance model is solved in a mathematically exact formalism. The main topic of this formalism is the asymptotic behaviour of the full three-body-resolvent in the differential directions of the six-dimensional position space of the Jacobi coordinates. The scattering amplitudes and cross sections in all two-body channels and breakup are explicitly presented. Furthermore a very illustrative kinematical three-body model, the so called 'three-body-neb', is developed. Special regards in this connection are devoted to the analysis of possible interference possibilities of the main three-body-resonance with other resonance types of the three-body model. In a further section the Pauli-resonances are studied i) in the Wildermuth resonating group theory, ii) in Schmid's simulation models. It is shown under which circumstances Pauli-resonances may be positive energy bound states. (orig./HSI) [de

Clustering applications in financial and economic analysis of the crop production in the Russian regions

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Gromov Vladislav Vladimirovich

2013-08-01

Full Text Available We used the complex mathematical modeling, multivariate statistical-analysis, fuzzy sets to analyze the financial and economic state of the crop production in Russian regions. We developed a system of indicators, detecting the state agricultural sector in the region, based on the results of correlation, factor, cluster analysis and statistics of the Federal State Statistics Service. We performed clustering analyses to divide regions of Russia on selected factors into five groups. A qualitative and quantitative characteristics of each cluster was received.

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

Science.gov (United States)

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

Análise de Clusters. Vantagens da Abordagem Baseada em Dinâmica de Sistemas

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Paula Karina Salume

2016-01-01

Full Text Available From a systemic and dynamic perspective, this theoretical essay aims to discuss how the process offormation and development of clusters can be analyzed. To do so, we review some pivotal studies inthe area such as the Marshallian perspective, the Italian case, the view of economic geography andthe competitiveness and innovation approach. Moreover, we review investigations based on dynamicapproaches for analyzing clusters such as the theory of the cluster life cycle and the system dynamics.We identify pieces of research that more recently have suggested the use of dynamics approaches basedon the fact that they adequate to capture the multiple facets of the process of formation and evolutionof spatial clusters. We conclude this essay by offering propositions for future empirical tests. Wehope that this essay guides the theoretical choices of the researchers interested in this research topic.

3D Viewer Platform of Cloud Clustering Management System: Google Map 3D

Science.gov (United States)

Choi, Sung-Ja; Lee, Gang-Soo

The new management system of framework for cloud envrionemnt is needed by the platfrom of convergence according to computing environments of changes. A ISV and small business model is hard to adapt management system of platform which is offered from super business. This article suggest the clustering management system of cloud computing envirionments for ISV and a man of enterprise in small business model. It applies the 3D viewer adapt from map3D & earth of google. It is called 3DV_CCMS as expand the CCMS[1].

Introduction to cluster dynamics

CERN Document Server

Reinhard, Paul-Gerhard

2008-01-01

Clusters as mesoscopic particles represent an intermediate state of matter between single atoms and solid material. The tendency to miniaturise technical objects requires knowledge about systems which contain a ""small"" number of atoms or molecules only. This is all the more true for dynamical aspects, particularly in relation to the qick development of laser technology and femtosecond spectroscopy. Here, for the first time is a highly qualitative introduction to cluster physics. With its emphasis on cluster dynamics, this will be vital to everyone involved in this interdisciplinary subje

Cluster approach to realization of innovation development strategy for the agroindustrial complex of the region

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Valentina Aleksandrovna Kundius

2011-12-01

Full Text Available This paper reviews cluster approach as an innovative management technology for the regional economy. The results of studying the theory and practice of clustering of the regional economy, the formation of agribusiness and food clusters in agribusiness are presented. Basic features and operation of the cluster systems are revealed and distinguished from other forms of cooperative and economic interactions between small and big business features, motivational components of integration into clusters. On the basis of scientific propositions, a model of regional economic clusters is formulated; specific territorial distribution and level of aggregation of clusters in the agricultural sector were distinguished. It is proposed to refer agroindustrial clusters to the clusters that represent the associations of organization of various fields in a single reproduction cycle from raw material to finished products sales including all stages of reproduction on the basis of innovation and investment activity. A structuring work on principles of agro-clusters was held, sustainable competitive advantage and the formation mechanisms of the development of agro-industrial clusters have been grounded.

