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Sample records for hierarchical clustering results

  1. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

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

  2. Hierarchical clustering for graph visualization

    CERN Document Server

    Clémençon, Stéphan; Rossi, Fabrice; Tran, Viet Chi

    2012-01-01

    This paper describes a graph visualization methodology based on hierarchical maximal modularity clustering, with interactive and significant coarsening and refining possibilities. An application of this method to HIV epidemic analysis in Cuba is outlined.

  3. Hierarchical Formation of Galactic Clusters

    CERN Document Server

    Elmegreen, B G

    2006-01-01

    Young stellar groupings and clusters have hierarchical patterns ranging from flocculent spiral arms and star complexes on the largest scale to OB associations, OB subgroups, small loose groups, clusters and cluster subclumps on the smallest scales. There is no obvious transition in morphology at the cluster boundary, suggesting that clusters are only the inner parts of the hierarchy where stars have had enough time to mix. The power-law cluster mass function follows from this hierarchical structure: n(M_cl) M_cl^-b for b~2. This value of b is independently required by the observation that the summed IMFs from many clusters in a galaxy equals approximately the IMF of each cluster.

  4. Galaxy formation through hierarchical clustering

    Science.gov (United States)

    White, Simon D. M.; Frenk, Carlos S.

    1991-01-01

    Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

  5. Intuitionistic fuzzy hierarchical clustering algorithms

    Institute of Scientific and Technical Information of China (English)

    Xu Zeshui

    2009-01-01

    Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.

  6. Hierarchical Clustering and Active Galaxies

    CERN Document Server

    Hatziminaoglou, E; Manrique, A

    2000-01-01

    The growth of Super Massive Black Holes and the parallel development of activity in galactic nuclei are implemented in an analytic code of hierarchical clustering. The evolution of the luminosity function of quasars and AGN will be computed with special attention paid to the connection between quasars and Seyfert galaxies. One of the major interests of the model is the parallel study of quasar formation and evolution and the History of Star Formation.

  7. Hesitant fuzzy agglomerative hierarchical clustering algorithms

    Science.gov (United States)

    Zhang, Xiaolu; Xu, Zeshui

    2015-02-01

    Recently, hesitant fuzzy sets (HFSs) have been studied by many researchers as a powerful tool to describe and deal with uncertain data, but relatively, very few studies focus on the clustering analysis of HFSs. In this paper, we propose a novel hesitant fuzzy agglomerative hierarchical clustering algorithm for HFSs. The algorithm considers each of the given HFSs as a unique cluster in the first stage, and then compares each pair of the HFSs by utilising the weighted Hamming distance or the weighted Euclidean distance. The two clusters with smaller distance are jointed. The procedure is then repeated time and again until the desirable number of clusters is achieved. Moreover, we extend the algorithm to cluster the interval-valued hesitant fuzzy sets, and finally illustrate the effectiveness of our clustering algorithms by experimental results.

  8. Hierarchical clustering using correlation metric and spatial continuity constraint

    Science.gov (United States)

    Stork, Christopher L.; Brewer, Luke N.

    2012-10-02

    Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

  9. Comparison of multianalyte proficiency test results by sum of ranking differences, principal component analysis, and hierarchical cluster analysis.

    Science.gov (United States)

    Škrbić, Biljana; Héberger, Károly; Durišić-Mladenović, Nataša

    2013-10-01

    Sum of ranking differences (SRD) was applied for comparing multianalyte results obtained by several analytical methods used in one or in different laboratories, i.e., for ranking the overall performances of the methods (or laboratories) in simultaneous determination of the same set of analytes. The data sets for testing of the SRD applicability contained the results reported during one of the proficiency tests (PTs) organized by EU Reference Laboratory for Polycyclic Aromatic Hydrocarbons (EU-RL-PAH). In this way, the SRD was also tested as a discriminant method alternative to existing average performance scores used to compare mutlianalyte PT results. SRD should be used along with the z scores--the most commonly used PT performance statistics. SRD was further developed to handle the same rankings (ties) among laboratories. Two benchmark concentration series were selected as reference: (a) the assigned PAH concentrations (determined precisely beforehand by the EU-RL-PAH) and (b) the averages of all individual PAH concentrations determined by each laboratory. Ranking relative to the assigned values and also to the average (or median) values pointed to the laboratories with the most extreme results, as well as revealed groups of laboratories with similar overall performances. SRD reveals differences between methods or laboratories even if classical test(s) cannot. The ranking was validated using comparison of ranks by random numbers (a randomization test) and using seven folds cross-validation, which highlighted the similarities among the (methods used in) laboratories. Principal component analysis and hierarchical cluster analysis justified the findings based on SRD ranking/grouping. If the PAH-concentrations are row-scaled, (i.e., z scores are analyzed as input for ranking) SRD can still be used for checking the normality of errors. Moreover, cross-validation of SRD on z scores groups the laboratories similarly. The SRD technique is general in nature, i.e., it can

  10. PERFORMANCE OF SELECTED AGGLOMERATIVE HIERARCHICAL CLUSTERING METHODS

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    Nusa Erman

    2015-01-01

    Full Text Available A broad variety of different methods of agglomerative hierarchical clustering brings along problems how to choose the most appropriate method for the given data. It is well known that some methods outperform others if the analysed data have a specific structure. In the presented study we have observed the behaviour of the centroid, the median (Gower median method, and the average method (unweighted pair-group method with arithmetic mean – UPGMA; average linkage between groups. We have compared them with mostly used methods of hierarchical clustering: the minimum (single linkage clustering, the maximum (complete linkage clustering, the Ward, and the McQuitty (groups method average, weighted pair-group method using arithmetic averages - WPGMA methods. We have applied the comparison of these methods on spherical, ellipsoid, umbrella-like, “core-and-sphere”, ring-like and intertwined three-dimensional data structures. To generate the data and execute the analysis, we have used R statistical software. Results show that all seven methods are successful in finding compact, ball-shaped or ellipsoid structures when they are enough separated. Conversely, all methods except the minimum perform poor on non-homogenous, irregular and elongated ones. Especially challenging is a circular double helix structure; it is being correctly revealed only by the minimum method. We can also confirm formerly published results of other simulation studies, which usually favour average method (besides Ward method in cases when data is assumed to be fairly compact and well separated.

  11. Fast, Linear Time Hierarchical Clustering using the Baire Metric

    CERN Document Server

    Contreras, Pedro

    2011-01-01

    The Baire metric induces an ultrametric on a dataset and is of linear computational complexity, contrasted with the standard quadratic time agglomerative hierarchical clustering algorithm. In this work we evaluate empirically this new approach to hierarchical clustering. We compare hierarchical clustering based on the Baire metric with (i) agglomerative hierarchical clustering, in terms of algorithm properties; (ii) generalized ultrametrics, in terms of definition; and (iii) fast clustering through k-means partititioning, in terms of quality of results. For the latter, we carry out an in depth astronomical study. We apply the Baire distance to spectrometric and photometric redshifts from the Sloan Digital Sky Survey using, in this work, about half a million astronomical objects. We want to know how well the (more costly to determine) spectrometric redshifts can predict the (more easily obtained) photometric redshifts, i.e. we seek to regress the spectrometric on the photometric redshifts, and we use clusterwi...

  12. Constructing storyboards based on hierarchical clustering analysis

    Science.gov (United States)

    Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

    2005-07-01

    There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

  13. Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

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    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.

  14. Hierarchical Approach in Clustering to Euclidean Traveling Salesman Problem

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    Fajar, Abdulah; Herman, Nanna Suryana; Abu, Nur Azman; Shahib, Sahrin

    There has been growing interest in studying combinatorial optimization problems by clustering strategy, with a special emphasis on the traveling salesman problem (TSP). TSP naturally arises as a sub problem in much transportation, manufacturing and logistics application, this problem has caught much attention of mathematicians and computer scientists. A clustering approach will decompose TSP into sub graph and form cluster, so it may reduce problem size into smaller problem. Impact of hierarchical approach will be investigated to produce a better clustering strategy that fit into Euclidean TSP. Clustering strategy to Euclidean TSP consist of two main step, there are; clustering and tour construction. The significant of this research is clustering approach solution result has error less than 10% compare to best known solution (TSPLIB) and there is improvement to a hierarchical clustering algorithm in order to fit in such Euclidean TSP solution method.

  15. Assembling hierarchical cluster solids with atomic precision.

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    Turkiewicz, Ari; Paley, Daniel W; Besara, Tiglet; Elbaz, Giselle; Pinkard, Andrew; Siegrist, Theo; Roy, Xavier

    2014-11-12

    Hierarchical solids created from the binary assembly of cobalt chalcogenide and iron oxide molecular clusters are reported. Six different molecular clusters based on the octahedral Co6E8 (E = Se or Te) and the expanded cubane Fe8O4 units are used as superatomic building blocks to construct these crystals. The formation of the solid is driven by the transfer of charge between complementary electron-donating and electron-accepting clusters in solution that crystallize as binary ionic compounds. The hierarchical structures are investigated by single-crystal X-ray diffraction, providing atomic and superatomic resolution. We report two different superstructures: a superatomic relative of the CsCl lattice type and an unusual packing arrangement based on the double-hexagonal close-packed lattice. Within these superstructures, we demonstrate various compositions and orientations of the clusters.

  16. A New Metrics for Hierarchical Clustering

    Institute of Scientific and Technical Information of China (English)

    YANGGuangwen; SHIShuming; WANGDingxing

    2003-01-01

    Hierarchical clustering is a popular method of performing unsupervised learning. Some metric must be used to determine the similarity between pairs of clusters in hierarchical clustering. Traditional similarity metrics either can deal with simple shapes (i.e. spherical shapes) only or are very sensitive to outliers (the chaining effect). The main contribution of this paper is to propose some potential-based similarity metrics (APES and AMAPES) between clusters in hierarchical clustering, inspired by the concepts of the electric potential and the gravitational potential in electromagnetics and astronomy. The main features of these metrics are: the first, they have strong antijamming capability; the second, they are capable of finding clusters of different shapes such as spherical, spiral, chain, circle, sigmoid, U shape or other complex irregular shapes; the third, existing algorithms and research fruits for classical metrics can be adopted to deal with these new potential-based metrics with no or little modification. Experiments showed that the new metrics are more superior to traditional ones. Different potential functions are compared, and the sensitivity to parameters is also analyzed in this paper.

  17. Managing Clustered Data Using Hierarchical Linear Modeling

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    Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

    2012-01-01

    Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

  18. Managing Clustered Data Using Hierarchical Linear Modeling

    Science.gov (United States)

    Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

    2012-01-01

    Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

  19. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

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    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

  20. Robust Pseudo-Hierarchical Support Vector Clustering

    DEFF Research Database (Denmark)

    Hansen, Michael Sass; Sjöstrand, Karl; Olafsdóttir, Hildur

    2007-01-01

    Support vector clustering (SVC) has proven an efficient algorithm for clustering of noisy and high-dimensional data sets, with applications within many fields of research. An inherent problem, however, has been setting the parameters of the SVC algorithm. Using the recent emergence of a method...... for calculating the entire regularization path of the support vector domain description, we propose a fast method for robust pseudo-hierarchical support vector clustering (HSVC). The method is demonstrated to work well on generated data, as well as for detecting ischemic segments from multidimensional myocardial...

  1. Hierarchical Overlapping Clustering of Network Data Using Cut Metrics

    CERN Document Server

    Gama, Fernando; Ribeiro, Alejandro

    2016-01-01

    A novel method to obtain hierarchical and overlapping clusters from network data -i.e., a set of nodes endowed with pairwise dissimilarities- is presented. The introduced method is hierarchical in the sense that it outputs a nested collection of groupings of the node set depending on the resolution or degree of similarity desired, and it is overlapping since it allows nodes to belong to more than one group. Our construction is rooted on the facts that a hierarchical (non-overlapping) clustering of a network can be equivalently represented by a finite ultrametric space and that a convex combination of ultrametrics results in a cut metric. By applying a hierarchical (non-overlapping) clustering method to multiple dithered versions of a given network and then convexly combining the resulting ultrametrics, we obtain a cut metric associated to the network of interest. We then show how to extract a hierarchical overlapping clustering structure from the aforementioned cut metric. Furthermore, the so-called overlappi...

  2. Hierarchical Control for Multiple DC Microgrids Clusters

    DEFF Research Database (Denmark)

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

    2014-01-01

    This paper presents a distributed hierarchical control framework to ensure reliable operation of dc Microgrid (MG) clusters. In this hierarchy, primary control is used to regulate the common bus voltage inside each MG locally. An adaptive droop method is proposed for this level which determines....... Another distributed policy is employed then to regulate the power flow among the MGs according to their local SOCs. The proposed distributed controllers on each MG communicate with only the neighbor MGs through a communication infrastructure. Finally, the small signal model is expanded for dc MG clusters...

  3. Breaking the hierarchy - a new cluster selection mechanism for hierarchical clustering methods

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    Zweig Katharina A

    2009-10-01

    Full Text Available Abstract Background Hierarchical clustering methods like Ward's method have been used since decades to understand biological and chemical data sets. In order to get a partition of the data set, it is necessary to choose an optimal level of the hierarchy by a so-called level selection algorithm. In 2005, a new kind of hierarchical clustering method was introduced by Palla et al. that differs in two ways from Ward's method: it can be used on data on which no full similarity matrix is defined and it can produce overlapping clusters, i.e., allow for multiple membership of items in clusters. These features are optimal for biological and chemical data sets but until now no level selection algorithm has been published for this method. Results In this article we provide a general selection scheme, the level independent clustering selection method, called LInCS. With it, clusters can be selected from any level in quadratic time with respect to the number of clusters. Since hierarchically clustered data is not necessarily associated with a similarity measure, the selection is based on a graph theoretic notion of cohesive clusters. We present results of our method on two data sets, a set of drug like molecules and set of protein-protein interaction (PPI data. In both cases the method provides a clustering with very good sensitivity and specificity values according to a given reference clustering. Moreover, we can show for the PPI data set that our graph theoretic cohesiveness measure indeed chooses biologically homogeneous clusters and disregards inhomogeneous ones in most cases. We finally discuss how the method can be generalized to other hierarchical clustering methods to allow for a level independent cluster selection. Conclusion Using our new cluster selection method together with the method by Palla et al. provides a new interesting clustering mechanism that allows to compute overlapping clusters, which is especially valuable for biological and

  4. Technique for fast and efficient hierarchical clustering

    Science.gov (United States)

    Stork, Christopher

    2013-10-08

    A fast and efficient technique for hierarchical clustering of samples in a dataset includes compressing the dataset to reduce a number of variables within each of the samples of the dataset. A nearest neighbor matrix is generated to identify nearest neighbor pairs between the samples based on differences between the variables of the samples. The samples are arranged into a hierarchy that groups the samples based on the nearest neighbor matrix. The hierarchy is rendered to a display to graphically illustrate similarities or differences between the samples.

  5. Magnetic susceptibilities of cluster-hierarchical models

    Science.gov (United States)

    McKay, Susan R.; Berker, A. Nihat

    1984-02-01

    The exact magnetic susceptibilities of hierarchical models are calculated near and away from criticality, in both the ordered and disordered phases. The mechanism and phenomenology are discussed for models with susceptibilities that are physically sensible, e.g., nondivergent away from criticality. Such models are found based upon the Niemeijer-van Leeuwen cluster renormalization. A recursion-matrix method is presented for the renormalization-group evaluation of response functions. Diagonalization of this matrix at fixed points provides simple criteria for well-behaved densities and response functions.

  6. A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis

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    Shaoning Li

    2017-01-01

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

  7. A Framework for Hierarchical Clustering Based Indexing in Search Engines

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    Parul Gupta

    2011-01-01

    Full Text Available Granting efficient and fast accesses to the index is a key issuefor performances of Web Search Engines. In order to enhancememory utilization and favor fast query resolution, WSEs useInverted File (IF indexes that consist of an array of theposting lists where each posting list is associated with a termand contains the term as well as the identifiers of the documentscontaining the term. Since the document identifiers are stored insorted order, they can be stored as the difference between thesuccessive documents so as to reduce the size of the index. Thispaper describes a clustering algorithm that aims atpartitioning the set of documents into ordered clusters so thatthe documents within the same cluster are similar and are beingassigned the closer document identifiers. Thus the averagevalue of the differences between the successive documents willbe minimized and hence storage space would be saved. Thepaper further presents the extension of this clustering algorithmto be applied for the hierarchical clustering in which similarclusters are clubbed to form a mega cluster and similar megaclusters are then combined to form super cluster. Thus thepaper describes the different levels of clustering whichoptimizes the search process by directing the searchto a specific path from higher levels of clustering to the lowerlevels i.e. from super clusters to mega clusters, then to clustersand finally to the individual documents so that the user gets thebest possible matching results in minimum possible time.

  8. A Hierarchical Clustering Methodology for the Estimation of Toxicity

    Science.gov (United States)

    A Quantitative Structure Activity Relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural sim...

  9. Hierarchical Cluster Assembly in Globally Collapsing Clouds

    CERN Document Server

    Vazquez-Semadeni, Enrique; Colin, Pedro

    2016-01-01

    We discuss the mechanism of cluster formation in a numerical simulation of a molecular cloud (MC) undergoing global hierarchical collapse (GHC). The global nature of the collapse implies that the SFR increases over time. The hierarchical nature of the collapse consists of small-scale collapses within larger-scale ones. The large-scale collapses culminate a few Myr later than the small-scale ones and consist of filamentary flows that accrete onto massive central clumps. The small-scale collapses form clumps that are embedded in the filaments and falling onto the large-scale collapse centers. The stars formed in the early, small-scale collapses share the infall motion of their parent clumps. Thus, the filaments feed both gaseous and stellar material to the massive central clump. This leads to the presence of a few older stars in a region where new protostars are forming, and also to a self-similar structure, in which each unit is composed of smaller-scale sub-units that approach each other and may merge. Becaus...

  10. Hierarchical Cluster Analysis – Various Approaches to Data Preparation

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    Z. Pacáková

    2013-09-01

    Full Text Available The article deals with two various approaches to data preparation to avoid multicollinearity. The aim of the article is to find similarities among the e-communication level of EU states using hierarchical cluster analysis. The original set of fourteen indicators was first reduced on the basis of correlation analysis while in case of high correlation indicator of higher variability was included in further analysis. Secondly the data were transformed using principal component analysis while the principal components are poorly correlated. For further analysis five principal components explaining about 92% of variance were selected. Hierarchical cluster analysis was performed both based on the reduced data set and the principal component scores. Both times three clusters were assumed following Pseudo t-Squared and Pseudo F Statistic, but the final clusters were not identical. An important characteristic to compare the two results found was to look at the proportion of variance accounted for by the clusters which was about ten percent higher for the principal component scores (57.8% compared to 47%. Therefore it can be stated, that in case of using principal component scores as an input variables for cluster analysis with explained proportion high enough (about 92% for in our analysis, the loss of information is lower compared to data reduction on the basis of correlation analysis.

  11. Concept Association and Hierarchical Hamming Clustering Model in Text Classification

    Institute of Scientific and Technical Information of China (English)

    Su Gui-yang; Li Jian-hua; Ma Ying-hua; Li Sheng-hong; Yin Zhong-hang

    2004-01-01

    We propose two models in this paper. The concept of association model is put forward to obtain the co-occurrence relationships among keywords in the documents and the hierarchical Hamming clustering model is used to reduce the dimensionality of the category feature vector space which can solve the problem of the extremely high dimensionality of the documents' feature space. The results of experiment indicate that it can obtain the co-occurrence relations among keywords in the documents which promote the recall of classification system effectively. The hierarchical Hamming clustering model can reduce the dimensionality of the category feature vector efficiently, the size of the vector space is only about 10% of the primary dimensionality.

  12. Image Segmentation by Hierarchical Spatial and Color Spaces Clustering

    Institute of Scientific and Technical Information of China (English)

    YU Wei

    2005-01-01

    Image segmentation, as a basic building block for many high-level image analysis problems, has attracted many research attentions over years. Existing approaches, however, are mainly focusing on the clustering analysis in the single channel information, i.e., either in color or spatial space, which may lead to unsatisfactory segmentation performance. Considering the spatial and color spaces jointly, this paper proposes a new hierarchical image segmentation algorithm, which alternately clusters the image regions in color and spatial spaces in a fine to coarse manner. Without losing the perceptual consistence, the proposed algorithm achieves the segmentation result using only very few number of colors according to user specification.

  13. Global Considerations in Hierarchical Clustering Reveal Meaningful Patterns in Data

    Science.gov (United States)

    Varshavsky, Roy; Horn, David; Linial, Michal

    2008-01-01

    Background A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the only method applied. Methodology/Principal Findings We show that hierarchical clustering that involve global considerations, such as top-down (TD, divisive), or glocal (global-local) algorithms are better suited to reveal meaningful patterns in the data. This is demonstrated, by testing the correspondence between the results of several algorithms (TD, glocal and BU) and the correct annotations provided by experts. The correspondence was tested in multiple domains including gene expression experiments, stock trade records and functional protein families. The performance of each of the algorithms is evaluated by statistical criteria that are assigned to clusters (nodes of the hierarchy tree) based on expert-labeled data. Whereas TD algorithms perform better on global patterns, BU algorithms perform well and are advantageous when finer granularity of the data is sought. In addition, a novel TD algorithm that is based on genuine density of the data points is presented and is shown to outperform other divisive and agglomerative methods. Application of the algorithm to more than 500 protein sequences belonging to ion-channels illustrates the potential of the method for inferring overlooked functional annotations. ClustTree, a graphical Matlab toolbox for applying various hierarchical clustering algorithms and testing their quality is made available. Conclusions Although currently rarely used, global approaches, in particular, TD or glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping of proteins families. As demonstrated, it can also provide

  14. A fast quad-tree based two dimensional hierarchical clustering.

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    Rajadurai, Priscilla; Sankaranarayanan, Swamynathan

    2012-01-01

    Recently, microarray technologies have become a robust technique in the area of genomics. An important step in the analysis of gene expression data is the identification of groups of genes disclosing analogous expression patterns. Cluster analysis partitions a given dataset into groups based on specified features. Euclidean distance is a widely used similarity measure for gene expression data that considers the amount of changes in gene expression. However, the huge number of genes and the intricacy of biological networks have highly increased the challenges of comprehending and interpreting the resulting group of data, increasing processing time. The proposed technique focuses on a QT based fast 2-dimensional hierarchical clustering algorithm to perform clustering. The construction of the closest pair data structure is an each level is an important time factor, which determines the processing time of clustering. The proposed model reduces the processing time and improves analysis of gene expression data.

  15. Multi-mode clustering model for hierarchical wireless sensor networks

    Science.gov (United States)

    Hu, Xiangdong; Li, Yongfu; Xu, Huifen

    2017-03-01

    The topology management, i.e., clusters maintenance, of wireless sensor networks (WSNs) is still a challenge due to its numerous nodes, diverse application scenarios and limited resources as well as complex dynamics. To address this issue, a multi-mode clustering model (M2 CM) is proposed to maintain the clusters for hierarchical WSNs in this study. In particular, unlike the traditional time-trigger model based on the whole-network and periodic style, the M2 CM is proposed based on the local and event-trigger operations. In addition, an adaptive local maintenance algorithm is designed for the broken clusters in the WSNs using the spatial-temporal demand changes accordingly. Numerical experiments are performed using the NS2 network simulation platform. Results validate the effectiveness of the proposed model with respect to the network maintenance costs, node energy consumption and transmitted data as well as the network lifetime.

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

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

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

  17. Properties of hierarchically forming star clusters

    CERN Document Server

    Maschberger, Th; Bonnell, I A; Kroupa, P

    2010-01-01

    We undertake a systematic analysis of the early (< 0.5 Myr) evolution of clustering and the stellar initial mass function in turbulent fragmentation simulations. These large scale simulations for the first time offer the opportunity for a statistical analysis of IMF variations and correlations between stellar properties and cluster richness. The typical evolutionary scenario involves star formation in small-n clusters which then progressively merge; the first stars to form are seeds of massive stars and achieve a headstart in mass acquisition. These massive seeds end up in the cores of clusters and a large fraction of new stars of lower mass is formed in the outer parts of the clusters. The resulting clusters are therefore mass segregated at an age of 0.5 Myr, although the signature of mass segregation is weakened during mergers. We find that the resulting IMF has a smaller exponent (alpha=1.8-2.2) than the Salpeter value (alpha=2.35). The IMFs in subclusters are truncated at masses only somewhat larger th...

  18. A combined multidimensional scaling and hierarchical clustering view for the exploratory analysis of multidimensional data

    Science.gov (United States)

    Craig, Paul; Roa-Seïler, Néna

    2013-01-01

    This paper describes a novel information visualization technique that combines multidimensional scaling and hierarchical clustering to support the exploratory analysis of multidimensional data. The technique displays the results of multidimensional scaling using a scatter plot where the proximity of any two items' representations is approximate to their similarity according to a Euclidean distance metric. The results of hierarchical clustering are overlaid onto this view by drawing smoothed outlines around each nested cluster. The difference in similarity between successive cluster combinations is used to colour code clusters and make stronger natural clusters more prominent in the display. When a cluster or group of items is selected, multidimensional scaling and hierarchical clustering are re-applied to a filtered subset of the data, and animation is used to smooth the transition between successive filtered views. As a case study we demonstrate the technique being used to analyse survey data relating to the appropriateness of different phrases to different emotionally charged situations.

  19. Multiscale stochastic hierarchical image segmentation by spectral clustering

    Institute of Scientific and Technical Information of China (English)

    LI XiaoBin; TIAN Zheng

    2007-01-01

    This paper proposes a sampling based hierarchical approach for solving the computational demands of the spectral clustering methods when applied to the problem of image segmentation. The authors first define the distance between a pixel and a cluster, and then derive a new theorem to estimate the number of samples needed for clustering. Finally, by introducing a scale parameter into the similarity function, a novel spectral clustering based image segmentation method has been developed. An important characteristic of the approach is that in the course of image segmentation one needs not only to tune the scale parameter to merge the small size clusters or split the large size clusters but also take samples from the data set at the different scales. The multiscale and stochastic nature makes it feasible to apply the method to very large grouping problem. In addition, it also makes the segmentation compute in time that is linear in the size of the image. The experimental results on various synthetic and real world images show the effectiveness of the approach.

  20. Hierarchical Clustering and the Concept of Space Distortion.

    Science.gov (United States)

    Hubert, Lawrence; Schultz, James

    An empirical assesssment of the space distortion properties of two prototypic hierarchical clustering procedures is given in terms of an occupancy model developed from combinatorics. Using one simple example, the single-link and complete-link clustering strategies now in common use in the behavioral sciences are empirically shown to be space…

  1. The Hierarchical Distribution of Young Stellar Clusters in Nearby Galaxies

    Science.gov (United States)

    Grasha, Kathryn; Calzetti, Daniela

    2017-01-01

    We investigate the spatial distributions of young stellar clusters in six nearby galaxies to trace the large scale hierarchical star-forming structures. The six galaxies are drawn from the Legacy ExtraGalactic UV Survey (LEGUS). We quantify the strength of the clustering among stellar clusters as a function of spatial scale and age to establish the survival timescale of the substructures. We separate the clusters into different classes, compact (bound) clusters and associations (unbound), and compare the clustering among them. We find that younger star clusters are more strongly clustered over small spatial scales and that the clustering disappears rapidly for ages as young as a few tens of Myr, consistent with clusters slowly losing the fractal dimension inherited at birth from their natal molecular clouds.

  2. Hierarchical Clustering Given Confidence Intervals of Metric Distances

    CERN Document Server

    Huang, Weiyu

    2016-01-01

    This paper considers metric spaces where distances between a pair of nodes are represented by distance intervals. The goal is to study methods for the determination of hierarchical clusters, i.e., a family of nested partitions indexed by a resolution parameter, induced from the given distance intervals of the metric spaces. Our construction of hierarchical clustering methods is based on defining admissible methods to be those methods that abide to the axioms of value - nodes in a metric space with two nodes are clustered together at the convex combination of the distance bounds between them - and transformation - when both distance bounds are reduced, the output may become more clustered but not less. Two admissible methods are constructed and are shown to provide universal upper and lower bounds in the space of admissible methods. Practical implications are explored by clustering moving points via snapshots and by clustering networks representing brain structural connectivity using the lower and upper bounds...

  3. Hierarchical modeling of cluster size in wildlife surveys

    Science.gov (United States)

    Royle, J. Andrew

    2008-01-01

    Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

  4. Update Legal Documents Using Hierarchical Ranking Models and Word Clustering

    OpenAIRE

    Pham, Minh Quang Nhat; Nguyen, Minh Le; Shimazu, Akira

    2010-01-01

    Our research addresses the task of updating legal documents when newinformation emerges. In this paper, we employ a hierarchical ranking model tothe task of updating legal documents. Word clustering features are incorporatedto the ranking models to exploit semantic relations between words. Experimentalresults on legal data built from the United States Code show that the hierarchicalranking model with word clustering outperforms baseline methods using VectorSpace Model, and word cluster-based ...

  5. Kinematic gait patterns in healthy runners: A hierarchical cluster analysis.

    Science.gov (United States)

    Phinyomark, Angkoon; Osis, Sean; Hettinga, Blayne A; Ferber, Reed

    2015-11-01

    Previous studies have demonstrated distinct clusters of gait patterns in both healthy and pathological groups, suggesting that different movement strategies may be represented. However, these studies have used discrete time point variables and usually focused on only one specific joint and plane of motion. Therefore, the first purpose of this study was to determine if running gait patterns for healthy subjects could be classified into homogeneous subgroups using three-dimensional kinematic data from the ankle, knee, and hip joints. The second purpose was to identify differences in joint kinematics between these groups. The third purpose was to investigate the practical implications of clustering healthy subjects by comparing these kinematics with runners experiencing patellofemoral pain (PFP). A principal component analysis (PCA) was used to reduce the dimensionality of the entire gait waveform data and then a hierarchical cluster analysis (HCA) determined group sets of similar gait patterns and homogeneous clusters. The results show two distinct running gait patterns were found with the main between-group differences occurring in frontal and sagittal plane knee angles (Pgait strategies. These results suggest care must be taken when selecting samples of subjects in order to investigate the pathomechanics of injured runners.

  6. MultiDendrograms: Variable-Group Agglomerative Hierarchical Clustering

    CERN Document Server

    Gomez, Sergio; Montiel, Justo; Torres, David

    2012-01-01

    MultiDendrograms is a Java-written application that computes agglomerative hierarchical clusterings of data. Starting from a distances (or weights) matrix, MultiDendrograms is able to calculate its dendrograms using the most common agglomerative hierarchical clustering methods. The application implements a variable-group algorithm that solves the non-uniqueness problem found in the standard pair-group algorithm. This problem arises when two or more minimum distances between different clusters are equal during the agglomerative process, because then different output clusterings are possible depending on the criterion used to break ties between distances. MultiDendrograms solves this problem implementing a variable-group algorithm that groups more than two clusters at the same time when ties occur.

  7. Performance Analysis of Hierarchical Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    K.Ranjini

    2011-07-01

    Full Text Available Clustering is the classification of objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters, so that the data in each subset (ideally share some common trait - often proximity according to some defined distance measure. Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. This paper explains the implementation of agglomerative and divisive clustering algorithms applied on various types of data. The details of the victims of Tsunami in Thailand during the year 2004, was taken as the test data. Visual programming is used for implementation and running time of the algorithms using different linkages (agglomerative to different types of data are taken for analysis.

  8. Hierarchical clusters of phytoplankton variables in dammed water bodies

    Science.gov (United States)

    Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

    2017-06-01

    In this paper a dataset containing biological variables of the water column of several Portuguese reservoirs is analyzed. Hierarchical cluster analysis is used to obtain clusters of phytoplankton variables of the phylum Cyanophyta, with the objective of validating the classification of Portuguese reservoirs previewly presented in [1] which were divided into three clusters: (1) Interior Tagus and Aguieira; (2) Douro; and (3) Other rivers. Now three new clusters of Cyanophyta variables were found. Kruskal-Wallis and Mann-Whitney tests are used to compare the now obtained Cyanophyta clusters and the previous Reservoirs clusters, in order to validate the classification of the water quality of reservoirs. The amount of Cyanophyta algae present in the reservoirs from the three clusters is significantly different, which validates the previous classification.

  9. Exploiting Homogeneity of Density in Incremental Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Dwi H. Widiyantoro

    2006-11-01

    Full Text Available Hierarchical clustering is an important tool in many applications. As it involves a large data set that proliferates over time, reclustering the data set periodically is not an efficient process. Therefore, the ability to incorporate a new data set incrementally into an existing hierarchy becomes increasingly demanding. This article describes Homogen, a system that employs a new algorithm for generating a hierarchy of concepts and clusters incrementally from a stream of observations. The system aims to construct a hierarchy that satisfies the homogeneity and the monotonicity properties. Working in a bottom-up fashion, a new observation is placed in the hierarchy and a sequence of hierarchy restructuring processes is performed only in regions that have been affected by the presence of the new observation. Additionally, it combines multiple restructuring techniques that address different restructuring objectives to get a synergistic effect. The system has been tested on a variety of domains including structured and unstructured data sets. The experimental results reveal that the system is able to construct a concept hierarchy that is consistent regardless of the input data order and whose quality is comparable to the quality of those produced by non incremental clustering algorithms.

  10. Content Based Image Retrieval using Hierarchical and K-Means Clustering Techniques

    Directory of Open Access Journals (Sweden)

    V.S.V.S. Murthy

    2010-03-01

    Full Text Available In this paper we present an image retrieval system that takes an image as the input query and retrieves images based on image content. Content Based Image Retrieval is an approach for retrieving semantically-relevant images from an image database based on automatically-derived image features. The unique aspect of the system is the utilization of hierarchical and k-means clustering techniques. The proposed procedure consists of two stages. First, here we are going to filter most of the images in the hierarchical clustering and then apply the clustered images to KMeans, so that we can get better favored image results.

  11. Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Vishal Krishna Singh

    2016-02-01

    Full Text Available Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs. In such an environment, reducing the in-network communication and distributing the load evenly over the network can reduce the overall energy consumption and maximize the network lifetime significantly. In this work, the aforementioned problem of network lifetime and uneven energy consumption in large scale wireless sensor networks is addressed. This work proposes a hierarchical compressed sensing (HCS scheme to reduce the in-network communication during the data gathering process. Co-related sensor readings are collected via a hierarchical clustering scheme. A compressed sensing (CS based data processing scheme is devised to transmit the data from the source to the sink. The proposed HCS is able to identify the optimal position for the application of CS to achieve reduced and similar number of transmissions on all the nodes in the network. An activity map is generated to validate the reduced and uniformly distributed communication load of the WSN. Based on the number of transmissions per data gathering round, the bit-hop metric model is used to analyse the overall energy consumption. Simulation results validate the efficiency of the proposed method over the existing CS based approaches.

  12. Hierarchical clustering techniques for image database organization and summarization

    Science.gov (United States)

    Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    This paper investigates clustering techniques as a method of organizing image databases to support popular visual management functions such as searching, browsing and navigation. Different types of hierarchical agglomerative clustering techniques are studied as a method of organizing features space as well as summarizing image groups by the selection of a few appropriate representatives. Retrieval performance using both single and multiple level hierarchies are experimented with and the algorithms show an interesting relationship between the top k correct retrievals and the number of comparisons required. Some arguments are given to support the use of such cluster-based techniques for managing distributed image databases.

  13. Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities

    CERN Document Server

    Eriksson, Brian; Singh, Aarti; Nowak, Robert

    2011-01-01

    Hierarchical clustering based on pairwise similarities is a common tool used in a broad range of scientific applications. However, in many problems it may be expensive to obtain or compute similarities between the items to be clustered. This paper investigates the hierarchical clustering of N items based on a small subset of pairwise similarities, significantly less than the complete set of N(N-1)/2 similarities. First, we show that if the intracluster similarities exceed intercluster similarities, then it is possible to correctly determine the hierarchical clustering from as few as 3N log N similarities. We demonstrate this order of magnitude savings in the number of pairwise similarities necessitates sequentially selecting which similarities to obtain in an adaptive fashion, rather than picking them at random. We then propose an active clustering method that is robust to a limited fraction of anomalous similarities, and show how even in the presence of these noisy similarity values we can resolve the hierar...

  14. A Framework for Analyzing Software Quality using Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Arashdeep Kaur

    2011-02-01

    Full Text Available Fault proneness data available in the early software life cycle from previous releases or similar kind of projects will aid in improving software quality estimations. Various techniques have been proposed in the literature which includes statistical method, machine learning methods, neural network techniques and clustering techniques for the prediction of faulty and non faulty modules in the project. In this study, Hierarchical clustering algorithm is being trained and tested with lifecycle data collected from NASA projects namely, CM1, PC1 and JM1 as predictive models. These predictive models contain requirement metrics and static code metrics. We have combined requirement metric model with static code metric model to get fusion metric model. Further we have investigated that which of the three prediction models is found to be the best prediction model on the basis of fault detection. The basic hypothesis of software quality estimation is that automatic quality prediction models enable verificationexperts to concentrate their attention and resources at problem areas of the system under development. The proposed approach has been implemented in MATLAB 7.4. The results show that when all the prediction techniques are evaluated, the best prediction model is found to be the fusion metric model. This proposed model is also compared with other quality models available in the literature and is found to be efficient for predicting faulty modules.

  15. Evaluation by hierarchical clustering of multiple cytokine expression after phytohemagglutinin stimulation

    Directory of Open Access Journals (Sweden)

    Yang Chunhe

    2016-01-01

    Full Text Available The hierarchical clustering method has been used for exploration of gene expression and proteomic profiles; however, little research into its application in the examination of expression of multiplecytokine/chemokine responses to stimuli has been reported. Thus, little progress has been made on how phytohemagglutinin(PHA affects cytokine expression profiling on a large scale in the human hematological system. To investigate the characteristic expression pattern under PHA stimulation, Luminex, a multiplex bead-based suspension array, was performed. The data set collected from human peripheral blood mononuclear cells (PBMC was analyzed using the hierarchical clustering method. It was revealed that two specific chemokines (CCL3 andCCL4 underwent significantly greater quantitative changes during induction of expression than other tested cytokines/chemokines after PHA stimulation. This result indicates that hierarchical clustering is a useful tool for detecting fine patterns during exploration of biological data, and that it can play an important role in comparative studies.

