WorldWideScience

Sample records for gene-oriented clustering tool

  1. Chromosome Gene Orientation Inversion Networks (GOINs) of Plasmodium Proteome.

    Science.gov (United States)

    Quevedo-Tumailli, Viviana F; Ortega-Tenezaca, Bernabé; González-Díaz, Humbert

    2018-03-02

    The spatial distribution of genes in chromosomes seems not to be random. For instance, only 10% of genes are transcribed from bidirectional promoters in humans, and many more are organized into larger clusters. This raises intriguing questions previously asked by different authors. We would like to add a few more questions in this context, related to gene orientation inversions. Does gene orientation (inversion) follow a random pattern? Is it relevant to biological activity somehow? We define a new kind of network coined as the gene orientation inversion network (GOIN). GOIN's complex network encodes short- and long-range patterns of inversion of the orientation of pairs of gene in the chromosome. We selected Plasmodium falciparum as a case of study due to the high relevance of this parasite to public health (causal agent of malaria). We constructed here for the first time all of the GOINs for the genome of this parasite. These networks have an average of 383 nodes (genes in one chromosome) and 1314 links (pairs of gene with inverse orientation). We calculated node centralities and other parameters of these networks. These numerical parameters were used to study different properties of gene inversion patterns, for example, distribution, local communities, similarity to Erdös-Rényi random networks, randomness, and so on. We find clues that seem to indicate that gene orientation inversion does not follow a random pattern. We noted that some gene communities in the GOINs tend to group genes encoding for RIFIN-related proteins in the proteome of the parasite. RIFIN-like proteins are a second family of clonally variant proteins expressed on the surface of red cells infected with Plasmodium falciparum. Consequently, we used these centralities as input of machine learning (ML) models to predict the RIFIN-like activity of 5365 proteins in the proteome of Plasmodium sp. The best linear ML model found discriminates RIFIN-like from other proteins with sensitivity and

  2. Cluster development in the SA tooling industry

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    Von Leipzig, Konrad

    2015-11-01

    Full Text Available This paper explores the concept of clustering in general, analysing research and experiences in different countries and regions, and summarising factors leading to success or contributing to failure of specific cluster initiatives. Based on this, requirements for the establishment of clusters are summarised. Next, initiatives especially in the South African tool and die making (TDM industry are considered. Through a benchmarking approach, the strengths and weaknesses of individual local tool rooms are analysed, and conclusions are drawn particularly about South African characteristics of the industry. From these results, and from structured interviews with individual tool room owners, difficulties in the establishment of a South African tooling cluster are explored, and specific areas of concern are pointed out.

  3. Design tool for offshore wind farm clusters

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Giebel, Gregor; Waldl, Igor

    2015-01-01

    . The software includes wind farm wake models, energy yield models, inter-array and long cable and grid component models, grid code compliance and ancillary services models. The common score for evaluation in order to compare different layouts is levelized cost of energy (LCoE). The integrated DTOC software...... Research Alliance (EERA) and a number of industrial partners. The approach has been to develop a robust, efficient, easy to use and flexible tool, which integrates software relevant for planning offshore wind farms and wind farm clusters and supports the user with a clear optimization work flow...... is developed within the project using open interface standards and is now available as the commercial software product Wind&Economy....

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

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    Jae-Woo Chang

    2005-02-01

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

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

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    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/.

  6. Network Analysis Tools: from biological networks to clusters and pathways.

    Science.gov (United States)

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

    2008-01-01

    Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

  7. CATCHprofiles: Clustering and Alignment Tool for ChIP Profiles

    DEFF Research Database (Denmark)

    G. G. Nielsen, Fiona; Galschiøt Markus, Kasper; Møllegaard Friborg, Rune

    2012-01-01

    IP-profiling data and detect potentially meaningful patterns, the areas of enrichment must be aligned and clustered, which is an algorithmically and computationally challenging task. We have developed CATCHprofiles, a novel tool for exhaustive pattern detection in ChIP profiling data. CATCHprofiles is built upon...... a computationally efficient implementation for the exhaustive alignment and hierarchical clustering of ChIP profiling data. The tool features a graphical interface for examination and browsing of the clustering results. CATCHprofiles requires no prior knowledge about functional sites, detects known binding patterns...... it an invaluable tool for explorative research based on ChIP profiling data. CATCHprofiles and the CATCH algorithm run on all platforms and is available for free through the CATCH website: http://catch.cmbi.ru.nl/. User support is available by subscribing to the mailing list catch-users@bioinformatics.org....

  8. Design tool for offshore wind farm cluster planning

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Madsen, Peter Hauge; Giebel, Gregor

    2015-01-01

    In the framework of the FP7 project EERA DTOC: Design Tool for Offshore wind farm Cluster, a new software supporting the planning of offshore wind farms was developed, based on state-of-the-art approaches from large scale wind potential to economic benchmarking. The model portfolio includes WAs......P, FUGA, WRF, Net-Op, LCoE model, CorWind, FarmFlow, EeFarm and grid code compliance calculations. The development is done by members from European Energy Research Alliance (EERA) and guided by several industrial partners. A commercial spin-off from the project is the tool ‘Wind & Economy’. The software...... by the software and several tests were performed. The calculations include the smoothing effect on produced energy between wind farms located in different regional wind zones and the short time scales relevant for assessing balancing power. The grid code compliance was tested for several cases and the results...

  9. Clustering and Flow Conservation Monitoring Tool for Software Defined Networks

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    Jesús Antonio Puente Fernández

    2018-04-01

    Full Text Available Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN is a new concept of network architecture that provides the separation of control plane (controller and data plane (switches in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

  10. Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.

    Science.gov (United States)

    Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon

    2018-04-03

    Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

  11. XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

    Science.gov (United States)

    2015-01-01

    Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

  12. Educational clusters as a tool ofpublic policy on the market of educational services

    OpenAIRE

    M. I. Vorona

    2016-01-01

    Due to the new challenges, the implementation of cluster technology can be considired to be one of the innovative and promising tools of national and regional economy’ competitiveness raise. The cluster approach can be used is in different areas, but most attention in thie article has been paid to the problems of industrial clusters. At the same time, educational clusters remain to be poorly implemented in practice and, consequently, they are less studied theoretically. The aim of the arti...

  13. Cluster Analysis as an Analytical Tool of Population Policy

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    Oksana Mikhaylovna Shubat

    2017-12-01

    Full Text Available The predicted negative trends in Russian demography (falling birth rates, population decline actualize the need to strengthen measures of family and population policy. Our research purpose is to identify groups of Russian regions with similar characteristics in the family sphere using cluster analysis. The findings should make an important contribution to the field of family policy. We used hierarchical cluster analysis based on the Ward method and the Euclidean distance for segmentation of Russian regions. Clustering is based on four variables, which allowed assessing the family institution in the region. The authors used the data of Federal State Statistics Service from 2010 to 2015. Clustering and profiling of each segment has allowed forming a model of Russian regions depending on the features of the family institution in these regions. The authors revealed four clusters grouping regions with similar problems in the family sphere. This segmentation makes it possible to develop the most relevant family policy measures in each group of regions. Thus, the analysis has shown a high degree of differentiation of the family institution in the regions. This suggests that a unified approach to population problems’ solving is far from being effective. To achieve greater results in the implementation of family policy, a differentiated approach is needed. Methods of multidimensional data classification can be successfully applied as a relevant analytical toolkit. Further research could develop the adaptation of multidimensional classification methods to the analysis of the population problems in Russian regions. In particular, the algorithms of nonparametric cluster analysis may be of relevance in future studies.

  14. Cluster analysis as a prediction tool for pregnancy outcomes.

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    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  15. Optically-Selected Cluster Catalogs As a Precision Cosmology Tool

    Energy Technology Data Exchange (ETDEWEB)

    Rozo, Eduardo; /Ohio State U. /Chicago U. /KICP, Chicago; Wechsler, Risa H.; /KICP, Chicago /KIPAC, Menlo Park; Koester, Benjamin P.; /Michigan U. /Chicago U., Astron.; Evrard, August E.; McKay, Timothy A.; /Michigan U.

    2007-03-26

    We introduce a framework for describing the halo selection function of optical cluster finders. We treat the problem as being separable into a term that describes the intrinsic galaxy content of a halo (the Halo Occupation Distribution, or HOD) and a term that captures the effects of projection and selection by the particular cluster finding algorithm. Using mock galaxy catalogs tuned to reproduce the luminosity dependent correlation function and the empirical color-density relation measured in the SDSS, we characterize the maxBCG algorithm applied by Koester et al. to the SDSS galaxy catalog. We define and calibrate measures of completeness and purity for this algorithm, and demonstrate successful recovery of the underlying cosmology and HOD when applied to the mock catalogs. We identify principal components--combinations of cosmology and HOD parameters--that are recovered by survey counts as a function of richness, and demonstrate that percent-level accuracies are possible in the first two components, if the selection function can be understood to {approx} 15% accuracy.

  16. Cluster Flow: A user-friendly bioinformatics workflow tool [version 1; referees: 3 approved

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    Philip Ewels

    2016-12-01

    Full Text Available Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

  17. Clusters of galaxies as tools in observational cosmology : results from x-ray analysis

    International Nuclear Information System (INIS)

    Weratschnig, J.M.

    2009-01-01

    Clusters of galaxies are the largest gravitationally bound structures in the universe. They can be used as ideal tools to study large scale structure formation (e.g. when studying merger clusters) and provide highly interesting environments to analyse several characteristic interaction processes (like ram pressure stripping of galaxies, magnetic fields). In this dissertation thesis, we have studied several clusters of galaxies using X-ray observations. To obtain scientific results, we have applied different data reduction and analysis methods. With a combination of morphological and spectral analysis, the merger cluster Abell 514 was studied in much detail. It has a highly interesting morphology and shows signs for an ongoing merger as well as a shock. using a new method to detect substructure, we have analysed several clusters to determine whether any substructure is present in the X-ray image. This hints towards a real structure in the distribution of the intra-cluster medium (ICM) and is evidence for ongoing mergers. The results from this analysis are extensively used with the cluster of galaxies Abell S1136. Here, we study the ICM distribution and compare its structure with the spatial distribution of star forming galaxies. Cluster magnetic fields are another important topic of my thesis. They can be studied in Radio observations, which can be put into relation with results from X-ray observations. using observational data from several clusters, we could support the theory that cluster magnetic fields are frozen into the ICM. (author)

  18. Clustering Algorithm As A Planning Support Tool For Rural Electrification Optimization

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    Ronaldo Pornillosa Parreno Jr

    2015-08-01

    Full Text Available Abstract In this study clustering algorithm was developed to optimize electrification plans by screening and grouping potential customers to be supplied with electricity. The algorithm provided adifferent approach in clustering problem which combines conceptual and distance-based clustering algorithmsto analyze potential clusters using spanning tree with the shortest possible edge weight and creating final cluster trees based on the test of inconsistency for the edges. The clustering criteria consists of commonly used distance measure with the addition of household information as basis for the ability to pay ATP value. The combination of these two parameters resulted to a more significant and realistic clusters since distance measure alone could not take the effect of the household characteristics in screening the most sensible groupings of households. In addition the implications of varying geographical features were incorporated in the algorithm by using routing index across the locations of the households. This new approach of connecting the households in an area was applied in an actual case study of one village or barangay that was not yet energized. The results of clustering algorithm generated cluster trees which could becomethetheoretical basis for power utilities to plan the initial network arrangement of electrification. Scenario analysis conducted on the two strategies of clustering the households provideddifferent alternatives for the optimization of the cost of electrification. Futhermorethe benefits associated with the two strategies formulated from the two scenarios was evaluated using benefit cost ratio BC to determine which is more economically advantageous. The results of the study showed that clustering algorithm proved to be effective in solving electrification optimization problem and serves its purpose as a planning support tool which can facilitate electrification in rural areas and achieve cost-effectiveness.

  19. 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.

  20. Topological clustering as a tool for planning water quality monitoring in water distribution networks

    DEFF Research Database (Denmark)

    Kirstein, Jonas Kjeld; Albrechtsen, Hans-Jørgen; Rygaard, Martin

    2015-01-01

    ) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided...... into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Nørrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers...... particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist...

  1. On the blind use of statistical tools in the analysis of globular cluster stars

    Science.gov (United States)

    D'Antona, Francesca; Caloi, Vittoria; Tailo, Marco

    2018-04-01

    As with most data analysis methods, the Bayesian method must be handled with care. We show that its application to determine stellar evolution parameters within globular clusters can lead to paradoxical results if used without the necessary precautions. This is a cautionary tale on the use of statistical tools for big data analysis.

  2. Peac – A set of tools to quickly enable Proof on a cluster

    International Nuclear Information System (INIS)

    Ganis, G; Vala, M

    2012-01-01

    With advent of the analysis phase of Lhcdata-processing, interest in Proof technology has considerably increased. While setting up a simple Proof cluster for basic usage is reasonably straightforward, exploiting the several new functionalities added in recent times may be complicated. Peac, standing for Proof Enabled Analysis Cluster, is a set of tools aiming to facilitate the setup and management of a Proof cluster. Peac is based on the experience made by setting up Proof for the Alice analysis facilities. It allows to easily build and configure Root and the additional software needed on the cluster, and may serve as distributor of binaries via Xrootd. Peac uses Proof-On-Demand (PoD) for resource management (start, stop or daemons). Finally, Peac sets-up and configures dataset management (using the Afdsmgrd daemon), as well as cluster monitoring (machine status and Proof query summaries) using MonAlisa. In this respect, a MonAlisa page has been dedicated to Peac users, so that a cluster managed by Peac can be automatically monitored. In this paper we present and describe the status and main components of Peac and show details about its usage.

  3. Cluster tool for in situ processing and comprehensive characteriza tion of thin films at high temperatures.

    Science.gov (United States)

    Wenisch, Robert; Lungwitz, Frank; Hanf, Daniel; Heller, Rene; Zscharschuch, Jens; Hübner, René; von Borany, Johannes; Abrasonis, Gintautas; Gemming, Sibylle; Escobar-Galindo, Ramon; Krause, Matthias

    2018-05-31

    A new cluster tool for in situ real-time processing and depth-resolved compositional, structural and optical characterization of thin films at temperatures from -100 to 800 °C is described. The implemented techniques comprise magnetron sputtering, ion irradiation, Rutherford backscattering spectrometry, Raman spectroscopy and spectroscopic ellipsometry. The capability of the cluster tool is demonstrated for a layer stack MgO/ amorphous Si (~60 nm)/ Ag (~30 nm), deposited at room temperature and crystallized with partial layer exchange by heating up to 650°C. Its initial and final composition, stacking order and structure were monitored in situ in real time and a reaction progress was defined as a function of time and temperature.

  4. Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wucherl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koo, Michelle [Univ. of California, Berkeley, CA (United States); Cao, Yu [California Inst. of Technology (CalTech), Pasadena, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nugent, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Wu, Kesheng [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-09-17

    Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

  5. Server consolidation for heterogeneous computer clusters using Colored Petri Nets and CPN Tools

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    Issam Al-Azzoni

    2015-10-01

    Full Text Available In this paper, we present a new approach to server consolidation in heterogeneous computer clusters using Colored Petri Nets (CPNs. Server consolidation aims to reduce energy costs and improve resource utilization by reducing the number of servers necessary to run the existing virtual machines in the cluster. It exploits the emerging technology of live migration which allows migrating virtual machines between servers without stopping their provided services. Server consolidation approaches attempt to find migration plans that aim to minimize the necessary size of the cluster. Our approach finds plans which not only minimize the overall number of used servers, but also minimize the total data migration overhead. The latter objective is not taken into consideration by other approaches and heuristics. We explore the use of CPN Tools in analyzing the state spaces of the CPNs. Since the state space of the CPN model can grow exponentially with the size of the cluster, we examine different techniques to generate and analyze the state space in order to find good plans to server consolidation within acceptable time and computing power.

  6. Cluster analysis as a tool of guests segmentation by the degree of their demand

    Directory of Open Access Journals (Sweden)

    Damijan Mumel

    2002-01-01

    Full Text Available Authors demonstrate the use of cluster analysis in finding out (ascertaining the homogenity/heterogenity of guests as to the degree of their demand. The degree of guests’ demand is defined according to the importance of perceived service quality components measured by SERVQUAL, which was adopted and adapted, according to the specifics of health spa industry in Slovenia. Goals of the article are: (a the identification of the profile of importance of general health spa service quality components, and (b the identification of groups of guests (segments according to the degree of their demand in the research in 1991 compared with 1999. Cluster analysis serves as useful tool for guest segmentation since it reveals the existence of important differences in the structure of guests in the year 1991 compared with the year 1999. The results serve as a useful database for management in health spas.

  7. piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER.

    Science.gov (United States)

    Ray, Rishav; Pandey, Priyanka

    2017-12-19

    With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. GraphCrunch 2: Software tool for network modeling, alignment and clustering.

    Science.gov (United States)

    Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

    2011-01-19

    Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an

  9. GraphCrunch 2: Software tool for network modeling, alignment and clustering

    Directory of Open Access Journals (Sweden)

    Hayes Wayne

    2011-01-01

    Full Text Available Abstract Background Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. Results We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL" for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other

  10. Physics development of web-based tools for use in hardware clusters doing lattice physics

    International Nuclear Information System (INIS)

    Dreher, P.; Akers, W.; Chen, J.; Chen, Y.; Watson, C.

    2002-01-01

    Jefferson Lab and MIT are developing a set of web-based tools within the Lattice Hadron Physics Collaboration to allow lattice QCD theorists to treat the computational facilities located at the two sites as a single meta-facility. The prototype Lattice Portal provides researchers the ability to submit jobs to the cluster, browse data caches, and transfer files between cache and off-line storage. The user can view the configuration of the PBS servers and to monitor both the status of all batch queues as well as the jobs in each queue. Work is starting on expanding the present system to include job submissions at the meta-facility level (shared queue), as well as multi-site file transfers and enhanced policy-based data management capabilities

  11. Physics development of web-based tools for use in hardware clusters doing lattice physics

    International Nuclear Information System (INIS)

    Dreher, P.; Akers, Walt; Jian-ping Chen; Chen, Y.; William, A. Watson III

    2001-01-01

    Jefferson Lab and MIT are developing a set of web-based tools within the Lattice Hadron Physics Collaboration to allow lattice QCD theorists to treat the computational facilities located at the two sites as a single meta-facility. The prototype Lattice Portal provides researchers the ability to submit jobs to the cluster, browse data caches, and transfer files between cache and off-line storage. The user can view the configuration of the PBS servers and to monitor both the status of all batch queues as well as the jobs in each queue. Work is starting on expanding the present system to include job submissions at the meta-facility level (shared queue), as well as multi-site file transfers and enhanced policy-based data management capabilities

  12. The concept of cluster- villages as planning tool in the rural districts of Denmark

    DEFF Research Database (Denmark)

    Laursen, Lea Louise Holst; Møller, Jørgen

    on economies of scale, or the decentralised model based on proximity. In the developments and debate relating to these matters, strategic and visionary planning is back in the municipal arena as the only tool capable of handling the many different challenges facing the municipalities. Mellem disse...... and uses each other’s strengths, as well as developing the individual village in addition to the specific potentials of that village. In recent years, rural Denmark has been undergoing a sweeping and very noticeable process of adjustment, Development in municipal service provision plays a particular...... to forskellige positioner ser vi en ny mulighed for landsbyudvikling, som vi kalder Clustervillages. In order to investigate the potentials and possibilities of the cluster-village concept the paper will seek to unfold the concept strategically; looking into the benefits of such concept. Further, the paper seeks...

  13. Physics development of web-based tools for use in hardware clusters doing lattice physics

    Energy Technology Data Exchange (ETDEWEB)

    Dreher, P.; Akers, W.; Chen, J.; Chen, Y.; Watson, C

    2002-03-01

    Jefferson Lab and MIT are developing a set of web-based tools within the Lattice Hadron Physics Collaboration to allow lattice QCD theorists to treat the computational facilities located at the two sites as a single meta-facility. The prototype Lattice Portal provides researchers the ability to submit jobs to the cluster, browse data caches, and transfer files between cache and off-line storage. The user can view the configuration of the PBS servers and to monitor both the status of all batch queues as well as the jobs in each queue. Work is starting on expanding the present system to include job submissions at the meta-facility level (shared queue), as well as multi-site file transfers and enhanced policy-based data management capabilities.

  14. EERA-DTOC Project: Design Tools for Offshore Wind Farm Clusters; Proyecto EERA-DTOC: herramientas para el diseno de clusters de Parques Eolicos Marinos

    Energy Technology Data Exchange (ETDEWEB)

    Palomares, A. M.

    2015-07-01

    In the EERA-DTOC Project an integrated and validated software design tool for the optimization of offshore wind farms and wind farm clusters has been developed. The CIEMAT contribution to this project has change the view on mesoscale wind forecasting models, which were not so far considered capable of modeling wind farm scale phenomena. It has been shown the ability of the WRF model to simulate the wakes caused by the wind turbines on the downwind ones (inter-turbine wakes within a wind farm) as well as the wakes between wind farms within a cluster. (Author)

  15. ASPECT: A spectra clustering tool for exploration of large spectral surveys

    Science.gov (United States)

    in der Au, A.; Meusinger, H.; Schalldach, P. F.; Newholm, M.

    2012-11-01

    Context. Analysing the empirical output from large surveys is an important challenge in contemporary science. Difficulties arise, in particular, when the database is huge and the properties of the object types to be selected are poorly constrained a priori. Aims: We present the novel, semi-automated clustering tool ASPECT for analysing voluminous archives of spectra. Methods: The heart of the program is a neural network in the form of a Kohonen self-organizing map. The resulting map is designed as an icon map suitable for the inspection by eye. The visual analysis is supported by the option to blend in individual object properties such as redshift, apparent magnitude, or signal-to-noise ratio. In addition, the package provides several tools for the selection of special spectral types, e.g. local difference maps which reflect the deviations of all spectra from one given input spectrum (real or artificial). Results: ASPECT is able to produce a two-dimensional topological map of a huge number of spectra. The software package enables the user to browse and navigate through a huge data pool and helps them to gain an insight into underlying relationships between the spectra and other physical properties and to get the big picture of the entire data set. We demonstrate the capability of ASPECT by clustering the entire data pool of ~6 × 105 spectra from the Data Release 4 of the Sloan Digital Sky Survey (SDSS). To illustrate the results regarding quality and completeness we track objects from existing catalogues of quasars and carbon stars, respectively, and connect the SDSS spectra with morphological information from the GalaxyZoo project. Code is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/547/A115

  16. clusters

    Indian Academy of Sciences (India)

    2017-09-27

    Sep 27, 2017 ... Author for correspondence (zh4403701@126.com). MS received 15 ... lic clusters using density functional theory (DFT)-GGA of the DMOL3 package. ... In the process of geometric optimization, con- vergence thresholds ..... and Postgraduate Research & Practice Innovation Program of. Jiangsu Province ...

  17. clusters

    Indian Academy of Sciences (India)

    environmental as well as technical problems during fuel gas utilization. ... adsorption on some alloys of Pd, namely PdAu, PdAg ... ried out on small neutral and charged Au24,26,27, Cu,28 ... study of Zanti et al.29 on Pdn (n = 1–9) clusters.

  18. The Whisper Relaxation Sounder onboard Cluster: A Powerful Tool for Space Plasma Diagnosis around the Earth

    International Nuclear Information System (INIS)

    Trotignon, J.G.; Decreau, P.M.E.; Rauch, J.L.; LeGuirriec, E.; Canu, P.; Darrouzet, F.

    2001-01-01

    The WHISPER relaxation sounder that is onboard the four CLUSTER spacecraft has for main scientific objectives to monitor the natural waves in the 2 kHz - 80 kHz frequency range and, mostly, to determine the total plasma density from the solar wind down to the Earth's plasmasphere. To fulfil these objectives, the WHISPER uses the two long double sphere antennae of the Electric Field and Wave experiment as transmitting and receiving sensors. In its active working mode, the WHISPER works according to principles that have been worked out for topside sounding. A radio wave transmitter sends an almost monochromatic and short wave train. A few milliseconds after, a receiver listens to the surrounding plasma response. Strong and long lasting echoes are actually received whenever the transmitting frequencies coincide with characteristic plasma frequencies. Provided that these echoes, also called resonances, may be identified, the WHISPER relaxation sounder becomes a reliable and powerful tool for plasma diagnosis. When the transmitter is off, the WHISPER behaves like a passive receiver, allowing natural waves to be monitored. The paper aims mainly at the resonance identification process description and the WHISPER capabilities and performance highlighting. (author)

  19. Quasi-free experiments as a tool for the study of 6Li cluster structure

    International Nuclear Information System (INIS)

    Lattuada, M.; Riggi, F.; Spitaleri, C.; Vinciguerra, D.

    1984-01-01

    The value of the α-d clustering probability in 6 Li deduced from quasi-free experiments may be influenced by the choice of the inter-cluster wave function. Several functional forms usually taken to describe the relative motion of the two clusters have been examined. The effect of the choice of the intercluster wave function on the information deduced by analysing quasi-free data in the plane-wave impulse approximation was investigated

  20. New spectroscopic tool for cluster science: Nonexponential laser fluence dependence of photofragmentation

    International Nuclear Information System (INIS)

    Haberland, H.; Issendorff, B.v.

    1996-01-01

    The photodestruction of Hg 7 ++ and Hg 9 ++ has been measured as a function of photon flux. A polarization dependent deviation from a purely exponential intensity decrease was observed in both cases. This effect, which in essence is an alignment phenomenon, can be used to characterize dissociating electronic transitions of molecules and clusters. For the clusters studied it is due to a one-dimensional transition dipole moment having a fixed direction within the cluster. The effect is expected to play a role in many photoabsorption experiments where molecule/cluster ionization or fragmentation is studied under high photon fluxes. copyright 1996 The American Physical Society

  1. ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands.

    NARCIS (Netherlands)

    Groeneveld, Geert H; Dalhuijsen, Anton; Kara-Zaïtri, Chakib; Hamilton, Bob; de Waal, Margot W; van Dissel, Jaap T; van Steenbergen, Jim E

    2017-01-01

    Clusters of infectious diseases are frequently detected late. Real-time, detailed information about an evolving cluster and possible associated conditions is essential for local policy makers, travelers planning to visit the area, and the local population. This is currently illustrated in the Zika

  2. The "p"-Median Model as a Tool for Clustering Psychological Data

    Science.gov (United States)

    Kohn, Hans-Friedrich; Steinley, Douglas; Brusco, Michael J.

    2010-01-01

    The "p"-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around "exemplars", that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of…

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

    Science.gov (United States)

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

    2018-05-25

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

  4. Homo-FRET imaging as a tool to quantify protein and lipid clustering.

    Science.gov (United States)

    Bader, Arjen N; Hoetzl, Sandra; Hofman, Erik G; Voortman, Jarno; van Bergen en Henegouwen, Paul M P; van Meer, Gerrit; Gerritsen, Hans C

    2011-02-25

    Homo-FRET, Förster resonance energy transfer between identical fluorophores, can be conveniently measured by observing its effect on the fluorescence anisotropy. This review aims to summarize the possibilities of fluorescence anisotropy imaging techniques to investigate clustering of identical proteins and lipids. Homo-FRET imaging has the ability to determine distances between fluorophores. In addition it can be employed to quantify cluster sizes as well as cluster size distributions. The interpretation of homo-FRET signals is complicated by the fact that both the mutual orientations of the fluorophores and the number of fluorophores per cluster affect the fluorescence anisotropy in a similar way. The properties of the fluorescence probes are very important. Taking these properties into account is critical for the correct interpretation of homo-FRET signals in protein- and lipid-clustering studies. This is be exemplified by studies on the clustering of the lipid raft markers GPI and K-ras, as well as for EGF receptor clustering in the plasma membrane. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. X ray emission: a tool and a probe for laser - clusters interaction

    International Nuclear Information System (INIS)

    Prigent, Ch.

    2004-12-01

    In intense laser-cluster interaction, the experimental results show a strong energetic coupling between radiation and matter. We have measured absolute X-ray yields and charge state distributions under well control conditions as a function of physical parameters governing the interaction; namely laser intensity, pulse duration, wavelength or polarization state of the laser light, the size and the species of the clusters (Ar, Kr, Xe). We have highlighted, for the first time, an intensity threshold in the X-ray production very low (∼ 2.10 14 W/cm 2 for a pulse duration of 300 fs) which can results from an effect of the dynamical polarisation of clusters in an intense electric field. A weak dependence with the wavelength (400 nm / 800 nm) on the absolute X-ray yields has been found. Moreover, we have observed a saturation of the X-ray emission probability below a critical cluster size. (author)

  6. Automated Parallel Computing Tools for Multicore Machines and Clusters, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to improve productivity of high performance computing for applications on multicore computers and clusters. These machines built from one or more chips...

  7. Photometric redshifts as a tool for studying the Coma cluster galaxy populations

    Science.gov (United States)

    Adami, C.; Ilbert, O.; Pelló, R.; Cuillandre, J. C.; Durret, F.; Mazure, A.; Picat, J. P.; Ulmer, M. P.

    2008-12-01

    Aims: We apply photometric redshift techniques to an investigation of the Coma cluster galaxy luminosity function (GLF) at faint magnitudes, in particular in the u* band where basically no studies are presently available at these magnitudes. Methods: Cluster members were selected based on probability distribution function from photometric redshift calculations applied to deep u^*, B, V, R, I images covering a region of almost 1 deg2 (completeness limit R ~ 24). In the area covered only by the u* image, the GLF was also derived after a statistical background subtraction. Results: Global and local GLFs in the B, V, R, and I bands obtained with photometric redshift selection are consistent with our previous results based on a statistical background subtraction. The GLF in the u* band shows an increase in the faint end slope towards the outer regions of the cluster. The analysis of the multicolor type spatial distribution reveals that late type galaxies are distributed in clumps in the cluster outskirts, where X-ray substructures are also detected and where the GLF in the u* band is steeper. Conclusions: We can reproduce the GLFs computed with classical statistical subtraction methods by applying a photometric redshift technique. The u* GLF slope is steeper in the cluster outskirts, varying from α ~ -1 in the cluster center to α ~ -2 in the cluster periphery. The concentrations of faint late type galaxies in the cluster outskirts could explain these very steep slopes, assuming a short burst of star formation in these galaxies when entering the cluster. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is also partly based on data products produced at

  8. Photo fragmentation dynamics of small argon clusters and biological molecular: new tools by trapping and vectorial correlation

    International Nuclear Information System (INIS)

    Lepere, V.

    2006-09-01

    The present work concerns the building up of a complex set-up whose aim being the investigation of the photo fragmentation of ionised clusters and biological molecules. This new tool is based on the association of several techniques. Two ion sources are available: clusters produced in a supersonic beam are ionised by 70 eV electrons while ions of biological interest are produced in an 'electro-spray'. Ro-vibrational cooling is achieved in a 'Zajfman' electrostatic ion trap. The lifetime of ions can also be measured using the trap. Two types of lasers are used to excite the ionised species: the femtosecond laser available at the ELYSE facilities and a nanosecond laser. Both lasers have a repetition rate of 1 kHz. The neutral and ionised fragments are detected in coincidence using a sophisticated detection system allowing time and localisation of the various fragments to be determined. With such a tool, I was able to investigate in details the fragmentation dynamics of ionised clusters and bio-molecules. The first experiments deal with the measurement of the lifetime of the Ar 2+ dimer II(1/2)u metastable state. The relative population of this state was also determined. The Ar 2+ and Ar 3+ photo-fragmentation was then studied and electronic transitions responsible for their dissociation identified. The detailed analysis of our data allowed to distinguish the various fragmentation mechanisms. Finally, a preliminary investigation of the protonated tryptamine fragmentation is presented. (author)

  9. Clustering of Cochlear Oscillations in Frequency Plateaus as a Tool to Investigate SOAE Generation

    DEFF Research Database (Denmark)

    Epp, Bastian; Wit, Hero; van Dijk, Pim

    2016-01-01

    of coupled oscillators (OAM) [7] are also found in a transmission line model (TLM) which is able to generate realistic SOAEs [2] and if these frequency plateaus can be used to explain the formation of SOAEs. The simulations showed a clustering of oscillators along the simulated basilar membrane Both, the OAM...

  10. Homo-FRET Imaging as a tool to quantify protein and lipid clustering

    NARCIS (Netherlands)

    Bader, A.N.; Hoetzl, S.; Hofman, E.G.; Voortman, J.; van Bergen en Henegouwen, P.M.P.; van Meer, G.; Gerritsen, H.C.

    2010-01-01

    Homo-FRET, Förster resonance energy transfer between identical fluorophores, can be conveniently measured by observing its effect on the fluorescence anisotropy. This review aims to summarize the possibilities of fluorescence anisotropy imaging techniques to investigate clustering of identical

  11. The Multimorbidity Cluster Analysis Tool: Identifying Combinations and Permutations of Multiple Chronic Diseases Using a Record-Level Computational Analysis

    Directory of Open Access Journals (Sweden)

    Kathryn Nicholson

    2017-12-01

    Full Text Available Introduction: Multimorbidity, or the co-occurrence of multiple chronic health conditions within an individual, is an increasingly dominant presence and burden in modern health care systems.  To fully capture its complexity, further research is needed to uncover the patterns and consequences of these co-occurring health states.  As such, the Multimorbidity Cluster Analysis Tool and the accompanying Multimorbidity Cluster Analysis Toolkit have been created to allow researchers to identify distinct clusters that exist within a sample of participants or patients living with multimorbidity.  Development: The Tool and Toolkit were developed at Western University in London, Ontario, Canada.  This open-access computational program (JAVA code and executable file was developed and tested to support an analysis of thousands of individual records and up to 100 disease diagnoses or categories.  Application: The computational program can be adapted to the methodological elements of a research project, including type of data, type of chronic disease reporting, measurement of multimorbidity, sample size and research setting.  The computational program will identify all existing, and mutually exclusive, combinations and permutations within the dataset.  An application of this computational program is provided as an example, in which more than 75,000 individual records and 20 chronic disease categories resulted in the detection of 10,411 unique combinations and 24,647 unique permutations among female and male patients.  Discussion: The Tool and Toolkit are now available for use by researchers interested in exploring the complexities of multimorbidity.  Its careful use, and the comparison between results, will be valuable additions to the nuanced understanding of multimorbidity.

  12. Educational clusters as a tool ofpublic policy on the market of educational services

    Directory of Open Access Journals (Sweden)

    M. I. Vorona

    2016-08-01

    Due to this, the innovative educational cluster has been determined as a voluntary association of geographically close interacting entities, educational institutions, government, banking and private sector, innovative enterprises/organizations infrastructure. Such interaction is characterized by the production of competitive educational, cultural, social services, the availability of the agreed development strategy aimed at the interests of each participant and the region being a territory of cluster’s localization.

  13. Parallel variable selection of molecular dynamics clusters as a tool for calculation of spectroscopic properties

    Czech Academy of Sciences Publication Activity Database

    Kessler, Jiří; Dračínský, Martin; Bouř, Petr

    2013-01-01

    Roč. 34, č. 5 (2013), s. 366-371 ISSN 0192-8651 R&D Projects: GA ČR GAP208/11/0105; GA MŠk(CZ) LH11033 Grant - others:GA MŠk(CZ) LM2010005 Institutional support: RVO:61388963 Keywords : molecular dynamics * clusters * density functional theory * Raman optical activity * NMR Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 3.601, year: 2013

  14. Cluster-transfer reactions with radioactive beams: a spectroscopic tool for neutron-rich nuclei

    CERN Document Server

    AUTHOR|(CDS)2086156; Raabe, Riccardo; Bracco, Angela

    In this thesis work, an exploratory experiment to investigate cluster-transfer reactions with radioactive beams in inverse kinematics is presented. The aim of the experiment was to test the potential of cluster-transfer reactions at the Coulomb barrier, as a possible mean to perform $\\gamma$ spectroscopy studies of exotic neutron-rich nuclei at medium-high energies and spins. The experiment was performed at ISOLDE (CERN), employing the heavy-ion reaction $^{98}$Rb + $^{7}$Li at 2.85 MeV/A. Cluster-transfer reaction channels were studied through particle-$\\gamma$ coincidence measurements, using the MINIBALL Ge array coupled to the charged particle Si detectors T-REX. Sr, Y and Zr neutron-rich nuclei with A $\\approx$ 100 were populated by either triton- or $\\alpha$ transfer from $^{7}$Li to the beam nuclei and the emitted complementary charged fragment was detected in coincidence with the $\\gamma$ cascade of the residues, after few neutrons evaporation. The measured $\\gamma$ spectra were studied in detail and t...

  15. Effect of Deep Cryogenic treatment on AISI A8 Tool steel & Development of Wear Mechanism maps using Fuzzy Clustering

    Science.gov (United States)

    Pillai, Nandakumar; Karthikeyan, R., Dr.

    2018-04-01

    Tool steels are widely classified according to their constituents and type of thermal treatments carried out to obtain its properties. Viking a special purpose tool steel coming under AISI A8 cold working steel classification is widely used for heavy duty blanking and forming operations. The optimum combination of wear resistance and toughness as well as ease of machinability in pre-treated condition makes this material accepted in heavy cutting and non cutting tool manufacture. Air or vacuum hardening is recommended as the normal treatment procedure to obtain the desired mechanical and tribological properties for steels under this category. In this study, we are incorporating a deep cryogenic phase within the conventional treatment cycle both before and after tempering. The thermal treatments at sub zero temperatures up to -195°C using cryogenic chamber with liquid nitrogen as medium was conducted. Micro structural changes in its microstructure and the corresponding improvement in the tribological and physical properties are analyzed. The cryogenic treatment leads to more conversion of retained austenite to martensite and also formation of fine secondary carbides. The microstructure is studied using the micrographs taken using optical microscopy. The wear tests are conducted on DUCOM tribometer for different combinations of speed and load under normal temperature. The wear rates and coefficient of friction obtained from these experiments are used to developed wear mechanism maps with the help of fuzzy c means clustering and probabilistic neural network models. Fuzzy C means clustering is an effective algorithm to group data of similar patterns. The wear mechanisms obtained from the computationally developed maps are then compared with the SEM photographs taken and the improvement in properties due to this additional cryogenic treatment is validated.