CTEx Beowulf cluster for MCNP performance

International Nuclear Information System (INIS)

Gonzaga, Roberto N.; Amorim, Aneuri S. de; Balthar, Mario Cesar V.

2011-01-01

This work is an introduction to the CTEx Nuclear Defense Department's Beowulf Cluster. Building a Beowulf Cluster is a complex learning process that greatly depends upon your hardware and software requirements. The feasibility and efficiency of performing MCNP5 calculations with a small, heterogeneous computing cluster built in Red Hat's Fedora Linux operating system personal computers (PC) are explored. The performance increases that may be expected with such clusters are estimated for cases that typify general radiation transport calculations. Our results show that the speed increase from additional slave PCs is nearly linear up to 10 processors. The pre compiled parallel binary version of MCNP uses the Message-Passing Interface (MPI) protocol. The use of this pre compiled parallel version of MCNP5 with the MPI protocol on a small, heterogeneous computing cluster built from Red Hat's Fedora Linux operating system PCs is the subject of this work. (author)

Kinetic and radiation processes in cluster plasmas

International Nuclear Information System (INIS)

Smirnov, B.M.

1996-01-01

The analysis of processes is made for a cluster plasma which is a xenon arc plasma of a high pressure with an admixture of tungsten cluster ions. Because cluster ions emit radiation, this system is a light source which parameters are determined by various processes such as heat release and transport of charged particles in the plasma, radiative processes involving clusters, processes of cluster evaporation and attachment of atoms to it that leads to an equilibrium between clusters and vapor of their atoms, processes of cluster generation, processes of the ionization equilibrium between cluster ions and plasma electrons, transport of cluster ions in the discharge plasma in all directions. These processes govern by properties of a specific cluster plasma under consideration. (author)

Energy Efficient Routing in Wireless Sensor Networks Through Balanced Clustering

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Christos Douligeris

2013-01-01

Full Text Available The wide utilization of Wireless Sensor Networks (WSNs is obstructed by the severely limited energy constraints of the individual sensor nodes. This is the reason why a large part of the research in WSNs focuses on the development of energy efficient routing protocols. In this paper, a new protocol called Equalized Cluster Head Election Routing Protocol (ECHERP, which pursues energy conservation through balanced clustering, is proposed. ECHERP models the network as a linear system and, using the Gaussian elimination algorithm, calculates the combinations of nodes that can be chosen as cluster heads in order to extend the network lifetime. The performance evaluation of ECHERP is carried out through simulation tests, which evince the effectiveness of this protocol in terms of network energy efficiency when compared against other well-known protocols.

Individualization as driving force of clustering phenomena in humans.

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Michael Mäs

Full Text Available One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict "monoculture" in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in

The Astronomy of Africa's Health Systems Literature During the MDG Era: Where Are the Systems Clusters?

Science.gov (United States)

Phillips, James F; Sheff, Mallory; Boyer, Christopher B

2015-09-01

Growing international concern about the need for improved health systems in Africa has catalyzed an expansion of the health systems literature. This review applies a bibliometric procedure to analyze the acceleration of scientific writing on this theme. We focus on research published during the Millennium Development Goal (MDG) era between 1990 and 2014, reporting findings from a systematic review of a database comprised of 17,655 articles about health systems themes from sub-Saharan African countries or subregions. Using bibliometric tools for co-word textual analysis, we analyzed the incidence and associations of keywords and phrases to generate and visualize topical foci on health systems as clusters of themes, much in the manner that astronomers represent groupings of stars as galaxies of celestial entities. The association of keywords defines their relative position, with the size of images weighted by the relative frequency of terms. Sets of associated keywords are arrayed as stars that cluster as "galaxies" of concepts in the knowledge universe represented by health systems research from sub-Saharan Africa. Results show that health systems research is dominated by literature on diseases and categorical systems research topics, rather than on systems science that cuts across diseases or specific systemic themes. Systems research is highly developed in South Africa but relatively uncommon elsewhere in the region. "Black holes" are identified by searching for terms in our keyword library related to terms in widely cited reviews of health systems. Results identify several themes that are unexpectedly uncommon in the country-specific health systems literature. This includes research on the processes of achieving systems change, the health impact of systems strengthening, processes that explain the systems determinants of health outcomes, or systematic study of organizational dysfunction and ways to improve system performance. Research quantifying the relationship

Ethical implications of excessive cluster sizes in cluster randomised trials.