  16. Hierarchical trie packet classification algorithm based on expectation-maximization clustering

    Science.gov (United States)

    Bi, Xia-an; Zhao, Junxia

    2017-01-01

    With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm. PMID:28704476

  17. Non-hierarchical clustering methods on factorial subspaces

    OpenAIRE

    Tortora, Cristina

    2011-01-01

    Cluster analysis (CA) aims at finding homogeneous group of individuals, where homogeneous is referred to individuals that present similar characteristics. Many CA techniques already exist, among the non-hierarchical ones the most known, thank to its simplicity and computational property, is k-means method. However, the method is unstable when the number of variables is large and when variables are correlated. This problem leads to the development of two-step methods, they perform a linear tra...

  18. Extending stability through hierarchical clusters in Echo State Networks

    Directory of Open Access Journals (Sweden)

    Sarah Jarvis

    2010-07-01

    Full Text Available Echo State Networks (ESN are reservoir networks that satisfy well-established criteria for stability when constructed as feedforward networks. Recent evidence suggests that stability criteria are altered in the presence of reservoir substructures, such as clusters. Understanding how the reservoir architecture affects stability is thus important for the appropriate design of any ESN. To quantitatively determine the influence of the most relevant network parameters, we analysed the impact of reservoir substructures on stability in hierarchically clustered ESNs (HESN, as they allow a smooth transition from highly structured to increasingly homogeneous reservoirs. Previous studies used the largest eigenvalue of the reservoir connectivity matrix (spectral radius as a predictor for stable network dynamics. Here, we evaluate the impact of clusters, hierarchy and intercluster connectivity on the predictive power of the spectral radius for stability. Both hierarchy and low relative cluster sizes extend the range of spectral radius values, leading to stable networks, while increasing intercluster connectivity decreased maximal spectral radius.

  19. Globular cluster formation with multiple stellar populations from hierarchical star cluster complexes

    Science.gov (United States)

    Bekki, Kenji

    2017-01-01

    Most old globular clusters (GCs) in the Galaxy are observed to have internal chemical abundance spreads in light elements. We discuss a new GC formation scenario based on hierarchical star formation within fractal molecular clouds. In the new scenario, a cluster of bound and unbound star clusters (`star cluster complex', SCC) that have a power-law cluster mass function with a slope (β) of 2 is first formed from a massive gas clump developed in a dwarf galaxy. Such cluster complexes and β = 2 are observed and expected from hierarchical star formation. The most massive star cluster (`main cluster'), which is the progenitor of a GC, can accrete gas ejected from asymptotic giant branch (AGB) stars initially in the cluster and other low-mass clusters before the clusters are tidally stripped or destroyed to become field stars in the dwarf. The SCC is initially embedded in a giant gas hole created by numerous supernovae of the SCC so that cold gas outside the hole can be accreted onto the main cluster later. New stars formed from the accreted gas have chemical abundances that are different from those of the original SCC. Using hydrodynamical simulations of GC formation based on this scenario, we show that the main cluster with the initial mass as large as [2 - 5] × 105M⊙ can accrete more than 105M⊙ gas from AGB stars of the SCC. We suggest that merging of hierarchical star cluster complexes can play key roles in stellar halo formation around GCs and self-enrichment processes in the early phase of GC formation.

  20. Mapping informative clusters in a hierarchical [corrected] framework of FMRI multivariate analysis.

    Directory of Open Access Journals (Sweden)

    Rui Xu

    Full Text Available Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies.

  1. Hierarchically Clustered Star Formation in the Magellanic Clouds

    CERN Document Server

    Gouliermis, Dimitrios A; Ossenkopf, Volker; Klessen, Ralf S; Dolphin, Andrew E

    2012-01-01

    We present a cluster analysis of the bright main-sequence and faint pre--main-sequence stellar populations of a field ~ 90 x 90 pc centered on the HII region NGC 346/N66 in the Small Magellanic Cloud, from imaging with HST/ACS. We extend our earlier analysis on the stellar cluster population in the region to characterize the structuring behavior of young stars in the region as a whole with the use of stellar density maps interpreted through techniques designed for the study of the ISM structuring. In particular, we demonstrate with Cartwrigth & Whitworth's Q parameter, dendrograms, and the Delta-variance wavelet transform technique that the young stellar populations in the region NGC 346/N66 are hierarchically clustered, in agreement with other regions in the Magellanic Clouds observed with HST. The origin of this hierarchy is currently under investigation.

  2. Hierarchical cluster-tendency analysis of the group structure in the foreign exchange market

    Science.gov (United States)

    Wu, Xin-Ye; Zheng, Zhi-Gang

    2013-08-01

    A hierarchical cluster-tendency (HCT) method in analyzing the group structure of networks of the global foreign exchange (FX) market is proposed by combining the advantages of both the minimal spanning tree (MST) and the hierarchical tree (HT). Fifty currencies of the top 50 World GDP in 2010 according to World Bank's database are chosen as the underlying system. By using the HCT method, all nodes in the FX market network can be "colored" and distinguished. We reveal that the FX networks can be divided into two groups, i.e., the Asia-Pacific group and the Pan-European group. The results given by the hierarchical cluster-tendency method agree well with the formerly observed geographical aggregation behavior in the FX market. Moreover, an oil-resource aggregation phenomenon is discovered by using our method. We find that gold could be a better numeraire for the weekly-frequency FX data.

  3. An agglomerative hierarchical approach to visualization in Bayesian clustering problems.

    Science.gov (United States)

    Dawson, K J; Belkhir, K

    2009-07-01

    Clustering problems (including the clustering of individuals into outcrossing populations, hybrid generations, full-sib families and selfing lines) have recently received much attention in population genetics. In these clustering problems, the parameter of interest is a partition of the set of sampled individuals--the sample partition. In a fully Bayesian approach to clustering problems of this type, our knowledge about the sample partition is represented by a probability distribution on the space of possible sample partitions. As the number of possible partitions grows very rapidly with the sample size, we cannot visualize this probability distribution in its entirety, unless the sample is very small. As a solution to this visualization problem, we recommend using an agglomerative hierarchical clustering algorithm, which we call the exact linkage algorithm. This algorithm is a special case of the maximin clustering algorithm that we introduced previously. The exact linkage algorithm is now implemented in our software package PartitionView. The exact linkage algorithm takes the posterior co-assignment probabilities as input and yields as output a rooted binary tree, or more generally, a forest of such trees. Each node of this forest defines a set of individuals, and the node height is the posterior co-assignment probability of this set. This provides a useful visual representation of the uncertainty associated with the assignment of individuals to categories. It is also a useful starting point for a more detailed exploration of the posterior distribution in terms of the co-assignment probabilities.

  4. Determination of genetic structure of germplasm collections: are traditional hierarchical clustering methods appropriate for molecular marker data?

    Science.gov (United States)

    Odong, T L; van Heerwaarden, J; Jansen, J; van Hintum, T J L; van Eeuwijk, F A

    2011-07-01

    Despite the availability of newer approaches, traditional hierarchical clustering remains very popular in genetic diversity studies in plants. However, little is known about its suitability for molecular marker data. We studied the performance of traditional hierarchical clustering techniques using real and simulated molecular marker data. Our study also compared the performance of traditional hierarchical clustering with model-based clustering (STRUCTURE). We showed that the cophenetic correlation coefficient is directly related to subgroup differentiation and can thus be used as an indicator of the presence of genetically distinct subgroups in germplasm collections. Whereas UPGMA performed well in preserving distances between accessions, Ward excelled in recovering groups. Our results also showed a close similarity between clusters obtained by Ward and by STRUCTURE. Traditional cluster analysis can provide an easy and effective way of determining structure in germplasm collections using molecular marker data, and, the output can be used for sampling core collections or for association studies.

  5. D Nearest Neighbour Search Using a Clustered Hierarchical Tree Structure

    Science.gov (United States)

    Suhaibah, A.; Uznir, U.; Anton, F.; Mioc, D.; Rahman, A. A.

    2016-06-01

    Locating and analysing the location of new stores or outlets is one of the common issues facing retailers and franchisers. This is due to assure that new opening stores are at their strategic location to attract the highest possible number of customers. Spatial information is used to manage, maintain and analyse these store locations. However, since the business of franchising and chain stores in urban areas runs within high rise multi-level buildings, a three-dimensional (3D) method is prominently required in order to locate and identify the surrounding information such as at which level of the franchise unit will be located or is the franchise unit located is at the best level for visibility purposes. One of the common used analyses used for retrieving the surrounding information is Nearest Neighbour (NN) analysis. It uses a point location and identifies the surrounding neighbours. However, with the immense number of urban datasets, the retrieval and analysis of nearest neighbour information and their efficiency will become more complex and crucial. In this paper, we present a technique to retrieve nearest neighbour information in 3D space using a clustered hierarchical tree structure. Based on our findings, the proposed approach substantially showed an improvement of response time analysis compared to existing approaches of spatial access methods in databases. The query performance was tested using a dataset consisting of 500,000 point locations building and franchising unit. The results are presented in this paper. Another advantage of this structure is that it also offers a minimal overlap and coverage among nodes which can reduce repetitive data entry.

  6. The Hierarchical Clustering of Tax Burden in the EU27

    Directory of Open Access Journals (Sweden)

    Simkova Nikola

    2015-09-01

    Full Text Available The issue of taxation has become more important due to a significant share of the government revenue. There are several ways of expressing the tax burden of countries. This paper describes the traditional approach as a share of tax revenue to GDP which is applied to the total taxation and the capital taxation as a part of tax systems affecting investment decisions. The implicit tax rate on capital created by Eurostat also offers a possible explanation of the tax burden on capital, so its components are analysed in detail. This study uses one of the econometric methods called the hierarchical clustering. The data on which the clustering is based comprises countries in the EU27 for the period of 1995 – 2012. The aim of this paper is to reveal clusters of countries in the EU27 with similar tax burden or tax changes. The findings suggest that mainly newly acceding countries (2004 and 2007 are in a group of countries with a low tax burden which tried to encourage investors by favourable tax rates. On the other hand, there are mostly countries from the original EU15. Some clusters may be explained by similar historical development, geographic and demographic characteristics.

  7. Hierarchical star cluster assembly in globally collapsing molecular clouds

    Science.gov (United States)

    Vázquez-Semadeni, Enrique; González-Samaniego, Alejandro; Colín, Pedro

    2017-05-01

    We discuss the mechanism of cluster formation in a numerical simulation of a molecular cloud (MC) undergoing global hierarchical collapse, focusing on how the gas motions in the parent cloud control the assembly of the cluster. The global collapse implies that the star formation rate (SFR) increases over time. The collapse is hierarchical because it consists of small-scale collapses within larger scale ones. The latter culminate a few Myr later than the first small-scale ones and consist of filamentary flows that accrete on to massive central clumps. The small-scale collapses consist of clumps that are embedded in the filaments and falling on to the large-scale collapse centres. The stars formed in the early, small-scale collapses share the infall motion of their parent clumps, so that the filaments feed both gas and stars to the massive central clump. This process leads to the presence of a few older stars in a region where new protostars are forming, and also to a self-similar structure, in which each unit is composed of smaller scale subunits that approach each other and may merge. Because the older stars formed in the filaments share the infall motion of the gas on to the central clump, they tend to have larger velocities and to be distributed over larger areas than the younger stars formed in the central clump. Finally, interpreting the initial mass function (IMF) simply as a probability distribution implies that massive stars only form once the local SFR is large enough to sample the IMF up to high masses. In combination with the increase of the SFR, this implies that massive stars tend to appear late in the evolution of the MC, and only in the central massive clumps. We discuss the correspondence of these features with observed properties of young stellar clusters, finding very good qualitative agreement.

  8. A Bayesian Alternative to Mutual Information for the Hierarchical Clustering of Dependent Random Variables.

    Directory of Open Access Journals (Sweden)

    Guillaume Marrelec

    Full Text Available The use of mutual information as a similarity measure in agglomerative hierarchical clustering (AHC raises an important issue: some correction needs to be applied for the dimensionality of variables. In this work, we formulate the decision of merging dependent multivariate normal variables in an AHC procedure as a Bayesian model comparison. We found that the Bayesian formulation naturally shrinks the empirical covariance matrix towards a matrix set a priori (e.g., the identity, provides an automated stopping rule, and corrects for dimensionality using a term that scales up the measure as a function of the dimensionality of the variables. Also, the resulting log Bayes factor is asymptotically proportional to the plug-in estimate of mutual information, with an additive correction for dimensionality in agreement with the Bayesian information criterion. We investigated the behavior of these Bayesian alternatives (in exact and asymptotic forms to mutual information on simulated and real data. An encouraging result was first derived on simulations: the hierarchical clustering based on the log Bayes factor outperformed off-the-shelf clustering techniques as well as raw and normalized mutual information in terms of classification accuracy. On a toy example, we found that the Bayesian approaches led to results that were similar to those of mutual information clustering techniques, with the advantage of an automated thresholding. On real functional magnetic resonance imaging (fMRI datasets measuring brain activity, it identified clusters consistent with the established outcome of standard procedures. On this application, normalized mutual information had a highly atypical behavior, in the sense that it systematically favored very large clusters. These initial experiments suggest that the proposed Bayesian alternatives to mutual information are a useful new tool for hierarchical clustering.

  9. A Bayesian Alternative to Mutual Information for the Hierarchical Clustering of Dependent Random Variables.

    Science.gov (United States)

    Marrelec, Guillaume; Messé, Arnaud; Bellec, Pierre

    2015-01-01

    The use of mutual information as a similarity measure in agglomerative hierarchical clustering (AHC) raises an important issue: some correction needs to be applied for the dimensionality of variables. In this work, we formulate the decision of merging dependent multivariate normal variables in an AHC procedure as a Bayesian model comparison. We found that the Bayesian formulation naturally shrinks the empirical covariance matrix towards a matrix set a priori (e.g., the identity), provides an automated stopping rule, and corrects for dimensionality using a term that scales up the measure as a function of the dimensionality of the variables. Also, the resulting log Bayes factor is asymptotically proportional to the plug-in estimate of mutual information, with an additive correction for dimensionality in agreement with the Bayesian information criterion. We investigated the behavior of these Bayesian alternatives (in exact and asymptotic forms) to mutual information on simulated and real data. An encouraging result was first derived on simulations: the hierarchical clustering based on the log Bayes factor outperformed off-the-shelf clustering techniques as well as raw and normalized mutual information in terms of classification accuracy. On a toy example, we found that the Bayesian approaches led to results that were similar to those of mutual information clustering techniques, with the advantage of an automated thresholding. On real functional magnetic resonance imaging (fMRI) datasets measuring brain activity, it identified clusters consistent with the established outcome of standard procedures. On this application, normalized mutual information had a highly atypical behavior, in the sense that it systematically favored very large clusters. These initial experiments suggest that the proposed Bayesian alternatives to mutual information are a useful new tool for hierarchical clustering.

  10. Lyman Alpha Emitters in the Hierarchically Clustering Galaxy Formation

    CERN Document Server

    Kobayashi, Masakazu A R; Nagashima, Masahiro

    2007-01-01

    We present a new theoretical model for the luminosity functions (LFs) of Lyman alpha (Lya) emitting galaxies in the framework of hierarchical galaxy formation. We extend a semi-analytic model of galaxy formation that reproduces a number of observations for local galaxies, without changing the original model parameters but introducing a physically-motivated modelling to describe the escape fraction of Lya photons from host galaxies (f_esc). Though a previous study using a hierarchical clustering model simply assumed a constant and universal value of f_esc, we incorporate two new effects on f_esc: extinction by interstellar dust and galaxy-scale outflow induced as a star formation feedback. It is found that the new model nicely reproduces all the observed Lya LFs of the Lya emitters (LAEs) at different redshifts in z ~ 3--6. Our model predicts that galaxies with strong outflows and f_esc ~ 1 are dominant in the observed LFs, which is consistent with available observations while the simple universal f_esc model ...

  11. The structure of dark matter halos in hierarchical clustering theories

    CERN Document Server

    Subramanian, K; Ostriker, J P; Subramanian, Kandaswamy; Cen, Renyue; Ostriker, Jeremiah P.

    1999-01-01

    During hierarchical clustering, smaller masses generally collapse earlier than larger masses and so are denser on the average. The core of a small mass halo could be dense enough to resist disruption and survive undigested, when it is incorporated into a bigger object. We explore the possibility that a nested sequence of undigested cores in the center of the halo, which have survived the hierarchical, inhomogeneous collapse to form larger and larger objects, determines the halo structure in the inner regions. For a flat universe with $P(k) \\propto k^n$, scaling arguments then suggest that the core density profile is, $\\rho \\propto r^{-\\alpha}$ with $\\alpha = (9+3n)/(5+n)$. But whether such behaviour obtains depends on detailed dynamics. We first examine the dynamics using a fluid approach to the self-similar collapse solutions for the dark matter phase space density, including the effect of velocity dispersions. We highlight the importance of tangential velocity dispersions to obtain density profiles shallowe...

  12. Hand Tracking based on Hierarchical Clustering of Range Data

    CERN Document Server

    Cespi, Roberto; Lindner, Marvin

    2011-01-01

    Fast and robust hand segmentation and tracking is an essential basis for gesture recognition and thus an important component for contact-less human-computer interaction (HCI). Hand gesture recognition based on 2D video data has been intensively investigated. However, in practical scenarios purely intensity based approaches suffer from uncontrollable environmental conditions like cluttered background colors. In this paper we present a real-time hand segmentation and tracking algorithm using Time-of-Flight (ToF) range cameras and intensity data. The intensity and range information is fused into one pixel value, representing its combined intensity-depth homogeneity. The scene is hierarchically clustered using a GPU based parallel merging algorithm, allowing a robust identification of both hands even for inhomogeneous backgrounds. After the detection, both hands are tracked on the CPU. Our tracking algorithm can cope with the situation that one hand is temporarily covered by the other hand.

  13. Identifying Reference Objects by Hierarchical Clustering in Java Environment

    Directory of Open Access Journals (Sweden)

    RAHUL SAHA

    2011-09-01

    Full Text Available Recently Java programming environment has become so popular. Java programming language is a language that is designed to be portable enough to be executed in wide range of computers ranging from cell phones to supercomputers. Computer programs written in Java are compiled into Java Byte code instructions that are suitable for execution by a Java Virtual Machine implementation. Java virtual Machine is commonly implemented in software by means of an interpreter for the Java Virtual Machine instruction set. As an object oriented language, Java utilizes the concept of objects. Our idea is to identify the candidate objects references in a Java environment through hierarchical cluster analysis using reference stack and execution stack.

  14. The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS

    NARCIS (Netherlands)

    Zhou, Q.; Leng, F.; Leydesdorff, L.

    2015-01-01

    Purpose: To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions. Design/methodology/approach: We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare the

  15. The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS

    NARCIS (Netherlands)

    Zhou, Q.; Leng, F.; Leydesdorff, L.

    2015-01-01

    Purpose: To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions. Design/methodology/approach: We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare

  16. Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering

    Science.gov (United States)

    Tilton, James C.

    2002-01-01

    This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.

  17. Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics.

    Directory of Open Access Journals (Sweden)

    Korsuk Sirinukunwattana

    Full Text Available Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites.google.com/site/gaussianbhc/

  18. Determination of genetic structure of germplasm collections: are traditional hierarchical clustering methods appropriate for molecular marker data?

    NARCIS (Netherlands)

    Odong, T.L.; Heerwaarden, van J.; Jansen, J.; Hintum, van T.J.L.; Eeuwijk, van F.A.

    2011-01-01

    Despite the availability of newer approaches, traditional hierarchical clustering remains very popular in genetic diversity studies in plants. However, little is known about its suitability for molecular marker data. We studied the performance of traditional hierarchical clustering techniques using

  19. An energy efficient cooperative hierarchical MIMO clustering scheme for wireless sensor networks.

    Science.gov (United States)

    Nasim, Mehwish; Qaisar, Saad; Lee, Sungyoung

    2012-01-01

    In this work, we present an energy efficient hierarchical cooperative clustering scheme for wireless sensor networks. Communication cost is a crucial factor in depleting the energy of sensor nodes. In the proposed scheme, nodes cooperate to form clusters at each level of network hierarchy ensuring maximal coverage and minimal energy expenditure with relatively uniform distribution of load within the network. Performance is enhanced by cooperative multiple-input multiple-output (MIMO) communication ensuring energy efficiency for WSN deployments over large geographical areas. We test our scheme using TOSSIM and compare the proposed scheme with cooperative multiple-input multiple-output (CMIMO) clustering scheme and traditional multihop Single-Input-Single-Output (SISO) routing approach. Performance is evaluated on the basis of number of clusters, number of hops, energy consumption and network lifetime. Experimental results show significant energy conservation and increase in network lifetime as compared to existing schemes.

  20. Clinical fracture risk evaluated by hierarchical agglomerative clustering

    DEFF Research Database (Denmark)

    Kruse, Christian; Eiken, P; Vestergaard, P

    2017-01-01

    profiles. INTRODUCTION: The purposes of this study were to establish and quantify patient clusters of high, average and low fracture risk using an unsupervised machine learning algorithm. METHODS: Regional and national Danish patient data on dual-energy X-ray absorptiometry (DXA) scans, medication...... containing less than 250 subjects. Clusters were identified as high, average or low fracture risk based on bone mineral density (BMD) characteristics. Cluster-based descriptive statistics and relative Z-scores for variable means were computed. RESULTS: Ten thousand seven hundred seventy-five women were...... as low fracture risk with high to very high BMD. A mean age of 60 years was the earliest that allowed for separation of high-risk clusters. DXA scan results could identify high-risk subjects with different antiresorptive treatment compliance levels based on similarities and differences in lumbar spine...

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

    Science.gov (United States)

    Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

    2017-09-01

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

  2. Hierarchical clusters in families with type 2 diabetes

    Science.gov (United States)

    García-Solano, Beatriz; Gallegos-Cabriales, Esther C; Gómez-Meza, Marco V; García-Madrid, Guillermina; Flores-Merlo, Marcela; García-Solano, Mauro

    2015-01-01

    Families represent more than a set of individuals; family is more than a sum of its individual members. With this classification, nurses can identify the family health-illness beliefs obey family as a unit concept, and plan family inclusion into the type 2 diabetes treatment, whom is not considered in public policy, despite families share diet, exercise, and self-monitoring with a member who suffers type 2 diabetes. The aim of this study was to determine whether the characteristics, functionality, routines, and family and individual health in type 2 diabetes describes the differences and similarities between families to consider them as a unit. We performed an exploratory, descriptive hierarchical cluster analysis of 61 families using three instruments and a questionnaire, in addition to weight, height, body fat percentage, hemoglobin A1c, total cholesterol, triglycerides, low-density lipoprotein and high-density lipoprotein. The analysis produced three groups of families. Wilk’s lambda demonstrated statistically significant differences provided by age (Λ = 0.778, F = 2.098, p = 0.010) and family health (Λ = 0.813, F = 2.650, p = 0.023). A post hoc Tukey test coincided with the three subsets. Families with type 2 diabetes have common elements that make them similar, while sharing differences that make them unique. PMID:27347419

  3. Applying of hierarchical clustering to analysis of protein patterns in the human cancer-associated liver.

    Directory of Open Access Journals (Sweden)

    Natalia A Petushkova

    Full Text Available There are two ways that statistical methods can learn from biomedical data. One way is to learn classifiers to identify diseases and to predict outcomes using the training dataset with established diagnosis for each sample. When the training dataset is not available the task can be to mine for presence of meaningful groups (clusters of samples and to explore underlying data structure (unsupervised learning.We investigated the proteomic profiles of the cytosolic fraction of human liver samples using two-dimensional electrophoresis (2DE. Samples were resected upon surgical treatment of hepatic metastases in colorectal cancer. Unsupervised hierarchical clustering of 2DE gel images (n = 18 revealed a pair of clusters, containing 11 and 7 samples. Previously we used the same specimens to measure biochemical profiles based on cytochrome P450-dependent enzymatic activities and also found that samples were clearly divided into two well-separated groups by cluster analysis. It turned out that groups by enzyme activity almost perfectly match to the groups identified from proteomic data. Of the 271 reproducible spots on our 2DE gels, we selected 15 to distinguish the human liver cytosolic clusters. Using MALDI-TOF peptide mass fingerprinting, we identified 12 proteins for the selected spots, including known cancer-associated species.Our results highlight the importance of hierarchical cluster analysis of proteomic data, and showed concordance between results of biochemical and proteomic approaches. Grouping of the human liver samples and/or patients into differing clusters may provide insights into possible molecular mechanism of drug metabolism and creates a rationale for personalized treatment.

  4. The formation of NGC 3603 young starburst cluster: "prompt" hierarchical assembly or monolithic starburst?

    CERN Document Server

    Banerjee, Sambaran

    2014-01-01

    The formation of very young massive clusters or "starburst" clusters is currently one of the most widely debated topic in astronomy. The classical notion dictates that a star cluster is formed in-situ in a dense molecular gas clump followed by a substantial residual gas expulsion. On the other hand, based on the observed morphologies of many young stellar associations, a hierarchical formation scenario is alternatively suggested. A very young (age $\\approx$ 1 Myr), massive ($>10^4M_\\odot$) star cluster like the Galactic NGC 3603 young cluster (HD 97950) is an appropriate testbed for distinguishing between such "monolithic" and "hierarchical" formation scenarios. A recent study by Banerjee and Kroupa (2014) demonstrates that the monolithic scenario remarkably reproduces the HD 97950 cluster. In the present work, we explore the possibility of the formation of the above cluster via hierarchical assembly of subclusters. These subclusters are initially distributed over a wide range of spatial volumes and have vari...

  5. A novel approach to the problem of non-uniqueness of the solution in hierarchical clustering.

    Science.gov (United States)

    Cattinelli, Isabella; Valentini, Giorgio; Paulesu, Eraldo; Borghese, Nunzio Alberto

    2013-07-01

    The existence of multiple solutions in clustering, and in hierarchical clustering in particular, is often ignored in practical applications. However, this is a non-trivial problem, as different data orderings can result in different cluster sets that, in turns, may lead to different interpretations of the same data. The method presented here offers a solution to this issue. It is based on the definition of an equivalence relation over dendrograms that allows developing all and only the significantly different dendrograms for the same dataset, thus reducing the computational complexity to polynomial from the exponential obtained when all possible dendrograms are considered. Experimental results in the neuroimaging and bioinformatics domains show the effectiveness of the proposed method.

  6. A COMPARISON BETWEEN SINGLE LINKAGE AND COMPLETE LINKAGE IN AGGLOMERATIVE HIERARCHICAL CLUSTER ANALYSIS FOR IDENTIFYING TOURISTS SEGMENTS

    OpenAIRE

    Noor Rashidah Rashid

    2012-01-01

    Cluster Analysis is a multivariate method in statistics. Agglomerative Hierarchical Cluster Analysis is one of approaches in Cluster Analysis. There are two linkage methods in Agglomerative Hierarchical Cluster Analysis which are Single Linkage and Complete Linkage. The purpose of this study is to compare between Single Linkage and Complete Linkage in Agglomerative Hierarchical Cluster Analysis. The comparison of performances between these linkage methods was shown by using Kruskal-Wallis tes...

  7. Evolutionary-Hierarchical Bases of the Formation of Cluster Model of Innovation Economic Development

    Directory of Open Access Journals (Sweden)

    Yuliya Vladimirovna Dubrovskaya

    2016-10-01

    Full Text Available The functioning of a modern economic system is based on the interaction of objects of different hierarchical levels. Thus, the problem of the study of innovation processes taking into account the mutual influence of the activities of these economic actors becomes important. The paper dwells evolutionary basis for the formation of models of innovation development on the basis of micro and macroeconomic analysis. Most of the concepts recognized that despite a big number of diverse models, the coordination of the relations between economic agents is of crucial importance for the successful innovation development. According to the results of the evolutionary-hierarchical analysis, the authors reveal key phases of the development of forms of business cooperation, science and government in the domestic economy. It has become the starting point of the conception of the characteristics of the interaction in the cluster models of innovation development of the economy. Considerable expectancies on improvement of the national innovative system are connected with the development of cluster and network structures. The main objective of government authorities is the formation of mechanisms and institutions that will foster cooperation between members of the clusters. The article explains that the clusters cannot become the factors in the growth of the national economy, not being an effective tool for interaction between the actors of the regional innovative systems.

  8. SHIPS: Spectral Hierarchical clustering for the Inference of Population Structure in genetic studies.

    Science.gov (United States)

    Bouaziz, Matthieu; Paccard, Caroline; Guedj, Mickael; Ambroise, Christophe

    2012-01-01

    Inferring the structure of populations has many applications for genetic research. In addition to providing information for evolutionary studies, it can be used to account for the bias induced by population stratification in association studies. To this end, many algorithms have been proposed to cluster individuals into genetically homogeneous sub-populations. The parametric algorithms, such as Structure, are very popular but their underlying complexity and their high computational cost led to the development of faster parametric alternatives such as Admixture. Alternatives to these methods are the non-parametric approaches. Among this category, AWclust has proven efficient but fails to properly identify population structure for complex datasets. We present in this article a new clustering algorithm called Spectral Hierarchical clustering for the Inference of Population Structure (SHIPS), based on a divisive hierarchical clustering strategy, allowing a progressive investigation of population structure. This method takes genetic data as input to cluster individuals into homogeneous sub-populations and with the use of the gap statistic estimates the optimal number of such sub-populations. SHIPS was applied to a set of simulated discrete and admixed datasets and to real SNP datasets, that are data from the HapMap and Pan-Asian SNP consortium. The programs Structure, Admixture, AWclust and PCAclust were also investigated in a comparison study. SHIPS and the parametric approach Structure were the most accurate when applied to simulated datasets both in terms of individual assignments and estimation of the correct number of clusters. The analysis of the results on the real datasets highlighted that the clusterings of SHIPS were the more consistent with the population labels or those produced by the Admixture program. The performances of SHIPS when applied to SNP data, along with its relatively low computational cost and its ease of use make this method a promising

  9. A dynamic hierarchical clustering method for trajectory-based unusual video event detection.

    Science.gov (United States)

    Jiang, Fan; Wu, Ying; Katsaggelos, Aggelos K

    2009-04-01

    The proposed unusual video event detection method is based on unsupervised clustering of object trajectories, which are modeled by hidden Markov models (HMM). The novelty of the method includes a dynamic hierarchical process incorporated in the trajectory clustering algorithm to prevent model overfitting and a 2-depth greedy search strategy for efficient clustering.

  10. THE EVOLUTION OF BRIGHTEST CLUSTER GALAXIES IN A HIERARCHICAL UNIVERSE

    Energy Technology Data Exchange (ETDEWEB)

    Tonini, Chiara; Bernyk, Maksym; Croton, Darren [Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Melbourne, VIC 3122 (Australia); Maraston, Claudia; Thomas, Daniel [Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX (United Kingdom)

    2012-11-01

    We investigate the evolution of brightest cluster galaxies (BCGs) from redshift z {approx} 1.6 to z = 0. We upgrade the hierarchical semi-analytic model of Croton et al. with a new spectro-photometric model that produces realistic galaxy spectra, making use of the Maraston stellar populations and a new recipe for the dust extinction. We compare the model predictions of the K-band luminosity evolution and the J - K, V - I, and I - K color evolution with a series of data sets, including those of Collins et al. who argued that semi-analytic models based on the Millennium simulation cannot reproduce the red colors and high luminosity of BCGs at z > 1. We show instead that the model is well in range of the observed luminosity and correctly reproduces the color evolution of BCGs in the whole redshift range up to z {approx} 1.6. We argue that the success of the semi-analytic model is in large part due to the implementation of a more sophisticated spectro-photometric model. An analysis of the model BCGs shows an increase in mass by a factor of 2-3 since z {approx} 1, and star formation activity down to low redshifts. While the consensus regarding BCGs is that they are passively evolving, we argue that this conclusion is affected by the degeneracy between star formation history and stellar population models used in spectral energy distribution fitting, and by the inefficacy of toy models of passive evolution to capture the complexity of real galaxies, especially those with rich merger histories like BCGs. Following this argument, we also show that in the semi-analytic model the BCGs show a realistic mix of stellar populations, and that these stellar populations are mostly old. In addition, the age-redshift relation of the model BCGs follows that of the universe, meaning that given their merger history and star formation history, the ageing of BCGs is always dominated by the ageing of their stellar populations. In a {Lambda}CDM universe, we define such evolution as &apos

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

    Science.gov (United States)

    Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

    2017-07-01

    Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

  12. Iterative Maps with Hierarchical Clustering for the Observed Scales of Astrophysical and Cosmological Structures

    CERN Document Server

    Capozziello, S; De Siena, S; Guerra, F; Illuminati, F

    2000-01-01

    We derive, in order of magnitude, the observed astrophysical and cosmologicalscales in the Universe, from neutron stars to superclusters of galaxies, up to,asymptotically, the observed radius of the Universe. This result is obtained byintroducing a recursive scheme of alternating hierachical mechanisms ofthree-dimensional and two-dimensional close packings of gravitationallyinteracting objects. The iterative scheme yields a rapidly converging geometricsequence, which can be described as a hierarchical clustering of aggregates,having the observed radius of the Universe as its fixed point.

  13. Hierarchical and Non-Hierarchical Linear and Non-Linear Clustering Methods to “Shakespeare Authorship Question”

    Directory of Open Access Journals (Sweden)

    Refat Aljumily

    2015-09-01

    Full Text Available A few literary scholars have long claimed that Shakespeare did not write some of his best plays (history plays and tragedies and proposed at one time or another various suspect authorship candidates. Most modern-day scholars of Shakespeare have rejected this claim, arguing that strong evidence that Shakespeare wrote the plays and poems being his name appears on them as the author. This has caused and led to an ongoing scholarly academic debate for quite some long time. Stylometry is a fast-growing field often used to attribute authorship to anonymous or disputed texts. Stylometric attempts to resolve this literary puzzle have raised interesting questions over the past few years. The following paper contributes to “the Shakespeare authorship question” by using a mathematically-based methodology to examine the hypothesis that Shakespeare wrote all the disputed plays traditionally attributed to him. More specifically, the mathematically based methodology used here is based on Mean Proximity, as a linear hierarchical clustering method, and on Principal Components Analysis, as a non-hierarchical linear clustering method. It is also based, for the first time in the domain, on Self-Organizing Map U-Matrix and Voronoi Map, as non-linear clustering methods to cover the possibility that our data contains significant non-linearities. Vector Space Model (VSM is used to convert texts into vectors in a high dimensional space. The aim of which is to compare the degrees of similarity within and between limited samples of text (the disputed plays. The various works and plays assumed to have been written by Shakespeare and possible authors notably, Sir Francis Bacon, Christopher Marlowe, John Fletcher, and Thomas Kyd, where “similarity” is defined in terms of correlation/distance coefficient measure based on the frequency of usage profiles of function words, word bi-grams, and character triple-grams. The claim that Shakespeare authored all the disputed

  14. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2015-07-01

    Full Text Available In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4 where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution

  15. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2015-11-01

    Full Text Available In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4 where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the

  16. Validation of hierarchical cluster analysis for identification of bacterial species using 42 bacterial isolates

    Science.gov (United States)

    Ghebremedhin, Meron; Yesupriya, Shubha; Luka, Janos; Crane, Nicole J.

    2015-03-01

    Recent studies have demonstrated the potential advantages of the use of Raman spectroscopy in the biomedical field due to its rapidity and noninvasive nature. In this study, Raman spectroscopy is applied as a method for differentiating between bacteria isolates for Gram status and Genus species. We created models for identifying 28 bacterial isolates using spectra collected with a 785 nm laser excitation Raman spectroscopic system. In order to investigate the groupings of these samples, partial least squares discriminant analysis (PLSDA) and hierarchical cluster analysis (HCA) was implemented. In addition, cluster analyses of the isolates were performed using various data types consisting of, biochemical tests, gene sequence alignment, high resolution melt (HRM) analysis and antimicrobial susceptibility tests of minimum inhibitory concentration (MIC) and degree of antimicrobial resistance (SIR). In order to evaluate the ability of these models to correctly classify bacterial isolates using solely Raman spectroscopic data, a set of 14 validation samples were tested using the PLSDA models and consequently the HCA models. External cluster evaluation criteria of purity and Rand index were calculated at different taxonomic levels to compare the performance of clustering using Raman spectra as well as the other datasets. Results showed that Raman spectra performed comparably, and in some cases better than, the other data types with Rand index and purity values up to 0.933 and 0.947, respectively. This study clearly demonstrates that the discrimination of bacterial species using Raman spectroscopic data and hierarchical cluster analysis is possible and has the potential to be a powerful point-of-care tool in clinical settings.

  17. Prioritizing the risk of plant pests by clustering methods; self-organising maps, k-means and hierarchical clustering

    Directory of Open Access Journals (Sweden)

    Susan Worner

    2013-09-01

    Full Text Available For greater preparedness, pest risk assessors are required to prioritise long lists of pest species with potential to establish and cause significant impact in an endangered area. Such prioritization is often qualitative, subjective, and sometimes biased, relying mostly on expert and stakeholder consultation. In recent years, cluster based analyses have been used to investigate regional pest species assemblages or pest profiles to indicate the risk of new organism establishment. Such an approach is based on the premise that the co-occurrence of well-known global invasive pest species in a region is not random, and that the pest species profile or assemblage integrates complex functional relationships that are difficult to tease apart. In other words, the assemblage can help identify and prioritise species that pose a threat in a target region. A computational intelligence method called a Kohonen self-organizing map (SOM, a type of artificial neural network, was the first clustering method applied to analyse assemblages of invasive pests. The SOM is a well known dimension reduction and visualization method especially useful for high dimensional data that more conventional clustering methods may not analyse suitably. Like all clustering algorithms, the SOM can give details of clusters that identify regions with similar pest assemblages, possible donor and recipient regions. More important, however SOM connection weights that result from the analysis can be used to rank the strength of association of each species within each regional assemblage. Species with high weights that are not already established in the target region are identified as high risk. However, the SOM analysis is only the first step in a process to assess risk to be used alongside or incorporated within other measures. Here we illustrate the application of SOM analyses in a range of contexts in invasive species risk assessment, and discuss other clustering methods such as k

  18. Hierarchical Regional Disparities and Potential Sector Identification Using Modified Agglomerative Clustering

    Science.gov (United States)

    Munandar, T. A.; Azhari; Mushdholifah, A.; Arsyad, L.

