WorldWideScience

Sample records for gene-oriented clustering tool

  1. Large Crater Clustering tool

    Science.gov (United States)

    Laura, Jason; Skinner, James A.; Hunter, Marc A.

    2017-08-01

    In this paper we present the Large Crater Clustering (LCC) tool set, an ArcGIS plugin that supports the quantitative approximation of a primary impact location from user-identified locations of possible secondary impact craters or the long-axes of clustered secondary craters. The identification of primary impact craters directly supports planetary geologic mapping and topical science studies where the chronostratigraphic age of some geologic units may be known, but more distant features have questionable geologic ages. Previous works (e.g., McEwen et al., 2005; Dundas and McEwen, 2007) have shown that the source of secondary impact craters can be estimated from secondary impact craters. This work adapts those methods into a statistically robust tool set. We describe the four individual tools within the LCC tool set to support: (1) processing individually digitized point observations (craters), (2) estimating the directional distribution of a clustered set of craters, back projecting the potential flight paths (crater clusters or linearly approximated catenae or lineaments), (3) intersecting projected paths, and (4) intersecting back-projected trajectories to approximate the local of potential source primary craters. We present two case studies using secondary impact features mapped in two regions of Mars. We demonstrate that the tool is able to quantitatively identify primary impacts and supports the improved qualitative interpretation of potential secondary crater flight trajectories.

  2. Design tool for offshore wind farm clusters

    DEFF Research Database (Denmark)

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

    2015-01-01

    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......The Design Tool for Offshore wind farm Clusters (DTOC) is a software tool to facilitate the optimised design of both, individual and clusters of offshore wind farms. DTOC is developed with the support of an EC funded FP7 project with contributions from science partners from the European Energy...... is developed within the project using open interface standards and is now available as the commercial software product Wind&Economy....

  3. Design tool for offshore wind farm clusters

    DEFF Research Database (Denmark)

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

    2015-01-01

    The Design Tool for Offshore wind farm Clusters (DTOC) is a software tool to facilitate the optimised design of both, individual and clusters of offshore wind farms. DTOC is developed with the support of an EC funded FP7 project with contributions from science partners from the European Energy...... is developed within the project using open interface standards and is now available as the commercial software product Wind&Economy....... 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...

  4. DiffTool: building, visualizing and querying protein clusters.

    Science.gov (United States)

    Chetouani, Farid; Glaser, Philippe; Kunst, Frank

    2002-08-01

    DiffTool is a resource to build and visualize protein clusters computed from a sequence database. The package provides a clustering tool to construct protein families according to sequence similarities and a web interface to query the corresponding clusters. A subtractive genome analysis tool selects protein families specific for a genome or a group of genomes. For each protein cluster, DiffTool includes access to sequences, coloured multiple alignments and phylogenetic trees. A cluster database built from yeast and complete prokaryotic genomes is queryable at http://bioweb.pasteur.fr/seqanal/difftool. All the Perl sources are freely available to non-profit organizations upon request.

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

    Directory of Open Access Journals (Sweden)

    Ahmed Abdullah

    2015-06-01

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

  6. BioCluster: tool for identification and clustering of Enterobacteriaceae based on biochemical data.

    Science.gov (United States)

    Abdullah, Ahmed; Sabbir Alam, S M; Sultana, Munawar; Hossain, M Anwar

    2015-06-01

    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/. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

  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. 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

    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....

  9. 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 WAsP,...... are useful for wind farm planning of the grid and necessary components and controls.......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...

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Multi-netclust: an efficient tool for finding connected clusters in multi-parametric networks

    NARCIS (Netherlands)

    Kuzniar, A.; Dhir, S.; Nijveen, H.; Pongor, S.; Leunissen, J.A.M.

    2010-01-01

    Multi-netclust is a simple tool that allows users to extract connected clusters of data represented by different networks given in the form of matrices. The tool uses user-defined threshold values to combine the matrices, and uses a straightforward, memory-efficient graph algorithm to find clusters

  12. 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

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

    Science.gov (United States)

    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.

  14. Optimal Machine Tools Selection Using Interval-Valued Data FCM Clustering Algorithm

    OpenAIRE

    Xin, Yupeng; Tian, Xitian; Huang, Lijiang

    2014-01-01

    Machine tool selection directly affects production rates, accuracy, and flexibility. In order to quickly and accurately select the appropriate machine tools in machining process planning, this paper proposes an optimal machine tools selection method based on interval-valued data fuzzy C-means (FCM) clustering algorithm. We define the machining capability meta (MAE) as the smallest unit to describe machining capacity of machine tools and establish MAE library based on the MAE information model...

  15. A Temperature Sensor Clustering Method for Thermal Error Modeling of Heavy Milling Machine Tools

    Directory of Open Access Journals (Sweden)

    Fengchun Li

    2017-01-01

    Full Text Available A clustering method is an effective way to select the proper temperature sensor location for thermal error modeling of machine tools. In this paper, a new temperature sensor clustering method is proposed. By analyzing the characteristics of the temperature of the sensors in a heavy floor-type milling machine tool, an indicator involving both the Euclidean distance and the correlation coefficient was proposed to reflect the differences between temperature sensors, and the indicator was expressed by a distance matrix to be used for hierarchical clustering. Then, the weight coefficient in the distance matrix and the number of the clusters (groups were optimized by a genetic algorithm (GA, and the fitness function of the GA was also rebuilt by establishing the thermal error model at one rotation speed, then deriving its accuracy at two different rotation speeds with a temperature disturbance. Thus, the parameters for clustering, as well as the final selection of the temperature sensors, were derived. Finally, the method proposed in this paper was verified on a machine tool. According to the selected temperature sensors, a thermal error model of the machine tool was established and used to predict the thermal error. The results indicate that the selected temperature sensors can accurately predict thermal error at different rotation speeds, and the proposed temperature sensor clustering method for sensor selection is expected to be used for the thermal error modeling for other machine tools.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. The Avalon Beowulf Cluster: A Dependable Tool for Scientific Simulation

    Science.gov (United States)

    Warren, Michael

    2000-03-01

    Avalon is a 140 processor Alpha/Linux Beowulf cluster constructed entirely from commodity personal computer technology and freely available software. Computational Physics simulations performed on Avalon resulted in the award of a 1998 Gordon Bell price/performance prize for significant achievement in parallel processing. Avalon ranked as the 113th fastest computer in the world on the November 1998 TOP500 list, obtaining a result of 48.6 Gigaflops on the parallel Linpack benchmark. The price of hardware and final assembly labor for Avalon totalled 313,000 dollars in the fall of 1998. Avalon currently provides over 15,000 node-hours of production computing time per week, split among about 10 production users. Obtaining an equivalent amount of computing through Los Alamos institutional sources would cost a minimicrons of 30,000 per week. The machine also supports code development for another 60 users. Significant simulations have been performed on Avalon in fields of astrophysics, molecular dynamics, nonlinear dynamics as well as other areas. The largest single simulation performed on Avalon computed a total of over 10^16 floating point operations. We will describe some of the applications which have obtained good performance on Avalon, and their characteristics. Our goal has been to provide dependable cycles for computational physics, and not to perform research into clustered computing systems. One of the main lessons learned from the Avalon project is that the details of the hardware are not nearly as important as the attitudes and expectations of the users and managers of the hardware.

  19. 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

    identification of potential contamination and affected consumers in contamination cases. Although still in development, the method shows potential for assisting utilities during planning of monitoring programs and as decision support tool during emergency contingency situations.......Topological clustering was explored as a tool for water supply utilities in preparation of monitoring and contamination contingency plans. A complex water distribution network model of Copenhagen, Denmark, was simplified by topological clustering into recognizable water movement patterns to: (1......) 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...

  20. Business, manufacturing, and system integration issues in cluster tool process control

    Science.gov (United States)

    Richardson, David

    1991-03-01

    An intensified business environment with acce''erated pace of technoLogy development within the semiconductor industry can lead companies to consider emerging techniques in cluster tooling and Computer Integrated Manufacturing (CIM) systems applications. A logical model of interfaces that exist within a corporate manufacturing environment yields a control hierarchy that is present from the tool up through the corporate computing entity. With these various levels of computer control there is a clearly identified need for consistent information management functions throughout this logical hierarchy. One of the complexities of existing CIM systems is the lack of a coherent data model that transcends all levels of the hierarchy. The creation of coherent information (derived from data collection) requires this consistent management of data and the cluster tool or any other semiconductor manufacturing equipment for that matter becomes a vital link in the information chain. In fact the equipment level of the control hierarchy is the majority source of data required to successfully meet the manufacturing and business needs of the corporation. An example will be developed in this paper of using a cluster tool as a highly integrated mini-fab environment to demonstrate the desirable CIM system concepts. This mini-fab characteristic of cluster tools and other highly integrated manufacturing cell configurations will be used to investigate the CIM system impacts on this class of manufacturing capability. The investigation will look at the host-to-equipment relationship in a

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

    Directory of Open Access Journals (Sweden)

    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.

  2. A web-based restriction endonuclease tool for mycobacteriophage cluster prediction.

    Science.gov (United States)

    Gissendanner, Chris R; Wiedemeier, Allison M D; Wiedemeier, Paul D; Minton, Russell L; Bhuiyan, Swapan; Harmson, Jeremy S; Findley, Ann M

    2014-10-01

    A recent explosion in the amount of genomic data has revealed a large genetic diversity in the bacteriophages that infect Mycobacterium smegmatis. In an effort to assess the novelty of newly described mycobacteriophage isolates and provide a preliminary determination of their probable cluster assignment prior to full genome sequencing, we have developed a systematic approach that relies on restriction endonuclease analysis. We demonstrate that a web-based tool, the Phage Enzyme Tool (or PET), is capable of rapidly facilitating this analysis and exhibits reliability in the putative placement of mycobacteriophages into specific clusters of previously sequenced phages. We propose that this tool represents a useful analytical step in the initial study of phage genomes and that this tool will increase the efficiency of phage genome characterization and enhance the educational activities involving mycobacteriophage discovery. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. XGet: a highly scalable and efficient file transfer tool for clusters

    Energy Technology Data Exchange (ETDEWEB)

    Greenberg, Hugh [Los Alamos National Laboratory; Ionkov, Latchesar [Los Alamos National Laboratory; Minnich, Ronald [SNL

    2008-01-01

    As clusters rapidly grow in size, transferring files between nodes can no longer be solved by the traditional transfer utilities due to their inherent lack of scalability. In this paper, we describe a new file transfer utility called XGet, which was designed to address the scalability problem of standard tools. We compared XGet against four transfer tools: Bittorrent, Rsync, TFTP, and Udpcast and our results show that XGet's performance is superior to the these utilities in many cases.

  4. 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.

  5. Optimal Machine Tools Selection Using Interval-Valued Data FCM Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Yupeng Xin

    2014-01-01

    Full Text Available Machine tool selection directly affects production rates, accuracy, and flexibility. In order to quickly and accurately select the appropriate machine tools in machining process planning, this paper proposes an optimal machine tools selection method based on interval-valued data fuzzy C-means (FCM clustering algorithm. We define the machining capability meta (MAE as the smallest unit to describe machining capacity of machine tools and establish MAE library based on the MAE information model. According to the manufacturing process requirements, the MAEs can be queried from MAE library. Subsequently, interval-valued data FCM algorithm is used to select the appropriate machine tools for manufacturing process. Through computing matching degree between manufacturing process machining constraints and MAEs, we get the most appropriate MAEs and the corresponding machine tools. Finally, a case study of an exhaust duct part of the aeroengine is presented to demonstrate the applicability of the proposed method.

  6. Multi-netclust: an efficient tool for finding connected clusters in multi-parametric networks.

    Science.gov (United States)

    Kuzniar, Arnold; Dhir, Somdutta; Nijveen, Harm; Pongor, Sándor; Leunissen, Jack A M

    2010-10-01

    Multi-netclust is a simple tool that allows users to extract connected clusters of data represented by different networks given in the form of matrices. The tool uses user-defined threshold values to combine the matrices, and uses a straightforward, memory-efficient graph algorithm to find clusters that are connected in all or in either of the networks. The tool is written in C/C++ and is available either as a form-based or as a command-line-based program running on Linux platforms. The algorithm is fast, processing a network of > 10(6) nodes and 10(8) edges takes only a few minutes on an ordinary computer. http://www.bioinformatics.nl/netclust/.

  7. 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.

  8. 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.

  9. Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads.

    Science.gov (United States)

    Chong, Zechen; Ruan, Jue; Wu, Chung-I

    2012-11-01

    The innovation of restriction-site associated DNA sequencing (RAD-seq) method takes full advantage of next-generation sequencing technology. By clustering paired-end short reads into groups with their own unique tags, RAD-seq assembly problem is divided into subproblems. Fast and accurately clustering and assembling millions of RAD-seq reads with sequencing errors, different levels of heterozygosity and repetitive sequences is a challenging question. Rainbow is developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq. First, Rainbow clusters reads using a spaced seed method. Then, Rainbow implements a heterozygote calling like strategy to divide potential groups into haplotypes in a top-down manner. And along a guided tree, it iteratively merges sibling leaves in a bottom-up manner if they are similar enough. Here, the similarity is defined by comparing the 2nd reads of a RAD segment. This approach tries to collapse heterozygote while discriminate repetitive sequences. At last, Rainbow uses a greedy algorithm to locally assemble merged reads into contigs. Rainbow not only outputs the optimal but also suboptimal assembly results. Based on simulation and a real guppy RAD-seq data, we show that Rainbow is more competent than the other tools in dealing with RAD-seq data. Source code in C, Rainbow is freely available at http://sourceforge.net/projects/bio-rainbow/files/

  10. 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.

  11. 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.

  12. 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

  13. Ancillary services analysis of an offshore wind farm cluster-technical integration steps of a simulation tool

    OpenAIRE

    Hennig, Tobias; Löwer, Lothar; Faiella, Luis Mariano; Stock, Sebastian; Jansen, Malte; Hofmann, Lutz; Rohrig, Kurt

    2014-01-01

    In this publication, the authors present methodology and example results for the analysis of ancillary services of an offshore wind farm cluster and its electrical power system. Thereby the operation tool Wind Cluster Management System (WCMS) is used as simulation tool to evaluate certain planning scenarios. Emphasis is made on two topics: 1) the integration of high voltage direct current (HVDC) technology to the WCMS, 2) the ancillary service analysis. As examples, voltage source converter b...

  14. 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...... 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...

  15. Clustered lot quality assurance sampling: a pragmatic tool for timely assessment of vaccination coverage.

    Science.gov (United States)

    Greenland, K; Rondy, M; Chevez, A; Sadozai, N; Gasasira, A; Abanida, E A; Pate, M A; Ronveaux, O; Okayasu, H; Pedalino, B; Pezzoli, L

    2011-07-01

    To evaluate oral poliovirus vaccine (OPV) coverage of the November 2009 round in five Northern Nigeria states with ongoing wild poliovirus transmission using clustered lot quality assurance sampling (CLQAS). We selected four local government areas in each pre-selected state and sampled six clusters of 10 children in each Local Government Area, defined as the lot area. We used three decision thresholds to classify OPV coverage: 75-90%, 55-70% and 35-50%. A full lot was completed, but we also assessed in retrospect the potential time-saving benefits of stopping sampling when a lot had been classified. We accepted two local government areas (LGAs) with vaccination coverage above 75%. Of the remaining 18 rejected LGAs, 11 also failed to reach 70% coverage, of which four also failed to reach 50%. The average time taken to complete a lot was 10 h. By stopping sampling when a decision was reached, we could have classified lots in 5.3, 7.7 and 7.3 h on average at the 90%, 70% and 50% coverage targets, respectively. Clustered lot quality assurance sampling was feasible and useful to estimate OPV coverage in Northern Nigeria. The multi-threshold approach provided useful information on the variation of IPD vaccination coverage. CLQAS is a very timely tool, allowing corrective actions to be directly taken in insufficiently covered areas. © 2011 Blackwell Publishing Ltd.

  16. clusters

    Indian Academy of Sciences (India)

    2017-09-27

    Sep 27, 2017 ... while CuCoNO, Co3NO, Cu3CoNO, Cu2Co3NO, Cu3Co3NO and Cu6CoNO clusters display stronger chemical stability. Magnetic and electronic properties are also discussed. The magnetic moment is affected by charge transfer and the spd hybridization. Keywords. CumConNO (m + n = 2–7) clusters; ...

  17. 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

  18. 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

  19. 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

  20. cluster

    Indian Academy of Sciences (India)

    has been investigated electrochemically in positive and negative microenvironments, both in solution and in film. Charge nature around the active centre ... in plants, bacteria and also in mammals. This cluster is also an important constituent of a ..... selection of non-cysteine amino acid in the active centre of Rieske proteins.

  1. Clustering Disjoint HJ-Biplot: A new tool for identifying pollution patterns in geochemical studies.

    Science.gov (United States)

    Nieto-Librero, A B; Sierra, C; Vicente-Galindo, M P; Ruíz-Barzola, O; Galindo-Villardón, M P

    2017-06-01

    This paper introduces a new mathematical algorithm termed Clustering Disjoint HJ-Biplot (CDBiplot), which searches for the underlying data structure in order to find the best classification of the object groups in a reduced space. To this end, disjoint factorial axes are generated, in which each variable only contributes to the formation of one factorial axis. A graphical representation of the individuals and variables is performed using the HJ-Biplot method. In order to facilitate the use of this new method within any practical context, a function in the language R has been developed. This work applies the CDBiplot to study an environmental geochemistry case involving environmental pollution in river surface sediments. The study focuses on an area close to an important mining and metallurgical site, where sediments share a similar geological origin and chemical composition. The algorithm permitted a detailed study of the geochemical interactions and performed an excellent separation of the samples. Thus, the groups obtained were formed according to a similar geological origin, location, and nature of the anthropogenic inputs based only on chemical composition data. These results allowed clear identification of the sources of pollution and the delimitation of the polluted zones. All things considered, we conclude that the proposed algorithm is a powerful tool for studying environmental geochemistry data sets, and suggest that the application of this methodology be extended to other research fields. Copyright © 2017 Elsevier Ltd. All rights reserved.

  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. Assessment tools for fuzzy clustered regions of interest for site-specific crop management

    Science.gov (United States)

    Meyer, George E.; Camargo Neto, Joao; Jones, David D.

    2004-03-01

    Fuzzy excess green (ExG) crisp indices and clustering algorithms such as the Gustafson-Kessel (GK) have been successfully used for unsupervised classification of hidden and prominent regions of interest (ROI"s), namely green plants in crop color images against bare clay soil, corn residue and wheat residue, typical of the Great Plains. Each process can be enhanced with Zadeh (Z) and Gath-Geva (GG) fuzzy enhancement techniques. Enhanced indices and clusters can be then sorted by final degree of fuzziness, and recombined into labeled, false-color class images, which can be used as templates for further shape and textural analyses. ROI"s with the lowest degree of fuzziness were consistently found to be plant clusters according to foveated or prominence of the region size within the image. Clustering performance according to partition densities and hyper volume was also evaluated. These latter measures can be used to select the number of clusters and evaluate the computational time needed to find plant ROI"s with complex backgrounds under different lighting conditions. Enhanced GK clustering methods have performed very well and have identified plants in bare soil, corn residue plants , and wheat straw plants, well into the high 90 percentages, depending on plant age category and the relative proportion of plant size within the image. Improved clustering algorithms with textural finger printing could be potentially useful for unsupervised remote sensing, mapping, crop management, weed, and pest control for precision agriculture.

  4. 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...

  5. RAMI: a tool for identification and characterization of phylogenetic clusters in microbial communities.

    Science.gov (United States)

    Pommier, Thomas; Canbäck, Björn; Lundberg, Per; Hagström, Ake; Tunlid, Anders

    2009-03-15

    The most common approach to estimate microbial diversity is based on the analysis of DNA sequences of specific target genes including ribosomal genes. Commonly, the sequences are grouped into operational taxonomic units based on genetic distance (sequence similarity) instead of genetic change (patristic distance). This method may fail to adequately identify clusters of evolutionary related sequences and it provides no information on the phylogenetic structure of the community. An ease-of-use web application for this purpose has been missing. We have developed RAMI, which clusters related nodes in a phylogenetic tree based on the patristic distance. RAMI also produces indices of cluster properties and other indices used in population and community studies on-the-fly. RAMI is licensed under GNU GPL and can be run or downloaded from http://www.acgt.se/online.html. http://www.acgt.se/RAMI/SuppInfo.

  6. Fuzzy Clustering Analysis in Environmental Impact Assessment--A Complement Tool to Environmental Quality Index.

    Science.gov (United States)

    Kung, Hsiang-Te; And Others

    1993-01-01

    In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. (Author)

  7. 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.

  8. Dynamic quantum clustering: a tool for visual exploration of structures in data

    Energy Technology Data Exchange (ETDEWEB)

    Weinstein, Marvin; /SLAC; Horn, David; /Tel Aviv U.

    2009-10-17

    A given set of data-points in some feature space may be associated with a Schroedinger equation whose potential is determined by the data. This is known to lead to good clustering solutions. Here we extend this approach into a full-fledged dynamical scheme using a time-dependent Schroedinger equation. Moreover, we approximate this Hamiltonian formalism by a truncated calculation within a set of Gaussian wave functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition or feature filtering.

  9. Dynamic Quantum Clustering: A Tool for Unsupervised Exploration of Structures in Data

    Energy Technology Data Exchange (ETDEWEB)

    Weinstein, Marvin; /SLAC; Horn, David; /Tel Aviv U.

    2008-10-30

    A given set of data-points in some feature space may be associated with a Schroedinger equation whose potential is determined by the data. This is known to lead to good clustering solutions. Here we extend this approach into a full-fledged dynamical scheme using a time-dependent Schroedinger equation with a small diffusion component. Moreover, we approximate this Hamiltonian formalism by a truncated calculation within a set of Gaussian wave functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition or feature filtering.

  10. 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

  11. 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.

  12. A novel preformulation tool to group microcrystalline celluloses using artificial neural network and data clustering.

    Science.gov (United States)

    Soh, Josephine L P; Chen, Fei; Liew, Celine V; Shi, Daming; Heng, Paul W S

    2004-12-01

    To group microcrystalline celluloses (MCCs) using a combination of artificial neural network (ANN) and data clustering. Radial basis function (RBF) network was used to model the torque measurements of the various MCCs. Output from the RBF network was used to group the MCCs using a data clustering technique known as discrete incremental clustering (DIC). Rheological or torque profiles of various MCCs at different combinations of mixing time and water:MCC ratios were obtained using mixer torque rheometry (MTR). Correlation analysis was performed on the derived torque parameter Torque(max) and physical properties of the MCCs. Depending on the leniency of the predefined threshold parameters, the 11 MCCs can be assigned into 2 or 3 groups. Grouping results were also able to identify bulk and tapped densities as major factors governing water-MCC interaction. MCCs differed in their water retentive capacities whereby the denser Avicel PH 301 and PH 302 were more sensitive to the added water. An objective grouping of MCCs can be achieved with a combination of ANN and DIC. This aids in the preliminary assessment of new or unknown MCCs. Key properties that control the performance of MCCs in their interactions with water can be discovered.

  13. 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...

  14. New tools for reconstruction and heterologous expression of natural product biosynthetic gene clusters.

    Science.gov (United States)

    Luo, Yunzi; Enghiad, Behnam; Zhao, Huimin

    2016-02-01

    Natural product scaffolds remain a major source and inspiration for human therapeutics. However, generation of a natural product in the post-genomic era often requires reconstruction of the corresponding biosynthetic gene cluster in a heterologous host. In the burgeoning fields of synthetic biology and metabolic engineering, a significant amount of efforts has been devoted to develop DNA assembly techniques with higher efficiency, fidelity, and modularity, and heterologous expression systems with higher productivity and yield. Here we describe recent advances in DNA assembly and host engineering and highlight their applications in natural product discovery and engineering.

  15. On Clustering during and after Crisis as the Tool for Analyzing the Global Economic Architecture

    Directory of Open Access Journals (Sweden)

    Kobylianska Alla V.