Science.gov (United States)

Hemming, Karla; Taljaard, Monica; Forbes, Gordon; Eldridge, Sandra M; Weijer, Charles

2018-02-20

The cluster randomised trial (CRT) is commonly used in healthcare research. It is the gold-standard study design for evaluating healthcare policy interventions. A key characteristic of this design is that as more participants are included, in a fixed number of clusters, the increase in achievable power will level off. CRTs with cluster sizes that exceed the point of levelling-off will have excessive numbers of participants, even if they do not achieve nominal levels of power. Excessively large cluster sizes may have ethical implications due to exposing trial participants unnecessarily to the burdens of both participating in the trial and the potential risks of harm associated with the intervention. We explore these issues through the use of two case studies. Where data are routinely collected, available at minimum cost and the intervention poses low risk, the ethical implications of excessively large cluster sizes are likely to be low (case study 1). However, to maximise the social benefit of the study, identification of excessive cluster sizes can allow for prespecified and fully powered secondary analyses. In the second case study, while there is no burden through trial participation (because the outcome data are routinely collected and non-identifiable), the intervention might be considered to pose some indirect risk to patients and risks to the healthcare workers. In this case study it is therefore important that the inclusion of excessively large cluster sizes is justifiable on other grounds (perhaps to show sustainability). In any randomised controlled trial, including evaluations of health policy interventions, it is important to minimise the burdens and risks to participants. Funders, researchers and research ethics committees should be aware of the ethical issues of excessively large cluster sizes in cluster trials. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

Science.gov (United States)

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

Conformational Clusters of Phosphorylated Tyrosine.

Science.gov (United States)

Abdelrasoul, Maha; Ponniah, Komala; Mao, Alice; Warden, Meghan S; Elhefnawy, Wessam; Li, Yaohang; Pascal, Steven M

2017-12-06

Tyrosine phosphorylation plays an important role in many cellular and intercellular processes including signal transduction, subcellular localization, and regulation of enzymatic activity. In 1999, Blom et al., using the limited number of protein data bank (PDB) structures available at that time, reported that the side chain structures of phosphorylated tyrosine (pY) are partitioned into two conserved conformational clusters ( Blom, N.; Gammeltoft, S.; Brunak, S. J. Mol. Biol. 1999 , 294 , 1351 - 1362 ). We have used the spectral clustering algorithm to cluster the increasingly growing number of protein structures with pY sites, and have found that the pY residues cluster into three distinct side chain conformations. Two of these pY conformational clusters associate strongly with a narrow range of tyrosine backbone conformation. The novel cluster also highly correlates with the identity of the n + 1 residue, and is strongly associated with a sequential pYpY conformation which places two adjacent pY side chains in a specific relative orientation. Further analysis shows that the three pY clusters are associated with distinct distributions of cognate protein kinases.

NUCORE - A system for nuclear structure calculations with cluster-core models

International Nuclear Information System (INIS)

Heras, C.A.; Abecasis, S.M.

1982-01-01

Calculation of nuclear energy levels and their electromagnetic properties, modelling the nucleus as a cluster of a few particles and/or holes interacting with a core which in turn is modelled as a quadrupole vibrator (cluster-phonon model). The members of the cluster interact via quadrupole-quadrupole and pairing forces. (orig.)

STAR CLUSTERS IN M31. IV. A COMPARATIVE ANALYSIS OF ABSORPTION LINE INDICES IN OLD M31 AND MILKY WAY CLUSTERS

International Nuclear Information System (INIS)

Schiavon, Ricardo P.; Caldwell, Nelson; Morrison, Heather; Harding, Paul; Courteau, Stéphane; MacArthur, Lauren A.; Graves, Genevieve J.

2012-01-01

We present absorption line indices measured in the integrated spectra of globular clusters both from the Galaxy and from M31. Our samples include 41 Galactic globular clusters, and more than 300 clusters in M31. The conversion of instrumental equivalent widths into the Lick system is described, and zero-point uncertainties are provided. Comparison of line indices of old M31 clusters and Galactic globular clusters suggests an absence of important differences in chemical composition between the two cluster systems. In particular, CN indices in the spectra of M31 and Galactic clusters are essentially consistent with each other, in disagreement with several previous works. We reanalyze some of the previous data, and conclude that reported CN differences between M31 and Galactic clusters were mostly due to data calibration uncertainties. Our data support the conclusion that the chemical compositions of Milky Way and M31 globular clusters are not substantially different, and that there is no need to resort to enhanced nitrogen abundances to account for the optical spectra of M31 globular clusters.