    2017-03-01

    Disparities in regional development methods are commonly identified using the Klassen Typology and Location Quotient. Both methods typically use the data on the gross regional domestic product (GRDP) sectors of a particular region. The Klassen approach can identify regional disparities by classifying the GRDP sector data into four classes, namely Quadrants I, II, III, and IV. Each quadrant indicates a certain level of regional disparities based on the GRDP sector value of the said region. Meanwhile, the Location Quotient (LQ) is usually used to identify potential sectors in a particular region so as to determine which sectors are potential and which ones are not potential. LQ classifies each sector into three classes namely, the basic sector, the non-basic sector with a competitive advantage, and the non-basic sector which can only meet its own necessities. Both Klassen Typology and LQ are unable to visualize the relationship of achievements in the development clearly of each region and sector. This research aimed to develop a new approach to the identification of disparities in regional development in the form of hierarchical clustering. The method of Hierarchical Agglomerative Clustering (HAC) was employed as the basis of the hierarchical clustering model for identifying disparities in regional development. Modifications were made to HAC using the Klassen Typology and LQ. Then, HAC which had been modified using the Klassen Typology was called MHACK while HAC which had been modified using LQ was called MACLoQ. Both algorithms can be used to identify regional disparities (MHACK) and potential sectors (MACLoQ), respectively, in the form of hierarchical clusters. Based on the MHACK in 31 regencies in Central Java Province, it is identified that 3 regencies (Demak, Jepara, and Magelang City) fall into the category of developed and rapidly-growing regions, while the other 28 regencies fall into the category of developed but depressed regions. Results of the MACLo

  19. The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies

    Science.gov (United States)

    Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Dale, D. A.; Fumagalli, M.; Grebel, E. K.; Johnson, K. E.; Kahre, L.; Kennicutt, R. C.; Messa, M.; Pellerin, A.; Ryon, J. E.; Smith, L. J.; Shabani, F.; Thilker, D.; Ubeda, L.

    2017-05-01

    We present a study of the hierarchical clustering of the young stellar clusters in six local (3-15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ˜40-60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.

  20. Hierarchical Agglomerative Clustering Schemes for Energy-Efficiency in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Taleb Tariq

    2017-06-01

    Full Text Available Extending the lifetime of wireless sensor networks (WSNs while delivering the expected level of service remains a hot research topic. Clustering has been identified in the literature as one of the primary means to save communication energy. In this paper, we argue that hierarchical agglomerative clustering (HAC provides a suitable foundation for designing highly energy efficient communication protocols for WSNs. To this end, we study a new mechanism for selecting cluster heads (CHs based both on the physical location of the sensors and their residual energy. Furthermore, we study different patterns of communications between the CHs and the base station depending on the possible transmission ranges and the ability of the sensors to act as traffic relays. Simulation results show that our proposed clustering and communication schemes outperform well-knows existing approaches by comfortable margins. In particular, networks lifetime is increased by more than 60% compared to LEACH and HEED, and by more than 30% compared to K-means clustering.

  1. Hierarchical Clustering Algorithm based on Attribute Dependency for Attention Deficit Hyperactive Disorder

    Directory of Open Access Journals (Sweden)

    J Anuradha

    2014-05-01

    Full Text Available Attention Deficit Hyperactive Disorder (ADHD is a disruptive neurobehavioral disorder characterized by abnormal behavioral patterns in attention, perusing activity, acting impulsively and combined types. It is predominant among school going children and it is tricky to differentiate between an active and an ADHD child. Misdiagnosis and undiagnosed cases are very common. Behavior patterns are identified by the mentors in the academic environment who lack skills in screening those kids. Hence an unsupervised learning algorithm can cluster the behavioral patterns of children at school for diagnosis of ADHD. In this paper, we propose a hierarchical clustering algorithm to partition the dataset based on attribute dependency (HCAD. HCAD forms clusters of data based on the high dependent attributes and their equivalence relation. It is capable of handling large volumes of data with reasonably faster clustering than most of the existing algorithms. It can work on both labeled and unlabelled data sets. Experimental results reveal that this algorithm has higher accuracy in comparison to other algorithms. HCAD achieves 97% of cluster purity in diagnosing ADHD. Empirical analysis of application of HCAD on different data sets from UCI repository is provided.

  2. Signatures of Hierarchical Clustering in Dark Matter Detection Experiments

    CERN Document Server

    Stiff, D; Frieman, Joshua A

    2001-01-01

    In the cold dark matter model of structure formation, galaxies are assembled hierarchically from mergers and the accretion of subclumps. This process is expected to leave residual substructure in the Galactic dark halo, including partially disrupted clumps and their associated tidal debris. We develop a model for such halo substructure and study its implications for dark matter (WIMP and axion) detection experiments. We combine the Press-Schechter model for the distribution of halo subclump masses with N-body simulations of the evolution and disruption of individual clumps as they orbit through the evolving Galaxy to derive the probability that the Earth is passing through a subclump or stream of a given density. Our results suggest that it is likely that the local complement of dark matter particles includes a 1-5% contribution from a single clump. The implications for dark matter detection experiments are significant, since the disrupted clump is composed of a `cold' flow of high-velocity particles. We desc...

  3. Hierarchical Control for Multiple DC-Microgrids Clusters

    DEFF Research Database (Denmark)

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

    2014-01-01

    DC microgrids (MGs) have gained research interest during the recent years because of many potential advantages as compared to the ac system. To ensure reliable operation of a low-voltage dc MG as well as its intelligent operation with the other DC MGs, a hierarchical control is proposed in this p......DC microgrids (MGs) have gained research interest during the recent years because of many potential advantages as compared to the ac system. To ensure reliable operation of a low-voltage dc MG as well as its intelligent operation with the other DC MGs, a hierarchical control is proposed...

  4. Hierarchical Cluster Analysis: Comparison of Three Linkage Measures and Application to Psychological Data

    Directory of Open Access Journals (Sweden)

    Odilia Yim

    2015-02-01

    Full Text Available Cluster analysis refers to a class of data reduction methods used for sorting cases, observations, or variables of a given dataset into homogeneous groups that differ from each other. The present paper focuses on hierarchical agglomerative cluster analysis, a statistical technique where groups are sequentially created by systematically merging similar clusters together, as dictated by the distance and linkage measures chosen by the researcher. Specific distance and linkage measures are reviewed, including a discussion of how these choices can influence the clustering process by comparing three common linkage measures (single linkage, complete linkage, average linkage. The tutorial guides researchers in performing a hierarchical cluster analysis using the SPSS statistical software. Through an example, we demonstrate how cluster analysis can be used to detect meaningful subgroups in a sample of bilinguals by examining various language variables.

  5. Hierarchical cluster analysis of progression patterns in open-angle glaucoma patients with medical treatment.

    Science.gov (United States)

    Bae, Hyoung Won; Rho, Seungsoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

    2014-04-29

    To classify medically treated open-angle glaucoma (OAG) by the pattern of progression using hierarchical cluster analysis, and to determine OAG progression characteristics by comparing clusters. Ninety-five eyes of 95 OAG patients who received medical treatment, and who had undergone visual field (VF) testing at least once per year for 5 or more years. OAG was classified into subgroups using hierarchical cluster analysis based on the following five variables: baseline mean deviation (MD), baseline visual field index (VFI), MD slope, VFI slope, and Glaucoma Progression Analysis (GPA) printout. After that, other parameters were compared between clusters. Two clusters were made after a hierarchical cluster analysis. Cluster 1 showed -4.06 ± 2.43 dB baseline MD, 92.58% ± 6.27% baseline VFI, -0.28 ± 0.38 dB per year MD slope, -0.52% ± 0.81% per year VFI slope, and all "no progression" cases in GPA printout, whereas cluster 2 showed -8.68 ± 3.81 baseline MD, 77.54 ± 12.98 baseline VFI, -0.72 ± 0.55 MD slope, -2.22 ± 1.89 VFI slope, and seven "possible" and four "likely" progression cases in GPA printout. There were no significant differences in age, sex, mean IOP, central corneal thickness, and axial length between clusters. However, cluster 2 included more high-tension glaucoma patients and used a greater number of antiglaucoma eye drops significantly compared with cluster 1. Hierarchical cluster analysis of progression patterns divided OAG into slow and fast progression groups, evidenced by assessing the parameters of glaucomatous progression in VF testing. In the fast progression group, the prevalence of high-tension glaucoma was greater and the number of antiglaucoma medications administered was increased versus the slow progression group. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

  6. Periorbital melasma: Hierarchical cluster analysis of clinical features in Asian patients.

    Science.gov (United States)

    Jung, Y S; Bae, J M; Kim, B J; Kang, J-S; Cho, S B

    2017-03-19

    Studies have shown melasma lesions to be distributed across the face in centrofacial, malar, and mandibular patterns. Meanwhile, however, melasma lesions of the periorbital area have yet to be thoroughly described. We analyzed normal and ultraviolet light-exposed photographs of patients with melasma. The periorbital melasma lesions were measured according to anatomical reference points and a hierarchical cluster analysis was performed. The periorbital melasma lesions showed clinical features of fine and homogenous melasma pigmentation, involving both the upper and lower eyelids that extended to other anatomical sites with a darker and coarser appearance. The hierarchical cluster analysis indicated that patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. Significant differences between cluster 1 and cluster 2 were found in lateral distance and inferolateral distance, but not in medial distance and superior distance. Comparing the two clusters, patients in cluster 2 were found to be significantly older and more commonly accompanied by melasma lesions of the temple and medial cheek. Our hierarchical cluster analysis of periorbital melasma lesions demonstrated that Asian patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. Analysis of genetic association in Listeria and Diabetes using Hierarchical Clustering and Silhouette Index

    Science.gov (United States)

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

    2016-04-01

    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, where significative groups of genes are defined based on some criteria. This task is usually performed by clustering algorithms, where the whole family of genes, or a subset of them, are clustered into meaningful groups based on their expression values in a set of experiment. In this work we used a methodology based on the Silhouette index as a measure of cluster quality for individual gene groups, and a combination of several variants of hierarchical clustering to generate the candidate groups, to obtain sets of co-expressed genes for two real data examples. We analyzed the quality of the best ranked groups, obtained by the algorithm, using an online bioinformatics tool that provides network information for the selected genes. Moreover, to verify the performance of the algorithm, considering the fact that it doesn’t find all possible subsets, we compared its results against a full search, to determine the amount of good co-regulated sets not detected.

  8. On the Formation of Cool, Non-Flowing Cores in Galaxy Clusters via Hierarchical Mergers

    CERN Document Server

    Burns, J O; Norman, M L; Bryan, G L

    2003-01-01

    We present a new model for the creation of cool cores in rich galaxy clusters within a LambdaCDM cosmological framework using the results from high spatial dynamic range, adaptive mesh hydro/N-body simulations. It is proposed that cores of cool gas first form in subclusters and these subclusters merge to create rich clusters with cool, central X-Ray excesses. The rich cool clusters do not possess ``cooling flows'' due to the presence of bulk velocities in the intracluster medium in excess of 1000 km/sec produced by on-going accretion of gas from supercluster filaments. This new model has several attractive features including the presence of substantial core substructure within the cool cores, and it predicts the appearance of cool bullets, cool fronts, and cool filaments all of which have been recently observed with X-Ray satellites. This hierarchical formation model is also consistent with the observation that cool cores in Abell clusters occur preferentially in dense supercluster environments. On the other ...

  9. The Evolution of Galaxy Clustering in Hierarchical Models

    OpenAIRE

    1999-01-01

    The main ingredients of recent semi-analytic models of galaxy formation are summarised. We present predictions for the galaxy clustering properties of a well specified LCDM model whose parameters are constrained by observed local galaxy properties. We present preliminary predictions for evolution of clustering that can be probed with deep pencil beam surveys.

  10. Clustering of galaxies in a hierarchical universe - II. Evolution to high redshift

    Science.gov (United States)

    Kauffmann, Guinevere; Colberg, Jörg M.; Diaferio, Antonaldo; White, Simon D. M.

    1999-08-01

    In hierarchical cosmologies the evolution of galaxy clustering depends both on cosmological quantities such as Omega, Lambda and P(k), which determine how collapsed structures - dark matter haloes - form and evolve, and on the physical processes - cooling, star formation, radiative and hydrodynamic feedback - which drive the formation of galaxies within these merging haloes. In this paper we combine dissipationless cosmological N-body simulations and semi-analytic models of galaxy formation in order to study how these two aspects interact. We focus on the differences in clustering predicted for galaxies of differing luminosity, colour, morphology and star formation rate, and on what these differences can teach us about the galaxy formation process. We show that a `dip' in the amplitude of galaxy correlations between z=0 and z=1 can be an important diagnostic. Such a dip occurs in low-density CDM models, because structure forms early, and dark matter haloes of mass ~10^12M_solar, containing galaxies with luminosities ~L_*, are unbiased tracers of the dark matter over this redshift range; their clustering amplitude then evolves similarly to that of the dark matter. At higher redshifts, bright galaxies become strongly biased and the clustering amplitude increases again. In high density models, structure forms late, and bias evolves much more rapidly. As a result, the clustering amplitude of L_* galaxies remains constant from z=0 to z=1. The strength of these effects is sensitive to sample selection. The dip becomes weaker for galaxies with lower star formation rates, redder colours, higher luminosities and earlier morphological types. We explain why this is the case, and how it is related to the variation with redshift of the abundance and environment of the observed galaxies. We also show that the relative peculiar velocities of galaxies are biased low in our models, but that this effect is never very strong. Studies of clustering evolution as a function of galaxy

  11. Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data

    Directory of Open Access Journals (Sweden)

    Reilly John J

    2005-06-01

    Full Text Available Abstract Background Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past, but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease (COPD undergoing pulmonary rehabilitation. Accelerometers were used to collect data for 10 different classes of activity. Features were extracted to capture essential properties of the data set and reduce the dimensionality of the problem at hand. Cluster measures were utilized to find natural groupings in the data set and then construct a hierarchy of the relationships between clusters to guide the process of merging clusters that are too similar to distinguish reliably. It provides a means to assess whether the benefits of merging for performance of a classifier outweigh the loss of resolution incurred through merging. Results Analysis of the COPD data set demonstrated that motor tasks related to ambulation can be reliably discriminated from tasks performed in a seated position with the legs in motion or stationary using two features derived from one accelerometer. Classifying motor tasks within the category of activities related to ambulation requires more advanced techniques. While in certain cases all the tasks could be accurately classified, in others merging clusters associated with different motor tasks was necessary. When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion Hierarchical

  12. Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data

    Science.gov (United States)

    Sherrill, Delsey M; Moy, Marilyn L; Reilly, John J; Bonato, Paolo

    2005-01-01

    Background Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past, but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease (COPD) undergoing pulmonary rehabilitation. Accelerometers were used to collect data for 10 different classes of activity. Features were extracted to capture essential properties of the data set and reduce the dimensionality of the problem at hand. Cluster measures were utilized to find natural groupings in the data set and then construct a hierarchy of the relationships between clusters to guide the process of merging clusters that are too similar to distinguish reliably. It provides a means to assess whether the benefits of merging for performance of a classifier outweigh the loss of resolution incurred through merging. Results Analysis of the COPD data set demonstrated that motor tasks related to ambulation can be reliably discriminated from tasks performed in a seated position with the legs in motion or stationary using two features derived from one accelerometer. Classifying motor tasks within the category of activities related to ambulation requires more advanced techniques. While in certain cases all the tasks could be accurately classified, in others merging clusters associated with different motor tasks was necessary. When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion Hierarchical clustering methods are relevant

  13. Kendall’s tau and agglomerative clustering for structure determination of hierarchical Archimedean copulas

    Directory of Open Access Journals (Sweden)

    Górecki J.

    2017-01-01

    Full Text Available Several successful approaches to structure determination of hierarchical Archimedean copulas (HACs proposed in the literature rely on agglomerative clustering and Kendall’s correlation coefficient. However, there has not been presented any theoretical proof justifying such approaches. This work fills this gap and introduces a theorem showing that, given the matrix of the pairwise Kendall correlation coefficients corresponding to a HAC, its structure can be recovered by an agglomerative clustering technique.

  14. 3D Nearest Neighbour Search Using a Clustered Hierarchical Tree Structure

    DEFF Research Database (Denmark)

    Suhaibah, A.; Uznir, U.; Antón Castro, Francesc/François

    2016-01-01

    , with the immense number of urban datasets, the retrieval and analysis of nearest neighbour information and their efficiency will become more complex and crucial. In this paper, we present a technique to retrieve nearest neighbour information in 3D space using a clustered hierarchical tree structure. Based on our...... findings, the proposed approach substantially showed an improvement of response time analysis compared to existing approaches of spatial access methods in databases. The query performance was tested using a dataset consisting of 500,000 point locations building and franchising unit. The results...... of the franchise unit will be located or is the franchise unit located is at the best level for visibility purposes. One of the common used analyses used for retrieving the surrounding information is Nearest Neighbour (NN) analysis. It uses a point location and identifies the surrounding neighbours. However...

  15. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    Science.gov (United States)

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  16. Non-Hierarchical Clustering as a method to analyse an open-ended ...

    African Journals Online (AJOL)

    Apple

    tests, provide instructors with tools to probe students' conceptual knowledge of various fields of science and ... quantitative non-hierarchical clustering analysis method known as k-means (Everitt, Landau, Leese & Stahl, ...... undergraduate engineering students in creating ... mathematics-formal reasoning and the contextual.

  17. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    Science.gov (United States)

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  18. Analysis of genomic signatures in prokaryotes using multinomial regression and hierarchical clustering

    DEFF Research Database (Denmark)

    Ussery, David; Bohlin, Jon; Skjerve, Eystein

    2009-01-01

    Recently there has been an explosion in the availability of bacterial genomic sequences, making possible now an analysis of genomic signatures across more than 800 hundred different bacterial chromosomes, from a wide variety of environments. Using genomic signatures, we pair-wise compared 867...... different genomic DNA sequences, taken from chromosomes and plasmids more than 100,000 base-pairs in length. Hierarchical clustering was performed on the outcome of the comparisons before a multinomial regression model was fitted. The regression model included the cluster groups as the response variable...... AT content. Small improvements to the regression model, although significant, were also obtained by factors such as sequence size, habitat, growth temperature, selective pressure measured as oligonucleotide usage variance, and oxygen requirement.The statistics obtained using hierarchical clustering...

  19. Query Results Clustering by Extending SPARQL with CLUSTER BY

    Science.gov (United States)

    Ławrynowicz, Agnieszka

    The task of dynamic clustering of the search results proved to be useful in the Web context, where the user often does not know the granularity of the search results in advance. The goal of this paper is to provide a declarative way for invoking dynamic clustering of the results of queries submitted over Semantic Web data. To achieve this goal the paper proposes an approach that extends SPARQL by clustering abilities. The approach introduces a new statement, CLUSTER BY, into the SPARQL grammar and proposes semantics for such extension.

  20. Clustering dynamic textures with the hierarchical em algorithm for modeling video.

    Science.gov (United States)

    Mumtaz, Adeel; Coviello, Emanuele; Lanckriet, Gert R G; Chan, Antoni B

    2013-07-01

    Dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model has been applied to a wide variety of computer vision problems, such as motion segmentation, motion classification, and video registration. In this paper, we derive a new algorithm for clustering DT models that is based on the hierarchical EM algorithm. The proposed clustering algorithm is capable of both clustering DTs and learning novel DT cluster centers that are representative of the cluster members in a manner that is consistent with the underlying generative probabilistic model of the DT. We also derive an efficient recursive algorithm for sensitivity analysis of the discrete-time Kalman smoothing filter, which is used as the basis for computing expectations in the E-step of the HEM algorithm. Finally, we demonstrate the efficacy of the clustering algorithm on several applications in motion analysis, including hierarchical motion clustering, semantic motion annotation, and learning bag-of-systems (BoS) codebooks for dynamic texture recognition.

  1. Improving the Decision Value of Hierarchical Text Clustering Using Term Overlap Detection

    Directory of Open Access Journals (Sweden)

    Nilupulee Nathawitharana

    2015-09-01

    Full Text Available Humans are used to expressing themselves with written language and language provides a medium with which we can describe our experiences in detail incorporating individuality. Even though documents provide a rich source of information, it becomes very difficult to identify, extract, summarize and search when vast amounts of documents are collected especially over time. Document clustering is a technique that has been widely used to group documents based on similarity of content represented by the words used. Once key groups are identified further drill down into sub-groupings is facilitated by the use of hierarchical clustering. Clustering and hierarchical clustering are very useful when applied to numerical and categorical data and cluster accuracy and purity measures exist to evaluate the outcomes of a clustering exercise. Although the same measures have been applied to text clustering, text clusters are based on words or terms which can be repeated across documents associated with different topics. Therefore text data cannot be considered as a direct ‘coding’ of a particular experience or situation in contrast to numerical and categorical data and term overlap is a very common characteristic in text clustering. In this paper we propose a new technique and methodology for term overlap capture from text documents, highlighting the different situations such overlap could signify and discuss why such understanding is important for obtaining value from text clustering. Experiments were conducted using a widely used text document collection where the proposed methodology allowed exploring the term diversity for a given document collection and obtain clusters with minimum term overlap.

  2. Multilevel hierarchical kernel spectral clustering for real-life large scale complex networks.

    Directory of Open Access Journals (Sweden)

    Raghvendra Mall

    Full Text Available Kernel spectral clustering corresponds to a weighted kernel principal component analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a representative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is determined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community detection techniques like the Louvain, OSLOM and Infomap methods. We show that a major advantage of our proposed approach is the ability to locate good quality clusters at both the finer and coarser levels of hierarchy using internal cluster quality metrics on 7 real-life networks.

  3. HCsnip: An R Package for Semi-supervised Snipping of the Hierarchical Clustering Tree.

    Science.gov (United States)

    Obulkasim, Askar; van de Wiel, Mark A

    2015-01-01

    Hierarchical clustering (HC) is one of the most frequently used methods in computational biology in the analysis of high-dimensional genomics data. Given a data set, HC outputs a binary tree leaves of which are the data points and internal nodes represent clusters of various sizes. Normally, a fixed-height cut on the HC tree is chosen, and each contiguous branch of data points below that height is considered as a separate cluster. However, the fixed-height branch cut may not be ideal in situations where one expects a complicated tree structure with nested clusters. Furthermore, due to lack of utilization of related background information in selecting the cutoff, induced clusters are often difficult to interpret. This paper describes a novel procedure that aims to automatically extract meaningful clusters from the HC tree in a semi-supervised way. The procedure is implemented in the R package HCsnip available from Bioconductor. Rather than cutting the HC tree at a fixed-height, HCsnip probes the various way of snipping, possibly at variable heights, to tease out hidden clusters ensconced deep down in the tree. The cluster extraction process utilizes, along with the data set from which the HC tree is derived, commonly available background information. Consequently, the extracted clusters are highly reproducible and robust against various sources of variations that "haunted" high-dimensional genomics data. Since the clustering process is guided by the background information, clusters are easy to interpret. Unlike existing packages, no constraint is placed on the data type on which clustering is desired. Particularly, the package accepts patient follow-up data for guiding the cluster extraction process. To our knowledge, HCsnip is the first package that is able to decomposes the HC tree into clusters with piecewise snipping under the guidance of patient time-to-event information. Our implementation of the semi-supervised HC tree snipping framework is generic, and can

  4. The evolution of Brightest Cluster Galaxies in a hierarchical universe

    CERN Document Server

    Tonini, Chiara; Croton, Darren; Maraston, Claudia; Thomas, Daniel

    2012-01-01

    We investigate the evolution of Brightest Cluster Galaxies (BCGs) from redshift z~1.6 to z~0. We use the semi-analytic model of Croton et al. (2006) with a new spectro-photometric model based on the Maraston (2005) stellar populations and a new recipe for the dust extinction. We compare the model predictions of the K-band luminosity evolution and the J-K, V-I and I-K colour evolution with a series of datasets, including Collins et al. (Nature, 2009) who argued that semi-analytic models based on the Millennium simulation cannot reproduce the red colours and high luminosity of BCGs at z>1. We show instead that the model is well in range of the observed luminosity and correctly reproduces the colour evolution of BCGs in the whole redshift range up to z~1.6. We argue that the success of the semi-analytic model is in large part due to the implementation of a more sophisticated spectro-photometric model. An analysis of the model BCGs shows an increase in mass by a factor ~2 since z~1, and star formation activity do...

  5. Bayesian latent variable models for hierarchical clustered count outcomes with repeated measures in microbiome studies.

    Science.gov (United States)

    Xu, Lizhen; Paterson, Andrew D; Xu, Wei

    2017-04-01

    Motivated by the multivariate nature of microbiome data with hierarchical taxonomic clusters, counts that are often skewed and zero inflated, and repeated measures, we propose a Bayesian latent variable methodology to jointly model multiple operational taxonomic units within a single taxonomic cluster. This novel method can incorporate both negative binomial and zero-inflated negative binomial responses, and can account for serial and familial correlations. We develop a Markov chain Monte Carlo algorithm that is built on a data augmentation scheme using Pólya-Gamma random variables. Hierarchical centering and parameter expansion techniques are also used to improve the convergence of the Markov chain. We evaluate the performance of our proposed method through extensive simulations. We also apply our method to a human microbiome study.

  6. A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Xiaowei Li

    2017-01-01

    Full Text Available A large number of studies demonstrated that major depressive disorder (MDD is characterized by the alterations in brain functional connections which is also identifiable during the brain’s “resting-state.” But, in the present study, the approach of constructing functional connectivity is often biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Therefore, minimum spanning tree (MST analysis and the hierarchical clustering were first used for the depression disease in this study. Resting-state electroencephalogram (EEG sources were assessed from 15 healthy and 23 major depressive subjects. Then the coherence, MST, and the hierarchical clustering were obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients was significantly higher than that of the healthy controls especially in the left temporal region. The MST results indicated the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lost clustering in frontal regions. Our findings suggested that there was a stronger brain interaction in the MDD group and a left-right functional imbalance in the frontal regions for MDD controls.

  7. An Exactly Soluble Hierarchical Clustering Model Inverse Cascades, Self-Similarity, and Scaling

    CERN Document Server

    Gabrielov, A; Turcotte, D L

    1999-01-01

    We show how clustering as a general hierarchical dynamical process proceeds via a sequence of inverse cascades to produce self-similar scaling, as an intermediate asymptotic, which then truncates at the largest spatial scales. We show how this model can provide a general explanation for the behavior of several models that has been described as ``self-organized critical,'' including forest-fire, sandpile, and slider-block models.

  8. Semantic Clustering of Search Engine Results.

    Science.gov (United States)

    Soliman, Sara Saad; El-Sayed, Maged F; Hassan, Yasser F

    2015-01-01

    This paper presents a novel approach for search engine results clustering that relies on the semantics of the retrieved documents rather than the terms in those documents. The proposed approach takes into consideration both lexical and semantics similarities among documents and applies activation spreading technique in order to generate semantically meaningful clusters. This approach allows documents that are semantically similar to be clustered together rather than clustering documents based on similar terms. A prototype is implemented and several experiments are conducted to test the prospered solution. The result of the experiment confirmed that the proposed solution achieves remarkable results in terms of precision.

  9. Semantic Clustering of Search Engine Results

    Directory of Open Access Journals (Sweden)

    Sara Saad Soliman

    2015-01-01

    Full Text Available This paper presents a novel approach for search engine results clustering that relies on the semantics of the retrieved documents rather than the terms in those documents. The proposed approach takes into consideration both lexical and semantics similarities among documents and applies activation spreading technique in order to generate semantically meaningful clusters. This approach allows documents that are semantically similar to be clustered together rather than clustering documents based on similar terms. A prototype is implemented and several experiments are conducted to test the prospered solution. The result of the experiment confirmed that the proposed solution achieves remarkable results in terms of precision.

  10. Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.

    Science.gov (United States)

    Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G

    2014-09-30

    This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Permutation Tests of Hierarchical Cluster Analyses of Carrion Communities and Their Potential Use in Forensic Entomology.

    Science.gov (United States)

    van der Ham, Joris L

    2016-05-19

    Forensic entomologists can use carrion communities' ecological succession data to estimate the postmortem interval (PMI). Permutation tests of hierarchical cluster analyses of these data provide a conceptual method to estimate part of the PMI, the post-colonization interval (post-CI). This multivariate approach produces a baseline of statistically distinct clusters that reflect changes in the carrion community composition during the decomposition process. Carrion community samples of unknown post-CIs are compared with these baseline clusters to estimate the post-CI. In this short communication, I use data from previously published studies to demonstrate the conceptual feasibility of this multivariate approach. Analyses of these data produce series of significantly distinct clusters, which represent carrion communities during 1- to 20-day periods of the decomposition process. For 33 carrion community samples, collected over an 11-day period, this approach correctly estimated the post-CI within an average range of 3.1 days.

  12. To Aggregate or Not and Potentially Better Questions for Clustered Data: The Need for Hierarchical Linear Modeling in CTE Research

    Science.gov (United States)

    Nimon, Kim

    2012-01-01

    Using state achievement data that are openly accessible, this paper demonstrates the application of hierarchical linear modeling within the context of career technical education research. Three prominent approaches to analyzing clustered data (i.e., modeling aggregated data, modeling disaggregated data, modeling hierarchical data) are discussed…

  13. [Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses].

    Science.gov (United States)

    Ning, P; Guo, Y F; Sun, T Y; Zhang, H S; Chai, D; Li, X M

    2016-09-01

    To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis. A population sample of adult patients in Donghuamen community, Dongcheng district and Qinghe community, Haidian district, Beijing from April 2012 to January 2015, who had wheeze within the last 12 months, underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, total serum IgE levels, blood eosinophil level and a peak flow diary. Nine variables were chosen as evaluating parameters, including pre-salbutamol forced expired volume in one second(FEV1)/forced vital capacity(FVC) ratio, pre-salbutamol FEV1, percentage of post-salbutamol change in FEV1, residual capacity, diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level, peak expiratory flow(PEF) variability, serum IgE level, cumulative tobacco cigarette consumption (pack-years) and respiratory symptoms (cough and expectoration). Subjects' different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified. (1) Four clusters were identified by hierarchical cluster analysis. Cluster 1 was chronic bronchitis in smokers with normal pulmonary function. Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease (COPD) patients with mild airflow limitation. Cluster 3 included COPD patients with heavy smoking, poor quality of life and severe airflow limitation. Cluster 4 recognized atopic patients with mild airflow limitation, elevated serum IgE and clinical features of asthma. Significant differences were revealed regarding pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, maximal mid-expiratory flow curve(MMEF)% pred, carbon monoxide diffusing capacity per liter of alveolar(DLCO)/(VA)% pred, residual volume(RV)% pred, total serum IgE level, smoking history (pack-years), St.George's respiratory questionnaire

  14. Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra

    Science.gov (United States)

    Unglert, K.; Radić, V.; Jellinek, A. M.

    2016-06-01

    Variations in the spectral content of volcano seismicity related to changes in volcanic activity are commonly identified manually in spectrograms. However, long time series of monitoring data at volcano observatories require tools to facilitate automated and rapid processing. Techniques such as self-organizing maps (SOM) and principal component analysis (PCA) can help to quickly and automatically identify important patterns related to impending eruptions. For the first time, we evaluate the performance of SOM and PCA on synthetic volcano seismic spectra constructed from observations during two well-studied eruptions at Klauea Volcano, Hawai'i, that include features observed in many volcanic settings. In particular, our objective is to test which of the techniques can best retrieve a set of three spectral patterns that we used to compose a synthetic spectrogram. We find that, without a priori knowledge of the given set of patterns, neither SOM nor PCA can directly recover the spectra. We thus test hierarchical clustering, a commonly used method, to investigate whether clustering in the space of the principal components and on the SOM, respectively, can retrieve the known patterns. Our clustering method applied to the SOM fails to detect the correct number and shape of the known input spectra. In contrast, clustering of the data reconstructed by the first three PCA modes reproduces these patterns and their occurrence in time more consistently. This result suggests that PCA in combination with hierarchical clustering is a powerful practical tool for automated identification of characteristic patterns in volcano seismic spectra. Our results indicate that, in contrast to PCA, common clustering algorithms may not be ideal to group patterns on the SOM and that it is crucial to evaluate the performance of these tools on a control dataset prior to their application to real data.

  15. Hierarchical black hole triples in young star clusters: impact of Kozai-Lidov resonance on mergers

    Science.gov (United States)

    Kimpson, Thomas O.; Spera, Mario; Mapelli, Michela; Ziosi, Brunetto M.

    2016-12-01

    Mergers of compact-object binaries are one of the most powerful sources of gravitational waves (GWs) in the frequency range of second-generation ground-based GW detectors (advanced LIGO and Virgo). Dynamical simulations of young dense star clusters (SCs) indicate that ˜27 per cent of all double compact-object binaries are members of hierarchical triple systems (HTs). In this paper, we consider 570 HTs composed of three compact objects (black holes or neutron stars) that formed dynamically in N-body simulations of young dense SCs. We simulate them for a Hubble time with a new code based on the Mikkola's algorithmic regularization scheme, including the 2.5 post-Newtonian term. We find that ˜88 per cent of the simulated systems develop Kozai-Lidov (KL) oscillations. KL resonance triggers the merger of the inner binary in three systems (corresponding to 0.5 per cent of the simulated HTs), by increasing the eccentricity of the inner binary. Accounting for KL oscillations leads to an increase of the total expected merger rate by ≈50 per cent. All binaries that merge because of KL oscillations were formed by dynamical exchanges (i.e. none is a primordial binary) and have chirp mass >20 M⊙. This result might be crucial to interpret the formation channel of the first recently detected GW events.

  16. MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and -Norm Minimization

    Directory of Open Access Journals (Sweden)

    Kellermann Walter

    2007-01-01

    Full Text Available We address the problem of underdetermined BSS. While most previous approaches are designed for instantaneous mixtures, we propose a time-frequency-domain algorithm for convolutive mixtures. We adopt a two-step method based on a general maximum a posteriori (MAP approach. In the first step, we estimate the mixing matrix based on hierarchical clustering, assuming that the source signals are sufficiently sparse. The algorithm works directly on the complex-valued data in the time-frequency domain and shows better convergence than algorithms based on self-organizing maps. The assumption of Laplacian priors for the source signals in the second step leads to an algorithm for estimating the source signals. It involves the -norm minimization of complex numbers because of the use of the time-frequency-domain approach. We compare a combinatorial approach initially designed for real numbers with a second-order cone programming (SOCP approach designed for complex numbers. We found that although the former approach is not theoretically justified for complex numbers, its results are comparable to, or even better than, the SOCP solution. The advantage is a lower computational cost for problems with low input/output dimensions.

  17. Hierarchical clustering

    Directory of Open Access Journals (Sweden)

    L. Infante

    2002-01-01

    Full Text Available En esta contribuci on presento resultados recientes sobre las propiedades de acumulaci on de galaxias, grupos, c umulos y superc umulos de bajo redshift (z 1. Presento, a su vez, lo esperado y lo medido con respecto al grado de evoluci on de la acumulaci on de galaxias. Hemos usado el cat alogo fotom etrico de galaxias extra do de las primeras im agenes del \\Sloan Digital Sky Survey", para estudiar las propiedades de acumulaci on de peque~nas estructuras de galaxias, pares, tr os, cuartetos, quintetos, etc. Un an alisis de la funci on de correlaci on de dos puntos, en un area de 250 grados cuadrados del cielo, muestra que estos objetos, al parecer, est an mucho m as acumulados que galaxias individuales.

  18. Hierarchical Clustering of Large Databases and Classification of Antibiotics at High Noise Levels

    Directory of Open Access Journals (Sweden)

    Alexander V. Yarkov

    2008-12-01

    Full Text Available A new algorithm for divisive hierarchical clustering of chemical compounds based on 2D structural fragments is suggested. The algorithm is deterministic, and given a random ordering of the input, will always give the same clustering and can process a database up to 2 million records on a standard PC. The algorithm was used for classification of 1,183 antibiotics mixed with 999,994 random chemical structures. Similarity threshold, at which best separation of active and non active compounds took place, was estimated as 0.6. 85.7% of the antibiotics were successfully classified at this threshold with 0.4% of inaccurate compounds. A .sdf file was created with the probe molecules for clustering of external databases.

  19. A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony

    Directory of Open Access Journals (Sweden)

    Farshad Faezy Razi

    2014-06-01

    Full Text Available Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers’ Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers.

  20. Using Dynamic Quantum Clustering to Analyze Hierarchically Heterogeneous Samples on the Nanoscale

    Energy Technology Data Exchange (ETDEWEB)

    Hume, Allison; /Princeton U. /SLAC

    2012-09-07

    Dynamic Quantum Clustering (DQC) is an unsupervised, high visual data mining technique. DQC was tested as an analysis method for X-ray Absorption Near Edge Structure (XANES) data from the Transmission X-ray Microscopy (TXM) group. The TXM group images hierarchically heterogeneous materials with nanoscale resolution and large field of view. XANES data consists of energy spectra for each pixel of an image. It was determined that DQC successfully identifies structure in data of this type without prior knowledge of the components in the sample. Clusters and sub-clusters clearly reflected features of the spectra that identified chemical component, chemical environment, and density in the image. DQC can also be used in conjunction with the established data analysis technique, which does require knowledge of components present.

  1. A hierarchical cluster analysis of normal-tension glaucoma using spectral-domain optical coherence tomography parameters.