  16. Defining and Controlling the Heterogeneity of a Cluster: the Wrekavoc Tool

    OpenAIRE

    Canon , Louis-Claude; Dubuisson , Olivier; Gustedt , Jens; Jeannot , Emmanuel

    2010-01-01

    International audience; The experimental validation and the testing of solutions that are designed for heterogeneous environments is challenging. We introduce Wrekavoc as an accurate tool for this purpose: it runs unmodified applications on emulated multisite heterogeneous platforms. Its principal technique consists in downgrading the performance of the platform characteristics in a prescribed way. The platform characteristics include the compute nodes themselves (CPU and memory) and the inte...

  17. Principal Component and Cluster Analysis as a Tool in the Assessment of Tomato Hybrids and Cultivars

    Directory of Open Access Journals (Sweden)

    G. Evgenidis

    2011-01-01

    Full Text Available Determination of germplasm diversity and genetic relationships among breeding materials is an invaluable aid in crop improvement strategies. This study assessed the breeding value of tomato source material. Two commercial hybrids along with an experimental hybrid and four cultivars were assessed with cluster and principal component analyses based on morphophysiological data, yield and quality, stability of performance, heterosis, and combining abilities. The assessment of commercial hybrids revealed a related origin and subsequently does not support the identification of promising offspring in their crossing. The assessment of the cultivars discriminated them according to origin and evolutionary and selection effects. On the Principal Component 1, the largest group with positive loading included, yield components, heterosis, general and specific combining ability, whereas the largest negative loading was obtained by qualitative and descriptive traits. The Principal Component 2 revealed two smaller groups, a positive one with phenotypic traits and a negative one with tolerance to inbreeding. Stability of performance was loaded positively and/or negatively. In conclusion, combing ability, yield components, and heterosis provided a mechanism for ensuring continued improvement in plant selection programs.

  18. Robust segmentation of medical images using competitive hop field neural network as a clustering tool

    International Nuclear Information System (INIS)

    Golparvar Roozbahani, R.; Ghassemian, M. H.; Sharafat, A. R.

    2001-01-01

    This paper presents the application of competitive Hop field neural network for medical images segmentation. Our proposed approach consists of Two steps: 1) translating segmentation of the given medical image into an optimization problem, and 2) solving this problem by a version of Hop field network known as competitive Hop field neural network. Segmentation is considered as a clustering problem and its validity criterion is based on both intra set distance and inter set distance. The algorithm proposed in this paper is based on gray level features only. This leads to near optimal solutions if both intra set distance and inter set distance are considered at the same time. If only one of these distances is considered, the result of segmentation process by competitive Hop field neural network will be far from optimal solution and incorrect even for very simple cases. Furthermore, sometimes the algorithm receives at unacceptable states. Both these problems may be solved by contributing both in tera distance and inter distances in the segmentation (optimization) process. The performance of the proposed algorithm is tested on both phantom and real medical images. The promising results and the robustness of algorithm to system noises show near optimal solutions

  19. Magnesium isotopes: a tool to understand self-enrichment in globular clusters

    Science.gov (United States)

    Ventura, P.; D'Antona, F.; Imbriani, G.; Di Criscienzo, M.; Dell'Agli, F.; Tailo, M.

    2018-06-01

    A critical issue in the asymptotic giant branch (AGB) self-enrichment scenario for the formation of multiple populations in globular clusters (GCs) is the inability to reproduce the magnesium isotopic ratios, despite the model in principle can account for the depletion of magnesium. In this work, we analyse how the uncertainties on the various p-capture cross sections affect the results related to the magnesium content of the ejecta of AGB stars. The observed distribution of the magnesium isotopes and of the overall Mg-Al trend in M13 and NGC 6752 are successfully reproduced when the proton-capture rate by 25Mg at the temperatures ˜100 MK, in particular the 25Mg(p, γ)26Alm channel, is enhanced by a factor ˜3 with respect to the most recent experimental determinations. This assumption also allows us to reproduce the full extent of the Mg spread and the Mg-Si anticorrelation observed in NGC 2419. The uncertainties in the rate of the 25Mg(p, γ)26Alm reaction at the temperatures of interest here leave space for our assumption and we suggest that new experimental measurements are needed to settle this problem. We also discuss the competitive model based on the supermassive star nucleosynthesis.

  20. 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

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

    Science.gov (United States)

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

    2014-12-01

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

  2. Pain management in cancer center inpatients: a cluster randomized trial to evaluate a systematic integrated approach—The Edinburgh Pain Assessment and Management Tool

    OpenAIRE

    Fallon, M; Walker, J; Colvin, L; Rodriguez, A; Murray, G; Sharpe, M

    2018-01-01

    Purpose Pain is suboptimally managed in patients with cancer. We aimed to compare the effect of a policy of adding a clinician-delivered bedside pain assessment and management tool (Edinburgh Pain Assessment and management Tool [EPAT]) to usual care (UC) versus UC alone on pain outcomes. Patients and Methods In a two-arm, parallel group, cluster randomized (1:1) trial, we observed pain outcomes in 19 cancer centers in the United Kingdom and then randomly assigned the centers to eithe...

  3. Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling

    NARCIS (Netherlands)

    Veeger, C.P.L.; Etman, L.F.P.; Herk, van J.; Rooda, J.E.

    2009-01-01

    Predicting the mean cycle time as a function of throughput and product mix is helpful in making the production planning for cluster tools. To predict the mean cycle time, detailed simulation models may be used. However, detailed models require much development time, and it may not be possible to

  4. HIV-TRACE (Transmission Cluster Engine): a tool for large scale molecular epidemiology of HIV-1 and other rapidly evolving pathogens.

    Science.gov (United States)

    Kosakovsky Pond, Sergei L; Weaver, Steven; Leigh Brown, Andrew J; Wertheim, Joel O

    2018-01-31

    In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoeleather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, i.e., on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from github.com/veg/hivtrace, along with the accompanying result visualization module from github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens. © The Author 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Cluster as a Tool to Increase the Competitiveness and Innovative Activity of Enterprises of the Defense Industry Complex

    Directory of Open Access Journals (Sweden)

    Katrina B. Dobrova

    2017-01-01

    Full Text Available Purpose: the main goal of the publication is to make a comprehensive study of the possible application of the cluster approach to improve the competitiveness and innovation activity of enterprises of the defense industry complex.Methods: the methodology of the research is based on the collection and analysis of initial data and information, the article uses a systematic approach to the study of socio-economic processes and phenomena. The research is based on modern theory of competition, innovation, as well as the modern paradigm of cluster development of the economy. In preparing the study, practical materials from Corporation “Rostec”.Results: the article gives the notion of cluster, the prospects for the use of the cluster approach to enhance competitiveness and innovation enterprises of the military-industrial complex. It is noted that the activation of interaction with the “civil sector” is particularly relevant in the context of the reduction of the state defense order, and the theory and practice of cluster management offers a number of forms of cluster interaction between the enterprises of the defense industry and the civil sector. It is emphasized that the development of cluster mechanisms can solve a number of problems related to the insufficient financial stability of defense industry enterprises in the context of a reduction in the state defense order, low innovation activity and the lack of developed models of interaction with small innovative enterprises. Ultimately, the use of cluster mechanisms in the development of defense enterprises is intended to enhance the competitiveness of the complex, both nationally and globally. It is stated that the existing clusters are not able to fully solve a number of specific tasks related to the diversification of integrated defense industry structures. Attention is drawn to the fact that existing clusters are not able to fully solve a number of specific tasks related to the

  6. Country clustering applied to the water and sanitation sector: a new tool with potential applications in research and policy.

    Science.gov (United States)

    Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

    2014-03-01

    The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were distinct from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. Copyright © 2013 Elsevier GmbH. All rights reserved.

  7. Jets from jets: re-clustering as a tool for large radius jet reconstruction and grooming at the LHC

    Science.gov (United States)

    Nachman, Benjamin; Nef, Pascal; Schwartzman, Ariel; Swiatlowski, Maximilian; Wanotayaroj, Chaowaroj

    2015-02-01

    Jets with a large radius R ≳ 1 and grooming algorithms are widely used to fully capture the decay products of boosted heavy particles at the Large Hadron Collider (LHC). Unlike most discriminating variables used in such studies, the jet radius is usually not optimized for specific physics scenarios. This is because every jet configuration must be calibrated, insitu, to account for detector response and other experimental effects. One solution to enhance the availability of large- R jet configurations used by the LHC experiments is jet re-clustering. Jet re-clustering introduces an intermediate scale r groomed jets. Jet re-clustering has the benefit that no additional large-R calibration is necessary, allowing the re-clustered large radius parameter to be optimized in the context of specific precision measurements or searches for new physics.

  8. Jets from jets: re-clustering as a tool for large radius jet reconstruction and grooming at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Nachman, Benjamin; Nef, Pascal; Schwartzman, Ariel; Swiatlowski, Maximilian [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Wanotayaroj, Chaowaroj [Center for High Energy Physics, University of Oregon,1371 E. 13th Ave, Eugene, OR 97403 (United States)

    2015-02-12

    Jets with a large radius R≳1 and grooming algorithms are widely used to fully capture the decay products of boosted heavy particles at the Large Hadron Collider (LHC). Unlike most discriminating variables used in such studies, the jet radius is usually not optimized for specific physics scenarios. This is because every jet configuration must be calibrated, insitu, to account for detector response and other experimental effects. One solution to enhance the availability of large-R jet configurations used by the LHC experiments is jet re-clustering. Jet re-clustering introduces an intermediate scale rclustering configurations and show that re-clustered large radius jets have essentially the same jet mass performance as large radius groomed jets. Jet re-clustering has the benefit that no additional large-R calibration is necessary, allowing the re-clustered large radius parameter to be optimized in the context of specific precision measurements or searches for new physics.

  9. Jets from jets: re-clustering as a tool for large radius jet reconstruction and grooming at the LHC

    International Nuclear Information System (INIS)

    Nachman, Benjamin; Nef, Pascal; Schwartzman, Ariel; Swiatlowski, Maximilian; Wanotayaroj, Chaowaroj

    2015-01-01

    Jets with a large radius R≳1 and grooming algorithms are widely used to fully capture the decay products of boosted heavy particles at the Large Hadron Collider (LHC). Unlike most discriminating variables used in such studies, the jet radius is usually not optimized for specific physics scenarios. This is because every jet configuration must be calibrated, insitu, to account for detector response and other experimental effects. One solution to enhance the availability of large-R jet configurations used by the LHC experiments is jet re-clustering. Jet re-clustering introduces an intermediate scale rclustering configurations and show that re-clustered large radius jets have essentially the same jet mass performance as large radius groomed jets. Jet re-clustering has the benefit that no additional large-R calibration is necessary, allowing the re-clustered large radius parameter to be optimized in the context of specific precision measurements or searches for new physics.

  10. I-HASTREAM : density-based hierarchical clustering of big data streams and its application to big graph analytics tools

    NARCIS (Netherlands)

    Hassani, M.; Spaus, P.; Cuzzocrea, A.; Seidl, T.

    2016-01-01

    Big Data Streams are very popular at now, as stirred-up by a plethora of modern applications such as sensor networks, scientific computing tools, Web intelligence, social network analysis and mining tools, and so forth. Here, the main research issue consists in how to effectively and efficiently

  11. A Cluster Randomized-Controlled Trial of the Impact of the Tools of the Mind Curriculum on Self-Regulation in Canadian Preschoolers.

    Science.gov (United States)

    Solomon, Tracy; Plamondon, Andre; O'Hara, Arland; Finch, Heather; Goco, Geraldine; Chaban, Peter; Huggins, Lorrie; Ferguson, Bruce; Tannock, Rosemary

    2017-01-01

    Early self-regulation predicts school readiness, academic success, and quality of life in adulthood. Its development in the preschool years is rapid and also malleable. Thus, preschool curricula that promote the development of self-regulation may help set children on a more positive developmental trajectory. We conducted a cluster-randomized controlled trial of the Tools of the Mind preschool curriculum, a program that targets self-regulation through imaginative play and self-regulatory language (Tools; clinical trials identifier NCT02462733). Previous research with Tools is limited, with mixed evidence of its effectiveness. Moreover, it is unclear whether it would benefit all preschoolers or primarily those with poorly developed cognitive capacities (e.g., language, executive function, attention). The study goals were to ascertain whether the Tools program leads to greater gains in self-regulation compared to Playing to Learn (YMCA PTL), another play based program that does not target self-regulation specifically, and whether the effects were moderated by children's initial language and hyperactivity/inattention. Two hundred and sixty 3- to 4-year-olds attending 20 largely urban daycares were randomly assigned, at the site level, to receive either Tools or YMCA PTL (the business-as-usual curriculum) for 15 months. We assessed self-regulation at pre-, mid and post intervention, using two executive function tasks, and two questionnaires regarding behavior at home and at school, to capture development in cognitive as well as socio-emotional aspects of self-regulation. Fidelity data showed that only the teachers at the Tools sites implemented Tools, and did so with reasonable success. We found that children who received Tools made greater gains on a behavioral measure of executive function than their YMCA PTL peers, but the difference was significant only for those children whose parents rated them high in hyperactivity/inattention initially. The effect of Tools did

  12. A Cluster Randomized-Controlled Trial of the Impact of the Tools of the Mind Curriculum on Self-Regulation in Canadian Preschoolers

    Directory of Open Access Journals (Sweden)

    Tracy Solomon

    2018-01-01

    Full Text Available Early self-regulation predicts school readiness, academic success, and quality of life in adulthood. Its development in the preschool years is rapid and also malleable. Thus, preschool curricula that promote the development of self-regulation may help set children on a more positive developmental trajectory. We conducted a cluster-randomized controlled trial of the Tools of the Mind preschool curriculum, a program that targets self-regulation through imaginative play and self-regulatory language (Tools; clinical trials identifier NCT02462733. Previous research with Tools is limited, with mixed evidence of its effectiveness. Moreover, it is unclear whether it would benefit all preschoolers or primarily those with poorly developed cognitive capacities (e.g., language, executive function, attention. The study goals were to ascertain whether the Tools program leads to greater gains in self-regulation compared to Playing to Learn (YMCA PTL, another play based program that does not target self-regulation specifically, and whether the effects were moderated by children’s initial language and hyperactivity/inattention. Two hundred and sixty 3- to 4-year-olds attending 20 largely urban daycares were randomly assigned, at the site level, to receive either Tools or YMCA PTL (the business-as-usual curriculum for 15 months. We assessed self-regulation at pre-, mid and post intervention, using two executive function tasks, and two questionnaires regarding behavior at home and at school, to capture development in cognitive as well as socio-emotional aspects of self-regulation. Fidelity data showed that only the teachers at the Tools sites implemented Tools, and did so with reasonable success. We found that children who received Tools made greater gains on a behavioral measure of executive function than their YMCA PTL peers, but the difference was significant only for those children whose parents rated them high in hyperactivity/inattention initially. The

  13. Cluster ion beam facilities

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  14. Fuzzy Clustering

    DEFF Research Database (Denmark)

    Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

    2000-01-01

    A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  15. Clustering biomass-based technologies towards zero emissions - a tool how the Earth's resources can be shifted back to sustainability

    International Nuclear Information System (INIS)

    Gravitis, J.; Pauli, G.

    2001-01-01

    The Zero Emissions Research Initiative (ZERI) was founded on the fundamental concept that, in order to achieve environmentally sustainable development, industries must maximize the use of available raw materials and utilize their own wastes and by-products to the fullest extent possible so as to eliminate all emissions into the air, water and soil. Research focuses on what are considered to be four central components of zero emissions biobased industries: (I) integrated biosystems, (II) materials separation technologies, (III) biorefinery, and (IV) zero emissions systems design. In this way, industries may be organized into clusters within one single system, or in interdependent sets of industries. (authors)

  16. Starpc: a library for communication among tools on a parallel computer cluster. User's and developer's guide to Starpc

    International Nuclear Information System (INIS)

    Takemiya, Hiroshi; Yamagishi, Nobuhiro

    2000-02-01

    We report on a RPC(Remote Procedure Call)-based communication library, Starpc, for a parallel computer cluster. Starpc supports communication between Java Applets and C programs as well as between C programs. Starpc has the following three features. (1) It enables communication between Java Applets and C programs on an arbitrary computer without security violation, although Java Applets are supposed to communicate only with programs on the specific computer (Web server) in subject to a restriction on security. (2) Diverse network communication protocols are available on Starpc, because of using Nexus communication library developed at Argonne National Laboratory. (3) It works on many kinds of computers including eight parallel computers and four WS servers. In this report, the usage of Starpc and the development of applications using Starpc are described. (author)

  17. 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)

  18. The impact of the carer support needs assessment tool (CSNAT in community palliative care using a stepped wedge cluster trial.

    Directory of Open Access Journals (Sweden)

    Samar M Aoun

    Full Text Available Family caregiving towards the end-of-life entails considerable emotional, social, financial and physical costs for caregivers. Evidence suggests that good support can improve caregiver psychological outcomes. The primary aim of this study was to investigate the impact of using the carer support needs assessment tool (CSNAT, as an intervention to identify and address support needs in end of life home care, on family caregiver outcomes. A stepped wedge design was used to trial the CSNAT intervention in three bases of Silver Chain Hospice Care in Western Australia, 2012-14. The intervention consisted of at least two visits from nurses (2-3 weeks apart to identify, review and address caregivers' needs. The outcome measures for the intervention and control groups were caregiver strain and distress as measured by the Family Appraisal of Caregiving Questionnaire (FACQ-PC, caregiver mental and physical health as measured by SF-12v2, and caregiver workload as measured by extent of caregiver assistance with activities of daily living, at baseline and follow up. Total recruitment was 620. There was 45% attrition for each group between baseline and follow-up mainly due to patient deaths resulting in 322 caregivers completing the study (233 in the intervention group and 89 in the control group. At follow-up, the intervention group showed significant reduction in caregiver strain relative to controls, p=0.018, d=0.348 (95% CI 0.25 to 0.41. Priority support needs identified by caregivers included knowing what to expect in the future, having time for yourself in the day and dealing with your feelings and worries. Despite the challenges at the clinician, organisational and trial levels, the CSNAT intervention led to an improvement in caregiver strain. Effective implementation of an evidence-informed and caregiver-led tool represents a necessary step towards helping palliative care providers better assess and address caregiver needs, ensuring adequate family

  19. Mobile-health tool to improve maternal and neonatal health care in Bangladesh: a cluster randomized controlled trial.

    Science.gov (United States)

    Tobe, Ruoyan Gai; Haque, Syed Emdadul; Ikegami, Kiyoko; Mori, Rintaro

    2018-04-16

    In Bangladesh, the targets on reduction of maternal mortality and utilization of related obstetric services provided by skilled health personnel in Millennium Development Goals 5 remains unmet, and the progress in reduction of neonatal mortality lag behind that in the reduction of infant and under-five mortalities, remaining as an essential issue towards the achievement of maternal and neonatal health targets in health related Sustainable Development Goals (SDGs). As access to appropriate perinatal care is crucial to reduce maternal and neonatal deaths, recently several mobile platform-based health programs sponsored by donor countries and Non-Governmental Organizations have targeted to reduce maternal and child mortality. On the other hand, good health-care is necessary for the development. Thus, we designed this implementation research to improve maternal and child health care for targeting SDGs. This cluster randomized trial will be conducted in Lohagora of Narail District and Dhamrai of Dhaka District. Participants are pregnant women in the respective areas. The total sample size is 3000 where 500 pregnant women will get Mother and Child Handbook (MCH) and messages using mobile phone on health care during pregnancy and antenatal care about one year in each area. The other 500 in each area will get health education using only MCH book. The rest 1000 participants will be controlled; it means 500 in each area. We randomly assigned the intervention and controlled area based on smallest administrative area (Unions) in Bangladesh. The data collection and health education will be provided through trained research officers starting from February 2017 to August 2018. Each health education session is conducting in their house. The study proposal was reviewed and approved by NCCD, Japan and Bangladesh Medical Research Council (BMRC), Bangladesh. The data will be analyzed using STATA and SPSS software. For the improvement of maternal and neonatal care, this community

  20. Evaluation of an early detection tool for social-emotional and behavioral problems in toddlers: The Brief Infant Toddler Social and Emotional Assessment - A cluster randomized trial

    Directory of Open Access Journals (Sweden)

    Carter Alice S

    2011-06-01

    Full Text Available Abstract Background The prevalence of social-emotional and behavioral problems is estimated to be 8 to 9% among preschool children. Effective early detection tools are needed to promote the provision of adequate care at an early stage. The Brief Infant-Toddler Social and Emotional Assessment (BITSEA was developed for this purpose. This study evaluates the effectiveness of the BITSEA to enhance social-emotional and behavioral health of preschool children. Methods and Design A cluster randomized controlled trial is set up in youth health care centers in the larger Rotterdam area in the Netherlands, to evaluate the BITSEA. The 31 youth health care centers are randomly allocated to either the control group or the intervention group. The intervention group uses the scores on the BITSEA and cut-off points to evaluate a child's social-emotional and behavioral health and to decide whether or not the child should be referred. The control group provides care as usual, which involves administering a questionnaire that structures the conversation between child health professionals and parents. At a one year follow-up measurement the social-emotional and behavioral health of all children included in the study population will be evaluated. Discussion It is hypothesized that better results will be found, in terms of social-emotional and behavioral health in the intervention group, compared to the control group, due to more adequate early detection, referral and more appropriate and timely care. Trial registration Current Controlled Trials NTR2035

  1. Prevention of Hospital-Acquired Adverse Drug Reactions in Older People Using Screening Tool of Older Persons' Prescriptions and Screening Tool to Alert to Right Treatment Criteria: A Cluster Randomized Controlled Trial.

    Science.gov (United States)

    O'Connor, Marie N; O'Sullivan, David; Gallagher, Paul F; Eustace, Joseph; Byrne, Stephen; O'Mahony, Denis

    2016-08-01

    To determine whether use of the Screening Tool of Older Persons' Prescriptions (STOPP) and Screening Tool to Alert to Right Treatment (START) criteria reduces incident hospital-acquired adverse drug reactions (ADRs), 28-day medication costs, and median length of hospital stay in older adults admitted with acute illness. Single-blind cluster randomized controlled trial (RCT) of unselected older adults hospitalized over a 13-month period. Tertiary referral hospital in southern Ireland. Consecutively admitted individuals aged 65 and older (N = 732). Single time point presentation to attending physicians of potentially inappropriate medications according to the STOPP/START criteria. The primary outcome was the proportion of participants experiencing one or more ADRs during the index hospitalization. Secondary outcomes were median length of stay (LOS) and 28-day total medication cost. One or more ADRs occurred in 78 of the 372 control participants (21.0%; median age 78, interquartile range (IQR) 72-84) and in 42 of the 360 intervention participants (11.7%; median age 80, IQR 73-85) (absolute risk reduction = 9.3%, number needed to treat = 11). The median LOS in the hospital was 8 days (IQR 4-14 days) in both groups. At discharge, median medication cost was significantly lower in the intervention group (€73.16, IQR €38.68-121.72) than in the control group (€90.62, IQR €49.38-162.53) (Wilcoxon rank test Z statistic = -3.274, P older adults but did not affect median LOS. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

  2. Design of a cluster-randomized trial of electronic health record-based tools to address overweight and obesity in primary care.

    Science.gov (United States)

    Baer, Heather J; Wee, Christina C; DeVito, Katerina; Orav, E John; Frolkis, Joseph P; Williams, Deborah H; Wright, Adam; Bates, David W

    2015-08-01

    Primary care providers often fail to identify patients who are overweight or obese or discuss weight management with them. Electronic health record-based tools may help providers with the assessment and management of overweight and obesity. We describe the design of a trial to examine the effectiveness of electronic health record-based tools for the assessment and management of overweight and obesity among adult primary care patients, as well as the challenges we encountered. We developed several new features within the electronic health record used by primary care practices affiliated with Brigham and Women's Hospital in Boston, MA. These features included (1) reminders to measure height and weight, (2) an alert asking providers to add overweight or obesity to the problem list, (3) reminders with tailored management recommendations, and (4) a Weight Management screen. We then conducted a pragmatic, cluster-randomized controlled trial in 12 primary care practices. We randomized 23 clinical teams ("clinics") within the practices to the intervention group (n = 11) or the control group (n = 12). The new features were activated only for clinics in the intervention group. The intervention was implemented in two phases: the height and weight reminders went live on 15 December 2011 (Phase 1), and all of the other features went live on 11 June 2012 (Phase 2). Study enrollment went from December 2011 through December 2012, and follow-up ended in December 2013. The primary outcomes were 6-month and 12-month weight change among adult patients with body mass index ≥25 who had a visit at one of the primary care clinics during Phase 2. Secondary outcome measures included the proportion of patients with a recorded body mass index in the electronic health record, the proportion of patients with body mass index ≥25 who had a diagnosis of overweight or obesity on the electronic health record problem list, and the proportion of patients with body mass index ≥25 who had

  3. G-NEST: a gene neighborhood scoring tool to identify co-conserved, co-expressed genes

    Directory of Open Access Journals (Sweden)

    Lemay Danielle G

    2012-09-01

    Full Text Available Abstract Background In previous studies, gene neighborhoods—spatial clusters of co-expressed genes in the genome—have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Scoring Tool (G-NEST which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously. Results Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods. Conclusions Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The

  4. 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...

  5. 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...

  6. Privacy-preserving distributed clustering

    NARCIS (Netherlands)

    Erkin, Z.; Veugen, T.; Toft, T.; Lagendijk, R.L.

    2013-01-01

    Clustering is a very important tool in data mining and is widely used in on-line services for medical, financial and social environments. The main goal in clustering is to create sets of similar objects in a data set. The data set to be used for clustering can be owned by a single entity, or in some

  7. X ray emission: a tool and a probe for laser - clusters interaction; L'emission X: un outil et une sonde pour l'interaction laser - agregats

    Energy Technology Data Exchange (ETDEWEB)

    Prigent, Ch

    2004-12-01

    In intense laser-cluster interaction, the experimental results show a strong energetic coupling between radiation and matter. We have measured absolute X-ray yields and charge state distributions under well control conditions as a function of physical parameters governing the interaction; namely laser intensity, pulse duration, wavelength or polarization state of the laser light, the size and the species of the clusters (Ar, Kr, Xe). We have highlighted, for the first time, an intensity threshold in the X-ray production very low ({approx} 2.10{sup 14} W/cm{sup 2} for a pulse duration of 300 fs) which can results from an effect of the dynamical polarisation of clusters in an intense electric field. A weak dependence with the wavelength (400 nm / 800 nm) on the absolute X-ray yields has been found. Moreover, we have observed a saturation of the X-ray emission probability below a critical cluster size. (author)

  8. Cluster headache

    Science.gov (United States)

    Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... Doctors do not know exactly what causes cluster headaches. They ... (chemical in the body released during an allergic response) or ...

  9. TreeCluster: Massively scalable transmission clustering using phylogenetic trees

    OpenAIRE

    Moshiri, Alexander

    2018-01-01

    Background: The ability to infer transmission clusters from molecular data is critical to designing and evaluating viral control strategies. Viral sequencing datasets are growing rapidly, but standard methods of transmission cluster inference do not scale well beyond thousands of sequences. Results: I present TreeCluster, a cross-platform tool that performs transmission cluster inference on a given phylogenetic tree orders of magnitude faster than existing inference methods and supports multi...

  10. Clustered lot quality assurance sampling: a tool to monitor immunization coverage rapidly during a national yellow fever and polio vaccination campaign in Cameroon, May 2009.

    Science.gov (United States)

    Pezzoli, L; Tchio, R; Dzossa, A D; Ndjomo, S; Takeu, A; Anya, B; Ticha, J; Ronveaux, O; Lewis, R F

    2012-01-01

    We used the clustered lot quality assurance sampling (clustered-LQAS) technique to identify districts with low immunization coverage and guide mop-up actions during the last 4 days of a combined oral polio vaccine (OPV) and yellow fever (YF) vaccination campaign conducted in Cameroon in May 2009. We monitored 17 pre-selected districts at risk for low coverage. We designed LQAS plans to reject districts with YF vaccination coverage LQAS proved to be useful in guiding the campaign vaccination strategy before the completion of the operations.

  11. Weighted Clustering

    DEFF Research Database (Denmark)

    Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

    2012-01-01

    We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

  12. A Fast SVM-Based Tongue’s Colour Classification Aided by k-Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis

    Directory of Open Access Journals (Sweden)

    Nur Diyana Kamarudin

    2017-01-01

    Full Text Available In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye’s ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue’s multicolour classification based on a support vector machine (SVM whose support vectors are reduced by our proposed k-means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k-means clustering is used to cluster a tongue image into four clusters of image background (black, deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds.

  13. A Fast SVM-Based Tongue's Colour Classification Aided by k-Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis

    Science.gov (United States)

    Ooi, Chia Yee; Kawanabe, Tadaaki; Odaguchi, Hiroshi; Kobayashi, Fuminori

    2017-01-01

    In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k-means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k-means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds. PMID:29065640

  14. A Fast SVM-Based Tongue's Colour Classification Aided by k-Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis.

    Science.gov (United States)

    Kamarudin, Nur Diyana; Ooi, Chia Yee; Kawanabe, Tadaaki; Odaguchi, Hiroshi; Kobayashi, Fuminori

    2017-01-01

    In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k -means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k -means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds.

  15. 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.

  16. Isotopic clusters

    International Nuclear Information System (INIS)

    Geraedts, J.M.P.

    1983-01-01

    Spectra of isotopically mixed clusters (dimers of SF 6 ) are calculated as well as transition frequencies. The result leads to speculations about the suitability of the laser-cluster fragmentation process for isotope separation. (Auth.)

  17. Cluster Headache

    Science.gov (United States)

    ... a role. Unlike migraine and tension headache, cluster headache generally isn't associated with triggers, such as foods, hormonal changes or stress. Once a cluster period begins, however, drinking alcohol ...

  18. Cluster Headache

    OpenAIRE

    Pearce, Iris

    1985-01-01

    Cluster headache is the most severe primary headache with recurrent pain attacks described as worse than giving birth. The aim of this paper was to make an overview of current knowledge on cluster headache with a focus on pathophysiology and treatment. This paper presents hypotheses of cluster headache pathophysiology, current treatment options and possible future therapy approaches. For years, the hypothalamus was regarded as the key structure in cluster headache, but is now thought to be pa...

  19. Categorias Cluster

    OpenAIRE

    Queiroz, Dayane Andrade

    2015-01-01

    Neste trabalho apresentamos as categorias cluster, que foram introduzidas por Aslak Bakke Buan, Robert Marsh, Markus Reineke, Idun Reiten e Gordana Todorov, com o objetivo de categoriíicar as algebras cluster criadas em 2002 por Sergey Fomin e Andrei Zelevinsky. Os autores acima, em [4], mostraram que existe uma estreita relação entre algebras cluster e categorias cluster para quivers cujo grafo subjacente é um diagrama de Dynkin. Para isto desenvolveram uma teoria tilting na estrutura triang...

  20. Meaningful Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Calapristi, Augustin J.; Crow, Vernon L.; Hetzler, Elizabeth G.; Turner, Alan E.

    2004-05-26

    We present an approach to the disambiguation of cluster labels that capitalizes on the notion of semantic similarity to assign WordNet senses to cluster labels. The approach provides interesting insights on how document clustering can provide the basis for developing a novel approach to word sense disambiguation.

  1. Horticultural cluster

    OpenAIRE

    SHERSTIUK S.V.; POSYLAYEVA K.I.

    2013-01-01

    In the article there are the theoretical and methodological approaches to the nature and existence of the cluster. The cluster differences from other kinds of cooperative and integration associations. Was develop by scientific-practical recommendations for forming a competitive horticultur cluster.

  2. Photo fragmentation dynamics of small argon clusters and biological molecular: new tools by trapping and vectorial correlation; Dynamique de photofragmentation de petits agregats d'argon et de molecules biologiques: nouvel outil par piegeage et correlation vectorielle

    Energy Technology Data Exchange (ETDEWEB)

    Lepere, V

    2006-09-15

    The present work concerns the building up of a complex set-up whose aim being the investigation of the photo fragmentation of ionised clusters and biological molecules. This new tool is based on the association of several techniques. Two ion sources are available: clusters produced in a supersonic beam are ionised by 70 eV electrons while ions of biological interest are produced in an 'electro-spray'. Ro-vibrational cooling is achieved in a 'Zajfman' electrostatic ion trap. The lifetime of ions can also be measured using the trap. Two types of lasers are used to excite the ionised species: the femtosecond laser available at the ELYSE facilities and a nanosecond laser. Both lasers have a repetition rate of 1 kHz. The neutral and ionised fragments are detected in coincidence using a sophisticated detection system allowing time and localisation of the various fragments to be determined. With such a tool, I was able to investigate in details the fragmentation dynamics of ionised clusters and bio-molecules. The first experiments deal with the measurement of the lifetime of the Ar{sup 2+} dimer II(1/2)u metastable state. The relative population of this state was also determined. The Ar{sup 2+} and Ar{sup 3+} photo-fragmentation was then studied and electronic transitions responsible for their dissociation identified. The detailed analysis of our data allowed to distinguish the various fragmentation mechanisms. Finally, a preliminary investigation of the protonated tryptamine fragmentation is presented. (author)

  3. Cluster Matters

    DEFF Research Database (Denmark)

    Gulati, Mukesh; Lund-Thomsen, Peter; Suresh, Sangeetha

    2018-01-01

    sell their products successfully in international markets, but there is also an increasingly large consumer base within India. Indeed, Indian industrial clusters have contributed to a substantial part of this growth process, and there are several hundred registered clusters within the country...... of this handbook, which focuses on the role of CSR in MSMEs. Hence we contribute to the literature on CSR in industrial clusters and specifically CSR in Indian industrial clusters by investigating the drivers of CSR in India’s industrial clusters....

  4. Evaluation of an early detection tool for social-emotional and behavioral problems in toddlers: The Brief Infant Toddler Social and Emotional Assessment - A cluster randomized trial

    NARCIS (Netherlands)

    I. Kruizinga (Ingrid); W. Jansen (Wilma); A.S. Carter (Alice); H. Raat (Hein)

    2011-01-01

    textabstractBackground: The prevalence of social-emotional and behavioral problems is estimated to be 8 to 9% among preschool children. Effective early detection tools are needed to promote the provision of adequate care at an early stage. The Brief Infant-Toddler Social and Emotional Assessment

  5. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

    On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

  6. Cluster evolution

    International Nuclear Information System (INIS)

    Schaeffer, R.

    1987-01-01

    The galaxy and cluster luminosity functions are constructed from a model of the mass distribution based on hierarchical clustering at an epoch where the matter distribution is non-linear. These luminosity functions are seen to reproduce the present distribution of objects as can be inferred from the observations. They can be used to deduce the redshift dependence of the cluster distribution and to extrapolate the observations towards the past. The predicted evolution of the cluster distribution is quite strong, although somewhat less rapid than predicted by the linear theory

  7. Hierarchical cluster-based partial least squares regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models.

    Science.gov (United States)

    Tøndel, Kristin; Indahl, Ulf G; Gjuvsland, Arne B; Vik, Jon Olav; Hunter, Peter; Omholt, Stig W; Martens, Harald

    2011-06-01

    Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. HC-PLSR is a promising approach for

  8. Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR is an efficient tool for metamodelling of nonlinear dynamic models

    Directory of Open Access Journals (Sweden)

    Omholt Stig W

    2011-06-01

    Full Text Available Abstract Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs to variation in features of the trajectories of the state variables (outputs throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR, where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR and ordinary least squares (OLS regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback

  9. OBSERVED SCALING RELATIONS FOR STRONG LENSING CLUSTERS: CONSEQUENCES FOR COSMOLOGY AND CLUSTER ASSEMBLY

    International Nuclear Information System (INIS)

    Comerford, Julia M.; Moustakas, Leonidas A.; Natarajan, Priyamvada

    2010-01-01

    Scaling relations of observed galaxy cluster properties are useful tools for constraining cosmological parameters as well as cluster formation histories. One of the key cosmological parameters, σ 8 , is constrained using observed clusters of galaxies, although current estimates of σ 8 from the scaling relations of dynamically relaxed galaxy clusters are limited by the large scatter in the observed cluster mass-temperature (M-T) relation. With a sample of eight strong lensing clusters at 0.3 8 , but combining the cluster concentration-mass relation with the M-T relation enables the inclusion of unrelaxed clusters as well. Thus, the resultant gains in the accuracy of σ 8 measurements from clusters are twofold: the errors on σ 8 are reduced and the cluster sample size is increased. Therefore, the statistics on σ 8 determination from clusters are greatly improved by the inclusion of unrelaxed clusters. Exploring cluster scaling relations further, we find that the correlation between brightest cluster galaxy (BCG) luminosity and cluster mass offers insight into the assembly histories of clusters. We find preliminary evidence for a steeper BCG luminosity-cluster mass relation for strong lensing clusters than the general cluster population, hinting that strong lensing clusters may have had more active merging histories.

  10. Application of MALDI-TOF MS fingerprinting as a quick tool for identification and clustering of foodborne pathogens isolated from food products.