STAR CLUSTERS IN M31. IV. A COMPARATIVE ANALYSIS OF ABSORPTION LINE INDICES IN OLD M31 AND MILKY WAY CLUSTERS

Energy Technology Data Exchange (ETDEWEB)

Schiavon, Ricardo P. [Gemini Observatory, Hilo, HI 96720 (United States); Caldwell, Nelson [Smithsonian Astrophysical Observatory, Cambridge, MA 02138 (United States); Morrison, Heather; Harding, Paul [Department of Astronomy, Case Western Reserve University, Cleveland, OH 44106-7215 (United States); Courteau, Stephane [Department of Physics, Engineering Physics and Astronomy, Queen' s University, Kingston, ON K7L 3N6 (Canada); MacArthur, Lauren A. [Herzberg Institute of Astrophysics, National Research Council of Canada/University of Victoria, Victoria, B.C. V9E 2E7 (Canada); Graves, Genevieve J., E-mail: rschiavon@gemini.edu, E-mail: caldwell@cfa.harvard.edu, E-mail: paul.harding@case.edu, E-mail: heather@vegemite.case.edu, E-mail: courteau@astro.queensu.ca, E-mail: Lauren.MacArthur@nrc-cnrc.gc.ca, E-mail: graves@astro.berkeley.edu [Department of Astronomy, University of California, Berkeley, CA 94720 (United States)

2012-01-15

We present absorption line indices measured in the integrated spectra of globular clusters both from the Galaxy and from M31. Our samples include 41 Galactic globular clusters, and more than 300 clusters in M31. The conversion of instrumental equivalent widths into the Lick system is described, and zero-point uncertainties are provided. Comparison of line indices of old M31 clusters and Galactic globular clusters suggests an absence of important differences in chemical composition between the two cluster systems. In particular, CN indices in the spectra of M31 and Galactic clusters are essentially consistent with each other, in disagreement with several previous works. We reanalyze some of the previous data, and conclude that reported CN differences between M31 and Galactic clusters were mostly due to data calibration uncertainties. Our data support the conclusion that the chemical compositions of Milky Way and M31 globular clusters are not substantially different, and that there is no need to resort to enhanced nitrogen abundances to account for the optical spectra of M31 globular clusters.

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.

Space Transportation System Availability Relationships to Life Cycle Cost

Science.gov (United States)

Rhodes, Russel E.; Donahue, Benjamin B.; Chen, Timothy T.

2009-01-01

Future space transportation architectures and designs must be affordable. Consequently, their Life Cycle Cost (LCC) must be controlled. For the LCC to be controlled, it is necessary to identify all the requirements and elements of the architecture at the beginning of the concept phase. Controlling LCC requires the establishment of the major operational cost drivers. Two of these major cost drivers are reliability and maintainability, in other words, the system's availability (responsiveness). Potential reasons that may drive the inherent availability requirement are the need to control the number of unique parts and the spare parts required to support the transportation system's operation. For more typical space transportation systems used to place satellites in space, the productivity of the system will drive the launch cost. This system productivity is the resultant output of the system availability. Availability is equal to the mean uptime divided by the sum of the mean uptime plus the mean downtime. Since many operational factors cannot be projected early in the definition phase, the focus will be on inherent availability which is equal to the mean time between a failure (MTBF) divided by the MTBF plus the mean time to repair (MTTR) the system. The MTBF is a function of reliability or the expected frequency of failures. When the system experiences failures the result is added operational flow time, parts consumption, and increased labor with an impact to responsiveness resulting in increased LCC. The other function of availability is the MTTR, or maintainability. In other words, how accessible is the failed hardware that requires replacement and what operational functions are required before and after change-out to make the system operable. This paper will describe how the MTTR can be equated to additional labor, additional operational flow time, and additional structural access capability, all of which drive up the LCC. A methodology will be presented that

Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis

Directory of Open Access Journals (Sweden)