    Science.gov (United States)

    Bae, Hyoung Won; Ji, Yongwoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

    2015-01-01

    Normal-tension glaucoma (NTG) is a heterogenous disease, and there is still controversy about subclassifications of this disorder. On the basis of spectral-domain optical coherence tomography (SD-OCT), we subdivided NTG with hierarchical cluster analysis using optic nerve head (ONH) parameters and retinal nerve fiber layer (RNFL) thicknesses. A total of 200 eyes of 200 NTG patients between March 2011 and June 2012 underwent SD-OCT scans to measure ONH parameters and RNFL thicknesses. We classified NTG into homogenous subgroups based on these variables using a hierarchical cluster analysis, and compared clusters to evaluate diverse NTG characteristics. Three clusters were found after hierarchical cluster analysis. Cluster 1 (62 eyes) had the thickest RNFL and widest rim area, and showed early glaucoma features. Cluster 2 (60 eyes) was characterized by the largest cup/disc ratio and cup volume, and showed advanced glaucomatous damage. Cluster 3 (78 eyes) had small disc areas in SD-OCT and were comprised of patients with significantly younger age, longer axial length, and greater myopia than the other 2 groups. A hierarchical cluster analysis of SD-OCT scans divided NTG patients into 3 groups based upon ONH parameters and RNFL thicknesses. It is anticipated that the small disc area group comprised of younger and more myopic patients may show unique features unlike the other 2 groups.

  2. Intensity-based hierarchical clustering in CT-scans: application to interactive segmentation in cardiology

    Science.gov (United States)

    Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

    2011-03-01

    The segmentation of anatomical structures in Computed Tomography Angiography (CTA) is a pre-operative task useful in image guided surgery. Even though very robust and precise methods have been developed to help achieving a reliable segmentation (level sets, active contours, etc), it remains very time consuming both in terms of manual interactions and in terms of computation time. The goal of this study is to present a fast method to find coarse anatomical structures in CTA with few parameters, based on hierarchical clustering. The algorithm is organized as follows: first, a fast non-parametric histogram clustering method is proposed to compute a piecewise constant mask. A second step then indexes all the space-connected regions in the piecewise constant mask. Finally, a hierarchical clustering is achieved to build a graph representing the connections between the various regions in the piecewise constant mask. This step builds up a structural knowledge about the image. Several interactive features for segmentation are presented, for instance association or disassociation of anatomical structures. A comparison with the Mean-Shift algorithm is presented.

  3. Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition.

    Science.gov (United States)

    Liu, An-An; Su, Yu-Ting; Nie, Wei-Zhi; Kankanhalli, Mohan

    2017-01-01

    This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition. Specifically, we formulate the objective function into the group-wise least square loss regularized by low rank and sparsity with respect to two latent variables, model parameters and grouping information, for joint optimization. To handle this non-convex optimization, we decompose it into two sub-tasks, multi-task learning and task relatedness discovery. First, we convert this non-convex objective function into the convex formulation by fixing the latent grouping information. This new objective function focuses on multi-task learning by strengthening the shared-action relationship and action-specific feature learning. Second, we leverage the learned model parameters for the task relatedness measure and clustering. In this way, HC-MTL can attain both optimal action models and group discovery by alternating iteratively. The proposed method is validated on three kinds of challenging datasets, including six realistic action datasets (Hollywood2, YouTube, UCF Sports, UCF50, HMDB51 & UCF101), two constrained datasets (KTH & TJU), and two multi-view datasets (MV-TJU & IXMAS). The extensive experimental results show that: 1) HC-MTL can produce competing performances to the state of the arts for action recognition and grouping; 2) HC-MTL can overcome the difficulty in heuristic action grouping simply based on human knowledge; 3) HC-MTL can avoid the possible inconsistency between the subjective action grouping depending on human knowledge and objective action grouping based on the feature subspace distributions of multiple actions. Comparison with the popular clustered multi-task learning further reveals that the discovered latent relatedness by HC-MTL aids inducing the group-wise multi-task learning and boosts the performance. To the best of our knowledge, ours is the first work that breaks the assumption that all actions are either

  4. Hierarchical clustering of ryanodine receptors enables emergence of a calcium clock in sinoatrial node cells.

    Science.gov (United States)

    Stern, Michael D; Maltseva, Larissa A; Juhaszova, Magdalena; Sollott, Steven J; Lakatta, Edward G; Maltsev, Victor A

    2014-05-01

    The sinoatrial node, whose cells (sinoatrial node cells [SANCs]) generate rhythmic action potentials, is the primary pacemaker of the heart. During diastole, calcium released from the sarcoplasmic reticulum (SR) via ryanodine receptors (RyRs) interacts with membrane currents to control the rate of the heartbeat. This "calcium clock" takes the form of stochastic, partially periodic, localized calcium release (LCR) events that propagate, wave-like, for limited distances. The detailed mechanisms controlling the calcium clock are not understood. We constructed a computational model of SANCs, including three-dimensional diffusion and buffering of calcium in the cytosol and SR; explicit, stochastic gating of individual RyRs and L-type calcium channels; and a full complement of voltage- and calcium-dependent membrane currents. We did not include an anatomical submembrane space or inactivation of RyRs, the two heuristic components that have been used in prior models but are not observed experimentally. When RyRs were distributed in discrete clusters separated by >1 µm, only isolated sparks were produced in this model and LCR events did not form. However, immunofluorescent staining of SANCs for RyR revealed the presence of bridging RyR groups between large clusters, forming an irregular network. Incorporation of this architecture into the model led to the generation of propagating LCR events. Partial periodicity emerged from the interaction of LCR events, as observed experimentally. This calcium clock becomes entrained with membrane currents to accelerate the beating rate, which therefore was controlled by the activity of the SERCA pump, RyR sensitivity, and L-type current amplitude, all of which are targets of β-adrenergic-mediated phosphorylation. Unexpectedly, simulations revealed the existence of a pathological mode at high RyR sensitivity to calcium, in which the calcium clock loses synchronization with the membrane, resulting in a paradoxical decrease in beating

  5. Diversity of Xiphinema americanum-group Species and Hierarchical Cluster Analysis of Morphometrics.

    Science.gov (United States)

    Lamberti, F; Ciancio, A

    1993-09-01

    Of the 39 species composing the Xiphinema americanum group, 14 were described originally from North America and two others have been reported from this region. Many species are very similar morphologically and can be distinguished only by a difficult comparison of various combinations of some morphometric characters. Study of morphometrics of 49 populations, including the type populations of the 39 species attributed to this group, by principal component analysis and hierarchical cluster analysis placed the populations into five subgroups, proposed here as the X. brevicolle subgroup (seven species), the X. americanum subgroup (17 species), the X. taylori subgroup (two species), the X. pachtaicum subgroup (eight species), and the X. lambertii subgroup (five species).

  6. CLUSTAG & WCLUSTAG: Hierarchical Clustering Algorithms for Efficient Tag-SNP Selection

    Science.gov (United States)

    Ao, Sio-Iong

    More than 6 million single nucleotide polymorphisms (SNPs) in the human genome have been genotyped by the HapMap project. Although only a pro portion of these SNPs are functional, all can be considered as candidate markers for indirect association studies to detect disease-related genetic variants. The complete screening of a gene or a chromosomal region is nevertheless an expensive undertak ing for association studies. A key strategy for improving the efficiency of association studies is to select a subset of informative SNPs, called tag SNPs, for analysis. In the chapter, hierarchical clustering algorithms have been proposed for efficient tag SNP selection.

  7. Asteroid family identification using the Hierarchical Clustering Method and WISE/NEOWISE physical properties

    CERN Document Server

    Masiero, Joseph R; Bauer, J M; Grav, T; Nugent, C R; Stevenson, R

    2013-01-01

    Using albedos from WISE/NEOWISE to separate distinct albedo groups within the Main Belt asteroids, we apply the Hierarchical Clustering Method to these subpopulations and identify dynamically associated clusters of asteroids. While this survey is limited to the ~35% of known Main Belt asteroids that were detected by NEOWISE, we present the families linked from these objects as higher confidence associations than can be obtained from dynamical linking alone. We find that over one-third of the observed population of the Main Belt is represented in the high-confidence cores of dynamical families. The albedo distribution of family members differs significantly from the albedo distribution of background objects in the same region of the Main Belt, however interpretation of this effect is complicated by the incomplete identification of lower-confidence family members. In total we link 38,298 asteroids into 76 distinct families. This work represents a critical step necessary to debias the albedo and size distributio...

  8. Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

    Science.gov (United States)

    Fernández-Arjona, María del Mar; Grondona, Jesús M.; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D.

    2017-01-01

    It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable

  9. Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

    Directory of Open Access Journals (Sweden)

    Guo Junqiao

    2008-09-01

    Full Text Available Abstract Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations.

  10. 3D NEAREST NEIGHBOUR SEARCH USING A CLUSTERED HIERARCHICAL TREE STRUCTURE

    Directory of Open Access Journals (Sweden)

    A. Suhaibah

    2016-06-01

    Full Text Available Locating and analysing the location of new stores or outlets is one of the common issues facing retailers and franchisers. This is due to assure that new opening stores are at their strategic location to attract the highest possible number of customers. Spatial information is used to manage, maintain and analyse these store locations. However, since the business of franchising and chain stores in urban areas runs within high rise multi-level buildings, a three-dimensional (3D method is prominently required in order to locate and identify the surrounding information such as at which level of the franchise unit will be located or is the franchise unit located is at the best level for visibility purposes. One of the common used analyses used for retrieving the surrounding information is Nearest Neighbour (NN analysis. It uses a point location and identifies the surrounding neighbours. However, with the immense number of urban datasets, the retrieval and analysis of nearest neighbour information and their efficiency will become more complex and crucial. In this paper, we present a technique to retrieve nearest neighbour information in 3D space using a clustered hierarchical tree structure. Based on our findings, the proposed approach substantially showed an improvement of response time analysis compared to existing approaches of spatial access methods in databases. The query performance was tested using a dataset consisting of 500,000 point locations building and franchising unit. The results are presented in this paper. Another advantage of this structure is that it also offers a minimal overlap and coverage among nodes which can reduce repetitive data entry.

  11. Recent results on the hierarchical triple system HD 150136

    Science.gov (United States)

    Gosset, E.; Berger, J. P.; Absil, O.; Le Bouquin, J. B.; Sana, H.; Mahy, L.; De Becker, M.

    2013-06-01

    HD 150136 is a hierarchical triple system, non-thermal radio emitter, made of three O stars totalling some 130 solar masses. The 2.67-day inner orbit is rather well-known. Recent works derived a good approximation for the outer orbit with a period of 3000 days. We report here on interferometric observations that allow us to angularly resolve the outer orbit. First evidences for an astrometric displacement are given. The determination of the outer system orbit gives access to the inclinations of the systems and to the masses, including the one of the O3-O3.5 primary star.

  12. [The hierarchical clustering analysis of hyperspectral image based on probabilistic latent semantic analysis].

    Science.gov (United States)

    Yi, Wen-Bin; Shen, Li; Qi, Yin-Feng; Tang, Hong

    2011-09-01

    The paper introduces the Probabilistic Latent Semantic Analysis (PLSA) to the image clustering and an effective image clustering algorithm using the semantic information from PLSA is proposed which is used for hyperspectral images. Firstly, the ISODATA algorithm is used to obtain the initial clustering result of hyperspectral image and the clusters of the initial clustering result are considered as the visual words of the PLSA. Secondly, the object-oriented image segmentation algorithm is used to partition the hyperspectral image and segments with relatively pure pixels are regarded as documents in PLSA. Thirdly, a variety of identification methods which can estimate the best number of cluster centers is combined to get the number of latent semantic topics. Then the conditional distributions of visual words in topics and the mixtures of topics in different documents are estimated by using PLSA. Finally, the conditional probabilistic of latent semantic topics are distinguished using statistical pattern recognition method, the topic type for each visual in each document will be given and the clustering result of hyperspectral image are then achieved. Experimental results show the clusters of the proposed algorithm are better than K-MEANS and ISODATA in terms of object-oriented property and the clustering result is closer to the distribution of real spatial distribution of surface.

  13. 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.

  14. DATA CLASSIFICATION WITH NEURAL CLASSIFIER USING RADIAL BASIS FUNCTION WITH DATA REDUCTION USING HIERARCHICAL CLUSTERING

    Directory of Open Access Journals (Sweden)

    M. Safish Mary

    2012-04-01

    Full Text Available Classification of large amount of data is a time consuming process but crucial for analysis and decision making. Radial Basis Function networks are widely used for classification and regression analysis. In this paper, we have studied the performance of RBF neural networks to classify the sales of cars based on the demand, using kernel density estimation algorithm which produces classification accuracy comparable to data classification accuracy provided by support vector machines. In this paper, we have proposed a new instance based data selection method where redundant instances are removed with help of a threshold thus improving the time complexity with improved classification accuracy. The instance based selection of the data set will help reduce the number of clusters formed thereby reduces the number of centers considered for building the RBF network. Further the efficiency of the training is improved by applying a hierarchical clustering technique to reduce the number of clusters formed at every step. The paper explains the algorithm used for classification and for conditioning the data. It also explains the complexities involved in classification of sales data for analysis and decision-making.

  15. Modeling Hierarchically Clustered Longitudinal Survival Processes with Applications to Child Mortality and Maternal Health

    Directory of Open Access Journals (Sweden)

    Kuate-Defo, Bathélémy

    2001-01-01

    Full Text Available EnglishThis paper merges two parallel developments since the 1970s of newstatistical tools for data analysis: statistical methods known as hazard models that are used foranalyzing event-duration data and statistical methods for analyzing hierarchically clustered dataknown as multilevel models. These developments have rarely been integrated in research practice andthe formalization and estimation of models for hierarchically clustered survival data remain largelyuncharted. I attempt to fill some of this gap and demonstrate the merits of formulating and estimatingmultilevel hazard models with longitudinal data.FrenchCette étude intègre deux approches statistiques de pointe d'analyse des donnéesquantitatives depuis les années 70: les méthodes statistiques d'analyse desdonnées biographiques ou méthodes de survie et les méthodes statistiquesd'analyse des données hiérarchiques ou méthodes multi-niveaux. Ces deuxapproches ont été très peu mis en symbiose dans la pratique de recherche et parconséquent, la formulation et l'estimation des modèles appropriés aux donnéeslongitudinales et hiérarchiquement nichées demeure essentiellement un champd'investigation vierge. J'essaye de combler ce vide et j'utilise des données réellesen santé publique pour démontrer les mérites et contextes de formulation etd'estimation des modèles multi-niveaux et multi-états des données biographiqueset longitudinales.

  16. Energy Efficient Backoff Hierarchical Clustering Algorithms for Multi-Hop Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    Jun Wang; Yong-Tao Cao; Jun-Yuan Xie; Shi-Fu Chen

    2011-01-01

    Compared with flat routing protocols, clustering is a fundamental performance improvement technique in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we integrate the multi-hop technique with a backoff-based clustering algorithm to organize sensors. By using an adaptive backoff strategy, the algorithm not only realizes load balance among sensor node, but also achieves fairly uniform cluster head distribution across the network. Simulation results also demonstrate our algorithm is more energy-efficient than classical ones. Our algorithm is also easily extended to generate a hierarchy of cluster heads to obtain better network management and energy-efficiency.

  17. Classification of cancer cell lines using an automated two-dimensional liquid mapping method with hierarchical clustering techniques.

    Science.gov (United States)

    Wang, Yanfei; Wu, Rong; Cho, Kathleen R; Shedden, Kerby A; Barder, Timothy J; Lubman, David M

    2006-01-01

    A two-dimensional liquid mapping method was used to map the protein expression of eight ovarian serous carcinoma cell lines and three immortalized ovarian surface epithelial cell lines. Maps were produced using pI as the separation parameter in the first dimension and hydrophobicity based upon reversed-phase HPLC separation in the second dimension. The method can be reproducibly used to produce protein expression maps over a pH range from 4.0 to 8.5. A dynamic programming method was used to correct for minor shifts in peaks during the HPLC gradient between sample runs. The resulting corrected maps can then be compared using hierarchical clustering to produce dendrograms indicating the relationship between different cell lines. It was found that several of the ovarian surface epithelial cell lines clustered together, whereas specific groups of serous carcinoma cell lines clustered with each other. Although there is limited information on the current biology of these cell lines, it was shown that the protein expression of certain cell lines is closely related to each other. Other cell lines, including one ovarian clear cell carcinoma cell line, two endometrioid carcinoma cell lines, and three breast epithelial cell lines, were also mapped for comparison to show that their protein profiles cluster differently than the serous samples and to study how they cluster relative to each other. In addition, comparisons can be made between proteins differentially expressed between cell lines that may serve as markers of ovarian serous carcinomas. The automation of the method allows reproducible comparison of many samples, and the use of differential analysis limits the number of proteins that might require further analysis by mass spectrometry techniques.

  18. From Snakes to Stars, the Statistics of Collapsed Objects - II. Testing a Generic Scaling Ansatz for Hierarchical Clustering

    CERN Document Server

    Munshi, D; Melott, A L; Munshi, Dipak; Coles, Peter; Melott, Adrian L.

    1999-01-01

    We develop a diagrammatic technique to represent the multi-point cumulative probability density function (CPDF) of mass fluctuations in terms of the statistical properties of individual collapsed objects and relate this to other statistical descriptors such as cumulants, cumulant correlators and factorial moments. We use this approach to establish key scaling relations describing various measurable statistical quantities if clustering follows a simple general scaling ansatz, as expected in hierarchical models. We test these detailed predictions against high-resolution numerical simulations. We show that, when appropriate variables are used, the count probability distribution function (CPDF) and void probability distribution function (VPF) shows clear scaling properties in the non-linear regime. Generalising the results to the two-point count probability distribution function (2CPDF), and the bivariate void probability function (2VPF) we find good match with numerical simulations. We explore the behaviour of t...

  19. Biomolecule-Assisted Hydrothermal Synthesis and Self-Assembly of Bi2Te3 Nanostring-Cluster Hierarchical Structure

    DEFF Research Database (Denmark)

    Mi, Jianli; Lock, Nina; Sun, Ting;

    2010-01-01

    A simple biomolecule-assisted hydrothermal approach has been developed for the fabrication of Bi2Te3 thermoelectric nanomaterials. The product has a nanostring-cluster hierarchical structure which is composed of ordered and aligned platelet-like crystals. The platelets are100 nm in diameter...

  20. Clustering of Galaxies in a Hierarchical Universe 2 evolution to High Redshift

    CERN Document Server

    Kauffmann, G; Diaferio, A; White, S D M; Kauffmann, Guinevere; Colberg, Joerg M.; Diaferio, Antonaldo; White, Simon D.M.

    1998-01-01

    In hierarchical cosmologies the evolution of galaxy clustering depends both on cosmological quantities such as Omega and Lambda, which determine how dark matter halos form and evolve, and on the physical processes - cooling, star formation and feedback - which drive the formation of galaxies within these merging halos. In this paper, we combine dissipationless cosmological N-body simulations and semi-analytic models of galaxy formation in order to study how these two aspects interact. We focus on the differences in clustering predicted for galaxies of differing luminosity, colour, morphology and star formation rate and on what these differences can teach us about the galaxy formation process. We show that a "dip" in the amplitude of galaxy correlations between z=0 and z=1 can be an important diagnostic. Such a dip occurs in low-density CDM models because structure forms early and dark matter halos of 10**12 solar masses, containing galaxies with luminosities around L*, are unbiased tracers of the dark matter ...

  1. Quality Assured Optimal Resource Provisioning and Scheduling Technique Based on Improved Hierarchical Agglomerative Clustering Algorithm (IHAC

    Directory of Open Access Journals (Sweden)

    A. Meenakshi

    2016-08-01

    Full Text Available Resource allocation is the task of convenient resources to different uses. In the context of an resources, entire economy, can be assigned by different means, such as markets or central planning. Cloud computing has become a new age technology that has got huge potentials in enterprises and markets. Clouds can make it possible to access applications and associated data from anywhere. The fundamental motive of the resource allocation is to allot the available resource in the most effective manner. In the initial phase, a representative resource usage distribution for a group of nodes with identical resource usage patterns is evaluated as resource bundle which can be easily employed to locate a group of nodes fulfilling a standard criterion. In the document, an innovative clustering-based resource aggregation viz. the Improved Hierarchal Agglomerative Clustering Algorithm (IHAC is elegantly launched to realize the compact illustration of a set of identically behaving nodes for scalability. In the subsequent phase concerned with energetic resource allocation procedure, the hybrid optimization technique is brilliantly brought in. The novel technique is devised for scheduling functions to cloud resources which duly consider both financial and evaluation expenses. The efficiency of the novel Resource allocation system is assessed by means of several parameters such the reliability, reusability and certain other metrics. The optimal path choice is the consequence of the hybrid optimization approach. The new-fangled technique allocates the available resource based on the optimal path.

  2. Demographic Data Assessment using Novel 3DCCOM Spatial Hierarchical Clustering: A Case Study of Sonipat Block, Haryana

    Directory of Open Access Journals (Sweden)

    Mamta Malik

    2011-09-01

    Full Text Available Cluster detection is a tool employed by GIS scientists who specialize in the field of spatial analysis. This study employed a combination of GIS, RS and a novel 3DCCOM spatial data clustering algorithm to assess the rural demographic development strategies of Sonepat block, Haryana, India. This Study is undertaken in the rural and rural-based district in India to demonstrate the integration of village-level spatial and non-spatial data in GIS environment using Hierarchical Clustering. Spatial clusters of living standard parameters, including family members, male and female population, sex ratio, total male and female education ratio etc. The paper also envisages future development and usefulness of this community GIS, Spatial data clustering tool for grass-root level planning. Any data that showsgeographic (spatial variability can be subject to cluster analysis.

  3. Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

    Science.gov (United States)

    Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

    2014-11-01

    Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  4. Hierarchical clustering of breast cancer methylomes revealed differentially methylated and expressed breast cancer genes.

    Directory of Open Access Journals (Sweden)

    I-Hsuan Lin

    Full Text Available Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs and the hypomethylation of the megabase-sized partially methylated domains (PMDs are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.

  5. Comparing chemistry to outcome: the development of a chemical distance metric, coupled with clustering and hierarchal visualization applied to macromolecular crystallography.

    Directory of Open Access Journals (Sweden)

    Andrew E Bruno

    Full Text Available Many bioscience fields employ high-throughput methods to screen multiple biochemical conditions. The analysis of these becomes tedious without a degree of automation. Crystallization, a rate limiting step in biological X-ray crystallography, is one of these fields. Screening of multiple potential crystallization conditions (cocktails is the most effective method of probing a proteins phase diagram and guiding crystallization but the interpretation of results can be time-consuming. To aid this empirical approach a cocktail distance coefficient was developed to quantitatively compare macromolecule crystallization conditions and outcome. These coefficients were evaluated against an existing similarity metric developed for crystallization, the C6 metric, using both virtual crystallization screens and by comparison of two related 1,536-cocktail high-throughput crystallization screens. Hierarchical clustering was employed to visualize one of these screens and the crystallization results from an exopolyphosphatase-related protein from Bacteroides fragilis, (BfR192 overlaid on this clustering. This demonstrated a strong correlation between certain chemically related clusters and crystal lead conditions. While this analysis was not used to guide the initial crystallization optimization, it led to the re-evaluation of unexplained peaks in the electron density map of the protein and to the insertion and correct placement of sodium, potassium and phosphate atoms in the structure. With these in place, the resulting structure of the putative active site demonstrated features consistent with active sites of other phosphatases which are involved in binding the phosphoryl moieties of nucleotide triphosphates. The new distance coefficient, CDcoeff, appears to be robust in this application, and coupled with hierarchical clustering and the overlay of crystallization outcome, reveals information of biological relevance. While tested with a single example the

  6. CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

    Science.gov (United States)

    Franke, R.

    2016-11-01

    In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

  7. Cluster based hierarchical resource searching model in P2P network

    Institute of Scientific and Technical Information of China (English)

    Yang Ruijuan; Liu Jian; Tian Jingwen

    2007-01-01

    For the problem of large network load generated by the Gnutella resource-searching model in Peer to Peer (P2P) network, a improved model to decrease the network expense is proposed, which establishes a duster in P2P network,auto-organizes logical layers, and applies a hybrid mechanism of directional searching and flooding. The performance analysis and simulation results show that the proposed hierarchical searching model has availably reduced the generated message load and that its searching-response time performance is as fairly good as that of the Gnutella model.

  8. New Alzheimer amyloid beta responsive genes identified in human neuroblastoma cells by hierarchical clustering.

    Directory of Open Access Journals (Sweden)

    Markus Uhrig

    Full Text Available Alzheimer's disease (AD is characterized by neuronal degeneration and cell loss. Abeta(42, in contrast to Abeta(40, is thought to be the pathogenic form triggering the pathological cascade in AD. In order to unravel overall gene regulation we monitored the transcriptomic responses to increased or decreased Abeta(40 and Abeta(42 levels, generated and derived from its precursor C99 (C-terminal fragment of APP comprising 99 amino acids in human neuroblastoma cells. We identified fourteen differentially expressed transcripts by hierarchical clustering and discussed their involvement in AD. These fourteen transcripts were grouped into two main clusters each showing distinct differential expression patterns depending on Abeta(40 and Abeta(42 levels. Among these transcripts we discovered an unexpected inverse and strong differential expression of neurogenin 2 (NEUROG2 and KIAA0125 in all examined cell clones. C99-overexpression had a similar effect on NEUROG2 and KIAA0125 expression as a decreased Abeta(42/Abeta(40 ratio. Importantly however, an increased Abeta(42/Abeta(40 ratio, which is typical of AD, had an inverse expression pattern of NEUROG2 and KIAA0125: An increased Abeta(42/Abeta(40 ratio up-regulated NEUROG2, but down-regulated KIAA0125, whereas the opposite regulation pattern was observed for a decreased Abeta(42/Abeta(40 ratio. We discuss the possibilities that the so far uncharacterized KIAA0125 might be a counter player of NEUROG2 and that KIAA0125 could be involved in neurogenesis, due to the involvement of NEUROG2 in developmental neural processes.

  9. Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

    Directory of Open Access Journals (Sweden)

    Diane G O Saunders

    Full Text Available Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i contain a secretion signal, (ii are encoded by in planta induced genes, (iii have similarity to haustorial proteins, (iv are small and cysteine rich, (v contain a known effector motif or a nuclear localization signal, (vi are encoded by genes with long intergenic regions, (vii contain internal repeats, and (viii do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.

  10. Using Hierarchical Clustering of Secreted Protein Families to Classify and Rank Candidate Effectors of Rust Fungi

    Science.gov (United States)

    Saunders, Diane G. O.; Win, Joe; Cano, Liliana M.; Szabo, Les J.; Kamoun, Sophien; Raffaele, Sylvain

    2012-01-01

    Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i) contain a secretion signal, (ii) are encoded by in planta induced genes, (iii) have similarity to haustorial proteins, (iv) are small and cysteine rich, (v) contain a known effector motif or a nuclear localization signal, (vi) are encoded by genes with long intergenic regions, (vii) contain internal repeats, and (viii) do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components. PMID:22238666

  11. Symptom Clusters in People Living with HIV Attending Five Palliative Care Facilities in Two Sub-Saharan African Countries: A Hierarchical Cluster Analysis.

    Science.gov (United States)

    Moens, Katrien; Siegert, Richard J; Taylor, Steve; Namisango, Eve; Harding, Richard

    2015-01-01

    Symptom research across conditions has historically focused on single symptoms, and the burden of multiple symptoms and their interactions has been relatively neglected especially in people living with HIV. Symptom cluster studies are required to set priorities in treatment planning, and to lessen the total symptom burden. This study aimed to identify and compare symptom clusters among people living with HIV attending five palliative care facilities in two sub-Saharan African countries. Data from cross-sectional self-report of seven-day symptom prevalence on the 32-item Memorial Symptom Assessment Scale-Short Form were used. A hierarchical cluster analysis was conducted using Ward's method applying squared Euclidean Distance as the similarity measure to determine the clusters. Contingency tables, X2 tests and ANOVA were used to compare the clusters by patient specific characteristics and distress scores. Among the sample (N=217) the mean age was 36.5 (SD 9.0), 73.2% were female, and 49.1% were on antiretroviral therapy (ART). The cluster analysis produced five symptom clusters identified as: 1) dermatological; 2) generalised anxiety and elimination; 3) social and image; 4) persistently present; and 5) a gastrointestinal-related symptom cluster. The patients in the first three symptom clusters reported the highest physical and psychological distress scores. Patient characteristics varied significantly across the five clusters by functional status (worst functional physical status in cluster one, pclusters two and three, p=0.012); global distress (F=26.8, pcluster one, best for cluster four). The greatest burden is associated with cluster one, and should be prioritised in clinical management. Further symptom cluster research in people living with HIV with longitudinally collected symptom data to test cluster stability and identify common symptom trajectories is recommended.

  12. Structural system identification using degree of freedom-based reduction and hierarchical clustering algorithm

    Science.gov (United States)

    Chang, Seongmin; Baek, Sungmin; Kim, Ki-Ook; Cho, Maenghyo

    2015-06-01

    A system identification method has been proposed to validate finite element models of complex structures using measured modal data. Finite element method is used for the system identification as well as the structural analysis. In perturbation methods, the perturbed system is expressed as a combination of the baseline structure and the related perturbations. The changes in dynamic responses are applied to determine the structural modifications so that the equilibrium may be satisfied in the perturbed system. In practical applications, the dynamic measurements are carried out on a limited number of accessible nodes and associated degrees of freedom. The equilibrium equation is, in principle, expressed in terms of the measured (master, primary) and unmeasured (slave, secondary) degrees of freedom. Only the specified degrees of freedom are included in the equation formulation for identification and the unspecified degrees of freedom are eliminated through the iterative improved reduction scheme. A large number of system parameters are included as the unknown variables in the system identification of large-scaled structures. The identification problem with large number of system parameters requires a large amount of computation time and resources. In the present study, a hierarchical clustering algorithm is applied to reduce the number of system parameters effectively. Numerical examples demonstrate that the proposed method greatly improves the accuracy and efficiency in the inverse problem of identification.

  13. Hierarchical black hole triples in young star clusters: impact of Kozai-Lidov resonance on mergers

    CERN Document Server

    Kimpson, Thomas O; Mapelli, Michela; Ziosi, Brunetto M

    2016-01-01

    Mergers of compact object binaries are one of the most powerful sources of gravitational waves (GWs) in the frequency range of second-generation ground-based gravitational wave detectors (Advanced LIGO and Virgo). Dynamical simulations of young dense star clusters (SCs) indicate that ~27 per cent of all double compact object binaries are members of hierarchical triple systems (HTs). In this paper, we consider 570 HTs composed of three compact objects (black holes or neutron stars) that formed dynamically in N-body simulations of young dense SCs. We simulate them for a Hubble time with a new code based on the Mikkola's algorithmic regularization scheme, including the 2.5 post-Newtonian term. We find that ~88 per cent of the simulated systems develop Kozai-Lidov (KL) oscillations. KL resonance triggers the merger of the inner binary in three systems (corresponding to 0.5 per cent of the simulated HTs), by increasing the eccentricity of the inner binary. Accounting for KL oscillations leads to an increase of the...

  14. Ingredients and Process Standardization of Thepla: An Indian Unleavened Vegetable Flatbread using Hierarchical Cluster Analysis

    Directory of Open Access Journals (Sweden)

    S.S. Arya

    2012-10-01

    Full Text Available Thepla is an Indian unleavened flatbread made from whole-wheat flour with added spices and vegetables. It is particularly consumed in western zone of the India. The preparation of thepla is tedious, time consuming and requires skill. In the present study standardization of thepla ingredients were carried out by standardizing each ingredient on the basis of Overall Acceptability (OA score. Sensory analysis was carried out using nine-point hedonic rating scale with ten trained panellists. Standardized ingredients of thepla were: salt 3%, red chili powder 2.5%, fenugreek leaves 12%, cumin seed powder 0.6%, coriander seed powder 0.6%, ginger garlic paste (1:1 6%, asafoetida 0.6% and oil 3% w/w of whole wheat flour on the basis of highest sensory OA score. Further thepla process parameters such as time, temperature, diameter of thepla and weight of dough were standardized on the basis of sensory OA score. Obtained sensory score data was processed for Hierarchical Cluster Analysis (HCA.

  15. A new Hierarchical Group Key Management based on Clustering Scheme for Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Ayman EL-SAYED

    2014-05-01

    Full Text Available The migration from wired network to wireless network has been a global trend in the past few decades because they provide anytime-anywhere networking services. The wireless networks are rapidly deployed in the future, secure wireless environment will be mandatory. As well, The mobility and scalability brought by wireless network made it possible in many applications. Among all the contemporary wireless networks,Mobile Ad hoc Networks (MANET is one of the most important and unique applications. MANET is a collection of autonomous nodes or terminals which communicate with each other by forming a multihop radio network and maintaining connectivity in a decentralized manner. Due to the nature of unreliable wireless medium data transfer is a major problem in MANET and it lacks security and reliability of data. The most suitable solution to provide the expected level of security to these services is the provision of a key management protocol. A Key management is vital part of security. This issue is even bigger in wireless network compared to wired network. The distribution of keys in an authenticated manner is a difficult task in MANET. When a member leaves or joins the group, it needs to generate a new key to maintain forward and backward secrecy. In this paper, we propose a new group key management schemes namely a Hierarchical, Simple, Efficient and Scalable Group Key (HSESGK based on clustering management scheme for MANETs and different other schemes are classified. Group members deduce the group key in a distributed manner.

  16. First LOFAR results on galaxy clusters

    CERN Document Server

    Ferrari, C; Bonafede, A; Bîrzan, L; Brüggen, M; Brunetti, G; Cassano, R; Conway, J; De Gasperin, F; Heald, G; Jackson, N; Macario, G; McKean, J; Offringa, A R; Orrù, E; Pizzo, R; Rafferty, D A; Röttgering, H J A; Shulevski, A; Tasse, C; van der Tol, S; van Weeren, R J; Wise, M; van Zwieten, J E

    2012-01-01

    Deep radio observations of galaxy clusters have revealed the existence of diffuse radio sources related to the presence of relativistic electrons and weak magnetic fields in the intracluster volume. The role played by this non-thermal intracluster component on the thermodynamical evolution of galaxy clusters is debated, with important implications for cosmological and astrophysical studies of the largest gravitationally bound structures of the Universe. The low surface brightness and steep spectra of diffuse cluster radio sources make them more easily detectable at low-frequencies. LOFAR is the first instrument able to detect diffuse radio emission in hundreds of massive galaxy clusters up to their formation epoch. We present the first observations of clusters imaged by LOFAR and the huge perspectives opened by this instrument for non-thermal cluster studies.

  17. Recent Experimental Results on Nuclear Cluster Physics

    CERN Document Server

    Beck, C

    2016-01-01

    Knowledge on nuclear cluster physics has increased considerably since the pioneering discovery of 12C+12C resonances half a century ago and nuclear clustering remains one of the most fruitful domains of nuclear physics, facing some of the greatest challenges and opportunities in the years ahead. The occurrence of "exotic" shapes and/or Bose-Einstein alpha condensates in light N-Z alpha-conjugate nuclei is investigated. Evolution of clustering from stability to the drip-lines examined with clustering aspects persisting in light neutron-rich nuclei is consistent with the extension of the "Ikeda-diagram" to non alpha-conjugate nuclei.

  18. Hierarchical multiple bit clusters and patterned media enabled by novel nanofabrication techniques -- High resolution electron beam lithography and block polymer self assembly

    Science.gov (United States)

    Xiao, Qijun

    This thesis discusses the full scope of a project exploring the physics of hierarchical clusters of interacting nanomagnets. These clusters may be relevant for novel applications such as multilevel data storage devices. The work can be grouped into three main activities: micromagnetic simulation, fabrication and characterization of proof-of-concept prototype devices, and efforts to scale down the structures by creating the hierarchical structures with the aid of diblock copolymer self assembly. Theoretical micromagnetic studies and simulations based on Landau-Lifshitz-Gilbert (LLG) equation were conducted on nanoscale single domain magnetic entities. For the simulated nanomagnet clusters with perpendicular uniaxial anisotropy, the simulation showed the switching field distributions, the stability of the magnetostatic states with distinctive total cluster perpendicular moments, and the stepwise magnetic switching curves. For simulated nanomagnet clusters with in-plane shape anisotropy, the simulation showed the stepwise switching behaviors governed by thermal agitation and cluster configurations. Proof-of-concept cluster devices with three interacting Co nanomagnets were fabricated by e-beam lithography (EBL) and pulse-reverse electrochemical deposition (PRECD). EBL patterning on a suspended 100 nm SiN membrane showed improved lateral lithography resolution to 30 nm. The Co nanomagnets deposited using the PRECD method showed perpendicular anisotropy. The switching experiments with external applied fields were able to switch the Co nanomagnets through the four magnetostatic states with distinctive total perpendicular cluster magnetization, and proved the feasibility of multilevel data storage devices based on the cluster concept. Shrinking the structures size was experimented by the aid of diblock copolymer. Thick poly(styrene)-b-poly(methyl methacrylate) (PS-b-PMMA) diblock copolymer templates aligned with external electrical field were used to fabricate long Ni

  19. Taxonomy of Manufacturing Flexibility at Manufacturing Companies Using Imperialist Competitive Algorithms, Support Vector Machines and Hierarchical Cluster Analysis

    Directory of Open Access Journals (Sweden)

    M. Khoobiyan

    2017-04-01

    Full Text Available Manufacturing flexibility is a multidimensional concept and manufacturing companies act differently in using these dimensions. The purpose of this study is to investigate taxonomy and identify dominant groups of manufacturing flexibility. Dimensions of manufacturing flexibility are extracted by content analysis of literature and expert judgements. Manufacturing flexibility was measured by using a questionnaire developed to survey managers of manufacturing companies. The sample size was set at 379. To identify dominant groups of flexibility based on dimensions of flexibility determined, Hierarchical Cluster Analysis (HCA, Imperialist Competitive Algorithms (ICAs and Support Vector Machines (SVMs were used by cluster validity indices. The best algorithm for clustering was SVMs with three clusters, designated as leading delivery-based flexibility, frugal flexibility and sufficient plan-based flexibility.