    Science.gov (United States)

    Elbehiry, Ayman; Marzouk, Eman; Hamada, Mohamed; Al-Dubaib, Musaad; Alyamani, Essam; Moussa, Ihab M; AlRowaidhan, Anhar; Hemeg, Hassan A

    2017-10-01

    Foodborne pathogens can be associated with a wide variety of food products and it is very important to identify them to supply safe food and prevent foodborne infections. Since traditional techniques are timeconsuming and laborious, this study was designed for rapid identification and clustering of foodborne pathogens isolated from various restaurants in Al-Qassim region, Kingdom of Saudi Arabia (KSA) using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Sixty-nine bacterial and thirty-two fungal isolates isolated from 80 food samples were used in this study. Preliminary identification was carried out through culture and BD Phoenix™ methods. A confirmatory identification technique was then performed using MALDI-TOF MS. The BD Phoenix results revealed that 97% (67/69 isolates) of bacteria were correctly identified as 75% Enterobacter cloacae, 95.45% Campylobacter jejuni and 100% for Escherichia coli, Salmonella enterica, Staphylococcus aureus, Acinetobacter baumannii, and Klebsiella pneumoniae. While 94.44% (29/32 isolates) of fungi were correctly identified as 77.77% Alternaria alternate, 88.88% Aspergillus niger and 100% for Aspergillus flavus, Penicillium digitatum, Candida albicans and Debaryomyces hansenii. However, all bacterial and fungal isolates were 100% properly identified by MALDI-TOF MS fingerprinting with a score value ≥2.00. A gel view illustrated that the spectral peaks for the identified isolates fluctuate between 3,000 and 10,000 Da. The results of main spectra library (MSP) dendrogram showed that the bacterial and fungal isolates matched with 19 and 9 reference strains stored in the Bruker taxonomy, respectively. Our results indicated that MALDI-TOF MS is a promising technique for fast and accurate identification of foodborne pathogens.

  11. Mobile phones as a health communication tool to improve skilled attendance at delivery in Zanzibar: a cluster-randomised controlled trial.

    Science.gov (United States)

    Lund, S; Hemed, M; Nielsen, B B; Said, A; Said, K; Makungu, M H; Rasch, V

    2012-09-01

    To examine the association between a mobile phone intervention and skilled delivery attendance in a resource-limited setting. Pragmatic cluster-randomised controlled trial with primary healthcare facilities as the unit of randomisation. Primary healthcare facilities in Zanzibar. Two thousand, five hundred and fifty pregnant women (1311 interventions and 1239 controls) who attended antenatal care at one of the selected primary healthcare facilities were included at their first antenatal care visit and followed until 42 days after delivery. All pregnant women were eligible for study participation. Twenty-four primary healthcare facilities in six districts in Zanzibar were allocated by simple randomisation to either mobile phone intervention (n = 12) or standard care (n = 12). The intervention consisted of a short messaging service (SMS) and mobile phone voucher component. Skilled delivery attendance. The mobile phone intervention was associated with an increase in skilled delivery attendance: 60% of the women in the intervention group versus 47% in the control group delivered with skilled attendance. The intervention produced a significant increase in skilled delivery attendance amongst urban women (odds ratio, 5.73; 95% confidence interval, 1.51-21.81), but did not reach rural women. The mobile phone intervention significantly increased skilled delivery attendance amongst women of urban residence. Mobile phone solutions may contribute to the saving of lives of women and their newborns and the achievement of Millennium Development Goals 4 and 5, and should be considered by maternal and child health policy makers in developing countries. © 2012 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2012 RCOG.

  12. A Comprehensive Study of Neutralizing Antigenic Sites on the Hepatitis E Virus (HEV) Capsid by Constructing, Clustering, and Characterizing a Tool Box*

    Science.gov (United States)

    Zhao, Min; Li, Xiao-Jing; Tang, Zi-Min; Yang, Fan; Wang, Si-Ling; Cai, Wei; Zhang, Ke; Xia, Ning-Shao; Zheng, Zi-Zheng

    2015-01-01

    The hepatitis E virus (HEV) ORF2 encodes a single structural capsid protein. The E2s domain (amino acids 459–606) of the capsid protein has been identified as the major immune target. All identified neutralizing epitopes are located on this domain; however, a comprehensive characterization of antigenic sites on the domain is lacking due to its high degree of conformation dependence. Here, we used the statistical software SPSS to analyze cELISA (competitive ELISA) data to classify monoclonal antibodies (mAbs), which recognized conformational epitopes on E2s domain. Using this novel analysis method, we identified various conformational mAbs that recognized the E2s domain. These mAbs were distributed into 6 independent groups, suggesting the presence of at least 6 epitopes. Twelve representative mAbs covering the six groups were selected as a tool box to further map functional antigenic sites on the E2s domain. By combining functional and location information of the 12 representative mAbs, this study provided a complete picture of potential neutralizing epitope regions and immune-dominant determinants on E2s domain. One epitope region is located on top of the E2s domain close to the monomer interface; the other is located on the monomer side of the E2s dimer around the groove zone. Besides, two non-neutralizing epitopes were also identified on E2s domain that did not stimulate neutralizing antibodies. Our results help further the understanding of protective mechanisms induced by the HEV vaccine. Furthermore, the tool box with 12 representative mAbs will be useful for studying the HEV infection process. PMID:26085097

  13. 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.

  14. Clustering analysis

    International Nuclear Information System (INIS)

    Romli

    1997-01-01

    Cluster analysis is the name of group of multivariate techniques whose principal purpose is to distinguish similar entities from the characteristics they process.To study this analysis, there are several algorithms that can be used. Therefore, this topic focuses to discuss the algorithms, such as, similarity measures, and hierarchical clustering which includes single linkage, complete linkage and average linkage method. also, non-hierarchical clustering method, which is popular name K -mean method ' will be discussed. Finally, this paper will be described the advantages and disadvantages of every methods

  15. Cluster analysis

    CERN Document Server

    Everitt, Brian S; Leese, Morven; Stahl, Daniel

    2011-01-01

    Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.Real life examples are used throughout to demons

  16. Cluster editing

    DEFF Research Database (Denmark)

    Böcker, S.; Baumbach, Jan

    2013-01-01

    . The problem has been the inspiration for numerous algorithms in bioinformatics, aiming at clustering entities such as genes, proteins, phenotypes, or patients. In this paper, we review exact and heuristic methods that have been proposed for the Cluster Editing problem, and also applications......The Cluster Editing problem asks to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. Although the problem has been proven NP-complete several times, it has nevertheless attracted much research both from the theoretical and the applied side...

  17. Occupational Clusters.

    Science.gov (United States)

    Pottawattamie County School System, Council Bluffs, IA.

    The 15 occupational clusters (transportation, fine arts and humanities, communications and media, personal service occupations, construction, hospitality and recreation, health occupations, marine science occupations, consumer and homemaking-related occupations, agribusiness and natural resources, environment, public service, business and office…

  18. Effectiveness of the Assessment of Burden of COPD (ABC) tool on health-related quality of life in patients with COPD: a cluster randomised controlled trial in primary and hospital care

    Science.gov (United States)

    Slok, Annerika H M; Kotz, Daniel; van Breukelen, Gerard; Chavannes, Niels H; Rutten-van Mölken, Maureen P M H; Kerstjens, Huib A M; van der Molen, Thys; Asijee, Guus M; Dekhuijzen, P N Richard; Holverda, Sebastiaan; Salomé, Philippe L; Goossens, Lucas M A; Twellaar, Mascha; in ‘t Veen, Johannes C C M; van Schayck, Onno C P

    2016-01-01

    Objective Assessing the effectiveness of the Assessment of Burden of COPD (ABC) tool on disease-specific quality of life in patients with chronic obstructive pulmonary disease (COPD) measured with the St. George's Respiratory Questionnaire (SGRQ), compared with usual care. Methods A pragmatic cluster randomised controlled trial, in 39 Dutch primary care practices and 17 hospitals, with 357 patients with COPD (postbronchodilator FEV1/FVC ratio <0.7) aged ≥40 years, who could understand and read the Dutch language. Healthcare providers were randomly assigned to the intervention or control group. The intervention group applied the ABC tool, which consists of a short validated questionnaire assessing the experienced burden of COPD, objective COPD parameter (eg, lung function) and a treatment algorithm including a visual display and treatment advice. The control group provided usual care. Researchers were blinded to group allocation during analyses. Primary outcome was the number of patients with a clinically relevant improvement in SGRQ score between baseline and 18-month follow-up. Secondary outcomes were the COPD Assessment Test (CAT) and the Patient Assessment of Chronic Illness Care (PACIC; a measurement of perceived quality of care). Results At 18-month follow-up, 34% of the 146 patients from 27 healthcare providers in the intervention group showed a clinically relevant improvement in the SGRQ, compared with 22% of the 148 patients from 29 healthcare providers in the control group (OR 1.85, 95% CI 1.08 to 3.16). No difference was found on the CAT (−0.26 points (scores ranging from 0 to 40); 95% CI −1.52 to 0.99). The PACIC showed a higher improvement in the intervention group (0.32 points (scores ranging from 1 to 5); 95% CI 0.14 to 0.50). Conclusions This study showed that use of the ABC tool may increase quality of life and perceived quality of care. Trial registration number NTR3788; Results. PMID:27401361

  19. Co-clustering models, algorithms and applications

    CERN Document Server

    Govaert, Gérard

    2013-01-01

    Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach. Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixture

  20. 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

  1. Cluster generator

    Science.gov (United States)

    Donchev, Todor I [Urbana, IL; Petrov, Ivan G [Champaign, IL

    2011-05-31

    Described herein is an apparatus and a method for producing atom clusters based on a gas discharge within a hollow cathode. The hollow cathode includes one or more walls. The one or more walls define a sputtering chamber within the hollow cathode and include a material to be sputtered. A hollow anode is positioned at an end of the sputtering chamber, and atom clusters are formed when a gas discharge is generated between the hollow anode and the hollow cathode.

  2. 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...

  3. Cluster headache

    OpenAIRE

    Leroux, Elizabeth; Ducros, Anne

    2008-01-01

    Abstract Cluster headache (CH) is a primary headache disease characterized by recurrent short-lasting attacks (15 to 180 minutes) of excruciating unilateral periorbital pain accompanied by ipsilateral autonomic signs (lacrimation, nasal congestion, ptosis, miosis, lid edema, redness of the eye). It affects young adults, predominantly males. Prevalence is estimated at 0.5–1.0/1,000. CH has a circannual and circadian periodicity, attacks being clustered (hence the name) in bouts that can occur ...

  4. Design of the Lifestyle Interventions for severe mentally ill Outpatients in the Netherlands (LION) trial; a cluster randomised controlled study of a multidimensional web tool intervention to improve cardiometabolic health in patients with severe mental illness.

    Science.gov (United States)

    Looijmans, Anne; Jörg, Frederike; Bruggeman, Richard; Schoevers, Robert; Corpeleijn, Eva

    2017-03-21

    The cardiometabolic health of persons with a severe mental illness (SMI) is alarming with obesity rates of 45-55% and diabetes type 2 rates of 10-15%. Unhealthy lifestyle behaviours play a large role in this. Despite the multidisciplinary guideline for SMI patients recommending to monitor and address patients' lifestyle, most mental health care professionals have limited lifestyle-related knowledge and skills, and (lifestyle) treatment protocols are lacking. Evidence-based practical lifestyle tools may support both patients and staff in improving patients' lifestyle. This paper describes the Lifestyle Interventions for severe mentally ill Outpatients in the Netherlands (LION) trial, to investigate whether a multidimensional lifestyle intervention using a web tool can be effective in improving cardiometabolic health in SMI patients. The LION study is a 12-month pragmatic single-blind multi-site cluster randomised controlled trial. 21 Flexible Assertive Community Treatment (ACT) teams and eight sheltered living teams of five mental health organizations in the Netherlands are invited to participate. Per team, nurses are trained in motivational interviewing and use of the multidimensional web tool, covering lifestyle behaviour awareness, lifestyle knowledge, motivation and goal setting. Nurses coach patients to change their lifestyle using the web tool, motivational interviewing and stages-of-change techniques during biweekly sessions in a) assessing current lifestyle behaviour using the traffic light method (healthy behaviours colour green, unhealthy behaviours colour red), b) creating a lifestyle plan with maximum three attainable lifestyle goals and c) discussing the lifestyle plan regularly. The study population is SMI patients and statistical inference is on patient level using multilevel analyses. Primary outcome is waist circumference and other cardiometabolic risk factors after six and twelve months intervention, which are measured as part of routine outcome

  5. The impact of a knowledge translation intervention employing educational outreach and a point-of-care reminder tool vs standard lay health worker training on tuberculosis treatment completion rates: study protocol for a cluster randomized controlled trial.

    Science.gov (United States)

    Puchalski Ritchie, Lisa M; van Lettow, Monique; Makwakwa, Austine; Chan, Adrienne K; Hamid, Jemila S; Kawonga, Harry; Martiniuk, Alexandra L C; Schull, Michael J; van Schoor, Vanessa; Zwarenstein, Merrick; Barnsley, Jan; Straus, Sharon E

    2016-09-07

    Despite availability of effective treatment, tuberculosis (TB) remains an important cause of morbidity and mortality globally, with low- and middle-income countries most affected. In many such settings, including Malawi, the high burden of disease and severe shortage of skilled healthcare workers has led to task-shifting of outpatient TB care to lay health workers (LHWs). LHWs improve access to healthcare and some outcomes, including TB completion rates, but lack of training and supervision limit their impact. The goals of this study are to improve TB care provided by LHWs in Malawi by refining, implementing, and evaluating a knowledge translation strategy designed to address a recognized gap in LHWs' TB and job-specific knowledge and, through this, to improve patient outcomes. We are employing a mixed-methods design that includes a pragmatic cluster randomized controlled trial and a process evaluation using qualitative methods. Trial participants will include all health centers providing TB care in four districts in the South East Zone of Malawi. The intervention employs educational outreach, a point-of-care reminder tool, and a peer support network. The primary outcome is proportion of treatment successes, defined as the total of TB patients cured or completing treatment, with outcomes taken from Ministry of Health treatment records. With an alpha of 0.05, power of 0.80, a baseline treatment success of 0.80, intraclass correlation coefficient of 0.1 based on our pilot study, and an estimated 100 clusters (health centers providing TB care), a minimum of 6 patients per cluster is required to detect a clinically significant 0.10 increase in the proportion of treatment successes. Our process evaluation will include interviews with LHWs and patients, and a document analysis of LHW training logs, quarterly peer trainer meetings, and mentorship meeting notes. An estimated 10-15 LHWs and 10-15 patients will be required to reach saturation in each of 2 planned interview

  6. Statistical Significance for Hierarchical Clustering

    Science.gov (United States)

    Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

    2017-01-01

    Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

  7. Speckle imaging of globular clusters

    International Nuclear Information System (INIS)

    Sams, B.J. III

    1990-01-01

    Speckle imaging is a powerful tool for high resolution astronomy. Its application to the core regions of globular clusters produces high resolution stellar maps of the bright stars, but is unable to image the faint stars which are most reliable dynamical indicators. The limits on resolving these faint, extended objects are physical, not algorithmic, and cannot be overcome using speckle. High resolution maps may be useful for resolving multicomponent stellar systems in the cluster centers. 30 refs

  8. Genetic algorithm based two-mode clustering of metabolomics data

    NARCIS (Netherlands)

    Hageman, J.A.; van den Berg, R.A.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

    2008-01-01

    Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering

  9. Clustering Dycom

    KAUST Repository

    Minku, Leandro L.; Hou, Siqing

    2017-01-01

    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

  10. Computational Design of Clusters for Catalysis

    Science.gov (United States)

    Jimenez-Izal, Elisa; Alexandrova, Anastassia N.

    2018-04-01

    When small clusters are studied in chemical physics or physical chemistry, one perhaps thinks of the fundamental aspects of cluster electronic structure, or precision spectroscopy in ultracold molecular beams. However, small clusters are also of interest in catalysis, where the cold ground state or an isolated cluster may not even be the right starting point. Instead, the big question is: What happens to cluster-based catalysts under real conditions of catalysis, such as high temperature and coverage with reagents? Myriads of metastable cluster states become accessible, the entire system is dynamic, and catalysis may be driven by rare sites present only under those conditions. Activity, selectivity, and stability are highly dependent on size, composition, shape, support, and environment. To probe and master cluster catalysis, sophisticated tools are being developed for precision synthesis, operando measurements, and multiscale modeling. This review intends to tell the messy story of clusters in catalysis.

  11. Cluster analysis of received constellations for optical performance monitoring

    NARCIS (Netherlands)

    van Weerdenburg, J.J.A.; van Uden, R.; Sillekens, E.; de Waardt, H.; Koonen, A.M.J.; Okonkwo, C.

    2016-01-01

    Performance monitoring based on centroid clustering to investigate constellation generation offsets. The tool allows flexibility in constellation generation tolerances by forwarding centroids to the demapper. The relation of fibre nonlinearities and singular value decomposition of intra-cluster

  12. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    The cluster theory attributed to Michael Porter has significantly influenced industrial policies in countries across Europe and North America since the beginning of the 1990s. Institutions such as the EU, OECD and the World Bank and governments in countries such as the UK, France, The Netherlands...... or management. Both the Accelerate Wales and the Accelerate Cluster programmes target this issue by trying to establish networks between companies that can be used to supply knowledge from research institutions to manufacturing companies. The paper concludes that public sector interventions can make...... businesses. The universities were not considered by the participating companies to be important parts of the local business environment and inputs from universities did not appear to be an important source to access knowledge about new product development or new techniques in production, distribution...

  13. Regional Innovation Clusters

    Data.gov (United States)

    Small Business Administration — The Regional Innovation Clusters serve a diverse group of sectors and geographies. Three of the initial pilot clusters, termed Advanced Defense Technology clusters,...

  14. Cluster analysis

    OpenAIRE

    Mucha, Hans-Joachim; Sofyan, Hizir

    2000-01-01

    As an explorative technique, duster analysis provides a description or a reduction in the dimension of the data. It classifies a set of observations into two or more mutually exclusive unknown groups based on combinations of many variables. Its aim is to construct groups in such a way that the profiles of objects in the same groups are relatively homogenous whereas the profiles of objects in different groups are relatively heterogeneous. Clustering is distinct from classification techniques, ...

  15. Cluster algebras in mathematical physics

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  16. Educational Outreach with an Integrated Clinical Tool for Nurse-Led Non-communicable Chronic Disease Management in Primary Care in South Africa: A Pragmatic Cluster Randomised Controlled Trial.

    Science.gov (United States)

    Fairall, Lara R; Folb, Naomi; Timmerman, Venessa; Lombard, Carl; Steyn, Krisela; Bachmann, Max O; Bateman, Eric D; Lund, Crick; Cornick, Ruth; Faris, Gill; Gaziano, Thomas; Georgeu-Pepper, Daniella; Zwarenstein, Merrick; Levitt, Naomi S

    2016-11-01

    In many low-income countries, care for patients with non-communicable diseases (NCDs) and mental health conditions is provided by nurses. The benefits of nurse substitution and supplementation in NCD care in high-income settings are well recognised, but evidence from low- and middle-income countries is limited. Primary Care 101 (PC101) is a programme designed to support and expand nurses' role in NCD care, comprising educational outreach to nurses and a clinical management tool with enhanced prescribing provisions. We evaluated the effect of the programme on primary care nurses' capacity to manage NCDs. In a cluster randomised controlled trial design, 38 public sector primary care clinics in the Western Cape Province, South Africa, were randomised. Nurses in the intervention clinics were trained to use the PC101 management tool during educational outreach sessions delivered by health department trainers and were authorised to prescribe an expanded range of drugs for several NCDs. Control clinics continued use of the Practical Approach to Lung Health and HIV/AIDS in South Africa (PALSA PLUS) management tool and usual training. Patients attending these clinics with one or more of hypertension (3,227), diabetes (1,842), chronic respiratory disease (1,157) or who screened positive for depression (2,466), totalling 4,393 patients, were enrolled between 28 March 2011 and 10 November 2011. Primary outcomes were treatment intensification in the hypertension, diabetes, and chronic respiratory disease cohorts, defined as the proportion of patients in whom treatment was escalated during follow-up over 14 mo, and case detection in the depression cohort. Primary outcome data were analysed for 2,110 (97%) intervention and 2,170 (97%) control group patients. Treatment intensification rates in intervention clinics were not superior to those in the control clinics (hypertension: 44% in the intervention group versus 40% in the control group, risk ratio [RR] 1.08 [95% CI 0.94 to 1

  17. Clustering methods for the optimization of atomic cluster structure

    Science.gov (United States)

    Bagattini, Francesco; Schoen, Fabio; Tigli, Luca

    2018-04-01

    In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.

  18. CORECLUSTER: A Degeneracy Based Graph Clustering Framework

    OpenAIRE

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

    2014-01-01

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

  19. Cluster growing process and a sequence of magic numbers

    DEFF Research Database (Denmark)

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

    2003-01-01

    demonstrate that in this way all known global minimum structures of the Lennard-Jones (LJ) 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 for the clusters of noble gas atoms......We present a new theoretical framework for modeling the cluster growing process. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system, and absorbing its energy at each step, we find cluster growing paths up to the cluster sizes of more than 100 atoms. We...

  20. 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

  1. X ray emission: a tool and a probe for laser - clusters interaction; L'emission X: un outil et une sonde pour l'interaction laser - agregats

    Energy Technology Data Exchange (ETDEWEB)

    Prigent, Ch

    2004-12-01

    In intense laser-cluster interaction, the experimental results show a strong energetic coupling between radiation and matter. We have measured absolute X-ray yields and charge state distributions under well control conditions as a function of physical parameters governing the interaction; namely laser intensity, pulse duration, wavelength or polarization state of the laser light, the size and the species of the clusters (Ar, Kr, Xe). We have highlighted, for the first time, an intensity threshold in the X-ray production very low ({approx} 2.10{sup 14} W/cm{sup 2} for a pulse duration of 300 fs) which can results from an effect of the dynamical polarisation of clusters in an intense electric field. A weak dependence with the wavelength (400 nm / 800 nm) on the absolute X-ray yields has been found. Moreover, we have observed a saturation of the X-ray emission probability below a critical cluster size. (author)

  2. Large scale cluster computing workshop

    International Nuclear Information System (INIS)

    Dane Skow; Alan Silverman

    2002-01-01

    Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community

  3. 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.

  4. Cluster headache

    Directory of Open Access Journals (Sweden)

    Ducros Anne

    2008-07-01

    Full Text Available Abstract Cluster headache (CH is a primary headache disease characterized by recurrent short-lasting attacks (15 to 180 minutes of excruciating unilateral periorbital pain accompanied by ipsilateral autonomic signs (lacrimation, nasal congestion, ptosis, miosis, lid edema, redness of the eye. It affects young adults, predominantly males. Prevalence is estimated at 0.5–1.0/1,000. CH has a circannual and circadian periodicity, attacks being clustered (hence the name in bouts that can occur during specific months of the year. Alcohol is the only dietary trigger of CH, strong odors (mainly solvents and cigarette smoke and napping may also trigger CH attacks. During bouts, attacks may happen at precise hours, especially during the night. During the attacks, patients tend to be restless. CH may be episodic or chronic, depending on the presence of remission periods. CH is associated with trigeminovascular activation and neuroendocrine and vegetative disturbances, however, the precise cautive mechanisms remain unknown. Involvement of the hypothalamus (a structure regulating endocrine function and sleep-wake rhythms has been confirmed, explaining, at least in part, the cyclic aspects of CH. The disease is familial in about 10% of cases. Genetic factors play a role in CH susceptibility, and a causative role has been suggested for the hypocretin receptor gene. Diagnosis is clinical. Differential diagnoses include other primary headache diseases such as migraine, paroxysmal hemicrania and SUNCT syndrome. At present, there is no curative treatment. There are efficient treatments to shorten the painful attacks (acute treatments and to reduce the number of daily attacks (prophylactic treatments. Acute treatment is based on subcutaneous administration of sumatriptan and high-flow oxygen. Verapamil, lithium, methysergide, prednisone, greater occipital nerve blocks and topiramate may be used for prophylaxis. In refractory cases, deep-brain stimulation of the

  5. IntroductionThe Cluster mission

    Directory of Open Access Journals (Sweden)

    M. Fehringer

    Full Text Available The Cluster mission, ESA’s first cornerstone project, together with the SOHO mission, dating back to the first proposals in 1982, was finally launched in the summer of 2000. On 16 July and 9 August, respectively, two Russian Soyuz rockets blasted off from the Russian cosmodrome in Baikonour to deliver two Cluster spacecraft, each into their proper orbit. By the end of August 2000, the four Cluster satellites had reached their final tetrahedral constellation. The commissioning of 44 instruments, both individually and as an ensemble of complementary tools, was completed five months later to ensure the optimal use of their combined observational potential. On 1 February 2001, the mission was declared operational. The main goal of the Cluster mission is to study the small-scale plasma structures in three dimensions in key plasma regions, such as the solar wind, bow shock, magnetopause, polar cusps, magnetotail and the auroral zones. With its unique capabilities of three-dimensional spatial resolution, Cluster plays a major role in the International Solar Terrestrial Program (ISTP, where Cluster and the Solar and Heliospheric Observatory (SOHO are the European contributions. Cluster’s payload consists of state-of-the-art plasma instrumentation to measure electric and magnetic fields from the quasi-static up to high frequencies, and electron and ion distribution functions from energies of nearly 0 eV to a few MeV. The science operations are coordinated by the Joint Science Operations Centre (JSOC, at the Rutherford Appleton Laboratory (UK, and implemented by the European Space Operations Centre (ESOC, in Darmstadt, Germany. A network of eight national data centres has been set up for raw data processing, for the production of physical parameters, and their distribution to end users all over the world. The latest information on the Cluster mission can be found at http://sci.esa.int/cluster/.

  6. IntroductionThe Cluster mission

    Directory of Open Access Journals (Sweden)

    C. P. Escoubet

    2001-09-01

    Full Text Available The Cluster mission, ESA’s first cornerstone project, together with the SOHO mission, dating back to the first proposals in 1982, was finally launched in the summer of 2000. On 16 July and 9 August, respectively, two Russian Soyuz rockets blasted off from the Russian cosmodrome in Baikonour to deliver two Cluster spacecraft, each into their proper orbit. By the end of August 2000, the four Cluster satellites had reached their final tetrahedral constellation. The commissioning of 44 instruments, both individually and as an ensemble of complementary tools, was completed five months later to ensure the optimal use of their combined observational potential. On 1 February 2001, the mission was declared operational. The main goal of the Cluster mission is to study the small-scale plasma structures in three dimensions in key plasma regions, such as the solar wind, bow shock, magnetopause, polar cusps, magnetotail and the auroral zones. With its unique capabilities of three-dimensional spatial resolution, Cluster plays a major role in the International Solar Terrestrial Program (ISTP, where Cluster and the Solar and Heliospheric Observatory (SOHO are the European contributions. Cluster’s payload consists of state-of-the-art plasma instrumentation to measure electric and magnetic fields from the quasi-static up to high frequencies, and electron and ion distribution functions from energies of nearly 0 eV to a few MeV. The science operations are coordinated by the Joint Science Operations Centre (JSOC, at the Rutherford Appleton Laboratory (UK, and implemented by the European Space Operations Centre (ESOC, in Darmstadt, Germany. A network of eight national data centres has been set up for raw data processing, for the production of physical parameters, and their distribution to end users all over the world. The latest information on the Cluster mission can be found at http://sci.esa.int/cluster/.

  7. Brightest Cluster Galaxies in REXCESS Clusters

    Science.gov (United States)

    Haarsma, Deborah B.; Leisman, L.; Bruch, S.; Donahue, M.

    2009-01-01

    Most galaxy clusters contain a Brightest Cluster Galaxy (BCG) which is larger than the other cluster ellipticals and has a more extended profile. In the hierarchical model, the BCG forms through many galaxy mergers in the crowded center of the cluster, and thus its properties give insight into the assembly of the cluster as a whole. In this project, we are working with the Representative XMM-Newton Cluster Structure Survey (REXCESS) team (Boehringer et al 2007) to study BCGs in 33 X-ray luminous galaxy clusters, 0.055 < z < 0.183. We are imaging the BCGs in R band at the Southern Observatory for Astrophysical Research (SOAR) in Chile. In this poster, we discuss our methods and give preliminary measurements of the BCG magnitudes, morphology, and stellar mass. We compare these BCG properties with the properties of their host clusters, particularly of the X-ray emitting gas.

  8. Multiple Clustering Views via Constrained Projections

    DEFF Research Database (Denmark)

    Dang, Xuan-Hong; Assent, Ira; Bailey, James

    2012-01-01

    Clustering, the grouping of data based on mutual similarity, is often used as one of principal tools to analyze and understand data. Unfortunately, most conventional techniques aim at finding only a single clustering over the data. For many practical applications, especially those being described...... in high dimensional data, it is common to see that the data can be grouped into different yet meaningful ways. This gives rise to the recently emerging research area of discovering alternative clusterings. In this preliminary work, we propose a novel framework to generate multiple clustering views....... The framework relies on a constrained data projection approach by which we ensure that a novel alternative clustering being found is not only qualitatively strong but also distinctively different from a reference clustering solution. We demonstrate the potential of the proposed framework using both synthetic...

  9. Cluster Ion Implantation in Graphite and Diamond

    DEFF Research Database (Denmark)

    Popok, Vladimir

    2014-01-01

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

  10. Partitional clustering algorithms

    CERN Document Server

    2015-01-01

    This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

  11. Clustering Coefficients for Correlation Networks.

    Science.gov (United States)

    Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

    2018-01-01

    Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

  12. Clustering Coefficients for Correlation Networks

    Directory of Open Access Journals (Sweden)

    Naoki Masuda

    2018-03-01

    Full Text Available Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients

  13. Clustering Coefficients for Correlation Networks

    Science.gov (United States)

    Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

    2018-01-01

    Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

  14. 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.

  15. 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.

  16. Effects on energetic impact of atomic clusters with surfaces

    International Nuclear Information System (INIS)

    Popok, V.N.; Vuchkovich, S.; Abdela, A.; Campbell, E.E.B.

    2007-01-01

    A brief state-of-the-art review in the field of cluster ion interaction with surface is presented. Cluster beams are efficient tools for manipulating agglomerates of atoms providing control over the synthesis as well as modification of surfaces on the nm-scale. The application of cluster beams for technological purposes requires knowledge of the physics of cluster-surface impact. This has some significant differences compared to monomer ion - surface interactions. The main effects of cluster-surface collisions are discussed. Recent results obtained in experiments on silicon surface nanostructuring using keV-energy implantation of inert gas cluster ions are presented and compared with molecular dynamics simulations. (authors)

  17. Interactive visual exploration and refinement of cluster assignments.

    Science.gov (United States)

    Kern, Michael; Lex, Alexander; Gehlenborg, Nils; Johnson, Chris R

    2017-09-12

    With ever-increasing amounts of data produced in biology research, scientists are in need of efficient data analysis methods. Cluster analysis, combined with visualization of the results, is one such method that can be used to make sense of large data volumes. At the same time, cluster analysis is known to be imperfect and depends on the choice of algorithms, parameters, and distance measures. Most clustering algorithms don't properly account for ambiguity in the source data, as records are often assigned to discrete clusters, even if an assignment is unclear. While there are metrics and visualization techniques that allow analysts to compare clusterings or to judge cluster quality, there is no comprehensive method that allows analysts to evaluate, compare, and refine cluster assignments based on the source data, derived scores, and contextual data. In this paper, we introduce a method that explicitly visualizes the quality of cluster assignments, allows comparisons of clustering results and enables analysts to manually curate and refine cluster assignments. Our methods are applicable to matrix data clustered with partitional, hierarchical, and fuzzy clustering algorithms. Furthermore, we enable analysts to explore clustering results in context of other data, for example, to observe whether a clustering of genomic data results in a meaningful differentiation in phenotypes. Our methods are integrated into Caleydo StratomeX, a popular, web-based, disease subtype analysis tool. We show in a usage scenario that our approach can reveal ambiguities in cluster assignments and produce improved clusterings that better differentiate genotypes and phenotypes.

  18. Diversity among galaxy clusters

    International Nuclear Information System (INIS)

    Struble, M.F.; Rood, H.J.

    1988-01-01

    The classification of galaxy clusters is discussed. Consideration is given to the classification scheme of Abell (1950's), Zwicky (1950's), Morgan, Matthews, and Schmidt (1964), and Morgan-Bautz (1970). Galaxies can be classified based on morphology, chemical composition, spatial distribution, and motion. The correlation between a galaxy's environment and morphology is examined. The classification scheme of Rood-Sastry (1971), which is based on clusters's morphology and galaxy population, is described. The six types of clusters they define include: (1) a cD-cluster dominated by a single large galaxy, (2) a cluster dominated by a binary, (3) a core-halo cluster, (4) a cluster dominated by several bright galaxies, (5) a cluster appearing flattened, and (6) an irregularly shaped cluster. Attention is also given to the evolution of cluster structures, which is related to initial density and cluster motion

  19. What Makes Clusters Decline?

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    2015-01-01

    Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark. The longit...... but being quick to withdraw in times of crisis....

  20. Clustering of correlated networks

    OpenAIRE

    Dorogovtsev, S. N.

    2003-01-01

    We obtain the clustering coefficient, the degree-dependent local clustering, and the mean clustering of networks with arbitrary correlations between the degrees of the nearest-neighbor vertices. The resulting formulas allow one to determine the nature of the clustering of a network.

  1. cluML: A markup language for clustering and cluster validity assessment of microarray data.

    Science.gov (United States)

    Bolshakova, Nadia; Cunningham, Pádraig

    2005-01-01

    cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

  2. Relevant Subspace Clustering

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

    2009-01-01

    Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace...... clusters. Their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. In this work, we propose a novel model for relevant subspace clustering (RESCU). We present a global optimization which detects the most interesting non-redundant subspace clusters...... achieves top clustering quality while competing approaches show greatly varying performance....

  3. PREFACE: Nuclear Cluster Conference; Cluster'07

    Science.gov (United States)

    Freer, Martin

    2008-05-01

    The Cluster Conference is a long-running conference series dating back to the 1960's, the first being initiated by Wildermuth in Bochum, Germany, in 1969. The most recent meeting was held in Nara, Japan, in 2003, and in 2007 the 9th Cluster Conference was held in Stratford-upon-Avon, UK. As the name suggests the town of Stratford lies upon the River Avon, and shortly before the conference, due to unprecedented rainfall in the area (approximately 10 cm within half a day), lay in the River Avon! Stratford is the birthplace of the `Bard of Avon' William Shakespeare, and this formed an intriguing conference backdrop. The meeting was attended by some 90 delegates and the programme contained 65 70 oral presentations, and was opened by a historical perspective presented by Professor Brink (Oxford) and closed by Professor Horiuchi (RCNP) with an overview of the conference and future perspectives. In between, the conference covered aspects of clustering in exotic nuclei (both neutron and proton-rich), molecular structures in which valence neutrons are exchanged between cluster cores, condensates in nuclei, neutron-clusters, superheavy nuclei, clusters in nuclear astrophysical processes and exotic cluster decays such as 2p and ternary cluster decay. The field of nuclear clustering has become strongly influenced by the physics of radioactive beam facilities (reflected in the programme), and by the excitement that clustering may have an important impact on the structure of nuclei at the neutron drip-line. It was clear that since Nara the field had progressed substantially and that new themes had emerged and others had crystallized. Two particular topics resonated strongly condensates and nuclear molecules. These topics are thus likely to be central in the next cluster conference which will be held in 2011 in the Hungarian city of Debrechen. Martin Freer Participants and Cluster'07

  4. Effectiveness of the Assessment of Burden of COPD (ABC) tool on health-related quality of life in patients with COPD : A cluster randomised controlled trial in primary and hospital care

    NARCIS (Netherlands)

    A.H.M. Slok (Annerika); D. Kotz (Daniel); G.J.P. van Breukelen (Gerard); N.H. Chavannes (Nicolas); M.P.M.H. Rutten-van Mölken (Maureen); H.A.M. Kerstjens (Huib); T. van der Molen (Thys); G.M. Asijee (Guus); P.N.R. Dekhuijzen (Richard); S. Holverda (Sebastiaan); P.L. Salome´ (Philippe); L.M.A. Goossens (Lucas); M. Twellaar (Mascha); J.C.C.M. In't Veen (Johannes C.C.M.); O.C.P. Schayck (Onno)

    2016-01-01

    markdownabstractObjective: Assessing the effectiveness of the Assessment of Burden of COPD (ABC) tool on diseasespecific quality of life in patients with chronic obstructive pulmonary disease (COPD) measured with the St. George's Respiratory Questionnaire (SGRQ), compared with usual care.

  5. The GNEMRE Dendro Tool.

    Energy Technology Data Exchange (ETDEWEB)

    Merchant, Bion John

    2007-10-01

    The GNEMRE Dendro Tool provides a previously unrealized analysis capability in the field of nuclear explosion monitoring. Dendro Tool allows analysts to quickly and easily determine the similarity between seismic events using the waveform time-series for each of the events to compute cross-correlation values. Events can then be categorized into clusters of similar events. This analysis technique can be used to characterize historical archives of seismic events in order to determine many of the unique sources that are present. In addition, the source of any new events can be quickly identified simply by comparing the new event to the historical set.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Management of cluster headache

    DEFF Research Database (Denmark)

    Tfelt-Hansen, Peer C; Jensen, Rigmor H

    2012-01-01

    The prevalence of cluster headache is 0.1% and cluster headache is often not diagnosed or misdiagnosed as migraine or sinusitis. In cluster headache there is often a considerable diagnostic delay - an average of 7 years in a population-based survey. Cluster headache is characterized by very severe...... or severe orbital or periorbital pain with a duration of 15-180 minutes. The cluster headache attacks are accompanied by characteristic associated unilateral symptoms such as tearing, nasal congestion and/or rhinorrhoea, eyelid oedema, miosis and/or ptosis. In addition, there is a sense of restlessness...... and agitation. Patients may have up to eight attacks per day. Episodic cluster headache (ECH) occurs in clusters of weeks to months duration, whereas chronic cluster headache (CCH) attacks occur for more than 1 year without remissions. Management of cluster headache is divided into acute attack treatment...