    2017-03-01

    Full Text Available The article is aimed at analyzing the development of global economy from the viewpoint of formation of ideas of its aggregation by means of the cluster analysis. It is found that during 1995-2014 in the world there were about 20 countries which GDP in total amounted to 80% of the global GDP. According to these data Japan, the USA, Germany, China, and Brazil formed a kernel of global economy. Further results of the cluster analysis have allowed to draw conclusions that during the observation period the United States and the Russian Federation remained the main centrodes of global economy. Despite the crisis of 2008, integration of global economy continued, most notably from the viewpoint of monetary indicators. The subsequent researches should be concerned with studying the economic policy directed to the internal economic development, the external relations, and formation of global economic policy, as well as to analyzing economic relations between the identified centrodes and other countries. This will help to understand the reasons of the contemporary global economic integration and to prognosticate its development in the future.

  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. 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.

    2018-03-01

    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 analyze 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 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 super massive star nucleosynthesis.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. A Multi-component Matched Filter Cluster Confirmation Tool for eROSITA: Initial Application to the RASS and DES-SV Datasets

    Energy Technology Data Exchange (ETDEWEB)

    Klein, M.; et al.

    2017-06-20

    We describe a multi-component matched filter cluster confirmation tool (MCMF) designed for the study of large X-ray source catalogs produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts $0.05cluster catalogs and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is $\\delta z / (1+z)=0.010$. We find a well defined X-ray luminosity-$\\lambda_{\\mathrm{MCMF}}$ relation with an intrinsic scatter of $\\delta \\ln(\\lambda_\\mathrm{MCMF}| L_\\mathrm{x})=0.21$. Matching our catalog with the DES-SV redMaPPer catalog yields good agreement in redshift and richness estimates; comparing our catalog with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our dataset are consistent with the high mass extension of the RASS based $\\lambda_{\\mathrm{MCMF}}$-mass relation

  6. 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

    2018-01-01

    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

  7. 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

  8. 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

  9. 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)

  10. A comprehensive tool for efficient design and operation of polygeneration-based energy μgrids serving a cluster of buildings. Part II: Analysis of the applicative potential

    International Nuclear Information System (INIS)

    Piacentino, Antonio; Barbaro, Chiara

    2013-01-01

    Highlights: ► A tool for the optimization of CHCP systems is applied to a four-buildings case study. ► Analyses are performed for both individual buildings and clusters of buildings. ► Effects of the width of temporal basis on results’ reliability are discussed. ► Sensitivity of plant design and operation to economic and normative provisions is studied. ► The tool reveals useful for both private investors and energy policy makers. - Abstract: The potential of polygeneration systems, in terms of profitability, energy saving and pollutant emissions reduction, highly depends on several factors such as plant efficiency, local normative and tariff conditions and reference technologies adopted to compare the results. In Part I of this paper a reliable tool was described, capable of optimizing the lay-out, design and operation of an integrated polygeneration system serving a cluster of buildings with their heat, cooling and power demand; the tool represents an excellent instrument to perform sensitivity analyses, thus enabling the analyst to formulate general design criteria and predict the effects of any change in the boundary conditions or in the normative provisions concerning support mechanisms for polygeneration plants. In this Part II of the paper, with reference to a cluster of four buildings located over a small area, once assumed a fixed topology of the site (in terms of distance between buildings) the sensitivity of plant design and operation is investigated, posing a particular focus on some context conditions: (1) the minimum primary energy saving imposed for the “high efficient cogeneration” assessment, (2) the reference efficiency of “separate power production” systems adopted to evaluate energy savings, (3) the local energy prices and (4) the incidence of tax exemption for the fuel consumed by polygeneration plants. The sensitivity analyses are preceded by an accurate study on the robustness of solutions, performed by assuming different

  11. 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)

  12. Advanced analysis tool for X-ray photoelectron spectroscopy profiling: Cleaning of perovskite SrTiO{sub 3} oxide surface using argon cluster ion source

    Energy Technology Data Exchange (ETDEWEB)

    Aureau, D., E-mail: damien.aureau@uvsq.fr [Institut Lavoisier de Versailles, (UMR 8180) Université de Versailles-Saint-Quentin-en-Yvelines–CNRS, 45 Av. des États-Unis, 78035 Versailles (France); Ridier, K. [Institut Lavoisier de Versailles, (UMR 8180) Université de Versailles-Saint-Quentin-en-Yvelines–CNRS, 45 Av. des États-Unis, 78035 Versailles (France); Groupe d' Étude de la Matière Condensée (UMR 8635) Université de Versailles Saint-Quentin-en-Yvelines–CNRS, 45 Av. des États-Unis, 78035 Versailles (France); Bérini, B.; Dumont, Y.; Keller, N. [Groupe d' Étude de la Matière Condensée (UMR 8635) Université de Versailles Saint-Quentin-en-Yvelines–CNRS, 45 Av. des États-Unis, 78035 Versailles (France); Vigneron, J.; Bouttemy, M.; Etcheberry, A. [Institut Lavoisier de Versailles, (UMR 8180) Université de Versailles-Saint-Quentin-en-Yvelines–CNRS, 45 Av. des États-Unis, 78035 Versailles (France); Fouchet, A. [Groupe d' Étude de la Matière Condensée (UMR 8635) Université de Versailles Saint-Quentin-en-Yvelines–CNRS, 45 Av. des États-Unis, 78035 Versailles (France)

    2016-02-29

    This article shows the comparison between three different ionic bombardments during X-ray photoelectron spectroscopy (XPS) studies of single crystalline SrTiO{sub 3} (STO) substrates. The abrasion using a “cluster argon ion source” is compared with the standard “monoatomic Ar”. The influence of the energy of the monoatomic ions used is clearly demonstrated. While the chemically adsorbed species on the STO surface are removed, such bombardment strongly modifies the surface. A reduction of part of the titanium atoms and the appearance of a different chemical environment for surface strontium atoms are observed. Implantation of argon ions is also detected. Cluster ion etching is used on oxide surface and, in this case only, due to a much lower kinetic energy per atom compared to monoatomic ions, the possibility to remove surface contaminants at the surface without modification of the XP spectra is clearly demonstrated, ensuring that the stoichiometry of the surface is preserved. Such result is crucial for everybody working with oxide surfaces to obtain a non-modified XPS analysis. The progressive effect of this powerful tool allows the monitoring of the removal of surface contamination in the first steps of the bombardment which was not achievable with usual guns. - Highlights: • The effects of three argon etchings are studied as a function of time on SrTiO3 oxide. • A method for obtaining non-modified chemical analysis of oxides is presented. • The soft removal of adsorbed species thanks to argon cluster is demonstrated. • The damages induced on SrTiO3 surface by ionic bombardment are shown. • The influence of the kinetic energy of incoming Ar atoms is examined.

  13. 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

  14. Effectiveness of the Assessment of Burden of Chronic Obstructive Pulmonary Disease (ABC) tool: study protocol of a cluster randomised trial in primary and secondary care.

    Science.gov (United States)

    Slok, Annerika H M; In 't Veen, Johannes C C M; Chavannes, Niels H; van der Molen, Thys; Mölken, Maureen Pmh Rutten-van; Kerstjens, Huib A M; Asijee, Guus M; Salomé, Philippe L; Holverda, Sebastiaan; Dekhuijzen, Richard P N; Schuiten, Denise; van Breukelen, Gerard; Kotz, Daniel; van Schayck, Onno C P

    2014-08-07

    Chronic Obstructive Pulmonary Disease (COPD) is a growing worldwide problem that imposes a great burden on the daily life of patients. Since there is no cure, the goal of treating COPD is to maintain or improve quality of life. We have developed a new tool, the Assessment of Burden of COPD (ABC) tool, to assess and visualize the integrated health status of patients with COPD, and to provide patients and healthcare providers with a treatment algorithm. This tool may be used during consultations to monitor the burden of COPD and to adjust treatment if necessary. The aim of the current study is to analyse the effectiveness of the ABC tool compared with usual care on health related quality of life among COPD patients over a period of 18 months. A cluster randomised controlled trial will be conducted in COPD patients in both primary and secondary care throughout the Netherlands. An intervention group, receiving care based on the ABC tool, will be compared with a control group receiving usual care. The primary outcome will be the change in score on a disease-specific-quality-of-life questionnaire, the Saint George Respiratory Questionnaire. Secondary outcomes will be a different questionnaire (the COPD Assessment Test), lung function and number of exacerbations. During the 18 months follow-up, seven measurements will be conducted, including a baseline and final measurement. Patients will receive questionnaires to be completed at home. Additional data, such as number of exacerbations, will be recorded by the patients' healthcare providers. A total of 360 patients will be recruited by 40 general practitioners and 20 pulmonologists. Additionally, a process evaluation will be performed among patients and healthcare providers. The new ABC tool complies with the 2014 Global Initiative for Chronic Obstructive Lung Disease guidelines, which describe the necessity to classify patients on both their airway obstruction and a comprehensive symptom assessment. It has been developed

  15. 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

  16. Bussines Clusters

    Directory of Open Access Journals (Sweden)

    Sarmiza Pencea

    2010-10-01

    Full Text Available Clusters are complex economic structures in which similar companies, their up-stream and down-stream business partners, universities, research institutes, educational units, various service providers, diverse private and public institutions concentrate geografically, striving to get economies of agglomeration and scale, to capitalize on the resulting spill over effects, to cut costs, to better harness resources, to exchange information and experience, to improve quality, innovation, skills and productivity. By somehow unexpectedly combining competition and cooperation, they form a new, sophisticated stage in the evolution of production structures in quest of higher efficiency. This paper forays into the world of clusters and clusterization, which seem to increasingly capture the interest of businesses, scholars and policy makers. It looks at what clusters are, how they arise, what are their specific features, what benefits and challenges they can generate for companies and for the regions in which they locate and if and how they should be fostered by industrial policy interventions. The conclusion is that clusters can be very important development triggers and therefore they should be encouraged and nurtured by adequate policy measures. They should not only be used as a regular policy tool, but be placed at the very center of the development strategies of emerging economies.

  17. FINDCLUS : Fuzzy INdividual Differences CLUStering

    NARCIS (Netherlands)

    Giordani, Paolo; Kiers, Henk A. L.

    ADditive CLUStering (ADCLUS) is a tool for overlapping clustering of two-way proximity matrices (objects x objects). In Simple Additive Fuzzy Clustering (SAFC), a variant of ADCLUS is introduced providing a fuzzy partition of the objects, that is the objects belong to the clusters with the so-called

  18. Excitations in clusters

    International Nuclear Information System (INIS)

    Bertsch, G.F.

    2001-01-01

    Statistical reaction theory is an important tool for understanding dynamic processes in clusters as well as for extracting information about theirs energetics. The author reviews the statistical reaction theory and establishes formulas concerning cluster evaporation rates, electron emission and radiative cooling. The author recalls a number of useful formulas for describing the electromagnetic properties of small particles, generalizes them and applies them in the case of alkali metal clusters and of silver clusters. The author ends discussing carbon structures, going from small clusters and molecules to fullerenes and nano-tubes. (A.C.)

  19. 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

  20. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

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

    2008-01-01

    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...... 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...... 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...

  1. 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 ...

  2. 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...

  3. CLEAN: CLustering Enrichment ANalysis

    Science.gov (United States)

    Freudenberg, Johannes M; Joshi, Vineet K; Hu, Zhen; Medvedovic, Mario

    2009-01-01

    -expressed genes over using the traditional cluster-wide scores. Using gene-specific coherence scores also simplifies the comparisons of clusterings produced by different clustering algorithms and provides a simple tool for selecting genes with a "functionally coherent" expression profile. PMID:19640299

  4. 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

  5. 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.

  6. 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.

  7. Cluster Headache

    Science.gov (United States)

    ... re at risk of cluster headache. A family history. Having a parent or sibling who has had cluster headache might ... of Nondiscrimination Advertising Mayo Clinic is a not-for-profit organization ...

  8. 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.

  9. Whole genome sequencing as a tool to investigate a cluster of seven cases of listeriosis in Austria and Germany, 2011–2013

    Science.gov (United States)

    Schmid, D; Allerberger, F; Huhulescu, S; Pietzka, A; Amar, C; Kleta, S; Prager, R; Preußel, K; Aichinger, E; Mellmann, A; Raoult, D

    2014-01-01

    A cluster of seven human cases of listeriosis occurred in Austria and in Germany between April 2011 and July 2013. The Listeria monocytogenes serovar (SV) 1/2b isolates shared pulsed-field gel electrophoresis (PFGE) and fluorescent amplified fragment length polymorphism (fAFLP) patterns indistinguishable from those from five food producers. The seven human isolates, a control strain with a different PFGE/fAFLP profile and ten food isolates were subjected to whole genome sequencing (WGS) in a blinded fashion. A gene-by-gene comparison (multilocus sequence typing (MLST)+) was performed, and the resulting whole genome allelic profiles were compared using SeqSphere+ software version 1.0. On analysis of 2298 genes, the four human outbreak isolates from 2012 to 2013 had different alleles at ≤6 genes, i.e. differed by ≤6 genes from each other; the dendrogram placed these isolates in between five Austrian unaged soft cheese isolates from producer A (≤19-gene difference from the human cluster) and two Austrian ready-to-eat meat isolates from producer B (≤8-gene difference from the human cluster). Both food products appeared on grocery bills prospectively collected by these outbreak cases after hospital discharge. Epidemiological results on food consumption and MLST+ clearly separated the three cases in 2011 from the four 2012–2013 outbreak cases (≥48 different genes). We showed that WGS is capable of discriminating L. monocytogenes SV1/2b clones not distinguishable by PFGE and fAFLP. The listeriosis outbreak described clearly underlines the potential of sequence-based typing methods to offer enhanced resolution and comparability of typing systems for public health applications. PMID:24698214

  10. Whole genome sequencing as a tool to investigate a cluster of seven cases of listeriosis in Austria and Germany, 2011-2013.

    Science.gov (United States)

    Schmid, D; Allerberger, F; Huhulescu, S; Pietzka, A; Amar, C; Kleta, S; Prager, R; Preußel, K; Aichinger, E; Mellmann, A

    2014-05-01

    A cluster of seven human cases of listeriosis occurred in Austria and in Germany between April 2011 and July 2013. The Listeria monocytogenes serovar (SV) 1/2b isolates shared pulsed-field gel electrophoresis (PFGE) and fluorescent amplified fragment length polymorphism (fAFLP) patterns indistinguishable from those from five food producers. The seven human isolates, a control strain with a different PFGE/fAFLP profile and ten food isolates were subjected to whole genome sequencing (WGS) in a blinded fashion. A gene-by-gene comparison (multilocus sequence typing (MLST)+) was performed, and the resulting whole genome allelic profiles were compared using SeqSphere(+) software version 1.0. On analysis of 2298 genes, the four human outbreak isolates from 2012 to 2013 had different alleles at ≤6 genes, i.e. differed by ≤6 genes from each other; the dendrogram placed these isolates in between five Austrian unaged soft cheese isolates from producer A (≤19-gene difference from the human cluster) and two Austrian ready-to-eat meat isolates from producer B (≤8-gene difference from the human cluster). Both food products appeared on grocery bills prospectively collected by these outbreak cases after hospital discharge. Epidemiological results on food consumption and MLST+ clearly separated the three cases in 2011 from the four 2012-2013 outbreak cases (≥48 different genes). We showed that WGS is capable of discriminating L. monocytogenes SV1/2b clones not distinguishable by PFGE and fAFLP. The listeriosis outbreak described clearly underlines the potential of sequence-based typing methods to offer enhanced resolution and comparability of typing systems for public health applications. © 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

  11. 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)

  12. Effectiveness of the Assessment of Burden of Chronic Obstructive Pulmonary Disease (ABC) tool: Study protocol of a cluster randomised trial in primary and secondary care

    NARCIS (Netherlands)

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

    2014-01-01

    markdownabstractAbstract Background Chronic Obstructive Pulmonary Disease (COPD) is a growing worldwide problem that imposes a great burden on the daily life of patients. Since there is no cure, the goal of treating COPD is to maintain or improve quality of life. We have developed a new tool,

  13. Effectiveness of the Assessment of Burden of Chronic Obstructive Pulmonary Disease (ABC) tool: : study protocol of a cluster randomised trial in primary and secondary care

    NARCIS (Netherlands)

    Slok, Annerika H. M.; 't Veen, Johannes C. C. M. In; Chavannes, Niels H.; van der Molen, Thys; Rutten-van Molken, Maureen P. M. H.; Kerstjens, Huib A. M.; Asijee, Guus M.; Salome, Philippe L.; Holverda, Sebastiaan; Dekhuijzen, Richard P. N.; Schuiten, Denise; van Breukelen, Gerard; Kotz, Daniel; van Schayck, Onno C. P.

    2014-01-01

    Background: Chronic Obstructive Pulmonary Disease (COPD) is a growing worldwide problem that imposes a great burden on the daily life of patients. Since there is no cure, the goal of treating COPD is to maintain or improve quality of life. We have developed a new tool, the Assessment of Burden of

  14. Enhancing the use of Asthma and COPD Assessment Tools in Balearic Primary Care (ACATIB) : a region-wide cluster-controlled implementation trial

    NARCIS (Netherlands)

    Román-Rodríguez, Miguel; Pardo, Marina Garcia; López, Lucia Gorreto; Ruiz, Ana Uréndez; van Boven, Job Fm

    2016-01-01

    Asthma and chronic obstructive pulmonary disease (COPD) health status assessment tools have demonstrated their value in guiding clinical management. Their use in primary care is still suboptimal. The objective of this study was to assess the effect of an educational intervention programme on the use

  15. Using LC and Hierarchical Cluster Analysis as Tools to Distinguish Timbó Collections into Two Deguelia Species: A Contribution to Chemotaxonomy.

    Science.gov (United States)

    da Costa, Danielle; E Silva, Consuelo; Pinheiro, Aline; Frommenwiler, Débora; Arruda, Mara; Guilhon, Giselle; Alves, Cláudio; Arruda, Alberto; Da Silva, Milton

    2016-04-30

    The species Deguelia utilis and Deguelia rufescens var. urucu, popularly known as "timbó," have been used for many years as rotenone sources in insecticide formulations. In this work, a method was developed and validated using a high-performance liquid chromatography-photodiode array (HPLC-PDA) system, and results were analyzed using hierarchical cluster analysis (HCA). By quantifying the major rotenoids of these species, it was possible to establish a linear relation between them. The ratio between the concentrations of rotenone and deguelin for D. utilis is approximately 1:0.8, respectively, while for D. rufescens var. urucu it is 2:1. These results may help to distinguish these species contributing to their taxonomic identification.

  16. Using LC and Hierarchical Cluster Analysis as Tools to Distinguish Timbó Collections into Two Deguelia Species: A Contribution to Chemotaxonomy

    Directory of Open Access Journals (Sweden)

    Danielle da Costa

    2016-04-01

    Full Text Available The species Deguelia utilis and Deguelia rufescens var. urucu, popularly known as “timbó,” have been used for many years as rotenone sources in insecticide formulations. In this work, a method was developed and validated using a high-performance liquid chromatography-photodiode array (HPLC-PDA system, and results were analyzed using hierarchical cluster analysis (HCA. By quantifying the major rotenoids of these species, it was possible to establish a linear relation between them. The ratio between the concentrations of rotenone and deguelin for D. utilis is approximately 1:0.8, respectively, while for D. rufescens var. urucu it is 2:1. These results may help to distinguish these species contributing to their taxonomic identification.

  17. 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

  18. Weighted Clustering

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...

  19. 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...

  20. 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.

  1. 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.

  2. GibbsCluster: unsupervised clustering and alignment of peptide sequences

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

    2017-01-01

    -ligand system or of the assay used to interrogate it, experimental data often contain multiple sequence motifs. GibbsCluster is a powerful tool for unsupervised motif discovery because it can simultaneously cluster and align peptide data. The GibbsCluster 2.0 presented here is an improved version incorporating......-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0....... insertion and deletions accounting for variations in motif length in the peptide input. In basic terms, the program takes as input a set of peptide sequences and clusters them into meaningful groups. It returns the optimal number of clusters it identified, together with the sequence alignment and sequence...

  3. 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.

  4. 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

  5. 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

  6. Subgrouping for patients with low back pain: a multidimensional approach incorporating cluster analysis and the STarT Back Screening Tool.

    Science.gov (United States)

    Beneciuk, Jason M; Robinson, Michael E; George, Steven Z

    2015-01-01

    Early screening for psychological distress has been suggested to improve patient management for individuals experiencing low back pain. This study compared 2 approaches to psychological screening (ie, multidimensional and unidimensional) so that preliminary recommendations on which approach may be appropriate for use in clinical settings other than primary care could be provided. Specifically, this study investigated aspects of the STarT Back Screening Tool (SBT): 1) discriminant validity by evaluating its relationship with unidimensional psychological measures and 2) construct validity by evaluating how SBT risk categories compared to empirically derived subgroups using unidimensional psychological and disability measures. Patients (N = 146) receiving physical therapy for LBP were administered the SBT and a battery of unidimensional psychological measures at initial evaluation. Clinical measures consisted of pain intensity and self-reported disability. Several SBT risk-dependent relationships (ie, SBT low low profiles; therefore, 2 groups may provide a clearer representation of the level of pain-associated psychological distress, maladaptive coping, and disability in this setting compared with 3 groups as suggested when using the SBT in primary care settings. This study suggests that the SBT can replace administering several unidimensional psychological measures as a first-line screening measure for psychological distress. However, clinicians need to be aware of the potential for misclassification with SBT results when compared to unidimensional measures. This study also suggests that a modified SBT risk stratification scheme based on empirically derived subgroups could potentially assist in identifying elevated levels of pain-associated psychological distress, maladaptive coping, and disability in practice settings outside of primary care. Patients identified with elevated levels of pain-associated distress and maladaptive coping may be indicated for

  7. 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…

  8. Cancer Clusters

    Science.gov (United States)

    ... Peer Review and Funding Outcomes Step 4: Award Negotiation & Issuance Manage Your Award Grants Management Contacts Monitoring ... potentially hazardous working conditions, including suspected cancer clusters. Employees, authorized employee representatives, and employers can request these ...

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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

    2016-07-11

    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. A pragmatic cluster randomised controlled trial, in 39 Dutch primary care practices and 17 hospitals, with 357 patients with COPD (postbronchodilator FEV1/FVC ratio 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). 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). This study showed that use of the ABC tool may increase quality of life and perceived quality of care. NTR3788; Results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  14. 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

  15. 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

  16. Fuzzy Clustering

    DEFF Research Database (Denmark)

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

    2000-01-01

    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...

  17. Cluster Matters

    DEFF Research Database (Denmark)

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

    2018-01-01

    In this chapter, we investigate corporate social responsibility (CSR) in industrial clusters in the Indian context. We use the definition of CSR as given in the Indian Ministry of Corporate Affairs’ National Voluntary Guidelines (NVGs) for Business Responsibility: ‘the commitment of an enterprise...

  18. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    , Portugal and New Zealand have adopted the concept. Public sector interventions that aim to support cluster development in industries most often focus upon economic policy goals such as enhanced employment and improved productivity, but rarely emphasise broader societal policy goals relating to e.......g. sustainability or quality of life. The purpose of this paper is to explore how and to what extent public sector interventions that aim at forcing cluster development in industries can support sustainable development as defined in the Brundtland tradition and more recently elaborated in such concepts as eco...... in 2000 by the Welsh Automotive Task Force under the Welsh Assembly Government. The Accelerate programme takes basically different two directions: The first one, which was the first to be launched, is concerned with the upgrading of existing supply chains in the automotive industry in Wales. The programme...

  19. 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,...

  20. 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

  1. 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.