  20. A Performance-Prediction Model for PIC Applications on Clusters of Symmetric MultiProcessors: Validation with Hierarchical HPF+OpenMP Implementation

    Directory of Open Access Journals (Sweden)

    Sergio Briguglio

    2003-01-01

    Full Text Available A performance-prediction model is presented, which describes different hierarchical workload decomposition strategies for particle in cell (PIC codes on Clusters of Symmetric MultiProcessors. The devised workload decomposition is hierarchically structured: a higher-level decomposition among the computational nodes, and a lower-level one among the processors of each computational node. Several decomposition strategies are evaluated by means of the prediction model, with respect to the memory occupancy, the parallelization efficiency and the required programming effort. Such strategies have been implemented by integrating the high-level languages High Performance Fortran (at the inter-node stage and OpenMP (at the intra-node one. The details of these implementations are presented, and the experimental values of parallelization efficiency are compared with the predicted results.

  1. 建筑物层次空间聚类方法研究%Hierarchical spatial clustering of buildings

    Institute of Scientific and Technical Information of China (English)

    邓敏; 孙前虎; 文小岳; 徐枫

    2011-01-01

    建筑物空间聚类是实现居民地地图自动综合的有效方法.基于图论和Gestalt原理,发展了一种层次的建筑物聚类方法.该方法可以深层次地挖掘建筑物图形的视觉特性,将面状地物信息充分合理地表达在聚类结果中.依据视觉感知原理,借助Dealaunay三角网构建方法,分析了地图上建筑物的自身形状特性和相互间的邻接关系,并依据建筑物间的可视区域均值距离建立了加权邻近结构图,确定了建筑物的邻近关系(定性约束).根据Gestalt准则将邻近性、方向性和几何特征等量化为旋转卡壳距离约束和几何相似度约束.通过实例验证了层次聚类方法得到更加符合人类认知的建筑物聚类结果.%Spatial clustering provides an effective approach for generalization of residential area in automated cartographic generalization.Based on graph theory and Gestalt principle, a hierarchical approach is proposed in this paper.This approach can be utilized to discover the graphical structure formed by buildings, which is obtained with the consideration of shape, size and neighboring relations.The neighboring relations are determined by Dclaunay triangulation, which is a qualitative constraint among buildings.A weighted neighboring structural graph is obtained by setting visual distance as the weight of the linking edge between adjacent buildings.Two levels of quantitative constraints are developed by considering the Gestalt factors, I.e.proximity, orientation and geometry of buildings.One is the rotating calipers minimum distance;the other is the geometric similarity measure.Through experiments it is illustrated that the results by the hierarchical spatial clustering proposed in this paper are consistent with human perception.

  2. The GaLAxy Cluster Evolution Survey (GLACE): introduction and first results

    CERN Document Server

    Sánchez-Portal, M; Pintos-Castro, I; Pérez-Martínez, R; Smail, I; Alfaro, E; Altieri, B; Aragón-Salamanca, A; Balkowski, C; Balogh, M; Biviano, A; Bongiovanni, A; Bremer, M; Castander, F; Castañeda, H; Castro-Rodríguez, N; Coia, D; Duc, P A; Geach, J; González-Serrano, I; Haines, C; McBreen, B; Metcalfe, L; Pérez-Fournón, I; García, A M Pérez; Poggianti, B; Rodríguez-Espinosa, J M; Smith, G P; Temporin, S; Valtchanov, I

    2010-01-01

    Aimed at understanding the evolution of galaxies in clusters, the GLACE survey is mapping a set of optical lines ([OII]3727, [OIII]5007, Hbeta and Halpha/[NII] when possible) in several galaxy clusters at redshift around 0.40, 0.63 and 0.86, using the Tuneable Filters (TF) of the OSIRIS instrument (Cepa et al. 2005) at the 10.4m GTC telescope. This study will address key questions about the physical processes acting upon the infalling galaxies during the course of hierarchical growth of clusters. GLACE is already ongoing: we present some preliminary results on our observations of the galaxy cluster Cl0024+1654 at z = 0.395; on the other hand, GLACE@0.86 has been approved as ESO/GTC large project to be started in 2011.

  3. Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries

    Directory of Open Access Journals (Sweden)

    Muntaner Carles

    2012-04-01

    Full Text Available Abstract Background An important contribution of the social determinants of health perspective has been to inquire about non-medical determinants of population health. Among these, labour market regulations are of vital significance. In this study, we investigate the labour market regulations among low- and middle-income countries (LMICs and propose a labour market taxonomy to further understand population health in a global context. Methods Using Gross National Product per capita, we classify 113 countries into either low-income (n = 71 or middle-income (n = 42 strata. Principal component analysis of three standardized indicators of labour market inequality and poverty is used to construct 2 factor scores. Factor score reliability is evaluated with Cronbach's alpha. Using these scores, we conduct a hierarchical cluster analysis to produce a labour market taxonomy, conduct zero-order correlations, and create box plots to test their associations with adult mortality, healthy life expectancy, infant mortality, maternal mortality, neonatal mortality, under-5 mortality, and years of life lost to communicable and non-communicable diseases. Labour market and health data are retrieved from the International Labour Organization's Key Indicators of Labour Markets and World Health Organization's Statistical Information System. Results Six labour market clusters emerged: Residual (n = 16, Emerging (n = 16, Informal (n = 10, Post-Communist (n = 18, Less Successful Informal (n = 22, and Insecure (n = 31. Primary findings indicate: (i labour market poverty and population health is correlated in both LMICs; (ii association between labour market inequality and health indicators is significant only in low-income countries; (iii Emerging (e.g., East Asian and Eastern European countries and Insecure (e.g., sub-Saharan African nations clusters are the most advantaged and disadvantaged, respectively, with the remaining clusters experiencing levels of population

  4. Symptom Clusters in People Living with HIV Attending Five Palliative Care Facilities in Two Sub-Saharan African Countries: A Hierarchical Cluster Analysis.

    Directory of Open Access Journals (Sweden)

    Katrien Moens

    Full Text Available Symptom research across conditions has historically focused on single symptoms, and the burden of multiple symptoms and their interactions has been relatively neglected especially in people living with HIV. Symptom cluster studies are required to set priorities in treatment planning, and to lessen the total symptom burden. This study aimed to identify and compare symptom clusters among people living with HIV attending five palliative care facilities in two sub-Saharan African countries.Data from cross-sectional self-report of seven-day symptom prevalence on the 32-item Memorial Symptom Assessment Scale-Short Form were used. A hierarchical cluster analysis was conducted using Ward's method applying squared Euclidean Distance as the similarity measure to determine the clusters. Contingency tables, X2 tests and ANOVA were used to compare the clusters by patient specific characteristics and distress scores.Among the sample (N=217 the mean age was 36.5 (SD 9.0, 73.2% were female, and 49.1% were on antiretroviral therapy (ART. The cluster analysis produced five symptom clusters identified as: 1 dermatological; 2 generalised anxiety and elimination; 3 social and image; 4 persistently present; and 5 a gastrointestinal-related symptom cluster. The patients in the first three symptom clusters reported the highest physical and psychological distress scores. Patient characteristics varied significantly across the five clusters by functional status (worst functional physical status in cluster one, p<0.001; being on ART (highest proportions for clusters two and three, p=0.012; global distress (F=26.8, p<0.001, physical distress (F=36.3, p<0.001 and psychological distress subscale (F=21.8, p<0.001 (all subscales worst for cluster one, best for cluster four.The greatest burden is associated with cluster one, and should be prioritised in clinical management. Further symptom cluster research in people living with HIV with longitudinally collected symptom data to

  5. Assessing clustering results with reference taxonomies.

    Science.gov (United States)

    Valiente, Gabriel

    2006-01-01

    The comparative analysis of phylogenies obtained using different phylogenetic methods or different gene sequences for a given set of species, is usually done by computing some quantitative measure of similarity between the phylogenetic trees. Such a quantitative approach provides little insight into the actual similarities and differences between the alternative phylogenies. In this paper, we present a method for the qualitative assessment of a phylogenetic tree against a reference taxonomy, based on highlighting their common clusters. Our algorithms build a reference taxonomy for the taxa present in a given phylogenetic tree and produce a dendogram for the input phylogenetic tree, with branches in those clusters common to the reference taxonomy highlighted. Our implementation of the algorithms produces publication-quality graphics. For unrooted phylogenies, the method produces a radial cladogram for the input phylogenetic tree, with branches in common clusters to the reference taxonomy highlighted.

  6. Typing of unknown microorganisms based on quantitative analysis of fatty acids by mass spectrometry and hierarchical clustering

    Energy Technology Data Exchange (ETDEWEB)

    Li Tingting; Dai Ling; Li Lun; Hu Xuejiao; Dong Linjie; Li Jianjian; Salim, Sule Khalfan; Fu Jieying [Key Laboratory of Pesticides and Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, Hubei 430079 (China); Zhong Hongying, E-mail: hyzhong@mail.ccnu.edu.cn [Key Laboratory of Pesticides and Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, Hubei 430079 (China)

    2011-01-17

    Rapid identification of unknown microorganisms of clinical and agricultural importance is not only critical for accurate diagnosis of infections but also essential for appropriate and prompt treatment. We describe here a rapid method for microorganisms typing based on quantitative analysis of fatty acids by iFAT approach (Isotope-coded Fatty Acid Transmethylation). In this work, lyophilized cell lysates were directly mixed with 0.5 M NaOH solution in d3-methanol and n-hexane. After 1 min of ultrasonication, the top n-hexane layer was combined with a mixture of standard d0-methanol derived fatty acid methylesters with known concentration. Measurement of intensity ratios of d3/d0 labeled fragment ion and molecular ion pairs at the corresponding target fatty acids provides a quantitative basis for hierarchical clustering. In the resultant dendrogram, the Euclidean distance between unknown species and known species quantitatively reveals their differences or shared similarities in fatty acid related pathways. It is of particular interest to apply this method for typing fungal species because fungi has distinguished lipid biosynthetic pathways that have been targeted for lots of drugs or fungicides compared with bacteria and animals. The proposed method has no dependence on the availability of genome or proteome databases. Therefore, it is can be applicable for a broad range of unknown microorganisms or mutant species.

  7. The Andromeda Project: Final Results of Citizen Science Cluster Identification

    Science.gov (United States)

    Seth, Anil; Johnson, L. C.; Wallace, M.; Dalcanton, J.; Kapadia, A.; Lintott, C.; Simpson, R.; Skillman, E. D.; PHAT Team; Andromeda Project Team

    2014-01-01

    The Panchromatic Hubble Andromeda Treasury (PHAT) survey has completed data collection, having taken over 30 billion pixels of imaging data of the Andromeda galaxy over four years using the Hubble Space Telescope. These data contain the largest sample of star clusters observable in any galaxy, including our own Milky Way. The Andromeda Project is a citizen science project that recruited over 10,000 volunteers to identify thousands of star clusters in the PHAT imaging. We present results culminating from two rounds of cluster searching and the properties of the resulting sample. We discuss catalog completeness results derived from synthetic cluster data. This cluster sample represents a significant advance in our ability to study star and cluster formation on galaxy wide scales. We are using the resulting cluster sample to provide the best available constraints on the high-mass initial mass function and the fraction of star formation that results in bound star clusters.

  8. First LOFAR results on galaxy clusters

    NARCIS (Netherlands)

    Ferrari, C.; van Bemmel, I.; Bonafede, A.; Bîrzan, L.; Brüggen, M.; Brunetti, G.; Cassano, R.; Conway, J.; De Gasperin, F.; Heald, G.; Jackson, N.; Macario, G.; McKean, J.; Offringa, A. R.; Orrù, E.; Pizzo, R.; Rafferty, D. A.; Röttgering, H. J. A.; Shulevski, A.; Tasse, C.; van der Tol, S.; van Weeren, R. J.; Wise, M.; van Zwieten, J.E.; Boissier, S.; de Laverny, P.; Nardetto, N.; Samadi, R.; Valls-Gabaud, D.; Wozniak, H.; Boissier, S.; de Laverny, P.; Nardetto, N.; Samadi, R.; Valls-Gabaud, D.; Wozniak, H.

    2012-01-01

    Deep radio observations of galaxy clusters have revealed the existence of diffuse radio sources related to the presence of relativistic electrons and weak magnetic fields in the intracluster volume. The role played by this non-thermal intracluster component on the thermodynamical evolution of galaxy

  9. Clustering the Results of Brainstorm Sessions: Applying Word Similarity Techniques to Cluster Dutch Nouns

    NARCIS (Netherlands)

    Amrit, Chintan Amrit; Hek, Jeroen

    2016-01-01

    This research addresses the problem of clustering the results of brainstorm sessions. Going through all ideas and clustering them can be a time consuming task. In this research we design a computer-aided approach that can help with clustering of these results. We have limited ourselves to looking at

  10. Clustering the Results of Brainstorm Sessions: Applying Word Similarity Techniques to Cluster Dutch Nouns

    NARCIS (Netherlands)

    Amrit, Chintan; Hek, Jeroen

    2016-01-01

    This research addresses the problem of clustering the results of brainstorm sessions. Going through all ideas and clustering them can be a time consuming task. In this research we design a computer-aided approach that can help with clustering of these results. We have limited ourselves to looking at

  11. Classifying airborne radiometry data with Agglomerative Hierarchical Clustering: A tool for geological mapping in context of rainforest (French Guiana)

    Science.gov (United States)

    Martelet, G.; Truffert, C.; Tourlière, B.; Ledru, P.; Perrin, J.

    2006-09-01

    In highly weathered environments, it is crucial that geological maps provide information concerning both the regolith and the bedrock, for societal needs, such as land-use, mineral or water resources management. Often, geologists are facing the challenge of upgrading existing maps, as relevant information concerning weathering processes and pedogenesis is currently missing. In rugged areas in particular, where access to the field is difficult, ground observations are sparsely available, and need therefore to be complemented using methods based on remotely sensed data. For this purpose, we discuss the use of Agglomerative Hierarchical Clustering (AHC) on eU, K and eTh airborne gamma-ray spectrometry grids. The AHC process allows primarily to segment the geophysical maps into zones having coherent U, K and Th contents. The analysis of these contents are discussed in terms of geochemical signature for lithological attribution of classes, as well as the use of a dendrogram, which gives indications on the hierarchical relations between classes. Unsupervised classification maps resulting from AHC can be considered as spatial models of the distribution of the radioelement content in surface and sub-surface formations. The source of gamma rays emanating from the ground is primarily related to the geochemistry of the bedrock and secondarily to modifications of the radioelement distribution by weathering and other secondary mechanisms, such as mobilisation by wind or water. The interpretation of the obtained predictive classified maps, their U, K, Th contents, and the dendrogram, in light of available geological knowledge, allows to separate signatures related to regolith and solid geology. Consequently, classification maps can be integrated within a GIS environment and used by the geologist as a support for mapping bedrock lithologies and their alteration. We illustrate the AHC classification method in the region of Cayenne using high-resolution airborne radiometric data

  12. Rapid recognition of drug-resistance/sensitivity in leukemic cells by Fourier transform infrared microspectroscopy and unsupervised hierarchical cluster analysis.

    Science.gov (United States)

    Bellisola, Giuseppe; Cinque, Gianfelice; Vezzalini, Marzia; Moratti, Elisabetta; Silvestri, Giovannino; Redaelli, Sara; Gambacorti Passerini, Carlo; Wehbe, Katia; Sorio, Claudio

    2013-07-21

    We tested the ability of Fourier Transform (FT) InfraRed (IR) microspectroscopy (microFTIR) in combination with unsupervised Hierarchical Cluster Analysis (HCA) in identifying drug-resistance/sensitivity in leukemic cells exposed to tyrosine kinase inhibitors (TKIs). Experiments were carried out in a well-established mouse model of human Chronic Myelogenous Leukemia (CML). Mouse-derived pro-B Ba/F3 cells transfected with and stably expressing the human p210(BCR-ABL) drug-sensitive wild-type BCR-ABL or the V299L or T315I p210(BCR-ABL) drug-resistant BCR-ABL mutants were exposed to imatinib-mesylate (IMA) or dasatinib (DAS). MicroFTIR was carried out at the Diamond IR beamline MIRIAM where the mid-IR absorbance spectra of individual Ba/F3 cells were acquired using the high brilliance IR synchrotron radiation (SR) via aperture of 15 × 15 μm(2) in sizes. A conventional IR source (globar) was used to compare average spectra over 15 cells or more. IR signatures of drug actions were identified by supervised analyses in the spectra of TKI-sensitive cells. Unsupervised HCA applied to selected intervals of wavenumber allowed us to classify the IR patterns of viable (drug-resistant) and apoptotic (drug-sensitive) cells with an accuracy of >95%. The results from microFTIR + HCA analysis were cross-validated with those obtained via immunochemical methods, i.e. immunoblotting and flow cytometry (FC) that resulted directly and significantly correlated. We conclude that this combined microFTIR + HCA method potentially represents a rapid, convenient and robust screening approach to study the impact of drugs in leukemic cells as well as in peripheral blasts from patients in clinical trials with new anti-leukemic drugs.

  13. Teaching a machine to see: unsupervised image segmentation and categorisation using growing neural gas and hierarchical clustering

    CERN Document Server

    Hocking, Alex; Davey, Neil; Sun, Yi

    2015-01-01

    We present a novel unsupervised learning approach to automatically segment and label images in astronomical surveys. Automation of this procedure will be essential as next-generation surveys enter the petabyte scale: data volumes will exceed the capability of even large crowd-sourced analyses. We demonstrate how a growing neural gas (GNG) can be used to encode the feature space of imaging data. When coupled with a technique called hierarchical clustering, imaging data can be automatically segmented and labelled by organising nodes in the GNG. The key distinction of unsupervised learning is that these labels need not be known prior to training, rather they are determined by the algorithm itself. Importantly, after training a network can be be presented with images it has never 'seen' before and provide consistent categorisation of features. As a proof-of-concept we demonstrate application on data from the Hubble Space Telescope Frontier Fields: images of clusters of galaxies containing a mixture of galaxy type...

  14. Mining Knowledge from Result Comparison Between Spatial Clustering Themes

    Institute of Scientific and Technical Information of China (English)

    SHA Zongyao; BIAN Fuling

    2005-01-01

    This paper introduces some definitions and defines a set of calculating indexes to facilitate the research, and then presents an algorithm to complete the spatial clustering result comparison between different clustering themes. The research shows that some valuable spatial correlation patterns can be further found from the clustering result comparison with multi-themes, based on traditional spatial clustering as the first step. Those patterns can tell us what relations those themes have, and thus will help us have a deeper understanding of the studied spatial entities. An example is also given to demonstrate the principle and process of the method.

  15. Dwarf galaxies in the Antlia Cluster: First results

    CERN Document Server

    Castelli, A V S; Cellone, S A; Richtler, T; Dirsch, B; Infante, L; Aruta, C; Gómez, M

    2006-01-01

    We present the first results of a project aimed to study the galaxy population of the Antlia cluster, the third nearest galaxy cluster after Virgo and Fornax. The observations for the Antlia project consist of Washington wide-field images taken with the MOSAIC camera mounted at the prime focus of the CTIO 4-m Blanco telescope. Our preliminary results correspond to the identification and classification of dwarf galaxies in the central cluster region, extending the list of Ferguson & Sandage (1990). The final aim of our project is to study the luminosity function, morphology and structural parameters of dwarf galaxies in the Antlia cluster with a more complete sample.

  16. Efficient Clustering of Web Search Results Using Enhanced Lingo Algorithm

    Directory of Open Access Journals (Sweden)

    M. Manikantan

    2015-02-01

    Full Text Available Web query optimization is the focus of recent research and development efforts. To fetch the required information, the users are using search engines and sometimes through the website interfaces. One approach is search engine optimization which is used by the website developers to popularize their website through the search engine results. Clustering is a main task of explorative data mining process and a common technique for grouping the web search results into a different category based on the specific web contents. A clustering search engine called Lingo used only snippets to cluster the documents. Though this method takes less time to cluster the documents, it could not be able to produce the clusters of good quality. This study focuses on clustering all documents using by applying semantic similarity between words and then by applying modified lingo algorithm in less time and produce good quality.

  17. Result Diversification Based on Query-Specific Cluster Ranking

    NARCIS (Netherlands)

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

    2011-01-01

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

  18. Result diversification based on query-specific cluster ranking

    NARCIS (Netherlands)

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

    2011-01-01

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

  19. Result diversification based on query-specific cluster ranking

    NARCIS (Netherlands)

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

    2011-01-01

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

  20. Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

    Science.gov (United States)

    Ellefsen, Karl J.; Smith, David

    2016-01-01

    Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.

  1. Energy Efficient Zone Division Multihop Hierarchical Clustering Algorithm for Load Balancing in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Ashim Kumar Ghosh

    2011-12-01

    Full Text Available Wireless sensor nodes are use most embedded computing application. Multihop cluster hierarchy has been presented for large wireless sensor networks (WSNs that can provide scalable routing, data aggregation, and querying. The energy consumption rate for sensors in a WSN varies greatly based on the protocols the sensors use for communications. In this paper we present a cluster based routing algorithm. One of our main goals is to design the energy efficient routing protocol. Here we try to solve the usual problems of WSNs. We know the efficiency of WSNs depend upon the distance between node to base station and the amount of data to be transferred and the performance of clustering is greatly influenced by the selection of cluster-heads, which are in charge of creating clusters and controlling member nodes. This algorithm makes the best use of node with low number of cluster head know as super node. Here we divided the full region in four equal zones and the centre area of the region is used to select for super node. Each zone is considered separately and the zone may be or not divided further that’s depending upon the density of nodes in that zone and capability of the super node. This algorithm forms multilayer communication. The no of layer depends on the network current load and statistics. Our algorithm is easily extended to generate a hierarchy of cluster heads to obtain better network management and energy efficiency.

  2. Inter-Cluster Routing Authentication for Ad Hoc Networks by a Hierarchical Key Scheme

    Institute of Scientific and Technical Information of China (English)

    Yueh-Min Huang; Hua-Yi Lin; Tzone-I Wang

    2006-01-01

    Dissimilar to traditional networks, the features of mobile wireless devices that can actively form a network without any infrastructure mean that mobile ad hoc networks frequently display partition due to node mobility or link failures. These indicate that an ad hoc network is difficult to provide on-line access to a trusted authority server. Therefore,applying traditional Public Key Infrastructure (PKI) security framework to mobile ad hoc networks will cause insecurities.This study proposes a scalable and elastic key management scheme integrated into Cluster Based Secure Routing Protocol (CBSRP) to enhance security and non-repudiation of routing authentication, and introduces an ID-Based internal routing authentication scheme to enhance the routing performance in an internal cluster. Additionally, a method of performing routing authentication between internal and external clusters, as well as inter-cluster routing authentication, is developed.The proposed cluster-based key management scheme distributes trust to an aggregation of cluster heads using a threshold scheme faculty, provides Certificate Authority (CA) with a fault tolerance mechanism to prevent a single point of compromise or failure, and saves CA large repositories from maintaining member certificates, making ad hoc networks robust to malicious behaviors and suitable for numerous mobile devices.

  3. Efficient storage and retrieval of clustering results using relational database

    Institute of Scientific and Technical Information of China (English)

    Deng Shengchun; He Zengyou; Xu Xiaofei; Li Qinzhi

    2005-01-01

    The problem of how to efficiently store and query the clustering results was considered. Three different storage schemas for clustering results using relational database were proposed, namely, full schema (f-schema), partial schema (p-schema) and compressed schema (c-schema). At the same time, a classification for queries issued to the clustering results was also presented. Finally, we empirically studied the performance of proposed queries on different storage schemas. To our knowledge, this is the first work to address the problem.

  4. A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda.

    Science.gov (United States)

    Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

    2016-03-01

    In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards' method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. © The Author 2015

  5. The experimental results on the quality of clustering diverse set of data using a modified algorithm chameleon

    Directory of Open Access Journals (Sweden)

    Татьяна Борисовна Шатовская

    2015-03-01

    Full Text Available In this work results of modified Chameleon algorithm are discussed. Hierarchical multilevel algorithms consist of several stages: building the graph, coarsening, partitioning, recovering. Exploring of clustering quality for different data sets with different combinations of algorithms on different stages of the algorithm is the main aim of the article. And also aim is improving the construction phase through the optimization algorithm of choice k in the building the graph k-nearest neighbors

  6. Genetic Algorithm for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sajid Hussain

    2007-09-01

    Full Text Available Large scale wireless sensor networks (WSNs can be used for various pervasive and ubiquitous applications such as security, health-care, industry automation, agriculture, environment and habitat monitoring. As hierarchical clusters can reduce the energy consumption requirements for WSNs, we investigate intelligent techniques for cluster formation and management. A genetic algorithm (GA is used to create energy efficient clusters for data dissemination in wireless sensor networks. The simulation results show that the proposed intelligent hierarchical clustering technique can extend the network lifetime for different network deployment environments.

  7. Fingerprint analysis of Hibiscus mutabilis L. leaves based on ultra performance liquid chromatography with photodiode array detector combined with similarity analysis and hierarchical clustering analysis methods

    Directory of Open Access Journals (Sweden)

    Xianrui Liang

    2013-01-01

    Full Text Available Background: A method for chemical fingerprint analysis of Hibiscus mutabilis L. leaves was developed based on ultra performance liquid chromatography with photodiode array detector (UPLC-PAD combined with similarity analysis (SA and hierarchical clustering analysis (HCA. Materials and Methods: 10 batches of Hibiscus mutabilis L. leaves samples were collected from different regions of China. UPLC-PAD was employed to collect chemical fingerprints of Hibiscus mutabilis L. leaves. Results: The relative standard deviations (RSDs of the relative retention times (RRT and relative peak areas (RPA of 10 characteristic peaks (one of them was identified as rutin in precision, repeatability and stability test were less than 3%, and the method of fingerprint analysis was validated to be suitable for the Hibiscus mutabilis L. leaves. Conclusions: The chromatographic fingerprints showed abundant diversity of chemical constituents qualitatively in the 10 batches of Hibiscus mutabilis L. leaves samples from different locations by similarity analysis on basis of calculating the correlation coefficients between each two fingerprints. Moreover, the HCA method clustered the samples into four classes, and the HCA dendrogram showed the close or distant relations among the 10 samples, which was consistent to the SA result to some extent.

  8. Investigating the provenance of iron artifacts of the Royal Iron Factory of Sao Joao de Ipanema by hierarchical cluster analysis of EDS microanalyses of slag inclusions

    Energy Technology Data Exchange (ETDEWEB)

    Mamani-Calcina, Elmer Antonio; Landgraf, Fernando Jose Gomes; Azevedo, Cesar Roberto de Farias, E-mail: c.azevedo@usp.br [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Escola Politecnica. Departmento de Engenharia Metalurgica e de Materiais

    2017-01-15

    Microstructural characterization techniques, including EDX (Energy Dispersive X-ray Analysis) microanalyses, were used to investigate the slag inclusions in the microstructure of ferrous artifacts of the Royal Iron Factory of Sao Joao de Ipanema (first steel plant of Brazil, XIX century), the D. Pedro II Bridge (located in Bahia, assembled in XIX century and produced in Scotland) and the archaeological sites of Sao Miguel de Missoes (Rio Grande do Sul, Brazil, production site of iron artifacts, the XVIII century) and Afonso Sardinha (Sao Paulo, Brazil production site of iron artifacts, XVI century). The microanalyses results of the main micro constituents of the microstructure of the slag inclusions were investigated by hierarchical cluster analysis and the dendrogram with the microanalyses results of the wüstite phase (using as critical variables the contents of MnO, MgO, Al{sub 2}O{sub 3}, V{sub 2}O{sub 5} and TiO{sub 2}) allowed the identification of four clusters, which successfully represented the samples of the four investigated sites (Ipanema, Sardinha, Missoes and Bahia). Finally, the comparatively low volumetric fraction of slag inclusions in the samples of Ipanema (∼1%) suggested the existence of technological expertise at the iron making processing in the Royal Iron Factory of Sao Joao de Ipanema. (author)

  9. Discovery of Overlapping and Hierarchical Communities Based on Extended Link Cluster Sequence%基于增广边簇序列的重叠层次社区发现

    Institute of Scientific and Technical Information of China (English)

    郭红; 黄佳鑫; 郭昆

    2015-01-01

    The mining and discovery of overlapping and hierarchical communities is a hot topic in the area of social network research. Firstly, an algorithm, discovery of link conmunities based on extended link cluster sequence ( DLC ECS) , is proposed to detect overlapping and hierarchical communities in social networks efficiently. Based on the extended link cluster sequence corresponding to community structures with various densities, the optimal link community is detected after searching for the global optimal density. The link communities are transformed into the node communities, and thus the overlapping communities can be found out. Then, hierarchical link communities extraction based on extended link cluster sequence ( HLCE ECS ) is designed. Hierarchical link communities from the extended link cluster sequence is found by the proposed algorithm. The link communities are transformed into the node communities to find out the overlapping and hierarchical communities. Experimental results on are artificial and real-world datasets demonstrate that DLC ECS algorithm significantly improves the community quality and HLCE ECS algorithm effectively discovers meaningful hierarchical communities.%高质量重叠层次社区的挖掘和发现已成为社会网络研究热点,为更有效地发现社会网络中具有重叠层次性的社区结构,提出基于增广边簇序列的边社区发现算法( DLC ECS)。在产生包含所有可能密度参数对应的社区结构的增广边簇序列的基础上,找出全局最优的密度参数,发现全局最优的边社区结构,将识别的边社区结构转化为节点社区结构,发现具有重叠结构的社区。在该序列的基础上,提出层次边社区提取算法( HLCE ECS),快速发现序列中的层次边社区结构,将识别的边社区结构转化为节点社区结构,发现同时具有重叠和层次结构的社区。在真实数据集和人工数据集上的实验表明,DLC ECS具有

  10. Analytical relations concerning the collapse time in hierarchically clustered cosmological models

    CERN Document Server

    Gambera, M

    1997-01-01

    By means of numerical methods, we solve the equations of motion for the collapse of a shell of baryonic matter, made of galaxies and substructure falling into the central regions of a cluster of galaxies, taking into account the effect of the dynamical friction. The parameters on which the dynamical friction mainly depends are: the peaks' height, the number of peaks inside a protocluster multiplied by the correlation function evaluated at the origin, the filtering radius and the nucleus radius of the protocluster of galaxies. We show how the collapse time (Tau) of the shell depends on these parameters. We give a formula that links the dynamical friction coefficient (Eta) o the parameters mentioned above and an analytic relation between the collapse time and (Eta). Finally, we obtain an analytical relation between (Tau) and the mean overdensity (mean Delta) within the shell. All the analytical relations that we find are in excellent agreement with the numerical integration.

  11. Formation of an O-Star Cluster by Hierarchical Accretion in G20.08-0.14 N

    CERN Document Server

    Galván-Madrid, Roberto; Zhang, Qizhou; Kurtz, Stan; Rodríguez, Luis F; Ho, Paul T P

    2009-01-01

    Spectral line and continuum observations of the ionized and molecular gas in G20.08-0.14 N explore the dynamics of accretion over a range of spatial scales in this massive star forming region. Very Large Array observations of NH_3 at 4'' angular resolution show a large scale (0.5 pc) molecular accretion flow around and into a star cluster with three small, bright HII regions. Higher resolution (0.4'') observations with the Submillimeter Array in hot core molecules (CH_3CN, OCS, and SO_2) and the VLA in NH_3, show that the two brightest and smallest HII regions are themselves surrounded by smaller scale (0.05 pc) accretion flows. The axes of rotation of the large and small scale flows are aligned, and the time scale for the contraction of the cloud is short enough, 0.1 Myr, for the large scale accretion flow to deliver significant mass to the smaller scales within the star formation time scale. The flow structure appears to be continuous and hierarchical from larger to smaller scales. Millimeter radio recombin...

  12. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...

  13. Planck intermediate results. VIII. Filaments between interacting clusters

    Science.gov (United States)

    Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Balbi, A.; Banday, A. J.; Barreiro, R. B.; Battaner, J. G. Bartlett E.; Benabed, K.; Benoît, A.; Bernard, J.-P.; Bersanelli, M.; Bhatia, R.; Bikmaev, I.; Böhringer, H.; Bonaldi, A.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bourdin, H.; Burenin, R.; Burigana, C.; Cabella, P.; Cardoso, J.-F.; Castex, G.; Catalano, A.; Cayón, L.; Chamballu, A.; Chary, R.-R.; Chiang, L.-Y.; Chon, G.; Christensen, P. R.; Clements, D. L.; Colafrancesco, S.; Colombo, L. P. L.; Comis, B.; Coulais, A.; Crill, B. P.; Cuttaia, F.; Danese, L.; Davis, R. J.; de Bernardis, P.; de Gasperis, G.; de Zotti, G.; Delabrouille, J.; Démoclès, J.; Désert, F.-X.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Dörl, U.; Douspis, M.; Dupac, X.; Efstathiou, G.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Frailis, M.; Franceschi, E.; Frommert, M.; Ganga, K.; Génova-Santos, T.; Giard, M.; Gilfanov, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Harrison, D.; Hempel, A.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hovest, W.; Hurier, G.; Jaffe, T. R.; Jaffe, A. H.; Jagemann, T.; Jones, W. C.; Juvela, M.; Khamitov, I.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lawrence, C. R.; Le Jeune, M.; Leonardi, R.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Luzzi, G.; Macías-Pérez, J. F.; Maffei, B.; Maino, D.; Mandolesi, N.; Maris, M.; Marleau, F.; Marshall, D. J.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Mei, S.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Mitra, S.; Miville-Deschènes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Piffaretti, R.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Savini, G.; Schaefer, B. M.; Scott, D.; Smoot, G. F.; Starck, J.-L.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Valenziano, L.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Welikala, N.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zonca, A.

    2013-02-01

    Context. About half of the baryons of the Universe are expected to be in the form of filaments of hot and low-density intergalactic medium. Most of these baryons remain undetected even by the most advanced X-ray observatories, which are limited in sensitivity to the diffuse low-density medium. Aims: The Planck satellite has provided hundreds of detections of the hot gas in clusters of galaxies via the thermal Sunyaev-Zel'dovich (tSZ) effect and is an ideal instrument for studying extended low-density media through the tSZ effect. In this paper we use the Planck data to search for signatures of a fraction of these missing baryons between pairs of galaxy clusters. Methods: Cluster pairs are good candidates for searching for the hotter and denser phase of the intergalactic medium (which is more easily observed through the SZ effect). Using an X-ray catalogue of clusters and the Planck data, we selected physical pairs of clusters as candidates. Using the Planck data, we constructed a local map of the tSZ effect centred on each pair of galaxy clusters. ROSAT data were used to construct X-ray maps of these pairs. After modelling and subtracting the tSZ effect and X-ray emission for each cluster in the pair, we studied the residuals on both the SZ and X-ray maps. Results: For the merging cluster pair A399-A401 we observe a significant tSZ effect signal in the intercluster region beyond the virial radii of the clusters. A joint X-ray SZ analysis allows us to constrain the temperature and density of this intercluster medium. We obtain a temperature of kT = 7.1 ± 0.9 keV (consistent with previous estimates) and a baryon density of (3.7 ± 0.2) × 10-4 cm-3. Conclusions: The Planck satellite mission has provided the first SZ detection of the hot and diffuse intercluster gas.

  14. Hierarchical Cont-Bouchaud model

    CERN Document Server

    Paluch, Robert; Holyst, Janusz A

    2015-01-01

    We extend the well-known Cont-Bouchaud model to include a hierarchical topology of agent's interactions. The influence of hierarchy on system dynamics is investigated by two models. The first one is based on a multi-level, nested Erdos-Renyi random graph and individual decisions by agents according to Potts dynamics. This approach does not lead to a broad return distribution outside a parameter regime close to the original Cont-Bouchaud model. In the second model we introduce a limited hierarchical Erdos-Renyi graph, where merging of clusters at a level h+1 involves only clusters that have merged at the previous level h and we use the original Cont-Bouchaud agent dynamics on resulting clusters. The second model leads to a heavy-tail distribution of cluster sizes and relative price changes in a wide range of connection densities, not only close to the percolation threshold.

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

    Directory of Open Access Journals (Sweden)

    Omholt Stig W

    2011-06-01

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

  16. Segmentation Algorithm for Oil Spill SAR Images Based on Hierarchical Agglomerative Clustering%基于HAC的溢油SAR图像分割算法

    Institute of Scientific and Technical Information of China (English)

    苏腾飞; 孟俊敏; 张晰

    2013-01-01

    图像分割是SAR溢油检测中的关键步骤,但由于SAR影像中存在斑点噪声,使得一般的图像分割算法难以收到理想的效果,严重影响溢油检测的精度.发展一种基于凝聚层次聚类(Hierarchical Agglomerative Clustering,HAC)的溢油SAR图像分割算法.该算法利用多尺度分割的思想,能够有效保持SAR影像中溢油斑块的形状特征,并能减少细碎斑块的产生.利用2010年墨西哥湾的Envisat ASAR影像开展了溢油SAR图像分割实验,并将该算法和Canny边缘检测、OTSU阈值分割、FCM分割、水平集分割等方法进行了对比.结果显示,HAC方法可以有效减少细碎斑块的产生,有助于提高SAR溢油检测的精度.%Image segmentation is a crucial stage in the SAR oil spill detection.However,the common image segmentation algorithms can hardly achieve satisfactory results due to speckle noise in the SAR images,thus affecting seriously the accuracy of oil spill detection.For this reason,an image segmentation algorithm which is based on HAC (Hierarchical Agglomerative Clustering) is developed for the oil spill SAR images.This method takes advantage of multi-resolution segmentation to maintain effectively the shape property of oil spill patches,and can reduce the formation of small patches.By using Envisat ASAR images of the Gulf of Mexico obtained in 2010,an experiment of SAR oil spill image segmentation has been conducted.Comparing with other approaches such as Canny,OTSU,FCM and Levelset,the results show that HAC can effectively reduce the producing of small patches,which is helpful to improve the accuracy of SAR oil spill detection.

  17. Partial least square and hierarchical clustering in ADMET modeling: prediction of blood-brain barrier permeation of α-adrenergic and imidazoline receptor ligands.