  8. 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

  9. Cluster Decline and Resilience

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark, 1963......-2011. Our longitudinal study reveals that technological lock-in and exit of key firms have contributed to impairment of the cluster’s resilience in adapting to disruptions. Entrepreneurship has a positive effect on cluster resilience, while multinational companies have contradicting effects by bringing...... in new resources to the cluster but being quick to withdraw in times of crisis....

  10. Comprehensive cluster analysis with Transitivity Clustering.

    Science.gov (United States)

    Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

    2011-03-01

    Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

  11. LMC clusters: young

    International Nuclear Information System (INIS)

    Freeman, K.C.

    1980-01-01

    The young globular clusters of the LMC have ages of 10 7 -10 8 y. Their masses and structure are similar to those of the smaller galactic globular clusters. Their stellar mass functions (in the mass range 6 solar masses to 1.2 solar masses) vary greatly from cluster to cluster, although the clusters are similar in total mass, age, structure and chemical composition. It would be very interesting to know why these clusters are forming now in the LMC and not in the Galaxy. The author considers the 'young globular' or 'blue populous' clusters of the LMC. The ages of these objects are 10 7 to 10 8 y, and their masses are 10 4 to 10 5 solar masses, so they are populous enough to be really useful for studying the evolution of massive stars. The author concentrates on the structure and stellar content of these young clusters. (Auth.)

  12. Star clusters and associations

    International Nuclear Information System (INIS)

    Ruprecht, J.; Palous, J.

    1983-01-01

    All 33 papers presented at the symposium were inputted to INIS. They dealt with open clusters, globular clusters, stellar associations and moving groups, and local kinematics and galactic structures. (E.S.)

  13. Cluster beam injection

    International Nuclear Information System (INIS)

    Bottiglioni, F.; Coutant, J.; Fois, M.

    1978-01-01

    Areas of possible applications of cluster injection are discussed. The deposition inside the plasma of molecules, issued from the dissociation of the injected clusters, has been computed. Some empirical scaling laws for the penetration are given

  14. Clustering at high redshifts

    International Nuclear Information System (INIS)

    Shaver, P.A.

    1986-01-01

    Evidence for clustering of and with high-redshift QSOs is discussed. QSOs of different redshifts show no clustering, but QSOs of similar redshifts appear to be clustered on a scale comparable to that of galaxies at the present epoch. In addition, spectroscopic studies of close pairs of QSOs indicate that QSOs are surrounded by a relatively high density of absorbing matter, possibly clusters of galaxies

  15. Shared decision making in type 2 diabetes with a support decision tool that takes into account clinical factors, the intensity of treatment and patient preferences : Design of a cluster randomised (OPTIMAL) trial

    NARCIS (Netherlands)

    Den Ouden, Henk; Vos, Rimke C.; Reidsma, Carla; Rutten, Guy Ehm

    2015-01-01

    Background: No more than 10-15% of type 2 diabetes mellitus (T2DM) patients achieve all treatment goals regarding glycaemic control, lipids and blood pressure. Shared decision making (SDM) should increase that percentage; however, not all support decision tools are appropriate. Because the

  16. Effectiveness of the Assessment of Burden of COPD (ABC) tool on health-related quality of life in patients with COPD: a cluster randomised controlled trial in primary and hospital care

    NARCIS (Netherlands)

    A.H.M. Slok (Annerika); D. Kotz (Daniel); G. van Breukelen (Gerard); N.H. Chavannes (Nicolas); M.P.M.H. Rutten-van Mölken (Maureen); H.A.M. Kerstjens (Huib); T. van der Molen (Thys); G.M. Asijee (Guus); P.N.R. Dekhuijzen (Richard); S. Holverda (Sebastiaan); P.L. Salome (Philippe); L.M.A. Goossens (Lucas); M. Twellaar (Mascha); J.C.C.M. in 't Veen (Johannes); O.C.P. van Schayck (Onno)

    2016-01-01

    markdownabstract__Objective:__ Assessing the effectiveness of the Assessment of Burden of COPD (ABC) tool on diseasespecific quality of life in patients with chronic obstructive pulmonary disease (COPD) measured with the St. George’s Respiratory Questionnaire (SGRQ), compared with usual care.

  17. Fragmentation of percolation cluster perimeters

    Science.gov (United States)

    Debierre, Jean-Marc; Bradley, R. Mark

    1996-05-01

    We introduce a model for the fragmentation of porous random solids under the action of an external agent. In our model, the solid is represented by a bond percolation cluster on the square lattice and bonds are removed only at the external perimeter (or `hull') of the cluster. This model is shown to be related to the self-avoiding walk on the Manhattan lattice and to the disconnection events at a diffusion front. These correspondences are used to predict the leading and the first correction-to-scaling exponents for several quantities defined for hull fragmentation. Our numerical results support these predictions. In addition, the algorithm used to construct the perimeters reveals itself to be a very efficient tool for detecting subtle correlations in the pseudo-random number generator used. We present a quantitative test of two generators which supports recent results reported in more systematic studies.

  18. Cluster Physics with Merging Galaxy Clusters

    Directory of Open Access Journals (Sweden)

    Sandor M. Molnar

    2016-02-01

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

  19. Size selected metal clusters

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. The Optical Absorption Spectra of Small Silver Clusters (5-11) ... Soft Landing and Fragmentation of Small Clusters Deposited in Noble-Gas Films. Harbich, W.; Fedrigo, S.; Buttet, J. Phys. Rev. B 1998, 58, 7428. CO combustion on supported gold clusters. Arenz M ...

  20. The Durban Auto Cluster

    DEFF Research Database (Denmark)

    Lorentzen, Jochen; Robbins, Glen; Barnes, Justin

    2004-01-01

    The paper describes the formation of the Durban Auto Cluster in the context of trade liberalization. It argues that the improvement of operational competitiveness of firms in the cluster is prominently due to joint action. It tests this proposition by comparing the gains from cluster activities...

  1. 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.

  2. Marketing research cluster analysis

    OpenAIRE

    Marić Nebojša

    2002-01-01

    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.

  3. Minimalist's linux cluster

    International Nuclear Information System (INIS)

    Choi, Chang-Yeong; Kim, Jeong-Hyun; Kim, Seyong

    2004-01-01

    Using barebone PC components and NIC's, we construct a linux cluster which has 2-dimensional mesh structure. This cluster has smaller footprint, is less expensive, and use less power compared to conventional linux cluster. Here, we report our experience in building such a machine and discuss our current lattice project on the machine

  4. Range-clustering queries

    NARCIS (Netherlands)

    Abrahamsen, M.; de Berg, M.T.; Buchin, K.A.; Mehr, M.; Mehrabi, A.D.

    2017-01-01

    In a geometric k -clustering problem the goal is to partition a set of points in R d into k subsets such that a certain cost function of the clustering is minimized. We present data structures for orthogonal range-clustering queries on a point set S : given a query box Q and an integer k>2 , compute

  5. Cosmology with cluster surveys

    Indian Academy of Sciences (India)

    Abstract. Surveys of clusters of galaxies provide us with a powerful probe of the den- sity and nature of the dark energy. The red-shift distribution of detected clusters is highly sensitive to the dark energy equation of state parameter w. Upcoming Sunyaev–. Zel'dovich (SZ) surveys would provide us large yields of clusters to ...

  6. Clusters in nonsmooth oscillator networks

    Science.gov (United States)

    Nicks, Rachel; Chambon, Lucie; Coombes, Stephen

    2018-03-01

    For coupled oscillator networks with Laplacian coupling, the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory, this approach has recently been extended to treat more general cluster states. However, the MSF and its generalizations require the determination of a set of Floquet multipliers from variational equations obtained by linearization around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by, the framework is often explored using numerical techniques. Here, we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of saltation matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration, we analyze an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris-Lecar neuron model. We use these examples to emphasize that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly, the procedure that we present here, for understanding cluster synchronization in networks, is valid for a wide variety of systems in

  7. Orbital localization criterion as a complementary tool in the bonding analysis by means of electron localization function: study of the Si(n)(BH)(5-n)(2-) (n = 0-5) clusters.

    Science.gov (United States)

    Oña, Ofelia B; Alcoba, Diego R; Torre, Alicia; Lain, Luis; Torres-Vega, Juan J; Tiznado, William

    2013-12-05

    A recently proposed molecular orbital localization procedure, based on the electron localization function (ELF) technique, has been used to describe chemical bonding in the cluster series Sin(BH)(5-n)(2-) (n = 0-5). The method combines the chemically intuitive information obtained from the traditional ELF analysis with the flexibility and generality of canonical molecular orbital theory. This procedure attempts to localize the molecular orbitals in regions that have the highest probability for finding a pair of electrons, providing a chemical bonding description according to the classical Lewis theory. The results confirm that conservation of the structures upon isoelectronic replacement of a B-H group by a Si atom, allowing evolution from B5H5(2-) to Si5(2-), is in total agreement with the preservation of the chemical bonding pattern.

  8. Improved Ant Colony Clustering Algorithm and Its Performance Study

    Science.gov (United States)

    Gao, Wei

    2016-01-01

    Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533

  9. Cluster analysis for applications

    CERN Document Server

    Anderberg, Michael R

    1973-01-01

    Cluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis.Comprised of 10 chapters, this book begins with an introduction to the subject o

  10. Clusters in nuclei

    CERN Document Server

    Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This third volume follows the successful Lect. Notes Phys. 818 (Vol. 1) and 848 (Vol. 2), and comprises six extensive lectures covering the following topics:  - Gamma Rays and Molecular Structure - Faddeev Equation Approach for Three Cluster Nuclear Reactions - Tomography of the Cluster Structure of Light Nuclei Via Relativistic Dissociation - Clustering Effects Within the Dinuclear Model : From Light to Hyper-heavy Molecules in Dynamical Mean-field Approach - Clusterization in Ternary Fission - Clusters in Light N...

  11. Spatial cluster modelling

    CERN Document Server

    Lawson, Andrew B

    2002-01-01

    Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal ...

  12. Clusters and how to make it work : Cluster Strategy Toolkit

    NARCIS (Netherlands)

    Manickam, Anu; van Berkel, Karel

    2014-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  13. Multiscale visual quality assessment for cluster analysis with self-organizing maps

    Science.gov (United States)

    Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

    2011-01-01

    Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

  14. Computational Aspects of Nuclear Coupled-Cluster Theory

    International Nuclear Information System (INIS)

    Dean, David Jarvis; Hagen, Gaute; Hjorth-Jensen, M.; Papenbrock, T.F.

    2008-01-01

    Coupled-cluster theory represents an important theoretical tool that we use to solve the quantum many-body problem. Coupled-cluster theory also lends itself to computation in a parallel computing environment. In this article, we present selected results from ab initio studies of stable and weakly bound nuclei utilizing computational techniques that we employ to solve coupled-cluster theory. We also outline several perspectives for future research directions in this area.

  15. Spectromicroscopy of self-assembled protein clusters

    Energy Technology Data Exchange (ETDEWEB)

    Schonschek, O.; Hormes, J.; Herzog, V. [Univ. of Bonn (Germany)

    1997-04-01

    The aim of this project is to use synchrotron radiation as a tool to study biomedical questions concerned with the thyroid glands. The biological background is outlined in a recent paper. In short, Thyroglobulin (TG), the precursor protein of the hormone thyroxine, forms large (20 - 500 microns in diameter) clusters in the extracellular lumen of thyrocytes. The process of the cluster formation is still not well understood but is thought to be a main storage mechanism of TG and therefore thyroxine inside the thyroid glands. For human thyroids, the interconnections of the proteins inside the clusters are mainly disulfide bondings. Normally, sulfur bridges are catalyzed by an enzyme called Protein Disulfide Bridge Isomerase (PDI). While this enzyme is supposed to be not present in any extracellular space, the cluster formation of TG takes place in the lumen between the thyrocytes. A possible explanation is the autocatalysis of TG.

  16. Comparing the performance of biomedical clustering methods

    DEFF Research Database (Denmark)

    Wiwie, Christian; Baumbach, Jan; Röttger, Richard

    2015-01-01

    expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future......Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene....... This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide...

  17. Agricultural Clusters in the Netherlands

    NARCIS (Netherlands)

    Schouten, M.A.; Heijman, W.J.M.

    2012-01-01

    Michael Porter was the first to use the term cluster in an economic context. He introduced the term in The Competitive Advantage of Nations (1990). The term cluster is also known as business cluster, industry cluster, competitive cluster or Porterian cluster. This article aims at determining and

  18. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

  19. 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.

  20. Simulation tools

    CERN Document Server

    Jenni, F

    2006-01-01

    In the last two decades, simulation tools made a significant contribution to the great progress in development of power electronics. Time to market was shortened and development costs were reduced drastically. Falling costs, as well as improved speed and precision, opened new fields of application. Today, continuous and switched circuits can be mixed. A comfortable number of powerful simulation tools is available. The users have to choose the best suitable for their application. Here a simple rule applies: The best available simulation tool is the tool the user is already used to (provided, it can solve the task). Abilities, speed, user friendliness and other features are continuously being improved—even though they are already powerful and comfortable. This paper aims at giving the reader an insight into the simulation of power electronics. Starting with a short description of the fundamentals of a simulation tool as well as properties of tools, several tools are presented. Starting with simplified models ...

  1. Electron: Cluster interactions

    International Nuclear Information System (INIS)

    Scheidemann, A.A.; Knight, W.D.

    1994-02-01

    Beam depletion spectroscopy has been used to measure absolute total inelastic electron-sodium cluster collision cross sections in the energy range from E ∼ 0.1 to E ∼ 6 eV. The investigation focused on the closed shell clusters Na 8 , Na 20 , Na 40 . The measured cross sections show an increase for the lowest collision energies where electron attachment is the primary scattering channel. The electron attachment cross section can be understood in terms of Langevin scattering, connecting this measurement with the polarizability of the cluster. For energies above the dissociation energy the measured electron-cluster cross section is energy independent, thus defining an electron-cluster interaction range. This interaction range increases with the cluster size

  2. Clustering high dimensional data

    DEFF Research Database (Denmark)

    Assent, Ira

    2012-01-01

    High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...

  3. Comprehensive studies of hydrogeochemical processes and quality status of groundwater with tools of cluster, grouping analysis, and fuzzy set method using GIS platform: a case study of Dalcheon in Ulsan City, Korea.

    Science.gov (United States)

    Venkatramanan, S; Chung, S Y; Rajesh, R; Lee, S Y; Ramkumar, T; Prasanna, M V

    2015-08-01

    This research aimed at developing comprehensive assessments of physicochemical quality of groundwater for drinking and irrigation purposes at Dalcheon in Ulsan City, Korea. The mean concentration of major ions represented as follows: Ca (94.3 mg/L) > Mg (41.7 mg/L) > Na (19.2 mg/L) > K (3.2 mg/L) for cations and SO4 (351 mg/L) > HCO3 (169 mg/L) > Cl (19 mg/L) for anions. Thematic maps for physicochemical parameters of groundwater were prepared, classified, weighted, and integrated in GIS method with fuzzy logic. The maps exhibited that suitable zone of drinking and irrigation purpose occupied in SE, NE, and NW sectors. The undesirable zone of drinking purpose was observed in SW and central parts and that of irrigation was in the western part of the study area. This was influenced by improperly treated effluents from an abandoned iron ore mine, irrigation, and domestic fields. By grouping analysis, groundwater types were classified into Ca(HCO3)2, (Ca,Mg)Cl2, and CaCl2, and CaHCO3 was the most predominant type. Grouping analysis also showed three types of irrigation water such as C1S1, C1S2, and C1S3. C1S3 type of high salinity to low sodium hazard was the most dominant in the study area. Equilibrium processes elucidated the groundwater samples were in the saturated to undersaturated condition with respect to aragonite, calcite, dolomite, and gypsum due to precipitation and deposition processes. Cluster analysis suggested that high contents of SO4 and HCO3 with low Cl was related with water-rock interactions and along with mining impact. This study showed that the effluents discharged from mining waste was the main sources of groundwater quality deterioration.

  4. Substructure in clusters of galaxies

    International Nuclear Information System (INIS)

    Fitchett, M.J.

    1988-01-01

    Optical observations suggesting the existence of substructure in clusters of galaxies are examined. Models of cluster formation and methods used to detect substructure in clusters are reviewed. Consideration is given to classification schemes based on a departure of bright cluster galaxies from a spherically symmetric distribution, evidence for statistically significant substructure, and various types of substructure, including velocity, spatial, and spatial-velocity substructure. The substructure observed in the galaxy distribution in clusters is discussed, focusing on observations from general cluster samples, the Virgo cluster, the Hydra cluster, Centaurus, the Coma cluster, and the Cancer cluster. 88 refs

  5. Nuclear cluster states

    International Nuclear Information System (INIS)

    Rae, W.D.M.; Merchant, A.C.

    1993-01-01

    We review clustering in light nuclei including molecular resonances in heavy ion reactions. In particular we study the systematics, paying special attention to the relationships between cluster states and superdeformed configurations. We emphasise the selection rules which govern the formation and decay of cluster states. We review some recent experimental results from Daresbury and elsewhere. In particular we report on the evidence for a 7-α chain state in 28 Si in experiments recently performed at the NSF, Daresbury. Finally we begin to address theoretically the important question of the lifetimes of cluster states as deduced from the experimental energy widths of the resonances. (Author)

  6. 15th Cluster workshop

    CERN Document Server

    Laakso, Harri; Escoubet, C. Philippe; The Cluster Active Archive : Studying the Earth’s Space Plasma Environment

    2010-01-01

    Since the year 2000 the ESA Cluster mission has been investigating the small-scale structures and processes of the Earth's plasma environment, such as those involved in the interaction between the solar wind and the magnetospheric plasma, in global magnetotail dynamics, in cross-tail currents, and in the formation and dynamics of the neutral line and of plasmoids. This book contains presentations made at the 15th Cluster workshop held in March 2008. It also presents several articles about the Cluster Active Archive and its datasets, a few overview papers on the Cluster mission, and articles reporting on scientific findings on the solar wind, the magnetosheath, the magnetopause and the magnetotail.

  7. Clusters in simple fluids

    International Nuclear Information System (INIS)

    Sator, N.

    2003-01-01

    This article concerns the correspondence between thermodynamics and the morphology of simple fluids in terms of clusters. Definitions of clusters providing a geometric interpretation of the liquid-gas phase transition are reviewed with an eye to establishing their physical relevance. The author emphasizes their main features and basic hypotheses, and shows how these definitions lead to a recent approach based on self-bound clusters. Although theoretical, this tutorial review is also addressed to readers interested in experimental aspects of clustering in simple fluids

  8. 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

  9. Lifting to cluster-tilting objects in higher cluster categories

    OpenAIRE

    Liu, Pin

    2008-01-01

    In this note, we consider the $d$-cluster-tilted algebras, the endomorphism algebras of $d$-cluster-tilting objects in $d$-cluster categories. We show that a tilting module over such an algebra lifts to a $d$-cluster-tilting object in this $d$-cluster category.

  10. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...

  11. Soft landing of size selected clusters in rare gas matrices

    International Nuclear Information System (INIS)

    Lau, J.T; Wurth, W.; Ehrke, H-U.; Achleitner, A.

    2003-01-01

    Soft landing of mass selected clusters in rare gas matrices is a technique used to preserve mass selection in cluster deposition. To prevent fragmentation upon deposition, the substrate is covered with rare gas matrices to dissipate the cluster kinetic energy upon impact. Theoretical and experimental studies demonstrate the power of this technique. Besides STM, optical absorption, excitation, and fluorescence experiments, x-ray absorption at core levels can be used as a tool to study soft landing conditions, as will be shown here. X-ray absorption spectroscopy is also well suited to follow diffusion and agglomeration of clusters on surfaces via energy shifts in core level absorption

  12. Neurostimulation in cluster headache

    DEFF Research Database (Denmark)

    Pedersen, Jeppe L; Barloese, Mads; Jensen, Rigmor H

    2013-01-01

    PURPOSE OF REVIEW: Neurostimulation has emerged as a viable treatment for intractable chronic cluster headache. Several therapeutic strategies are being investigated including stimulation of the hypothalamus, occipital nerves and sphenopalatine ganglion. The aim of this review is to provide...... effective strategy must be preferred as first-line therapy for intractable chronic cluster headache....

  13. Cauchy cluster process

    DEFF Research Database (Denmark)

    Ghorbani, Mohammad

    2013-01-01

    In this paper we introduce an instance of the well-know Neyman–Scott cluster process model with clusters having a long tail behaviour. In our model the offspring points are distributed around the parent points according to a circular Cauchy distribution. Using a modified Cramér-von Misses test...

  14. When Clusters become Networks

    NARCIS (Netherlands)

    S.M.W. Phlippen (Sandra); G.A. van der Knaap (Bert)

    2007-01-01

    textabstractPolicy makers spend large amounts of public resources on the foundation of science parks and other forms of geographically clustered business activities, in order to stimulate regional innovation. Underlying the relation between clusters and innovation is the assumption that co-located

  15. Mixed-Initiative Clustering

    Science.gov (United States)

    Huang, Yifen

    2010-01-01

    Mixed-initiative clustering is a task where a user and a machine work collaboratively to analyze a large set of documents. We hypothesize that a user and a machine can both learn better clustering models through enriched communication and interactive learning from each other. The first contribution or this thesis is providing a framework of…

  16. Coma cluster of galaxies

    Science.gov (United States)

    1999-01-01

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

  17. 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

  18. Alpha clustering in nuclei

    International Nuclear Information System (INIS)

    Hodgson, P.E.

    1990-01-01

    The effects of nucleon clustering in nuclei are described, with reference to both nuclear structure and nuclear reactions, and the advantages of using the cluster formalism to describe a range of phenomena are discussed. It is shown that bound and scattering alpha-particle states can be described in a unified way using an energy-dependent alpha-nucleus potential. (author)

  19. Mining the National Career Assessment Examination Result Using Clustering Algorithm

    Science.gov (United States)

    Pagudpud, M. V.; Palaoag, T. T.; Padirayon, L. M.

    2018-03-01

    Education is an essential process today which elicits authorities to discover and establish innovative strategies for educational improvement. This study applied data mining using clustering technique for knowledge extraction from the National Career Assessment Examination (NCAE) result in the Division of Quirino. The NCAE is an examination given to all grade 9 students in the Philippines to assess their aptitudes in the different domains. Clustering the students is helpful in identifying students’ learning considerations. With the use of the RapidMiner tool, clustering algorithms such as Density-Based Spatial Clustering of Applications with Noise (DBSCAN), k-means, k-medoid, expectation maximization clustering, and support vector clustering algorithms were analyzed. The silhouette indexes of the said clustering algorithms were compared, and the result showed that the k-means algorithm with k = 3 and silhouette index equal to 0.196 is the most appropriate clustering algorithm to group the students. Three groups were formed having 477 students in the determined group (cluster 0), 310 proficient students (cluster 1) and 396 developing students (cluster 2). The data mining technique used in this study is essential in extracting useful information from the NCAE result to better understand the abilities of students which in turn is a good basis for adopting teaching strategies.

  20. 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

  1. Negotiating Cluster Boundaries

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    2017-01-01

    Palm oil was introduced to Malay(si)a as an alternative to natural rubber, inheriting its cluster organizational structure. In the late 1960s, Malaysia became the world’s largest palm oil exporter. Based on archival material from British colonial institutions and agency houses, this paper focuses...... on the governance dynamics that drove institutional change within this cluster during decolonization. The analysis presents three main findings: (i) cluster boundaries are defined by continuous tug-of-war style negotiations between public and private actors; (ii) this interaction produces institutional change...... within the cluster, in the form of cumulative ‘institutional rounds’ – the correction or disruption of existing institutions or the creation of new ones; and (iii) this process leads to a broader inclusion of local actors in the original cluster configuration. The paper challenges the prevalent argument...

  2. Mathematical classification and clustering

    CERN Document Server

    Mirkin, Boris

    1996-01-01

    I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina­ torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de­ velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par­ titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in­ novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in ...

  3. 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.

  4. Herd Clustering: A synergistic data clustering approach using collective intelligence

    KAUST Repository

    Wong, Kachun; Peng, Chengbin; Li, Yue; Chan, Takming

    2014-01-01

    , this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances

  5. Formation of global energy minimim structures in the growth process of Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Koshelev, Andrey; Shutovich, Andrey

    2003-01-01

    that in this way all known global minimum structures of the Lennard-Jones (LJ) 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 numbers sequence for the clusters of noble gases atoms and compare...

  6. Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

    2009-12-22

    Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

  7. Cluster-cluster correlations and constraints on the correlation hierarchy

    Science.gov (United States)

    Hamilton, A. J. S.; Gott, J. R., III

    1988-01-01

    The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.

  8. Formation of stable products from cluster-cluster collisions

    International Nuclear Information System (INIS)

    Alamanova, Denitsa; Grigoryan, Valeri G; Springborg, Michael

    2007-01-01

    The formation of stable products from copper cluster-cluster collisions is investigated by using classical molecular-dynamics simulations in combination with an embedded-atom potential. The dependence of the product clusters on impact energy, relative orientation of the clusters, and size of the clusters is studied. The structures and total energies of the product clusters are analysed and compared with those of the colliding clusters before impact. These results, together with the internal temperature, are used in obtaining an increased understanding of cluster fusion processes

  9. Integrated spectral study of small angular diameter galactic open clusters

    Science.gov (United States)

    Clariá, J. J.; Ahumada, A. V.; Bica, E.; Pavani, D. B.; Parisi, M. C.

    2017-10-01

    This paper presents flux-calibrated integrated spectra obtained at Complejo Astronómico El Leoncito (CASLEO, Argentina) for a sample of 9 Galactic open clusters of small angular diameter. The spectra cover the optical range (3800-6800 Å), with a resolution of ˜14 Å. With one exception (Ruprecht 158), the selected clusters are projected into the fourth Galactic quadrant (282o evaluate their membership status. The current cluster sample complements that of 46 open clusters previously studied by our group in an effort to gather a spectral library with several clusters per age bin. The cluster spectral library that we have been building is an important tool to tie studies of resolved and unresolved stellar content.

  10. Tune Your Brown Clustering, Please

    DEFF Research Database (Denmark)

    Derczynski, Leon; Chester, Sean; Bøgh, Kenneth Sejdenfaden

    2015-01-01

    Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly...

  11. Cluster Management Institutionalization

    DEFF Research Database (Denmark)

    Normann, Leo; Agger Nielsen, Jeppe

    2015-01-01

    of how it was legitimized as a “ready-to-use” management model. Further, our account reveals how cluster management translated into considerably different local variants as it travelled into specific organizations. However, these processes have not occurred sequentially with cluster management first...... legitimized at the field level, then spread, and finally translated into action in the adopting organizations. Instead, we observed entangled field and organizational-level processes. Accordingly, we argue that cluster management institutionalization is most readily understood by simultaneously investigating...

  12. The concept of cluster

    DEFF Research Database (Denmark)

    Laursen, Lea Louise Holst; Møller, Jørgen

    2013-01-01

    villages in order to secure their future. This paper will address the concept of cluster-villages as a possible approach to strengthen the conditions of contemporary Danish villages. Cluster-villages is a concept that gather a number of villages in a network-structure where the villages both work together...... to forskellige positioner ser vi en ny mulighed for landsbyudvikling, som vi kalder Clustervillages. In order to investigate the potentials and possibilities of the cluster-village concept the paper will seek to unfold the concept strategically; looking into the benefits of such concept. Further, the paper seeks...

  13. Raspberry Pi super cluster

    CERN Document Server

    Dennis, Andrew K

    2013-01-01

    This book follows a step-by-step, tutorial-based approach which will teach you how to develop your own super cluster using Raspberry Pi computers quickly and efficiently.Raspberry Pi Super Cluster is an introductory guide for those interested in experimenting with parallel computing at home. Aimed at Raspberry Pi enthusiasts, this book is a primer for getting your first cluster up and running.Basic knowledge of C or Java would be helpful but no prior knowledge of parallel computing is necessary.

  14. 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

  15. Contextualizing the Cluster

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    This dissertation examines the case of the palm oil cluster in Malaysia and Indonesia, today one of the largest agricultural clusters in the world. My analysis focuses on the evolution of the cluster from the 1880s to the 1970s in order to understand how it helped these two countries to integrate...... into the global economy in both colonial and post-colonial times. The study is based on empirical material drawn from five UK archives and background research using secondary sources, interviews, and archive visits to Malaysia and Singapore. The dissertation comprises three articles, each discussing a major under...

  16. Atomic cluster collisions

    Science.gov (United States)

    Korol, Andrey V.; Solov'yov, Andrey

    2013-01-01

    Atomic cluster collisions are a field of rapidly emerging research interest by both experimentalists and theorists. The international symposium on atomic cluster collisions (ISSAC) is the premier forum to present cutting-edge research in this field. It was established in 2003 and the most recent conference was held in Berlin, Germany in July of 2011. This Topical Issue presents original research results from some of the participants, who attended this conference. This issues specifically focuses on two research areas, namely Clusters and Fullerenes in External Fields and Nanoscale Insights in Radiation Biodamage.

  17. Combining cluster number counts and galaxy clustering

    Energy Technology Data Exchange (ETDEWEB)

    Lacasa, Fabien; Rosenfeld, Rogerio, E-mail: fabien@ift.unesp.br, E-mail: rosenfel@ift.unesp.br [ICTP South American Institute for Fundamental Research, Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo (Brazil)

    2016-08-01

    The abundance of clusters and the clustering of galaxies are two of the important cosmological probes for current and future large scale surveys of galaxies, such as the Dark Energy Survey. In order to combine them one has to account for the fact that they are not independent quantities, since they probe the same density field. It is important to develop a good understanding of their correlation in order to extract parameter constraints. We present a detailed modelling of the joint covariance matrix between cluster number counts and the galaxy angular power spectrum. We employ the framework of the halo model complemented by a Halo Occupation Distribution model (HOD). We demonstrate the importance of accounting for non-Gaussianity to produce accurate covariance predictions. Indeed, we show that the non-Gaussian covariance becomes dominant at small scales, low redshifts or high cluster masses. We discuss in particular the case of the super-sample covariance (SSC), including the effects of galaxy shot-noise, halo second order bias and non-local bias. We demonstrate that the SSC obeys mathematical inequalities and positivity. Using the joint covariance matrix and a Fisher matrix methodology, we examine the prospects of combining these two probes to constrain cosmological and HOD parameters. We find that the combination indeed results in noticeably better constraints, with improvements of order 20% on cosmological parameters compared to the best single probe, and even greater improvement on HOD parameters, with reduction of error bars by a factor 1.4-4.8. This happens in particular because the cross-covariance introduces a synergy between the probes on small scales. We conclude that accounting for non-Gaussian effects is required for the joint analysis of these observables in galaxy surveys.

  18. Homological methods, representation theory, and cluster algebras

    CERN Document Server

    Trepode, Sonia

    2018-01-01

    This text presents six mini-courses, all devoted to interactions between representation theory of algebras, homological algebra, and the new ever-expanding theory of cluster algebras. The interplay between the topics discussed in this text will continue to grow and this collection of courses stands as a partial testimony to this new development. The courses are useful for any mathematician who would like to learn more about this rapidly developing field; the primary aim is to engage graduate students and young researchers. Prerequisites include knowledge of some noncommutative algebra or homological algebra. Homological algebra has always been considered as one of the main tools in the study of finite-dimensional algebras. The strong relationship with cluster algebras is more recent and has quickly established itself as one of the important highlights of today’s mathematical landscape. This connection has been fruitful to both areas—representation theory provides a categorification of cluster algebras, wh...

  19. Topics in modelling of clustered data

    CERN Document Server

    Aerts, Marc; Ryan, Louise M; Geys, Helena

    2002-01-01

    Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and social science studies. It focuses on providing a comprehensive treatment of marginal, conditional, and random effects models using, among others, likelihood, pseudo-likelihood, and generalized estimating equations methods. The authors motivate and illustrate all aspects of these models in a variety of real applications. They discuss several variations and extensions, including individual-level covariates and combined continuous and discrete outcomes. Flexible modelling with fractional and local polynomials, omnibus lack-of-fit tests, robustification against misspecification, exact, and bootstrap inferential procedures all receive extensive treatment. The application...

  20. Metal cluster compounds - chemistry and importance; clusters containing isolated main group element atoms, large metal cluster compounds, cluster fluxionality

    International Nuclear Information System (INIS)

    Walther, B.

    1988-01-01

    This part of the review on metal cluster compounds deals with clusters containing isolated main group element atoms, with high nuclearity clusters and metal cluster fluxionality. It will be obvious that main group element atoms strongly influence the geometry, stability and reactivity of the clusters. High nuclearity clusters are of interest in there own due to the diversity of the structures adopted, but their intermediate position between molecules and the metallic state makes them a fascinating research object too. These both sites of the metal cluster chemistry as well as the frequently observed ligand and core fluxionality are related to the cluster metal and surface analogy. (author)

  1. ANALISIS SEGMENTASI PELANGGAN MENGGUNAKAN KOMBINASI RFM MODEL DAN TEKNIK CLUSTERING

    Directory of Open Access Journals (Sweden)

    Beta Estri Adiana

    2018-04-01

    Full Text Available Intense competition in the business field motivates a small and medium enterprises (SMEs to manage customer services to the maximal. Improve of customer royalty by grouping cunstomers into some of groups and determining appropriate and effective marketing strategies for each group. Customer segmentation can be performed by data mining approach with clustering method. The main purpose of this paper is customer segmentation and measure their loyalty to a SME’s product. Using CRISP-DM method which consist of six phases, namely business understanding, data understanding, data preparatuin, modeling, evaluation and deployment. The K-Means algorithm is used for cluster formation and RapidMiner as a tool used to evaluate the result of clusters. Cluster formation is based on RFM (recency, frequency, monetary analysis. Davies Bouldin Index (DBI is used to find the optimal number of clusters (k. The customers are divided into 3 clusters, total of customer in first cluster is 30 customers who entered in typical customer category, the second cluster there are 8 customer whho entered in superstar customer and 89 customers in third cluster is dormant cluster category.

  2. Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

    Science.gov (United States)

    Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

    2017-01-01

    Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

  3. Disentangling Porterian Clusters

    DEFF Research Database (Denmark)

    Jagtfelt, Tue

    , contested theory become so widely disseminated and applied as a normative and prescriptive strategy for economic development? The dissertation traces the introduction of the cluster notion into the EU’s Lisbon Strategy and demonstrates how its inclusion originates from Porter’s colleagues: Professor Örjan...... to his membership on the Commission on Industrial Competitiveness, and that the cluster notion found in his influential book, Nations, represents a significant shift in his conception of cluster compared with his early conceptions. This shift, it is argued, is a deliberate attempt by Porter to create...... a paradigmatic textbook that follows Kuhn’s blueprint for scientific revolutions by instilling Nations with circular references and thus creating a local linguistic holism conceptualized through an encompassing notion of cluster. The dissertation concludes that the two research questions are philosophically...

  4. 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)

  5. From collisions to clusters

    DEFF Research Database (Denmark)

    Loukonen, Ville; Bork, Nicolai; Vehkamaki, Hanna

    2014-01-01

    -principles molecular dynamics collision simulations of (sulphuric acid)1(water)0, 1 + (dimethylamine) → (sulphuric acid)1(dimethylamine)1(water)0, 1 cluster formation processes. The simulations indicate that the sticking factor in the collisions is unity: the interaction between the molecules is strong enough...... control. As a consequence, the clusters show very dynamic ion pair structure, which differs from both the static structure optimisation calculations and the equilibrium first-principles molecular dynamics simulations. In some of the simulation runs, water mediates the proton transfer by acting as a proton...... to overcome the possible initial non-optimal collision orientations. No post-collisional cluster break up is observed. The reasons for the efficient clustering are (i) the proton transfer reaction which takes place in each of the collision simulations and (ii) the subsequent competition over the proton...

  6. Clustering of Emerging Flux

    Science.gov (United States)

    Ruzmaikin, A.

    1997-01-01

    Observations show that newly emerging flux tends to appear on the Solar surface at sites where there is flux already. This results in clustering of solar activity. Standard dynamo theories do not predict this effect.

  7. How Clusters Work

    Science.gov (United States)

    Technology innovation clusters are geographic concentrations of interconnected companies, universities, and other organizations with a focus on environmental technology. They play a key role in addressing the nation’s pressing environmental problems.

  8. Evolution of clustered storage

    CERN Multimedia

    CERN. Geneva; Van de Vyvre, Pierre

    2007-01-01

    The session actually featured two presentations: * Evolution of clustered storage by Lance Hukill, Quantum Corporation * ALICE DAQ - Usage of a Cluster-File System: Quantum StorNext by Pierre Vande Vyvre, CERN-PH the second one prepared at short notice by Pierre (thanks!) to present how the Quantum technologies are being used in the ALICE experiment. The abstract to Mr Hukill's follows. Clustered Storage is a technology that is driven by business and mission applications. The evolution of Clustered Storage solutions starts first at the alignment between End-users needs and Industry trends: * Push-and-Pull between managing for today versus planning for tomorrow * Breaking down the real business problems to the core applications * Commoditization of clients, servers, and target devices * Interchangeability, Interoperability, Remote Access, Centralized control * Oh, and yes, there is a budget and the "real world" to deal with This presentation will talk through these needs and trends, and then ask the question, ...

  9. Galaxy clusters and cosmology

    CERN Document Server

    White, S

    1994-01-01

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

  10. Applications of Clustering

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Applications of Clustering. Biology – medical imaging, bioinformatics, ecology, phylogenies problems etc. Market research. Data Mining. Social Networks. Any problem measuring similarity/correlation. (dimensions represent different parameters)

  11. Clustering Game Behavior Data

    DEFF Research Database (Denmark)

    Bauckhage, C.; Drachen, Anders; Sifa, Rafet

    2015-01-01

    of the causes, the proliferation of behavioral data poses the problem of how to derive insights therefrom. Behavioral data sets can be large, time-dependent and high-dimensional. Clustering offers a way to explore such data and to discover patterns that can reduce the overall complexity of the data. Clustering...... and other techniques for player profiling and play style analysis have, therefore, become popular in the nascent field of game analytics. However, the proper use of clustering techniques requires expertise and an understanding of games is essential to evaluate results. With this paper, we address game data...... scientists and present a review and tutorial focusing on the application of clustering techniques to mine behavioral game data. Several algorithms are reviewed and examples of their application shown. Key topics such as feature normalization are discussed and open problems in the context of game analytics...