    Directory of Open Access Journals (Sweden)

    Lara R Fairall

    2016-11-01

    Full Text Available 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

  2. Photoionization Spectroscopy of Clusters

    Science.gov (United States)

    Dao, Phan Danh

    Studies of the electronic energies in van der Waals molecules (sometimes referred to as clusters or complexes) help one unravel the microscopic details of the condensed state. Furthermore, they provide the connection between gas-phase and condensed-phase sciences. To achieve this goal, we undertake (1) the spectroscopic studies of van der Waals complexes; (2) the determination of the ionization energies of van der Waals complexes, as well as of mixed alkali metal clusters (e.g., K(,n)O); and (3) the studies of processes that occur upon and after the ionization of van der Waals molecules (namely, dissociation and intracluster reactions). A brief discussion of the non-equilibrium synthesis of weakly bound molecules is given. The operation and performance of the pulsed supersonic jet are described along with some theoretical considerations. The characteristic features of the technique of laser ionization are presented with emphasis on its performance as a spectroscopic tool. Resonance two-photon ionization and time-of-flight mass spectrometry provide us with the tool to measure the perturbed electronic excited state of van der Waals complexes. In these studies, the chromophore species is an aromatic molecule having a single ring (phenylacetylene and para-xylene); and the "solvent" species are rare gas atoms, as well as a variey of molecules. In the case of chromophore-rare gas complexes, the S(,1) excited state is red-shifted, with respect to the nascent chromophore, and the magnitude of the shift shows a definite dependence on the atomic polarizability. Other salient trends of the measured spectral shifts are also discussed. In the measurement of complex ionization energies, the use of two tunable UV lasers is required. With p-xylene(.)Ar(,n) complexes (n = 1-6), these energies vary almost linearly with the number of atoms. Also discussed in the text are the effects of ionization in a weak DC field. A simple hydrogenic model of field-ionization is experimentally

  3. 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

  4. 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....... 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......-ranging comparison we were able to develop a short guideline for biomedical clustering tasks. ClustEval allows biomedical researchers to pick the appropriate tool for their data type and allows method developers to compare their tool to the state of the art....

  5. 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...... and real world datasets and discuss some future research directions with the approach....

  6. 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)

  7. Heavy hitters via cluster-preserving clustering

    DEFF Research Database (Denmark)

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

    2016-01-01

    , 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...... problem in which each heavy hitter is encoded as some form of noisy spectral cluster in a much bigger graph, and the goal is to identify every cluster. Since every heavy hitter must be found, correctness requires that every cluster be found. We thus need a "cluster-preserving clustering" algorithm......, that partitions the graph into clusters with the promise of not destroying any original cluster. To do this we first apply standard spectral graph partitioning, and then we use some novel combinatorial techniques to modify the cuts obtained so as to make sure that the original clusters are sufficiently preserved...

  8. 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...

  9. 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.

  10. 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...

  11. 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/.

  12. 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.

  13. 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...

  14. 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

  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. 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.

  17. 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

  18. SSI-OSCAR: a Cluster Distribution for High Performance Computing Using a Single System Image

    OpenAIRE

    Vallée , Geoffroy; Scott , Stephen ,; Morin , Christine; Berthou , Jean-Yves; Prisker , Hugues

    2005-01-01

    The ease use and management of clusters needs tools to install, update and transparently manage distributed clusters resources. The management of clusters (node installations and updates) is a well-known problem and some high performance computing specific distributions are available today. These distributions, like OSCAR, allow users to install and manage clusters without specialized knowledge, allowing quick cluster deployment. The ease use of cluster is possible globally and transparently ...

  19. 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.

  20. Cluster knockout reactions

    Indian Academy of Sciences (India)

    2014-04-07

    Apr 7, 2014 ... Cluster knockout reactions are expected to reveal the amount of clustering (such as that of , d and even of heavier clusters such as 12C, 16O etc.) in the target nucleus. In simple terms, incident medium high-energy nuclear projectile interacts strongly with the cluster (present in the target nucleus) as if it ...

  1. 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...

  2. Automated clustering-based workload characterization

    Science.gov (United States)

    Pentakalos, Odysseas I.; Menasce, Daniel A.; Yesha, Yelena

    1996-01-01

    The demands placed on the mass storage systems at various federal agencies and national laboratories are continuously increasing in intensity. This forces system managers to constantly monitor the system, evaluate the demand placed on it, and tune it appropriately using either heuristics based on experience or analytic models. Performance models require an accurate workload characterization. This can be a laborious and time consuming process. It became evident from our experience that a tool is necessary to automate the workload characterization process. This paper presents the design and discusses the implementation of a tool for workload characterization of mass storage systems. The main features of the tool discussed here are: (1)Automatic support for peak-period determination. Histograms of system activity are generated and presented to the user for peak-period determination; (2) Automatic clustering analysis. The data collected from the mass storage system logs is clustered using clustering algorithms and tightness measures to limit the number of generated clusters; (3) Reporting of varied file statistics. The tool computes several statistics on file sizes such as average, standard deviation, minimum, maximum, frequency, as well as average transfer time. These statistics are given on a per cluster basis; (4) Portability. The tool can easily be used to characterize the workload in mass storage systems of different vendors. The user needs to specify through a simple log description language how the a specific log should be interpreted. The rest of this paper is organized as follows. Section two presents basic concepts in workload characterization as they apply to mass storage systems. Section three describes clustering algorithms and tightness measures. The following section presents the architecture of the tool. Section five presents some results of workload characterization using the tool.Finally, section six presents some concluding remarks.

  3. Clustering in analytical chemistry.

    Science.gov (United States)

    Drab, Klaudia; Daszykowski, Michal

    2014-01-01

    Data clustering plays an important role in the exploratory analysis of analytical data, and the use of clustering methods has been acknowledged in different fields of science. In this paper, principles of data clustering are presented with a direct focus on clustering of analytical data. The role of the clustering process in the analytical workflow is underlined, and its potential impact on the analytical workflow is emphasized.

  4. 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.

  5. Clustering of Lyman-Alpha Emitters galaxies

    Science.gov (United States)

    Francke, Harold

    2009-06-01

    Galaxy clustering properties have been studied for decades to constrain cosmological parameters and have today, with large datasets of high-redshift sources piling up, become a powerful tool to discriminate and characterize primeval galaxies. In the last years, several Lyman-Alpha Emitter (LAE) galaxy samples have been gathered, which are big, uniform and compact enough to allow clustering analysis. Here we present a summary of the discussion session on the clustering properties of LAEs at the "Understanding Lyman-Alpha Emitters" conference.

  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. Laboratory study of gravel-bed cluster formation and disintegration

    Science.gov (United States)

    Heays, K. G.; Friedrich, H.; Melville, B. W.

    2014-03-01

    Increased knowledge of clusters is essential for the understanding of sediment transport behavior and the monitoring and protection of aquatic life. A physical study using graded river gravels is conducted in a laboratory environment. Using photogrammetry and painted gravels, a cluster identification tool (CIT) is developed based on image subtraction between subsequent frames, allowing identification of any stable areas and groups of particles on the bed. This is combined with digital particle tracking (DPT) to present a novel approach for monitoring the formation and disintegration of clusters. Clusters from graded gravels are formed successfully during the experimental stage, allowing investigation into the complex dynamic behavior of cluster formation and disintegration in a simulated natural environment. Various anchor stone arrangements are used in the experiments. However, only about one fifth of the potential anchor stones on the bed surface enable cluster formation. In general, clusters classified as "typical" and "heap" are most common. Inspection of temporal cluster coverage of the test-bed surface shows that the proportion of clusters present on the surface tends to grow with time. Maximum cluster surface coverage of between 5% and 34% is observed. In addition, particles entering and departing from clusters are monitored. Most commonly, particles enter from directly upstream of the cluster, however >20% of particles approach from a direction >20 deg from the streamwise direction. Approximately 35% of all particles directly upstream of a cluster bypass the cluster.

  9. 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.

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

    DEFF Research Database (Denmark)

    Zong, Yu; Xu, Guandong; Jin, Pin

    2011-01-01

    resulting from the severe difficulty of ambiguity, redundancy and less semantic nature of tags. Clustering method is a useful tool to address the aforementioned difficulties. Most of the researches on tag clustering are directly using traditional clustering algorithms such as K-means or Hierarchical...... algorithm for Tags (APPECT). The main steps of APPECT are: (1) we execute the K-means algorithm on a tag similarity matrix for M times and collect a set of tag clustering results Z={C1,C2,…,Cm}; (2) we form the approximate backbone of Z by executing a greedy search; (3) we fix the approximate backbone...... Agglomerative Clustering on tagging data, which possess the inherent drawbacks, such as the sensitivity of initialization. In this paper, we instead make use of the approximate backbone of tag clustering results to find out better tag clusters. In particular, we propose an APProximate backbonE-based Clustering...

  11. From collisions to clusters

    DEFF Research Database (Denmark)

    Loukonen, Ville; Bork, Nicolai; Vehkamaki, Hanna

    2014-01-01

    The clustering of sulphuric acid with base molecules is one of the main pathways of new-particle formation in the Earth's atmosphere. First step in the clustering process is likely the formation of a (sulphuric acid)1(base)1(water)n cluster. Here, we present results from direct first-principles m......The clustering of sulphuric acid with base molecules is one of the main pathways of new-particle formation in the Earth's atmosphere. First step in the clustering process is likely the formation of a (sulphuric acid)1(base)1(water)n cluster. Here, we present results from direct first...... bridge. In general, water is able to notably stabilise the formed clusters by allocating a fraction of the released clustering energy....

  12. Loose-cluster approximation

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Loose-cluster approximation. Continuous curve Our Theory. Dashed curve Our Simulation. Loose cluster approx. not only. captures -the anomalous. qualitative features but is also,. quantitatively, quite accurate. Notes:

  13. Cluster beam injection

    International Nuclear Information System (INIS)

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

    1977-11-01

    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. 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

  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. 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.

  17. 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.

  18. 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

  19. Range-clustering queries

    DEFF Research Database (Denmark)

    Abrahamsen, Mikkel; de Berg, Mark; Buchin, Kevin

    2017-01-01

    an optimal k-clustering for S P ∩ Q. We obtain the following results. • We present a general method to compute a (1 + ϵ)-approximation to a range-clustering query, where ϵ > 0 is a parameter that can be specified as part of the query. Our method applies to a large class of clustering problems, including k...

  20. Cosmology with cluster surveys

    Indian Academy of Sciences (India)

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

  1. Cosmology with cluster surveys

    Indian Academy of Sciences (India)

    Cosmology with cluster surveys. SUBHABRATA MAJUMDAR. CITA, University of Toronto, Toronto, ON, M5S 3H8, Canada. E-mail: subha@cita.utoronto.ca. 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.

  2. Structures of Mn clusters

    Indian Academy of Sciences (India)

    Abstract. The geometries of several Mn clusters in the size range Mn13–Mn23 are studied via the generalized gradient approximation to density functional theory. For the 13- and 19-atom clusters, the icosahedral structures are found to be most stable, while for the 15-atom cluster, the bcc structure is more favoured.

  3. 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.

  4. 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...

  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. Energy yield prediction of offshore wind farm clusters at the EERA-DTOC European project

    DEFF Research Database (Denmark)

    Cantero, E.; Hasager, Charlotte Bay; Réthoré, Pierre-Elouan

    2013-01-01

    A new integrated design tool for optimization of offshore wind farm clusters is under development in the European Energy Research Alliance – Design Tools for Offshore wind farm Cluster project (EERA DTOC). The project builds on already established design tools from the project partners and possib...

  9. Energy Yield Prediction of Offshore Wind Farm Clusters at the EERA-DTOC European Project

    DEFF Research Database (Denmark)

    Cantero, E.; Hasager, Charlotte Bay; Réthoré, Pierre-Elouan

    2014-01-01

    A new integrated design tool for optimization of offshore wind farm clusters is under development in the European Energy Research Alliance – Design Tools for Offshore wind farm Cluster project (EERA DTOC). The project builds on already established design tools from the project partners and possib...

  10. PEACE: Parallel Environment for Assembly and Clustering of Gene Expression.

    Science.gov (United States)

    Rao, D M; Moler, J C; Ozden, M; Zhang, Y; Liang, C; Karro, J E

    2010-07-01

    We present PEACE, a stand-alone tool for high-throughput ab initio clustering of transcript fragment sequences produced by Next Generation or Sanger Sequencing technologies. It is freely available from www.peace-tools.org. Installed and managed through a downloadable user-friendly graphical user interface (GUI), PEACE can process large data sets of transcript fragments of length 50 bases or greater, grouping the fragments by gene associations with a sensitivity comparable to leading clustering tools. Once clustered, the user can employ the GUI's analysis functions, facilitating the easy collection of statistics and allowing them to single out specific clusters for more comprehensive study or assembly. Using a novel minimum spanning tree-based clustering method, PEACE is the equal of leading tools in the literature, with an interface making it accessible to any user. It produces results of quality virtually identical to those of the WCD tool when applied to Sanger sequences, significantly improved results over WCD and TGICL when applied to the products of Next Generation Sequencing Technology and significantly improved results over Cap3 in both cases. In short, PEACE provides an intuitive GUI and a feature-rich, parallel clustering engine that proves to be a valuable addition to the leading cDNA clustering tools.

  11. 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

  12. Improved Ant Colony Clustering Algorithm and Its Performance Study

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2016-01-01

    Full Text Available 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.

  13. 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

  14. Clustering high dimensional data

    DEFF Research Database (Denmark)

    Assent, Ira

    2012-01-01

    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......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...... that provide different cluster models and different algorithmic approaches for cluster detection. Common to all approaches is the fact that they require some underlying assessment of similarity between data objects. In this article, we provide an overview of the effects of high-dimensional spaces...

  15. 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 ...

  16. 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...

  17. Modeling Clustered Data with Very Few Clusters.

    Science.gov (United States)

    McNeish, Daniel; Stapleton, Laura M

    2016-01-01

    Small-sample inference with clustered data has received increased attention recently in the methodological literature, with several simulation studies being presented on the small-sample behavior of many methods. However, nearly all previous studies focus on a single class of methods (e.g., only multilevel models, only corrections to sandwich estimators), and the differential performance of various methods that can be implemented to accommodate clustered data with very few clusters is largely unknown, potentially due to the rigid disciplinary preferences. Furthermore, a majority of these studies focus on scenarios with 15 or more clusters and feature unrealistically simple data-generation models with very few predictors. This article, motivated by an applied educational psychology cluster randomized trial, presents a simulation study that simultaneously addresses the extreme small sample and differential performance (estimation bias, Type I error rates, and relative power) of 12 methods to account for clustered data with a model that features a more realistic number of predictors. The motivating data are then modeled with each method, and results are compared. Results show that generalized estimating equations perform poorly; the choice of Bayesian prior distributions affects performance; and fixed effect models perform quite well. Limitations and implications for applications are also discussed.

  18. Cluster assembly in nitrogenase.

    Science.gov (United States)

    Sickerman, Nathaniel S; Rettberg, Lee A; Lee, Chi Chung; Hu, Yilin; Ribbe, Markus W

    2017-05-09

    The versatile enzyme system nitrogenase accomplishes the challenging reduction of N 2 and other substrates through the use of two main metalloclusters. For molybdenum nitrogenase, the catalytic component NifDK contains the [Fe 8 S 7 ]-core P-cluster and a [MoFe 7 S 9 C-homocitrate] cofactor called the M-cluster. These chemically unprecedented metalloclusters play a critical role in the reduction of N 2 , and both originate from [Fe 4 S 4 ] clusters produced by the actions of NifS and NifU. Maturation of P-cluster begins with a pair of these [Fe 4 S 4 ] clusters on NifDK called the P*-cluster. An accessory protein NifZ aids in P-cluster fusion, and reductive coupling is facilitated by NifH in a stepwise manner to form P-cluster on each half of NifDK. For M-cluster biosynthesis, two [Fe 4 S 4 ] clusters on NifB are coupled with a carbon atom in a radical-SAM dependent process, and concomitant addition of a 'ninth' sulfur atom generates the [Fe 8 S 9 C]-core L-cluster. On the scaffold protein NifEN, L-cluster is matured to M-cluster by the addition of Mo and homocitrate provided by NifH. Finally, matured M-cluster in NifEN is directly transferred to NifDK, where a conformational change locks the cofactor in place. Mechanistic insights into these fascinating biosynthetic processes are detailed in this chapter. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  19. ASteCA: Automated Stellar Cluster Analysis

    Science.gov (United States)

    Perren, G. I.; Vázquez, R. A.; Piatti, A. E.

    2015-04-01

    We present the Automated Stellar Cluster Analysis package (ASteCA), a suit of tools designed to fully automate the standard tests applied on stellar clusters to determine their basic parameters. The set of functions included in the code make use of positional and photometric data to obtain precise and objective values for a given cluster's center coordinates, radius, luminosity function and integrated color magnitude, as well as characterizing through a statistical estimator its probability of being a true physical cluster rather than a random overdensity of field stars. ASteCA incorporates a Bayesian field star decontamination algorithm capable of assigning membership probabilities using photometric data alone. An isochrone fitting process based on the generation of synthetic clusters from theoretical isochrones and selection of the best fit through a genetic algorithm is also present, which allows ASteCA to provide accurate estimates for a cluster's metallicity, age, extinction and distance values along with its uncertainties. To validate the code we applied it on a large set of over 400 synthetic MASSCLEAN clusters with varying degrees of field star contamination as well as a smaller set of 20 observed Milky Way open clusters (Berkeley 7, Bochum 11, Czernik 26, Czernik 30, Haffner 11, Haffner 19, NGC 133, NGC 2236, NGC 2264, NGC 2324, NGC 2421, NGC 2627, NGC 6231, NGC 6383, NGC 6705, Ruprecht 1, Tombaugh 1, Trumpler 1, Trumpler 5 and Trumpler 14) studied in the literature. The results show that ASteCA is able to recover cluster parameters with an acceptable precision even for those clusters affected by substantial field star contamination. ASteCA is written in Python and is made available as an open source code which can be downloaded ready to be used from its official site.

  20. Machine tool

    International Nuclear Information System (INIS)

    Kang, Myeong Sun

    1981-01-01

    This book indicates machine tool, which includes cutting process and processing by cutting process, theory of cutting like tool angle and chip molding, cutting tool such as milling cutter and drill, summary and introduction of following machine ; spindle drive and feed drive, pivot and pivot bearing, frame, guide way and table, drilling machine, boring machine, shaper and planer, milling machine, machine tool for precision finishing like lapping machine and super finishing machine gear cutter.

  1. Peculiar motions of galaxy clusters: correlation function approach

    Science.gov (United States)

    Iqbal, Naseer; Masood, Tabasum; Hamid, Mubashir; Ahmad, Naveel; Maqbool, Bari

    2014-10-01

    The correlation function theory on the basis of prescribed boundary conditions provides a deeper understanding in studying the dynamical parameters of galaxy clusters. The approach approximates that the moderate dense systems discussed by a two point correlation function is helpful for describing the dynamical nature of galaxy clusters. The projected theory of two point correlation function for point mass and extended mass structures can be used an alternative tool in measuring the average peculiar motion and temperature profile of galaxy clusters.

  2. Time-clustering investigation of fire temporal fluctuations in Portugal

    Directory of Open Access Journals (Sweden)

    L. Telesca

    2010-04-01

    Full Text Available Temporal clustering structures were identified and quantified in fire sequences recorded from 1980 to 2005 in Continental Portugal, by using the Allan Factor statistics, a statistical tool suited to reveal clustering behaviour in point processes. The obtained results show the presence of daily and annual periodicities, superimposed onto a scaling behaviour, which features the sequence of wildfires as a fractal time process with a rather high degree of time-clusterization of the events.

  3. 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.

  4. 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

  5. Blaeu: Mapping and navigating large tables with cluster analysis

    NARCIS (Netherlands)

    T.H.J. Sellam (Thibault); C.P. Cijvat (Robin); R.A. Koopmanschap (Richard); M.L. Kersten (Martin)

    2016-01-01

    textabstractBlaeu is an interactive database exploration tool. Its aim is to guide casual users through large data tables, ultimately triggering insights and serendipity. To do so, it relies on a double cluster analysis mechanism. It clusters the data vertically: it detects themes, groups of

  6. 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.

  7. 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 ...

  8. Cluster Management Institutionalization

    DEFF Research Database (Denmark)

    Normann, Leo; Agger Nielsen, Jeppe

    2015-01-01

    This article explores a new management form – cluster management – in Danish public sector day care. Although cluster management has been widely adopted in Danish day care at the municipality level, it has attracted only sparse research attention. We use theoretical insights from Scandinavian...... institutionalism together with a longitudinal case-based inquiry into how cluster management has entered and penetrated the management practices of day care in Denmark. We demonstrate how cluster management became widely adopted in the day care field not only because of its intrinsic properties but also because...... 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...

  9. Disentangling Porterian Clusters

    DEFF Research Database (Denmark)

    Jagtfelt, Tue

    This dissertation investigates the contemporary phenomenon of industrial clusters based on the work of Michael E. Porter, the central progenitor and promoter of the cluster notion. The dissertation pursues two central questions: 1) What is a cluster? and 2) How could Porter’s seemingly fuzzy...... 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...

  10. 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.

  11. 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.

  12. How atomic nuclei cluster.

    Science.gov (United States)

    Ebran, J-P; Khan, E; Nikšić, T; Vretenar, D

    2012-07-18

    Nucleonic matter displays a quantum-liquid structure, but in some cases finite nuclei behave like molecules composed of clusters of protons and neutrons. Clustering is a recurrent feature in light nuclei, from beryllium to nickel. Cluster structures are typically observed as excited states close to the corresponding decay threshold; the origin of this phenomenon lies in the effective nuclear interaction, but the detailed mechanism of clustering in nuclei has not yet been fully understood. Here we use the theoretical framework of energy-density functionals, encompassing both cluster and quantum liquid-drop aspects of nuclei, to show that conditions for cluster formation can in part be traced back to the depth of the confining nuclear potential. For the illustrative example of neon-20, we show that the depth of the potential determines the energy spacings between single-nucleon orbitals in deformed nuclei, the localization of the corresponding wavefunctions and, therefore, the degree of nucleonic density clustering. Relativistic functionals, in particular, are characterized by deep single-nucleon potentials. When compared to non-relativistic functionals that yield similar ground-state properties (binding energy, deformation, radii), they predict the occurrence of much more pronounced cluster structures. More generally, clustering is considered as a transitional phenomenon between crystalline and quantum-liquid phases of fermionic systems.

  13. 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

  14. Statistical properties of convex clustering

    OpenAIRE

    Tan, Kean Ming; Witten, Daniela

    2015-01-01

    In this manuscript, we study the statistical properties of convex clustering. We establish that convex clustering is closely related to single linkage hierarchical clustering and $k$-means clustering. In addition, we derive the range of the tuning parameter for convex clustering that yields a non-trivial solution. We also provide an unbiased estimator of the degrees of freedom, and provide a finite sample bound for the prediction error for convex clustering. We compare convex clustering to so...

  15. Nonlocalized clustering and evolution of cluster structure in nuclei

    Science.gov (United States)

    Horiuchi, H.

    2017-06-01

    It is shown that the THSR (Tohsaki-Horiuchi-Schuck-Roepke) wave function describe well not only cluster-gas like structures but also ordinary cluster structures with spatial localization of clusters. Based on this fact, the container model has been proposed as a new model of cluster dynamics. For better description of cluster dynamics, extended version of container model has been introduced. The container model of cluster dynamics teaches us how is the evolution of cluster structure which starts from the ground state having shell-model structure to many kinds of cluster states up to the cluster-gas states.

  16. 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.

  17. 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...

  18. Nuclear clustering in the energy density functional approach

    Energy Technology Data Exchange (ETDEWEB)

    Ebran, J.-P., E-mail: jean-paul.ebran@cea.fr [CEA,DAM,DIF, F-91297 Arpajon (France); Khan, E. [Institut de Physique Nucléaire, Université Paris-Sud CEA, IN2P3 CNRS, F-91406 Orsay Cedex (France); Nikšić, T.; Vretenar, D. [Physics Department, Faculty of Science, University of Zagreb, 10000 Zagreb (Croatia)

    2015-10-15

    Nuclear Energy Density Functionals (EDFs) are a microscopic tool of choice extensively used over the whole chart to successfully describe the properties of atomic nuclei ensuing from their quantum liquid nature. In the last decade, they also have proved their ability to deal with the cluster phenomenon, shedding a new light on its fundamental understanding by treating on an equal footing both quantum liquid and cluster aspects of nuclei. Such a unified microscopic description based on nucleonic degrees of freedom enables to tackle the question pertaining to the origin of the cluster phenomenon and emphasizes intrinsic mechanisms leading to the emergence of clusters in nuclei.