    Science.gov (United States)

    Nikolic, Katarina; Filipic, Slavica; Smoliński, Adam; Kaliszan, Roman; Agbaba, Danica

    2013-01-01

    PURPOSE. Rate of brain penetration (logPS), brain/plasma equilibration rate (logPS-brain), and extent of blood-brain barrier permeation (logBB) of 29 α-adrenergic and imidazoline-receptors ligands were examined in Quantitative-Structure-Property Relationship (QSPR) study. METHODS. Experimentally determined chromatographic retention data (logKw at pH 4.4, slope (S) at pH 4.4, logKw at pH 7.4, slope (S) at pH 7.4, logKw at pH 9.1, and slope (S) at pH 9.1) and capillary electrophoresis migration parameters (μeff at pH 4.4, μeff at pH 7.4, and μeff at pH 9.1), together with calculated molecular descriptors, were used as independent variables in the QSPR study by use of partial least square (PLS) methodology. RESULTS. Predictive potential of the formed QSPR models, QSPR(logPS), QSPR(logPS-brain), QSPR(logBB), was confirmed by cross- and external validation. Hydrophilicity (Hy) and H-indices (H7m) were selected as significant parameters negatively correlated with both logPS and logPS-brain, while topological polar surface area (TPSA(NO)) was chosen as molecular descriptor negatively correlated with both logPS and logBB. The principal component analysis (PCA) and hierarchical clustering analysis (HCA) were applied to cluster examined drugs based on their chromatographic, electrophoretic and molecular properties. Significant positive correlations were obtained between the slope (S) at pH 7.4 and logBB in A/B cluster and between the logKw at pH 9.1 and logPS in C/D cluster. CONCLUSIONS. Results of the QSPR, clustering and correlation studies could be used as novel tool for evaluation of blood-brain barrier permeation of related α-adrenergic/imidazoline receptor ligands.This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.PURPOSE. Rate of brain penetration (logPS), brain/plasma equilibration rate (logPS-brain), and extent of blood-brain barrier permeation (logBB) of 29

  18. Hierarchical Affinity Propagation

    CERN Document Server

    Givoni, Inmar; Frey, Brendan J

    2012-01-01

    Affinity propagation is an exemplar-based clustering algorithm that finds a set of data-points that best exemplify the data, and associates each datapoint with one exemplar. We extend affinity propagation in a principled way to solve the hierarchical clustering problem, which arises in a variety of domains including biology, sensor networks and decision making in operational research. We derive an inference algorithm that operates by propagating information up and down the hierarchy, and is efficient despite the high-order potentials required for the graphical model formulation. We demonstrate that our method outperforms greedy techniques that cluster one layer at a time. We show that on an artificial dataset designed to mimic the HIV-strain mutation dynamics, our method outperforms related methods. For real HIV sequences, where the ground truth is not available, we show our method achieves better results, in terms of the underlying objective function, and show the results correspond meaningfully to geographi...

  19. Record Matching Over Query Results Using Fuzzy Ontological Document Clustering

    Directory of Open Access Journals (Sweden)

    V.Vijayaraja

    2011-02-01

    Full Text Available Record matching is an essential step in duplicate detection as it identifies records representing same real-world entity. Supervised record matching methods require users to provide training data andtherefore cannot be applied for web databases where query results are generated on-the-fly. To overcome the problem, a new record matching method named Unsupervised Duplicate Elimination (UDE is proposed for identifying and eliminating duplicates among records in dynamic query results. The idea of this paper is to adjust the weights of record fields in calculating similarities among records. Two classifiers namely weight component similarity summing classifier, support vector machine classifier are iteratively employed with UDE where the first classifier utilizes the weights set to match records from different data sources. With the matched records as positive dataset and non duplicate records as negative set, the second classifier identifies new duplicates. Then, a new methodology to automatically interpret and cluster knowledge documents using an ontology schema is presented. Moreover, a fuzzy logic control approach is used to match suitable document cluster(s for given patents based on their derived ontological semantic webs. Thus, this paper takes advantage of similarity among records from web databases and solves the online duplicate detection problem.

  20. Hierarchical cluster analysis and chemical characterisation of Myrtus communis L. essential oil from Yemen region and its antimicrobial, antioxidant and anti-colorectal adenocarcinoma properties.

    Science.gov (United States)

    Anwar, Sirajudheen; Crouch, Rebecca A; Awadh Ali, Nasser A; Al-Fatimi, Mohamed A; Setzer, William N; Wessjohann, Ludger

    2017-01-09

    The hydrodistilled essential oil obtained from the dried leaves of Myrtus communis, collected in Yemen, was analysed by GC-MS. Forty-one compounds were identified, representing 96.3% of the total oil. The major constituents of essential oil were oxygenated monoterpenoids (87.1%), linalool (29.1%), 1,8-cineole (18.4%), α-terpineol (10.8%), geraniol (7.3%) and linalyl acetate (7.4%). The essential oil was assessed for its antimicrobial activity using a disc diffusion assay and resulted in moderate to potent antibacterial and antifungal activities targeting mainly Bacillus subtilis, Staphylococcus aureus and Candida albicans. The oil moderately reduced the diphenylpicrylhydrazyl radical (IC50 = 4.2 μL/mL or 4.1 mg/mL). In vitro cytotoxicity evaluation against HT29 (human colonic adenocarcinoma cells) showed that the essential oil exhibited a moderate antitumor effect with IC50 of 110 ± 4 μg/mL. Hierarchical cluster analysis of M. communis has been carried out based on the chemical compositions of 99 samples reported in the literature, including Yemeni sample.

  1. Ultra high performance liquid chromatography with electrospray ionization tandem mass spectrometry coupled with hierarchical cluster analysis to evaluate Wikstroemia indica (L.) C. A. Mey. from different geographical regions.

    Science.gov (United States)

    Wei, Lan; Wang, Xiaobo; Mu, Shanxue; Sun, Lixin; Yu, Zhiguo

    2015-06-01

    A sensitive, rapid and simple ultra high performance liquid chromatography with electrospray ionization tandem mass spectrometry method was developed to determine seven constituents (umbelliferone, apigenin, triumbelletin, daphnoretin, arctigenin, genkwanin and emodin) in Wikstroemia indica (L.) C. A. Mey. The chromatographic analysis was performed on an ACQUITY UPLC® BEH C18 column (2.1 × 50 mm, 1.7 μm) by gradient elution with the mobile phase of 0.05% formic acid aqueous solution (A) and acetonitrile (B). Multiple reaction monitoring mode with positive and negative electrospray ionization interface was carried out to detect the components. This method was validated in terms of specificity, linearity, accuracy, precision and stability. Excellent linear behavior was observed over the certain concentration ranges with the correlation coefficient values higher than 0.999. The intraday and innerday precisions were within 2.0%. The recoveries of seven analytes were 99.4-101.1% with relative standard deviation less than 1.2%. The 18 Wikstroemia indica samples from different origins were classified by hierarchical clustering analysis according to the contents of seven components. The results demonstrated that the developed method could successfully be used to quantify simultaneously of seven components in Wikstroemia indica and could be a helpful tool for the detection and confirmation of the quality of traditional Chinese medicines.

  2. Principal factor and hierarchical cluster analyses for the performance assessment of an urban wastewater treatment plant in the Southeast of Spain.

    Science.gov (United States)

    Bayo, Javier; López-Castellanos, Joaquín

    2016-07-01

    Process performance and operation of wastewater treatment plants (WWTP) are carried out to ensure their compliance with legislative requirements imposed by European Union. Because a high amount of variables are daily measured, a coherent and structured approach of such a system is required to understand its inherent behavior and performance efficiency. In this sense, both principal factor analysis (PFA) and hierarchical cluster analysis (HCA) are multivariate techniques that have been widely applied to extract and structure information for different purposes. In this paper, both statistical tools are applied in an urban WWTP situated in the Southeast of Spain, a zone with special characteristics related to the geochemical background composition of water and an important use of fertilizers. Four main factors were extracted in association with nutrients, the ionic component, the organic load to the WWTP, and the efficiency of the whole process. HCA allowed distinguish between influent and effluent parameters, although a deeper examination resulted in a dendrogram with groupings similar to those previously reported for PFA.

  3. Research of Parallel Programming Techniques of Hierarchical Model Based on SMP Clusters%基于SMP机群的层次化并行编程技术的研究

    Institute of Scientific and Technical Information of China (English)

    祝永志; 张丹丹; 曹宝香; 禹继国

    2012-01-01

    针对多核SMP机群的体系结构特点,讨论了MPI+ OpenMP混合并行程序设计技术.提出了一种多层次化混合设计新方法.设计了N-body问题的多层次化并行算法,并在曙光5000A机群上与传统的混合算法作了性能方面的比较.结果表明,该层次化混合并行算法具有更好的扩展性和加速比.%For multi-core SMP cluster systems, this paper discusses hybrid parallel programming techniques based on MPI and OpenMP.We propose a new hybrid parallel programming methods lhat are aware of architecture hierarchy on SMP cluster systems. We design a hierarchically parallel algorithm on the N-body problem, and compared its performance with traditional hybrid parallel algorithms on the Dawning 5000A cluster. The results indicate that our hierarchically hybrid parallel algorithm has better scalability and speedup than others.

  4. First results obtained by the Cluster STAFF experiment

    Directory of Open Access Journals (Sweden)

    N. Cornilleau-Wehrlin

    Full Text Available The Spatio Temporal Analysis of Field Fluctuations (STAFF experiment is one of the five experiments, which constitute the Cluster Wave Experiment Consortium (WEC. STAFF consists of a three-axis search coil magnetometer to measure magnetic fluctuations at frequencies up to 4 kHz, a waveform unit (up to either 10 Hz or 180 Hz and a Spectrum Analyser (up to 4 kHz. The Spectrum Analyser combines the 3 magnetic components of the waves with the two electric components measured by the Electric Fields and Waves experiment (EFW to calculate in real time the 5 × 5 Hermitian cross-spectral matrix at 27 frequencies distributed logarithmically in the frequency range 8 Hz to 4 kHz. The time resolution varies between 0.125 s and 4 s. The first results show the capabilities of the experiment, with examples in different regions of the magnetosphere-solar wind system that were encountered by Cluster at the beginning of its operational phase. First results obtained by the use of some of the tools that have been prepared specifically for the Cluster mission are described. The characterisation of the motion of the bow shock between successive crossings, using the reciprocal vector method, is given. The full characterisation of the waves analysed by the Spectrum Analyser, thanks to a dedicated program called PRASSADCO, is applied to some events; in particular a case of very confined electromagnetic waves in the vicinity of the equatorial region is presented and discussed.

    Key words. Magnetospheric physics (magnetopause, cusp and boundary layer – Space plasma physics (waves and instabilities; shock waves

  5. Robustness Results for Hierarchical Diff-EDF Scheduling upon Heterogeneous Real-Time Packet Networks

    Directory of Open Access Journals (Sweden)

    Moutaz Saleh

    2007-01-01

    Full Text Available Packet networks are currently enabling the integration of traffic with a wide range of characteristics that extend from video traffic with stringent QoS requirements to the best-effort traffic requiring no guarantees. QoS guarantees can be provided in conventional packet networks by the use of proper packet scheduling algorithms. As a computer revolution, many scheduling algorithms have been proposed to provide different schemes of QoS guarantees with Earliest Deadline First (EDF as the most popular one. With EDF scheduling, all flows receive the same miss rate regardless of their traffic characteristics and deadlines. This makes the standard EDF algorithm unsuitable for situations in which the different flows have different miss rate requirements since in order to meet all miss rate requirements it is necessary to limit admissions so as to satisfy the flow with the most stringent miss rate requirements. In this study, we propose a new priority assignment scheduling algorithm, Hierarchal Diff-EDF (Differentiate Earliest Deadline First, which can meet the real-time needs of these applications while continuing to provide best effort service to non-real time traffic. The Hierarchal Diff-EDF features a feedback control mechanism that detects overload conditions and modifies packet priority assignments accordingly.

  6. Results from a Second RXTE Observation of the Coma Cluster

    CERN Document Server

    Rephaeli, Y; Rephaeli, Yoel; Gruber, Duane

    2002-01-01

    The RXTE satellite observed the Coma cluster for 177 ksec during November and December 2000, a second observation motivated by the intriguing results from the first 87 ksec observation in 1996. Analysis of the new dataset confirms that thermal emission from isothermal gas does not provide a good fit to the spectral distribution of the emission from the inner 1 degree radial region. While the observed spectrum may be fit by emission from gas with a substantial temperature gradient, it is more likely that the emission includes also a secondary non-thermal component. If so, non-thermal emission comprises ~8% of the total 4--20 keV flux. Interpreting this emission as due to Compton scattering of relativistic electrons (which produce the known extended radio emission) by the cosmic microwave background radiation, we determine that the mean, volume-averaged magnetic field in the central region of Coma is B = 0.1-0.3 microgauss.

  7. Gene-Set Local Hierarchical Clustering (GSLHC--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups.

    Directory of Open Access Journals (Sweden)

    Feng-Hsiang Chung

    Full Text Available Gene-set-based analysis (GSA, which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA, which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap, an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap, in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases.

  8. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  9. 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

  10. First results from the Cluster wideband plasma wave investigation

    Directory of Open Access Journals (Sweden)

    D. A. Gurnett

    Full Text Available In this report we present the first results from the Cluster wideband plasma wave investigation. The four Cluster spacecraft were successfully placed in closely spaced, high-inclination eccentric orbits around the Earth during two separate launches in July – August 2000. Each spacecraft includes a wideband plasma wave instrument designed to provide high-resolution electric and magnetic field wave-forms via both stored data and direct downlinks to the NASA Deep Space Network. Results are presented for three commonly occurring magnetospheric plasma wave phenomena: (1 whistlers, (2 chorus, and (3 auroral kilometric radiation. Lightning-generated whistlers are frequently observed when the spacecraft is inside the plasmasphere. Usually the same whistler can be detected by all spacecraft, indicating that the whistler wave packet extends over a spatial dimension at least as large as the separation distances transverse to the magnetic field, which during these observations were a few hundred km. This is what would be expected for nonducted whistler propagation. No case has been found in which a strong whistler was detected at one spacecraft, with no signal at the other spacecraft, which would indicate ducted propagation. Whistler-mode chorus emissions are also observed in the inner region of the magnetosphere. In contrast to lightning-generated whistlers, the individual chorus elements seldom show a one-to-one correspondence between the spacecraft, indicating that a typical chorus wave packet has dimensions transverse to the magnetic field of only a few hundred km or less. In one case where a good one-to-one correspondence existed, significant frequency variations were observed between the spacecraft, indicating that the frequency of the wave packet may be evolving as the wave propagates. Auroral kilometric radiation, which is an intense radio emission generated along the auroral field lines, is frequently observed over the polar regions. The

  11. Environmental quenching and hierarchical cluster assembly: Evidence from spectroscopic ages of red-sequence galaxies in Coma

    CERN Document Server

    Smith, Russell J; Price, James; Hudson, Michael J; Phillipps, Steven

    2011-01-01

    We explore the variation in stellar population ages for Coma cluster galaxies as a function of projected cluster-centric distance, using a sample of 362 red-sequence galaxies with high signal-to-noise spectroscopy. The sample spans a wide range in luminosity (0.02-4 L*) and extends from the cluster core to near the virial radius. We find a clear distinction in the observed trends of the giant and dwarf galaxies. The ages of red-sequence giants are primarily determined by galaxy mass, with only weak modulation by environment, in the sense that galaxies at larger cluster-centric distance are slightly younger. For red-sequence dwarfs (with mass <10^10 Msun), the roles of mass and environment as predictors of age are reversed: there is little dependence on mass, but strong trends with projected cluster-centric radius are observed. The average age of dwarfs at the 2.5 Mpc limit of our sample is approximately half that of dwarfs near the cluster centre. The gradient in dwarf galaxy ages is a global cluster-centr...

  12. Planck intermediate results. VIII. Filaments between interacting clusters

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Atrio-Barandela, F; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartlett, J G; Battaner, E; Benabed, K; Benoît, A; Bernard, J -P; Bersanelli, M; Bhatia, R; Böhringer, H; Bonaldi, A; Bond, J R; Borrill, J; Bouchet, F R; Bourdin, H; Burigana, C; Cabella, P; Cardoso, J -F; Castex, G; Catalano, A; Cayón, L; Chamballu, A; Chary, R -R; Chiang, L -Y; Chon, G; Christensen, P R; Clements, D L; Colafrancesco, S; Colombo, L P L; Comis, B; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Danese, L; Davis, R J; de Bernardis, P; de Gasperis, G; de Zotti, G; Delabrouille, J; Désert, F -X; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Dörl, U; Douspis, M; Dupac, X; Efstathiou, G; Enßlin, T A; Eriksen, H K; Finelli, F; Flores-Cacho, I; Forni, O; Frailis, M; Franceschi, E; Frommert, M; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Gilfanov, M; Giraud-Héraud, Y; González-Nuevo, J; Górski, K M; Gregorio, A; Gruppuso, A; Hansen, F K; Harrison, D; Hempel, A; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hovest, W; Hurier, G; Jaffe, T R; Jaffe, A H; Jagemann, T; Jones, W C; Juvela, M; Kisner, T S; Kneissl, R; Knoche, J; Knox, L; Kunz, M; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lasenby, A; Lawrence, C R; Jeune, M Le; Leonardi, R; Lilje, P B; Linden-Vørnle, M; López-Caniego, M; Lubin, P M; Luzzi, G; Macías-Pérez, J F; Maffei, B; Maino, D; Mandolesi, N; Maris, M; Marleau, F; Marshall, D J; Martínez-González, E; Masi, S; Massardi, M; Matarrese, S; Matthai, F; Mazzotta, P; Mei, S; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Munshi, D; Murphy, J A; Naselsky, P; Nati, F; Natoli, P; Nørgaard-Nielsen, H U; Noviello, F; Osborne, S; Pajot, F; Paoletti, D; Pasian, F; Patanchon, G; Perdereau, O; Perotto, L; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Popa, L; Poutanen, T; Pratt, G W; Prunet, S; Rachen, J P; Rebolo, R; Reinecke, M; Remazeilles, M; Renault, C; Ricciardi, S; Riller, T; Ristorcelli, I; Rocha, G; Roman, M; Rosset, C; Rossetti, M; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Savini, G; Schaefer, B M; Scott, D; Smoot, G F; Starck, J -L; Sudiwala, R; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Valenziano, L; Van Tent, B; Vielva, P; Villa, F; Vittorio, N; Wade, L A; Wandelt, B D; Welikala, N; White, S D M; Yvon, D; Zacchei, A; Zonca, A

    2012-01-01

    About half of the baryons of the Universe are expected to be in the form of filaments of hot and low density intergalactic medium. Most of these baryons remain undetected even by the most advanced X-ray observatories which are limited in sensitivity to the diffuse low density medium. The Planck satellite has provided hundreds of detections of the hot gas in clusters of galaxies via the thermal Sunyaev-Zel'dovich (tSZ) effect and is an ideal instrument for studying extended low density media through the tSZ effect. In this paper we use the Planck data to search for signatures of a fraction of these missing baryons between pairs of galaxy clusters. Cluster pairs are good candidates for searching for the hotter and denser phase of the intergalactic medium (which is more easily observed through the SZ effect). Using an X-ray catalogue of clusters and the Planck data, we select physical pairs of clusters as candidates. Using the Planck data we construct a local map of the tSZ effect centered on each pair of galaxy...

  13. Hierarchical rutile TiO2 flower cluster-based high efficiency dye-sensitized solar cells via direct hydrothermal growth on conducting substrates.

    Science.gov (United States)

    Ye, Meidan; Liu, Hsiang-Yu; Lin, Changjian; Lin, Zhiqun

    2013-01-28

    Dye-sensitized solar cells (DSSCs) based on hierarchical rutile TiO(2) flower clusters prepared by a facile, one-pot hydrothermal process exhibit a high efficiency. Complex yet appealing rutile TiO(2) flower films are, for the first time, directly hydrothermally grown on a transparent conducting fluorine-doped tin oxide (FTO) substrate. The thickness and density of as-grown flower clusters can be readily tuned by tailoring growth parameters, such as growth time, the addition of cations of different valence and size, initial concentrations of precursor and cation, growth temperature, and acidity. Notably, the small lattice mismatch between the FTO substrate and rutile TiO(2) renders the epitaxial growth of a compact rutile TiO(2) layer on the FTO glass. Intriguingly, these TiO(2) flower clusters can then be exploited as photoanodes to produce DSSCs, yielding a power conversion efficiency of 2.94% despite their rutile nature, which is further increased to 4.07% upon the TiCl(4) treatment.

  14. 基于改进层次聚类的同家族变压器状态变化规律分析%Condition evolution regularity analysis of power transformer in the same family based on improved hierarchical clustering

    Institute of Scientific and Technical Information of China (English)

    李新叶; 李新芳

    2011-01-01

    Family quality default history affects the healthy condition of power transformer greatly in integrated condition assessment. And now, it is usually subjectively decided by expert's experience. A new quantitatively computing method is proposed, that is, using hierarchical clustering technology to analyze the potential evolution regularity and then computing the influence degree of family quality default history on healthy condition of power transformer. To make the clustering result more accurate, line slope distance of condition evolution is proposed as line shape similarity criterion, both data distance criterion and line slope distance criterion are used to cluster data. The experimental result shows that our method is better than traditional hierarchical clustering method, and it is more reasonable to use clustering analysis to calculate the influence degree of family quality default history on power transformer healthy condition.%在变压器状态综合评估的研究中,家族质量缺陷史对变压器健康状态有重要影响,目前多是凭专家经验主观确定.提出利用层次聚类分析技术对同家族变压器状态变化规律进行分析,根据分析结果定量计算家族质量缺陷史对变压器健康状态的影响程度.为提高聚类的准确性,提出用变压器状态变化曲线的斜率距离作为曲线形状的相似性判据,同时用曲线间点数值距离和斜率距离构成交集约束判据进行聚类.实例分析表明改进的层次聚类算法优于传统的层次聚类算法,由聚类分析结果计算家族质量缺陷史对变压器健康状态的影响得出的结果更合理.

  15. 一种层次聚类的RDF图语义检索方法研究%Hierarchical clustering-based semantic retrieval of RDF graph

    Institute of Scientific and Technical Information of China (English)

    刘宁; 左凤华; 张俊

    2012-01-01

    The cun-ent research related RDF graph retrieve exists some problems, such as low efficiency of memory usage, low search efficiency and so on. This paper proposed a hierarchical clustering semantic retrieval model on RDF graph and the method based on the model to solve aforesaid problems. That extracting entities from RDF graph and hierarchical clustering by the guidance of the ontology library made the complex graph structure into a tree structure for efficient retrieval. Orientating target object which was one of nodes in the model in RDF conducted the semantic expansion queries. Retrieval efficiency increased because retrieval scope narrow down as construction of retrieval model and recall ratio increased by the semantic expansion queries.%针对当前信息资源描述框架(RDF)检索过程中存在的内存使用过大及检索效率低等问题,提出一个RDF图的层次聚类语义检索模型,设计并实现了相应的检索方法.首先从RDF图中抽取实体数据,在本体库的指导下,通过层次聚类,将复杂的图形结构转换为适合检索的树型结构;根据在树中查找到的目标对象,确定其在RDF图中的位置,进行语义扩充查询.检索模型的构建缩小了检索范围,从而提高了检索效率,其语义扩充查询还可以得到较好的查全率.

  16. Delineation of Stenotrophomonas maltophilia isolates from cystic fibrosis patients by fatty acid methyl ester profiles and matrix-assisted laser desorption/ionization time-of-flight mass spectra using hierarchical cluster analysis and principal component analysis.

    Science.gov (United States)

    Vidigal, Pedrina Gonçalves; Mosel, Frank; Koehling, Hedda Luise; Mueller, Karl Dieter; Buer, Jan; Rath, Peter Michael; Steinmann, Joerg

    2014-12-01

    Stenotrophomonas maltophilia is an opportunist multidrug-resistant pathogen that causes a wide range of nosocomial infections. Various cystic fibrosis (CF) centres have reported an increasing prevalence of S. maltophilia colonization/infection among patients with this disease. The purpose of this study was to assess specific fingerprints of S. maltophilia isolates from CF patients (n = 71) by investigating fatty acid methyl esters (FAMEs) through gas chromatography (GC) and highly abundant proteins by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and to compare them with isolates obtained from intensive care unit (ICU) patients (n = 20) and the environment (n = 11). Principal component analysis (PCA) of GC-FAME patterns did not reveal a clustering corresponding to distinct CF, ICU or environmental types. Based on the peak area index, it was observed that S. maltophilia isolates from CF patients produced significantly higher amounts of fatty acids in comparison with ICU patients and the environmental isolates. Hierarchical cluster analysis (HCA) based on the MALDI-TOF MS peak profiles of S. maltophilia revealed the presence of five large clusters, suggesting a high phenotypic diversity. Although HCA of MALDI-TOF mass spectra did not result in distinct clusters predominantly composed of CF isolates, PCA revealed the presence of a distinct cluster composed of S. maltophilia isolates from CF patients. Our data suggest that S. maltophilia colonizing CF patients tend to modify not only their fatty acid patterns but also their protein patterns as a response to adaptation in the unfavourable environment of the CF lung. © 2014 The Authors.

  17. 基于类轮廓层次聚类方法的研究%RESEARCH ON CLASS-PROFILE-BASED HIERARCHICAL CLUSTERING METHOD

    Institute of Scientific and Technical Information of China (English)

    孟海东; 唐旋

    2011-01-01

    传统的聚类算法在考虑类与类之间的连通性特征和近似性特征上往往顾此失彼.首先给出类边界点和类轮廓的基本定义以及寻求方法,然后基于类间连通性特征和近似性特征的综合考虑,拟定一些类间相似性度量标准和方法,最后提出一种基于类轮廓的层次聚类算法.该算法能够有效处理任意形状的簇,且能够区分孤立点和噪声数据.通过对图像数据集和Iris标准数据集的聚类分析,验证了该算法的可行性和有效性.%Traditional clustering algorithms are often incapable of roundly considering the connectivity and similarity characteristics among classes. The thesis firstly presents the fundamental definition of class boundary point and class profile; secondly, with comprehensive consideration based on connectivity characteristics and similarity characteristics among classes, defines some standards and methods for inter class similarity measurement; thirdly, proposes a class-profile-based hierarchical clustering algorithm, which is able to effectively process arbitrary shaped clusters and distinguish isolated points from noise data. The feasibility and effectiveness of the algorithm is validated through clustering analysis on image data sets and Iris standard data sets.

  18. Cosmic dust detection by the Cluster spacecraft: First results

    Science.gov (United States)

    Vaverka, Jakub; De Spiegeleer, Alexandre; Hamrin, Maria; Kero, Johan; Mann, Ingrid; Norberg, Carol; Pellinen-Wannberg, Asta; Pitkänen, Timo

    2016-04-01

    There are several different techniques that are used to measure cosmic dust entering the Earth's atmosphere such as space-born dust detectors, meteor and HPLA radars, and optical methods. One complementary method could be to use electric field instruments initially designed to measure electric waves. A plasma cloud generated by a hypervelocity dust impact on a spacecraft body can be detected by the electric field instruments commonly operated on spacecraft. Since Earth-orbiting missions are generally not equipped with conventional dust detectors, the electric field instruments offer an alternative method to measure the Earth's dust environment. We present the first detection of dust impacts on one of the Earth-orbiting Cluster satellites with the Wideband Data Plasma Wave Receiver (WBD). We first describe the concept of dust impact ionization and of the impact detection. Based on these considerations the mass and the velocity of the impinging dust grains can be estimated from the amplitude of the Cluster voltage pulses. In the case of the Cluster instrument an automatic gain control adjusts the dynamic range of the recorded signals. Depending on the gain level the impact signal can both be affected by saturation or be too weak for analysis. We describe how this influences the duty cycle of the impact measurements. We finally discuss the suitability of this method for monitoring dust fluxes near Earth and compare it with other methods.

  19. Clustering Approach to Stock Market Prediction

    Directory of Open Access Journals (Sweden)

    M.Suresh Babu

    2012-01-01

    Full Text Available Clustering is an adaptive procedure in which objects are clustered or grouped together, based on the principle of maximizing the intra-class similarity and minimizing the inter-class similarity. Various clustering algorithms have been developed which results to a good performance on datasets for cluster formation. This paper analyze the major clustering algorithms: K-Means, Hierarchical clustering algorithm and reverse K means and compare the performance of these three major clustering algorithms on the aspect of correctly class wise cluster building ability of algorithm. An effective clustering method, HRK (Hierarchical agglomerative and Recursive K-means clustering is proposed, to predict the short-term stock price movements after the release of financial reports. The proposed method consists of three phases. First, we convert each financial report into a feature vector and use the hierarchical agglomerative clustering method to divide the converted feature vectors into clusters. Second, for each cluster, we recursively apply the K-means clustering method to partition each cluster into sub-clusters so that most feature vectors in each subcluster belong to the same class. Then, for each sub cluster, we choose its centroid as the representative feature vector. Finally, we employ the representative feature vectors to predict the stock price movements. The experimental results show the proposed method outperforms SVM in terms of accuracy and average profits.

  20. Early results from the Whisper instrument on Cluster: An overview

    DEFF Research Database (Denmark)

    Decreau, P.M.E.; Fergeau, P.; Krasnoselskikh, V.

    2001-01-01

    The Whisper instrument yields two data sets: (i) the electron density determined via the relaxation sounder, and (ii) the spectrum of natural plasma emissions in the frequency band 2-80 kHz. Both data sets allow for the three-dimensional exploration of the magnetosphere by the Cluster mission...... in normal telemetry mode and 0.3 s in burst mode telemetry, respectively. Recorded on board the four spacecraft, the Whisper density data set forms a reference for other techniques measuring the electron population. We give examples of Whisper density data used to derive the vector gradient, and estimate...

  1. Ultrathin mesoporous Co3O4 nanosheets-constructed hierarchical clusters as high rate capability and long life anode materials for lithium-ion batteries

    Science.gov (United States)

    Wu, Shengming; Xia, Tian; Wang, Jingping; Lu, Feifei; Xu, Chunbo; Zhang, Xianfa; Huo, Lihua; Zhao, Hui

    2017-06-01

    Herein, Ultrathin mesoporous Co3O4 nanosheets-constructed hierarchical clusters (UMCN-HCs) have been successfully synthesized via a facile hydrothermal method followed by a subsequent thermolysis treatment at 600 °C in air. The products consist of cluster-like Co3O4 microarchitectures, which are assembled by numerous ultrathin mesoporous Co3O4 nanosheets. When tested as anode materials for lithium-ion batteries, UMCN-HCs deliver a high reversible capacity of 1067 mAh g-1 at a current density of 100 mA g-1 after 100 cycles. Even at 2 A g-1, a stable capacity as high as 507 mAh g-1 can be achieved after 500 cycles. The high reversible capacity, excellent cycling stability, and good rate capability of UMCN-HCs may be attributed to their mesoporous sheet-like nanostructure. The sheet-layered structure of UMCN-HCs may buffer the volume change during the lithiation-delithiation process, and the mesoporous characteristic make lithium-ion transfer more easily at the interface between the active electrode and the electrolyte.

  2. Planck early results: Cluster Sunyaev-Zeldovich optical scaling relations

    CERN Document Server

    Aghanim, N; Ashdown, M; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartelmann, M; Bartlett, J G; Battaner, E; Benabed, K; Benoît, A; Bernard, J -P; Bersanelli, M; Bhatia, R; Bock, J J; Bonaldi, A; Bond, J R; Borrill, J; Bouchet, F R; Brown, M L; Bucher, M; Burigana, C; Cabella, P; Cardoso, J -F; Catalano, A; Cayón, L; Challinor, A; Chamballu, A; Chiang, L -Y; Chiang, C; Chon, G; Christensen, P R; Churazov, E; Clements, D L; Colafrancesco, S; Colombi, S; Couchot, F; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Danese, L; Davis, R J; de Bernardis, P; de Gasperis, G; de Rosa, A; de Zotti, G; Delabrouille, J; Delouis, J -M; Désert, F -X; Diego, J M; Dolag, K; Donzelli, S; Doré, O; Dörl, U; Douspis, M; Dupac, X; Efstathiou, G; En\\sslin, T A; Finelli, F; Flores, I; Forni, O; Frailis, M; Franceschi, E; Fromenteau, S; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Giardino, G; Giraud-Héraud, Y; González-Nuevo, J; Górski, K M; Gratton, S; Gregorio, A; Gruppuso, A; Harrison, D; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hovest, W; Hoyland, R J; Huffenberger, K M; Jaffe, A H; Jones, W C; Juvela, M; Keihänen, E; Keskitalo, R; Kisner, T S; Kneissl, R; Knox, L; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lasenby, A; Laureijs, R J; Lawrence, C R; Leach, S; Leonardi, R; Linden-V\\ornle, M; López-Caniego, M; Lubin, P M; Macías-Pérez, J F; MacTavish, C J; Maffei, B; Maino, D; Mandolesi, N; Mann, R; Maris, M; Marleau, F; Martínez-González, E; Masi, S; Matarrese, S; Matthai, F; Mazzotta, P; Mei, S; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, A; Naselsky, P; Natoli, P; Netterfield, C B; N\\orgaard-Nielsen, H U; Noviello, F; Novikov, D; Novikov, I; O'Dwyer, I J; Osborne, S; Pajot, F; Pasian, F; Patanchon, G; Perdereau, O; Perotto, L; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Poutanen, T; Pratt, G W; Prézeau, G; Prunet, S; Puget, J -L; Rebolo, R; Reinecke, M; Renault, C; Ricciardi, S; Riller, T; Ristorcelli, I; Rocha, G; Rosset, C; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Savini, G; Schaefer, B M; Scott, D; Seiffert, M D; Shellard, P; Smoot, G F; Starck, J -L; Stivoli, F; Stolyarov, V; Sudiwala, R; Sunyaev, R; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Torre, J -P; Tristram, M; Tuovinen, J; Valenziano, L; Vibert, L; Vielva, P; Villa, F; Vittorio, N; Wandelt, B D; White, S D M; White, M; Yvon, D; Zacchei, A; Zonca, A

    2011-01-01

    We present the Sunyaev-Zeldovich (SZ) signal-to-richness scaling relation (Y500-N200) for the MaxBCG cluster catalogue. Employing a multi-frequency matched filter on the Planck sky maps, we measure the SZ signal for each cluster by adapting the filter according to weak-lensing calibrated mass-richness relations (N200-M500). We bin our individual measurements and detect the SZ signal down to the lowest richness systems (N200=10) with high significance, achieving a detection of the SZ signal in systems with mass as low as M500~5e13 Msolar. The observed Y500-N200 relation is well modeled by a power law over the full richness range. It has a lower normalisation at given N200 than predicted based on X-ray models and published mass-richness relations. An X-ray subsample, however, does conform to the predicted scaling, and model predictions do reproduce the relation between our measured bin-average SZ signal and measured bin-average X-ray luminosities. At fixed richness, we find an intrinsic dispersion in the Y500-N...

  3. The statistics of foreshock cavities: results of a Cluster survey

    Directory of Open Access Journals (Sweden)

    L. Billingham

    2008-11-01

    Full Text Available We use Cluster magnetic field, thermal ion, and energetic particle observations upstream of the Earth's bow shock to investigate the occurrence patterns of foreshock cavities. Such cavities are thought to form when bundles of magnetic field connect to the quasi-parallel bow shock. Shock-processed suprathermal ions can then stream along the field, back against the flow of the solar wind. These suprathermals enhance the pressure on shock-connected field lines causing them to expand into the surrounding ambient solar wind plasma. Foreshock cavities exhibit depressions in magnetic field magnitude and thermal ion density, associated with enhanced fluxes of energetic ions. We find typical cavity duration to be few minutes with interior densities and magnetic field magnitudes dropping to ~60% of those in the surrounding solar wind. Cavities are found to occur preferentially in fast, moderate magnetic field strength solar wind streams. Cavities are observed in all parts of the Cluster orbit upstream of the bow shock. When localised in a coordinate system organised by the underlying physical processes in the foreshock, there is a systematic change in foreshock cavity location with IMF cone angle. At low (high cone angles foreshock cavities are observed outside (inside the expected upstream boundary of the intermediate ion foreshock.

  4. Critérios de formação de carteiras de ativos por meio de Hierarchical Clusters

    Directory of Open Access Journals (Sweden)

    Pierre Lucena

    2010-04-01

    Full Text Available Este artigo tem como objetivo principal apresentar e testar uma ferramenta de estatística multivariada em modelos financeiros. Essa metodologia, conhecida como análise de clusters, separa as observações em grupos com suas determinadas características, em contraste com a metodologia tradicional, que é somente a ordem com os quantis. Foi aplicada essa ferramenta em 213 ações negociadas na Bolsa de São Paulo (Bovespa, separando os grupos por tamanho e book-tomarket. Depois, as novas carteiras foram aplicadas no modelo de Fama e French (1996, comparando os resultados numa formação de carteira para quantil e análise de cluster. Foram encontrados melhores resultados na segunda metodologia. Os autores concluem que a análise de cluster pode ser mais adequada porque tende a formar grupos mais homogeneizados, sendo sua aplicação útil para a formação de carteiras e para a teoria financeira.

  5. A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification

    Directory of Open Access Journals (Sweden)

    Marín Ignacio

    2007-11-01

    Full Text Available Abstract Background Classification procedures are widely used in phylogenetic inference, the analysis of expression profiles, the study of biological networks, etc. Many algorithms have been proposed to establish the similarity between two different classifications of the same elements. However, methods to determine significant coincidences between hierarchical and non-hierarchical partitions are still poorly developed, in spite of the fact that the search for such coincidences is implicit in many analyses of massive data. Results We describe a novel strategy to compare a hierarchical and a dichotomic non-hierarchical classification of elements, in order to find clusters in a hierarchical tree in which elements of a given "flat" partition are overrepresented. The key improvement of our strategy respect to previous methods is using permutation analyses of ranked clusters to determine whether regions of the dendrograms present a significant enrichment. We show that this method is more sensitive than previously developed strategies and how it can be applied to several real cases, including microarray and interactome data. Particularly, we use it to compare a hierarchical representation of the yeast mitochondrial interactome and a catalogue of known mitochondrial protein complexes, demonstrating a high level of congruence between those two classifications. We also discuss extensions of this method to other cases which are conceptually related. Conclusion Our method is highly sensitive and outperforms previously described strategies. A PERL script that implements it is available at http://www.uv.es/~genomica/treetracker.