  12. Clustering on Membranes

    DEFF Research Database (Denmark)

    Johannes, Ludger; Pezeshkian, Weria; Ipsen, John H

    2018-01-01

    Clustering of extracellular ligands and proteins on the plasma membrane is required to perform specific cellular functions, such as signaling and endocytosis. Attractive forces that originate in perturbations of the membrane's physical properties contribute to this clustering, in addition to direct...... protein-protein interactions. However, these membrane-mediated forces have not all been equally considered, despite their importance. In this review, we describe how line tension, lipid depletion, and membrane curvature contribute to membrane-mediated clustering. Additional attractive forces that arise...... from protein-induced perturbation of a membrane's fluctuations are also described. This review aims to provide a survey of the current understanding of membrane-mediated clustering and how this supports precise biological functions....

  13. Air void clustering.

    Science.gov (United States)

    2015-06-01

    Air void clustering around coarse aggregate in concrete has been identified as a potential source of : low strengths in concrete mixes by several Departments of Transportation around the country. Research was : carried out to (1) develop a quantitati...

  14. tclust: An R Package for a Trimming Approach to Cluster Analysis

    Directory of Open Access Journals (Sweden)

    2012-04-01

    Full Text Available Outlying data can heavily influence standard clustering methods. At the same time, clustering principles can be useful when robustifying statistical procedures. These two reasons motivate the development of feasible robust model-based clustering approaches. With this in mind, an R package for performing non-hierarchical robust clustering, called tclust, is presented here. Instead of trying to “fit” noisy data, a proportion α of the most outlying observations is trimmed. The tclust package efficiently handles different cluster scatter constraints. Graphical exploratory tools are also provided to help the user make sensible choices for the trimming proportion as well as the number of clusters to search for.

  15. Speaker segmentation and clustering

    OpenAIRE

    Kotti, M; Moschou, V; Kotropoulos, C

    2008-01-01

    07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced. This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker...

  16. 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

  17. BUILDING e-CLUSTERS

    OpenAIRE

    Milan Davidovic

    2013-01-01

    E-clusters are strategic alliance in TIMES technology sector (Telecommunication, Information technology, Multimedia, Entertainment, Security) where products and processes are digitalized. They enable horizontal and vertical integration of small and medium companies and establish new added value e-chains. E-clusters also build supply chains based on cooperation relationship, innovation, organizational knowledge and compliance of intellectual properties. As an innovative approach for economic p...

  18. Clusters and exotic processes

    International Nuclear Information System (INIS)

    Schiffer, J.P.

    1975-01-01

    An attempt is made to present some data which may be construed as indicating that perhaps clusters play a role in high energy and exotic pion or kaon interactions with complex (A much greater than 16) nuclei. Also an attempt is made to summarize some very recent experimental work on pion interactions with nuclei which may or may not in the end support a picture in which clusters play an important role. (U.S.)

  19. Robust continuous clustering.

    Science.gov (United States)

    Shah, Sohil Atul; Koltun, Vladlen

    2017-09-12

    Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.

  20. Cluster bomb ocular injuries.

    Science.gov (United States)

    Mansour, Ahmad M; Hamade, Haya; Ghaddar, Ayman; Mokadem, Ahmad Samih; El Hajj Ali, Mohamad; Awwad, Shady

    2012-01-01

    To present the visual outcomes and ocular sequelae of victims of cluster bombs. This retrospective, multicenter case series of ocular injury due to cluster bombs was conducted for 3 years after the war in South Lebanon (July 2006). Data were gathered from the reports to the Information Management System for Mine Action. There were 308 victims of clusters bombs; 36 individuals were killed, of which 2 received ocular lacerations and; 272 individuals were injured with 18 receiving ocular injury. These 18 surviving individuals were assessed by the authors. Ocular injury occurred in 6.5% (20/308) of cluster bomb victims. Trauma to multiple organs occurred in 12 of 18 cases (67%) with ocular injury. Ocular findings included corneal or scleral lacerations (16 eyes), corneal foreign bodies (9 eyes), corneal decompensation (2 eyes), ruptured cataract (6 eyes), and intravitreal foreign bodies (10 eyes). The corneas of one patient had extreme attenuation of the endothelium. Ocular injury occurred in 6.5% of cluster bomb victims and 67% of the patients with ocular injury sustained trauma to multiple organs. Visual morbidity in civilians is an additional reason for a global ban on the use of cluster bombs.

  1. Determination of atomic cluster structure with cluster fusion algorithm

    DEFF Research Database (Denmark)

    Obolensky, Oleg I.; Solov'yov, Ilia; Solov'yov, Andrey V.

    2005-01-01

    We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters.......We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters....

  2. Authoring Tools

    Science.gov (United States)

    Treviranus, Jutta

    Authoring tools that are accessible and that enable authors to produce accessible Web content play a critical role in web accessibility. Widespread use of authoring tools that comply to the W3C Authoring Tool Accessibility Guidelines (ATAG) would ensure that even authors who are neither knowledgeable about nor particularly motivated to produce accessible content do so by default. The principles and techniques of ATAG are discussed. Some examples of accessible authoring tools are described including authoring tool content management components such as TinyMCE. Considerations for creating an accessible collaborative environment are also covered. As part of providing accessible content, the debate between system-based personal optimization and one universally accessible site configuration is presented. The issues and potential solutions to address the accessibility crisis presented by the advent of rich internet applications are outlined. This challenge must be met to ensure that a large segment of the population is able to participate in the move toward the web as a two-way communication mechanism.

  3. 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.

  4. Cluster dynamics at different cluster size and incident laser wavelengths

    International Nuclear Information System (INIS)

    Desai, Tara; Bernardinello, Andrea

    2002-01-01

    X-ray emission spectra from aluminum clusters of diameter -0.4 μm and gold clusters of dia. ∼1.25 μm are experimentally studied by irradiating the cluster foil targets with 1.06 μm laser, 10 ns (FWHM) at an intensity ∼10 12 W/cm 2 . Aluminum clusters show a different spectra compared to bulk material whereas gold cluster evolve towards bulk gold. Experimental data are analyzed on the basis of cluster dimension, laser wavelength and pulse duration. PIC simulations are performed to study the behavior of clusters at higher intensity I≥10 17 W/cm 2 for different size of the clusters irradiated at different laser wavelengths. Results indicate the dependence of cluster dynamics on cluster size and incident laser wavelength

  5. Tool steels

    DEFF Research Database (Denmark)

    Højerslev, C.

    2001-01-01

    On designing a tool steel, its composition and heat treatment parameters are chosen to provide a hardened and tempered martensitic matrix in which carbides are evenly distributed. In this condition the matrix has an optimum combination of hardness andtoughness, the primary carbides provide...... resistance against abrasive wear and secondary carbides (if any) increase the resistance against plastic deformation. Tool steels are alloyed with carbide forming elements (Typically: vanadium, tungsten, molybdenumand chromium) furthermore some steel types contains cobalt. Addition of alloying elements...... serves primarily two purpose (i) to improve the hardenabillity and (ii) to provide harder and thermally more stable carbides than cementite. Assuming proper heattreatment, the properties of a tool steel depends on the which alloying elements are added and their respective concentrations....

  6. 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....

  7. Management Tools

    Science.gov (United States)

    1987-01-01

    Manugistics, Inc. (formerly AVYX, Inc.) has introduced a new programming language for IBM and IBM compatible computers called TREES-pls. It is a resource management tool originating from the space shuttle, that can be used in such applications as scheduling, resource allocation project control, information management, and artificial intelligence. Manugistics, Inc. was looking for a flexible tool that can be applied to many problems with minimal adaptation. Among the non-government markets are aerospace, other manufacturing, transportation, health care, food and beverage and professional services.

  8. Cluster Implantation and Deposition Apparatus

    DEFF Research Database (Denmark)

    Hanif, Muhammad; Popok, Vladimir

    2015-01-01

    In the current report, a design and capabilities of a cluster implantation and deposition apparatus (CIDA) involving two different cluster sources are described. The clusters produced from gas precursors (Ar, N etc.) by PuCluS-2 can be used to study cluster ion implantation in order to develop...

  9. Subspace K-means clustering

    NARCIS (Netherlands)

    Timmerman, Marieke E.; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

    2013-01-01

    To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the

  10. 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.

  11. 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...

  12. Design tools

    Science.gov (United States)

    Anton TenWolde; Mark T. Bomberg

    2009-01-01

    Overall, despite the lack of exact input data, the use of design tools, including models, is much superior to the simple following of rules of thumbs, and a moisture analysis should be standard procedure for any building envelope design. Exceptions can only be made for buildings in the same climate, similar occupancy, and similar envelope construction. This chapter...

  13. The structure of nearby clusters of galaxies Hierarchical clustering and an application to the Leo region

    CERN Document Server

    Materne, J

    1978-01-01

    A new method of classifying groups of galaxies, called hierarchical clustering, is presented as a tool for the investigation of nearby groups of galaxies. The method is free from model assumptions about the groups. The scaling of the different coordinates is necessary, and the level from which one accepts the groups as real has to be determined. Hierarchical clustering is applied to an unbiased sample of galaxies in the Leo region. Five distinct groups result which have reasonable physical properties, such as low crossing times and conservative mass-to-light ratios, and which follow a radial velocity- luminosity relation. Only 4 out of 39 galaxies were adopted as field galaxies. (27 refs).

  14. Spanning Tree Based Attribute Clustering

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Jorge, Cordero Hernandez

    2009-01-01

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

  15. Allergen Sensitization Pattern by Sex: A Cluster Analysis in Korea.

    Science.gov (United States)

    Ohn, Jungyoon; Paik, Seung Hwan; Doh, Eun Jin; Park, Hyun-Sun; Yoon, Hyun-Sun; Cho, Soyun

    2017-12-01

    Allergens tend to sensitize simultaneously. Etiology of this phenomenon has been suggested to be allergen cross-reactivity or concurrent exposure. However, little is known about specific allergen sensitization patterns. To investigate the allergen sensitization characteristics according to gender. Multiple allergen simultaneous test (MAST) is widely used as a screening tool for detecting allergen sensitization in dermatologic clinics. We retrospectively reviewed the medical records of patients with MAST results between 2008 and 2014 in our Department of Dermatology. A cluster analysis was performed to elucidate the allergen-specific immunoglobulin (Ig)E cluster pattern. The results of MAST (39 allergen-specific IgEs) from 4,360 cases were analyzed. By cluster analysis, 39items were grouped into 8 clusters. Each cluster had characteristic features. When compared with female, the male group tended to be sensitized more frequently to all tested allergens, except for fungus allergens cluster. The cluster and comparative analysis results demonstrate that the allergen sensitization is clustered, manifesting allergen similarity or co-exposure. Only the fungus cluster allergens tend to sensitize female group more frequently than male group.

  16. Exotic cluster structures on

    CERN Document Server

    Gekhtman, M; Vainshtein, A

    2017-01-01

    This is the second paper in the series of papers dedicated to the study of natural cluster structures in the rings of regular functions on simple complex Lie groups and Poisson-Lie structures compatible with these cluster structures. According to our main conjecture, each class in the Belavin-Drinfeld classification of Poisson-Lie structures on \\mathcal{G} corresponds to a cluster structure in \\mathcal{O}(\\mathcal{G}). The authors have shown before that this conjecture holds for any \\mathcal{G} in the case of the standard Poisson-Lie structure and for all Belavin-Drinfeld classes in SL_n, n<5. In this paper the authors establish it for the Cremmer-Gervais Poisson-Lie structure on SL_n, which is the least similar to the standard one.

  17. From superdeformation to clusters

    Energy Technology Data Exchange (ETDEWEB)

    Betts, R R [Argonne National Lab., IL (United States). Physics Div.

    1992-08-01

    Much of the discussion at the conference centred on superdeformed states and their study by precise gamma spectrometry. The author suggests that the study of superdeformation by fission fragments and by auto-scattering is of importance, and may become more important. He concludes that there exists clear evidence of shell effects at extreme deformation in light nuclei studied by fission or cluster decay. The connection between the deformed shell model and the multi-center shell model can be exploited to give give insight into the cluster structure of these extremely deformed states, and also gives hope of a spectroscopy based on selection rules for cluster decay. A clear disadvantage at this stage is inability to make this spectroscopy more quantitative through calculation of the decay widths. The introduction of a new generation of high segmentation, high resolution, particle arrays has and will have a major impact on this aspect of the study of highly deformed nuclei. 20 refs., 16 figs.

  18. Offshore Wind Farm Clusters - Towards new integrated Design Tool

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Réthoré, Pierre-Elouan; Peña, Alfredo

    In EERA DTOC testing of existing wind farm wake models against four validation data test sets from large offshore wind farms is carried out. This includes Horns Rev-1 in the North Sea, Lillgrund in the Baltic Sea, Roedsand-2 in the Baltic Sea and from 10 large offshore wind farms in Northern Euro...

  19. MARKETING COMMUNICATION TO INDUSTRIAL CLUSTERS OF SLOVAK REPUBLIC

    Directory of Open Access Journals (Sweden)

    Erika Loučanová

    2013-12-01

    Full Text Available Currently, the growing attention is paid to the promotion and development of clusters, i.e. concentration of businesses and other cooperating institutions in a sector and region. Despite of the economy globalization and sophisticated global communications technologies, the factor of geographical concentration should be declined, however the experts highlight the importance of direct contact with local and tacit knowledge. The aim of this paper is analyzing of marketing communication tools in different clusters of Slovakia.

  20. Synchronization as Aggregation: Cluster Kinetics of Pulse-Coupled Oscillators.

    Science.gov (United States)

    O'Keeffe, Kevin P; Krapivsky, P L; Strogatz, Steven H

    2015-08-07

    We consider models of identical pulse-coupled oscillators with global interactions. Previous work showed that under certain conditions such systems always end up in sync, but did not quantify how small clusters of synchronized oscillators progressively coalesce into larger ones. Using tools from the study of aggregation phenomena, we obtain exact results for the time-dependent distribution of cluster sizes as the system evolves from disorder to synchrony.

  1. The mass-temperature relation for clusters of galaxies

    DEFF Research Database (Denmark)

    Hjorth, J.; Oukbir, J.; van Kampen, E.

    1998-01-01

    A tight mass-temperature relation, M(r)/r proportional to T-x, is expected in most cosmological models if clusters of galaxies are homologous and the intracluster gas is in global equilibrium with the dark matter. We here calibrate this relation using eight clusters with well-defined global tempe...... redshift, the relation represents a new tool for determination of cosmological parameters, notably the cosmological constant Lambda....

  2. Refractory chronic cluster headache

    DEFF Research Database (Denmark)

    Mitsikostas, Dimos D; Edvinsson, Lars; Jensen, Rigmor H

    2014-01-01

    Chronic cluster headache (CCH) often resists to prophylactic pharmaceutical treatments resulting in patients' life damage. In this rare but pragmatic situation escalation to invasive management is needed but framing criteria are lacking. We aimed to reach a consensus for refractory CCH definition...... for clinical and research use. The preparation of the final consensus followed three stages. Internal between authors, a larger between all European Headache Federation members and finally an international one among all investigators that have published clinical studies on cluster headache the last five years...

  3. I Cluster geografici

    Directory of Open Access Journals (Sweden)

    Maurizio Rosina

    2010-03-01

    Full Text Available Geographic ClustersOver the past decade, public alphanumeric database have been growing at exceptional rate. Most of data can be georeferenced, so that is possible gaining new knowledge from such databases. The contribution of this paper is two-fold. We first present a model of geographic clusters, which uses only geographic and functionally data properties. The model is useful to process huge amount of public/government data, even daily upgrading. After that, we merge the model into the framework GEOPOI (GEOcoding Points Of Interest, and show some graphic map results.

  4. I Cluster geografici

    Directory of Open Access Journals (Sweden)

    Maurizio Rosina

    2010-03-01

    Full Text Available Geographic Clusters Over the past decade, public alphanumeric database have been growing at exceptional rate. Most of data can be georeferenced, so that is possible gaining new knowledge from such databases. The contribution of this paper is two-fold. We first present a model of geographic clusters, which uses only geographic and functionally data properties. The model is useful to process huge amount of public/government data, even daily upgrading. After that, we merge the model into the framework GEOPOI (GEOcoding Points Of Interest, and show some graphic map results.

  5. Clustering via Kernel Decomposition

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan

    2006-01-01

    Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....

  6. Android Malware Classification Using K-Means Clustering Algorithm

    Science.gov (United States)

    Hamid, Isredza Rahmi A.; Syafiqah Khalid, Nur; Azma Abdullah, Nurul; Rahman, Nurul Hidayah Ab; Chai Wen, Chuah

    2017-08-01

    Malware was designed to gain access or damage a computer system without user notice. Besides, attacker exploits malware to commit crime or fraud. This paper proposed Android malware classification approach based on K-Means clustering algorithm. We evaluate the proposed model in terms of accuracy using machine learning algorithms. Two datasets were selected to demonstrate the practicing of K-Means clustering algorithms that are Virus Total and Malgenome dataset. We classify the Android malware into three clusters which are ransomware, scareware and goodware. Nine features were considered for each types of dataset such as Lock Detected, Text Detected, Text Score, Encryption Detected, Threat, Porn, Law, Copyright and Moneypak. We used IBM SPSS Statistic software for data classification and WEKA tools to evaluate the built cluster. The proposed K-Means clustering algorithm shows promising result with high accuracy when tested using Random Forest algorithm.

  7. A Historical Approach to Clustering in Emerging Economies

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    of external factors. Indeed, researchers have explained clusters as self-contained entities and reduced their success to local exceptionality. In contrast, emerging literature has shown that clusters are integrated in broader structures beyond their location and are rather building blocks of today’s global...... economy. The working paper goes on to present two historical cases from the global south to explain how clusters work as major tools for international business. Particularly in the developing world, multinationals have used clusters as platforms for channeling foreign investment, knowledge, and imported...... inputs. The study concludes by stressing the importance of using historical evidence and data to look at clusters as agglomerations of actors and companies operating not just at the local level but across broader global networks. In doing so the historical perspective provides explanations lacking...

  8. Recommending the heterogeneous cluster type multi-processor system computing

    International Nuclear Information System (INIS)

    Iijima, Nobukazu

    2010-01-01

    Real-time reactor simulator had been developed by reusing the equipment of the Musashi reactor and its performance improvement became indispensable for research tools to increase sampling rate with introduction of arithmetic units using multi-Digital Signal Processor(DSP) system (cluster). In order to realize the heterogeneous cluster type multi-processor system computing, combination of two kinds of Control Processor (CP) s, Cluster Control Processor (CCP) and System Control Processor (SCP), were proposed with Large System Control Processor (LSCP) for hierarchical cluster if needed. Faster computing performance of this system was well evaluated by simulation results for simultaneous execution of plural jobs and also pipeline processing between clusters, which showed the system led to effective use of existing system and enhancement of the cost performance. (T. Tanaka)

  9. 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.

  10. Value, Cost, and Sharing: Open Issues in Constrained Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2006-01-01

    Clustering is an important tool for data mining, since it can identify major patterns or trends without any supervision (labeled data). Over the past five years, semi-supervised (constrained) clustering methods have become very popular. These methods began with incorporating pairwise constraints and have developed into more general methods that can learn appropriate distance metrics. However, several important open questions have arisen about which constraints are most useful, how they can be actively acquired, and when and how they should be propagated to neighboring points. This position paper describes these open questions and suggests future directions for constrained clustering research.

  11. Multi-Optimisation Consensus Clustering

    Science.gov (United States)

    Li, Jian; Swift, Stephen; Liu, Xiaohui

    Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

  12. Photochemistry in rare gas clusters

    International Nuclear Information System (INIS)

    Moeller, T.; Haeften, K. von; Pietrowski, R. von

    1999-01-01

    In this contribution photochemical processes in pure rare gas clusters will be discussed. The relaxation dynamics of electronically excited He clusters is investigated with luminescence spectroscopy. After electronic excitation of He clusters many sharp lines are observed in the visible and infrared spectral range which can be attributed to He atoms and molecules desorbing from the cluster. It turns out that the desorption of electronically excited He atoms and molecules is an important decay channel. The findings for He clusters are compared with results for Ar clusters. While desorption of electronically excited He atoms is observed for all clusters containing up to several thousand atoms a corresponding process in Ar clusters is only observed for very small clusters (N<10). (orig.)

  13. Photochemistry in rare gas clusters

    Energy Technology Data Exchange (ETDEWEB)

    Moeller, T.; Haeften, K. von; Pietrowski, R. von [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Hamburger Synchrotronstrahlungslabor; Laarman, T. [Universitaet Hamburg, II. Institut fuer Experimentalphysik, Luruper Chaussee 149, D-22761 Hamburg (Germany)

    1999-12-01

    In this contribution photochemical processes in pure rare gas clusters will be discussed. The relaxation dynamics of electronically excited He clusters is investigated with luminescence spectroscopy. After electronic excitation of He clusters many sharp lines are observed in the visible and infrared spectral range which can be attributed to He atoms and molecules desorbing from the cluster. It turns out that the desorption of electronically excited He atoms and molecules is an important decay channel. The findings for He clusters are compared with results for Ar clusters. While desorption of electronically excited He atoms is observed for all clusters containing up to several thousand atoms a corresponding process in Ar clusters is only observed for very small clusters (N<10). (orig.)

  14. Globular clusters, old and young

    International Nuclear Information System (INIS)

    Samus', N.N.

    1984-01-01

    The problem of similarity of and difference in the globular and scattered star clusters is considered. Star clusters in astronomy are related either to globular or to scattered ones according to the structure of Hertzsprung-Russell diagram constructed for star clusters, but not according to the appearance. The qlobular clusters in the Galaxy are composed of giants and subgiants, which testifies to the old age of the globular clusters. The Globular clusters in the Magellanic clouds are classified into ''red'' ones - similar to the globular clusters of the Galaxy, and ''blue'' ones - similar to them in appearance but differing extremely by the star composition and so by the age. The old star clusters are suggested to be called globular ones, while another name (''populous'', for example) is suggested to be used for other clusters similar to globular ones only in appearance

  15. 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

  16. 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.

  17. 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 ...

  18. Hardness of Clustering

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Hardness of Clustering. Both k-means and k-medians intractable (when n and d are both inputs even for k =2). The best known deterministic algorithms. are based on Voronoi partitioning that. takes about time. Need for approximation – “close” to optimal.

  19. On small clusters

    International Nuclear Information System (INIS)

    Bernardes, N.

    1984-01-01

    A discussion is presented of zero-point motion effects on the binding energy of a small cluster of identical particles interacting through short range attractive-repulsive forces. The model is appropriate to a discussion of both Van der Waals as well as nuclear forces. (Author) [pt

  20. Emergence of regional clusters

    DEFF Research Database (Denmark)

    Dahl, Michael S.; Østergaard, Christian Richter; Dalum, Bent

    2010-01-01

    The literature on regional clusters has increased considerably during the last decade. The emergence and growth patterns are usually explained by such factors as unique local culture, regional capabilities, tacit knowledge or the existence of location-specific externalities (knowledge spillovers...

  1. Supersonic copper clusters

    International Nuclear Information System (INIS)

    Powers, D.E.; Hansen, S.G.; Geusic, M.E.; Michalopoulos, D.L.; Smalley, R.E.

    1983-01-01

    Copper clusters ranging in size from 1 to 29 atoms have been prepared in a supersonic beam by laser vaporization of a rotating copper target rod within the throat of a pulsed supersonic nozzle using helium for the carrier gas. The clusters were cooled extensively in the supersonic expansion [T(translational) 1 to 4 K, T(rotational) = 4 K, T(vibrational) = 20 to 70 K]. These clusters were detected in the supersonic beam by laser photoionization with time-of-flight mass analysis. Using a number of fixed frequency outputs of an exciplex laser, the threshold behavior of the photoionization cross section was monitored as a function of cluster size.nce two-photon ionization (R2PI) with mass selective detection allowed the detection of five new electronic band systems in the region between 2690 and 3200 A, for each of the three naturally occurring isotopic forms of Cu 2 . In the process of scanning the R2PI spectrum of these new electronic states, the ionization potential of the copper dimer was determined to be 7.894 +- 0.015 eV

  2. Greedy subspace clustering.

    Science.gov (United States)

    2016-09-01

    We consider the problem of subspace clustering: given points that lie on or near the union of many low-dimensional linear subspaces, recover the subspaces. To this end, one first identifies sets of points close to the same subspace and uses the sets ...

  3. Data clustering algorithms and applications

    CERN Document Server

    Aggarwal, Charu C

    2013-01-01

    Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as fea

  4. Cluster structures in light nuclei

    International Nuclear Information System (INIS)

    Horiuchi, H.

    2000-01-01

    Complete text of publication follows. Clustering in neutron-rich nuclei is discussed. To understand the novel features (1,2,3) of the clustering in neutron-rich nuclei, the basic features of the clustering in stable nuclei (4) are briefly reviewed. In neutron-rich nuclei, the requirement of the stability of clusters is questioned and the threshold rule is no more obeyed. Examples of clustering in Be and B isotopes (4,5) are discussed in some detail. Possible existence of novel type of clustering near neutron dripline is suggested (1). (author)

  5. Cluster model of the nucleus

    International Nuclear Information System (INIS)

    Horiuchi, H.; Ikeda, K.

    1986-01-01

    This article reviews the development of the cluster model study. The stress is put on two points; one is how the cluster structure has come to be regarded as a fundamental structure in light nuclei together with the shell-model structure, and the other is how at present the cluster model is extended to and connected with the studies of the various subjects many of which are in the neighbouring fields. The authors the present the main theme with detailed explanations of the fundamentals of the microscopic cluster model which have promoted the development of the cluster mode. Examples of the microscopic cluster model study of light nuclear structure are given

  6. Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

    Science.gov (United States)

    Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

    2015-09-01

    We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Appropriate tools and methods for tropical microepidemiology: a ...

    African Journals Online (AJOL)

    Appropriate tools and methods for tropical microepidemiology: a case-study of malaria clustering in Ethiopia. Tedros A Ghebreyesus, Peter Byass, Karen H Witten, Asfaw Getachew, Mitiku Haile, Mekonnen Yohannes, Steven W Lindsay ...

  8. Lean Manufacturing Auto Cluster at Chennai

    Science.gov (United States)

    Bhaskaran, E.

    2012-10-01

    Due the presence of lot of automotive Industry, Chennai is known as Detroit of India, that producing over 40 % of the Indian vehicle and components. Lean manufacturing concepts have been widely recognized as an important tool in improving the competitiveness of industries. This is a continuous process involving everyone, starting from management to the shop floor. Automotive Component Industries (ACIs) in Ambattur Industrial Estate, Chennai has formed special purpose vehicle (SPV) society namely Ambattur Industrial Estate Manufacturers Association (AIEMA) Technology Centre (ATC) lean manufacturing cluster (ATC-LMC) during July 2010 under lean manufacturing competitiveness scheme, that comes under National Manufacturing Competitiveness Programme of Government of India. The Tripartite Agreement is taken place between National Productivity Council, consultants and cluster (ATC-LMC). The objective is to conduct diagnostic study, study on training and application of various lean manufacturing techniques and auditing in ten ACIs. The methodology adopted is collection of primary data/details from ten ACIs. In the first phase, diagnostic study is done and the areas for improvement in each of the cluster member companies are identified. In the second phase, training programs and implementation is done on 5S and other areas. In the third phase auditing is done and found that the lean manufacturing techniques implementation in ATC-LMC is sustainable and successful in every cluster companies, which will not only enhance competitiveness but also decrease cost, time and increase productivity. The technical efficiency of LMC companies also increases significantly.

  9. The Stormy Life of Galaxy Clusters

    Science.gov (United States)

    Rudnick, Lawrence

    2018-01-01

    Galaxy clusters, the largest gravitationally bound structures, hold the full history of their baryonic evolution, serve as important cosmological tools and allow us to probe unique physical regimes in their diffuse plasmas. With characteristic dynamical timescales of 107-109 years, these diffuse thermal and relativistic media continue to evolve, as dark matter drives major mergers and more gentle continuing accretion. The history of this assembly is encoded in the plasmas, and a wide range of observational and theoretical investigations are aimed at decoding their signatures. X-ray temperature and density variations, low Mach number shocks, and "cold front" discontinuities all illuminate clusters' continued evolution. Radio structures and spectra are passive indicators of merger shocks, while radio galaxy distortions reveal the complex motions in the intracluster medium. Deep in cluster cores, AGNs associated with brightest cluster galaxies provide ongoing energy, and perhaps even stabilize the intracluster medium. In this talk, we will recount this evolving picture of the stormy ICM, and suggest areas of likely advance in the coming years.

  10. The rotation of galaxy clusters

    International Nuclear Information System (INIS)

    Tovmassian, H.M.

    2015-01-01

    The method for detection of the galaxy cluster rotation based on the study of distribution of member galaxies with velocities lower and higher of the cluster mean velocity over the cluster image is proposed. The search for rotation is made for flat clusters with a/b> 1.8 and BMI type clusters which are expected to be rotating. For comparison there were studied also round clusters and clusters of NBMI type, the second by brightness galaxy in which does not differ significantly from the cluster cD galaxy. Seventeen out of studied 65 clusters are found to be rotating. It was found that the detection rate is sufficiently high for flat clusters, over 60 per cent, and clusters of BMI type with dominant cD galaxy, ≈ 35 per cent. The obtained results show that clusters were formed from the huge primordial gas clouds and preserved the rotation of the primordial clouds, unless they did not have mergings with other clusters and groups of galaxies, in the result of which the rotation has been prevented

  11. Single-cluster dynamics for the random-cluster model

    NARCIS (Netherlands)

    Deng, Y.; Qian, X.; Blöte, H.W.J.

    2009-01-01

    We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

  12. Choosing the Number of Clusters in K-Means Clustering

    Science.gov (United States)

    Steinley, Douglas; Brusco, Michael J.

    2011-01-01

    Steinley (2007) provided a lower bound for the sum-of-squares error criterion function used in K-means clustering. In this article, on the basis of the lower bound, the authors propose a method to distinguish between 1 cluster (i.e., a single distribution) versus more than 1 cluster. Additionally, conditional on indicating there are multiple…

  13. A Distributed Flocking Approach for Information Stream Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-01-01

    Intelligence analysts are currently overwhelmed with the amount of information streams generated everyday. There is a lack of comprehensive tool that can real-time analyze the information streams. Document clustering analysis plays an important role in improving the accuracy of information retrieval. However, most clustering technologies can only be applied for analyzing the static document collection because they normally require a large amount of computation resource and long time to get accurate result. It is very difficult to cluster a dynamic changed text information streams on an individual computer. Our early research has resulted in a dynamic reactive flock clustering algorithm which can continually refine the clustering result and quickly react to the change of document contents. This character makes the algorithm suitable for cluster analyzing dynamic changed document information, such as text information stream. Because of the decentralized character of this algorithm, a distributed approach is a very natural way to increase the clustering speed of the algorithm. In this paper, we present a distributed multi-agent flocking approach for the text information stream clustering and discuss the decentralized architectures and communication schemes for load balance and status information synchronization in this approach.

  14. Clustering of experimental data and its application to nuclear data evaluation

    International Nuclear Information System (INIS)

    Abboud, A.; Rashed, R.; Ibrahim, M.

    1997-01-01

    A semi-automatic pre-processing technique has been proposed by Iwasaki to classify the experimental data for a reaction into one or a small number of large data groups, called main cluster(s), and to eliminate some data which deviate from the main body of the data. The classifying method is based on a technique like pattern clustering in the information processing domain. Test of the data clustering formed reasonable main clusters for three activation cross-sections. This technique is a helpful tool in the neutron cross-section evaluation. (author). 4 refs, 1 fig., 3 tabs

  15. SU(3) techniques for angular momentum projected matrix elements in multi-cluster problems

    International Nuclear Information System (INIS)

    Hecht, K.T.; Zahn, W.

    1978-01-01

    In the theory of integral transforms for the evaluation of the resonating group kernels needed for cluster model calculations, the evaluation of matrix elements in an angular momentum coupled basis has proved to be difficult for cluster problems involving more than two fragments. For multi-cluster wave functions SU(3) coupling and recoupling techniques can furnish a tool for the practical evaluation matrix elements in an angular momentum coupled basis if the several relative motion harmonic oscillator functions in Bargmann space have simple SU(3) coupling properties. The method is illustrated by a three-cluster problem, such as 12 C = α + α + α, involving three 1 S clusters. 2 references

  16. Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm

    DEFF Research Database (Denmark)

    Grotkjær, Thomas; Winther, Ole; Regenberg, Birgitte

    2006-01-01

    Motivation: Hierarchical and relocation clustering (e.g. K-means and self-organizing maps) have been successful tools in the display and analysis of whole genome DNA microarray expression data. However, the results of hierarchical clustering are sensitive to outliers, and most relocation methods...... analysis by collecting re-occurring clustering patterns in a co-occurrence matrix. The results show that consensus clustering obtained from clustering multiple times with Variational Bayes Mixtures of Gaussians or K-means significantly reduces the classification error rate for a simulated dataset...

  17. Heavy hitters via cluster-preserving clustering

    DEFF Research Database (Denmark)

    Larsen, Kasper Green; Nelson, Jelani; Nguyen, Huy L.

    2016-01-01

    In the turnstile lp heavy hitters problem with parameter ε, one must maintain a high-dimensional vector xεRn subject to updates of the form update (i,Δ) causing the change xi≤ ← xi + Δ, where iε[n], ΔεR. Upon receiving a query, the goal is to report every "heavy hitter" iε[n] with |xi| ≥ε......|x|p as part of a list L⊆[n] of size O(1/εp), i.e. proportional to the maximum possible number of heavy hitters. For any pε(0,2] the COUNTSKETCH of [CCFC04] solves lp heavy hitters using O(ε-plog n) words of space with O(log n) update time, O(nlog n) query time to output L, and whose output after any query......, providing correctness whp. In fact, a simpler version of our algorithm for p = 1 in the strict turnstile model answers queries even faster than the "dyadic trick" by roughly a log n factor, dominating it in all regards. Our main innovation is an efficient reduction from the heavy hitters to a clustering...

  18. Evolution of the spherical clusters

    International Nuclear Information System (INIS)

    Surdin, V.G.

    1978-01-01

    The possible processes of the Galaxy spherical clusters formation and evolution are described on a popular level. The orbits of spherical cluster motion and their spatial velocities are determined. Given are the distrbutions of spherical cluster stars according to their velocities and the observed distribution of spherical clusters in the area of the Galaxy slow evolution. The dissipation and dynamic friction processes destructing clusters with the mass less than 10 4 of solar mass and bringing about the reduction of clusters in the Galaxy are considered. The paradox of forming mainly X-ray sources in spherical clusters is explained. The schematic image of possible ways of forming X-ray sources in spherical clusters is given

  19. Clusters in nuclei. Vol. 1

    International Nuclear Information System (INIS)

    Beck, Christian

    2010-01-01

    Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is presently one of the domains of heavy-ion nuclear physics facing both the greatest challenges and opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physics decided to team up in producing a comprehensive collection of lectures and tutorial reviews covering the field. This first volume, gathering seven extensive lectures, covers the follow topics: - Cluster Radioactivity - Cluster States and Mean Field Theories - Alpha Clustering and Alpha Condensates - Clustering in Neutron-rich Nuclei - Di-neutron Clustering - Collective Clusterization in Nuclei - Giant Nuclear Molecules By promoting new ideas and developments while retaining a pedagogical nature of presentation throughout, these lectures will both serve as a reference and as advanced teaching material for future courses and schools in the fields of nuclear physics and nuclear astrophysics. (orig.)

  20. 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

  1. Random matrix improved subspace clustering

    KAUST Repository

    Couillet, Romain; Kammoun, Abla

    2017-01-01

    This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show

  2. Eclipsing binaries in open clusters

    DEFF Research Database (Denmark)

    Southworth, John; Clausen, J.V.

    2006-01-01

    Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August......Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August...

  3. Dynamical aspects of galaxy clustering

    International Nuclear Information System (INIS)

    Fall, S.M.

    1980-01-01

    Some recent work on the origin and evolution of galaxy clustering is reviewed, particularly within the context of the gravitational instability theory and the hot big-bang cosmological model. Statistical measures of clustering, including correlation functions and multiplicity functions, are explained and discussed. The close connection between galaxy formation and clustering is emphasized. Additional topics include the dependence of galaxy clustering on the spectrum of primordial density fluctuations and the mean mass density of the Universe. (author)

  4. [Cluster analysis in biomedical researches].

    Science.gov (United States)

    Akopov, A S; Moskovtsev, A A; Dolenko, S A; Savina, G D

    2013-01-01

    Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research.

  5. THE ASSEMBLY OF GALAXY CLUSTERS

    International Nuclear Information System (INIS)

    Berrier, Joel C.; Stewart, Kyle R.; Bullock, James S.; Purcell, Chris W.; Barton, Elizabeth J.; Wechsler, Risa H.

    2009-01-01

    We study the formation of 53 galaxy cluster-size dark matter halos (M = 10 14.0-14.76 M sun ) formed within a pair of cosmological Λ cold dark matter N-body simulations, and track the accretion histories of cluster subhalos with masses large enough to host ∼0.3 L * galaxies. By associating subhalos with cluster galaxies, we find the majority of galaxies in clusters experience no 'preprocessing' in the group environment prior to their accretion into the cluster. On average, 70% of cluster galaxies fall into the cluster potential directly from the field, with no luminous companions in their host halos at the time of accretion; less than 12% are accreted as members of groups with five or more galaxies. Moreover, we find that cluster galaxies are significantly less likely to have experienced a merger in the recent past (∼<6 Gyr) than a field halo of the same mass. These results suggest that local cluster processes such as ram pressure stripping, galaxy harassment, or strangulation play the dominant role in explaining the difference between cluster and field populations at a fixed stellar mass, and that pre-evolution or past merging in the group environment is of secondary importance for setting cluster galaxy properties for most clusters. The accretion times for z = 0 cluster members are quite extended, with ∼20% incorporated into the cluster halo more than 7 Gyr ago and ∼20% within the last 2 Gyr. By comparing the observed morphological fractions in cluster and field populations, we estimate an approximate timescale for late-type to early-type transformation within the cluster environment to be ∼6 Gyr.