  19. 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…

  20. Securing Personal Network Clusters

    NARCIS (Netherlands)

    Jehangir, A.; Heemstra de Groot, S.M.

    2007-01-01

    A Personal Network is a self-organizing, secure and private network of a user’s devices notwithstanding their geographic location. It aims to utilize pervasive computing to provide users with new and improved services. In this paper we propose a model for securing Personal Network clusters. Clusters

  1. Calixarene-supported clusters

    DEFF Research Database (Denmark)

    Taylor, Stephanie M.; McIntosh, Ruaraidh D.; Piligkos, Stergios

    2012-01-01

    A combination of complementary cluster ligands results in the formation of a new calixarene-supported ferromagnetic [Mn(5)] cage that displays the characteristic bonding modes of each support.......A combination of complementary cluster ligands results in the formation of a new calixarene-supported ferromagnetic [Mn(5)] cage that displays the characteristic bonding modes of each support....

  2. Reflections on cluster policies

    NARCIS (Netherlands)

    Brakman, Steven; van Marrewijk, Charles

    Economic activity tends to cluster. This results in productivity gains. For policy makers this offers an opportunity to formulate and promote policies that foster clustering of economic activity. Paradoxically, although agglomeration rents are often found in empirical research, a rationale for

  3. 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

  4. Fuzzy clustering of mechanisms

    Indian Academy of Sciences (India)

    type synthesis phase of mechanical design. To the best of the authors' knowledge, this type of clustering of mechanisms has not been attempted before. Thus, this is the first attempt to cluster the mechanisms based on some quantitative measures. It may help the engineers to carry out type synthesis of the mechanisms.

  5. 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....

  6. CSR in Industrial Clusters

    DEFF Research Database (Denmark)

    Lund-Thomsen, Peter; Pillay, Renginee G.

    2012-01-01

    development in the South. At the turn of the millennium the industrial cluster debate expanded as clusters were perceived as a potential source of poverty reduction, while their role in promoting CSR among small and medium-sized enterprises began to take shape from 2006 onwards. At present, there is still...

  7. Cluster knockout reactions

    Indian Academy of Sciences (India)

    2014-04-07

    Apr 7, 2014 ... advancements in the area of (α, 2α) reactions and heavy cluster knockout reactions are discussed. Importance of the finite-range vertex and the final-state interactions are brought out. Keywords. Cluster knockout reactions; FR-DWIA calculations; t-matrix effective interaction. PACS Nos 14.20.Pt; 24.10.

  8. Multilevel functional clustering analysis.

    Science.gov (United States)

    Serban, Nicoleta; Jiang, Huijing

    2012-09-01

    In this article, we investigate clustering methods for multilevel functional data, which consist of repeated random functions observed for a large number of units (e.g., genes) at multiple subunits (e.g., bacteria types). To describe the within- and between variability induced by the hierarchical structure in the data, we take a multilevel functional principal component analysis (MFPCA) approach. We develop and compare a hard clustering method applied to the scores derived from the MFPCA and a soft clustering method using an MFPCA decomposition. In a simulation study, we assess the estimation accuracy of the clustering membership and the cluster patterns under a series of settings: small versus moderate number of time points; various noise levels; and varying number of subunits per unit. We demonstrate the applicability of the clustering analysis to a real data set consisting of expression profiles from genes activated by immunity system cells. Prevalent response patterns are identified by clustering the expression profiles using our multilevel clustering analysis. © 2012, The International Biometric Society.

  9. Cluster Synchronization Algorithms

    NARCIS (Netherlands)

    Xia, Weiguo; Cao, Ming

    2010-01-01

    This paper presents two approaches to achieving cluster synchronization in dynamical multi-agent systems. In contrast to the widely studied synchronization behavior, where all the coupled agents converge to the same value asymptotically, in the cluster synchronization problem studied in this paper,

  10. Fuzzy clustering of mechanisms

    Indian Academy of Sciences (India)

    two clustering techniques, the mechanisms have been classified in the present work and in future, it may be extended to develop an expert system, which can automate type synthesis phase of mechanical design. To the best of the authors' knowledge, this type of clustering of mechanisms has not been attempted before.

  11. Collisions between Globular Clusters

    Science.gov (United States)

    Belloni, D. T.; Rocha-Pinto, H. J.

    2014-10-01

    The study of globular clusters (GC) plays an important role in our understanding of the Universe since these systems are true laboratories for theories of stellar dynamics and evolution. We are interested in studying a globular cluster formed by a collision between two different GC with NBODY6 (Aarseth, 2003). Firstly, in order to understand this code, we analyse how tidal streams form from a globular cluster in a circular orbit (on the disk) around the center of the Milky Way. In the next stage of this work we will study that collision. The stellar escape or capture from globular cluster can be understood with the Restricted Three Body Problem. These stars escape in a chaotic orbit, and in some cases may return (again in a chaotic orbit) to the cluster due to the Galactic potential. In most cases, such stars quickly alter their escape chaotic orbits to orbits that are similar to the parent cluster's orbit. Our results show an agglomeration of stars in a normal direction related to the direction towards the center of the Milky Way, forming thus a stream. We can explain this considering that a circular orbit around the dominant potential is the most likely orbit, since it requires minimum energy. In this coordinate systems, the tidal tails (or streams) rotates around the cluster center with the same mean motion associated to cluster around the Milky Way center.

  12. Detecting clusters of mutations.

    Directory of Open Access Journals (Sweden)

    Tong Zhou

    Full Text Available Positive selection for protein function can lead to multiple mutations within a small stretch of DNA, i.e., to a cluster of mutations. Recently, Wagner proposed a method to detect such mutation clusters. His method, however, did not take into account that residues with high solvent accessibility are inherently more variable than residues with low solvent accessibility. Here, we propose a new algorithm to detect clustered evolution. Our algorithm controls for different substitution probabilities at buried and exposed sites in the tertiary protein structure, and uses random permutations to calculate accurate P values for inferred clusters. We apply the algorithm to genomes of bacteria, fly, and mammals, and find several clusters of mutations in functionally important regions of proteins. Surprisingly, clustered evolution is a relatively rare phenomenon. Only between 2% and 10% of the genes we analyze contain a statistically significant mutation cluster. We also find that not controlling for solvent accessibility leads to an excess of clusters in terminal and solvent-exposed regions of proteins. Our algorithm provides a novel method to identify functionally relevant divergence between groups of species. Moreover, it could also be useful to detect artifacts in automatically assembled genomes.

  13. 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)

  14. Fuzzy clustering analysis of microarray data.

    Science.gov (United States)

    Han, Lixin; Zeng, Xiaoqin; Yan, Hong

    2008-10-01

    Fuzzy clustering is a useful tool for identifying relevant subsets of microarray data. This paper proposes a fuzzy clustering method for microarray data analysis. An advantage of the method is that it used a combination of the fuzzy c-means and the principal component analysis to identify the groups of genes that show similar expression patterns. It allows a gene to belong to more than a gene expression pattern with different membership grades. The method is suitable for the analysis of large amounts of noisy microarray data.

  15. 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.

  16. 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 ...

  17. 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...

  18. 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

  19. Magic structures of binary metallic clusters

    Science.gov (United States)

    Ferrando, Riccardo

    2005-03-01

    The structure of binary metallic clusters is investigated by a variety of computational tools, ranging from genetic and basin-hopping global optimization algorithms, to molecular dynamics, and to density-functional calculations. Three different binary systems are investigated: Ag-Cu, Ag-Ni, and Ag-Pd. A new family of magic cluster structures is found. These clusters have the common feature of presenting a perfect core-shell chemical arrangement (with an outer Ag shell of monoatomic thickness) and of being polyicosahedra, that is being made of interpenetrating icosahedra of 13 atoms. Core-shell polyicosahedra are of special stability, which originates from the interplay of different factors. First of all, polyicosahedra are very compact structures, so that they maximize the number of nearest-neighbor bonds for a given size. However, in single-element clusters, these bonds are not optimal, since inner bonds are strongly compressed and surface bonds are expanded. This is the contrary of what is required from the bond order -bond length correlation in metals, which favors contracted surface bonds. In binary clusters, the situation is different. Substituting the inner atoms of a single-element polyicosahedron with different atoms of smaller size, the bonds can relax close to their optimal distance. This leads naturally to the appearance of core-shell polyicosahedra. In Ag-Cu, Ag-Ni and Ag-Pd the formation of these structures is reinforced by the tendency of Ag atoms to surface segregation. A similar mechanism of structural relaxation, originating from the interplay of cluster geometry and bond order - bond length correlation, is also the cause of the destabilization of icosahedral structures in pure Pt and Au clusters . In these clusters, the compressed inner atoms of the icosahedra can relax because of the formation of rosette structures at vertices in the outer layer.

  20. 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.

  1. Studies in clustering theory

    Science.gov (United States)

    Stell, George

    In recent years the properties of percolation models have been studied intensively. The purpose of our project was to develop a general theory of percolation and clustering between particles of arbitrary size and shape, with arbitrary correlations between them. The goal of such a theory includes the treatment of continuum percolation as well as a novel treatment of lattice percolation. We made substantial progress toward this goal. The quantities basic to a description of clustering, the mean cluster size, mean number of clusters, etc., were developed. Concise formulas were given for the terms in such series, and proved, at least for sufficiently low densities, that the series are absolutely convergent. These series can now be used to construct Pade approximants that will allow one to probe the percolation transition. A scaled-particle theory of percolation was developed which gives analytic approximants for the mean number of clusters in a large class of two and three dimensional percolation models. Although this quantity is essential in many applications, e.g., explaining colligative properties, and interpreting low-angle light-scattering data, no systematic studies of it have been done before this work. Recently carried out detailed computer simulations show that the mean number of clusters is given to high accuracy by several of there approximations. Extensions of this work will allow calculation of the complete cluster size distribution.

  2. Evolution Properties of Clusters and AXAF Contributions to understanding Clusters

    Science.gov (United States)

    Jones, Christine

    1998-01-01

    Our ROSAT survey for distant clusters of galaxies contains the largest solid angle of all ROSAT pointed surveying and thus has sufficient area to test the previously reported cluster evolution. We find significant negative cluster evolution, i.e,, at high redshifts there are fewer luminous clusters than at present. We compare optical cluster properties for the most distant clusters in the ROSAT survey with those measured for nearby clusters. We also present AXAF capabilities and show how AXAF will significantly extend our understanding of cluster properties and their cosmological evolution.

  3. Clusters of Circulating Tumor Cells: a Biophysical and Technological Perspective.

    Science.gov (United States)

    Au, Sam H; Edd, Jon; Haber, Daniel A; Maheswaran, Shyamala; Stott, Shannon L; Toner, Mehmet

    2017-09-01

    The vast majority of cancer associated deaths result from metastasis, yet the behaviors of its most potent cellular driver, circulating tumor cell clusters, are only beginning to be revealed. This review highlights recent advances to our understanding of tumor cell clusters with emphasis on enabling technologies. The importance of intercellular adhesions among cells in clusters have begun to be unraveled with the aid of promising microfluidic strategies for isolating clusters from patient blood. Due to their metastatic potency, the utility of circulating tumor cell clusters for cancer diagnosis, drug screening, precision oncology and as targets of antimetastatic therapeutics are being explored. The continued development of tools for exploring circulating tumor cell clusters will enhance our fundamental understanding of the metastatic process and may be instrumental in devising new strategies to suppress and eliminate metastasis.

  4. 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.

  5. Cluster Deposition and Implantation on/in Graphite

    DEFF Research Database (Denmark)

    Popok, Vladimir

    2013-01-01

    Cluster ion beam technique is a versatile tool which can be used for controllable formation of nanosize objects on the surface, modification and processing of surfaces and shallow layers on an atomic scale. In this chapter an overview of research on cluster interaction with graphite is presented....... 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 phenomenon of cluster stopping and the development of scaling law for cluster implantation in graphite. Graphite...... is chosen for surface experiments because it is a good model material; it has an atomically smooth surface that makes it easy to resolve very small deposited clusters or damaged areas. Layered structure of graphite with strong covalent bonds in the graphene sheets and very week van der Waals interactions...

  6. Spanning Tree Based Attribute Clustering

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Jorge, Cordero Hernandez

    2009-01-01

    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...

  7. 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...

  8. Extending Beowulf Clusters

    Science.gov (United States)

    Steinwand, Daniel R.; Maddox, Brian; Beckmann, Tim; Hamer, George

    2003-01-01

    Beowulf clusters can provide a cost-effective way to compute numerical models and process large amounts of remote sensing image data. Usually a Beowulf cluster is designed to accomplish a specific set of processing goals, and processing is very efficient when the problem remains inside the constraints of the original design. There are cases, however, when one might wish to compute a problem that is beyond the capacity of the local Beowulf system. In these cases, spreading the problem to multiple clusters or to other machines on the network may provide a cost-effective solution.

  9. Distant galactic open clusters

    International Nuclear Information System (INIS)

    Christian, C.A.

    1980-01-01

    The motivation for studying distant open clusters primarily arose out of a desire to gain some understanding of star formation processes in the general context of galactic structure. Of specific interest are faint open clusters near the galactic anticenter which are part of a larger survey of objects which may be located in the 'periphery' of the Galaxy. A sample of results from broad-band photometric studies for clusters near lsup(II)=180 0 , bsup(II)=0 0 is presented. (Auth.)

  10. 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

  11. 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.

  12. 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...

  13. Partially supervised speaker clustering.

    Science.gov (United States)

    Tang, Hao; Chu, Stephen Mingyu; Hasegawa-Johnson, Mark; Huang, Thomas S

    2012-05-01

    Content-based multimedia indexing, retrieval, and processing as well as multimedia databases demand the structuring of the media content (image, audio, video, text, etc.), one significant goal being to associate the identity of the content to the individual segments of the signals. In this paper, we specifically address the problem of speaker clustering, the task of assigning every speech utterance in an audio stream to its speaker. We offer a complete treatment to the idea of partially supervised speaker clustering, which refers to the use of our prior knowledge of speakers in general to assist the unsupervised speaker clustering process. By means of an independent training data set, we encode the prior knowledge at the various stages of the speaker clustering pipeline via 1) learning a speaker-discriminative acoustic feature transformation, 2) learning a universal speaker prior model, and 3) learning a discriminative speaker subspace, or equivalently, a speaker-discriminative distance metric. We study the directional scattering property of the Gaussian mixture model (GMM) mean supervector representation of utterances in the high-dimensional space, and advocate exploiting this property by using the cosine distance metric instead of the euclidean distance metric for speaker clustering in the GMM mean supervector space. We propose to perform discriminant analysis based on the cosine distance metric, which leads to a novel distance metric learning algorithm—linear spherical discriminant analysis (LSDA). We show that the proposed LSDA formulation can be systematically solved within the elegant graph embedding general dimensionality reduction framework. Our speaker clustering experiments on the GALE database clearly indicate that 1) our speaker clustering methods based on the GMM mean supervector representation and vector-based distance metrics outperform traditional speaker clustering methods based on the “bag of acoustic features” representation and statistical

  14. 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...

  15. 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...

  16. Flexible And Secure Access To Computing Clusters

    Directory of Open Access Journals (Sweden)

    Jan Meizner

    2010-01-01

    Full Text Available The investigation presented in this paper was prompted by the need to provide a manageablesolution for secure access to computing clusters with a federated authentication framework.This requirement is especially important for scientists who need direct access to computingnodes in order to run their applications (e.g. chemical or medical simulations with proprietary,open-source or custom-developed software packages. Our existing software, whichenables non-Web clients to use Shibboleth-secured services, has been extended to providedirect SSH access to cluster nodes using the Linux Pluggable Authentication Modules mechanism.This allows Shibboleth users to run the required software on clusters. Validationand performance comparison with existing SSH authentication mechanisms confirm that thepresented tools satisfy the stated requirements.

  17. 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.

  18. 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.

  19. 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, ...

  20. Transition Matrix Cluster Algorithms

    OpenAIRE

    Yevick, David; Lee, Yong Hwan

    2018-01-01

    We demonstrate that a series of simple procedures for increasing the efficiency of transition matrix calculations can be realized by integrating the standard single-spin reversal transition matrix method with global cluster inversion techniques.

  1. 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)

  2. 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....

  3. 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)

  4. 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...

  5. 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.

  6. 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...... statistic and the simulated pointwise envelopes it is shown that this model fits better than the Thomas process to the frequently analyzed long-leaf pine data-set....

  7. Structure of Silicon Clusters

    OpenAIRE

    Pan, Jun; Bahel, Atul; Ramakrishna, Mushti V.

    1995-01-01

    We determined the structures of silicon clusters in the 11-14 atom size range using the tight-binding molecular dynamics method. These calculations reveal that \\Si{11} is an icosahedron with one missing cap, \\Si{12} is a complete icosahedron, \\Si{13} is a surface capped icosahedron, and \\Si{14} is a 4-4-4 layer structure with two caps. The characteristic feature of these clusters is that they are all surface.

  8. 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.

  9. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

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

    2006-01-01

    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 ...

  10. 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....

  11. SPECTRAL IMAGING OF GALAXY CLUSTERS WITH PLANCK

    Energy Technology Data Exchange (ETDEWEB)

    Bourdin, H.; Mazzotta, P. [Dipartimento di Fisica, Università degli Studi di Roma “Tor Vergata,” via della Ricerca Scientifica, 1, I-00133 Roma (Italy); Rasia, E., E-mail: herve.bourdin@roma2.infn.it [INAF-Osservatorio Astronomico of Trieste, via Tiepolo 11, I-34121 Trieste (Italy)

    2015-12-20

    The Sunyaev–Zeldovich (SZ) effect is a promising tool for detecting the presence of hot gas out to the galaxy cluster peripheries. We developed a spectral imaging algorithm dedicated to the SZ observations of nearby galaxy clusters with Planck, with the aim of revealing gas density anisotropies related to the filamentary accretion of materials, or pressure discontinuities induced by the propagation of shock fronts. To optimize an unavoidable trade-off between angular resolution and precision of the SZ flux measurements, the algorithm performs a multi-scale analysis of the SZ maps as well as of other extended components, such as the cosmic microwave background (CMB) anisotropies and the Galactic thermal dust. The demixing of the SZ signal is tackled through kernel-weighted likelihood maximizations. The CMB anisotropies are further analyzed through a wavelet analysis, while the Galactic foregrounds and SZ maps are analyzed via a curvelet analysis that best preserves their anisotropic details. The algorithm performance has been tested against mock observations of galaxy clusters obtained by simulating the Planck High Frequency Instrument and by pointing at a few characteristic positions in the sky. These tests suggest that Planck should easily allow us to detect filaments in the cluster peripheries and detect large-scale shocks in colliding galaxy clusters that feature favorable geometry.

  12. 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....

  13. Relation chain based clustering analysis

    Science.gov (United States)

    Zhang, Cheng-ning; Zhao, Ming-yang; Luo, Hai-bo

    2011-08-01

    Clustering analysis is currently one of well-developed branches in data mining technology which is supposed to find the hidden structures in the multidimensional space called feature or pattern space. A datum in the space usually possesses a vector form and the elements in the vector represent several specifically selected features. These features are often of efficiency to the problem oriented. Generally, clustering analysis goes into two divisions: one is based on the agglomerative clustering method, and the other one is based on divisive clustering method. The former refers to a bottom-up process which regards each datum as a singleton cluster while the latter refers to a top-down process which regards entire data as a cluster. As the collected literatures, it is noted that the divisive clustering is currently overwhelming both in application and research. Although some famous divisive clustering methods are designed and well developed, clustering problems are still far from being solved. The k - means algorithm is the original divisive clustering method which initially assigns some important index values, such as the clustering number and the initial clustering prototype positions, and that could not be reasonable in some certain occasions. More than the initial problem, the k - means algorithm may also falls into local optimum, clusters in a rigid way and is not available for non-Gaussian distribution. One can see that seeking for a good or natural clustering result, in fact, originates from the one's understanding of the concept of clustering. Thus, the confusion or misunderstanding of the definition of clustering always derives some unsatisfied clustering results. One should consider the definition deeply and seriously. This paper demonstrates the nature of clustering, gives the way of understanding clustering, discusses the methodology of designing a clustering algorithm, and proposes a new clustering method based on relation chains among 2D patterns. In

  14. Enhanced peptide quantification using spectral count clustering and cluster abundance

    Directory of Open Access Journals (Sweden)

    Lee Seungmook

    2011-10-01

    , and 2,323 clusters both in the HCC and normal tissue samples. While it will be interesting to investigate peptide clusters only found from one sample, further examined spectral clusters identified both in the HCC and normal samples since our goal is to identify and assess differentially expressed peptides quantitatively. The next step was to perform a beta-binomial test to isolate differentially expressed peptides between the HCC and normal tissue samples. This test resulted in 84 peptides with significantly differential spectral counts between the HCC and normal tissue samples. We independently identified 50 and 95 peptides by SEQUEST, of which 24 and 56 peptides, respectively, were found to be known biomarkers for the human liver cancer. Comparing Q-FISH and SEQUEST results, we found 22 of the differentially expressed 84 peptides by Q-FISH were also identified by SEQUEST. Remarkably, of these 22 peptides discovered both by Q-FISH and SEQUEST, 13 peptides are known for human liver cancer and the remaining 9 peptides are known to be associated with other cancers. Conclusions We proposed a novel statistical method, Q-FISH, for accurately identifying protein species and simultaneously quantifying the expression levels of identified peptides from mass spectrometry data. Q-FISH analysis on human HCC and liver tissue samples identified many protein biomarkers that are highly relevant to HCC. Q-FISH can be a useful tool both for peptide identification and quantification on mass spectrometry data analysis. It may also prove to be more effective in discovering novel protein biomarkers than SEQUEST and other standard methods.

  15. Cluster analysis of BI-RADS descriptions of biopsy-proven breast lesions

    Science.gov (United States)

    Markey, Mia K.; Lo, Joseph Y.; Tourassi, Georgia D.; Floyd, Carey E., Jr.

    2002-05-01

    The purpose of this study was to identify and characterize clusters in a heterogeneous breast cancer computer-aided diagnosis database. Identification of subgroups within the database could help elucidate clinical trends and facilitate future model building. Agglomerative hierarchical clustering and k-means clustering were used to identify clusters in a large, heterogeneous computer-aided diagnosis database based on mammographic findings (BI-RADS) and patient age. The clusters were examined in terms of their feature distributions. The clusters showed logical separation of distinct clinical subtypes such as architectural distortions, masses, and calcifications. Moreover, the common subtypes of masses and calcifications were stratified into clusters based on age groupings. The percent of the cases that were malignant was notably different among the clusters. Cluster analysis can provide a powerful tool in discerning the subgroups present in a large, heterogeneous computer-aided diagnosis database.

  16. Fusion process of Lennard-Jones clusters: global minima and magic numbers formation

    DEFF Research Database (Denmark)

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

    2004-01-01

    measured for the clusters of noble gas atoms. Our method serves as an efficient alternative to the global optimization techniques based on the Monte-Carlo simulations and it can be applied for the solutions of a broad variety of problems in which atomic cluster structure is important.......We present a new theoretical framework for modeling the fusion process of Lennard–Jones (LJ) 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 paths up to the cluster size of 150 atoms....... We demonstrate that in this way all known global minima structures of the (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 and compare...