  6. A Hierarchical Clustering Method Based on the Threshold of Semantic Feature in Big Data%大数据中一种基于语义特征阈值的层次聚类方法

    Institute of Scientific and Technical Information of China (English)

    罗恩韬; 王国军

    2015-01-01

    云计算、健康医疗、街景地图服务、推荐系统等新兴服务促使数据的种类和规模以前所未有的速度增长,数据量的激增会导致很多共性问题.例如数据的可表示,可处理和可靠性问题.如何有效处理和分析数据之间的关系,提高数据的划分效率,建立数据的聚类分析模型,已经成为学术界和企业界共同亟待解决的问题.该文提出一种基于语义特征的层次聚类方法,首先根据数据的语义特征进行训练,然后在每个子集上利用训练结果进行层次聚类,最终产生整体数据的密度中心点,提高了数据聚类效率和准确性.此方法采样复杂度低,数据分析准确,易于实现,具有良好的判定性.%The type and scale of data has been promoted with a hitherto unknown speed by the emerging services including cloud computing, health care, street view services recommendation system and so on. However, the surge in the volume of data may lead to many common problems, such as the representability, reliability and handlability of data. Therefore, how to effectively handle the relationship between the data and the analysis to improve the efficiency of classification of the data and establish the data clustering analysis model has become an academic and business problem, which needs to be solved urgently. A hierarchical clustering method based on semantic feature is proposed. Firstly, the data should be trained according to the semantic features of data, and then is used the training result to process hierarchical clustering in each subset; finally, the density center point is produced. This method can improve the efficiency and accuracy of data clustering. This algorithm is of low complexity about sampling, high accuracy of data analysis and good judgment. Furthermore, the algorithm is easy to realize.

  7. Hierarchical Fragmentation and Jet-like Outflows in IRDC G28.34+0.06, a Growing Massive Protostar Cluster

    CERN Document Server

    Wang, Ke; Wu, Yuefang; Zhang, Huawei

    2011-01-01

    We present Submillimeter Array (SMA) \\lambda = 0.88mm observations of an infrared dark cloud (IRDC) G28.34+0.06. Located in the quiescent southern part of the G28.34 cloud, the region of interest is a massive ($>10^3$\\,\\msun) molecular clump P1 with a luminosity of $\\sim 10^3$ \\lsun, where our previous SMA observations at 1.3mm have revealed a string of five dust cores of 22-64 \\msun\\ along the 1 pc IR-dark filament. The cores are well aligned at a position angle of 48 degrees and regularly spaced at an average projected separation of 0.16 pc. The new high-resolution, high-sensitivity 0.88\\,mm image further resolves the five cores into ten compact condensations of 1.4-10.6 \\msun, with sizes a few thousands AU. The spatial structure at clump ($\\sim 1$ pc) and core ($\\sim 0.1$ pc) scales indicates a hierarchical fragmentation. While the clump fragmentation is consistent with a cylindrical collapse, the observed fragment masses are much larger than the expected thermal Jeans masses. All the cores are driving CO(...

  8. Planck intermediate results: VIII. Filaments between interacting clusters

    DEFF Research Database (Denmark)

    Castex, G.; Delabrouille, J.; Ganga, K.

    2013-01-01

    . The Planck satellite has provided hundreds of detections of the hot gas in clusters of galaxies via the thermal Sunyaev-Zel'dovich (tSZ) effect and is an ideal instrument for studying extended low-density media through the tSZ effect. In this paper we use the Planck data to search for signatures...... of this intercluster medium. We obtain a temperature of kT = 7.1 ± 0.9 keV (consistent with previous estimates) and a baryon density of (3.7 ± 0.2) × 10-4 cm -3. Conclusions. The Planck satellite mission has provided the first SZ detection of the hot and diffuse intercluster gas. © 2013 ESO....

  9. 一种分层分簇的组密钥管理方案%A HIERARCHICAL CLUSTERING-BASED GROUP KEY MANAGEMENT SCHEME

    Institute of Scientific and Technical Information of China (English)

    李珍格; 游林

    2014-01-01

    为了满足无线传感器网络组通信的安全,提出一种分层分簇的组密钥管理方案。该方案采用分层的体系结构,将组中节点分为管理层和普通层。BS通过构造特殊的组密钥多项式更新普通层组密钥,而管理层则采用二元单向函数进行组密钥的协商。分析表明,该方案很好满足了无线传感器网络中组密钥管理的前向安全性,后向安全性,并且减小了存储开销、计算开销和通信开销。%In this paper,a hierarchical clustering-based group key management scheme is proposed in order to satisfy the secure group communication in wireless sensor network.The proposed scheme adopts the hierarchical architecture and divides the nodes in the group into master-node layer and terminal layer.The group key of terminal layer is updated by constructing a special group key polynomial in BS,and the binary one-way function is used by the master-node layer for group key negotiation.Analysis demonstrates that the scheme well satisfies the forward security and backward security of the group key management in WSN,and reduces the storage overhead,computation overhead and communication overhead as well.

  10. Laser surface treatment and the resultant hierarchical topography of Ti grade 2 for biomedical application

    Science.gov (United States)

    Kuczyńska, Donata; Kwaśniak, Piotr; Marczak, Jan; Bonarski, Jan; Smolik, Jerzy; Garbacz, Halina

    2016-12-01

    Modern prosthesis often have a complex structure, where parts of an implant have different functional properties. This gradient of functional properties means that local surface modifications are required. Method presented in this study was develop to functionalize prefabricated elements with original roughness obtained by conventional treatments used to homogenize and clean surface of titanium implants. Demonstrated methodology results in multimodal, periodic grooved topography with roughness in a range from nano- to micrometers. The modified surfaces were characterized in terms of shape, roughness, wettability, surface energy and chemical composition. For this purpose, the following methods were used: scanning electron microscopy, optical profilometry, atomic force microscopy, contact angle measurements and X-ray photoelectron spectroscopy. Protein adsorption studies were conducted to determine the potential biomedical application of proposed method. In order to estimate the intensity and way of the protein adsorption process on different titanium surfaces, XPS studies and AFM measurements were performed. The systematic comparison of surface states and their osseointegration tendency will be useful to evaluate suitability of presented method as an single step treatment for local surface functionalization of currently produced implantable devices.

  11. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  12. 一种基于分层结构的Ad Hoc网络分簇路由协议研究%Research based on the hierarchical structure of the Ad Hoc network clustering routing protocol

    Institute of Scientific and Technical Information of China (English)

    冯永亮

    2015-01-01

    The traditional Ad Hoc network clustering routing protocol has low packet delivery ratio problem, this paper proposes a clustering routing protocol based on hierarchical structure. The advanced network layer using AODV routing protocol based backup, and the lower network layer adopts a smaller delay DSDV protocol. The simulation results show that the improved routing protocol improves the packet delivery rate, Shortening the end to end delay.%传统Ad Hoc网络分簇路由协议存在分组投递率低的问题,论文提出一种基于分层结构的分簇路由协议.高级网络层采用基于备份路由的AODV协议,而低级网络层则采用时延较小的DSDV协议.仿真结果显示,改进后的路由协议提高了分组投递率,缩短了端到端时延.

  13. Clustering of resting state networks.

    Directory of Open Access Journals (Sweden)

    Megan H Lee

    Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: 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.

  14. Semi-supervised consensus clustering for gene expression data analysis

    OpenAIRE

    Wang, Yunli; Pan, Youlian

    2014-01-01

    Background Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

  15. Quantitative and Chemical Fingerprint Analysis for the Quality Evaluation of Receptaculum Nelumbinis by RP-HPLC Coupled with Hierarchical Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Jin-Zhong Wu

    2013-01-01

    Full Text Available A simple and reliable method of high-performance liquid chromatography with photodiode array detection (HPLC-DAD was developed to evaluate the quality of Receptaculum Nelumbinis (dried receptacle of Nelumbo nucifera through establishing chromatographic fingerprint and simultaneous determination of five flavonol glycosides, including hyperoside, isoquercitrin, quercetin-3-O-β-d-glucuronide, isorhamnetin-3-O-β-d-galactoside and syringetin-3-O-β-d-glucoside. In quantitative analysis, the five components showed good regression (R > 0.9998 within linear ranges, and their recoveries were in the range of 98.31%–100.32%. In the chromatographic fingerprint, twelve peaks were selected as the characteristic peaks to assess the similarities of different samples collected from different origins in China according to the State Food and Drug Administration (SFDA requirements. Furthermore, hierarchical cluster analysis (HCA was also applied to evaluate the variation of chemical components among different sources of Receptaculum Nelumbinis in China. This study indicated that the combination of quantitative and chromatographic fingerprint analysis can be readily utilized as a quality control method for Receptaculum Nelumbinis and its related traditional Chinese medicinal preparations.

  16. HILIC-UPLC-MS/MS combined with hierarchical clustering analysis to rapidly analyze and evaluate nucleobases and nucleosides in Ginkgo biloba leaves.

    Science.gov (United States)

    Yao, Xin; Zhou, Guisheng; Tang, Yuping; Guo, Sheng; Qian, Dawei; Duan, Jin-Ao

    2015-02-01

    Ginkgo biloba leaf extract has been widely used in dietary supplements and more recently in some foods and beverages. In addition to the well-known flavonol glycosides and terpene lactones, G. biloba leaves are also rich in nucleobases and nucleosides. To determine the content of nucleobases and nucleosides in G. biloba leaves at trace levels, a reliable method has been established by using hydrophilic interaction ultra performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (HILIC-UPLC-TQ-MS/MS) working in multiple reaction monitoring mode. Eleven nucleobases and nucleosides were simultaneously determined in seven min. The proposed method was fully validated in terms of linearity, sensitivity, and repeatability, as well as recovery. Furthermore, hierarchical clustering analysis (HCA) was performed to evaluate and classify the samples according to the contents of the eleven chemical constituents. The established approach could be helpful for evaluation of the potential values as dietary supplements and the quality control of G. biloba leaves, which might also be utilized for the investigation of other medicinal herbs containing nucleobases and nucleosides.

  17. Avoiding progenitor bias: The structural and mass evolution of Brightest Group and Cluster Galaxies in Hierarchical models since z~1

    CERN Document Server

    Shankar, Francesco; Rettura, Alessandro; Bouillot, Vincent; Moreno, Jorge; Licitra, Rossella; Bernardi, Mariangela; Huertas-Company, Marc; Mei, Simona; Ascaso, Begoña; Sheth, Ravi; Delaye, Lauriane; Raichoor, Anand

    2015-01-01

    The mass and structural evolution of massive galaxies is one of the hottest topics in galaxy formation. This is because it may reveal invaluable insights into the still debated evolutionary processes governing the growth and assembly of spheroids. However, direct comparison between models and observations is usually prevented by the so-called "progenitor bias", i.e., new galaxies entering the observational selection at later epochs, thus eluding a precise study of how pre-existing galaxies actually evolve in size. To limit this effect, we here gather data on high-redshift brightest group and cluster galaxies, evolve their (mean) host halo masses down to z=0 along their main progenitors, and assign as their "descendants" local SDSS central galaxies matched in host halo mass. At face value, the comparison between high redshift and local data suggests a noticeable increase in stellar mass of a factor of >2 since z~1, and of >2.5 in mean effective radius. We then compare the inferred stellar mass and size growth ...

  18. Divisive Analysis (DIANA of hierarchical clustering and GPS data for level of service criteria of urban streets

    Directory of Open Access Journals (Sweden)

    Ashish Kumar Patnaik

    2016-03-01

    Full Text Available Level of Service (LOS for heterogeneous traffic flow on urban streets is not well defined in Indian context. Hence in this study an attempt is taken to classify urban road networks into number of street classes and average travel speeds on street segments into LOS categories. Divisive Analysis (DIANA Clustering is used for such classification of large amount of speed data collected using GPS receiver. DIANA algorithm and silhouette validation parameter are used to classify Free Flow Speeds (FFS into optimal number of classes and the same algorithm is applied on speed data to determine ranges of different LOS categories. Speed ranges for LOS categories (A–F expressed in percentage of FFS are found to be 90, 70, 50, 40, 25 and 20–25 respectively in the present study. On the other hand, in HCM (2000 it has been mentioned these values are 85 and above, 67–85, 50–67, 40–50, 30–40 and 30 and less percent respectively.

  19. High-performance supercapacitor and lithium-ion battery based on 3D hierarchical NH4F-induced nickel cobaltate nanosheet-nanowire cluster arrays as self-supported electrodes

    Science.gov (United States)

    Chen, Yuejiao; Qu, Baihua; Hu, Lingling; Xu, Zhi; Li, Qiuhong; Wang, Taihong

    2013-09-01

    A facile hydrothermal method is developed for large-scale production of three-dimensional (3D) hierarchical porous nickel cobaltate nanowire cluster arrays derived from nanosheet arrays with robust adhesion on Ni foam. Based on the morphology evolution upon reaction time, a possible formation process is proposed. The role of NH4F in formation of the structure has also been investigated based on different NH4F amounts. This unique structure significantly enhances the electroactive surface areas of the NiCo2O4 arrays, leading to better interfacial/chemical distributions at the nanoscale, fast ion and electron transfer and good strain accommodation. Thus, when it is used for supercapacitor testing, a specific capacitance of 1069 F g-1 at a very high current density of 100 A g-1 was obtained. Even after more than 10 000 cycles at various large current densities, a capacitance of 2000 F g-1 at 10 A g-1 with 93.8% retention can be achieved. It also exhibits a high-power density (26.1 kW kg-1) at a discharge current density of 80 A g-1. When used as an anode material for lithium-ion batteries (LIBs), it presents a high reversible capacity of 976 mA h g-1 at a rate of 200 mA g-1 with good cycling stability and rate capability. This array material is rarely used as an anode material. Our results show that this unique 3D hierarchical porous nickel cobaltite is promising for electrochemical energy applications.A facile hydrothermal method is developed for large-scale production of three-dimensional (3D) hierarchical porous nickel cobaltate nanowire cluster arrays derived from nanosheet arrays with robust adhesion on Ni foam. Based on the morphology evolution upon reaction time, a possible formation process is proposed. The role of NH4F in formation of the structure has also been investigated based on different NH4F amounts. This unique structure significantly enhances the electroactive surface areas of the NiCo2O4 arrays, leading to better interfacial/chemical distributions

  20. A climatology of surface ozone in the extra tropics: cluster analysis of observations and model results

    Directory of Open Access Journals (Sweden)

    O. A. Tarasova

    2007-08-01

    Full Text Available Important aspects of the seasonal variations of surface ozone are discussed. The underlying analysis is based on the long-term (1990–2004 ozone records of Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP and the World Data Center of Greenhouse Gases which do have a strong Northern Hemisphere bias. Seasonal variations are pronounced at most of the 114 locations for any time of the day. Seasonal-diurnal variability classification using hierarchical agglomeration clustering reveals 5 distinct clusters: clean/rural, semi-polluted non-elevated, semi-polluted semi-elevated, elevated and polar/remote marine types. For the cluster "clean/rural" the seasonal maximum is observed in April, both for night and day. For those sites with a double maximum or a wide spring-summer maximum, the one in spring appears both for day and night, while the one in summer is more pronounced for daytime and hence can be attributed to photochemical processes. For the spring maximum photochemistry is a less plausible explanation as no dependence of the maximum timing is observed. More probably the spring maximum is caused by dynamical/transport processes. Using data from the 3-D atmospheric chemistry general circulation model ECHAM5/MESSy1 covering the period of 1998–2005 a comparison has been performed for the identified clusters. For the model data four distinct classes of variability are detected. The majority of cases are covered by the regimes with a spring seasonal maximum or with a broad spring-summer maximum (with prevailing summer. The regime with winter–early spring maximum is reproduced by the model for southern hemispheric locations. Background and semi-polluted sites appear in the model in the same cluster. The seasonality in this model cluster is characterized by a pronounced spring (May maximum. For the model cluster that covers partly semi-elevated semi-polluted sites the role of the

  1. A climatology of surface ozone in the extra tropics: cluster analysis of observations and model results

    Directory of Open Access Journals (Sweden)

    O. A. Tarasova

    2007-12-01

    Full Text Available Important aspects of the seasonal variations of surface ozone are discussed. The underlying analysis is based on the long-term (1990–2004 ozone records of the Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP and the World Data Centre of Greenhouse Gases, which provide data mostly for the Northern Hemisphere. Seasonal variations are pronounced at most of the 114 locations at all times of the day. A seasonal-diurnal variations classification using hierarchical agglomeration clustering reveals 6 distinct clusters: clean background, rural, semi-polluted non-elevated, semi-polluted semi-elevated, elevated and polar/remote marine. For the "clean background" cluster the seasonal maximum is observed in March-April, both for night and day. For those sites with a double maximum or a wide spring-summer maximum, the spring maximum appears both for day and night, while the summer maximum is more pronounced for daytime and hence can be attributed to photochemical processes. The spring maximum is more likely caused by dynamical/transport processes than by photochemistry as it is observed in spring for all times of the day. We compare the identified clusters with corresponding data from the 3-D atmospheric chemistry general circulation model ECHAM5/MESSy1 covering the period of 1998–2005. For the model output as for the measurements 6 clusters are considered. The simulation shows at most of the sites a spring seasonal maximum or a broad spring-summer maximum (with higher summer mixing ratios. For southern hemispheric and polar remote locations the seasonal maximum in the simulation is shifted to spring, while the absolute mixing ratios are in good agreement with the measurements. The seasonality in the model cluster covering background locations is characterized by a pronounced spring (April–May maximum. For the model clusters which cover rural and semi-polluted sites the role of the

  2. New Results in Fuzzy Clustering Based on the Concept of Indistinguishability Relation

    Science.gov (United States)

    1984-01-01

    NEW RESULTS IN Fuzzy CLUSTERING BASED ON THE CONCEPT OF INDISTINGUISHABILITY RELATION KEYWORDS R . Lopez de Mantaras Facultat d ’Informatica...Universitat Politecnica de Barcelona Dulcet, 12. Barcelona-34. Spain. L. Valverde* Dept. de Matematiques i Estadistica Universitat Politecnica de... r -cluster that extend Ruspini’s definition (Ruspini, 1982). Our definition is based on the new concept of indis- tinguishability relation (Trillas

  3. First principles results of structural and electronic properties of ZnS clusters

    Indian Academy of Sciences (India)

    D L Lalsare; Anjali Kshirsagar

    2012-12-01

    We present results of the study of ZnS (1 ≤ ≤ 9) clusters, using the density functional formalism and projector augmented wave method within the generalized gradient approximation. Along with the structural and electronic properties, nature of bonding and overall stability of clusters has been studied.

  4. Segmenting Business Students Using Cluster Analysis Applied to Student Satisfaction Survey Results

    Science.gov (United States)

    Gibson, Allen

    2009-01-01

    This paper demonstrates a new application of cluster analysis to segment business school students according to their degree of satisfaction with various aspects of the academic program. The resulting clusters provide additional insight into drivers of student satisfaction that are not evident from analysis of the responses of the student body as a…

  5. High-performance supercapacitor and lithium-ion battery based on 3D hierarchical NH4F-induced nickel cobaltate nanosheet-nanowire cluster arrays as self-supported electrodes.

    Science.gov (United States)

    Chen, Yuejiao; Qu, Baihua; Hu, Lingling; Xu, Zhi; Li, Qiuhong; Wang, Taihong

    2013-10-21

    A facile hydrothermal method is developed for large-scale production of three-dimensional (3D) hierarchical porous nickel cobaltate nanowire cluster arrays derived from nanosheet arrays with robust adhesion on Ni foam. Based on the morphology evolution upon reaction time, a possible formation process is proposed. The role of NH4F in formation of the structure has also been investigated based on different NH4F amounts. This unique structure significantly enhances the electroactive surface areas of the NiCo2O4 arrays, leading to better interfacial/chemical distributions at the nanoscale, fast ion and electron transfer and good strain accommodation. Thus, when it is used for supercapacitor testing, a specific capacitance of 1069 F g(-1) at a very high current density of 100 A g(-1) was obtained. Even after more than 10,000 cycles at various large current densities, a capacitance of 2000 F g(-1) at 10 A g(-1) with 93.8% retention can be achieved. It also exhibits a high-power density (26.1 kW kg(-1)) at a discharge current density of 80 A g(-1). When used as an anode material for lithium-ion batteries (LIBs), it presents a high reversible capacity of 976 mA h g(-1) at a rate of 200 mA g(-1) with good cycling stability and rate capability. This array material is rarely used as an anode material. Our results show that this unique 3D hierarchical porous nickel cobaltite is promising for electrochemical energy applications.

  6. An updated catalog of M33 clusters and candidates: $UBVRI$ photometry, and some statistical results

    CERN Document Server

    Ma, Jun

    2012-01-01

    We present $UBVRI$ photometry for 392 star clusters and candidates in the field of M33, which are selected from the most recent star cluster catalog. In this catalog, the authors listed star clusters' parameters such as cluster positions, magnitudes and colors in the $UBVRIJHK_s$ filters, and so on. However, a large fraction of objects in this catalog do not have previously published photometry. Photometry is performed using archival images from the Local Group Galaxies Survey, which covers 0.8 deg$^2$ along the major axis of M33. Detailed comparisons show that, in general, our photometry is consistent with previous measurements. Positions (right ascension and declination) for some clusters are corrected here. Combined with previous literature, we constitute a large sample of M33 star clusters. Based on this cluster sample, we present some statistical results: none of the M33 youngest clusters ($\\sim 10^7$ yr) have masses approaching $10^5$ $M_{\\odot}$; roughly half the star clusters are consistent with the $...

  7. Weighted Clustering

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  8. Discovering hierarchical structure in normal relational data

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Herlau, Tue; Mørup, Morten

    2014-01-01

    Hierarchical clustering is a widely used tool for structuring and visualizing complex data using similarity. Traditionally, hierarchical clustering is based on local heuristics that do not explicitly provide assessment of the statistical saliency of the extracted hierarchy. We propose a non-param...

  9. The Electron Drift Instrument on Cluster: overview of first results

    Directory of Open Access Journals (Sweden)

    G. Paschmann

    Full Text Available EDI measures the drift velocity of artificially injected electron beams. From this drift velocity, the perpendicular electric field and the local magnetic field gradients can be deduced when employing different electron energies. The technique requires the injection of two electron beams at right angles to the magnetic field and the search for those directions within the plane that return the beams to their associated detectors after one or more gyrations. The drift velocity is then derived from the directions of the two beams and/or from the difference in their times-of-flight, measured via amplitude-modulation and coding of the emitted electron beams and correlation with the signal from the returning electrons. After careful adjustment of the control parameters, the beam recognition algorithms, and the onboard magnetometer calibrations during the commissioning phase, EDI is providing excellent data over a wide range of conditions. In this paper, we present first results in a variety of regions ranging from the polar cap, across the magnetopause, and well into the magnetosheath.

    Key words. Electron drift velocity (electric fields; plasma convection; instruments and techniques

  10. Evolution of star cluster systems in isolated galaxies: first results from direct N-body simulations

    Science.gov (United States)

    Rossi, L. J.; Bekki, K.; Hurley, J. R.

    2016-11-01

    The evolution of star clusters is largely affected by the tidal field generated by the host galaxy. It is thus in principle expected that under the assumption of a `universal' initial cluster mass function the properties of the evolved present-day mass function of star cluster systems should show a dependence on the properties of the galactic environment in which they evolve. To explore this expectation, a sophisticated model of the tidal field is required in order to study the evolution of star cluster systems in realistic galaxies. Along these lines, in this work we first describe a method developed for coupling N-body simulations of galaxies and star clusters. We then generate a data base of galaxy models along the Hubble sequence and calibrate evolutionary equations to the results of direct N-body simulations of star clusters in order to predict the clusters' mass evolution as function of the galactic environment. We finally apply our methods to explore the properties of evolved `universal' initial cluster mass functions and any dependence on the host galaxy morphology and mass distribution. The preliminary results show that an initial power-law distribution of the masses `universally' evolves into a lognormal distribution, with the properties correlated with the stellar mass and stellar mass density of the host galaxy.

  11. The initial mass function of young open clusters in the Galaxy: A preliminary result

    CERN Document Server

    Lim, Beomdu; Hur, Hyeonoh; Park, Byeong-Gon

    2015-01-01

    The initial mass function (IMF) is an essential tool with which to study star formation processes. We have initiated the photometric survey of young open clusters in the Galaxy, from which the stellar IMFs are obtained in a homogeneous way. A total of 16 famous young open clusters have preferentially been studied up to now. These clusters have a wide range of surface densities (log sigma = -1 to 3 [stars pc^2] for stars with mass larger than 5M_sun) and cluster masses (M_cl = 165 to 50,000M_sun), and also are distributed in five different spiral arms in the Galaxy. It is possible to test the dependence of star formation processes on the global properties of individual clusters or environmental conditions. We present a preliminary result on the variation of the IMF in this paper.

  12. Hierarchical clustering of genetic diversity associated to different levels of mutation and recombination in Escherichia coli: a study based on Mexican isolates.

    Science.gov (United States)

    González-González, Andrea; Sánchez-Reyes, Luna L; Delgado Sapien, Gabriela; Eguiarte, Luis E; Souza, Valeria

    2013-01-01

    Escherichia coli occur as either free-living microorganisms, or within the colons of mammals and birds as pathogenic or commensal bacteria. Although the Mexican population of intestinal E. coli maintains high levels of genetic diversity, the exact mechanisms by which this occurs remain unknown. We therefore investigated the role of homologous recombination and point mutation in the genetic diversification and population structure of Mexican strains of E. coli. This was explored using a multi locus sequence typing (MLST) approach in a non-outbreak related, host-wide sample of 128 isolates. Overall, genetic diversification in this sample appears to be driven primarily by homologous recombination, and to a lesser extent, by point mutation. Since genetic diversity is hierarchically organized according to the MLST genealogy, we observed that there is not a homogeneous recombination rate, but that different rates emerge at different clustering levels such as phylogenetic group, lineage and clonal complex (CC). Moreover, we detected clear signature of substructure among the A+B1 phylogenetic group, where the majority of isolates were differentiated into four discrete lineages. Substructure pattern is revealed by the presence of several CCs associated to a particular life style and host as well as to different genetic diversification mechanisms. We propose these findings as an alternative explanation for the maintenance of the clear phylogenetic signal of this species despite the prevalence of homologous recombination. Finally, we corroborate using both phylogenetic and genetic population approaches as an effective mean to establish epidemiological surveillance tailored to the ecological specificities of each geographic region.

  13. Interpolation centers' selection using hierarchical curvature-based clustering Selección de centros de interpolacion mediante agrupamiento jerárquico basado en curvatura

    Directory of Open Access Journals (Sweden)

    Juan C. Rodríguez

    2010-07-01

    Full Text Available Es ampliamente conocido que algunos campos relacionados con aplicaciones de gráficos realistas requieren modelos tridimensionales altamente detallados. Las tecnologías para esto están bien desarrolladas, sin embargo, en algunos casos los escáneres láser obtienen modelos complejos formados por millones de puntos, por lo que son computacionalmente intratables. En estos casos es conveniente obtener un conjunto reducido de estas muestras con las que reconstruir la superficie de la función. Obtener un enfoque de reducción adecuado que posea un equilibrio entre la pérdida de precisión de la función reconstruida, y el costo computacional es un problema no trivial. En este artículo presentamos un método jerárquico de aglomeración a través de la selección de centros mediante la geométrica, la distribución y la estimación de curvatura de las muestras en el espacio 3D.It is widely known that some fields related to graphic applications require realistic and full detailed three-dimensional models. Technologies for this kind of applications exist. However, in some cases, laser scanner get complex models composed of million of points, making its computationally difficult. In these cases, it is desirable to obtain a reduced set of these samples to reconstruct the function's surface. An appropriate reduction approach with a non-significant loss of accuracy in the reconstructed function with a good balance of computational load is usually a non-trivial problem. In this article, a hierarchical clustering based method by the selection of center using the geometric distribution and curvature estimation of the samples in the 3D space is described.

  14. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

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

  15. Community detection algorithm based on hierarchical clustering under signal missing in propagating process%传播过程中信号缺失的层次聚类社区发现算法

    Institute of Scientific and Technical Information of China (English)

    康茜; 李德玉; 王素格; 冀庆斌

    2015-01-01

    社区发现是社会网络分析的一个基本任务,而社区结构探测是社区发现的一个关键问题。将社区结构中的结点看作信号源,针对信号传递过程中存在信号缺失情况,提出了一种层次聚类社区发现算法。该算法通过度中心性来度量节点接收信号的概率,用于量化节点接受信号过程中的缺失值。经过信号传递,使网络的拓扑结构转化为向量间的几何关系,在此基础上,使用层次聚类算法用于发现社区。为了验证SMHC算法的有效性,通过在三个数据集上与SHC算法、CNM算法、GN算法、Similar算法进行比较,实验结果表明,SMHC算法在一定程度上提高了社区发现的正确率。%Community identification is a basic task of social network analysis, meanwhile the community structure detec-tion is a key problem of community identification. Each node in the community structure is regarded as the signal source. A hierarchical clustering community algorithm is proposed in order to settle the problem of signal missing in the process of signal transmission. The algorithm measures the probability of receiving signals of nodes by degree centrality to quantify the signal missing values. After the signal transmission, the topology of the network is transformed into geometric relation-ships among the vectors. On the basis, the hierarchical clustering algorithm is used to find the community structure. In order to validate the proposed method, this paper compares it with SHC algorithm, CNM algorithm, GN algorithm and Similar algorithm. Under three real networks, the Zachary Club, American Football and Netscience, the experimental results indi-cate that SMHC algorithm can effectively improve precision.

  16. A semantics-based method for clustering of Chinese web search results

    Science.gov (United States)

    Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

    2014-01-01

    Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

  17. Cluster-size distributions for irreversible cooperative filling of lattices. I. Exact one-dimensional results for coalescing clusters

    Energy Technology Data Exchange (ETDEWEB)

    Nord, R.S.; Hoffman, D.K.; Evans, J.W.

    1985-06-01

    We consider processes where the sites of an infinite, uniform lattice are filled irreversibly and cooperatively, with the rate of adsorption at a site depending on the state of its nearest neighbors (only). The asymmetry between empty and filled sites, associated with irreversibility, leads one to consider the closed infinite coupled hierarchies of rate equations for probabilities of connected and singly, doubly, etc., disconnected empty subconfigurations and results in an empty-site-shielding property. The latter allows exact solutions, via truncation, of these equations in one dimension and is used here to determine probabilities of filled s-tuples, f/sub s/ (f/sub 1/equivalenttheta is the coverage), and thus of clusters of exactly s filled sites, n/sub s/equivalentf/sub s/-2f/sub s+1/+f/sub s+2/ for s< or =13 and 11, respectively. When all rates are nonzero so that clusters can coalesce, the f/sub s/ and n/sub s/ distributions decay exponentially as s..-->..infinity, and we can accurately estimate the asymptotic decay rate lambda(theta)equivalent lim/sub s/..-->..infinity f/sub s+1//f/sub s/equivalent lim/sub s/..-->..infinity n/sub s+1//n/sub s/, where 0 = lambda(0)< or =lambda(theta)< or =lambda(1) = 1. Divergent behavior of the average cluster size, as theta..-->..1, is also considered.

  18. Hierarchical Neural Regression Models for Customer Churn Prediction

    Directory of Open Access Journals (Sweden)

    Golshan Mohammadi

    2013-01-01

    Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

  19. Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network.

    Science.gov (United States)

    Balaguer, Jan; Spiers, Hugo; Hassabis, Demis; Summerfield, Christopher

    2016-05-18

    Planning allows actions to be structured in pursuit of a future goal. However, in natural environments, planning over multiple possible future states incurs prohibitive computational costs. To represent plans efficiently, states can be clustered hierarchically into "contexts". For example, representing a journey through a subway network as a succession of individual states (stations) is more costly than encoding a sequence of contexts (lines) and context switches (line changes). Here, using functional brain imaging, we asked humans to perform a planning task in a virtual subway network. Behavioral analyses revealed that humans executed a hierarchically organized plan. Brain activity in the dorsomedial prefrontal cortex and premotor cortex scaled with the cost of hierarchical plan representation and unique neural signals in these regions signaled contexts and context switches. These results suggest that humans represent hierarchical plans using a network of caudal prefrontal structures. VIDEO ABSTRACT.

  20. Planck Intermediate Results. IV. The XMM-Newton validation programme for new Planck clusters

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartlett, J G; Battaner, E; Benabed, K; Benoît, A; Bernard, J -P; Bikmaev, I; Böhringer, H; Bonaldi, A; Borgani, S; Borrill, J; Bouchet, F R; Brown, M L; Burigana, C; Butler, R C; Cabella, P; Carvalho, P; Catalano, A; Cayón, L; Chamballu, A; Chary, R -R; Chiang, L -Y; Chon, G; Christensen, P R; Clements, D L; Colafrancesco, S; Colombi, S; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Davis, R J; de Bernardis, P; de Gasperis, G; de Zotti, G; Delabrouille, J; Démoclès, J; Désert, F -X; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Douspis, M; Dupac, X; Enßlin, T A; Eriksen, H K; Finelli, F; Flores-Cacho, I; Frailis, M; Franceschi, E; Frommert, M; Galeotta, S; Ganga, K; Génova-Santos, R T; Giraud-Héraud, Y; González-Nuevo, J; González-Riestra, R; Górski, K M; Gregorio, A; Hansen, F K; Harrison, D; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hornstrup, A; Hovest, W; Huffenberger, K M; Hurier, G; Jaffe, A H; Jagemann, T; Jones, W C; Juvela, M; Kneissl, R; Knoche, J; Knox, L; Kunz, M; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lasenby, A; Lawrence, C R; Jeune, M Le; Leach, S; Leonardi, R; Liddle, A; Lilje, P B; Linden-Vornle, M; López-Caniego, M; Luzzi, G; Macías-Pérez, J F; Maino, D; Mann, R; Marleau, F; Marshall, D J; Martínez-González, E; Masi, S; Massardi, M; Matarrese, S; Mazzotta, P; Mei, S; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Morgante, G; Mortlock, D; Munshi, D; Naselsky, P; Nati, F; Norgaard-Nielsen, H U; Noviello, F; Osborne, S; Pajot, F; Paoletti, D; Perdereau, O; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Platania, P; Pointecouteau, E; Polenta, G; Popa, L; Poutanen, T; Pratt, G W; Prunet, S; Puget, J -L; Reinecke, M; Remazeilles, M; Renault, C; Ricciardi, S; Rocha, G; Rosset, C; Rossetti, M; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Savini, G; Scott, D; Smoot, G F; Stanford, A; Stivoli, F; Sudiwala, R; Sunyaev, R; Sutton, D; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Valenziano, L; Van Tent, B; Vielva, P; Villa, F; Vittorio, N; Wade, L A; Wandelt, B D; Welikala, N; Weller, J; White, S D M; Yvon, D; Zacchei, A; Zonca, A

    2012-01-01

    We present the final results from the XMM-Newton validation follow-up of new Planck cluster candidates. We observed 15 new candidates, detected with signal-to-noise ratios between 4.0 and 6.1 in the 15.5-month nominal Planck survey. The candidates were selected using ancillary data flags derived from the ROSAT All Sky Survey (RASS) and Digitized Sky Survey all-sky maps, with the aim of pushing into the low SZ flux, high- z regime and testing RASS flags as indicators of candidate reliability. 14 new clusters were detected by XMM-Newton, 10 single clusters and 2 double systems. Redshifts from X-ray spectroscopy lie in the range 0.2 to 0.9, with six clusters at z>0.5. Estimated M500 ranges from 2.5 X 10^14 to 8 X 10^14 Msun. We discuss our results in the context of the full XMM validation programme, in which 51 new clusters have been detected. This includes 4 double and 2 triple systems, some of which are chance projections on the sky of clusters at different redshifts. Association with a source from the RASS-Br...

  1. Chandra Observation of the Globular Cluster NGC 6440 and a Comparison with Other Recent Results

    CERN Document Server

    Pooley, D; Verbunt, F; Homer, L; Margon, B; Gaensler, B M; Kaspi, V M; Miller, J M; Fox, D W; Van der Klis, M; Pooley, David; Lewin, Walter H. G.; Verbunt, Frank; Homer, Lee; Margon, Bruce; Gaensler, Bryan M.; Kaspi, Victoria M.; Miller, Jon M.; Fox, Derek W.; Klis, Michiel van der

    2001-01-01

    As part of our campaign to determine the nature of the various source populations of the low-luminosity globular cluster X-ray sources, we have obtained a Chandra X-ray Observatory ACIS-S3 image of the globular cluster NGC 6440. We detect 24 sources to a limiting luminosity of ~2 times 10^31 erg/s (0.5-2.5keV) inside the cluster's half-mass radius, all of which lie within ~2 core radii of the cluster center. We also find excess emission in and around the core which could be due to unresolved point sources. Based upon X-ray luminosities and colors, we conclude that there are 4-5 likely quiescent low-mass X-ray binaries and that most of the other sources are cataclysmic variables. We compare these results to Chandra results from other globular clusters and find the X-ray luminosity functions differ among the clusters.

  2. Exploring the profiles of nurses' job satisfaction in Macau: results of a cluster analysis.

    Science.gov (United States)

    Chan, Moon Fai; Leong, Sok Man; Luk, Andrew Leung; Yeung, Siu Ming; Van, Iat Kio

    2010-02-01

    To determine whether definable subtypes exist within a cohort of nurses with regard to factors associated with nurses' job satisfaction patterns and to compare whether these factors vary between nurses in groups with different profiles. Globally, the health care system is experiencing major changes and influence nurses' job satisfaction and may ultimately affect the quality of nursing care for patients. A descriptive survey. Data were collected using a self-reported structured questionnaire. Nurses were recruited in two hospitals in Macao. Two main outcome variables were collected: Predisposing characteristics and five components on job satisfaction outcomes. A cluster analysis yielded two clusters (n = 649). Cluster 1 consisted of 60.6% (n = 393) and Cluster 2 of 39.4% (n = 256) of the nurses. Cluster 1 nurses were younger, more educated and had less work experience and more intention to change their career than nurses in Cluster 2. Cluster 2 nurses had more work experiences, were of more senior grade and were more satisfied with their current job in terms of peer supports, autonomy and professional opportunities, scheduling and relationships with team members than nurses in Cluster 1. Findings might help by providing important information for health care managers to identify strategies/methods to target a specific group of nurses in hopes of increasing their job satisfaction levels. As a long-term investment, hospital management has to promote work environments that support job satisfaction to attract nurses and thereby improve the quality of nursing care. The results of this study might provide hospital managers with a model to design specified interventions to improve nurses' job satisfaction.