Rita Ismayilova

2014-01-01

Full Text Available Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent class cluster (LCC analysis on symptoms to determine clusters of brucellosis cases. A total of 454 cases reported between July 2011 and July 2013 were analyzed. LCC identified a two-cluster model and the Vuong-Lo-Mendell-Rubin likelihood ratio supported the cluster model. Brucellosis cases in the second cluster (19% reported higher percentages of poly-lymphadenopathy, hepatomegaly, arthritis, myositis, and neuritis and changes in liver function tests compared to cases of the first cluster. Patients in the second cluster had a severe brucellosis disease course and were associated with longer delay in seeking medical attention. Moreover, most of them were from Beylagan, a region focused on sheep and goat livestock production in south-central Azerbaijan. Patients in cluster 2 accounted for one-quarter of brucellosis cases and had a more severe clinical presentation. Delay in seeking medical care may explain severe illness. Future work needs to determine the factors that influence brucellosis case seeking and identify brucellosis species, particularly among cases from Beylagan.

Clustering of noise-induced oscillations

DEFF Research Database (Denmark)

Sosnovtseva, Olga; Fomin, A I; Postnov, D E

2001-01-01

The subject of our study is clustering in a population of excitable systems driven by Gaussian white noise and with randomly distributed coupling strength. The cluster state is frequency-locked state in which all functional units run at the same noise-induced frequency. Cooperative dynamics...

Dinamical properties of globular clusters: Primordial or evolutional?

Science.gov (United States)

Surdin, V. G.

1995-04-01

Some observable relations between globular cluster parameters appear as a result of dynamical evolution of the cluster system. These relations are inapplicable to the studies of the globular cluster origin

Electricity Consumption Clustering Using Smart Meter Data

Directory of Open Access Journals (Sweden)

Alexander Tureczek

2018-04-01

Full Text Available Electricity smart meter consumption data is enabling utilities to analyze consumption information at unprecedented granularity. Much focus has been directed towards consumption clustering for diversifying tariffs; through modern clustering methods, cluster analyses have been performed. However, the clusters developed exhibit a large variation with resulting shadow clusters, making it impossible to truly identify the individual clusters. Using clearly defined dwelling types, this paper will present methods to improve clustering by harvesting inherent structure from the smart meter data. This paper clusters domestic electricity consumption using smart meter data from the Danish city of Esbjerg. Methods from time series analysis and wavelets are applied to enable the K-Means clustering method to account for autocorrelation in data and thereby improve the clustering performance. The results show the importance of data knowledge and we identify sub-clusters of consumption within the dwelling types and enable K-Means to produce satisfactory clustering by accounting for a temporal component. Furthermore our study shows that careful preprocessing of the data to account for intrinsic structure enables better clustering performance by the K-Means method.

MANNER OF STOCKS SORTING USING CLUSTER ANALYSIS METHODS

Directory of Open Access Journals (Sweden)

Jana Halčinová

2014-06-01

Full Text Available The aim of the present article is to show the possibility of using the methods of cluster analysis in classification of stocks of finished products. Cluster analysis creates groups (clusters of finished products according to similarity in demand i.e. customer requirements for each product. Manner stocks sorting of finished products by clusters is described a practical example. The resultants clusters are incorporated into the draft layout of the distribution warehouse.

Improving clustering with metabolic pathway data.

Science.gov (United States)

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a

STAR CLUSTERS IN M31. II. OLD CLUSTER METALLICITIES AND AGES FROM HECTOSPEC DATA

International Nuclear Information System (INIS)

Caldwell, Nelson; Schiavon, Ricardo; Morrison, Heather; Harding, Paul; Rose, James A.

2011-01-01

We present new high signal-to-noise spectroscopic data on the M31 globular cluster (GC) system, obtained with the Hectospec multifiber spectrograph on the 6.5 m MMT. More than 300 clusters have been observed at a resolution of 5 A and with a median S/N of 75 per A, providing velocities with a median uncertainty of 6 km s -1 . The primary focus of this paper is the determination of mean cluster metallicities, ages, and reddenings. Metallicities were estimated using a calibration of Lick indices with [Fe/H] provided by Galactic GCs. These match well the metallicities of 24 M31 clusters determined from Hubble Space Telescope color-magnitude diagrams, the differences having an rms of 0.2 dex. The metallicity distribution is not generally bimodal, in strong distinction with the bimodal Galactic globular distribution. Rather, the M31 distribution shows a broad peak, centered at [Fe/H] = -1, possibly with minor peaks at [Fe/H] = -1.4, -0.7, and -0.2, suggesting that the cluster systems of M31 and the Milky Way had different formation histories. Ages for clusters with [Fe/H] > - 1 were determined using the automatic stellar population analysis program EZ A ges. We find no evidence for massive clusters in M31 with intermediate ages, those between 2 and 6 Gyr. Moreover, we find that the mean ages of the old GCs are remarkably constant over about a decade in metallicity (-0.95∼< [Fe/H] ∼<0.0).