  17. 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

  18. DNACLUST: accurate and efficient clustering of phylogenetic marker genes

    Directory of Open Access Journals (Sweden)

    Liu Bo

    2011-06-01

    Full Text Available Abstract Background Clustering is a fundamental operation in the analysis of biological sequence data. New DNA sequencing technologies have dramatically increased the rate at which we can generate data, resulting in datasets that cannot be efficiently analyzed by traditional clustering methods. This is particularly true in the context of taxonomic profiling of microbial communities through direct sequencing of phylogenetic markers (e.g. 16S rRNA - the domain that motivated the work described in this paper. Many analysis approaches rely on an initial clustering step aimed at identifying sequences that belong to the same operational taxonomic unit (OTU. When defining OTUs (which have no universally accepted definition, scientists must balance a trade-off between computational efficiency and biological accuracy, as accurately estimating an environment's phylogenetic composition requires computationally-intensive analyses. We propose that efficient and mathematically well defined clustering methods can benefit existing taxonomic profiling approaches in two ways: (i the resulting clusters can be substituted for OTUs in certain applications; and (ii the clustering effectively reduces the size of the data-sets that need to be analyzed by complex phylogenetic pipelines (e.g., only one sequence per cluster needs to be provided to downstream analyses. Results To address the challenges outlined above, we developed DNACLUST, a fast clustering tool specifically designed for clustering highly-similar DNA sequences. Given a set of sequences and a sequence similarity threshold, DNACLUST creates clusters whose radius is guaranteed not to exceed the specified threshold. Underlying DNACLUST is a greedy clustering strategy that owes its performance to novel sequence alignment and k-mer based filtering algorithms. DNACLUST can also produce multiple sequence alignments for every cluster, allowing users to manually inspect clustering results, and enabling more

  19. 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...... contributions to the theory of cluster stopping in matter as well as for practical applications requiring ultra-shallow implantation and modification of surfaces on the nanoscale. Metal clusters from the magnetron cluster source are of interest for the production of optical sensors to detect specific biological...

  20. 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...

  1. Cosmology and cluster formation

    International Nuclear Information System (INIS)

    Peebles, P.J.E.

    1990-01-01

    I discuss some issues that arise in the attempt to understand what rich clusters of galaxies might teach us about cosmology. First, the mean mass per galaxy in a cluster, if applied to all bright galaxies, yields a mean mass density ∼ 30 percent of the critical Einstein-de Sitter value. Is this because the mass per galaxy is biased low in clusters, or is there in a low density universe? Second, what is the sequence of creation? There are theories in which protoclusters form before galaxies, or after, or the two are more or less coeval. Third, can clusters have formed by gravitational instability out of Gaussian primeval density fluctuations? Or do the observations point to the non-Gaussian perturbations to be expected from cosmic strings, or explosions, or even some variants of inflation? These issues depend on a fourth: do we know the gross physical properties of clusters well enough to use them as constraints on cosmology? I argue that some are too well established to ignore. Their implications for the other issues are not so clear, but progress can be seen. (author)

  2. 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.

  3. Rotating clusters in nuclei

    International Nuclear Information System (INIS)

    Pauling, L.; Robinson, A.B.

    1975-01-01

    Values of R, the radius of rotation of the rotating cluster, are calculated from the energy of the lowest 2 + level of even-even nuclei with the assumption that the cluster consists of p 2 or n 2 respectively, for N or P magic, and of a helion (α) for N or P differing from a magic number by +-2. The values as a function of A show a zigzag course, which is correlated with the polyspheron structure of the nuclei. If the mantle is not overcrowded the cluster glides over the surface of the mantle and the value of R increases by one spheron diameter, about 3.2 fm. At certain values of N a change in structure of the nucleus occurs, with increase in radius of the core by half a spheron diameter, permitting the cluster to drop back into the mantle, with decrease in R by half a spheron diameter. In the lanthanon region of permanent prolate deformation the rotating cluster is a polyhelion, containing the number of helions permitted by the difference between Z or N and the nearest magic number, and in the actinon region it contains all the nucleons beyond 208 Pb, with maximum p 10 n 16 . An explanation is given of the difference between these regions. (author)

  4. 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...

  5. 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).

  6. 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...

  7. Clustering Game Behavior Data

    DEFF Research Database (Denmark)

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

    2015-01-01

    Recent years have seen a deluge of behavioral data from players hitting the game industry. Reasons for this data surge are many and include the introduction of new business models, technical innovations, the popularity of online games, and the increasing persistence of games. Irrespective...... 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...... 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...

  8. Spanish clitic clusters

    Directory of Open Access Journals (Sweden)

    María Cristina Cuervo

    2013-11-01

    Full Text Available This paper deals with a small set of data from clusters of three clitics in Spanish that questions the empirical adequacy and scope of previous analyses of clitic clusters in Romance. It is shown that the output of the Spurious se Rule is not identical to genuine se, at some level that is relevant for linearization of clitics within a cluster. A proposal is presented to capture the neglected data, and this is done in a way that illuminates the debate on the division of labour in clitic phenomena between phonology, morphology and syntax. Central questions in morphology, such as ordering of operations, syncretisms, linearization principles and consequences of lexical insertion are addressed and re-examined.

  9. 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.

  10. 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...... important role to play in both the popular and the political debate and in relation to everyday living conditions. The debate about the future of rural Denmark is also very much a debate about the kind of welfare model we choose in self-governing, municipal Denmark. The centralised, specialised model based...... 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...

  11. Clustering approach for unsupervised segmentation of malarial Plasmodium vivax parasite

    Science.gov (United States)

    Abdul-Nasir, Aimi Salihah; Mashor, Mohd Yusoff; Mohamed, Zeehaida

    2017-10-01

    Malaria is a global health problem, particularly in Africa and south Asia where it causes countless deaths and morbidity cases. Efficient control and prompt of this disease require early detection and accurate diagnosis due to the large number of cases reported yearly. To achieve this aim, this paper proposes an image segmentation approach via unsupervised pixel segmentation of malaria parasite to automate the diagnosis of malaria. In this study, a modified clustering algorithm namely enhanced k-means (EKM) clustering, is proposed for malaria image segmentation. In the proposed EKM clustering, the concept of variance and a new version of transferring process for clustered members are used to assist the assignation of data to the proper centre during the process of clustering, so that good segmented malaria image can be generated. The effectiveness of the proposed EKM clustering has been analyzed qualitatively and quantitatively by comparing this algorithm with two popular image segmentation techniques namely Otsu's thresholding and k-means clustering. The experimental results show that the proposed EKM clustering has successfully segmented 100 malaria images of P. vivax species with segmentation accuracy, sensitivity and specificity of 99.20%, 87.53% and 99.58%, respectively. Hence, the proposed EKM clustering can be considered as an image segmentation tool for segmenting the malaria images.

  12. Inferring marginal association with paired and unpaired clustered data.

    Science.gov (United States)

    Lorenz, Douglas J; Levy, Steven; Datta, Somnath

    2016-09-20

    In the marginal analysis of clustered data, where the marginal distribution of interest is that of a typical observation within a typical cluster, analysis by reweighting has been introduced as a useful tool for estimating parameters of these marginal distributions. Such reweighting methods have foundation in within-cluster resampling schemes that marginalize potential informativeness due to cluster size or within-cluster covariate distribution, to which reweighting methods are asymptotically equivalent. In this paper, we introduce a reweighting scheme for the marginal analysis of clustered data that generalizes prior reweighting methods, with a particular application to measuring bivariate correlation in unpaired clustered data, in which observations of two random variables are not naturally paired at the within-cluster level. We develop unpaired clustered data analogs of well-known product moment correlation coefficients (Pearson, Spearman, phi), as well as the polyserial coefficient for measuring correlation between one discrete and one continuous variable. We evaluate the performance of these coefficients via a simulation study and demonstrate their use by finding no statistically significant association between dental caries at an early age and dental fluorosis at age 13 using a large dental dataset. © The Author(s) 2016.

  13. 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.

  14. 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.

  15. 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....

  16. South Asian Cluster

    Directory of Open Access Journals (Sweden)

    Ionel Sergiu Pirju

    2014-12-01

    Full Text Available This article aims at presenting the South Asian cluster composed of India, Indonesia, Iran and Malaysia, the intercultural values that characterizes it, the supported leadership style and tracing the main macroeconomic considerations which characterizes them. The research is synchronic, analysing the contemporary situation of these countries without reference to their evolution in time, by using the positivist paradigm that explains the reality at one point. It will be analysed the overall cluster with the existing interactions between the countries that composes it, while the article being one of information will avoid building recommendation, or new theories.

  17. A Historical Approach to Clustering in Emerging Economies

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    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...... 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...

  18. Cluster-surface interaction: from soft landing to implantation

    DEFF Research Database (Denmark)

    Popok, Vladimir; Barke, Ingo; Campbell, Eleanor E.B.

    2011-01-01

    The current paper presents a state-of-the-art review in the field of interaction of atomic and molecular clusters with solids. We do not attempt to overview the entire broad field but rather concentrate on impact phenomena: how the physics of the cluster-surface interaction depends on the kinetic...... for utilisation in optics and electronics, as magnetic media and catalysts, in nanobiology and nanomedicine. We pay considerable attention to phenomena occurring on impact of clusters with increased kinetic energies. In particular, we discuss the physics of the intermediate regime between deposition...... for efficient smoothing of surfaces on the macroscopic scale. Several examples of successful applications of the cluster beam technique for polishing of surfaces are given. We also discuss how the physical sputtering can be combined with reactive accelerated cluster erosion. The latter can be an efficient tool...

  19. 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.

  20. Effective implementation of hierarchical clustering

    Science.gov (United States)

    Verma, Mudita; Vijayarajan, V.; Sivashanmugam, G.; Bessie Amali, D. Geraldine

    2017-11-01

    Hierarchical clustering is generally used for cluster analysis in which we build up a hierarchy of clusters. In order to find that which cluster should be split a large amount of observations are being carried out. Here the data set of US based personalities has been considered for clustering. After implementation of hierarchical clustering on the data set we group it in three different clusters one is of politician, sports person and musicians. Training set is the main parameter which decides the category which has to be assigned to the observations that are being collected. The category of these observations must be known. Recognition comes from the formulation of classification. Supervised learning has the main instance in the form of classification. While on the other hand Clustering is an instance of unsupervised procedure. Clustering consists of grouping of data that have similar properties which are either their own or are inherited from some other sources.

  1. 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.

  2. Clustering of resting state networks.

    Science.gov (United States)

    Lee, Megan H; Hacker, Carl D; Snyder, Abraham Z; Corbetta, Maurizio; Zhang, Dongyang; Leuthardt, Eric C; Shimony, Joshua S

    2012-01-01

    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.

  3. Clustering: a neural network approach.

    Science.gov (United States)

    Du, K-L

    2010-01-01

    Clustering is a fundamental data analysis method. It is widely used for pattern recognition, feature extraction, vector quantization (VQ), image segmentation, function approximation, and data mining. As an unsupervised classification technique, clustering identifies some inherent structures present in a set of objects based on a similarity measure. Clustering methods can be based on statistical model identification (McLachlan & Basford, 1988) or competitive learning. In this paper, we give a comprehensive overview of competitive learning based clustering methods. Importance is attached to a number of competitive learning based clustering neural networks such as the self-organizing map (SOM), the learning vector quantization (LVQ), the neural gas, and the ART model, and clustering algorithms such as the C-means, mountain/subtractive clustering, and fuzzy C-means (FCM) algorithms. Associated topics such as the under-utilization problem, fuzzy clustering, robust clustering, clustering based on non-Euclidean distance measures, supervised clustering, hierarchical clustering as well as cluster validity are also described. Two examples are given to demonstrate the use of the clustering methods.

  4. PVM Support for Clusters

    Science.gov (United States)

    Springer, P.

    2000-01-01

    The latest version of PVM (3.4.3) now contains support for a PC cluster running Linux, also known as a Beowulf system. A PVM user of a computer outside the Beowulf system can add the Beowulf as a single machine.

  5. Size selected metal clusters

    Indian Academy of Sciences (India)

    Soft Landing and Fragmentation of Small Clusters Deposited in Noble-Gas Films. Harbich, W.; Fedrigo, S.; Buttet, J. Phys. Rev. B 1998, 58, 7428 ... When gold is not noble: Nanoscale gold catalysts. Sanchez A, Abbet S, Heiz U J. Phys. Chem. A. 1999, 103, 9573.

  6. Structures of Mn clusters

    Indian Academy of Sciences (India)

    Unknown

    agreement about this), while Mn3–Mn8 are clearly ferro- magnetic (Pederson et al 1998; Nayak et al 1998), and the most stable bulk structure, α Mn, is an antiferromag- net. A recent Stern–Gerlach study by Knickelbein (2001) has added fresh interest to the study of Mn. The experi- mental results show that clusters in the ...

  7. 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 ...

  8. 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

  9. 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 ...

  10. 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.

  11. Structures of Mn clusters

    Indian Academy of Sciences (India)

    Unknown

    Mn clusters were studied with a planewave method employing ultrasoft ... using quasi Newton–Raphson and conjugate gradient methods. The optimizations were deemed sufficiently converged when the forces were about 1 meV/Å. The net magnetic moments were ... with LCAO-type local moments. Differing geometries ...

  12. Extended Fuzzy Clustering Algorithms

    NARCIS (Netherlands)

    U. Kaymak (Uzay); M. Setnes

    2000-01-01

    textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applied successfully in various fields including finance and marketing. Despite the successful applications, there are a number of issues that must be dealt with in practical applications of

  13. Cluster Decline and Resilience

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    -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...

  14. Emergence of regional clusters

    DEFF Research Database (Denmark)

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

    2010-01-01

    , networks, labour market pooling and specialised suppliers). However, these factors are not sufficient to explain the early formation of clusters. The dominant theories focus more on explaining ex-post dynamics than their early development. This chapter focuses on the early phase and uses an alternative...

  15. Galaxy Clustering and Merging

    Science.gov (United States)

    Wen, Z. L.

    2011-09-01

    Cosmic structure formation and galaxy evolution are important subjects in astrophysics. The thesis consists of two parts: (1) identification of galaxy clusters and studies of their properties; (2) identification of the mergers of luminous early-type galaxies and gravitational waves (GWs). Most of the galaxy clusters in the previous catalogs have redshifts z≤0.3 with richnesses not well determined. Using the photometric redshifts of galaxies from the Sixth Data Release of Sloan Digital Sky Survey (SDSS DR6), we identify 39716 clusters in the redshift range of 0.05contamination rate and the completeness of member galaxies are found to be ˜20% and ∼90%, respectively. Monte Carlo simulations show that the cluster detection rate is larger than 90% for the massive (M_{200}>2×10^{14} M_{⊙}) clusters with z≤0.42. The false detection rate is ˜5%. We obtain the richness, the summed luminosity and the gross galaxy number. They are tightly correlated with the X-ray luminosity and the temperature of clusters. The cluster mass is also found to be tightly related to the richness and summed luminosity in the form of M_{200}∝ R^{1.90±0.04} and M_{200}∝ L_r^{1.64±0.03}, respectively. In addition, 790 new candidates of X-ray clusters are found by cross-identification of our clusters with the unidentified source list of the ROSAT X-ray survey. By visual inspections of the detected clusters, we recognize 13 gravitational lensing candidates. Among all the candidates, four can be sure strong lensing systems even without further spectroscopic identification, five are more probable and four are possible lenses. In the second part, we discuss the merger rates of luminous early-type galaxies and GWs from the mergers of supermassive black holes (SMBHs). The merger rates of massive galaxies in the local universe are still not clear so far. We select a large sample (1209) of close pairs of galaxies with projected separations 7 kpc

  16. 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

  17. Benchmark of a Cubieboard cluster

    Science.gov (United States)

    Schnepf, M. J.; Gudu, D.; Rische, B.; Fischer, M.; Jung, C.; Hardt, M.

    2015-12-01

    We built a cluster of ARM-based Cubieboards2 which has a SATA interface to connect a harddrive. This cluster was set up as a storage system using Ceph and as a compute cluster for high energy physics analyses. To study the performance in these applications, we ran two benchmarks on this cluster. We also checked the energy efficiency of the cluster using the preseted benchmarks. Performance and energy efficency of our cluster were compared with a network-attached storage (NAS), and with a desktop PC.

  18. Traffic Accident, System Model and Cluster Analysis in GIS

    Directory of Open Access Journals (Sweden)

    Veronika Vlčková

    2015-07-01

    Full Text Available One of the many often frequented topics as normal journalism, so the professional public, is the problem of traffic accidents. This article illustrates the orientation of considerations to a less known context of accidents, with the help of constructive systems theory and its methods, cluster analysis and geoinformation engineering. Traffic accident is reframing the space-time, and therefore it can be to study with tools of technology of geographic information systems. The application of system approach enabling the formulation of the system model, grabbed by tools of geoinformation engineering and multicriterial and cluster analysis.

  19. 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.

  20. 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…

  1. Cluster forest based fuzzy logic for massive data clustering

    Science.gov (United States)

    Lahmar, Ines; Ben Ayed, Abdelkarim; Ben Halima, Mohamed; Alimi, Adel M.

    2017-03-01

    This article is focused in developing an improved cluster ensemble method based cluster forests. Cluster forests (CF) is considered as a version of clustering inspired from Random Forests (RF) in the context of clustering for massive data. It aggregates intermediate Fuzzy C-Means (FCM) clustering results via spectral clustering since pseudo-clustering results are presented in the spectral space in order to classify these data sets in the multidimensional data space. One of the main advantages is the use of FCM, which allows building fuzzy membership to all partitions of the datasets due to the fuzzy logic whereas the classical algorithms as K-means permitted to build just hard partitions. In the first place, we ameliorate the CF clustering algorithm with the integration of fuzzy FCM and we compare it with other existing clustering methods. In the second place, we compare K-means and FCM clustering methods with the agglomerative hierarchical clustering (HAC) and other theory presented methods using data benchmarks from UCI repository.

  2. 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

  3. On the Power and Limits of Sequence Similarity Based Clustering of Proteins Into Families

    DEFF Research Database (Denmark)

    Wiwie, Christian; Röttger, Richard

    2017-01-01

    important to also unravel the proteomic repertoire of an organism. A classical computational approach for detecting protein families is a sequence-based similarity calculation coupled with a subsequent cluster analysis. In this work we have intensively analyzed various clustering tools on a large scale. We...... used the data to investigate the behavior of the tools' parameters underlining the diversity of the protein families. Furthermore, we trained regression models for predicting the expected performance of a clustering tool for an unknown data set and aimed to also suggest optimal parameters...... in an automated fashion. Our analysis demonstrates the benefits and limitations of the clustering of proteins with low sequence similarity indicating that each protein family requires its own distinct set of tools and parameters. All results, a tool prediction service, and additional supporting material is also...

  4. 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.

  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...... for the clusters of noble gases atoms. Our method serves an efficient alternative to the global optimization techniques based on the Monte-Carlo simulations and it can be applied for the solution of a broad variety of problems in which atomic cluster structure is important....

  6. 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

  7. 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...

  8. Quantum Annealing for Combinatorial Clustering

    OpenAIRE

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

    2017-01-01

    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 scale...

  9. Remodularization Analysis Using Semantic Clustering

    OpenAIRE

    Santos, Gustavo; Tulio Valente, Marco; Anquetil, Nicolas

    2014-01-01

    International audience; In this paper, we report an experience on using and adapting Semantic Clustering to evaluate software remodularizations. Semantic Clustering is an approach that relies on information retrieval and clustering techniques to extract sets of similar classes in a system, according to their vocabularies. We adapted Semantic Clustering to support remodularization analysis. We evaluate our adaptation using six real-world remodularizations of four software systems. We report th...

  10. 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....... Eighty-five investigators reached by email. Proposed criteria were in the format of the International Classification of Headache Disorders III-beta (description, criteria, notes, comments and references). Following this evaluation eight drafts were prepared before the final. Twenty-four (28...

  11. Di - lambpha cluster states

    International Nuclear Information System (INIS)

    Motoba, Toshio

    1982-01-01

    The lightest (p, n, Λ) closed-shell hypernucleus sub(ΛΛ) sup(6)He can be considered as a most likely candidate for the unit of hypernuclear cluster structure. First the internal structure of lambpha, α sub(Λ) = sub(ΛΛ) sup(6)He, is investigated by solving the α + Λ + Λ three-body problem microscopically. The compact h. o. wave function (0 s) 6 is found to be a good description for α sub(Λ). Secondly, by using the fully microscopic GCM, we have demonstrated that di - α sub(Λ) cluster states constitute a characteristic rotational band of J = 0 + -- 6 + . The E2 transition rate from particle - stable 2 + to 0 + states is predicted to be 2 - order faster than the weak decay rate of this system. (author)

  12. Arabia Crater Cluster

    Science.gov (United States)

    2004-01-01

    27 May 2004 This Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image shows a portion of a large field of small craters clustered together in northeastern Arabia Terra. Crater clusters usually result from the secondary impact of debris thrown from a much larger impact or from the break-up and impact of fragments of a large meteor. Each crater has subsequently been partially filled by material that erodes to form a rugged crater floor surface, and the general appearance of each crater has been somewhat eroded and modified, as well. The image is located near 34.7oN, 314.7oW, and covers an area about 3 km (1.9 mi) across. Sunlight illuminates the scene from the lower left.

  13. Cluster knockout reactions

    Indian Academy of Sciences (India)

    2014-04-07

    Apr 7, 2014 ... (figure 2), the corresponding α–α t-matrix effective interactions are seen to be widely different (figure 3). 2. Formalism. The finite-range transition matrix element T n,l. BA in the triple differential cross-section [13], d3σ d 1d 2dE1. = Fkin × Sl × |T n,l. BA (kf 1, kf 2, ki)|2 for the (α, 2α) cluster knockout reactions is ...

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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).

  19. Recovery Rate of Clustering Algorithms

    NARCIS (Netherlands)

    Li, Fajie; Klette, Reinhard; Wada, T; Huang, F; Lin, S

    2009-01-01

    This article provides a simple and general way for defining the recovery rate of clustering algorithms using a given family of old clusters for evaluating the performance of the algorithm when calculating a family of new clusters. Under the assumption of dealing with simulated data (i.e., known old

  20. Indispensable tool

    International Nuclear Information System (INIS)

    Robinson, Arthur

    2001-01-01

    Synchrotron radiation has become an indispensable research tool for a growing number of scientists in a seemingly ever expanding number of disciplines. We can thank the European Synchrotron Research Facility (ESRF) in Grenoble for taking an innovative step toward achieving the educational goal of explaining the nature and benefits of synchrotron radiation to audiences ranging from the general public (including students) to government officials to scientists who may be unfamiliar with x-ray techniques and synchrotron radiation. ESRF is the driving force behind a new CD-ROM playable on both PCs and Macs titled Synchrotron light to explore matter. Published by Springer-Verlag, the CD contains both English and French versions of a comprehensive overview of the subject

  1. 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.

  2. Information Theoretic Subspace Clustering.

    Science.gov (United States)

    He, Ran; Wang, Liang; Sun, Zhenan; Zhang, Yingya; Li, Bo

    2016-12-01

    This paper addresses the problem of grouping the data points sampled from a union of multiple subspaces in the presence of outliers. Information theoretic objective functions are proposed to combine structured low-rank representations (LRRs) to capture the global structure of data and information theoretic measures to handle outliers. In theoretical part, we point out that group sparsity-induced measures ( l 2,1 -norm, l α -norm, and correntropy) can be justified from the viewpoint of half-quadratic (HQ) optimization, which facilitates both convergence study and algorithmic development. In particular, a general formulation is accordingly proposed to unify HQ-based group sparsity methods into a common framework. In algorithmic part, we develop information theoretic subspace clustering methods via correntropy. With the help of Parzen window estimation, correntropy is used to handle either outliers under any distributions or sample-specific errors in data. Pairwise link constraints are further treated as a prior structure of LRRs. Based on the HQ framework, iterative algorithms are developed to solve the nonconvex information theoretic loss functions. Experimental results on three benchmark databases show that our methods can further improve the robustness of LRR subspace clustering and outperform other state-of-the-art subspace clustering methods.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Sparse matrix decompositions for clustering

    OpenAIRE

    Blumensath, Thomas

    2014-01-01

    Clustering can be understood as a matrix decomposition problem, where a feature vector matrix is represented as a product of two matrices, a matrix of cluster centres and a matrix with sparse columns, where each column assigns individual features to one of the cluster centres. This matrix factorisation is the basis of classical clustering methods, such as those based on non-negative matrix factorisation but can also be derived for other methods, such as k-means clustering. In this paper we de...