  6. Chronorisk in cluster headache

    DEFF Research Database (Denmark)

    Barloese, Mads; Haddock, Bryan; Lund, Nunu T

    2018-01-01

    and a spectral analysis identifying oscillations in risk. Results The Gaussian model fit for the chronorisk distribution for all patients reporting diurnal rhythmicity (n = 286) had a goodness of fit R2 value of 0.97 and identified three times of increased risk peaking at 21:41, 02:02 and 06:23 hours....... In subgroups, three to five modes of increased risk were found and goodness of fit values ranged from 0.85-0.99. Spectral analysis revealed multiple distinct oscillation frequencies in chronorisk in subgroups including a dominant circadian oscillation in episodic patients and an ultradian in chronic....... Conclusions Chronorisk in cluster headache can be characterised as a sum of individual, timed events of increased risk, each having a Gaussian distribution. In episodic cluster headache, attacks follow a circadian rhythmicity whereas, in the chronic variant, ultradian oscillations are dominant reflecting...

  7. CSR in Industrial Clusters

    DEFF Research Database (Denmark)

    Lund-Thomsen, Peter; Pillay, Renginee G.

    2012-01-01

    Purpose – The paper seeks to review the literature on CSR in industrial clusters in developing countries, identifying the main strengths, weaknesses, and gaps in this literature, pointing to future research directions and policy implications in the area of CSR and industrial cluster development....... Design/methodology/approach – A literature review is conducted of both academic and policy-oriented writings that contain the keywords “industrial clusters” and “developing countries” in combination with one or more of the following terms: corporate social responsibility, environmental management, labor...... standards, child labor, climate change, social upgrading, and environmental upgrading. The authors examine the key themes in this literature, identify the main gaps, and point to areas where future work in this area could usefully be undertaken. Feedback has been sought from some of the leading authors...

  8. Clusters of Galaxies

    Science.gov (United States)

    Huchtmeier, W. K.; Richter, O. G.; Materne, J.

    1981-09-01

    The large-scale structure of the universe is dominated by clustering. Most galaxies seem to be members of pairs, groups, clusters, and superclusters. To that degree we are able to recognize a hierarchical structure of the universe. Our local group of galaxies (LG) is centred on two large spiral galaxies: the Andromeda nebula and our own galaxy. Three sr:naller galaxies - like M 33 - and at least 23 dwarf galaxies (KraanKorteweg and Tammann, 1979, Astronomische Nachrichten, 300, 181) can be found in the evironment of these two large galaxies. Neighbouring groups have comparable sizes (about 1 Mpc in extent) and comparable numbers of bright members. Small dwarf galaxies cannot at present be observed at great distances.

  9. 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.

  10. On clusters and clustering from atoms to fractals

    CERN Document Server

    Reynolds, PJ

    1993-01-01

    This book attempts to answer why there is so much interest in clusters. Clusters occur on all length scales, and as a result occur in a variety of fields. Clusters are interesting scientifically, but they also have important consequences technologically. The division of the book into three parts roughly separates the field into small, intermediate, and large-scale clusters. Small clusters are the regime of atomic and molecular physics and chemistry. The intermediate regime is the transitional regime, with its characteristics including the onset of bulk-like behavior, growth and aggregation, a

  11. Cosmology, Clusters and Calorimeters

    Science.gov (United States)

    Figueroa-Feliciano, Enectali

    2005-01-01

    I will review the current state of Cosmology with Clusters and discuss the application of microcalorimeter arrays to this field. With the launch of Astro-E2 this summer and a slew of new missions being developed, microcalorimeters are the next big thing in x-ray astronomy. I will cover the basics and not-so-basic concepts of microcalorimeter designs and look at the future to see where this technology will go.

  12. Three-atom clusters

    International Nuclear Information System (INIS)

    Pen'kov, F.M.

    1998-01-01

    The Born-Oppenheimer approximation is used to obtain an equation for the effective interaction in three atoms bound by a single electron. For low binding energies in an 'electron + atom' pair, long-range forces arise between the atoms, leading to bound states when the size of the three-atom cluster is a few tens of angstrom. A system made of alkali-metal atoms is considered as an example

  13. 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.

  14. Seizure clusters: characteristics and treatment.

    Science.gov (United States)

    Haut, Sheryl R

    2015-04-01

    Many patients with epilepsy experience 'clusters' or flurries of seizures, also termed acute repetitive seizures (ARS). Seizure clustering has a significant impact on health and quality of life. This review summarizes recent advances in the definition and neurophysiologic understanding of clustering, the epidemiology and risk factors for clustering and both inpatient and outpatient clinical implications. New treatments for seizure clustering/ARS are perhaps the area of greatest recent progress. Efforts have focused on creating a uniform definition of a seizure cluster. In neurophysiologic studies of refractory epilepsy, seizures within a cluster appear to be self-triggering. Clinical progress has been achieved towards a more precise prevalence of clustering, and consensus guidelines for epilepsy monitoring unit safety. The greatest recent advances are in the study of nonintravenous route of benzodiazepines as rescue medications for seizure clusters/ARS. Rectal benzodiazepines have been very effective but barriers to use exist. New data on buccal, intramuscular and intranasal preparations are anticipated to lead to a greater number of approved treatments. Progesterone may be effective for women who experience catamenial clusters. Seizure clustering is common, particularly in the setting of medically refractory epilepsy. Clustering worsens health and quality of life, and the field requires greater focus on clarifying of definition and clinical implications. Progress towards the development of nonintravenous routes of benzodiazepines has the potential to improve care in this area.

  15. Electron localization in water clusters

    International Nuclear Information System (INIS)

    Landman, U.; Barnett, R.N.; Cleveland, C.L.; Jortner, J.

    1987-01-01

    Electron attachment to water clusters was explored by the quantum path integral molecular dynamics method, demonstrating that the energetically favored localization mode involves a surface state of the excess electron, rather than the precursor of the hydrated electron. The cluster size dependence, the energetics and the charge distribution of these novel electron-cluster surface states are explored. 20 refs., 2 figs., 1 tab

  16. Subspace K-means clustering.

    Science.gov (United States)

    Timmerman, Marieke E; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

    2013-12-01

    To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning approaches. To evaluate subspace K-means, we performed a comparative simulation study, in which we manipulated the overlap of subspaces, the between-cluster variance, and the error variance. The study shows that the subspace K-means algorithm is sensitive to local minima but that the problem can be reasonably dealt with by using partitions of various cluster procedures as a starting point for the algorithm. Subspace K-means performs very well in recovering the true clustering across all conditions considered and appears to be superior to its competitor methods: K-means, reduced K-means, factorial K-means, mixtures of factor analyzers (MFA), and MCLUST. The best competitor method, MFA, showed a performance similar to that of subspace K-means in easy conditions but deteriorated in more difficult ones. Using data from a study on parental behavior, we show that subspace K-means analysis provides a rich insight into the cluster characteristics, in terms of both the relative positions of the clusters (via the centroids) and the shape of the clusters (via the within-cluster residuals).

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

    Directory of Open Access Journals (Sweden)

    Gulcin Salıngan

    2012-07-01

    Full Text Available Economic development has always been a moving target. Both the national and local governments have been facing the challenge of implementing the effective and efficient economic policy and program in order to best utilize their limited resources. One of the recent approaches in this area is called cluster-based economic analysis and strategy development. This study reviews key literature and some of the cluster based economic policies adopted by different governments. Based on this review, it proposes “the cluster life cycle” as a determining factor to identify the support requirements of clusters. A survey, designed based on literature review of International Cluster support programs, was conducted with 30 participants from 3 clusters with different maturity stage. This paper discusses the results of this study conducted among the cluster members in Eskişehir- Bilecik-Kütahya Region in Turkey on the requirement of the support to foster the development of related clusters.

  18. Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

    Science.gov (United States)

    Youroukova, Vania M; Dimitrova, Denitsa G; Valerieva, Anna D; Lesichkova, Spaska S; Velikova, Tsvetelina V; Ivanova-Todorova, Ekaterina I; Tumangelova-Yuzeir, Kalina D

    2017-06-01

    Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.

  19. Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

    Directory of Open Access Journals (Sweden)

    Lauren Hund

    Full Text Available Lot quality assurance sampling (LQAS surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

  20. Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

    Science.gov (United States)

    Hund, Lauren; Bedrick, Edward J; Pagano, Marcello

    2015-01-01

    Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

  1. Electronic structure of metal clusters

    International Nuclear Information System (INIS)

    Wertheim, G.K.

    1989-01-01

    Photoemission spectra of valence electrons in metal clusters, together with threshold ionization potential measurements, provide a coherent picture of the development of the electronic structure from the isolated atom to the large metallic cluster. An insulator-metal transition occurs at an intermediate cluster size, which serves to define the boundary between small and large clusters. Although the outer electrons may be delocalized over the entire cluster, a small cluster remains insulating until the density of states near the Fermi level exceeds 1/kT. In large clusters, with increasing cluster size, the band structure approaches that of the bulk metal. However, the bands remain significantly narrowed even in a 1000-atom cluster, giving an indication of the importance of long-range order. The core-electron binding-energy shifts of supported metal clusters depend on changes in the band structure in the initial state, as well as on various final-state effects, including changes in core hole screening and the coulomb energy of the final-state charge. For cluster supported on amorphous carbon, this macroscopic coulomb shift is often dominant, as evidenced by the parallel shifts of the core-electron binding energy and the Fermi edge. Auger data confirm that final-state effects dominate in cluster of Sn and some other metals. Surface atom core-level shifts provide a valuable guide to the contributions of initial-state changes in band structure to cluster core-electron binding energy shifts, especially for Au and Pt. The available data indicate that the shift observed in supported, metallic clusters arise largely from the charge left on the cluster by photoemission. As the metal-insulator transition is approached from above, metallic screening is suppressed and the shift is determined by the local environment. (orig.)

  2. Multiparticle production through isoscalar clusters

    International Nuclear Information System (INIS)

    Armburst, W.T.; Scott, D.M.

    1975-01-01

    The isoscalar cluster model for multiparticle production was extended to include clusters of A 2 meson pairs in addition to previously studied rho-rho and sigma clusters. The production of each type of cluster is given by an energy dependent Poisson distribution. The Poisson parameters determined from the charged particle multiplicity distributions indicate that the inclusion of A 2 -A 2 clusters does not improve the fit to the data. The predictions of the model for n 0 n/sub -/, f/sup 2//sub -,-/, and f/sup 2//sub 0,0/ compare favorably to the experimental values. (U.S.)

  3. Monitoring in a grid cluster

    International Nuclear Information System (INIS)

    Crooks, David; Mitchell, Mark; Roy, Gareth; Skipsey, Samuel Cadellin; Britton, David; Purdie, Stuart

    2014-01-01

    The monitoring of a grid cluster (or of any piece of reasonably scaled IT infrastructure) is a key element in the robust and consistent running of that site. There are several factors which are important to the selection of a useful monitoring framework, which include ease of use, reliability, data input and output. It is critical that data can be drawn from different instrumentation packages and collected in the framework to allow for a uniform view of the running of a site. It is also very useful to allow different views and transformations of this data to allow its manipulation for different purposes, perhaps unknown at the initial time of installation. In this context, we present the findings of an investigation of the Graphite monitoring framework and its use at the ScotGrid Glasgow site. In particular, we examine the messaging system used by the framework and means to extract data from different tools, including the existing framework Ganglia which is in use at many sites, in addition to adapting and parsing data streams from external monitoring frameworks and websites.

  4. Ionization of nitrogen cluster beam

    International Nuclear Information System (INIS)

    Yano, Katsuki; Be, S.H.; Enjoji, Hiroshi; Okamoto, Kosuke

    1975-01-01

    A nitrogen cluster beam (neutral particle intensity of 28.6 mAsub(eq)) is ionized by electron collisions in a Bayard-Alpert gauge type ionizer. The extraction efficiency of about 65% is obtained at an electron current of 10 mA with an energy of 50 eV. The mean cluster size produced at a pressure of 663 Torr and temperature of 77.3 K is 2x10 5 molecules per cluster. By the Coulomb repulsion force, multiply ionized cluster ions are broken up into smaller fragments and the cluster ion size reduces to one-fourth at an electron current of 15 mA. Mean neutral cluster sizes depend strongly on the initial degree of saturation PHI 0 and are 2x10 5 , 7x10 4 and 3x10 4 molecules per cluster at PHI 0 's of 0.87, 0.66 and 0.39, respectively. (auth.)

  5. Dense Fe cluster-assembled films by energetic cluster deposition

    International Nuclear Information System (INIS)

    Peng, D.L.; Yamada, H.; Hihara, T.; Uchida, T.; Sumiyama, K.

    2004-01-01

    High-density Fe cluster-assembled films were produced at room temperature by an energetic cluster deposition. Though cluster-assemblies are usually sooty and porous, the present Fe cluster-assembled films are lustrous and dense, revealing a soft magnetic behavior. Size-monodispersed Fe clusters with the mean cluster size d=9 nm were synthesized using a plasma-gas-condensation technique. Ionized clusters are accelerated electrically and deposited onto the substrate together with neutral clusters from the same cluster source. Packing fraction and saturation magnetic flux density increase rapidly and magnetic coercivity decreases remarkably with increasing acceleration voltage. The Fe cluster-assembled film obtained at the acceleration voltage of -20 kV has a packing fraction of 0.86±0.03, saturation magnetic flux density of 1.78±0.05 Wb/m 2 , and coercivity value smaller than 80 A/m. The resistivity at room temperature is ten times larger than that of bulk Fe metal

  6. K-means Clustering: Lloyd's algorithm

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. K-means Clustering: Lloyd's algorithm. Refines clusters iteratively. Cluster points using Voronoi partitioning of the centers; Centroids of the clusters determine the new centers. Bad example k = 3, n =4.

  7. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

    Science.gov (United States)

    Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

    2015-01-01

    The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

  8. Clustering of agricultural enterprises

    Directory of Open Access Journals (Sweden)

    Michaela Beranová

    2013-01-01

    Full Text Available Agricultural business is a very specific branch which is characterized by very low financial performance while this characteristic is given mainly by external factors as market pricing of agricultural commodities on one side, and production costs of agricultural commodities on the other side. This way, agricultural enterprises recognize negative values of gross margin in the Profit and Loss Statement but positive value of operating profit after even there are items of costs which are deducted. These results are derived from agricultural production subsidies which are recognized as income in the P/L Statement. In connection with this fact, the government subsidies are a substantial component of financial performance of agricultural enterprises.Primary research proceeded on the statistical sample of one hundred agricultural companies, has shown that also other specifics influencing financial performance of these businesses exist here. In order to determine the influences, the cluster analysis has been applied at using more than 10 variables. This approach has led to construction of clusters (groups of agricultural business entities with different characteristics of the group. The objective of this paper is to identify the main determinants of financial performance of agricultural enterprises and to determine their influences under different economic characteristics of these business entities. For this purpose, the regression analysis has been subsequently applied on the groups of companies coming out from the cluster analysis. Besides the operating profit which is the main driving force of financial performance measured with the economic value added (EVA in agricultural enterprises, also capital structure and cost of capital have been observed as very strong influences on financial performance but these factors have different directions of their influence on the economic value added under different financial characteristics of agricultural

  9. Humanitarian Logistics: a Clustering Methodology for Assisting Humanitarian Operations

    Directory of Open Access Journals (Sweden)

    Fabiana santos Lima

    2014-06-01

    Full Text Available In this paper, we propose a methodology to identify and classify regions by the type and frequency of disasters. The data on the clusters allow you to extract information that can be used in the preparedness phase as well as to identify the relief items needed to meet each cluster. Using this approach, the clusters are formed by using a computing tool that uses as the input the history data of the disasters in the Brazilian state of Santa Catarina, with a specific focus on: windstorms, hail, floods, droughts, landslides, and flash floods. The results show that the knowledge provided by the clustering analysis contributes to the decision making process in the response phase of Humanitarian Logistics (HL.

  10. Using cluster analysis to organize and explore regional GPS velocities

    Science.gov (United States)

    Simpson, Robert W.; Thatcher, Wayne; Savage, James C.

    2012-01-01

    Cluster analysis offers a simple visual exploratory tool for the initial investigation of regional Global Positioning System (GPS) velocity observations, which are providing increasingly precise mappings of actively deforming continental lithosphere. The deformation fields from dense regional GPS networks can often be concisely described in terms of relatively coherent blocks bounded by active faults, although the choice of blocks, their number and size, can be subjective and is often guided by the distribution of known faults. To illustrate our method, we apply cluster analysis to GPS velocities from the San Francisco Bay Region, California, to search for spatially coherent patterns of deformation, including evidence of block-like behavior. The clustering process identifies four robust groupings of velocities that we identify with four crustal blocks. Although the analysis uses no prior geologic information other than the GPS velocities, the cluster/block boundaries track three major faults, both locked and creeping.

  11. Clustered tuberculosis in a low-burden country

    DEFF Research Database (Denmark)

    Kamper-Jørgensen, Z; Andersen, A B; Kok-Jensen, A

    2012-01-01

    Molecular genotyping of Mycobacterium tuberculosis has proved to be a powerful tool in tuberculosis surveillance, epidemiology, and control. Based on results obtained through 15 years of nationwide IS6110 restriction fragment length polymorphism (RFLP) genotyping of M. tuberculosis cases in Denmark......, a country on the way toward tuberculosis elimination, we discuss M. tuberculosis transmission dynamics and point to areas for control interventions. Cases with 100% identical genotypes (RFLP patterns) were defined as clustered, and a cluster was defined as cases with an identical genotype. Of 4,601 included...... cases, corresponding to 76% of reported and 97% of culture-verified tuberculosis cases in the country, 56% were clustered, of which 69% were Danes. Generally, Danes were more often in large clusters (= 50 persons), older (mean age, 45 years), and male (male/female ratio, 2.5). Also, Danes had a higher...

  12. Exploring Undergraduates' Understanding of Photosynthesis Using Diagnostic Question Clusters

    Science.gov (United States)

    Parker, Joyce M.; Anderson, Charles W.; Heidemann, Merle; Merrill, John; Merritt, Brett; Richmond, Gail; Urban-Lurain, Mark

    2012-01-01

    We present a diagnostic question cluster (DQC) that assesses undergraduates' thinking about photosynthesis. This assessment tool is not designed to identify individual misconceptions. Rather, it is focused on students' abilities to apply basic concepts about photosynthesis by reasoning with a coordinated set of practices based on a few scientific…

  13. Computationally inexpensive interpretation of magnetic data for finite spin clusters

    DEFF Research Database (Denmark)

    Thuesen, Christian Aagaard; Weihe, Høgni; Bendix, Jesper

    2010-01-01

    We show that high-temperature expansion of the partition function is a computationally convenient tool to interpretation of magnetic properties of spin clusters wherein the spin centers are interacting via an isotropic Heisenberg exchange operator. High-temperature expansions up to order 12 are u...

  14. Hadoop cluster deployment

    CERN Document Server

    Zburivsky, Danil

    2013-01-01

    This book is a step-by-step tutorial filled with practical examples which will show you how to build and manage a Hadoop cluster along with its intricacies.This book is ideal for database administrators, data engineers, and system administrators, and it will act as an invaluable reference if you are planning to use the Hadoop platform in your organization. It is expected that you have basic Linux skills since all the examples in this book use this operating system. It is also useful if you have access to test hardware or virtual machines to be able to follow the examples in the book.

  15. Clusters in attractive colloids

    Energy Technology Data Exchange (ETDEWEB)

    Coniglio, A [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , Complesso Universitario di Monte Sant' Angelo, via Cintia 80126 Naples (Italy); Arcangelis, L de [Dipartimento di Ingegneria dell' Informazione and CNISM II Universita di Napoli, Aversa (CE) (Italy); Candia, A de [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , Complesso Universitario di Monte Sant' Angelo, via Cintia 80126 Naples (Italy); Gado, E Del [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , Complesso Universitario di Monte Sant' Angelo, via Cintia 80126 Naples (Italy); Fierro, A [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , Complesso Universitario di Monte Sant' Angelo, via Cintia 80126 Naples (Italy); Sator, N [Laboratoire de Physique Theorique de la Matiere Condensee, Universite Pierre et Marie Curie-Paris6, UMR (CNRS) 7600 Case 121, 4 Place Jussieu 75252 Paris Cedex 05 (France)

    2006-09-13

    We discuss how the anomalous increase of the viscosity in colloidal systems with short-range attraction can be related to the formation of long-living clusters. Based on molecular dynamics and Monte Carlo numerical simulations of different models, we propose a similar picture for colloidal gelation at low and intermediate volume fractions. On this basis, we analyze the distinct role played by the formation of long-living bonds and the crowding of the particles in the slow dynamics of attractive colloidal systems.

  16. Delineation of gravel-bed clusters via factorial kriging

    Science.gov (United States)

    Wu, Fu-Chun; Wang, Chi-Kuei; Huang, Guo-Hao

    2018-05-01

    Gravel-bed clusters are the most prevalent microforms that affect local flows and sediment transport. A growing consensus is that the practice of cluster delineation should be based primarily on bed topography rather than grain sizes. Here we present a novel approach for cluster delineation using patch-scale high-resolution digital elevation models (DEMs). We use a geostatistical interpolation method, i.e., factorial kriging, to decompose the short- and long-range (grain- and microform-scale) DEMs. The required parameters are determined directly from the scales of the nested variograms. The short-range DEM exhibits a flat bed topography, yet individual grains are sharply outlined, making the short-range DEM a useful aid for grain segmentation. The long-range DEM exhibits a smoother topography than the original full DEM, yet groupings of particles emerge as small-scale bedforms, making the contour percentile levels of the long-range DEM a useful tool for cluster identification. Individual clusters are delineated using the segmented grains and identified clusters via a range of contour percentile levels. Our results reveal that the density and total area of delineated clusters decrease with increasing contour percentile level, while the mean grain size of clusters and average size of anchor clast (i.e., the largest particle in a cluster) increase with the contour percentile level. These results support the interpretation that larger particles group as clusters and protrude higher above the bed than other smaller grains. A striking feature of the delineated clusters is that anchor clasts are invariably greater than the D90 of the grain sizes even though a threshold anchor size was not adopted herein. The average areal fractal dimensions (Hausdorff-Besicovich dimensions of the projected areas) of individual clusters, however, demonstrate that clusters delineated with different contour percentile levels exhibit similar planform morphologies. Comparisons with a

  17. Trimming and clustering sugarcane ESTs

    Directory of Open Access Journals (Sweden)

    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.

  18. Globular clusters - Fads and fallacies

    International Nuclear Information System (INIS)

    White, R.E.

    1991-01-01

    The types of globular clusters observed in the Milky Way Galaxy are described together with their known characteristics, with special attention given to correcting the erroneous statements made earlier about globular clusters. Among these are the following statements: the Galaxy is surrounded by many hundreds of globular clusters; all globular clusters are located toward the Galactic center, all globular clusters are metal poor and move about the Galaxy in highly elliptical paths; all globular clusters contain RR Lyrae-type variable stars, and the RR Lyrae stars found outside of globulars have come from cluster dissolution or ejection; all of the stars in a given cluster were born at the same time and have the same chemical composition; X-ray globulars are powered by central black holes; and the luminosity functions for globular clusters are well defined and well determined. Consideration is given to the fact that globular clusters in the Magellanic Clouds differ from those in the Milky Way by their age distribution and that the globulars of the SMC differ from those of the LMC

  19. 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.

  20. Techniques for Representation of Regional Clusters in Geographical In-formation Systems

    Directory of Open Access Journals (Sweden)

    Adriana REVEIU

    2011-01-01

    Full Text Available This paper provides an overview of visualization techniques adapted for regional clusters presentation in Geographic Information Systems. Clusters are groups of companies and insti-tutions co-located in a specific geographic region and linked by interdependencies in providing a related group of products and services. The regional clusters can be visualized by projecting the data into two-dimensional space or using parallel coordinates. Cluster membership is usually represented by different colours or by dividing clusters into several panels of a grille display. Taking into consideration regional clusters requirements and the multilevel administrative division of the Romania’s territory, I used two cartograms: NUTS2- regions and NUTS3- counties, to illustrate the tools for regional clusters representation.

  1. Macroeconomic Dimensions in the Clusterization Processes: Lithuanian Biomass Cluster Case

    Directory of Open Access Journals (Sweden)

    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.

  2. Multisource Images Analysis Using Collaborative Clustering

    Directory of Open Access Journals (Sweden)

    Pierre Gançarski

    2008-04-01

    Full Text Available The development of very high-resolution (VHR satellite imagery has produced a huge amount of data. The multiplication of satellites which embed different types of sensors provides a lot of heterogeneous images. Consequently, the image analyst has often many different images available, representing the same area of the Earth surface. These images can be from different dates, produced by different sensors, or even at different resolutions. The lack of machine learning tools using all these representations in an overall process constraints to a sequential analysis of these various images. In order to use all the information available simultaneously, we propose a framework where different algorithms can use different views of the scene. Each one works on a different remotely sensed image and, thus, produces different and useful information. These algorithms work together in a collaborative way through an automatic and mutual refinement of their results, so that all the results have almost the same number of clusters, which are statistically similar. Finally, a unique result is produced, representing a consensus among the information obtained by each clustering method on its own image. The unified result and the complementarity of the single results (i.e., the agreement between the clustering methods as well as the disagreement lead to a better understanding of the scene. The experiments carried out on multispectral remote sensing images have shown that this method is efficient to extract relevant information and to improve the scene understanding.

  3. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  4. Laser ionization of molecular clusters

    International Nuclear Information System (INIS)

    Desai, S.; Feigerle, C.S.

    1995-01-01

    Multiphoton ionization coupled with mass spectrometry was used to investigate molecular cluster distributions. Three examples will be discussed in this presentation. First, in studies of neat nitric oxide clusters, (NO) m , an interesting odd-even intensity alternation was observed and will be discussed in terms of electron-pairing considerations. In a separate study, the binary clusters comprising nitric oxide and methane preferentially form a stoichiometric cluster made up of repeating units of (NO) 2 CH 4 . These presumably represent a particularly strongly bound open-quotes van der Waalsclose quotes subunit. Finally, in similar studies of neat carbon disulfide clusters, (CS 2 ) m , additional photon absorption after the two-photon ionization step stimulates a series of intracluster ion-molecular reactions leading to formation of S m + and (CS) m + polymers, as well as intermediate species such as S m + (CS 2 ). This molecular cluster analogue of open-quotes laser snowclose quotes will be described in detail

  5. Cluster polylogarithms for scattering amplitudes

    International Nuclear Information System (INIS)

    Golden, John; Paulos, Miguel F; Spradlin, Marcus; Volovich, Anastasia

    2014-01-01

    Motivated by the cluster structure of two-loop scattering amplitudes in N=4 Yang-Mills theory we define cluster polylogarithm functions. We find that all such functions of weight four are made up of a single simple building block associated with the A 2 cluster algebra. Adding the requirement of locality on generalized Stasheff polytopes, we find that these A 2 building blocks arrange themselves to form a unique function associated with the A 3 cluster algebra. This A 3 function manifests all of the cluster algebraic structure of the two-loop n-particle MHV amplitudes for all n, and we use it to provide an explicit representation for the most complicated part of the n = 7 amplitude as an example. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Cluster algebras in mathematical physics’. (paper)

  6. Connecting Remote Clusters with ATM

    Energy Technology Data Exchange (ETDEWEB)

    Hu, T.C.; Wyckoff, P.S.

    1998-10-01

    Sandia's entry into utilizing clusters of networked workstations is called Computational Plant or CPlant for short. The design of CPlant uses Ethernet to boot the individual nodes, Myrinet to communicate within a node cluster, and ATM to connect between remote clusters. This SAND document covers the work done to enable the use of ATM on the CPlant nodes in the Fall of 1997.

  7. On origin of stellar clusters

    International Nuclear Information System (INIS)

    Tovmasyan, G.M.

    1977-01-01

    The ratios of the gas component of the mass of young stellar clusters to their stellar mass are considered. They change by more than four orders from one cluster to another. The results are in direct contradiction with the hypothesis of formation of cluster stars from a preliminarily existing gas cloud by its condensation, and they favour the Ambartsumian hypothesis of the joint origin of stars and gas clouds from superdense protostellar matter

  8. Random matrix improved subspace clustering

    KAUST Repository

    Couillet, Romain

    2017-03-06

    This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based on vector channel observations in the context of massive MIMO wireless communication networks is provided.

  9. Quantum annealing for combinatorial clustering

    Science.gov (United States)

    Kumar, Vaibhaw; Bass, Gideon; Tomlin, Casey; Dulny, Joseph

    2018-02-01

    Clustering is a powerful machine learning technique that groups "similar" data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between points. The straightforward approach involves examining all the possible assignments of points to each of the clusters. This approach guarantees the solution will be a global minimum; however, the number of possible assignments scales quickly with the number of data points and becomes computationally intractable even for very small datasets. In order to circumvent this issue, cost function minima are found using popular local search-based heuristic approaches such as k-means and hierarchical clustering. Due to their greedy nature, such techniques do not guarantee that a global minimum will be found and can lead to sub-optimal clustering assignments. Other classes of global search-based techniques, such as simulated annealing, tabu search, and genetic algorithms, may offer better quality results but can be too time-consuming to implement. In this work, we describe how quantum annealing can be used to carry out clustering. We map the clustering objective to a quadratic binary optimization problem and discuss two clustering algorithms which are then implemented on commercially available quantum annealing hardware, as well as on a purely classical solver "qbsolv." The first algorithm assigns N data points to K clusters, and the second one can be used to perform binary clustering in a hierarchical manner. We present our results in the form of benchmarks against well-known k-means clustering and discuss the advantages and disadvantages of the proposed techniques.

  10. Electronic and atomic impacts on large clusters

    International Nuclear Information System (INIS)

    Gspann, J.

    1982-01-01

    Describing first the generation and properties of molecular beams of large Van der Waals clusters such as speed distribution, cluster size distribution, and internal temperature of the clusters, the review then features the results of electronic impacts on large clusters: metastable electronic cluster excitations, ejection of positive cluster ions of less than 100 atoms from much larger parent clusters, and ionization of the large clusters. Atomic impacts at thermal energies are treated with respect to the scattering cross section of the clusters, their drag coefficient in free molecular flow, and the peculiarities of impacts on helium clusters of either isotope. (Auth.)

  11. Analysis of genetic association using hierarchical clustering and cluster validation indices.

    Science.gov (United States)

    Pagnuco, Inti A; Pastore, Juan I; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L

    2017-10-01

    It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. BRIGHTEST CLUSTER GALAXIES AND CORE GAS DENSITY IN REXCESS CLUSTERS

    International Nuclear Information System (INIS)

    Haarsma, Deborah B.; Leisman, Luke; Donahue, Megan; Bruch, Seth; Voit, G. Mark; Boehringer, Hans; Pratt, Gabriel W.; Pierini, Daniele; Croston, Judith H.; Arnaud, Monique

    2010-01-01

    We investigate the relationship between brightest cluster galaxies (BCGs) and their host clusters using a sample of nearby galaxy clusters from the Representative XMM-Newton Cluster Structure Survey. The sample was imaged with the Southern Observatory for Astrophysical Research in R band to investigate the mass of the old stellar population. Using a metric radius of 12 h -1 kpc, we found that the BCG luminosity depends weakly on overall cluster mass as L BCG ∝ M 0.18±0.07 cl , consistent with previous work. We found that 90% of the BCGs are located within 0.035 r 500 of the peak of the X-ray emission, including all of the cool core (CC) clusters. We also found an unexpected correlation between the BCG metric luminosity and the core gas density for non-cool-core (non-CC) clusters, following a power law of n e ∝ L 2.7±0.4 BCG (where n e is measured at 0.008 r 500 ). The correlation is not easily explained by star formation (which is weak in non-CC clusters) or overall cluster mass (which is not correlated with core gas density). The trend persists even when the BCG is not located near the peak of the X-ray emission, so proximity is not necessary. We suggest that, for non-CC clusters, this correlation implies that the same process that sets the central entropy of the cluster gas also determines the central stellar density of the BCG, and that this underlying physical process is likely to be mergers.

  13. Quasars in galaxy cluster environments

    International Nuclear Information System (INIS)

    Ellingson, E.

    1989-01-01

    The evolution of radio loud quasars is found to be strongly dependent upon their galaxy cluster environment. Previous studies have shown that bright quasars are found in rich clusters, while high luminosity quasars are found only in poorer environments. The analysis of low luminosity radio quiet quasars indicate that they are never found in rich environments, suggesting that they are a physically different class of objects. Properties of the quasar environment are investigated to determine constraints on the physical mechanisms of quasar formation and evolution. The optical cluster morphology indicates that the cluster cores have smaller radii and higher galaxy densities than are typical for low redshift clusters of similar richness. Radio morphologies may indicate that the formation of a dense intra-cluster medium is associated with the quasars' fading at these epochs. Galaxy colors appear to be normal, but there may be a tendency for clusters associated with high luminosity quasars to contain a higher fraction of gas-rich galaxies than those associated with low luminosity quasars. Multislit spectroscopic observations of galaxies associated with high luminosity quasars indicate that quasars are preferentially located in regions of low relative velocity dispersion, either in rich clusters of abnormally low dispersion, or in poor groups which are dynamically normal. This suggests that galaxy-galaxy interactions may play a role in quasar formation and sustenanace. Virialization of rich clusters and the subsequent increase in galaxy velocities may therefore be responsible for the fading of quasars in rich environments

  14. Anomalous properties of technetium clusters

    International Nuclear Information System (INIS)

    Kryuchkov, S.V.

    1985-01-01

    On the basis of critical evaluation of literature data in the field of chemistry of technetium cluster compounds with ligands of a weak field a conclusion is made on specific, ''anomalous'' properties of technetium cluster complexes which consist in an increased ability of the given element to the formation of a series of binuclear and multinuclear clusters, similar in composition and structure and easily transforming in each other. The majority of technetium clusters unlike similar compounds of other elements are paramagnetic with one unpaired electron on ''metallic'' MO of loosening type. All theoretical conceptions known today on the electronic structure of technetium clusters are considered. It is pointed out, that the best results in the explanation of ''anomalous'' properties of technetium clusters can be obtained in the framework of nonempirical methods of self-consistent field taking into account configuration interactions. It is also shown, that certain properties of technetium clusters can be explained on the basis of qualitative model of Coulomb repulsion of metal atoms in clusters. The conclusion is made, that technetium position in the Periodic table, as well as recently detected technetium property to the decrease of effective charge on its atoms during M-M bond formation promote a high ability of the element to cluster formation both with weak field ligands and with strong field one

  15. Optical properties of cluster plasma

    Energy Technology Data Exchange (ETDEWEB)

    Kishimoto, Yasuaki; Tajima, Toshiki [Japan Atomic Energy Research Inst., Neyagawa, Osaka (Japan). Kansai Research Establishment; Downer, M C

    1998-03-01

    It is shown that unlike a gas plasma or an electron plasma in a metal, an ionized clustered material (`cluster plasma`) permits propagation below the plasma cut-off of electromagnetic (EM) waves whose phase velocity is close to but below the speed of light. This results from the excitation of a plasma oscillation mode (and/or polarization mode) through the cluster surface which does not exist in usual gaseous plasma. The existence of this new optical mode, cluster mode, is confirmed via numerical simulation. (author)

  16. STM observations of ferromagnetic clusters

    International Nuclear Information System (INIS)

    Wawro, A.; Kasuya, A.

    1998-01-01

    Co, Fe and Ni clusters of nanometer size, deposited on silicon and graphite (highly oriented pyrolytic graphite), were observed by a scanning tunneling microscope. Deposition as well as the scanning tunneling microscope measurements were carried out in an ultrahigh vacuum system at room temperature. Detailed analysis of Co cluster height was done with the scanning tunneling microscope equipped with a ferromagnetic tip in a magnetic field up to 70 Oe. It is found that bigger clusters (few nanometers in height) exhibit a dependence of their apparent height on applied magnetic field. We propose that such behaviour originates from the ferromagnetic ordering of cluster and associate this effect to spin polarized tunneling. (author)

  17. Cluster processing business level monitor

    International Nuclear Information System (INIS)

    Muniz, Francisco J.

    2017-01-01

    This article describes a Cluster Processing Monitor. Several applications with this functionality can be freely found doing a search in the Google machine. However, those applications may offer more features that are needed on the Processing Monitor being proposed. Therefore, making the monitor output evaluation difficult to be understood by the user, at-a-glance. In addition, such monitors may add unnecessary processing cost to the Cluster. For these reasons, a completely new Cluster Processing Monitor module was designed and implemented. In the CDTN, Clusters are broadly used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)

  18. Percolation with multiple giant clusters

    International Nuclear Information System (INIS)

    Ben-Naim, E; Krapivsky, P L

    2005-01-01

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

  19. 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.

  20. Integrative cluster analysis in bioinformatics

    CERN Document Server

    Abu-Jamous, Basel; Nandi, Asoke K

    2015-01-01

    Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o

  1. Cluster analysis of track structure

    International Nuclear Information System (INIS)

    Michalik, V.