Solvable single-species aggregation-annihilation model for chain-shaped cluster growth

International Nuclear Information System (INIS)

Ke Jianhong; Lin Zhenquan; Zheng Yizhuang; Chen Xiaoshuang; Lu Wei

2007-01-01

We propose a single-species aggregation-annihilation model, in which an aggregation reaction between two clusters produces an active cluster and an annihilation reaction produces an inert one. By means of the mean-field rate equation, we respectively investigate the kinetic scaling behaviours of three distinct systems. The results exhibit that: (i) for the general aggregation-annihilation system, the size distribution of active clusters consistently approaches the conventional scaling form; (ii) for the system with the self-degeneration of the cluster's activities, it takes the modified scaling form; and (iii) for the system with the self-closing of active clusters, it does not scale. Moreover, the size distribution of inert clusters with small size takes a power-law form, while that of large inert clusters obeys the scaling law. The results also show that all active clusters will eventually transform into inert ones and the inert clusters of any size can be produced by such an aggregation-annihilation process. This model can be used to mimic the chain-shaped cluster growth and can provide some useful predictions for the kinetic behaviour of the system

Reanalysis of 24 Nearby Open Clusters using Gaia data

Science.gov (United States)

Yen, Steffi X.; Reffert, Sabine; Röser, Siegfried; Schilbach, Elena; Kharchenko, Nina V.; Piskunov, Anatoly E.

2018-04-01

We have developed a fully automated cluster characterization pipeline, which simultaneously determines cluster membership and fits the fundamental cluster parameters: distance, reddening, and age. We present results for 24 established clusters and compare them to literature values. Given the large amount of stellar data for clusters available from Gaia DR2 in 2018, this pipeline will be beneficial to analyzing the parameters of open clusters in our Galaxy.

Intrinsic alignment of redMaPPer clusters: cluster shape-matter density correlation

Science.gov (United States)

van Uitert, Edo; Joachimi, Benjamin

2017-07-01

We measure the alignment of the shapes of galaxy clusters, as traced by their satellite distributions, with the matter density field using the public redMaPPer catalogue based on Sloan Digital Sky Survey-Data Release 8 (SDSS-DR8), which contains 26 111 clusters up to z ˜ 0.6. The clusters are split into nine redshift and richness samples; in each of them, we detect a positive alignment, showing that clusters point towards density peaks. We interpret the measurements within the tidal alignment paradigm, allowing for a richness and redshift dependence. The intrinsic alignment (IA) amplitude at the pivot redshift z = 0.3 and pivot richness λ = 30 is A_IA^gen=12.6_{-1.2}^{+1.5}. We obtain tentative evidence that the signal increases towards higher richness and lower redshift. Our measurements agree well with results of maxBCG clusters and with dark-matter-only simulations. Comparing our results to the IA measurements of luminous red galaxies, we find that the IA amplitude of galaxy clusters forms a smooth extension towards higher mass. This suggests that these systems share a common alignment mechanism, which can be exploited to improve our physical understanding of IA.

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.

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.

Examination of Clustering in Eutectic Microstrcture

Directory of Open Access Journals (Sweden)

Bortnyik K.

2017-06-01

Full Text Available The eutectic microstructures are complex microstructures and a hard work to describe it with few numbers. The eutectics builds up eutectic cells. In the cells the phases are clustered. With the development of big databases the data mining also develops, and produces a lot of method to handling the large datasets, and earns information from the sets. One typical method is the clustering, which finds the groups in the datasets. In this article a partitioning and a hierarchical clustering is applied to eutectic structures to find the clusters. In the case of AlMn alloy the K-means algorithm work well, and find the eutectic cells. In the case of ductile cast iron the hierarchical clustering works better. With the combination of the partitioning and hierarchical clustering with the image transformation, an effective method is developed for clustering the objects in the microstructures.