  8. 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 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...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  9. 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.

  10. 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.)

  11. Statistics of sunspot group clusters

    Directory of Open Access Journals (Sweden)

    Getko Ryszarda

    2013-03-01

    Full Text Available The Zubrzycki method is utilized to find all sunspot groups which are close to each other during each Carrington rotation. The sunspot group areas and their positions for the years 1874–2008 are used. The descending, the ascending and the maximum phases of solar cycles for each solar hemisphere are considered separately. To establish the size of the region D where the clusters are searched, the correlation function dependent on the distance between two groups is applied. The method estimates the weighted area of each cluster. The weights dependent on the correlation function of distances between sunspot groups created each cluster. For each cluster the weighted position is also evaluated. The weights dependent on the areas of sunspot groups created a given cluster. The number distribution of the sunspot groups created each cluster and the cluster statistics within different phases of the 11-year cycle and within all considered solar cycles are also presented.

  12. 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

  13. 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

  14. 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.

  15. Measuring Cluster Relaxedness

    Energy Technology Data Exchange (ETDEWEB)

    Moreland, Blythe; /Michigan U. /SLAC

    2012-08-24

    When is a dark matter halo 'relaxed'? In our efforts to understand the structure of the universe, dark matter simulations have provided essential grounds for theoretical predictions. These simulations provide a wealth of ways of parameterizing and measuring the features of astronomical objects. It is these measurements on which we base comparisons of our world and our attempts to re-create it. One of the essential questions dark matter simulations help address is how dark matter halos evolve. How does one characterize different states of that evolution? The focus of this project is identifying cluster relaxedness and how it relates to the internal structure of the halo. A dark matter simulation consists of an N-body simulation which takes an initial set of positions and velocities of the dark matter particles and evolves them under the influence of gravity [6]. Though scientists have so far not been able to detect dark matter particles, the information from these simulations is still valuable especially given the relationship between dark matter halos and galaxy clusters. Galaxies sit within dark matter halos and recent evidence points to filaments of dark matter forming the framework on which galaxy clusters grow [7]. A dark matter halo is a collapsed group of gravitationally bound dark matter particles. Subsets of bound particles form subhalos or substructures. The dark matter simulation is carried out over time - with decreasing redshift (z) or increasing scale factor (a = 1/1+z ). (Thus, z = 0 or a = 1.0 is present-day.) The merger history of a halo can be represented pictorally by a merger tree. A major merger event occurs when a structure joins the main halo with the mass ratio between it and the main halo being above a certain threshold. These events mark important points in the halo's evolution. And it is at these events that one hopes, and perhaps is more likely, to relate measures of relaxedness to this mass accretion. Cluster relaxedness

  16. 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

  17. 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...

  18. DRACULA: Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy

    Science.gov (United States)

    Aguena, Michel; Busti, Vinicius C.; Camacho, Hugo; Sasdelli, Michele; Ishida, Emille E. O.; Vilalta, Ricardo; Trindade, Arlindo M. M.; Gieseke, Fabien; de Souza, Rafael S.; Fantaye, Yabebal T.; Mazzali, Paolo A.

    2015-12-01

    DRACULA classifies objects using dimensionality reduction and clustering. The code has an easy interface and can be applied to separate several types of objects. It is based on tools developed in scikit-learn, with some usage requiring also the H2O package.

  19. 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…

  20. A Beowulf-class computing cluster for the Monte Carlo production of the LHCb experiment

    CERN Document Server

    Avoni, G; Bertin, A; Bruschi, M; Capponi, M; Carbone, A; Collamati, A; De Castro, S; Fabbri, Franco Luigi; Faccioli, P; Galli, D; Giacobbe, B; Lax, I; Marconi, U; Massa, I; Piccinini, M; Poli, M; Semprini-Cesari, N; Spighi, R; Vagnoni, V M; Vecchi, S; Villa, M; Vitale, A; Zoccoli, A

    2003-01-01

    The computing cluster built at Bologna to provide the LHCb Collaboration with a powerful Monte Carlo production tool is presented. It is a performance oriented Beowulf-class cluster, made of rack mounted commodity components, designed to minimize operational support requirements and to provide full and continuous availability of the computing resources. In this paper we describe the architecture of the cluster, and discuss the technical solutions adopted for each specialized sub-system.

  1. SC3: consensus clustering of single-cell RNA-seq data.

    Science.gov (United States)

    Kiselev, Vladimir Yu; Kirschner, Kristina; Schaub, Michael T; Andrews, Tallulah; Yiu, Andrew; Chandra, Tamir; Natarajan, Kedar N; Reik, Wolf; Barahona, Mauricio; Green, Anthony R; Hemberg, Martin

    2017-05-01

    Single-cell RNA-seq enables the quantitative characterization of cell types based on global transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly tool for unsupervised clustering, which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach (http://bioconductor.org/packages/SC3). We demonstrate that SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.

  2. ENHANCE PERFORMANCE OF WEB PROXY CACHE CLUSTER USING CLOUD COMPUTING

    Directory of Open Access Journals (Sweden)

    Najat O. Alsaiari

    2013-12-01

    Full Text Available Web caching is a crucial technology in Internet because it represents an effective means for reducing bandwidth demands, improving web server availability and reducing network latencies. However, Web cache cluster, which is a potent solution to enhance web cache system’s capability, still, has limited capacity and cannot handle tremendous high workload. Maximizing resource utilization and system capability is a very important problem in Web cache cluster. This problem cannot be solved efficiently by merely using load balancing strategies. Thus, along with the advent of cloud computing, we can use cloud based proxies to achieve outstanding performance and higher resource efficiency, compared to traditional Web proxy cache clusters. In this paper, we propose an architecture for cloud based Web proxy cache cluster (CBWPCC and test the effectiveness of the proposed architecture, compared with traditional one in term of response time ,resource utilization using CloudSim tool.

  3. 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.

  4. 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...

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

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Årup; Frutiger, 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...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing. Hum. Brain Mapping 15...

  6. 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.

  7. SBA Innovation Clusters

    Science.gov (United States)

    2012-03-02

    Programs and services to help you start, grow and succeed www.sba.gov U.S. Small Business Administration Your Small Business Resource 1Approved for...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Small Business Administration ,Advanced Defense Technology Cluster,409 3rd St, SW...Z39-18 Programs and services to help you start, grow and succeed www.sba.gov U.S. Small Business Administration Your Small Business Resource

  8. Nanothermodynamics of iron clusters: Small clusters, icosahedral and fcc-cuboctahedral structures

    Science.gov (United States)

    Angelié, C.; Soudan, J.-M.

    2017-05-01

    The study of the thermodynamics and structures of iron clusters has been carried on, focusing on small clusters and initial icosahedral and fcc-cuboctahedral structures. Two combined tools are used. First, energy intervals are explored by the Monte Carlo algorithm, called σ-mapping, detailed in the work of Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. In its flat histogram version, it provides the classical density of states, gp(Ep), in terms of the potential energy of the system. Second, the iron system is described by a potential which is called "corrected EAM" (cEAM), explained in the work of Basire et al. [J. Chem. Phys. 141, 104304 (2014), Paper II]. Small clusters from 3 to 12 atoms in their ground state have been compared first with published Density Functional Theory (DFT) calculations, giving a complete agreement of geometries. The series of 13, 55, 147, and 309 atom icosahedrons is shown to be the most stable form for the cEAM potential. However, the 147 atom cluster has a special behaviour, since decreasing the energy from the liquid zone leads to the irreversible trapping of the cluster in a reproducible amorphous state, 7.38 eV higher in energy than the icosahedron. This behaviour is not observed at the higher size of 309 atoms. The heat capacity of the 55, 147, and 309 atom clusters revealed a pronounced peak in the solid zone, related to a solid-solid transition, prior to the melting peak. The corresponding series of 13, 55, and 147 atom cuboctahedrons has been compared, underscoring the unstability towards the icosahedral structure. This unstability occurs clearly in several steps for the 147 atom cluster, with a sudden transformation at a transition state. This illustrates the concerted icosahedron-cuboctahedron transformation of Buckminster Fuller-Mackay, which is calculated for the cEAM potential. Two other clusters of initial fcc structures with 24 and 38 atoms have been studied, as well as a 302 atom cluster. Each one relaxes

  9. Topological modeling and classification of mammographic microcalcification clusters.

    Science.gov (United States)

    Chen, Zhili; Strange, Harry; Oliver, Arnau; Denton, Erika R E; Boggis, Caroline; Zwiggelaar, Reyer

    2015-04-01

    The presence of microcalcification clusters is a primary sign of breast cancer; however, it is difficult and time consuming for radiologists to classify microcalcifications as malignant or benign. In this paper, a novel method for the classification of microcalcification clusters in mammograms is proposed. The topology/connectivity of individual microcalcifications is analyzed within a cluster using multiscale morphology. This is distinct from existing approaches that tend to concentrate on the morphology of individual microcalcifications and/or global (statistical) cluster features. A set of microcalcification graphs are generated to represent the topological structure of microcalcification clusters at different scales. Subsequently, graph theoretical features are extracted, which constitute the topological feature space for modeling and classifying microcalcification clusters. k-nearest-neighbors-based classifiers are employed for classifying microcalcification clusters. The validity of the proposed method is evaluated using two well-known digitized datasets (MIAS and DDSM) and a full-field digital dataset. High classification accuracies (up to 96%) and good ROC results (area under the ROC curve up to 0.96) are achieved. A full comparison with related publications is provided, which includes a direct comparison. The results indicate that the proposed approach is able to outperform the current state-of-the-art methods. Significance: This study shows that topology modeling is an important tool for microcalcification analysis not only because of the improved classification accuracy but also because the topological measures can be linked to clinical understanding.

  10. Clustering of Biological Datasets in the Era of Big Data

    Directory of Open Access Journals (Sweden)

    Röttger Richard

    2016-03-01

    Full Text Available Clustering is a long-standing problem in computer science and is applied in virtually any scientific field for exploring the inherent structure of datasets. In biomedical research, clustering tools have been utilized in manifold areas, among many others in expression analysis, disease subtyping or protein research. A plethora of different approaches have been developed but there is only little guideline what approach is the optimal in what particular situation. Furthermore, a typical cluster analysis is an entire process with several highly interconnected steps; from preprocessing, proximity calculation, the actual clustering to evaluation and optimization. Only when all steps seamlessly work together, an optimal result can be achieved. This renders a cluster analyses tiresome and error-prone especially for non-experts. A mere trial-and-error approach renders increasingly infeasible when considering the tremendous growth of available datasets; thus, a strategic and thoughtful course of action is crucial for a cluster analysis. This manuscript provides an overview of the crucial steps and the most common techniques involved in conducting a state-of-the-art cluster analysis of biomedical datasets.

  11. Density parameter estimation for finding clusters of homologous proteins-tracing actinobacterial pathogenicity lifestyles

    DEFF Research Database (Denmark)

    Röttger, Richard; Kalaghatgi, Prabhav; Sun, Peng

    2013-01-01

    : all clustering tools need a density parameter that adjusts the number and size of the clusters. This parameter is crucial but hard to estimate without gold standard data at hand. Developing a gold standard, however, is a difficult and time consuming task. Having a reliable method for detecting...

  12. 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...

  13. Gastrointestinal symptom representation in cancer symptom clusters: a synthesis of the literature.

    Science.gov (United States)

    Cherwin, Catherine H

    2012-03-01

    To review how gastrointestinal (GI)symptoms are represented within symptom clusters in patients with cancer receiving chemotherapy. MedLINE, PsycINFO, and CINAHL. Forty-two symptom clusters containing a GI component emerged. Only four clusters were replicated in different samples; 38 were unique clusters. Thirteen different symptom measurement tools were used across the studies. Nineteen different GI symptoms were measured; however, many chemotherapy- or cancer-related GI symptoms known to be present in this population were missing or underrepresented. Twenty-one of the studies reviewed identified a symptom cluster that was primarily (50% or greater) composed of GI symptoms. GI symptoms are prevalent in symptom clusters, but those clusters often are inconsistent. One explanation for this finding may be that current symptom measurement tools do not fully address GI symptoms commonly experienced by patients receiving chemotherapy. Future research should focus on using a comprehensive symptom assessment tool in a homogenous sample of participants who are receiving chemotherapy. Improved measurement of GI symptoms will advance symptom cluster research, which could impact assessment of chemotherapy-related symptoms and development of interventions for symptom clusters.

  14. 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...... give results which are dependent on the initialization of the algorithm. Therefore, it is difficult to assess the significance of the results. We have developed a consensus clustering algorithm, where the final result is averaged over multiple clustering runs, giving a robust and reproducible...

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. The Cluster as Market Organization

    DEFF Research Database (Denmark)

    Maskell, Peter; Lorenzen, Mark

    2003-01-01

    The many competing schools of thought concerning themselves with industrial clusters have atleast one thing in common: they all agree that clusters are real life phenomena characterized bythe co-localization of separate economic entities, which are in some sense related, but not joinedtogether by...... organization or market form. The cluster is one suchspecific market organization that is structured along territorial lines because this enables thebuilding of a set of institutions that are helpful in conducting certain kinds of economicactivities....

  20. The SMART CLUSTER METHOD - adaptive earthquake cluster analysis and declustering

    Science.gov (United States)

    Schaefer, Andreas; Daniell, James; Wenzel, Friedemann

    2016-04-01

    Earthquake declustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity with usual applications comprising of probabilistic seismic hazard assessments (PSHAs) and earthquake prediction methods. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation. Various methods have been developed to address this issue from other researchers. These have differing ranges of complexity ranging from rather simple statistical window methods to complex epidemic models. This study introduces the smart cluster method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal identification. Hereby, an adaptive search algorithm for data point clusters is adopted. It uses the earthquake density in the spatio-temporal neighbourhood of each event to adjust the search properties. The identified clusters are subsequently analysed to determine directional anisotropy, focussing on a strong correlation along the rupture plane and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010/2011 Darfield-Christchurch events, an adaptive classification procedure is applied to disassemble subsequent ruptures which may have been grouped into an individual cluster using near-field searches, support vector machines and temporal splitting. The steering parameters of the search behaviour are linked to local earthquake properties like magnitude of completeness, earthquake density and Gutenberg-Richter parameters. The method is capable of identifying and classifying earthquake clusters in space and time. It is tested and validated using earthquake data from California and New Zealand. As a result of the cluster identification process, each event in

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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)

  6. 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)

  7. 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)

  8. Active matter clusters at interfaces.

    Directory of Open Access Journals (Sweden)

    Katherine eCopenhagen

    2016-03-01

    Full Text Available Collective and directed motility or swarming is an emergent phenomenon displayed by many self-organized assemblies of active biological matter such as clusters of embryonic cells during tissue development, cancerous cells during tumor formation and metastasis, colonies of bacteria in a biofilm, or even flocks of birds and schools of fish at the macro-scale. Such clusters typically encounter very heterogeneous environments. What happens when a cluster encounters an interface between two different environments has implications for its function and fate. Here we study this problem by using a mathematical model of a cluster that treats it as a single cohesive unit that moves in two dimensions by exerting a force/torque per unit area whose magnitude depends on the nature of the local environment. We find that low speed (overdamped clusters encountering an interface with a moderate difference in properties can lead to refraction or even total internal reflection of the cluster. For large speeds (underdamped, where inertia dominates, the clusters show more complex behaviors crossing the interface multiple times and deviating from the predictable refraction and reflection for the low velocity clusters. We then present an extreme limit of the model in the absence of rotational damping where clusters can become stuck spiraling along the interface or move in large circular trajectories after leaving the interface. Our results show a wide range of behaviors that occur when collectively moving active biological matter moves across interfaces and these insights can be used to control motion by patterning environments.

  9. Sleep in cluster headache

    DEFF Research Database (Denmark)

    Barloese, M C J; Jennum, P J; Lund, N T

    2015-01-01

    BACKGROUND AND PURPOSE: Cluster headache (CH) is a primary headache disorder characterized by severe attacks of unilateral pain following a chronobiological pattern. There is a close connection with sleep as most attacks occur during sleep. Hypothalamic involvement and a particular association...... with rapid eye movement (REM) sleep have been suggested. Sleep in a large, well-characterized population of CH patients was investigated. METHODS: Polysomnography (PSG) was performed on two nights in 40 CH patients during active bout and one night in 25 age, sex and body mass index matched controls...... in hospital. Macrostructure and other features of sleep were analyzed and related to phenotype. Clinical headache characterization was obtained by semi-structured interview. RESULTS: Ninety-nine nights of PSG were analyzed. Findings included a reduced percentage of REM sleep (17.3% vs. 23.0%, P = 0...

  10. 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.

  11. 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

  12. Powerful CMD: a tool for color-magnitude diagram studies

    Science.gov (United States)

    Li, Zhong-Mu; Mao, Cai-Yan; Luo, Qi-Ping; Fan, Zhou; Zhao, Wen-Chang; Chen, Li; Li, Ru-Xi; Guo, Jian-Po

    2017-07-01

    We present a new tool for color-magnitude diagram (CMD) studies, Powerful CMD. This tool is built based on the advanced stellar population synthesis (ASPS) model, in which single stars, binary stars, rotating stars and star formation history have been taken into account. Via Powerful CMD, the distance modulus, color excess, metallicity, age, binary fraction, rotating star fraction and star formation history of star clusters can be determined simultaneously from observed CMDs. The new tool is tested via both simulated and real star clusters. Five parameters of clusters NGC 6362, NGC 6652, NGC 6838 and M67 are determined and compared to other works. It is shown that this tool is useful for CMD studies, in particular for those utilizing data from the Hubble Space Telescope (HST). Moreover, we find that inclusion of binaries in theoretical stellar population models may lead to smaller color excess compared to the case of single-star population models.

  13. Advances in Significance Testing for Cluster Detection

    Science.gov (United States)

    Coleman, Deidra Andrea

    surveillance data while controlling the Bayesian False Discovery Rate (BFDR). The procedure entails choosing an appropriate Bayesian model that captures the spatial dependency inherent in epidemiological data and considers all days of interest, selecting a test statistic based on a chosen measure that provides the magnitude of the maximumal spatial cluster for each day, and identifying a cutoff value that controls the BFDR for rejecting the collective null hypothesis of no outbreak over a collection of days for a specified region.We use our procedure to analyze botulism-like syndrome data collected by the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).

  14. 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

  15. 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.

  16. Energy yield prediction of offshore wind farm clusters at the EERA-DTOC European project

    DEFF Research Database (Denmark)

    Cantero, E.; Hasager, Charlotte Bay; Réthoré, Pierre-Elouan

    2013-01-01

    plant interconnection and energy yield models all interrelated with a simplified cost model for the evaluation of layout scenarios. The overall aim is to produce an efficient, easy to use and flexible tool - to facilitate the optimised design of individual and clusters of offshore wind farms....... A demonstration phase at the end of the project will assess the value of the integrated design tool with the help of potential end-users from industry. This abstracts summarizes the objectives and preliminary results of work package 3. In order to provide an accurate value of the expected net energy yield......A new integrated design tool for optimization of offshore wind farm clusters is under development in the European Energy Research Alliance – Design Tools for Offshore wind farm Cluster project (EERA DTOC). The project builds on already established design tools from the project partners and possibly...

  17. 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.

  18. Report on the ESO Workshop "Early Stages of Galaxy Cluster Formation 2017 (GCF2017)"

    Science.gov (United States)

    Mroczkowski, T.; Stroe, A.; Andreani, P.; Arnaud, M.; Arrigoni Battaia, F..; De Breuck, C..; Sobral, D.

    2017-12-01

    The formation of the largest gravitationally bound structures in the Universe, clusters of galaxies, and how these environments affect the galaxies within them are major themes in cosmology and galaxy evolution. The high-redshift progenitors of clusters, called "protoclusters", are still in the process of hierarchical assembly. The transition from protocluster to cluster is gradual, driven by accretion and spectacular mergers that are expected to last roughly one billion years. This workshop aimed to address open questions in protocluster and cluster formation, to define the similarities and distinctions between the two, and to evaluate the best tools and methods for their detection and study.

  19. 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

  20. 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)

  1. 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

  2. Cluster-based tangible programming

    CSIR Research Space (South Africa)

    Smith, Andrew C

    2014-05-01

    Full Text Available Clustering is the act of grouping items that belong together. In this paper we explore clustering as a means to construct tangible program logic, and specifically as a means to use multiple tangible objects collectively as a single tangible program...

  3. Observational constraints on cluster evolution

    NARCIS (Netherlands)

    Larsen, S.S.

    2008-01-01

    Current observational constraints on the dynamical evolution of star clusters are reviewed. Theory and observations now agree nicely on the mass dependency and time scales for disruption of young star clusters in galactic disks, but many problems still await resolution. The origin of the mass

  4. 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)

  5. 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

  6. 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....

  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. Innovative clusters: a solution for the economic development of Romania

    Directory of Open Access Journals (Sweden)

    Mihaela-Cornelia DAN

    2012-09-01

    Full Text Available The Europe 2020 Strategy emphasizes the importance of the smart, sustainable and inclusive growth. The flagships of the strategy (digital agenda for the EU, innovation union, resource efficient Europe, industrial policy for the globalization agenda are setting the frame for economic development. Innovative clusters are seen as a solution to the crisis, a tool for competitiveness and regional development. Given the economic situation of Romania we bring in discussion the potential of clusters in our country and the arguments and critics regarding their development.

  9. 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 z generation of CMB and large scale structure 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.

  10. Cluster Analytical Method of Fault Risk Analysis in Systems

    Science.gov (United States)

    Michaľčonok, German; Horalová Kalinová, Michaela

    2016-12-01

    In providing safety functions, the proposal of safety functions of control systems is an important part of a risk reduction strategy. In the specification of security requirements, it is necessary to determine and document individual characteristics and the desired performance level for each safety. This article presents the results of the experiment cluster analysis. The results of the experiment prove that the methods of cluster analysis provide a suitable tool for analyzing the reliability of safety systems analysis. Regarding the increasing complexity of the systems, we can state that the application of these methods in the subject area is a good choice.

  11. Symptom-Based Clustering in Chronic Rhinosinusitis Relates to History of Aspirin Sensitivity and Postsurgical Outcomes.

    Science.gov (United States)

    Divekar, Rohit; Patel, Neil; Jin, Jay; Hagan, John; Rank, Matthew; Lal, Devyani; Kita, Hirohito; O'Brien, Erin

    2015-01-01

    Symptoms burden in chronic rhinosinusitis (CRS) may be assessed by interviews or by means of validated tools such as the 22-item SinoNasal Outcome Test (SNOT-22). However, when only the total SNOT-22 scores are used, the pattern of symptom distribution and heterogeneity in patient symptoms is lost. To use a standardized symptom assessment tool (SNOT-22) on preoperative symptoms to understand symptom heterogeneity in CRS and to aid in characterization of distinguishing clinical features between subgroups. This was a retrospective review of 97 surgical patients with CRS. Symptom-based clusters were derived on the basis of presurgical SNOT-22 scores using unsupervised analysis and network graphs. Comparison between clusters was performed for clinical and demographic parameters, postsurgical symptom scores, and presence or absence of a history of aspirin sensitivity. Unsupervised analysis reveals coclustering of specific symptoms in the SNOT-22 tool. Using symptom-based clustering, patients with CRS were stratified into severe overall (mean total score, 90.8), severe sinonasal (score, 62), moderate sinonasal (score, 40), moderate nonsinonasal (score, 37) and mild sinonasal (score, 16) clusters. The last 2 clusters were associated with lack of history of aspirin sensitivity. The first cluster had a rapid relapse in symptoms postoperatively, and the last cluster demonstrated minimal symptomatic improvement after surgery. Symptom-based clusters in CRS reveal a distinct grouping of symptom burden that may relate to aspirin sensitivity and treatment outcomes. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  12. NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

    Science.gov (United States)

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

    2008-01-01

    The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources. PMID:18524799

  13. An effective fuzzy kernel clustering analysis approach for gene expression data.

    Science.gov (United States)

    Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

    2015-01-01

    Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

  14. 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.

  15. Relative Ages of Globular Clusters

    Science.gov (United States)

    Puzia, Thomas H.