    1991-01-01

    One of the possibilities of classifying track structures is application of conventional partition techniques of analysis of multidimensional data to the track structure. Using these cluster algorithms this paper attempts to find characteristics of radiation reflecting the spatial distribution of ionizations in the primary particle track. An absolute frequency distribution of clusters of ionizations giving the mean number of clusters produced by radiation per unit of deposited energy can serve as this characteristic. General computation techniques used as well as methods of calculations of distributions of clusters for different radiations are discussed. 8 refs.; 5 figs

  2. Cluster processing business level monitor

    Energy Technology Data Exchange (ETDEWEB)

    Muniz, Francisco J., E-mail: muniz@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

    2017-07-01

    This article describes a Cluster Processing Monitor. Several applications with this functionality can be freely found doing a search in the Google machine. However, those applications may offer more features that are needed on the Processing Monitor being proposed. Therefore, making the monitor output evaluation difficult to be understood by the user, at-a-glance. In addition, such monitors may add unnecessary processing cost to the Cluster. For these reasons, a completely new Cluster Processing Monitor module was designed and implemented. In the CDTN, Clusters are broadly used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)

  3. Statistical measures of galaxy clustering

    International Nuclear Information System (INIS)

    Porter, D.H.

    1988-01-01

    Consideration is given to the large-scale distribution of galaxies and ways in which this distribution may be statistically measured. Galaxy clustering is hierarchical in nature, so that the positions of clusters of galaxies are themselves spatially clustered. A simple identification of groups of galaxies would be an inadequate description of the true richness of galaxy clustering. Current observations of the large-scale structure of the universe and modern theories of cosmology may be studied with a statistical description of the spatial and velocity distributions of galaxies. 8 refs

  4. 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

  5. Russian Pharmaceutical Companies Export Potential in Emerging Regional Clusters

    Directory of Open Access Journals (Sweden)

    Elena Vladimirovna Sapir

    2016-12-01

    Full Text Available This article analyzes a diverse range of the enterprise’s export potential growth factors in emerging pharmaceutical clusters of Central European Russia. Classification and comparative analysis were used to identify export potential attributes (production, finance, labor and marketing, which have allowed to reveal the strong connection of cluster and regional factor groups with the results of export performance. The purpose of the study is to provide exports-seeking pharmaceutical companies with a set of tools to enhance their export potential. The hypothesis that the cumulative impact of the specified attributes leads to the strengthening of pharmaceutical cluster export potential and promotes an effective integration of the region in the world economic space, is developed and tested. The methodology combines the geo-economy-based theory with the theory of clusters competitive advantages. The impacts of export potential growth factors are estimated by using an econometric model based on math statistics. Thus, five Russian regional pharmaceutical clusters (Belgorod, Kaluga, Moscow, Oryol, Yaroslavl are shown. Findings identify an objective causal link between enterprise export potential growth and competitiveness factors of cluster origin (network business chains, production functions interconnectedness and flexibility, production localization. An action plan for the purpose of the maximum use of competitive advantages of the cluster organization for export activities of the entities of the pharmaceutical industry is developed. Conclusions and recommendations of the study are intended to enterprises in pharmaceutical industry and regions’ public authorities, implementing cluster development strategies. It is thus essential to improve marketing and organizational innovations, reduction of commercial expenses under the cluster environment, development of drugs production and delivery chains from R&D to end-users in order to enjoy greater

  6. 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

  7. The Confucian Asian cluster

    Directory of Open Access Journals (Sweden)

    Ionel Sergiu Pirju

    2013-11-01

    Full Text Available The Confucian Asian cluster consists of China, Hong Kong, Japan, Singapore, South Korea, and Taiwan. Confucian tradition countries were defined by achieving a consistent performance in the global economy, they still representing the major competitors in the EU and North American countries. Their progress is defined by a great national management that was able to influence beneficial management systems applied in organizations, these rules characterized by authority; aims to ensure the confidence in business. This article will present the intercultural values characterizing it, the leadership style and also tracing major macroeconomic considerations. The research is synchronic, analysing the contemporary situation of these countries, and the analysis will be interdisciplinary exploratory, identifying specific regional cultural elements.

  8. Dynamics of star clusters

    International Nuclear Information System (INIS)

    Goodman, J.; Hut, P.

    1985-01-01

    The enigma of core collapse receives much attention in this volume. In addition, several observational papers summarize recent techniques and results and discuss the stellar dynamical implications of the enormous progress in the quality of surface photometry, proper motion studies, radial velocity determinations, as well as space-based measurements in a variety of wavelengths. The value of these Proceedings as a standard reference work is enhanced by the inclusion of two appendices, featuring English translations of two seminal papers on stellar dynamics published in Russian and not previously available in a Western language. A third appendix contains an up-to-date catalogue of observationally determined parameters of galactic globular clusters, as well as theoretically inferred parameters. This catalogue will prove to be an essential reference for phenomenonological studies and an ideal testing ground for new theoretical developments. (orig.)

  9. Performance criteria for graph clustering and Markov cluster experiments

    NARCIS (Netherlands)

    S. van Dongen

    2000-01-01

    textabstractIn~[1] a cluster algorithm for graphs was introduced called the Markov cluster algorithm or MCL~algorithm. The algorithm is based on simulation of (stochastic) flow in graphs by means of alternation of two operators, expansion and inflation. The results in~[2] establish an intrinsic

  10. 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.

  11. Herd Clustering: A synergistic data clustering approach using collective intelligence

    KAUST Repository

    Wong, Kachun

    2014-10-01

    Traditional data mining methods emphasize on analytical abilities to decipher data, assuming that data are static during a mining process. We challenge this assumption, arguing that we can improve the analysis by vitalizing data. In this paper, this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances are represented by moving particles. Particles attract each other locally and form clusters by themselves as shown in the case studies reported. To demonstrate its effectiveness, the performance of HC is compared to other state-of-the art clustering methods on more than thirty datasets using four performance metrics. An application for DNA motif discovery is also conducted. The results support the effectiveness of HC and thus the underlying philosophy. © 2014 Elsevier B.V.

  12. Tool path in torus tool CNC machining

    Directory of Open Access Journals (Sweden)

    XU Ying

    2016-10-01

    Full Text Available This paper is about tool path in torus tool CNC machining.The mathematical model of torus tool is established.The tool path planning algorithm is determined through calculation of the cutter location,boundary discretization,calculation of adjacent tool path and so on,according to the conversion formula,the cutter contact point will be converted to the cutter location point and then these points fit a toolpath.Lastly,the path planning algorithm is implemented by using Matlab programming.The cutter location points for torus tool are calculated by Matlab,and then fit these points to a toolpath.While using UG software,another tool path of free surface is simulated of the same data.It is drew compared the two tool paths that using torus tool is more efficient.

  13. Clustering of experimental data and its application to nuclear data evaluation

    International Nuclear Information System (INIS)

    Abboud, A.; Rashed, R.; Ibrahim, M.

    1998-01-01

    A semi-automatic pre-processing technique has been proposed by Iwasaki to classify the experimental data for a reaction into one or a small number of large data groups, called main cluster (s), and to eliminate some data which deviates from the main body of the data. The classifying method is based on technique like pattern clustering in the information processing domain. Test of the data clustering formed reasonable main clusters for three activation cross-sections. This technique is a helpful tool in the neutron cross-section evaluation

  14. jClustering, an open framework for the development of 4D clustering algorithms.

    Directory of Open Access Journals (Sweden)

    José María Mateos-Pérez

    Full Text Available We present jClustering, an open framework for the design of clustering algorithms in dynamic medical imaging. We developed this tool because of the difficulty involved in manually segmenting dynamic PET images and the lack of availability of source code for published segmentation algorithms. Providing an easily extensible open tool encourages publication of source code to facilitate the process of comparing algorithms and provide interested third parties with the opportunity to review code. The internal structure of the framework allows an external developer to implement new algorithms easily and quickly, focusing only on the particulars of the method being implemented and not on image data handling and preprocessing. This tool has been coded in Java and is presented as an ImageJ plugin in order to take advantage of all the functionalities offered by this imaging analysis platform. Both binary packages and source code have been published, the latter under a free software license (GNU General Public License to allow modification if necessary.

  15. The Nordic Mobile Telecommunication Cluster

    DEFF Research Database (Denmark)

    Jørgensen, Ulrik

    2000-01-01

    A study of the historic role of the Nordic mobile telephone and telecommunications cluster and its background in both coordinated innovation policies and societal developments in Scandinavia.......A study of the historic role of the Nordic mobile telephone and telecommunications cluster and its background in both coordinated innovation policies and societal developments in Scandinavia....

  16. Yellow supergiants in open clusters

    International Nuclear Information System (INIS)

    Sowell, J.R.

    1986-01-01

    Superluminous giant stars (SLGs) have been reported in young globular clusters in the Large Magellanic Cloud (LMC). These stars appear to be in the post-asymptotic-giant-branch phase of evolution. This program was an investigation of galactic SLG candidates in open clusters, which are more like the LMC young globular clusters. These were chosen because luminosity, mass, and age determinations can be made for members since cluster distances and interstellar reddenings are known. Color magnitude diagrams were searched for candidates, using the same selection criteria as for SLGs in the LMC. Classification spectra were obtained of 115 program stars from McGraw-Hill Observatory and of 68 stars from Cerro Tololo Inter-American Observatory Chile. These stars were visually classified on the MK system using spectral scans of standard stars taken at the respective observations. Published information was combined with this program's data for 83 stars in 30 clusters. Membership probabilities were assigned to these stars, and the clusters were analyzed according to age. It was seen that the intrinsically brightest supergiants are found in the youngest clusters. With increasing cluster age, the absolute luminosities attained by the supergiants decline. Also, it appears that the evolutionary tracks of luminosity class II stars are more similar to those of class I than of class III

  17. Supersonic bare metal cluster beams

    International Nuclear Information System (INIS)

    Smalley, R.E.

    1991-01-01

    Progress continued this past year on two principal fronts in the study of bare metal clusters: photoelectron spectroscopy of mass selected negative ions, and surface chemisorption of cluster ions levitated in a superconducting magnet as monitored by fourier transform ion cyclotron resonance

  18. Two generalizations of Kohonen clustering

    Science.gov (United States)

    Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.

    1993-01-01

    The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

  19. Variation in verb cluster interruption

    NARCIS (Netherlands)

    Hendriks, Lotte

    2014-01-01

    Except for finite verbs in main clauses, verbs in Standard Dutch cluster together in a clause-final position. In certain Dutch dialects, non-verbal material can occur within this verb cluster (Verhasselt 1961; Koelmans 1965, among many others). These dialects vary with respect to which types of

  20. Chemical exposure and leukemia clusters

    International Nuclear Information System (INIS)

    Cartwright, R.A.

    1992-01-01

    This paper draws attention to the heterogeneous distribution of leukemia in childhood and in adults. The topic of cluster reports and generalized clustering is addressed. These issues are applied to what is known of the risk factor for both adult and childhood leukemia. Finally, the significance of parental occupational exposure and childhood leukemia is covered. (author). 23 refs

  1. Evaporation rate of nucleating clusters.

    Science.gov (United States)

    Zapadinsky, Evgeni

    2011-11-21

    The Becker-Döring kinetic scheme is the most frequently used approach to vapor liquid nucleation. In the present study it has been extended so that master equations for all cluster configurations are included into consideration. In the Becker-Döring kinetic scheme the nucleation rate is calculated through comparison of the balanced steady state and unbalanced steady state solutions of the set of kinetic equations. It is usually assumed that the balanced steady state produces equilibrium cluster distribution, and the evaporation rates are identical in the balanced and unbalanced steady state cases. In the present study we have shown that the evaporation rates are not identical in the equilibrium and unbalanced steady state cases. The evaporation rate depends on the number of clusters at the limit of the cluster definition. We have shown that the ratio of the number of n-clusters at the limit of the cluster definition to the total number of n-clusters is different in equilibrium and unbalanced steady state cases. This causes difference in evaporation rates for these cases and results in a correction factor to the nucleation rate. According to rough estimation it is 10(-1) by the order of magnitude and can be lower if carrier gas effectively equilibrates the clusters. The developed approach allows one to refine the correction factor with Monte Carlo and molecular dynamic simulations.

  2. A cluster algorithm for graphs

    NARCIS (Netherlands)

    S. van Dongen

    2000-01-01

    textabstractA cluster algorithm for graphs called the emph{Markov Cluster algorithm (MCL~algorithm) is introduced. The algorithm provides basically an interface to an algebraic process defined on stochastic matrices, called the MCL~process. The graphs may be both weighted (with nonnegative weight)

  3. 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)

  4. ANALYSIS OF DEVELOPING BATIK INDUSTRY CLUSTER IN BAKARAN VILLAGE CENTRAL JAVA PROVINCE

    Directory of Open Access Journals (Sweden)

    Hermanto Hermanto

    2017-06-01

    Full Text Available SMEs grow in a cluster in a certain geographical area. The entrepreneurs grow and thrive through the business cluster. Central Java Province has a lot of business clusters in improving the regional economy, one of which is batik industry cluster. Pati Regency is one of regencies / city in Central Java that has the lowest turnover. Batik industy cluster in Pati develops quite well, which can be seen from the increasing number of batik industry incorporated in the cluster. This research examines the strategy of developing the batik industry cluster in Pati Regency. The purpose of this research is to determine the proper strategy for developing the batik industry clusters in Pati. The method of research is quantitative. The analysis tool of this research is the Strengths, Weakness, Opportunity, Threats (SWOT analysis. The result of SWOT analysis in this research shows that the proper strategy for developing the batik industry cluster in Pati is optimizing the management of batik business cluster in Bakaran Village; the local government provides information of the facility of business capital loans; the utilization of labors from Bakaran Village while improving the quality of labors by training, and marketing the Bakaran batik to the broader markets while maintaining the quality of batik. Advice that can be given from this research is that the parties who have a role in batik industry cluster development in Bakaran Village, Pati Regency, such as the Local Government.

  5. RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

    Science.gov (United States)

    Castro-Mondragon, Jaime Abraham; Jaeger, Sébastien; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

    2017-07-27

    Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

    Directory of Open Access Journals (Sweden)

    Tushar H Jaware

    2013-10-01

    Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

  7. Using Vega Linux Cluster at Reactor Physics Dept

    International Nuclear Information System (INIS)

    Zefran, B.; Jeraj, R.; Skvarc, J.; Glumac, B.

    1999-01-01

    Experience using a Linux-based cluster for the reactor physics calculations are presented in this paper. Special attention is paid to the MCNP code in this environment and to practical guidelines how to prepare and use the paralel version of the code. Our results of a time comparison study are presented for two sets of inputs. The results are promising and speedup factor achieved on the Linux cluster agrees with previous tests on other parallel systems. We also tested tools for parallelization of other programs used at our Dept..(author)

  8. Clustering-based approaches to SAGE data mining

    Directory of Open Access Journals (Sweden)

    Wang Haiying

    2008-07-01

    Full Text Available Abstract Serial analysis of gene expression (SAGE is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the prediction of new gene functions and the identification of biomarkers in human cancer research. Clustering techniques have become fundamental approaches in these applications. This paper reviews relevant clustering techniques specifically designed for this type of data. It places an emphasis on current limitations and opportunities in this area for supporting biologically-meaningful data mining and visualisation.

  9. nIFTy galaxy cluster simulations II: radiative models

    CSIR Research Space (South Africa)

    Sembolini, F

    2016-04-01

    Full Text Available Valerio 2, I-34127 Trieste, Italy 12Physics Department, University of the Western Cape, Cape Town 7535, Sotuh Africa 13Physics Department, University of Western Cape, Bellville, Cape Town 7535, South Africa 14South African Astronomical Observatory, PO Box...IFTy cluster comparison project (Sembolini et al., 2015): a study of the latest state-of- the-art hydrodynamical codes using simulated galaxy clusters as a testbed for theories of galaxy formation. Simulations are indis- pensable tools in the interpretation...

  10. Cluster mislocation in kinematic Sunyaev-Zel'dovich effect extraction

    Science.gov (United States)

    Calafut, Victoria; Bean, Rachel; Yu, Byeonghee

    2017-12-01

    We investigate the impact of a variety of analysis assumptions that influence cluster identification and location on the kinematic Sunyaev-Zel'dovich (kSZ) pairwise momentum signal and covariance estimation. Photometric and spectroscopic galaxy tracers from SDSS, WISE, and DECaLs, spanning redshifts 0.05 surveys the statistical and photometric errors will shrink markedly. Our results demonstrate that uncertainties introduced through using galaxy proxies for cluster locations will need to be fully incorporated, and actively mitigated, for the kSZ to reach its full potential as a cosmological constraining tool for dark energy and neutrino physics.

  11. Dynamics of cluster structures in a financial market network

    Science.gov (United States)

    Kocheturov, Anton; Batsyn, Mikhail; Pardalos, Panos M.

    2014-11-01

    In the course of recent fifteen years the network analysis has become a powerful tool for studying financial markets. In this work we analyze stock markets of the USA and Sweden. We study cluster structures of a market network constructed from a correlation matrix of returns of the stocks traded in each of these markets. Such cluster structures are obtained by means of the P-Median Problem (PMP) whose objective is to maximize the total correlation between a set of stocks called medians of size p and other stocks. Every cluster structure is an undirected disconnected weighted graph in which every connected component (cluster) is a star, or a tree with one central node (called a median) and several leaf nodes connected with the median by weighted edges. Our main observation is that in non-crisis periods of time cluster structures change more chaotically, while during crises they show more stable behavior and fewer changes. Thus an increasing stability of a market graph cluster structure obtained via the PMP could be used as an indicator of a coming crisis.

  12. Filaments and clusters of galaxies

    International Nuclear Information System (INIS)

    Soltan, A.

    1987-01-01

    A statistical test to investigate filaments of galaxies is performed. Only particular form of filaments is considered, viz. filaments connecting Abell clusters of galaxies. Relative position of triplets ''cluster - field object - cluster'' is analysed. Though neither cluster sample nor field object sample are homogeneous and complete only peculiar form of selection effects could affect the present statistics. Comparison of observational data with simulations shows that less than 15 per cent of all field galaxies is concentrated in filaments connecting rich clusters. Most of the field objects used in the analysis are not normal galaxies and it is possible that this conclusion is not in conflict with apparent filaments seen in the Lick counts and in some nearby 3D maps of the galaxy distribution. 26 refs., 2 figs. (author)

  13. Radio investigations of clusters of galaxies

    International Nuclear Information System (INIS)

    Valentijn, E.A.

    1978-01-01

    This thesis contains a number of papers of the series entitled, A Westerbork Survey of Rich Clusters of Galaxies. The primary aim was to study the radio characteristics of cluster galaxies and especially the question whether their ''radio-activity'' is influenced by their location inside a cluster. It is enquired whether the presence of an intra-cluster medium (ICM), or the typical cluster evolution or cluster dynamical processes can give rise to radio-observable effects on the behaviour of cluster galaxies. 610 MHz WSRT observations of the Coma cluster (and radio observations of the Hercules supercluster) are presented. Extended radio sources in Abell clusters are then described. (Auth.)

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  15. Useful design tools?

    DEFF Research Database (Denmark)

    Jensen, Jesper Ole

    2005-01-01

    vague and contested concept of sustainability into concrete concepts and building projects. It describes a typology of tools: process tools, impact assessment tools, multi-criteria tools and tools for monitoring. It includes a Danish paradigmatic case study of stakeholder participation in the planning...... of a new sustainable settlement. The use of design tools is discussed in relation to innovation and stakeholder participation, and it is stressed that the usefulness of design tools is context dependent....

  16. A Linear Algebra Measure of Cluster Quality.

    Science.gov (United States)

    Mather, Laura A.

    2000-01-01

    Discussion of models for information retrieval focuses on an application of linear algebra to text clustering, namely, a metric for measuring cluster quality based on the theory that cluster quality is proportional to the number of terms that are disjoint across the clusters. Explains term-document matrices and clustering algorithms. (Author/LRW)

  17. Information Clustering Based on Fuzzy Multisets.

    Science.gov (United States)

    Miyamoto, Sadaaki

    2003-01-01

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

  18. CoC GIS Tools (GIS Tool)

    Data.gov (United States)

    Department of Housing and Urban Development — This tool provides a no-cost downloadable software tool that allows users to interact with professional quality GIS maps. Users access pre-compiled projects through...

  19. 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

  20. ClusterSignificance: A bioconductor package facilitating statistical analysis of class cluster separations in dimensionality reduced data

    DEFF Research Database (Denmark)

    Serviss, Jason T.; Gådin, Jesper R.; Eriksson, Per

    2017-01-01

    , e.g. genes in a specific pathway, alone can separate samples into these established classes. Despite this, the evaluation of class separations is often subjective and performed via visualization. Here we present the ClusterSignificance package; a set of tools designed to assess the statistical...... significance of class separations downstream of dimensionality reduction algorithms. In addition, we demonstrate the design and utility of the ClusterSignificance package and utilize it to determine the importance of long non-coding RNA expression in the identity of multiple hematological malignancies....

  1. From superdeformation to clusters

    International Nuclear Information System (INIS)

    Betts, R.R.

    1992-01-01

    Much of the discussion at this conference has centered on the topic of superdeformed states in nuclei, and their study with the exquisitely precise tool of gamma ray spectroscopy, carried out with state-of-the-art detector arrays. In the usual way in which superdeformed states are populated, via compound nucleus formation and evaporation, gamma decay is the last process to occur in the decay chain. In some other sense, it is also the last to occur in the meaning of least likely

  2. A note on the kappa statistic for clustered dichotomous data.

    Science.gov (United States)

    Zhou, Ming; Yang, Zhao

    2014-06-30

    The kappa statistic is widely used to assess the agreement between two raters. Motivated by a simulation-based cluster bootstrap method to calculate the variance of the kappa statistic for clustered physician-patients dichotomous data, we investigate its special correlation structure and develop a new simple and efficient data generation algorithm. For the clustered physician-patients dichotomous data, based on the delta method and its special covariance structure, we propose a semi-parametric variance estimator for the kappa statistic. An extensive Monte Carlo simulation study is performed to evaluate the performance of the new proposal and five existing methods with respect to the empirical coverage probability, root-mean-square error, and average width of the 95% confidence interval for the kappa statistic. The variance estimator ignoring the dependence within a cluster is generally inappropriate, and the variance estimators from the new proposal, bootstrap-based methods, and the sampling-based delta method perform reasonably well for at least a moderately large number of clusters (e.g., the number of clusters K ⩾50). The new proposal and sampling-based delta method provide convenient tools for efficient computations and non-simulation-based alternatives to the existing bootstrap-based methods. Moreover, the new proposal has acceptable performance even when the number of clusters is as small as K = 25. To illustrate the practical application of all the methods, one psychiatric research data and two simulated clustered physician-patients dichotomous data are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.

  3. More Planets in the Hyades Cluster

    Science.gov (United States)

    Kohler, Susanna

    2017-12-01

    A few weeks ago, Astrobites reported on a Neptune-sized planet discovered orbiting a star in the Hyades cluster. A separate study submitted at the same time, however, reveals that there may be even more planets lurking in this system.Thanks, KeplerArtists impression of the Kepler spacecraft and the mapping of the fields of the current K2 mission. [NASA]As we learn about the formation and evolution of planets outside of our own solar system, its important that we search for planets throughout different types of star clusters; observing both old and young clusters, for instance, can tell us about planets in different stages of their evolutionary histories. Luckily for us, we have a tool that has been doing exactly this: the Kepler mission.In true holiday spirit, Kepler is the gift that just keeps on giving. Though two of its reaction wheels have failed, Kepler now as its reincarnation, K2 just keeps detecting more planet transits. Whats more, detailed analysis of past Kepler/K2 data with ever more powerful techniques as well as the addition of high-precision parallaxes for stars from Gaia in the near future ensures that the Kepler data set will continue to reveal new exoplanet transits for many years to come.Image of the Hyades cluster, a star cluster that is only 800 million years old. [NASA/ESA/STScI]Hunting in the Young HyadesTwo studies using K2 data were recently submitted on exoplanet discoveries around EPIC 247589423 in the Hyades cluster, a nearby star cluster that is only 800 million years old. Astrobites reported on the first study in October and discussed details about the newly discovered mini-Neptune presented in that study.The second study, led by Andrew Mann (University of Texas at Austin and NASA Hubble Fellow at Columbia University), was published this week. This study presented a slightly different outcome: the authors detect the presence of not just the one, but three exoplanets orbiting EPIC 247589423.New DiscoveriesMann and collaborators searched

  4. Cluster Correlation in Mixed Models

    Science.gov (United States)

    Gardini, A.; Bonometto, S. A.; Murante, G.; Yepes, G.

    2000-10-01

    We evaluate the dependence of the cluster correlation length, rc, on the mean intercluster separation, Dc, for three models with critical matter density, vanishing vacuum energy (Λ=0), and COBE normalization: a tilted cold dark matter (tCDM) model (n=0.8) and two blue mixed models with two light massive neutrinos, yielding Ωh=0.26 and 0.14 (MDM1 and MDM2, respectively). All models approach the observational value of σ8 (and hence the observed cluster abundance) and are consistent with the observed abundance of damped Lyα systems. Mixed models have a motivation in recent results of neutrino physics; they also agree with the observed value of the ratio σ8/σ25, yielding the spectral slope parameter Γ, and nicely fit Las Campanas Redshift Survey (LCRS) reconstructed spectra. We use parallel AP3M simulations, performed in a wide box (of side 360 h-1 Mpc) and with high mass and distance resolution, enabling us to build artificial samples of clusters, whose total number and mass range allow us to cover the same Dc interval inspected through Automatic Plate Measuring Facility (APM) and Abell cluster clustering data. We find that the tCDM model performs substantially better than n=1 critical density CDM models. Our main finding, however, is that mixed models provide a surprisingly good fit to cluster clustering data.

  5. Fission of Polyanionic Metal Clusters

    Science.gov (United States)

    König, S.; Jankowski, A.; Marx, G.; Schweikhard, L.; Wolfram, M.

    2018-04-01

    Size-selected dianionic lead clusters Pbn2 -, n =34 - 56 , are stored in a Penning trap and studied with respect to their decay products upon photoexcitation. Contrary to the decay of other dianionic metal clusters, these lead clusters show a variety of decay channels. The mass spectra of the fragments are compared to the corresponding spectra of the monoanionic precursors. This comparison leads to the conclusion that, in the cluster size region below about n =48 , the fission reaction Pbn2 -→Pbn-10 -+Pb10- is the major decay process. Its disappearance at larger cluster sizes may be an indication of a nonmetal to metal transition. Recently, the pair of Pb10- and Pbn-10 - were observed as pronounced fragments in electron-attachment studies [S. König et al., Int. J. Mass Spectrom. 421, 129 (2017), 10.1016/j.ijms.2017.06.009]. The present findings suggest that this combination is the fingerprint of the decay of doubly charged lead clusters. With this assumption, the dianion clusters have been traced down to Pb212 -, whereas the smallest size for the direct observation was as high as n =28 .

  6. A possibilistic approach to clustering

    Science.gov (United States)

    Krishnapuram, Raghu; Keller, James M.

    1993-01-01

    Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

  7. 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.

  8. THE EXTENDED VIRGO CLUSTER CATALOG

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Suk; Rey, Soo-Chang; Lee, Youngdae; Chung, Jiwon; Pak, Mina; Yi, Wonhyeong; Lee, Woong [Department of Astronomy and Space Science, Chungnam National University, 99 Daehak-ro, Daejeon 305-764 (Korea, Republic of); Jerjen, Helmut [Research School of Astronomy and Astrophysics, The Australian National University, Cotter Road, Weston, ACT 2611 (Australia); Lisker, Thorsten [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg (ZAH), Mönchhofstraße 12-14, D-69120 Heidelberg (Germany); Sung, Eon-Chang [Korea Astronomy and Space Science institute, 776 Daedeokdae-ro, Daejeon 305-348 (Korea, Republic of)

    2015-01-01

    We present a new catalog of galaxies in the wider region of the Virgo cluster, based on the Sloan Digital Sky Survey (SDSS) Data Release 7. The Extended Virgo Cluster Catalog (EVCC) covers an area of 725 deg{sup 2} or 60.1 Mpc{sup 2}. It is 5.2 times larger than the footprint of the classical Virgo Cluster Catalog (VCC) and reaches out to 3.5 times the virial radius of the Virgo cluster. We selected 1324 spectroscopically targeted galaxies with radial velocities less than 3000 km s{sup –1}. In addition, 265 galaxies that have been overlooked in the SDSS spectroscopic survey but have available redshifts in the NASA Extragalactic Database are also included. Our selection process secured a total of 1589 galaxies, 676 of which are not included in the VCC. The certain and possible cluster members are defined by means of redshift comparison with a cluster infall model. We employed two independent and complementary galaxy classification schemes: the traditional morphological classification based on the visual inspection of optical images and a characterization of galaxies from their spectroscopic features. SDSS u, g, r, i, and z passband photometry of all EVCC galaxies was performed using Source Extractor. We compare the EVCC galaxies with the VCC in terms of morphology, spatial distribution, and luminosity function. The EVCC defines a comprehensive galaxy sample covering a wider range in galaxy density that is significantly different from the inner region of the Virgo cluster. It will be the foundation for forthcoming galaxy evolution studies in the extended Virgo cluster region, complementing ongoing and planned Virgo cluster surveys at various wavelengths.

  9. Haplotyping Problem, A Clustering Approach

    International Nuclear Information System (INIS)

    Eslahchi, Changiz; Sadeghi, Mehdi; Pezeshk, Hamid; Kargar, Mehdi; Poormohammadi, Hadi

    2007-01-01

    Construction of two haplotypes from a set of Single Nucleotide Polymorphism (SNP) fragments is called haplotype reconstruction problem. One of the most popular computational model for this problem is Minimum Error Correction (MEC). Since MEC is an NP-hard problem, here we propose a novel heuristic algorithm based on clustering analysis in data mining for haplotype reconstruction problem. Based on hamming distance and similarity between two fragments, our iterative algorithm produces two clusters of fragments; then, in each iteration, the algorithm assigns a fragment to one of the clusters. Our results suggest that the algorithm has less reconstruction error rate in comparison with other algorithms

  10. Supersymmetry for nuclear cluster systems

    International Nuclear Information System (INIS)

    Levai, G.; Cseh, J.; Van Isacker, P.

    2001-01-01

    A supersymmetry scheme is proposed for nuclear cluster systems. The bosonic sector of the superalgebra describes the relative motion of the clusters, while its fermionic sector is associated with their internal structure. An example of core+α configurations is discussed in which the core is a p-shell nucleus and the underlying superalgebra is U(4/12). The α-cluster states of the nuclei 20 Ne and 19 F are analysed and correlations between their spectra, electric quadrupole transitions, and one-nucleon transfer reactions are interpreted in terms of U(4/12) supersymmetry. (author)

  11. Implementation of a cluster Beowulf

    International Nuclear Information System (INIS)

    Victorino Guzman, Jorge Enrique

    2001-01-01

    One of the simulation systems that put a great stress on computational resources and performance are the climatic models, with a high cost of implementation, making difficult its acquisition. An alternative that offers good performance at a reasonable cost is the construction of Cluster Beowulf that allows to emulate the behaviour of a computer with several processors. In the present article we discuss the requirements of hardware for the construction of the Cluster Beowulf, the software resources for the implementation of the model CCM3.6 and the performance of the Cluster Beowulf, of the Group of Investigation in Meteorology at the National University of Colombia, with different number of processors

  12. A Clustering Graph Generator

    Energy Technology Data Exchange (ETDEWEB)

    Winlaw, Manda [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); De Sterck, Hans [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoffrey [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-26

    In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps to understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.

  13. Re-estimating sample size in cluster randomized trials with active recruitment within clusters

    NARCIS (Netherlands)

    van Schie, Sander; Moerbeek, Mirjam

    2014-01-01

    Often only a limited number of clusters can be obtained in cluster randomised trials, although many potential participants can be recruited within each cluster. Thus, active recruitment is feasible within the clusters. To obtain an efficient sample size in a cluster randomised trial, the cluster

  14. Clusters and how to make it work : toolkit for cluster strategy

    NARCIS (Netherlands)

    Manickam, Anu; van Berkel, Karel

    2013-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  15. 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...

  16. The power tool

    International Nuclear Information System (INIS)

    HAYFIELD, J.P.

    1999-01-01

    POWER Tool--Planning, Optimization, Waste Estimating and Resourcing tool, a hand-held field estimating unit and relational database software tool for optimizing disassembly and final waste form of contaminated systems and equipment

  17. Installing, Running and Maintaining Large Linux Clusters at CERN

    CERN Document Server

    Bahyl, V; van Eldik, Jan; Fuchs, Ulrich; Kleinwort, Thorsten; Murth, Martin; Smith, Tim; Bahyl, Vladimir; Chardi, Benjamin; Eldik, Jan van; Fuchs, Ulrich; Kleinwort, Thorsten; Murth, Martin; Smith, Tim

    2003-01-01

    Having built up Linux clusters to more than 1000 nodes over the past five years, we already have practical experience confronting some of the LHC scale computing challenges: scalability, automation, hardware diversity, security, and rolling OS upgrades. This paper describes the tools and processes we have implemented, working in close collaboration with the EDG project [1], especially with the WP4 subtask, to improve the manageability of our clusters, in particular in the areas of system installation, configuration, and monitoring. In addition to the purely technical issues, providing shared interactive and batch services which can adapt to meet the diverse and changing requirements of our users is a significant challenge. We describe the developments and tuning that we have introduced on our LSF based systems to maximise both responsiveness to users and overall system utilisation. Finally, this paper will describe the problems we are facing in enlarging our heterogeneous Linux clusters, the progress we have ...

  18. CLUSTER ANALYSIS UKRAINIAN REGIONAL DISTRIBUTION BY LEVEL OF INNOVATION

    Directory of Open Access Journals (Sweden)

    Roman Shchur

    2016-07-01

    Full Text Available   SWOT-analysis of the threats and benefits of innovation development strategy of Ivano-Frankivsk region in the context of financial support was сonducted. Methodical approach to determine of public-private partnerships potential that is tool of innovative economic development financing was identified. Cluster analysis of possibilities of forming public-private partnership in a particular region was carried out. Optimal set of problem areas that require urgent solutions and financial security is defined on the basis of cluster approach. It will help to form practical recommendations for the formation of an effective financial mechanism in the regions of Ukraine. Key words: the mechanism of innovation development financial provision, innovation development, public-private partnerships, cluster analysis, innovative development strategy.

  19. Intracluster light at the Frontier - II. The Frontier Fields Clusters

    Science.gov (United States)

    Montes, Mireia; Trujillo, Ignacio

    2018-02-01

    Multiwavelength deep observations are a key tool to understand the origin of the diffuse light in clusters of galaxies: the intracluster light (ICL). For this reason, we take advantage of the Hubble Frontier Fields (HFF) survey to investigate the properties of the stellar populations of the ICL of its six massive intermediate redshift (0.3 1015 M⊙) clusters is formed by the stripping of MW-like objects that have been accreted at z < 1, in agreement with current simulations. We do not find any significant increase in the fraction of light of the ICL with cosmic time, although the redshift range explored is narrow to derive any strong conclusion. When exploring the slope of the stellar mass density profile, we found that the ICL of the HFF clusters follows the shape of their underlying dark matter haloes, in agreement with the idea that the ICL is the result of the stripping of galaxies at recent times.

  20. The neutron porosity tool

    International Nuclear Information System (INIS)

    Oelgaard, P.L.

    1988-01-01

    The report contains a review of available information on neutron porosity tools with the emphasis on dual thermal-neutron-detector porosity tools and epithermal-neutron-detector porosity tools. The general principle of such tools is discussed and theoretical models are very briefly reviewed. Available data on tool designs are summarized with special regard to the source-detector distance. Tool operational data, porosity determination and correction of measurements are briefly discussed. (author) 15 refs

  1. Preset pivotal tool holder

    Science.gov (United States)

    Asmanes, Charles

    1979-01-01

    A tool fixture is provided for precise pre-alignment of a radiused edge cutting tool in a tool holder relative to a fixed reference pivot point established on said holder about which the tool holder may be selectively pivoted relative to the fixture base member to change the contact point of the tool cutting edge with a workpiece while maintaining the precise same tool cutting radius relative to the reference pivot point.

  2. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Support Distribution Machines

    Science.gov (United States)

    Ntampaka, Michelle; Trac, Hy; Sutherland, Dougal; Fromenteau, Sebastien; Poczos, Barnabas; Schneider, Jeff

    2018-01-01

    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership infor- mation and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width E=0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (E=2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement (E=0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncon- taminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

  3. Noninvasive neuromodulation in cluster headache

    DEFF Research Database (Denmark)

    Láinez, Miguel J A; Jensen, Rigmor

    2015-01-01

    PURPOSE OF REVIEW: Neuromodulation is an alternative in the management of medically intractable cluster headache patients. Most of the techniques are invasive, but in the last 2 years, some studies using a noninvasive device have been presented. The objective of this article is to review the data...... using this approach. RECENT FINDINGS: Techniques as occipital nerve stimulation or sphenopalatine ganglion stimulation are recommended as first-line therapy in refractory cluster patients, but they are invasive and maybe associated with complications. Noninvasive vagal nerve stimulation with an external...... device has been tried in cluster patients. Results from clinical practice and a single randomized clinical trial have been presented showing a reduction of the number of cluster attacks/week in the patients treated with the device. The rate of adverse events was low and most of them were mild. SUMMARY...

  4. Clustering of financial time series

    Science.gov (United States)

    D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

    2013-05-01

    This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

  5. Infrared spectroscopy of ionic clusters

    International Nuclear Information System (INIS)

    Price, J.M.