Cluster structures influenced by interaction with a surface.

Science.gov (United States)

Witt, Christopher; Dieterich, Johannes M; Hartke, Bernd

2018-05-30

Clusters on surfaces are vitally important for nanotechnological applications. Clearly, cluster-surface interactions heavily influence the preferred cluster structures, compared to clusters in vacuum. Nevertheless, systematic explorations and an in-depth understanding of these interactions and how they determine the cluster structures are still lacking. Here we present an extension of our well-established non-deterministic global optimization package OGOLEM from isolated clusters to clusters on surfaces. Applying this approach to intentionally simple Lennard-Jones test systems, we produce a first systematic exploration that relates changes in cluster-surface interactions to resulting changes in adsorbed cluster structures.

Examining the structural evolution of bicarbonate–water clusters: insights from photoelectron spectroscopy, basin-hopping structural search, and comparison with available IR spectral studies

Energy Technology Data Exchange (ETDEWEB)

Wen, Hui [Chinese Academy of Sciences (CAS), Hefei (China). Lab. of Atmospheric Physico-Chemistry, Anhui Inst. of Optics & Fine Mechanics; Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Physical Sciences Division; Hou, Gao-Lei [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Physical Sciences Division; Liu, Yi-Rong [Chinese Academy of Sciences (CAS), Hefei (China). Lab. of Atmospheric Physico-Chemistry, Anhui Inst. of Optics & Fine Mechanics; Wang, Xue-Bin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Physical Sciences Division; Huang, Wei [Chinese Academy of Sciences (CAS), Hefei (China). Lab. of Atmospheric Physico-Chemistry, Anhui Inst. of Optics & Fine Mechanics; Univ. of Science and Technology of China, Hefei (China). School of Environmental Science & Optoelectronic Technology

2016-05-31

Bicarbonate serves a crucial biochemical role in the physiological pH buffering system and also has important atmospheric implications. In the current study, HCO₃^$-$(H₂O)_n (n = 0-13) clusters were successfully produced via electrospray ionization of corresponding bulk salt solution, and were characterized by combining negative ion photoelectron spectroscopy and theoretical calculations. The photoelectron spectra reveal that the electron binding energy monotonically increases with the cluster size up to n = 10 and remains largely the same after n > 10. The photo-detaching feature of the solute HCO3$-$itself, which dominates in the small clusters, diminishes with increase of water coverage. Based on the charge distribution and molecular orbital analyses, the universal high electron binding energy tail that dominates in the larger clusters can be attributed to ionization of water. Thus, the transition of ionization from solute to solvent at the size larger than n=10 has been observed. Extensive theoretical structural search based on the Basin-Hopping unbiased method was carried out, and a plethora of low energy isomers have been obtained for each medium and large size. By comparing the simulated photoelectron spectra and calculated electron binding energies with the experiments, as well as by comparing the simulated infrared spectra with previously reported IR spectra, the probable global minima and the structural evolutionary routes are presented. The nature of bicarbonate-water interactions are mainly electrostatic as implied by the electron localization function (ELF) analysis.

A heart disease recognition embedded system with fuzzy cluster algorithm.

Science.gov (United States)

de Carvalho, Helton Hugo; Moreno, Robson Luiz; Pimenta, Tales Cleber; Crepaldi, Paulo C; Cintra, Evaldo

2013-06-01

This article presents the viability analysis and the development of heart disease identification embedded system. It offers a time reduction on electrocardiogram - ECG signal processing by reducing the amount of data samples, without any significant loss. The goal of the developed system is the analysis of heart signals. The ECG signals are applied into the system that performs an initial filtering, and then uses a Gustafson-Kessel fuzzy clustering algorithm for the signal classification and correlation. The classification indicated common heart diseases such as angina, myocardial infarction and coronary artery diseases. The system uses the European electrocardiogram ST-T Database (EDB) as a reference for tests and evaluation. The results prove the system can perform the heart disease detection on a data set reduced from 213 to just 20 samples, thus providing a reduction to just 9.4% of the original set, while maintaining the same effectiveness. This system is validated in a Xilinx Spartan(®)-3A FPGA. The field programmable gate array (FPGA) implemented a Xilinx Microblaze(®) Soft-Core Processor running at a 50MHz clock rate. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.