    Ages of extragalactic globular clusters can provide valuable insights into the formation and evolution of galaxies. In this contribution the photometric methods of age dating old globular cluster systems are summarised. The spectroscopic approach is reviewed with an emphasis of the fight choice of age diagnostics. We present a new method of quantifying the relatively best age-sensitive spectroscopic index given the quality of a data set and a certain theoretical stellar synthesis model. The relatively best diagnostic plot is constructed from the set of Lick indices and used to age date globular clusters in several early-type galaxies which are part of a large spectroscopic survey of extragalactic globular cluster systems. We find that, independently of host galaxy, metal-poor ([Fe/H] old (t > 8 Gyr) and coeval. Metal-rich clusters show a wide range of ages from ˜ 15 down to a few Gyr.

  16. 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.

  17. 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...

  18. 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)

  19. Semantic Based Cluster Content Discovery in Description First Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    MUHAMMAD WASEEM KHAN

    2017-01-01

    Full Text Available 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.

  20. 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

  1. Information Clustering Based on Fuzzy Multisets.

    Science.gov (United States)

    Miyamoto, Sadaaki

    2003-01-01

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

  2. 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

  3. Clustering and community detection in directed networks: A survey

    Science.gov (United States)

    Malliaros, Fragkiskos D.; Vazirgiannis, Michalis

    2013-12-01

    Networks (or graphs) appear as dominant structures in diverse domains, including sociology, biology, neuroscience and computer science. In most of the aforementioned cases graphs are directed - in the sense that there is directionality on the edges, making the semantics of the edges nonsymmetric as the source node transmits some property to the target one but not vice versa. An interesting feature that real networks present is the clustering or community structure property, under which the graph topology is organized into modules commonly called communities or clusters. The essence here is that nodes of the same community are highly similar while on the contrary, nodes across communities present low similarity. Revealing the underlying community structure of directed complex networks has become a crucial and interdisciplinary topic with a plethora of relevant application domains. Therefore, naturally there is a recent wealth of research production in the area of mining directed graphs - with clustering being the primary method sought and the primary tool for community detection and evaluation. The goal of this paper is to offer an in-depth comparative review of the methods presented so far for clustering directed networks along with the relevant necessary methodological background and also related applications. The survey commences by offering a concise review of the fundamental concepts and methodological base on which graph clustering algorithms capitalize on. Then we present the relevant work along two orthogonal classifications. The first one is mostly concerned with the methodological principles of the clustering algorithms, while the second one approaches the methods from the viewpoint regarding the properties of a good cluster in a directed network. Further, we present methods and metrics for evaluating graph clustering results, demonstrate interesting application domains and provide promising future research directions.

  4. 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

  5. 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.

  6. 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.

  7. 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 .

  8. Water clustering in glassy polymers.

    Science.gov (United States)

    Davis, Eric M; Elabd, Yossef A

    2013-09-12

    In this study, water solubility and water clustering in several glassy polymers, including poly(methyl methacrylate) (PMMA), poly(styrene) (PS), and poly(vinylpyrrolidone) (PVP), were measured using both quartz spring microbalance (QSM) and Fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectroscopy. Specifically, QSM was used to determine water solubility, while FTIR-ATR spectroscopy provided a direct, molecular-level measurement of water clustering. The Flory-Huggins theory was employed to obtain a measure of water-polymer interaction and water solubility, through both prediction and regression, where the theory failed to predict water solubility in both PMMA and PVP. Furthermore, a comparison of water clustering between direct FTIR-ATR spectroscopy measurements and predictions from the Zimm-Lundberg clustering analysis produced contradictory results. The failure of the Flory-Huggins theory and Zimm-Lundberg clustering analysis to describe water solubility and water clustering, respectively, in these glassy polymers is in part due to the equilibrium constraints under which these models are derived in contrast to the nonequilibrium state of glassy polymers. Additionally, FTIR-ATR spectroscopy results were compared to temperature-dependent diffusivity data, where a correlation between the activation energy for diffusion and the measured water clustering was observed.

  9. The Extended Virgo Cluster Catalog

    Science.gov (United States)

    Rey, Soo-Chang

    2015-08-01

    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 deg2 or 60.1 Mpc2. 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-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.

  10. THE EXTENDED VIRGO CLUSTER CATALOG

    International Nuclear Information System (INIS)

    Kim, Suk; Rey, Soo-Chang; Lee, Youngdae; Chung, Jiwon; Pak, Mina; Yi, Wonhyeong; Lee, Woong; Jerjen, Helmut; Lisker, Thorsten; Sung, Eon-Chang

    2014-01-01

    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 2 or 60.1 Mpc 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 –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

  11. 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.

  12. On a correlational clustering of integers

    OpenAIRE

    Aszalós, László; Hajdu, Lajos; Pethő, Attila

    2016-01-01

    Correlation clustering is a concept of machine learning. The ultimate goal of such a clustering is to find a partition with minimal conflicts. In this paper we investigate a correlation clustering of integers, based upon the greatest common divisor.

  13. 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.

  14. FunGeneClusterS

    DEFF Research Database (Denmark)

    Vesth, Tammi Camilla; Brandl, Julian; Andersen, Mikael Rørdam

    2016-01-01

    and industrial biotechnology applications. We have previously published a method for accurate prediction of clusters from genome and transcriptome data, which could also suggest cross-chemistry, however, this method was limited both in the number of parameters which could be adjusted as well as in user......Secondary metabolites of fungi are receiving an increasing amount of interest due to their prolific bioactivities and the fact that fungal biosynthesis of secondary metabolites often occurs from co-regulated and co-located gene clusters. This makes the gene clusters attractive for synthetic biology...

  15. 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

  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. Neural Gas Clustering Adapted for Given Size of Clusters

    Directory of Open Access Journals (Sweden)

    Iveta Dirgová Luptáková

    2016-01-01

    Full Text Available Clustering algorithms belong to major topics in big data analysis. Their main goal is to separate an unlabelled dataset into several subsets, with each subset ideally characterized by some unique characteristic of its data structure. Common clustering approaches cannot impose constraints on sizes of clusters. However, in many applications, sizes of clusters are bounded or known in advance. One of the more recent robust clustering algorithms is called neural gas which is popular, for example, for data compression and vector quantization used in speech recognition and signal processing. In this paper, we have introduced an adapted neural gas algorithm able to accommodate requirements for the size of clusters. The convergence of algorithm towards an optimum is tested on simple illustrative examples. The proposed algorithm provides better statistical results than its direct counterpart, balanced k-means algorithm, and, moreover, unlike the balanced k-means, the quality of results of our proposed algorithm can be straightforwardly controlled by user defined parameters.

  18. 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...

  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. Route Availabililty Planning Tool -

    Data.gov (United States)

    Department of Transportation — The Route Availability Planning Tool (RAPT) is a weather-assimilated decision support tool (DST) that supports the development and execution of departure management...

  1. Collective Management of Satellite Clusters

    National Research Council Canada - National Science Library

    Tierno, Jorge

    2002-01-01

    .... We applied optimization methods to develop low-fuel trajectories compatible with operational requirements and market-oriented programming to solve the cluster reconfiguration problem with minimal fuel usage...

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. Chemical evolution of star clusters.

    Science.gov (United States)

    van Loon, Jacco Th

    2010-02-28

    I discuss the chemical evolution of star clusters, with emphasis on old Galactic globular clusters (GCs), in relation to their formation histories. GCs are clearly formed in a complex fashion, under markedly different conditions from any younger clusters presently known. Those special conditions must be linked to the early formation epoch of the Galaxy and must not have occurred since. While a link to the formation of GCs in dwarf galaxies has been suggested, present-day dwarf galaxies are not representative of the gravitational potential wells within which the GCs formed. Instead, a formation deep within the proto-Galaxy or within dark-matter mini-haloes might be favoured. Not all GCs may have formed and evolved similarly. In particular, we may need to distinguish Galactic Halo from Galactic Bulge clusters.

  7. 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

  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. 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.

  10. 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.

  11. Acoustical sensing of cardiomyocyte cluster beating

    International Nuclear Information System (INIS)

    Tymchenko, Nina; Kunze, Angelika; Dahlenborg, Kerstin; Svedhem, Sofia; Steel, Daniella

    2013-01-01

    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

  12. 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.

  13. Merger relics of cluster galaxies

    Science.gov (United States)

    Yi, S. K.; Lee, J.; Jung, I.; Ji, I.; Sheen, Y.-K.

    2013-06-01

    Context. Sheen and collaborators recently found that a surprisingly large portion (38%) of massive early-type galaxies in heavy clusters show strong merger-related disturbed features. This contradicts the general understanding that massive clusters are hostile environments for galaxy mergers. Considering the significance of mergers in galaxy evolution, it is important to understand this. Aims: We aim to present a theoretical foundation that explains galaxy mergers in massive clusters. Methods: We used the N-body simulation technique to perform a cosmological-volume simulation and derive dark-halo merger trees. Then, we used the semi-analytic modeling technique to populate each halo with galaxies. We ran hydrodynamic simulations of galaxy mergers to estimate the lifetime of merger features for the imaging condition used by Sheen and collaborators. We applied this merger feature lifetime to our semi-analytic models. Finally, we counted the massive early-type galaxies in heavy model clusters that would show strong merger features. Results: While there still are substantial uncertainties, our preliminary results are remarkably close to the observed fraction of galaxies with merger features. Key ingredients for the success are twofold: firstly, the subhalo motion in dark haloes has been accurately traced, and, second, the lifetime of merger features has been properly estimated. As a result, merger features are expected to last very long in cluster environments. Many massive early-type galaxies in heavy clusters therefore show merger features not because they experience mergers in the current clusters in situ, but because they still carry their merger features from their previous halo environments. Conclusions: Investigating the merger relics of cluster galaxies is potentially important, because it uniquely allows us to backtrack the halo merger history.

  14. Fluorescent Silicon Clusters and Nanoparticles

    OpenAIRE

    von Haeften, Klaus

    2017-01-01

    The fluorescence of silicon clusters is reviewed. Atomic clusters of silicon have been at the focus of research for several decades because of the relevance of size effects for material properties, the importance of silicon in electronics and the potential applications in bio-medicine. To date numerous examples of nanostructured forms of fluorescent silicon have been reported. This article introduces the principles and underlying concepts relevant for fluorescence of nanostructured silicon su...

  15. Acculturation Clusters and Life Satisfaction

    OpenAIRE

    Brown,Carrie M.; Gibbons,Judith L.; Hughes,Honore M.

    2013-01-01

    The purpose of our study was to determine if acculturation variables from different acculturation domains form empirically extracted acculturation clusters [based on Berry's (1997) model], and if the clusters are related to the life satisfaction of first and second generation immigrant college students. One hundred twenty-two students attending a university in the Midwestern USA (70% female), representing more than 20 countries of origin, completed an online questionnaire. Hierarchical cluste...

  16. 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...

  17. Presentation on systems cluster research

    Science.gov (United States)

    Morgenthaler, George W.

    1989-01-01

    This viewgraph presentation presents an overview of systems cluster research performed by the Center for Space Construction. The goals of the research are to develop concepts, insights, and models for space construction and to develop systems engineering/analysis curricula for training future aerospace engineers. The following topics are covered: CSC systems analysis/systems engineering (SIMCON) model, CSC systems cluster schedule, system life-cycle, model optimization techniques, publications, cooperative efforts, and sponsored research.

  18. 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

  19. 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.

  20. The formation of star clusters

    Science.gov (United States)

    Whitmore, Bradley C.

    The ability of HST to resolve objects ten times smaller than possible from the ground has re-juvenated the study of young star clusters. A recurrent morphological theme found in nearby resolved systems is the observation of young (typically 1-10 Myr), massive (103 - 104 Msolar), compact (ρ≍105 Msolar pc-3) clusters which have evacuated the gas and dust from a spherical region around themselves. New stars are being triggered into formation along the edges of the envelopes, with pillars (similar to the Eagle Nebula) of molecular gas streaming away from the regions of star formation. The prototype for these objects is 30 Doradus. Another major theme has been the discovery of large numbers of young (typically 1-500 Myr), massive (103 - 108 Msolar), compact star clusters in merging, starbursting, and even some barred and spiral galaxies. The brightest of these clusters have all the attributes expected of protoglobular clusters, hence allowing us to study the formation of globular clusters in the local universe rather than trying to ascertain how they formed ≍14 Gyr ago. The prototype is the Antennae Galaxy.

  1. 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.)

  2. The formation of cluster galaxies

    Science.gov (United States)

    Mancone, Conor L.

    2012-06-01

    In this work I sought to understand the formation and evolution of galaxies. Specifically, I studied three key aspects of galaxy formation: star formation, mass assembly, and structural evolution. Past research has shown that the formation of a galaxy is strongly coupled to its local environment (i.e. the local galaxy density). Therefore, I studied the evolution of cluster galaxies because clusters are the highest density environments that exist in the universe. In turn, the observational results found herein form a foundation upon which to test theories of galaxy formation in the densest environments. I used the latest sample of galaxy clusters from the Bootes region to measure the near-infrared luminosity function (NIR LF) of cluster galaxies from 0 1.3. I used deeper IRAC imaging to study the NIR LF of high redshift cluster galaxies (1 pulsating AGB stars, which are poorly understood observationally but contribute substantially to the NIR light of a stellar population. I also created the Python Galaxy Fitter (PyGFit), a program which measures PSF matched photometry from crowded imaging with disparate PSFs and resolutions. This enabled accurate measurement of spectral energy distributions (SEDs) in crowded cluster fields.

  3. Understanding Galaxy Cluster MKW10

    Science.gov (United States)

    Sanders, Tim; Henry, Swain; Coble, Kimberly A.; Rosenberg, Jessica L.; Koopmann, Rebecca A.

    2015-01-01

    As part of the Undergraduate ALFALFA Team (UAT), we are studying the galaxy cluster MKW 10 (RA = 175.454, Dec = 10.306, z ~ 0.02), a poor cluster with a compact core in which tidal interactions have occurred. This cluster has been observed in HI and Hα. We used SDSS and NED to search for optical counterparts. By comparing data at multiple wavelengths, we hope to understand the structure, environment, and star formation history of this cluster. Following the techniques of others involved in the groups project and using the program TOPCAT to manipulate the data, we explored both the spatial and velocity distributions to determine cluster membership. We have determined that this cluster consists of 11 galaxies, mostly spiral in shape. Chicago State University is new the UAT and we began our work after taking part in the winter workshop at Arecibo.This work was supported by: Undergraduate ALFALFA Team NSF Grant AST-1211005 and the Illinois Space Grant Consortium.

  4. Velocity evolution of galaxy clustering

    Energy Technology Data Exchange (ETDEWEB)

    Saslaw, W.C.; Aarseth, S.J.

    1982-02-15

    We have examined the changing velocity distribution of galaxies as they cluster in computer models of the expanding universe. The models are 4000-body numerical simulations of galaxies with a large range of masses interacting gravitationally. Clustering in velocity space is measured by calculating the residual peculiar velocities around the Hubble expansion. These form ''Hubble streaks as clustering progresses. We distinguish isolated field galaxies from clustered galaxies. In contrast to the usual belief, the velocity dispersion of the most extreme field galaxies does not decrease adiabatically. Rather, it is dominated by the perturbations of distant large clusters as they form and it decreases much more slowly than the inverse expansion length scale, R/sup -1/. The velocity dispersion of extreme field galaxies is a good cosmological indicator of ..cap omega.. = rho/rho/sub crit/. Preliminary comparison of several simulations with observtions shows that our universe agrees better with low density models, ..cap omega..< or =0.1. The velocity dispersion of cluster centers of mass is a good cosmological marker as well. We also suggest another new method for estimating ..cap omega.., based on the history of extreme field galaxies.

  5. 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.

  6. Energy dissipation and clustering in granular streams

    Science.gov (United States)

    Waitukaitis, Scott; Royer, John; Gruetjen, Helge; Jaeger, Heinrich

    2009-11-01

    The presence of weak cohesive forces between macroscopic grains can lead to the break up of a free falling granular stream, similar to the surface-tension-driven break up of a liquid streamfootnotetext Royer, J. R. et al. Nature 459 1110 - 1113 (2009).. This sensitivity to minute forces suggests that these free falling streams could serve as a tool to probe the interactions between grains. In order to investigate the connection between the stream dynamics and the grain-grain interactions, we perform molecular dynamics simulations of a granular stream freely falling out of a hopper varying the cohesion and inelasticity of the grains. We find that in the absence of cohesive forces the stream breaks apart into isolated grains, in contrast to the clustering observed in simulations of inelastic granular gases. For sufficiently high cohesive forces we reproduce the break up of stream into droplets, while with lower cohesive forces the stream breaks up into smaller clusters consisting of only a few grains. Measuring the change in contact number and decay of velocity fluctuations with depth, we characterize the different regions of the force-inelasticity phase space.

  7. CASSIS and SMIPS: promoter-based prediction of secondary metabolite gene clusters in eukaryotic genomes.

    Science.gov (United States)

    Wolf, Thomas; Shelest, Vladimir; Nath, Neetika; Shelest, Ekaterina

    2016-04-15

    Secondary metabolites (SM) are structurally diverse natural products of high pharmaceutical importance. Genes involved in their biosynthesis are often organized in clusters, i.e., are co-localized and co-expressed. In silico cluster prediction in eukaryotic genomes remains problematic mainly due to the high variability of the clusters' content and lack of other distinguishing sequence features. We present Cluster Assignment by Islands of Sites (CASSIS), a method for SM cluster prediction in eukaryotic genomes, and Secondary Metabolites by InterProScan (SMIPS), a tool for genome-wide detection of SM key enzymes ('anchor' genes): polyketide synthases, non-ribosomal peptide synthetases and dimethylallyl tryptophan synthases. Unlike other tools based on protein similarity, CASSIS exploits the idea of co-regulation of the cluster genes, which assumes the existence of common regulatory patterns in the cluster promoters. The method searches for 'islands' of enriched cluster-specific motifs in the vicinity of anchor genes. It was validated in a series of cross-validation experiments and showed high sensitivity and specificity. CASSIS and SMIPS are freely available at https://sbi.hki-jena.de/cassis thomas.wolf@leibniz-hki.de or ekaterina.shelest@leibniz-hki.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  8. 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

  9. Equilibrium cluster fluids: pair interactions via inverse design.

    Science.gov (United States)

    Jadrich, R B; Bollinger, J A; Lindquist, B A; Truskett, T M

    2015-12-28

    Inverse methods of statistical mechanics are becoming productive tools in the design of materials with specific microstructures or properties. While initial studies have focused on solid-state design targets (e.g., assembly of colloidal superlattices), one can alternatively design fluid states with desired morphologies. This work addresses the latter and demonstrates how a simple iterative Boltzmann inversion strategy can be used to determine the isotropic pair potential that reproduces the radial distribution function of a fluid of amorphous clusters with prescribed size. The inverse designed pair potential of this "ideal" cluster fluid, with its broad attractive well and narrow repulsive barrier at larger separations, is qualitatively different from the so-called SALR form most commonly associated with equilibrium cluster formation in colloids, which features short-range attractive (SA) and long-range repulsive (LR) contributions. These differences reflect alternative mechanisms for promoting cluster formation with an isotropic pair potential, and they in turn produce structured fluids with qualitatively different static and dynamic properties. Specifically, equilibrium simulations show that the amorphous clusters resulting from the inverse designed potentials display more uniformity in size and shape, and they also show greater spatial and temporal resolution than those resulting from SALR interactions.

  10. Local Management of National Cluster Policies: Comparative Case Studies of Japanese, German, and French Biotechnology Clusters

    Directory of Open Access Journals (Sweden)

    Hiroyuki Okamuro

    2015-11-01

    Full Text Available Cluster policies have attracted increasing attention worldwide, but only a few studies have focused on their management by local cluster organizations. We investigate the relationship between national cluster policies and their management by local cluster organizations from a comparative perspective. For this purpose, we provide a detailed comparison of national cluster policies in Japan, Germany, and France as well as six prominent biotechnology clusters in these countries. Information on the focal clusters and on the management of cluster policies was obtained using semi-structured interviews with cluster managers. We find that national cluster policies considerably differ among these countries according to basic conditions of clusters and that the patterns of national cluster policy are closely related to those of local cluster management, despite some differences between clusters in the same country caused by various regional characteristics.

  11. 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.

  12. Implementation of hybrid clustering based on partitioning around medoids algorithm and divisive analysis on human Papillomavirus DNA

    Science.gov (United States)

    Arimbi, Mentari Dian; Bustamam, Alhadi; Lestari, Dian

    2017-03-01

    Data clustering can be executed through partition or hierarchical method for many types of data including DNA sequences. Both clustering methods can be combined by processing partition algorithm in the first level and hierarchical in the second level, called hybrid clustering. In the partition phase some popular methods such as PAM, K-means, or Fuzzy c-means methods could be applied. In this study we selected partitioning around medoids (PAM) in our partition stage. Furthermore, following the partition algorithm, in hierarchical stage we applied divisive analysis algorithm (DIANA) in order to have more specific clusters and sub clusters structures. The number of main clusters is determined using Davies Bouldin Index (DBI) value. We choose the optimal number of clusters if the results minimize the DBI value. In this work, we conduct the clustering on 1252 HPV DNA sequences data from GenBank. The characteristic extraction is initially performed, followed by normalizing and genetic distance calculation using Euclidean distance. In our implementation, we used the hybrid PAM and DIANA using the R open source programming tool. In our results, we obtained 3 main clusters with average DBI value is 0.979, using PAM in the first stage. After executing DIANA in the second stage, we obtained 4 sub clusters for Cluster-1, 9 sub clusters for Cluster-2 and 2 sub clusters in Cluster-3, with the BDI value 0.972, 0.771, and 0.768 for each main cluster respectively. Since the second stage produce lower DBI value compare to the DBI value in the first stage, we conclude that this hybrid approach can improve the accuracy of our clustering results.

  13. Building Simple Annotation Tools

    OpenAIRE

    Lin, Gordon

    2016-01-01

    The right annotation tool does not always exist for processing a particular natural language task. In these scenarios, researchers are required to build new annotation tools to fit the tasks at hand. However, developing new annotation tools is difficult and inefficient. There has not been careful consideration of software complexity in current annotation tools. Due to the problems of complexity, new annotation tools must reimplement common annotation features despite the availability of imple...

  14. The Origin and Evolution of Rich Clusters

    Science.gov (United States)

    Hora, Joseph

    observations will allow us to compare star formation in these massive inner Galaxy regions to star formation near the Sun, and in the outer Galaxy, and therefore to complete a more representative view of star formation. This work will further NASA's goals of learning about the universe and understanding how it began and evolved into what we see today. The knowledge we gain about the formation and evolution of stars in the most massive clusters in the Galaxy will enhance our understanding of these important processes, and the data products we develop will provide an important tool to other researchers, and a key resource for further observations with other NASA missions such as JWST.

  15. Cluster Grouping: A Strategy for Effective Teaching.

    Science.gov (United States)

    Dexter, D. Kay

    1998-01-01

    A teacher describes the use of cluster grouping to meet the needs of six gifted students in her heterogeneous classroom. Considered are the definition and rationale for cluster grouping, classroom structure, cluster identification and profile, facilitation of cluster curriculum differentiation, teacher perceptions, and student/parent perceptions.…

  16. 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…

  17. Statistics of clusters in binary linear lattices

    NARCIS (Netherlands)

    Felderhof, B.U.

    The statistics of clusters in binary linear lattices is studied on the assumption that the relative weight of an Al or Bm cluster is determined only by its size l or m, and is independent of the location of the cluster on the chain. The average cluster numbers and the variance of their fluctuations

  18. Quantum Monte Carlo methods and lithium cluster properties. [Atomic clusters

    Energy Technology Data Exchange (ETDEWEB)

    Owen, R.K.

    1990-12-01

    Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) (0.1981), 0.1895(9) (0.1874(4)), 0.1530(34) (0.1599(73)), 0.1664(37) (0.1724(110)), 0.1613(43) (0.1675(110)) Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) (0.0203(12)), 0.0188(10) (0.0220(21)), 0.0247(8) (0.0310(12)), 0.0253(8) (0.0351(8)) Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.