    1990-11-01

    This thesis describes new experiments wherein the infrared vibrational predissociation spectra of a number of mass-selected ionic cluster systems have been obtained and analyzed in the 2600 to 4000 cm -1 region. The species studied include: the hydrated hydronium ions, H 3 O + (H 2 O) 3 -10 , ammoniated ammonium ions, NH 4 + (NH 3 ) 1 -10 and cluster ions involving both water and ammonia around an ammonium ion core, (mixed clusters) NH 4 + (NH 3 ) n (H 2 O) m (n+m=4). In each case, the spectra reveal well resolved structures that can be assigned to transitions arising from the vibrational motions of both the ion core of the clusters and the surrounding neutral solvent molecules. 154 refs., 19 figs., 8 tabs

  6. Computer simulation of defect cluster

    Energy Technology Data Exchange (ETDEWEB)

    Kuramoto, Eiichi [Kyushu Univ., Kasuga, Fukuoka (Japan). Research Inst. for Applied Mechanics

    1996-04-01

    In order to elucidate individual element process of various defects and defect clusters of used materials under irradiation environments, interatomic potential with reliability was investigated. And for comparison with experimental results, it is often required to adopt the temperature effect and to investigate in details mechanism of one dimensional motion of micro conversion loop and so forth using the molecular dynamic (MD) method. Furthermore, temperature effect is also supposed for stable structure of defects and defect clusters, and many problems relating to alloy element are also remained. And, simulation on photon life at the defects and defect clusters thought to be important under comparison with equipment can also be supposed an improvement of effectiveness due to relation to theses products. In this paper, some topics in such flow was extracted to explain them. In particular, future important problems will be potential preparation of alloy, structure, dynamic behavior and limited temperature of intralattice atomic cluster. (G.K.)

  7. Transformation kinetics for nucleus clusters

    International Nuclear Information System (INIS)

    Villa, Elena; Rios, Paulo R.

    2009-01-01

    A rigorous mathematical approach based on stochastic geometry concepts is presented to extend previous Johnson-Mehl, Avrami, Kolmogorov treatment of transformation kinetics to situations in which nuclei are not homogeneously located in space but are located in clusters. An exact analytical solution is presented here for the first time assuming that nucleation sites follow a Matern cluster process. The influence of Matern cluster process parameters on subsequent growth kinetics and the microstructural path are illustrated by means of numerical examples. Moreover, using the superposition principle, exact analytical solutions are also obtained when nucleation takes place by a combination of a Matern cluster process and an inhomogeneous Poisson point process. The new solutions presented here significantly increase the number of exactly solvable cases available to formal kinetics.

  8. Infrared spectroscopy of ionic clusters

    Energy Technology Data Exchange (ETDEWEB)

    Price, J.M. (California Univ., Berkeley, CA (USA). Dept. of Chemistry Lawrence Berkeley Lab., CA (USA))

    1990-11-01

    This thesis describes new experiments wherein the infrared vibrational predissociation spectra of a number of mass-selected ionic cluster systems have been obtained and analyzed in the 2600 to 4000 cm{sup {minus}1} region. The species studied include: the hydrated hydronium ions, H{sub 3}O{sup +} (H{sub 2}O){sub 3 {minus}10}, ammoniated ammonium ions, NH{sub 4}{sup +}(NH{sub 3}){sub 1 {minus}10} and cluster ions involving both water and ammonia around an ammonium ion core, (mixed clusters) NH{sub 4}{sup +}(NH{sub 3}){sub n}(H{sub 2}O){sub m} (n+m=4). In each case, the spectra reveal well resolved structures that can be assigned to transitions arising from the vibrational motions of both the ion core of the clusters and the surrounding neutral solvent molecules. 154 refs., 19 figs., 8 tabs.

  9. Cluster randomization and political philosophy.

    Science.gov (United States)

    Chwang, Eric

    2012-11-01

    In this paper, I will argue that, while the ethical issues raised by cluster randomization can be challenging, they are not new. My thesis divides neatly into two parts. In the first, easier part I argue that many of the ethical challenges posed by cluster randomized human subjects research are clearly present in other types of human subjects research, and so are not novel. In the second, more difficult part I discuss the thorniest ethical challenge for cluster randomized research--cases where consent is genuinely impractical to obtain. I argue that once again these cases require no new analytic insight; instead, we should look to political philosophy for guidance. In other words, the most serious ethical problem that arises in cluster randomized research also arises in political philosophy. © 2011 Blackwell Publishing Ltd.

  10. INNOVATIVE CLUSTER OR COMPETITIVENESS POLE?

    Directory of Open Access Journals (Sweden)

    Liliana Scutaru

    2015-02-01

    Full Text Available The paper analyzes the situation of clusters in Romania and their areas of activity and innovation in entrepreneurship Romanian state. It is made also a territorial distribution of clusters on the eight regions. The findings lead to the conclusion that there are some clusters that have the vocation to become poles of competitiveness in areas such as renewable energy, automotive, electronics, health, biotechnology, mechatronics or ICT (Information and Communication Technology which represent the resources for future of the Romanian economy. Regarding the degree of innovation of Romanian Small and Medium Enterprises (SMEs, the level is relatively modest, 30.8% of all enterprises being innovative. If we were to answer the question the title suggests, we would say "yes" to both since the innovative cluster as well as the competitiveness pole promotes par excellence, innovation through study, research and stimulation of creativity. And this is more than enough to support economic growth of Romania and maintain the competitiveness worldwide.

  11. Air void clustering : [technical summary].

    Science.gov (United States)

    2015-06-01

    Air void clustering around coarse aggregate in concrete has been : identified as a potential source of low strengths in concrete mixes by : several Departments of Transportation around the country. Research : was carried out to (1) develop a quantita...

  12. Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

    Science.gov (United States)

    Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

    2014-11-01

    Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics.

    Science.gov (United States)

    The, Matthew; Käll, Lukas

    2016-03-04

    Shotgun proteomics experiments generate large amounts of fragment spectra as primary data, normally with high redundancy between and within experiments. Here, we have devised a clustering technique to identify fragment spectra stemming from the same species of peptide. This is a powerful alternative method to traditional search engines for analyzing spectra, specifically useful for larger scale mass spectrometry studies. As an aid in this process, we propose a distance calculation relying on the rarity of experimental fragment peaks, following the intuition that peaks shared by only a few spectra offer more evidence than peaks shared by a large number of spectra. We used this distance calculation and a complete-linkage scheme to cluster data from a recent large-scale mass spectrometry-based study. The clusterings produced by our method have up to 40% more identified peptides for their consensus spectra compared to those produced by the previous state-of-the-art method. We see that our method would advance the construction of spectral libraries as well as serve as a tool for mining large sets of fragment spectra. The source code and Ubuntu binary packages are available at https://github.com/statisticalbiotechnology/maracluster (under an Apache 2.0 license).

  14. Acoustical sensing of cardiomyocyte cluster beating

    Energy Technology Data Exchange (ETDEWEB)

    Tymchenko, Nina; Kunze, Angelika [Dept. of Applied Physics, Chalmers University of Technology, 412 96 Göteborg (Sweden); Dahlenborg, Kerstin [Cellectis, 413 46 Göteborg (Sweden); Svedhem, Sofia, E-mail: sofia.svedhem@chalmers.se [Dept. of Applied Physics, Chalmers University of Technology, 412 96 Göteborg (Sweden); Steel, Daniella [Cellectis, 413 46 Göteborg (Sweden)

    2013-06-14

    Highlights: •An example of the application of QCM-D to live cell studies. •Detection of human pluripotent stem cell-derived cardiomyocyte cluster beating. •Clusters were studied in a thin liquid film and in a large liquid volume. •The QCM-D beating profile provides an individual fingerprint of the hPS-CMCs. -- Abstract: Spontaneously beating human pluripotent stem cell-derived cardiomyocytes clusters (CMCs) represent an excellent in vitro tool for studies of human cardiomyocyte function and for pharmacological cardiac safety assessment. Such testing typically requires highly trained operators, precision plating, or large cell quantities, and there is a demand for real-time, label-free monitoring of small cell quantities, especially rare cells and tissue-like structures. Array formats based on sensing of electrical or optical properties of cells are being developed and in use by the pharmaceutical industry. A potential alternative to these techniques is represented by the quartz crystal microbalance with dissipation monitoring (QCM-D) technique, which is an acoustic surface sensitive technique that measures changes in mass and viscoelastic properties close to the sensor surface (from nm to μm). There is an increasing number of studies where QCM-D has successfully been applied to monitor properties of cells and cellular processes. In the present study, we show that spontaneous beating of CMCs on QCM-D sensors can be clearly detected, both in the frequency and the dissipation signals. Beating rates in the range of 66–168 bpm for CMCs were detected and confirmed by simultaneous light microscopy. The QCM-D beating profile was found to provide individual fingerprints of the hPS-CMCs. The presented results point towards acoustical assays for evaluation cardiotoxicity.

  15. Clustering of Sun Exposure Measurements

    OpenAIRE

    Have, Anna Szynkowiak; Larsen, Jan; Hansen, Lars Kai; Philipsen, Peter Alshede; Thieden, Elisabeth; Wulf, Hans Christian

    2002-01-01

    In a medically motivated Sun-exposure study, questionnaires concerning Sun-habits were collected from a number of subjects together with UV radiation measurements. This paper focuses on identifying clusters in the heterogeneous set of data for the purpose of understanding possible relations between Sun-habits exposure and eventually assessing the risk of skin cancer. A general probabilistic framework originally developed for text and Web mining is demonstrated to be useful for clustering of b...

  16. Vacancy clusters at nanoparticle surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Xu, J.; Moxom, J.; Somieski, B.; White, C.W. [Oak Ridge National Lab., TN (United States); Mills, A.P. Jr. [Bell Labs., Lucent Technologies, Murray Hill, NJ (United States); Suzuki, R.; Ishibashi, S. [Electrotechnical Lab., Tsukuba, Ibaraki (Japan); Ueda, A.; Henderson, D. [Physics Dept., Fisk Univ., Nashville, TN (United States)

    2001-07-01

    We detect vacancy clusters at Au nanoparticle surfaces using a combination of positron lifetime spectroscopy, 1- detector, and 2-detector measurements of Doppler broadening of annihilation radiation. Gold nanoparticles are formed by MeV implantation of gold ions into MgO (100) followed by annealing. Clusters of two Mg and two O vacancies (v{sub 4}) are attached to the gold nanoparticle surfaces within the projected range (R{sub p}). (orig.)

  17. Vacancy clusters at nanoparticle surfaces

    International Nuclear Information System (INIS)

    Xu, J.; Moxom, J.; Somieski, B.; White, C.W.; Mills, A.P. Jr.; Suzuki, R.; Ishibashi, S.; Ueda, A.; Henderson, D.

    2001-01-01

    We detect vacancy clusters at Au nanoparticle surfaces using a combination of positron lifetime spectroscopy, 1- detector, and 2-detector measurements of Doppler broadening of annihilation radiation. Gold nanoparticles are formed by MeV implantation of gold ions into MgO (100) followed by annealing. Clusters of two Mg and two O vacancies (v 4 ) are attached to the gold nanoparticle surfaces within the projected range (R p ). (orig.)

  18. Network clustering coefficient approach to DNA sequence analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gerhardt, Guenther J.L. [Universidade Federal do Rio Grande do Sul-Hospital de Clinicas de Porto Alegre, Rua Ramiro Barcelos 2350/sala 2040/90035-003 Porto Alegre (Brazil); Departamento de Fisica e Quimica da Universidade de Caxias do Sul, Rua Francisco Getulio Vargas 1130, 95001-970 Caxias do Sul (Brazil); Lemke, Ney [Programa Interdisciplinar em Computacao Aplicada, Unisinos, Av. Unisinos, 950, 93022-000 Sao Leopoldo, RS (Brazil); Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, Campus Universitario, 59072 970 Natal, RN (Brazil)]. E-mail: corso@dfte.ufrn.br

    2006-05-15

    In this work we propose an alternative DNA sequence analysis tool based on graph theoretical concepts. The methodology investigates the path topology of an organism genome through a triplet network. In this network, triplets in DNA sequence are vertices and two vertices are connected if they occur juxtaposed on the genome. We characterize this network topology by measuring the clustering coefficient. We test our methodology against two main bias: the guanine-cytosine (GC) content and 3-bp (base pairs) periodicity of DNA sequence. We perform the test constructing random networks with variable GC content and imposed 3-bp periodicity. A test group of some organisms is constructed and we investigate the methodology in the light of the constructed random networks. We conclude that the clustering coefficient is a valuable tool since it gives information that is not trivially contained in 3-bp periodicity neither in the variable GC content.

  19. Cluster structure in Cf nuclei

    International Nuclear Information System (INIS)

    Singh, Shailesh K.; Biswal, S.K.; Bhuyan, M.; Patra, S.K.; Gupta, R.K.

    2014-01-01

    Due to the availability of advance experimental facilities, it is possible to probe the nuclei upto their nucleon level very precisely and analyzed the internal structure which will help us to resolve some mysterious problem of the decay of nuclei. Recently, the relativistic nuclear collision, confirmed the α cluster type structure in the 12 C which is the mile stone for the cluster structure in nuclei. The clustering phenomena in light and intermediate elements in nuclear chart is very interesting. There is a lot of work done by our group in the clustering behaviour of the nuclei. In this paper, the various prospectus of clustering in the isotopes of Cf nucleus including fission state is discussed. Here, 242 Cf isotope for the analysis, which is experimentally known is taken. The relativistic mean field model with well established NL3 parameter set is taken. For getting the exact ground state configuration of the isotopes, the calculation for minimizing the potential energy surface is performed by constraint method. The clustering structure of other Cf isotopes is discussed

  20. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    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.

  1. Identification of Urban Leprosy Clusters

    Directory of Open Access Journals (Sweden)

    José Antonio Armani Paschoal

    2013-01-01

    Full Text Available Overpopulation of urban areas results from constant migrations that cause disordered urban growth, constituting clusters defined as sets of people or activities concentrated in relatively small physical spaces that often involve precarious conditions. Aim. Using residential grouping, the aim was to identify possible clusters of individuals in São José do Rio Preto, Sao Paulo, Brazil, who have or have had leprosy. Methods. A population-based, descriptive, ecological study using the MapInfo and CrimeStat techniques, geoprocessing, and space-time analysis evaluated the location of 425 people treated for leprosy between 1998 and 2010. Clusters were defined as concentrations of at least 8 people with leprosy; a distance of up to 300 meters between residences was adopted. Additionally, the year of starting treatment and the clinical forms of the disease were analyzed. Results. Ninety-eight (23.1% of 425 geocoded cases were located within one of ten clusters identified in this study, and 129 cases (30.3% were in the region of a second-order cluster, an area considered of high risk for the disease. Conclusion. This study identified ten clusters of leprosy cases in the city and identified an area of high risk for the appearance of new cases of the disease.

  2. Clusters in Nuclei. Vol. 2

    International Nuclear Information System (INIS)

    Beck, Christian

    2012-01-01

    Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This second volume follows the successful Lect. Notes Phys. 818 (Vol.1), and comprises six extensive lectures covering the following topics: - Microscopic cluster models - Neutron halo and break-up reactions - Break-up reaction models for two- and three-cluster projectiles - Clustering effects within the di-nuclear model - Nuclear alpha-particle condensates - Clusters in nuclei: experimental perspectives By promoting new ideas and developments while retaining a pedagogical style of presentation throughout, these lectures will serve as both a reference and an advanced teaching manual for future courses and schools in the fields of nuclear physics and nuclear astrophysics. (orig.)

  3. Clusters in Nuclei. Vol. 2

    Energy Technology Data Exchange (ETDEWEB)

    Beck, Christian (ed.) [Strasbourg Univ. (France). Inst. Pluridiciplinaire Hubert Curien

    2012-07-01

    Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This second volume follows the successful Lect. Notes Phys. 818 (Vol.1), and comprises six extensive lectures covering the following topics: - Microscopic cluster models - Neutron halo and break-up reactions - Break-up reaction models for two- and three-cluster projectiles - Clustering effects within the di-nuclear model - Nuclear alpha-particle condensates - Clusters in nuclei: experimental perspectives By promoting new ideas and developments while retaining a pedagogical style of presentation throughout, these lectures will serve as both a reference and an advanced teaching manual for future courses and schools in the fields of nuclear physics and nuclear astrophysics. (orig.)

  4. Identification of Urban Leprosy Clusters

    Science.gov (United States)

    Paschoal, José Antonio Armani; Paschoal, Vania Del'Arco; Nardi, Susilene Maria Tonelli; Rosa, Patrícia Sammarco; Ismael, Manuela Gallo y Sanches; Sichieri, Eduvaldo Paulo

    2013-01-01

    Overpopulation of urban areas results from constant migrations that cause disordered urban growth, constituting clusters defined as sets of people or activities concentrated in relatively small physical spaces that often involve precarious conditions. Aim. Using residential grouping, the aim was to identify possible clusters of individuals in São José do Rio Preto, Sao Paulo, Brazil, who have or have had leprosy. Methods. A population-based, descriptive, ecological study using the MapInfo and CrimeStat techniques, geoprocessing, and space-time analysis evaluated the location of 425 people treated for leprosy between 1998 and 2010. Clusters were defined as concentrations of at least 8 people with leprosy; a distance of up to 300 meters between residences was adopted. Additionally, the year of starting treatment and the clinical forms of the disease were analyzed. Results. Ninety-eight (23.1%) of 425 geocoded cases were located within one of ten clusters identified in this study, and 129 cases (30.3%) were in the region of a second-order cluster, an area considered of high risk for the disease. Conclusion. This study identified ten clusters of leprosy cases in the city and identified an area of high risk for the appearance of new cases of the disease. PMID:24288467

  5. Probing the dark energy with quasar clustering.

    Science.gov (United States)

    Calvão, M O; de Mello Neto, J R T; Waga, I

    2002-03-04

    We show through Monte Carlo simulations that the Alcock-Paczyński test, as applied to quasar clustering, is a powerful tool to probe the cosmological density and equation of state parameters Omega(m0), Omega(x0), and w. By taking into account the effect of peculiar velocities upon the correlation function we obtain for the Two-Degree Field QSO Redshift Survey the predicted confidence contours for the cosmological constant (w = -1) and spatially flat (Omega(m0)+Omega(x0) = 1) cases. For w = -1, the test is especially sensitive to the difference Omega(m0)-Omega(Lambda0), thus being ideal to combine with cosmic microwave background results. For the flat case, it is competitive with future supernova and galaxy number count tests, besides being complementary to them.

  6. Hadoop Cluster Deployment: A Methodological Approach

    Directory of Open Access Journals (Sweden)

    Ronaldo Celso Messias Correia

    2018-05-01

    Full Text Available For a long time, data has been treated as a general problem because it just represents fractions of an event without any relevant purpose. However, the last decade has been just about information and how to get it. Seeking meaning in data and trying to solve scalability problems, many frameworks have been developed to improve data storage and its analysis. As a framework, Hadoop was presented as a powerful tool to deal with large amounts of data. However, it still causes doubts about how to deal with its deployment and if there is any reliable method to compare the performance of distinct Hadoop clusters. This paper presents a methodology based on benchmark analysis to guide the Hadoop cluster deployment. The experiments employed The Apache Hadoop and the Hadoop distributions of Cloudera, Hortonworks, and MapR, analyzing the architectures on local and on clouding—using centralized and geographically distributed servers. The results show the methodology can be dynamically applied on a reliable comparison among different architectures. Additionally, the study suggests that the knowledge acquired can be used to improve the data analysis process by understanding the Hadoop architecture.

  7. Orthology detection combining clustering and synteny for very large datasets

    OpenAIRE

    Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K.; Prohaska, Sonja J.; Stadler, Peter F.

    2014-01-01

    The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the ...

  8. Characteristics of multiprocessing MCNP5 on small personal computer clusters

    International Nuclear Information System (INIS)

    Robinson, S M; Mc Conn, R J Jr; Pagh, R T; Schweppe, J E; Siciliano, E R

    2006-01-01

    The feasibility and efficiency of performing MCNP5 calculations with a small, heterogeneous computing cluster built from Microsoft ( R) Windows TM personal computers (PC) are explored. The performance increases that may be expected with such clusters are estimated for cases that typify general radiation-shielding calculations. Our results show that the speed increase from additional slave PCs is nearly linear up to 10 processors. Guidance is given as to the specific advantages of changing various parameters present in the system. Implementing load balancing, and reducing the overhead from the MCNP rendezvous mechanism add to heterogeneous cluster efficiency. Hyper-threading technology and matching the total number of slave processes to the total number of logical processors also yield modest speed increases in the range below 7 processors. Because of the ease of acquisition of heterogeneous desktop computers, and the peak in efficiency at the level of a few physical processors, a strong case is made for the use of small clusters as a tool for producing MCNP5 calculations rapidly, and detailed instructions for constructing such clusters are provided

  9. Nurses' beliefs about nursing diagnosis: A study with cluster analysis.

    Science.gov (United States)

    D'Agostino, Fabio; Pancani, Luca; Romero-Sánchez, José Manuel; Lumillo-Gutierrez, Iris; Paloma-Castro, Olga; Vellone, Ercole; Alvaro, Rosaria

    2018-06-01

    To identify clusters of nurses in relation to their beliefs about nursing diagnosis among two populations (Italian and Spanish); to investigate differences among clusters of nurses in each population considering the nurses' socio-demographic data, attitudes towards nursing diagnosis, intentions to make nursing diagnosis and actual behaviours in making nursing diagnosis. Nurses' beliefs concerning nursing diagnosis can influence its use in practice but this is still unclear. A cross-sectional design. A convenience sample of nurses in Italy and Spain was enrolled. Data were collected between 2014-2015 using tools, that is, a socio-demographic questionnaire and behavioural, normative and control beliefs, attitudes, intentions and behaviours scales. The sample included 499 nurses (272 Italians & 227 Spanish). Of these, 66.5% of the Italian and 90.7% of the Spanish sample were female. The mean age was 36.5 and 45.2 years old in the Italian and Spanish sample respectively. Six clusters of nurses were identified in Spain and four in Italy. Three clusters were similar among the two populations. Similar significant associations between age, years of work, attitudes towards nursing diagnosis, intentions to make nursing diagnosis and behaviours in making nursing diagnosis and cluster membership in each population were identified. Belief profiles identified unique subsets of nurses that have distinct characteristics. Categorizing nurses by belief patterns may help administrators and educators to tailor interventions aimed at improving nursing diagnosis use in practice. © 2018 John Wiley & Sons Ltd.

  10. Clustering Trajectories by Relevant Parts for Air Traffic Analysis.

    Science.gov (United States)

    Andrienko, Gennady; Andrienko, Natalia; Fuchs, Georg; Garcia, Jose Manuel Cordero

    2018-01-01

    Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering.

  11. Dutch Risk Assessment tools

    NARCIS (Netherlands)

    Venema, A.

    2015-01-01

    The ‘Risico- Inventarisatie- en Evaluatie-instrumenten’ is the name for the Dutch risk assessment (RA) tools. A RA tool can be used to perform a risk assessment including an evaluation of the identified risks. These tools were among the first online risk assessment tools developed in Europe. The

  12. New QC 7 tools

    International Nuclear Information System (INIS)

    1982-03-01

    This book tells of new QC with 7 tools which includes TQC and new QC with 7 tools which is for better propel, what is QC method to think? what is new QC 7 tool ? like KJ law, PDPC law, arrow and diagram law, and matrix diagram law, application of new QC 7 tools such as field to apply, application of new QC 7 tools for policy management the method of new QC 7 tools including related regulations KJ law, matrix and data analysis, PDPC law and education and introduction of new QC 7 tools.

  13. Cosmology with clusters in the CMB

    International Nuclear Information System (INIS)

    Majumdar, Subhabrata

    2008-01-01

    Ever since the seminal work by Sunyaev and Zel'dovich describing the distortion of the CMB spectrum, due to photons passing through the hot inter cluster gas on its way to us from the surface of last scattering (the so called Sunyaev-Zel'dovich effect (SZE)), small scale distortions of the CMB by clusters has been used to detect clusters as well as to do cosmology with clusters. Cosmology with clusters in the CMB can be divided into three distinct regimes: a) when the clusters are completely unresolved and contribute to the secondary CMB distortions power spectrum at small angular scales; b) when we can just about resolve the clusters so as to detect the clusters through its total SZE flux such that the clusters can be tagged and counted for doing cosmology and c) when we can completely resolve the clusters so as to measure their sizes and other cluster structural properties and their evolution with redshift. In this article, we take a look at these three aspects of SZE cluster studies and their implication for using clusters as cosmological probes. We show that clusters can be used as effective probes of cosmology, when in all of these three cases, one explores the synergy between cluster physics and cosmology as well take clues about cluster physics from the latest high precision cluster observations (for example, from Chandra and XMM - Newton). As a specific case, we show how an observationally motivated cluster SZ template can explain the CBI-excess without the need for a high σ 8 . We also briefly discuss 'self-calibration' in cluster surveys and the prospect of using clusters as an ensemble of cosmic rulers to break degeneracies arising in cluster cosmology.

  14. Electronic and chemical properties of indium clusters

    International Nuclear Information System (INIS)

    Rayane, D.; Khardi, S.; Tribollet, B.; Broyer, M.; Melinon, P.; Cabaud, B.; Hoareau, A.

    1989-01-01

    Indium clusters are produced by the inert gas condensation technique. The ionization potentials are found higher for small clusters than for the Indium atom. This is explained by the p character of the bonding as in aluminium. Doubly charge clusters are also observed and fragmentation processes discussed. Finally small Indium clusters 3< n<9 are found very reactive with hydrocarbon. (orig.)

  15. Bayesian Decision Theoretical Framework for Clustering

    Science.gov (United States)

    Chen, Mo

    2011-01-01

    In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…

  16. 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.

  17. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

    DEFF Research Database (Denmark)

    Weber, Tilmann; Blin, Kai; Duddela, Srikanth

    2015-01-01

    Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we...... introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration...... of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products...

  18. An introduction to cluster science

    CERN Document Server

    Dinh, Phuong Mai; Suraud, Eric

    2013-01-01

    Filling the need for a solid textbook, this short primer in cluster science is ideal for a one-semester lecture for advanced undergraduate students. It is based on a series of lectures given by the well-established and recognized authors for the past ten years. The book covers both the basics of the domain as well as up-to-date developments. It can be divided roughly into two parts. The first three chapters introduce basic concepts of cluster science. Chapter 1 provides a general introduction, complemented by chapter 2 on experimental and chapter 3 on theoretical aspects. The second half of the book is devoted to a systematic presentation of free cluster properties, and to a thorough discussion of the impact of clusters in other domains of science. These explicitly worked-out links between cluster physics and other research areas are unique both in terms of fundamental aspects and of applications, and cannot be found elsewhere in the literature. Also suitable for researchers outside of the field looking for...

  19. Reduct Driven Pattern Extraction from Clusters

    Directory of Open Access Journals (Sweden)

    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.

  20. 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)

  1. Continuous Security and Configuration Monitoring of HPC Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Lomeli, H. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bertsch, A. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fox, D. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-05-08

    Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration management systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking

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

    Science.gov (United States)

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

    2017-04-01

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

  3. Connection between Seyfert galaxies and clusters

    International Nuclear Information System (INIS)

    Petrosyan, A.R.

    1988-01-01

    To identify Seyfert galaxies that are members of clusters, the sample of known Seyfert galaxies (464 objects) is tested against the Zwicky, Abell, and southern clusters. On the basis of the criteria adopted in the paper, 67 Seyfert galaxies are selected as probable members of Zwicky clusters, 15 as members of Abell clusters, and 18 as members of southern clusters. Lists of these objects are given

  4. m-BIRCH: an online clustering approach for computer vision applications

    Science.gov (United States)

    Madan, Siddharth K.; Dana, Kristin J.

    2015-03-01

    We adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), to incrementally cluster large datasets of features commonly used in multimedia and computer vision. We call the adapted version modified-BIRCH (m-BIRCH). The algorithm uses only a fraction of the dataset memory to perform clustering, and updates the clustering decisions when new data comes in. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in data summarization. We use m-BIRCH to cluster 840K color SIFT descriptors, and 60K outlier corrupted grayscale patches. We use the algorithm to cluster datasets consisting of challenging non-convex clustering patterns. Our implementation of the algorithm provides an useful clustering tool and is made publicly available.

  5. AN EXAMINATION OF THE OPTICAL SUBSTRUCTURE OF GALAXY CLUSTERS HOSTING RADIO SOURCES

    International Nuclear Information System (INIS)

    Wing, Joshua D.; Blanton, Elizabeth L.

    2013-01-01

    Using radio sources from the Faint Images of the Radio Sky at Twenty-cm survey, and optical counterparts in the Sloan Digital Sky Survey, we have identified a large number of galaxy clusters. The radio sources within these clusters are driven by active galactic nuclei, and our cluster samples include clusters with bent, and straight, double-lobed radio sources. We also included a single-radio-component comparison sample. We examine these galaxy clusters for evidence of optical substructure, testing the possibility that bent double-lobed radio sources are formed as a result of large-scale cluster mergers. We use a suite of substructure analysis tools to determine the location and extent of substructure visible in the optical distribution of cluster galaxies, and compare the rates of substructure in clusters with different types of radio sources. We found no preference for significant substructure in clusters hosting bent double-lobed radio sources compared to those with other types of radio sources.

  6. Improved optical mass tracer for galaxy clusters calibrated using weak lensing measurements

    Science.gov (United States)

    Reyes, R.; Mandelbaum, R.; Hirata, C.; Bahcall, N.; Seljak, U.

    2008-11-01

    We develop an improved mass tracer for clusters of galaxies from optically observed parameters, and calibrate the mass relation using weak gravitational lensing measurements. We employ a sample of ~13000 optically selected clusters from the Sloan Digital Sky Survey (SDSS) maxBCG catalogue, with photometric redshifts in the range 0.1-0.3. The optical tracers we consider are cluster richness, cluster luminosity, luminosity of the brightest cluster galaxy (BCG) and combinations of these parameters. We measure the weak lensing signal around stacked clusters as a function of the various tracers, and use it to determine the tracer with the least amount of scatter. We further use the weak lensing data to calibrate the mass normalization. We find that the best mass estimator for massive clusters is a combination of cluster richness, N200, and the luminosity of the BCG, LBCG: , where is the observed mean BCG luminosity at a given richness. This improved mass tracer will enable the use of galaxy clusters as a more powerful tool for constraining cosmological parameters.

  7. Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data.

    Science.gov (United States)

    Kim, Sehwi; Jung, Inkyung

    2017-01-01

    The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns.

  8. Percolation technique for galaxy clustering

    Science.gov (United States)

    Klypin, Anatoly; Shandarin, Sergei F.

    1993-01-01

    We study percolation in mass and galaxy distributions obtained in 3D simulations of the CDM, C + HDM, and the power law (n = -1) models in the Omega = 1 universe. Percolation statistics is used here as a quantitative measure of the degree to which a mass or galaxy distribution is of a filamentary or cellular type. The very fast code used calculates the statistics of clusters along with the direct detection of percolation. We found that the two parameters mu(infinity), characterizing the size of the largest cluster, and mu-squared, characterizing the weighted mean size of all clusters excluding the largest one, are extremely useful for evaluating the percolation threshold. An advantage of using these parameters is their low sensitivity to boundary effects. We show that both the CDM and the C + HDM models are extremely filamentary both in mass and galaxy distribution. The percolation thresholds for the mass distributions are determined.

  9. Binding energies of cluster ions

    International Nuclear Information System (INIS)

    Parajuli, R.; Matt, S.; Scheier, P.; Echt, O.; Stamatovic, A.; Maerk, T.D.

    2002-01-01

    The binding energy of charged clusters may be measured by analyzing the kinetic energy released in the metastable decay of mass selected parent ions. Using finite heat bath theory to determine the binding energies of argon, neon, krypton, oxygen and nitrogen from their respective average kinetic energy released were carried out. A high-resolution double focussing two-sector mass spectrometer of reversed Nier-Johnson type geometry was used. MIKE ( mass-analysed ion kinetic energy) were measured to investigate decay reactions of mass-selected ions. For the inert gases neon (Ne n + ), argon (Ar n + ) and krypton (Kr n + ), it is found that the binding energies initially decrease with increasing size n and then level off at a value above the enthalpy of vaporization of the condensed phase. Oxygen cluster ions shown a characteristic dependence on cluster size (U-shape) indicating a change in the metastable fragmentation mechanism when going from the dimer to the decamer ion. (nevyjel)

  10. Stream Clustering of Growing Objects

    Science.gov (United States)

    Siddiqui, Zaigham Faraz; Spiliopoulou, Myra

    We study incremental clustering of objects that grow and accumulate over time. The objects come from a multi-table stream e.g. streams of Customer and Transaction. As the Transactions stream accumulates, the Customers’ profiles grow. First, we use an incremental propositionalisation to convert the multi-table stream into a single-table stream upon which we apply clustering. For this purpose, we develop an online version of K-Means algorithm that can handle these swelling objects and any new objects that arrive. The algorithm also monitors the quality of the model and performs re-clustering when it deteriorates. We evaluate our method on the PKDD Challenge 1999 dataset.

  11. Nanocomposites for Machining Tools

    Directory of Open Access Journals (Sweden)

    Daria Sidorenko

    2017-10-01

    Full Text Available Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance.

  12. Tool grinding machine

    Science.gov (United States)

    Dial, Sr., Charles E.

    1980-01-01

    The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thickness may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

  13. Improved tool grinding machine

    Science.gov (United States)

    Dial, C.E. Sr.

    The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thicknesses may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

  14. Fulfilment of Grid Code Obligations by Large Offshore Wind Farms Clusters Connected via HVDC Corridors

    OpenAIRE

    Attya, A.B.; Anaya-Lara, Olimpo; Ledesma, P.; Svendsen, Harald Georg

    2016-01-01

    - The foreseen high penetration levels of wind power will force the systems operators to apply restrictive constraints on wind power plants. The ability of offshore wind clusters, which are connected via HVDC, to fulfill the grid codes, especially those related to voltage stability is investigated. This came in the frame of a project to develop an integrated and practical tool to design offshore wind clusters (EERA-DTOC). The applied case studies examine the system stability during and aft...

  15. The k-means clustering technique: General considerations and implementation in Mathematica

    Directory of Open Access Journals (Sweden)

    Laurence Morissette

    2013-02-01

    Full Text Available Data clustering techniques are valuable tools for researchers working with large databases of multivariate data. In this tutorial, we present a simple yet powerful one: the k-means clustering technique, through three different algorithms: the Forgy/Lloyd, algorithm, the MacQueen algorithm and the Hartigan and Wong algorithm. We then present an implementation in Mathematica and various examples of the different options available to illustrate the application of the technique.

  16. Statistical analysis of the spatial distribution of galaxies and clusters

    International Nuclear Information System (INIS)

    Cappi, Alberto

    1993-01-01

    This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr

  17. Calibrating the Planck Cluster Mass Scale with Cluster Velocity Dispersions

    Science.gov (United States)

    Amodeo, Stefania; Mei, Simona; Stanford, Spencer A.; Bartlett, James G.; Melin, Jean-Baptiste; Lawrence, Charles R.; Chary, Ranga-Ram; Shim, Hyunjin; Marleau, Francine; Stern, Daniel

    2017-08-01

    We measure the Planck cluster mass bias using dynamical mass measurements based on velocity dispersions of a subsample of 17 Planck-detected clusters. The velocity dispersions were calculated using redshifts determined from spectra that were obtained at the Gemini observatory with the GMOS multi-object spectrograph. We correct our estimates for effects due to finite aperture, Eddington bias, and correlated scatter between velocity dispersion and the Planck mass proxy. The result for the mass bias parameter, (1-b), depends on the value of the galaxy velocity bias, {b}{{v}}, adopted from simulations: (1-b)=(0.51+/- 0.09){b}{{v}}3. Using a velocity bias of {b}{{v}}=1.08 from Munari et al., we obtain (1-b)=0.64+/- 0.11, I.e., an error of 17% on the mass bias measurement with 17 clusters. This mass bias value is consistent with most previous weak-lensing determinations. It lies within 1σ of the value that is needed to reconcile the Planck cluster counts with the Planck primary cosmic microwave background constraints. We emphasize that uncertainty in the velocity bias severely hampers the precision of the measurements of the mass bias using velocity dispersions. On the other hand, when we fix the Planck mass bias using the constraints from Penna-Lima et al., based on weak-lensing measurements, we obtain a positive velocity bias of {b}{{v}}≳ 0.9 at 3σ .

  18. Oxygen treatment of cluster headache

    DEFF Research Database (Denmark)

    Petersen, Anja S; Barloese, Mads C J; Jensen, Rigmor H

    2014-01-01

    PURPOSE: Our aim was to review the existing literature to document oxygen's therapeutic effect on cluster headache. METHOD: A PubMed search resulted in 28 hits, and from these and their references we found in total 11 relevant studies. We included six studies that investigated the efficacy......, but not a prophylactic effect. Despite the fact that only a few high-quality RCT studies are available, oxygen treatment is close to an ideal treatment because it is effective and safe. However, sufferers of cluster headache do not always have access to oxygen because of logistic and financial concerns....

  19. Epistemic communities and cluster dynamics

    DEFF Research Database (Denmark)

    Håkanson, Lars

    2003-01-01

    This paper questions the prevailing notions that firms within industrial clusters have privi-leged access to `tacit knowledge' that is unavailable - or available only at high cost - to firms located elsewhere, and that such access provides competitive advantages that help to explain the growth...... and development of both firms and regions. It outlines a model of cluster dynam-ics emphasizing two mutually interdependent processes: the concentration of specialized and complementary epistemic communities, on the one hand, and entrepreneurship and a high rate of new firm formation on the other....

  20. Thermodynamic basis for cluster kinetics

    DEFF Research Database (Denmark)

    Hu, Lina; Bian, Xiufang; Qin, Xubo

    2006-01-01

    Due to the inaccessibility of the supercooled region of marginal metallic glasses (MMGs) within the experimental time window, we study the cluster kinetics above the liquidus temperature, Tl, to acquire information on the fragility of the MMG systems. Thermodynamic basis for the stability...... of locally ordered structure in the MMG liquids is discussed in terms of the two-order-parameter model. It is found that the Arrhenius activation energy of clusters, h, is proportional to the chemical mixing enthalpy of alloys, Hchem. Fragility of the MMG forming liquids can be described by the ratio...