  19. 3D simulation of the Cluster-Cluster Aggregation model

    Science.gov (United States)

    Li, Chao; Xiong, Hailing

    2014-12-01

    We write a program to implement the Cluster-Cluster Aggregation (CCA) model with java programming language. By using the simulation program, the fractal aggregation growth process can be displayed dynamically in the form of a three-dimensional (3D) figure. Meanwhile, the related kinetics data of aggregation simulation can be also recorded dynamically. Compared to the traditional programs, the program has better real-time performance and is more helpful to observe the fractal growth process, which contributes to the scientific study in fractal aggregation. Besides, because of adopting java programming language, the program has very good cross-platform performance.

  20. [Violence clusters in Pernambuco, Brazil].

    Science.gov (United States)

    de Lima, Maria Luiza C; Ximenes, Ricardo A de A; Feitosa, Carlos Luna; de Souza, Edinilsa Ramos; de Albuquerque, Maria de Fátima P Militão; Barros, Maria Dilma de Alencar; de Souza, Wayner Vieira; Lapa, Tiago Maria

    2005-08-01

    To analyze the spatial distribution of homicide mortality rates among males 15 to 49 years old in the state of Pernambuco, Brazil, for the periods of 1980 to 1984 and 1995 to 1998, and to identify violence clusters. Mortality data were obtained from the Brazilian Ministry of Health's Mortality Information System. The mean homicide mortality rate was estimated for each municipality in the state for the two periods. The Moran coefficient was calculated to determine spatial autocorrelation. (The Moran coefficient ranges from -1 to +1, with a positive coefficient indicating a cluster of similar values, and a negative coefficient indicating adjacent dissimilar values.) To identify clusters of municipalities with either high or low homicide mortality rates, the local indicator of spatial association (LISA) was used. Finally, a Moran map was constructed to identify municipalities with statistically significant LISA values and to identify clusters of municipalities with either high or low homicide mortality rates. The Moran coefficient for 1980-1984 was 0.392, and for 1995-1998 it was 0.291 (P Maconha). This study suggests that the violence clusters are not the result of the socioeconomic conditions per se, but rather the consequence of the interaction between poor economic conditions and drug trafficking.

  1. Clusters - Territorial Networks. Where to?

    Directory of Open Access Journals (Sweden)

    Luiza Nicoleta Radu

    2013-08-01

    Full Text Available Globalization has led to an increased international trade relations between organizations spatially separated. This determined a greater spatial differentiation influenced by local and regional competition production systems. Territoriality has been considered as the main cause for the development of active areas, explaining also the success of certain local systems of production that became competitive on a global scale. The new school of regional competitiveness promoted by Porter (2003 identifies the cluster industry as a source of competitive advantages, supporting the identification and cluster setting – up as an objective of the public policy. In the last few years, clusters became an important basis for the new policies promoted at the level of the European Union. The challenges established through the Lisbon Strategy, respectively “to make the Europe the most competitive and dynamic based knowledge economy”, determinate a new approach of the economic policy in order to increase competitiveness. For the regional economy, the cluster has the aim to develop new strategies focused on the economic sectors of the regional development, by taking into account sectoral advantages. However, in terms of economic activities promoted at regional level, the spatial development is an essential component for increasing EU competitiveness in terms of economic globalization trends, regional networks being considered the most advanced form of cluster in the economic sector.

  2. Dynamic of Faceted Colloidal Clusters

    Science.gov (United States)

    Sindoro, Melinda; Jee, Ah-Young; Yu, Changqian; Granick, Steve

    2014-03-01

    We study the emulsion induced clustering of faceted metal organic frameworks (MOFs) and their dynamics. Our approach to anisotropic building block is through the rational synthesis of water stable and highly uniform MOFs. This generates colloidal-sized MOFs of defined polyhedral shape with tunable size in micrometer range that are suitable for in situ imaging. The 3D clusters formations are promoted by hydrophilic MOFs particles confined in aqueous droplets of binary water-lutidine mixture at transition temperature. Below this temperature, the water droplet decreases in volume due to one phase mixing with lutidine which forces the N-mers of faceted particles to aggregate in close contact. We compare the faceted clusters formed to those made of spherical particles in term of the building block sphericity. Other focus of our study involves the dynamic of the clusters. We found that, unlike spherical clusters, these faceted N-mers are highly stable on large scale of temperature due to their dominant capillary force on their facet-to-facet contact.

  3. Familial aggregation of cluster headache

    Directory of Open Access Journals (Sweden)

    Simao Cruz

    2013-11-01

    Full Text Available Several studies suggest a strong familial aggregation for cluster headache (CH, but so far none of them have included subjects with probable cluster headache (PCH in accordance with the International Classification of Headache Disorders. Objective To identify cases of probable cluster headache and to assess the familial aggregation of cluster headache by including these subjects. Method Thirty-six patients attending a headache consultation and diagnosed with trigeminal autonomic headaches were subjected to a questionnaire-based interview. A telephone interview was also applied to all the relatives who were pointed out as possibly affected as well as to some of the remaining relatives. Results Twenty-four probands fulfilled the criteria for CH or PCH; they had 142 first-degree relatives, of whom five were found to have CH or PCH, including one case of CH sine headache. The risk for first-degree relatives was observed to be increased by 35- to 46-fold. Conclusion Our results suggest a familial aggregation of cluster headache in the Portuguese population.

  4. 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

  5. Introduction: The Evolving Cluster and Protocluster Population.

    Science.gov (United States)

    Arnaud, Monique

    2017-07-01

    In this introductory talk, I place clusters and protoclusters, and their evolution, in the general context of the cosmic web formation. I also give an overview of the technics used to find clusters and their progenitors, and of the coverage of the redshift-mass plane achieved with current samples. I summarize the open questions that can be addressed from local merging cluster observations, statistical studies of the dynamical state of the cluster population, the cluster outskirts and protoclusters.

  6. 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.

  7. 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.

  8. Author Clustering on Large Bibliographies

    CERN Document Server

    Sterz, Christoph

    2014-01-01

    We analyze and design an algorithm for clustering large sets of authors in Bibliographies. Not considering a distance function for a mutual comparison, but transforming the data into a multidimensional metric space, the algorithm described is similar to locally sensitive hashing. The task lies in the field of Record-Linkage. The algorithm was designed and performed based on the data of the CERN Document Server, consisting out of more than 1.7 million metadata entries and is part of the digital assets-managing-software invenio. Meant as a prototype, the algorithm performs efficiently, clustering all authors on CDS in under 30 minutes. We will discuss extensions improving the recall rate, wich still remains inferior to the currently used clustering-approach.

  9. Privacy-preserving distributed clustering

    DEFF Research Database (Denmark)

    Erkin, Zekeriya; Veugen, Thijs; Toft, Tomas

    2013-01-01

    by taking the distributed structure of the system into account and improving the efficiency in terms of computation and communication by data packing. While our construction can be easily adjusted to a centralized or a distributed computing model, we rely on a set of particular users that help the service...... for distributed clustering that limits information leakage to the untrusted service provider that performs the clustering. To achieve this goal, we rely on cryptographic techniques, in particular homomorphic encryption, and further improve the state of the art of processing encrypted data in terms of efficiency...... provider with computations. Experimental results clearly indicate that the work we present is an efficient way of deploying a privacy-preserving clustering algorithm in a distributed manner....

  10. 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.

  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. Nanocomposites for Machining Tools.

    Science.gov (United States)

    Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

    2017-10-13

    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.

  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. 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.

  15. Base motif recognition and design of DNA templates for fluorescent silver clusters by machine learning.

    Science.gov (United States)

    Copp, Stacy M; Bogdanov, Petko; Debord, Mark; Singh, Ambuj; Gwinn, Elisabeth

    2014-09-03

    Discriminative base motifs within DNA templates for fluorescent silver clusters are identified using methods that combine large experimental data sets with machine learning tools for pattern recognition. Combining the discovery of certain multibase motifs important for determining fluorescence brightness with a generative algorithm, the probability of selecting DNA templates that stabilize fluorescent silver clusters is increased by a factor of >3. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Collaborative Clustering for Sensor Networks

    Science.gov (United States)

    Wagstaff. Loro :/; Green Jillian; Lane, Terran

    2011-01-01

    Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative

  17. 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....

  18. 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......: In the last decade, invasive neuromodulation treatments have demonstrated good efficacy in cluster refractory patients. Noninvasive approaches such as the noninvasive vagal nerve stimulation have shown efficacy in one trial and could be an easier alternative in the management of this debilitating headache. We...

  19. Silver clusters from nozzle expansions

    International Nuclear Information System (INIS)

    Hagena, O.F.

    1990-01-01

    This note reports on the first successful experiments to generate silver clusters (N≤100) in supersonic nozzle flows. A mixture of argon/silver-vapor was used expanding from a conical nozzle (0.35 mm, 10deg full cone angle, 17 mm long conical section). Source temperature and total pressure ranged up to 2200 K/300 kPa, and silver partial pressure up to 25 kPa. The data confirm the scaling laws developed to compare clustering of metals with that of rare gases. (orig.)

  20. 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....

  1. Numerical experiments on galaxy clustering

    International Nuclear Information System (INIS)

    Miller, R.H.

    1983-01-01

    A study of the way observable clustering depends on expansion history is reported. Observable shapes that result from evolving otherwise identical systems are intercompared to show differences due to different expansion histories. Four cases are compared: nonexpanding, Omega 1, and two open universes with 0.10 and 0.03 as final values of Omega. There is remarkably little diffrence in observable forms for the expanding cases. The 0.03 universe expanded by a factor 500 during the experiment. This study is an example of the way numerical experiments can be used in studies of galaxy clustering

  2. Clusters of Pneumocystis carinii pneumonia

    DEFF Research Database (Denmark)

    Helweg-Larsen, J; Tsolaki, A G; Miller, Raymonde

    1998-01-01

    Genotyping at the internal transcribed spacer (ITS) regions of the nuclear rRNA operon was performed on isolates of P. carinii sp. f. hominis from three clusters of P. carinii pneumonia among eight patients with haematological malignancies and six with HIV infection. Nine different ITS sequence...... types of P. carinii sp. f. hominis were identified in the samples from the patients with haematological malignancies, suggesting that this cluster of cases of P. carinii pneumonia was unlikely to have resulted from nosocomial transmission. A common ITS sequence type was observed in two of the patients...

  3. Clustering of Sun Exposure Measurements

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak; Larsen, Jan; Hansen, Lars Kai

    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 behavioral data. The framework combines principal component subspace projection with probabilistic...

  4. The state and creative clusters

    DEFF Research Database (Denmark)

    Vang, Jan; Jakobsen, Hannes

    2013-01-01

    Studies on the spatial organisation of so-called creative industries have exploded the last decade. This has resulted in an impressive amount of research on the clustering of creative industries, their reliance on buzz and why they are based on projects, and so forth. This literature has, however...... creative industries, especially film industries outside Hollywood. Based on an original empirical study of the Danish film cluster we show how it has emerged almost from scratch and positioned itself as a noteworthy player on the global scene industry during the last 20 years. Special attention is paid...

  5. Clustering in Hilbert simplex geometry

    KAUST Repository

    Nielsen, Frank

    2017-04-03

    Clustering categorical distributions in the probability simplex is a fundamental primitive often met in applications dealing with histograms or mixtures of multinomials. Traditionally, the differential-geometric structure of the probability simplex has been used either by (i) setting the Riemannian metric tensor to the Fisher information matrix of the categorical distributions, or (ii) defining the information-geometric structure induced by a smooth dissimilarity measure, called a divergence. In this paper, we introduce a novel computationally-friendly non-Riemannian framework for modeling the probability simplex: Hilbert simplex geometry. We discuss the pros and cons of those three statistical modelings, and compare them experimentally for clustering tasks.

  6. New authentication mechanism using certificates for big data analytic tools

    OpenAIRE

    Velthuis, Paul

    2017-01-01

    Companies analyse large amounts of sensitive data on clusters of machines, using a framework such as Apache Hadoop to handle inter-process communication, and big data analytic tools such as Apache Spark and Apache Flink to analyse the growing amounts of data. Big data analytic tools are mainly tested on performance and reliability. Security and authentication have not been enough considered and they lack behind. The goal of this research is to improve the authentication and security for data ...

  7. Hierarchical cluster analysis of ignitable liquids based on the total ion spectrum.

    Science.gov (United States)

    Waddell, Erin E; Frisch-Daiello, Jessica L; Williams, Mary R; Sigman, Michael E

    2014-09-01

    Gas chromatography-mass spectrometry (GC-MS) data of ignitable liquids in the Ignitable Liquids Reference Collection (ILRC) database were processed to obtain 445 total ion spectra (TIS), that is, average mass spectra across the chromatographic profile. Hierarchical cluster analysis, an unsupervised learning technique, was applied to find features useful for classification of ignitable liquids. A combination of the correlation distance and average linkage was utilized for grouping ignitable liquids with similar chemical composition. This study evaluated whether hierarchical cluster analysis of the TIS would cluster together ignitable liquids of the same ASTM class assignment, as designated in the ILRC database. The ignitable liquids clustered based on their chemical composition, and the ignitable liquids within each cluster were predominantly from one ASTM E1618-11 class. These results reinforce use of the TIS as a tool to aid in forensic fire debris analysis. © 2014 American Academy of Forensic Sciences.

  8. Galaxy Cluster Smashes Distance Record

    Science.gov (United States)

    2009-10-01

    he most distant galaxy cluster yet has been discovered by combining data from NASA's Chandra X-ray Observatory and optical and infrared telescopes. The cluster is located about 10.2 billion light years away, and is observed as it was when the Universe was only about a quarter of its present age. The galaxy cluster, known as JKCS041, beats the previous record holder by about a billion light years. Galaxy clusters are the largest gravitationally bound objects in the Universe. Finding such a large structure at this very early epoch can reveal important information about how the Universe evolved at this crucial stage. JKCS041 is found at the cusp of when scientists think galaxy clusters can exist in the early Universe based on how long it should take for them to assemble. Therefore, studying its characteristics - such as composition, mass, and temperature - will reveal more about how the Universe took shape. "This object is close to the distance limit expected for a galaxy cluster," said Stefano Andreon of the National Institute for Astrophysics (INAF) in Milan, Italy. "We don't think gravity can work fast enough to make galaxy clusters much earlier." Distant galaxy clusters are often detected first with optical and infrared observations that reveal their component galaxies dominated by old, red stars. JKCS041 was originally detected in 2006 in a survey from the United Kingdom Infrared Telescope (UKIRT). The distance to the cluster was then determined from optical and infrared observations from UKIRT, the Canada-France-Hawaii telescope in Hawaii and NASA's Spitzer Space Telescope. Infrared observations are important because the optical light from the galaxies at large distances is shifted into infrared wavelengths because of the expansion of the universe. The Chandra data were the final - but crucial - piece of evidence as they showed that JKCS041 was, indeed, a genuine galaxy cluster. The extended X-ray emission seen by Chandra shows that hot gas has been detected

  9. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

  10. Tools of online Marketing

    OpenAIRE

    Hossain, M. S.; Rahman, M. F.

    2017-01-01

    Abstract Online marketing is the most crucial issue in the modern marketing era but there was no previous research that could identify the tools of internet marketing before this study and it was the first study on the field of online marketing tools. This research was descriptive in nature and it has attempted to identify the major tools of internet marketing from the concepts of traditional marketing tools. Worldwide network is known as Internet that can exchange information between use...

  11. OOTW COST TOOLS

    Energy Technology Data Exchange (ETDEWEB)

    HARTLEY, D.S.III; PACKARD, S.L.

    1998-09-01

    This document reports the results of a study of cost tools to support the analysis of Operations Other Than War (OOTW). It recommends the continued development of the Department of Defense (DoD) Contingency Operational Support Tool (COST) as the basic cost analysis tool for 00TWS. It also recommends modifications to be included in future versions of COST and the development of an 00TW mission planning tool to supply valid input for costing.

  12. Properties of the open cluster system

    International Nuclear Information System (INIS)

    Janes, K.A.; Tilley, C.; Lynga, G.

    1988-01-01

    A system of weights corresponding to the precision of open cluster data is described. Using these weights, some properties of open clusters can be studied more accurately than was possible earlier. It is clear that there are three types of objects: unbound clusters, bound clusters in the thin disk, and older bound clusters. Galactic gradients of metallicity, longevity, and linear diameter are studied. Distributions at right angles to the galactic plane are discussed in the light of the different cluster types. The clumping of clusters in complexes is studied. An estimate of the selection effects influencing the present material of open cluster data is made in order to evaluate the role played by open clusters in the history of the galactic disk. 58 references

  13. Chaos theory perspective for industry clusters development

    Science.gov (United States)

    Yu, Haiying; Jiang, Minghui; Li, Chengzhang

    2016-03-01

    Industry clusters have outperformed in economic development in most developing countries. The contributions of industrial clusters have been recognized as promotion of regional business and the alleviation of economic and social costs. It is no doubt globalization is rendering clusters in accelerating the competitiveness of economic activities. In accordance, many ideas and concepts involve in illustrating evolution tendency, stimulating the clusters development, meanwhile, avoiding industrial clusters recession. The term chaos theory is introduced to explain inherent relationship of features within industry clusters. A preferred life cycle approach is proposed for industrial cluster recessive theory analysis. Lyapunov exponents and Wolf model are presented for chaotic identification and examination. A case study of Tianjin, China has verified the model effectiveness. The investigations indicate that the approaches outperform in explaining chaos properties in industrial clusters, which demonstrates industrial clusters evolution, solves empirical issues and generates corresponding strategies.

  14. A COMPARISON OF TWO FUZZY CLUSTERING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Samarjit Das

    2013-10-01

    Full Text Available - In fuzzy clustering, unlike hard clustering, depending on the membership value, a single object may belong exactly to one cluster or partially to more than one cluster. Out of a number of fuzzy clustering techniques Bezdek’s Fuzzy C-Means and GustafsonKessel clustering techniques are well known where Euclidian distance and Mahalanobis distance are used respectively as a measure of similarity. We have applied these two fuzzy clustering techniques on a dataset of individual differences consisting of fifty feature vectors of dimension (feature three. Based on some validity measures we have tried to see the performances of these two clustering techniques from three different aspects- first, by initializing the membership values of the feature vectors considering the values of the three features separately one at a time, secondly, by changing the number of the predefined clusters and thirdly, by changing the size of the dataset.

  15. ClusTrack: feature extraction and similarity measures for clustering of genome-wide data sets.

    Directory of Open Access Journals (Sweden)

    Halfdan Rydbeck

    Full Text Available Clustering is a popular technique for explorative analysis of data, as it can reveal subgroupings and similarities between data in an unsupervised manner. While clustering is routinely applied to gene expression data, there is a lack of appropriate general methodology for clustering of sequence-level genomic and epigenomic data, e.g. ChIP-based data. We here introduce a general methodology for clustering data sets of coordinates relative to a genome assembly, i.e. genomic tracks. By defining appropriate feature extraction approaches and similarity measures, we allow biologically meaningful clustering to be performed for genomic tracks using standard clustering algorithms. An implementation of the methodology is provided through a tool, ClusTrack, which allows fine-tuned clustering analyses to be specified through a web-based interface. We apply our methods to the clustering of occupancy of the H3K4me1 histone modification in samples from a range of different cell types. The majority of samples form meaningful subclusters, confirming that the definitions of features and similarity capture biological, rather than technical, variation between the genomic tracks. Input data and results are available, and can be reproduced, through a Galaxy Pages document at http://hyperbrowser.uio.no/hb/u/hb-superuser/p/clustrack. The clustering functionality is available as a Galaxy tool, under the menu option "Specialized analyzis of tracks", and the submenu option "Cluster tracks based on genome level similarity", at the Genomic HyperBrowser server: http://hyperbrowser.uio.no/hb/.

  16. Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes.

    Science.gov (United States)

    Maulik, Ujjwal; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

    2009-01-20

    The landscape of biological and biomedical research is being changed rapidly with the invention of microarrays which enables simultaneous view on the transcription levels of a huge number of genes across different experimental conditions or time points. Using microarray data sets, clustering algorithms have been actively utilized in order to identify groups of co-expressed genes. This article poses the problem of fuzzy clustering in microarray data as a multiobjective optimization problem which simultaneously optimizes two internal fuzzy cluster validity indices to yield a set of Pareto-optimal clustering solutions. Each of these clustering solutions possesses some amount of information regarding the clustering structure of the input data. Motivated by this fact, a novel fuzzy majority voting approach is proposed to combine the clustering information from all the solutions in the resultant Pareto-optimal set. This approach first identifies the genes which are assigned to some particular cluster with high membership degree by most of the Pareto-optimal solutions. Using this set of genes as the training set, the remaining genes are classified by a supervised learning algorithm. In this work, we have used a Support Vector Machine (SVM) classifier for this purpose. The performance of the proposed clustering technique has been demonstrated on five publicly available benchmark microarray data sets, viz., Yeast Sporulation, Yeast Cell Cycle, Arabidopsis Thaliana, Human Fibroblasts Serum and Rat Central Nervous System. Comparative studies of the use of different SVM kernels and several widely used microarray clustering techniques are reported. Moreover, statistical significance tests have been carried out to establish the statistical superiority of the proposed clustering approach. Finally, biological significance tests have been carried out using a web based gene annotation tool to show that the proposed method is able to produce biologically relevant clusters of co

  17. Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes

    Directory of Open Access Journals (Sweden)

    Bandyopadhyay Sanghamitra

    2009-01-01

    Full Text Available Abstract Background The landscape of biological and biomedical research is being changed rapidly with the invention of microarrays which enables simultaneous view on the transcription levels of a huge number of genes across different experimental conditions or time points. Using microarray data sets, clustering algorithms have been actively utilized in order to identify groups of co-expressed genes. This article poses the problem of fuzzy clustering in microarray data as a multiobjective optimization problem which simultaneously optimizes two internal fuzzy cluster validity indices to yield a set of Pareto-optimal clustering solutions. Each of these clustering solutions possesses some amount of information regarding the clustering structure of the input data. Motivated by this fact, a novel fuzzy majority voting approach is proposed to combine the clustering information from all the solutions in the resultant Pareto-optimal set. This approach first identifies the genes which are assigned to some particular cluster with high membership degree by most of the Pareto-optimal solutions. Using this set of genes as the training set, the remaining genes are classified by a supervised learning algorithm. In this work, we have used a Support Vector Machine (SVM classifier for this purpose. Results The performance of the proposed clustering technique has been demonstrated on five publicly available benchmark microarray data sets, viz., Yeast Sporulation, Yeast Cell Cycle, Arabidopsis Thaliana, Human Fibroblasts Serum and Rat Central Nervous System. Comparative studies of the use of different SVM kernels and several widely used microarray clustering techniques are reported. Moreover, statistical significance tests have been carried out to establish the statistical superiority of the proposed clustering approach. Finally, biological significance tests have been carried out using a web based gene annotation tool to show that the proposed method is able to

  18. Hole-Aligning Tool

    Science.gov (United States)

    Collins, Frank A.; Saude, Frank; Sep, Martin J.

    1996-01-01

    Tool designed for use in aligning holes in plates or other structural members to be joined by bolt through holes. Holes aligned without exerting forces perpendicular to planes of holes. Tool features screw-driven-wedge design similar to (but simpler than) that of some automotive exhaust-pipe-expanding tools.

  19. Pro Tools HD

    CERN Document Server

    Camou, Edouard

    2013-01-01

    An easy-to-follow guide for using Pro Tools HD 11 effectively.This book is ideal for anyone who already uses ProTools and wants to learn more, or is new to Pro Tools HD and wants to use it effectively in their own audio workstations.

  20. Vehicle Detection Tool - VDtect

    OpenAIRE

    Prateek, GV; Hari, KVS

    2012-01-01

    The report talks about the implementation of Vehicle Detection tool using opensource software - WxPython. The main functionality of this tool includes collection of data, plotting of magnetometer data and the count of the vehicles detected. The report list about how installation process and various functionality of the tool.