  3. 基于多空间多层次谱聚类的非监督SAR图像分割算法%Segmentation method for SAR images based on unsupervised spectral clustering of multi-hierarchical region

    Institute of Scientific and Technical Information of China (English)

    田玲; 邓旌波; 廖紫纤; 石博; 何楚

    2013-01-01

    提出了一种基于多层区域谱聚类的非监督SAR图像分割算法(multi-space and multi-hierarchical region based spectral clustering,MSMHSC).该算法首先在特征与几何空间求距离,快速获得初始过分割区域,然后在过分割区域的谱空间上进行聚类,最终实现非监督的SAR图像分割.该方法计算复杂度小,无须训练样本,使用层次化思想使其能更充分地利用SAR图像各类先验与似然信息.在MSTAR真实SAR数据集上的实验验证了该算法的快速性和有效性.%This paper proposed a method based on the hierarchical clustering concept.First,it over-segmented the source image into many small regions.And then,it conducted a spectral clustering algorithm on those regions.The algorithm was tested on the MSTAR SAR data set,and was proved to be fast and efficient.

  4. Argon cluster ion beams for organic depth profiling: results from a VAMAS interlaboratory study.

    Science.gov (United States)

    Shard, Alexander G; Havelund, Rasmus; Seah, Martin P; Spencer, Steve J; Gilmore, Ian S; Winograd, Nicholas; Mao, Dan; Miyayama, Takuya; Niehuis, Ewald; Rading, Derk; Moellers, Rudolf

    2012-09-18

    The depth profiling of organic materials with argon cluster ion sputtering has recently become widely available with several manufacturers of surface analytical instrumentation producing sources suitable for surface analysis. In this work, we assess the performance of argon cluster sources in an interlaboratory study under the auspices of VAMAS (Versailles Project on Advanced Materials and Standards). The results are compared to a previous study that focused on C(60)(q+) cluster sources using similar reference materials. Four laboratories participated using time-of-flight secondary-ion mass spectrometry for analysis, three of them using argon cluster sputtering sources and one using a C(60)(+) cluster source. The samples used for the study were organic multilayer reference materials consisting of a ∼400-nm-thick Irganox 1010 matrix with ∼1 nm marker layers of Irganox 3114 at depths of ∼50, 100, 200, and 300 nm. In accordance with a previous report, argon cluster sputtering is shown to provide effectively constant sputtering yields through these reference materials. The work additionally demonstrates that molecular secondary ions may be used to monitor the depth profile and depth resolutions approaching a full width at half maximum (fwhm) of 5 nm can be achieved. The participants employed energies of 2.5 and 5 keV for the argon clusters, and both the sputtering yields and depth resolutions are similar to those extrapolated from C(60)(+) cluster sputtering data. In contrast to C(60)(+) cluster sputtering, however, a negligible variation in sputtering yield with depth was observed and the repeatability of the sputtering yields obtained by two participants was better than 1%. We observe that, with argon cluster sputtering, the position of the marker layers may change by up to 3 nm, depending on which secondary ion is used to monitor the material in these layers, which is an effect not previously visible with C(60)(+) cluster sputtering. We also note that electron

  5. Cluster-size distributions for irreversible cooperative filling of lattices. I. Exact one-dimensional results for coalescing clusters

    Science.gov (United States)

    Nord, R. S.; Hoffman, D. K.; Evans, J. W.

    1985-06-01

    We consider processes where the sites of an infinite, uniform lattice are filled irreversibly and cooperatively, with the rate of adsorption at a site depending on the state of its nearest neighbors (only). The asymmetry between empty and filled sites, associated with irreversibility, leads one to consider the closed infinite coupled hierarchies of rate equations for probabilities of connected and singly, doubly, etc., disconnected empty subconfigurations and results in an empty-site-shielding property. The latter allows exact solutions, via truncation, of these equations in one dimension and is used here to determine probabilities of filled s-tuples, fs (f1≡θ is the coverage), and thus of clusters of exactly s filled sites, ns≡fs-2fs+1+fs+2 for s∞, and we can accurately estimate the asymptotic decay rate λ(θ)≡ lims-->∞ fs+1/fs≡ lims-->∞ ns+1/ns, where 0=λ(0)behavior of the average cluster size, as θ-->1, is also considered. In addition, we develop a novel technique to determine directly the asymptotic decay rate λ(θ) and indicate its extension to higher-dimensional irreversible cooperative filling (and to other dynamic processes on lattices).

  6. Hierarchical photocatalysts.

    Science.gov (United States)

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

    As a green and sustainable technology, semiconductor-based heterogeneous photocatalysis has received much attention in the last few decades because it has potential to solve both energy and environmental problems. To achieve efficient photocatalysts, various hierarchical semiconductors have been designed and fabricated at the micro/nanometer scale in recent years. This review presents a critical appraisal of fabrication methods, growth mechanisms and applications of advanced hierarchical photocatalysts. Especially, the different synthesis strategies such as two-step templating, in situ template-sacrificial dissolution, self-templating method, in situ template-free assembly, chemically induced self-transformation and post-synthesis treatment are highlighted. Finally, some important applications including photocatalytic degradation of pollutants, photocatalytic H2 production and photocatalytic CO2 reduction are reviewed. A thorough assessment of the progress made in photocatalysis may open new opportunities in designing highly effective hierarchical photocatalysts for advanced applications ranging from thermal catalysis, separation and purification processes to solar cells.

  7. Optimizd Design of Power Scheduling in WSN Based on Sink Root Data Tree with Hierarchical Clustering%Sink根数据聚集树分层的WSN电力调度优化设计

    Institute of Scientific and Technical Information of China (English)

    朱文忠

    2014-01-01

    为提高电力数据调度效率,缩短电力数据调度延时,提出一种改进的无通信冲突的分布式电力数据聚集调度近似算法,采用Sink根数据聚集树对无线传感器网络中各个节点电力资源数据进行分层数据调度,根据分布式数据集对各个电力节点之间的控制信息进行不断融合处理,在最大独立集的基础上建立一棵根在Sink的数据聚集树。每个节点分配一个时间片,使该节点能在无通信冲突的情况下传输数据。仿真实验表明,采用改进算法得到的聚集延时明显减小,有效保证了电力调度控制的实时性,电力信息数据分层融合度能达到90%以上,而改进前的算法只有10%~50%之间。%In order to improve the power data scheduling efficiency, shorten the power data scheduling delay, and improve matching and integration degree, and improved power scheduling optimization design method based on Sink root data tree hierarchical clustering was proposed for improve the management efficiency. We established a tree root in the Sink data ag-gregation tree based on the maximum independent set. Each node was assigned a time slice, so that the node could transmit data in the absence of communication conflict situations. Simulation results show that the improved algorithm has signifi-cantly reduced aggregation delay, and it has effectively ensured the real-time dispatching control, and the data hierarchical fusion degree can reach more than 90%, while the former algorithm is only 10%~50%.

  8. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

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

    Science.gov (United States)

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

    2017-01-01

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

  10. Preliminary Cluster Size and Efficiencies results of CMS RPC at GIF++

    CERN Document Server

    Gonzalez Blanco Gonzalez, Genoveva

    2016-01-01

    A brief description and first preliminary results of the Efficiencies and Cluster Size measurements of the CMS Resistive Plate Chambers, will be presented inside the Gamma Irradiation Facility GIF++ at CERN. Preliminary studies that sets the base performance measurements of CMS RPC for starting aging studies.

  11. 水声传感器网络簇头分层通信模式路由算法%Routing Protocol of Hierarchical Cluster-Communication Model in the Underwater Acoustic Sensor Network

    Institute of Scientific and Technical Information of China (English)

    马绅惟; 刘广钟

    2014-01-01

    Routing protocol plays a very important role in underwater acoustic sensor networks. Based on the traditional TEEN protocol, a new routing protocol named HCM-TEEN(Hierarchical Cluster-communication Model on TEEN) has been put forward. The improved algorithm sets a new threshold function on the basis of the process of cluster candidate and the cluster elimination, and then introduces a Hierarchical Cluster-communication model in the period of data transmission to optimize the routing process. The experiment by the Matlab proved that HCM-TEEN performed better than the traditional algorithm on the network lifetime and the network average residual energy.%路由协议在水声传感器网络研究领域中扮演着非常重要的角色。基于传统的TEEN协议路由算法,提出了水声传感器网络中簇头分层通信模式的路由算法(HCM-TEEN)。新算法从簇头候选与淘汰过程入手,设置新的阈值函数。在簇头确定完成后,在数据传输阶段引入簇头分层通信模式,从距离和能量的角度上优化路由选择。通过Matlab仿真实验显示, HCM-TEEN算法与传统的算法相比在网络生命周期和节点平均剩余能量上都更具优越性。

  12. Searching for globular cluster-like abundance patterns in young massive clusters - II. Results from the Antennae galaxies

    Science.gov (United States)

    Lardo, C.; Cabrera-Ziri, I.; Davies, B.; Bastian, N.

    2017-06-01

    The presence of multiple populations (MPs) with distinctive light element abundances is a widespread phenomenon in clusters older than 6 Gyr. Clusters with masses, luminosities, and sizes comparable to those of ancient globulars are still forming today. None the less, the presence of light element variations has been poorly investigated in such young systems, even if the knowledge of the age at which this phenomenon develops is crucial for theoretical models on MPs. We use J-band integrated spectra of three young (7-40 Myr) clusters in NGC 4038 to look for Al variations indicative of MPs. Assuming that the large majority (≥70 per cent) of stars are characterized by high Al content - as observed in Galactic clusters with comparable mass; we find that none of the studied clusters show significant Al variations. Small Al spreads have been measured in all the six young clusters observed in the near-infrared. While it is unlikely that young clusters only show low Al whereas old ones display different levels of Al variations; this suggests the possibility that MPs are not present at such young ages at least among the high-mass stellar component. Alternatively, the fraction of stars with field-like chemistry could be extremely large, mimicking low Al abundances in the integrated spectrum. Finally, since the near-infrared stellar continuum of young clusters is almost entirely due to luminous red supergiants, we can also speculate that MPs only manifest themselves in low-mass stars due to some evolutionary mechanism.

  13. Biomedical ontology improves biomedical literature clustering performance: a comparison study.

    Science.gov (United States)

    Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

    2007-01-01

    Document clustering has been used for better document retrieval and text mining. In this paper, we investigate if a biomedical ontology improves biomedical literature clustering performance in terms of the effectiveness and the scalability. For this investigation, we perform a comprehensive comparison study of various document clustering approaches such as hierarchical clustering methods, Bisecting K-means, K-means and Suffix Tree Clustering (STC). According to our experiment results, a biomedical ontology significantly enhances clustering quality on biomedical documents. In addition, our results show that decent document clustering approaches, such as Bisecting K-means, K-means and STC, gains some benefit from the ontology while hierarchical algorithms showing the poorest clustering quality do not reap the benefit of the biomedical ontology.

  14. Cluster commences operations : first exciting results to be announced at a media event in Paris

    Science.gov (United States)

    2001-02-01

    During the meeting, the ESA Director of Science Professor Roger-Maurice Bonnet and representatives of the Cluster project and the science teams will summarise Cluster's quest to investigate the Sun-Earth connection, describe the current status of this unique mission and present some of the exciting results that have already been obtained from the mini-flotilla. Cluster Background Launched in pairs last summer, the Cluster quartet - Salsa, Samba, Rumba and Tango - have recently completed a highly complex check-out which involved 105 separate spacecraft manoeuvres - an all-time record. After deployment of 16 45-metre wire booms and in-orbit testing of 44 scientific instruments (two more world records), the commissioning phase is now completed and scientists are beginning to see the fruits of their labour. During the next two years, Cluster will join ESA's Solar and Heliospheric Observatory (SOHO) spacecraft in exploring the interaction between Earth's magnetic field and the electrically charged particles swept along in the solar wind. This will be a particularly hectic and exciting period, since it coincides with the peak of the 11-year cycle of solar activity. At such times, explosive solar flares and coronal mass ejections buffet our planet, potentially causing widespread power cuts, disrupting radio and satellite communications and generating colourful auroral displays. By flying in tetrahedral formation, the Cluster quartet will provide the most detailed information ever obtained about the physical processes that take place as swarms of energetic particles invade near-Earth space. For the first time, scientists will be able to study in three dimensions the rapidly unfolding events taking place between 19 000 and 119 000 kilometres above our heads.

  15. Detect overlapping and hierarchical community structure in networks

    CERN Document Server

    Shen, Huawei; Cai, Kai; Hu, Mao-Bin

    2008-01-01

    Clustering and community structure is crucial for many network systems and the related dynamic processes. It has been shown that communities are usually overlapping and hierarchical. However, previous methods investigate these two properties of community structure separately. This paper propose an algorithm (EAGLE) to detect both the overlapping and hierarchical properties of complex community structure together. This algorithm deals with the set of maximal cliques and adopts an agglomerative framework. The quality function of modularity is extended to evaluate the goodness of a cover. The examples of application to real world networks give excellent results.

  16. Planck Intermediate Results. I. Further validation of new Planck clusters with XMM-Newton

    CERN Document Server

    Aghanim, N; Ashdown, M; Atrio-Barandela, F; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartlett, J G; Battaner, E; Bernard, J -P; Böhringer, H; Bonaldi, A; Borrill, J; Bourdin, H; Brown, M L; Burigana, C; Butler, R C; Cabella, P; Cardoso, J -F; Carvalho, P; Catalano, A; Cayón, L; Chamballu, A; Chary, R -R; Chiang, L -Y; Chon, G; Christensen, P R; Clements, D L; Colafrancesco, S; Colombi, S; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Davis, R J; de Bernardis, P; de Gasperis, G; de Zotti, G; Delabrouille, J; Démoclés, J; Désert, F -X; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Douspis, M; Dupac, X; Enßlin, T A; Eriksen, H K; Finelli, F; Flores-Cacho, I; Forni, O; Fosalba, P; Frailis, M; Fromenteau, S; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; González-Nuevo, J; González-Riestra, R; Gruppuso, A; Hansen, F K; Harrison, D; Hempel, A; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hornstrup, A; Huffenberger, K M; Hurier, G; Jasche, J; Juvela, M; Keihänen, E; Kisner, T S; Kneissl, R; Knoche, J; Knox, L; Kurki-Suonio, H; Lähteenmäki, A; Lamarre, J -M; Lasenby, A; Leonardi, R; Liddle, A; Lilje, P B; López-Caniego, M; Luzzi, G; Macías-Pérez, J F; Maino, D; Mann, R; Marleau, F; Marshall, D J; Martínez-González, E; Masi, S; Massardi, M; Matarrese, S; Matthai, F; Mazzotta, P; Meinhold, P R; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Naselsky, P; Natoli, P; Nørgaard-Nielsen, H U; Noviello, F; Osborne, S; Pasian, F; Patanchon, G; Perdereau, O; Perrotta, F; Piacentini, F; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Popa, L; Poutanen, T; Pratt, G W; Rachen, J P; Rebolo, R; Reinecke, M; Remazeilles, M; Renault, C; Ricciardi, S; Riller, T; Ristorcelli, I; Rosset, C; Rossetti, M; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Savini, G; Schaefer, B M; Scott, D; Smoot, G F; Starck, J -L; Stivoli, F; Sutton, D; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Valenziano, L; Van Tent, B; Vielva, P; Villa, F; Vittorio, N; Wandelt, B D; Weller, J; Yvon, D; Zacchei, A

    2011-01-01

    We present further results from the ongoing XMM-Newton validation follow-up of Planck cluster candidates, detailing X-ray observations of eleven candidates detected at a signal-to-noise ratio of 4.5results. Ten of the candidates are found to be bona fide clusters lying below the RASS flux limit. Redshift estimates are available for all confirmed systems via X-ray Fe-line spectroscopy. They lie in the redshift range 0.19clusters up to high z . The X-ray properties of the new clusters appear to be similar to previous new detections by Planck at lower z and higher SZ flux: the majority are X-ray underluminous for their mass and have a disturbed morphology. We detect a first indication for Malmquist bias in the Y_SZ-Y_X ...

  17. Multiple dynamical time-scales in networks with hierarchically nested modular organization

    Indian Academy of Sciences (India)

    Sitabhra Sinha; Swarup Poria

    2011-11-01

    Many natural and engineered complex networks have intricate mesoscopic organization, e.g., the clustering of the constituent nodes into several communities or modules. Often, such modularity is manifested at several different hierarchical levels, where the clusters defined at one level appear as elementary entities at the next higher level. Using a simple model of a hierarchical modular network, we show that such a topological structure gives rise to characteristic time-scale separation between dynamics occurring at different levels of the hierarchy. This generalizes our earlier result for simple modular networks, where fast intramodular and slow intermodular processes were clearly distinguished. Investigating the process of synchronization of oscillators in a hierarchical modular network, we show the existence of as many distinct time-scales as there are hierarchical levels in the system. This suggests a possible functional role of such mesoscopic organization principle in natural systems, viz., in the dynamical separation of events occurring at different spatial scales.

  18. TWO-STAGE CHARACTER CLASSIFICATION : A COMBINED APPROACH OF CLUSTERING AND SUPPORT VECTOR CLASSIFIERS

    NARCIS (Netherlands)

    Vuurpijl, L.; Schomaker, L.

    2000-01-01

    This paper describes a two-stage classification method for (1) classification of isolated characters and (2) verification of the classification result. Character prototypes are generated using hierarchical clustering. For those prototypes known to sometimes produce wrong classification results, a

  19. Dynamic Organization of Hierarchical Memories.

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2016-01-01

    In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a "dynamic categorization"; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity.

  20. GLOBULAR CLUSTER POPULATIONS: FIRST RESULTS FROM S{sup 4}G EARLY-TYPE GALAXIES

    Energy Technology Data Exchange (ETDEWEB)

    Zaritsky, Dennis [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Aravena, Manuel [Núcleo de Astronomía, Facultad de Ingeniería, Universidad Diego Portales, Avenida Ejército 441, Santiago (Chile); Athanassoula, E.; Bosma, Albert [Aix Marseille Université, CNRS, LAM (Laboratoire d' Astrophysique de Marseille) UMR 7326, F-13388 Marseille (France); Comerón, Sébastien; Laine, Jarkko; Laurikainen, Eija; Salo, Heikki [Astronomy Division, Department of Physics, P.O. Box 3000, FI-90014 University of Oulu (Finland); Elmegreen, Bruce G. [IBM T. J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, NY 10598 (United States); Erroz-Ferrer, Santiago; Knapen, Johan H. [Instituto de Astrofísica de Canarias, Vía Lácteas, E-38205 La Laguna (Spain); Gadotti, Dimitri A.; Muñoz-Mateos, Juan Carlos [European Southern Observatory, Casilla 19001, Santiago 19 (Chile); Hinz, Joannah L. [MMT Observatory, P.O. Box 210065, Tucson, AZ 85721 (United States); Ho, Luis C. [Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871 (China); Holwerda, Benne [Leiden Observatory, University of Leiden, Niels Bohrweg 4, NL-2333 Leiden (Netherlands); Sheth, Kartik, E-mail: dennis.zaritsky@gmail.com [National Radio Astronomy Observatory/NAASC, 520 Edgemont Road, Charlottesville, VA 22903 (United States)

    2015-02-01

    Using 3.6 μm images of 97 early-type galaxies, we develop and verify methodology to measure globular cluster populations from the S{sup 4}G survey images. We find that (1) the ratio, T {sub N}, of the number of clusters, N {sub CL}, to parent galaxy stellar mass, M {sub *}, rises weakly with M {sub *} for early-type galaxies with M {sub *} > 10{sup 10} M {sub ☉} when we calculate galaxy masses using a universal stellar initial mass function (IMF) but that the dependence of T {sub N} on M {sub *} is removed entirely once we correct for the recently uncovered systematic variation of IMF with M {sub *}; and (2) for M {sub *} < 10{sup 10} M {sub ☉}, there is no trend between N {sub CL} and M {sub *}, the scatter in T {sub N} is significantly larger (approaching two orders of magnitude), and there is evidence to support a previous, independent suggestion of two families of galaxies. The behavior of N {sub CL} in the lower-mass systems is more difficult to measure because these systems are inherently cluster-poor, but our results may add to previous evidence that large variations in cluster formation and destruction efficiencies are to be found among low-mass galaxies. The average fraction of stellar mass in clusters is ∼0.0014 for M {sub *} > 10{sup 10} M {sub ☉} and can be as large as ∼0.02 for less massive galaxies. These are the first results from the S{sup 4}G sample of galaxies and will be enhanced by the sample of early-type galaxies now being added to S{sup 4}G and complemented by the study of later-type galaxies within S{sup 4}G.

  1. Planck intermediate results. XXVI. Optical identification and redshifts of Planck clusters with the RTT150 telescope

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Aumont, J; Baccigalupi, C; Banday, A J; Barreiro, R B; Barrena, R; Bartolo, N; Battaner, E; Benabed, K; Benoit-Lévy, A; Bernard, J -P; Bersanelli, M; Bielewicz, P; Bikmaev, I; Böhringer, H; Bonaldi, A; Bonavera, L; Bond, J R; Borrill, J; Bouchet, F R; Burenin, R; Burigana, C; Butler, R C; Calabrese, E; Carvalho, P; Catalano, A; Chamballu, A; Chiang, H C; Chon, G; Christensen, P R; Churazov, E; Clements, D L; Colombo, L P L; Comis, B; Couchot, F; Curto, A; Cuttaia, F; Dahle, H; Danese, L; Davies, R D; Davis, R J; de Bernardis, P; de Rosa, A; de Zotti, G; Delabrouille, J; Diego, J M; Dole, H; Doré, O; Douspis, M; Ducout, A; Dupac, X; Efstathiou, G; Elsner, F; Enßlin, T A; Eriksen, H K; Finelli, F; Flores-Cacho, I; Forni, O; Frailis, M; Franceschi, E; Frejsel, A; Fromenteau, S; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Gilfanov, M; Giraud-Héraud, Y; Gjerløw, E; González-Nuevo, J; Górski, K M; Gruppuso, A; Hansen, F K; Hanson, D; Harrison, D L; Hempel, A; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Holmes, W A; Hornstrup, A; Hovest, W; Huffenberger, K M; Hurier, G; Jaffe, T R; Jones, W C; Juvela, M; Keihanen, E; Keskitalo, R; Khamitov, I; Kisner, T S; Kneissl, R; Knoche, J; Kunz, M; Kurki-Suonio, H; Lagache, G; Lasenby, A; Lattanzi, M; Lawrence, C R; Leonardi, R; Levrier, F; Liguori, M; Lilje, P B; Linden-Vørnle, M; López-Caniego, M; Lubin, P M; Mac\\'\\ias-Pérez, J F; Maino, D; Mandolesi, N; Maris, M; Martin, P G; Mart\\'\\inez-González, E; Masi, S; Matarrese, S; Mazzotta, P; Melin, J -B; Mendes, L; Mennella, A; Migliaccio, M; Miville-Deschenes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, J A; Naselsky, P; Nati, F; Natoli, P; Nørgaard-Nielsen, H U; Novikov, D; Novikov, I; Oxborrow, C A; Pagano, L; Pajot, F; Paoletti, D; Pasian, F; Perdereau, O; Perotto, L; Perrotta, F; Pettorino, V; Piacentini, F; Piat, M; Pietrobon, D; Plaszczynski, S; Pointecouteau, E; Polenta, G; Popa, L; Pratt, G W; Prunet, S; Puget, J -L; Rachen, J P; Reinecke, M; Remazeilles, M; Renault, C; Ricciardi, S; Ristorcelli, I; Rocha, G; Roman, M; Rosset, C; Rossetti, M; Roudier, G; Rubiño-Mart\\'\\in, J A; Rusholme, B; Sandri, M; Scott, D; Spencer, L D; Stolyarov, V; Sudiwala, R; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Tucci, M; Valenziano, L; Valiviita, J; Van Tent, B; Vibert, L; Vielva, P; Villa, F; Wade, L A; Wandelt, B D; Wehus, I K; Yvon, D; Zacchei, A; Zonca, A

    2014-01-01

    We present the results of approximately three years of observations of Planck Sunyaev-Zeldovich (SZ) sources with the Russian-Turkish 1.5-m telescope (RTT150), as a part of the optical follow-up programme undertaken by the Planck collaboration. During this time period approximately 20% of all dark and grey clear time available at the telescope was devoted to observations of Planck objects. Some observations of distant clusters were also done at the 6-m Bolshoy Telescope Azimutal'ny (BTA) of the Special Astrophysical Observatory of the Russian Academy of Sciences. In total, deep, direct images of more than one hundred fields were obtained in multiple filters. We identified 47 previously unknown galaxy clusters, 41 of which are included in the Planck catalogue of SZ sources. The redshifts of 65 Planck clusters were measured spectroscopically and 14 more were measured photometrically. We discuss the details of cluster optical identifications and redshift measurements. We also present new spectroscopic redhifts f...

  2. Planck intermediate results I. Further validation of new Planck clusters with XMM-Newton

    DEFF Research Database (Denmark)

    Aghanim, N.; Collaboration, Planck; Arnaud, M.

    2012-01-01

    . The sample was selected in order to test internal SZ quality flags, and the pertinence of these flags is discussed in light of the validation results. Ten of the candidates are found to be bona fide clusters lying below the RASS flux limit. Redshift estimates are available for all confirmed systems via X......-ray Fe-line spectroscopy. They lie in the redshift range 0.19 z z. The X-ray properties of the new clusters appear to be similar to previous new detections by Planck at lower z and higher SZ flux: the majority are X-ray underluminous...... of candidates previously confirmed with XMM-Newton. The X-ray and optical redshifts for a total of 20 clusters are found to be in excellent agreement. We also show that useful lower limits can be put on cluster redshifts using X-ray data only via the use of the Y-X vs. Y-SZ and X-ray flux F-X vs. Y-SZ relations....

  3. A Novel Method for Analyzing and Interpreting GCM Results Using Clustered Climate Regimes

    Science.gov (United States)

    Hoffman, F. M.; Hargrove, W. W.; Erickson, D. J.; Oglesby, R. J.

    2003-12-01

    A high-performance parallel clustering algorithm has been developed for analyzing and comparing climate model results and long time series climate measurements. Designed to identify biases and detect trends in disparate climate change data sets, this tool combines and simplifies large temporally-varying data sets from atmospheric measurements to multi-century climate model output. Clustering is a statistical procedure which provides an objective method for grouping multivariate conditions into a set of states or regimes within a given level of statistical tolerance. The groups or clusters--statistically defined across space and through time--possess centroids which represent the synoptic conditions of observations or model results contained in each state no matter when or where they occurred. The clustering technique was applied to five business-as-usual (BAU) scenarios from the Parallel Climate Model (PCM). Three fields of significance (surface temperature, precipitation, and soil moisture) were clustered from 2000 through 2098. Our analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The same analysis subsequently applied to the ensemble as a whole demonstrates the consistency and variability of trends from each ensemble member. The patterns of cluster changes can be used to show predicted variability in climate on global and continental scales. Novel three-dimensional phase space representations of these climate regimes show the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time, and by incrementing time, that same spot will trace out a trajectory or orbit among these climate regimes in phase space. When a

  4. Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

    Science.gov (United States)

    Girola Schneider, R.

    2017-07-01

    The fuzzy logic is a branch of the artificial intelligence founded on the concept that everything is a matter of degree. It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters. Fuzzy logic enables the researcher to work with "imprecise" information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic's techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

  5. Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

    Science.gov (United States)

    Santiago Girola Schneider, Rafael

    2015-08-01

    The fuzzy logic is a branch of the artificial intelligence founded on the concept that 'everything is a matter of degree.' It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others.The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters.Fuzzy logic enables the researcher to work with “imprecise” information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic’s techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

  6. COSMIC-LAB: Unexpected Results from High-resolution Spectra of AGB Stars in Globular Clusters

    CERN Document Server

    Lapenna, Emilio

    2016-01-01

    This thesis is aimed at clarifying one of the least studied phases of stellar evolution: the asymptotic giant branch (AGB). Recent results obtained for Galactic globular clusters (GCs) suggest that the AGB stage may contain crucial information about the evolutionary history of exotic stars (Beccari et al. 2006) and multiple-populations (Campbell et al. 2013) in the parent cluster. The thesis presents the analysis of a large sample of high-resolution spectra of AGB stars in four Galactic GCs, acquired at the Very Large Telescope (ESO) and the 2.2 meter telescope (MPG). The obtained results provide evidence of a previously unknown physical mechanism affecting the neutral species of some chemical elements in the atmosphere of most AGB stars: because of it, the abundances derived from neutral lines are systematically underestimated, while those measured from ionized lines remain unaffected. Such a behaviour exactly corresponds to what expected in the case of non-local thermodynamic equilibrium (NLTE) conditions i...

  7. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, M.

    1993-07-01

    In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

  8. Using hierarchical linear models to test differences in Swedish results from OECD’s PISA 2003: Integrated and subject-specific science education

    Directory of Open Access Journals (Sweden)

    Maria Åström

    2012-06-01

    Full Text Available The possible effects of different organisations of the science curriculum in schools participating in PISA 2003 are tested with a hierarchical linear model (HLM of two levels. The analysis is based on science results. Swedish schools are free to choose how they organise the science curriculum. They may choose to work subject-specifically (with Biology, Chemistry and Physics, integrated (with Science or to mix these two. In this study, all three ways of organising science classes in compulsory school are present to some degree. None of the different ways of organising science education displayed statistically significant better student results in scientific literacy as measured in PISA 2003. The HLM model used variables of gender, country of birth, home language, preschool attendance, an economic, social and cultural index as well as the teaching organisation.

  9. 1 Hierarchical Approaches to the Analysis of Genetic Diversity in ...

    African Journals Online (AJOL)

    2015-04-14

    Apr 14, 2015 ... Keywords: Genetic diversity, Hierarchical approach, Plant, Clustering,. Descriptive ... utilization) or by clustering (based on a phonetic analysis of individual ...... Improvement of Food Crop Preservatives for the next Millennium.

  10. Compact star forming galaxies as the progenitors of compact quiescent galaxies: Clustering result

    Science.gov (United States)

    Lin, Xiaozhi; Fan, Lulu; Kong, Xu; Fang, Guanwen

    2017-02-01

    We present a measurement of the spatial clustering of massive compact galaxies at 1.2 ≤ z ≤ 3 in CANDELS/3D-HST fields. We obtain the correlation length for compact quiescent galaxies (cQGs) at z ∼ 1.6 of r0 = 7.1-2.6+2.3 h-1 Mpc and compact star forming galaxies (cSFGs) at z ∼ 2.5 of r0 = 7.7-2.9+2.7 h-1 Mpc assuming a power-law slope γ = 1.8 . The characteristic dark matter halo masses MH of cQGs at z ∼ 1.6 and cSFGs at z ∼ 2.5 are ∼ 7.1 ×1012h-1M⊙ and ∼ 4.4 ×1012h-1M⊙ , respectively. Our clustering result suggests that cQGs at z ∼ 1.6 are possibly the progenitors of local luminous ETGs and the descendants of cSFGs and SMGs at z > 2. Thus an evolutionary connection involving SMGs, cSFGs, QSOs, cQGs and local luminous ETGs has been indicated by our clustering result.

  11. Compact star forming galaxies as the progenitors of compact quiescent galaxies: clustering result

    CERN Document Server

    Lin, Xiaozhi; Kong, Xu; Fang, Guanwen

    2016-01-01

    We present a measurement of the spatial clustering of massive compact galaxies at $1.2\\le z \\le 3$ in CANDELS/3D-HST fields. We obtain the correlation length for compact quiescent galaxies (cQGs) at $z\\sim1.6$ of $r_{0}=7.1_{-2.6}^{+2.3}\\ h^{-1}Mpc$ and compact star forming galaxies (cSFGs) at $z\\sim2.5$ of $r_{0}=7.7_{-2.9}^{+2.7}\\ h^{-1}Mpc$ assuming a power-law slope $\\gamma =1.8$. The characteristic dark matter halo masses $M_H$ of cQGs at $z\\sim1.6$ and cSFGs at $z\\sim2.5$ are $\\sim7.1\\times 10^{12}\\ h^{-1} M_\\odot$ and $\\sim4.4\\times10^{12}\\ h^{-1} M_\\odot$, respectively. Our clustering result suggests that cQGs at $z\\sim1.6$ are possibly the progenitors of local luminous ETGs and the descendants of cSFGs and SMGs at $z>2$. Thus an evolutionary connection involving SMGs, cSFGs, QSOs, cQGs and local luminous ETGs has been indicated by our clustering result.

  12. Clustering results - Gclust Server | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available uster Group [Cluster ID]: [Number of sequences belonging to cluster] sequences. Final thr = [Threshold] Grou...p [Cluster ID]: [Number of sequences belonging to cluster] sequences. Final thr =...ter ID: 2400) Group 2400: 38 sequences. Final thr = 1.00e-40 Group 2400: 38 sequences. Final thr = 1.00e-40

  13. HICOSMO: cosmology with a complete sample of galaxy clusters - II. Cosmological results

    Science.gov (United States)

    Schellenberger, G.; Reiprich, T. H.

    2017-10-01

    The X-ray bright, hot gas in the potential well of a galaxy cluster enables systematic X-ray studies of samples of galaxy clusters to constrain cosmological parameters. HIFLUGCS consists of the 64 X-ray brightest galaxy clusters in the Universe, building up a local sample. Here, we utilize this sample to determine, for the first time, individual hydrostatic mass estimates for all the clusters of the sample and, by making use of the completeness of the sample, we quantify constraints on the two interesting cosmological parameters, Ωm and σ8. We apply our total hydrostatic and gas mass estimates from the X-ray analysis to a Bayesian cosmological likelihood analysis and leave several parameters free to be constrained. We find Ωm = 0.30 ± 0.01 and σ8 = 0.79 ± 0.03 (statistical uncertainties, 68 per cent credibility level) using our default analysis strategy combining both a mass function analysis and the gas mass fraction results. The main sources of biases that we correct here are (1) the influence of galaxy groups (incompleteness in parent samples and differing behaviour of the Lx-M relation), (2) the hydrostatic mass bias, (3) the extrapolation of the total mass (comparing various methods), (4) the theoretical halo mass function and (5) other physical effects (non-negligible neutrino mass). We find that galaxy groups introduce a strong bias, since their number density seems to be over predicted by the halo mass function. On the other hand, incorporating baryonic effects does not result in a significant change in the constraints. The total (uncorrected) systematic uncertainties (∼20 per cent) clearly dominate the statistical uncertainties on cosmological parameters for our sample.

  14. The Cluster Magnetic Field Investigation: overview of in-flight performance and initial results

    Directory of Open Access Journals (Sweden)

    A. Balogh

    Full Text Available The accurate measurement of the magnetic field along the orbits of the four Cluster spacecraft is a primary objective of the mission. The magnetic field is a key constituent of the plasma in and around the magnetosphere, and it plays an active role in all physical processes that define the structure and dynamics of magnetospheric phenomena on all scales. With the four-point measurements on Cluster, it has become possible to study the three-dimensional aspects of space plasma phenomena on scales commeasurable with the size of the spacecraft constellation, and to distinguish temporal and spatial dependences of small-scale processes. We present an overview of the instrumentation used to measure the magnetic field on the four Cluster spacecraft and an overview the performance of the operational modes used in flight. We also report on the results of the preliminary in-orbit calibration of the magnetometers; these results show that all components of the magnetic field are measured with an accuracy approaching 0.1 nT. Further data analysis is expected to bring an even more accurate determination of the calibration parameters. Several examples of the capabilities of the investigation are presented from the commissioning phase of the mission, and from the different regions visited by the spacecraft to date: the tail current sheet, the dusk side magnetopause and magnetosheath, the bow shock and the cusp. We also describe the data processing flow and the implementation of data distribution to other Cluster investigations and to the scientific community in general.

    Key words. Interplanetary physics (instruments and techniques – magnetospheric physics (magnetospheric configuration and dynamics – space plasma physics (shock waves

  15. Gene Expression Data Knowledge Discovery using Global and Local Clustering

    CERN Document Server

    H, Swathi

    2010-01-01

    To understand complex biological systems, the research community has produced huge corpus of gene expression data. A large number of clustering approaches have been proposed for the analysis of gene expression data. However, extracting important biological knowledge is still harder. To address this task, clustering techniques are used. In this paper, hybrid Hierarchical k-Means algorithm is used for clustering and biclustering gene expression data is used. To discover both local and global clustering structure biclustering and clustering algorithms are utilized. A validation technique, Figure of Merit is used to determine the quality of clustering results. Appropriate knowledge is mined from the clusters by embedding a BLAST similarity search program into the clustering and biclustering process. To discover both local and global clustering structure biclustering and clustering algorithms are utilized. To determine the quality of clustering results, a validation technique, Figure of Merit is used. Appropriate ...

  16. Validation of genotype cluster investigations for Mycobacterium tuberculosis: application results for 44 clusters from four heterogeneous United States jurisdictions.

    Science.gov (United States)

    Teeter, Larry D; Vempaty, Padmaja; Nguyen, Duc T M; Tapia, Jane; Sharnprapai, Sharon; Ghosh, Smita; Kammerer, J Steven; Miramontes, Roque; Cronin, Wendy A; Graviss, Edward A

    2016-10-21

    Tracking the dissemination of specific Mycobacterium tuberculosis (Mtb) strains using genotyped Mtb isolates from tuberculosis patients is a routine public health practice in the United States. The present study proposes a standardized cluster investigation method to identify epidemiologic-linked patients in Mtb genotype clusters. The study also attempts to determine the proportion of epidemiologic-linked patients the proposed method would identify beyond the outcome of the conventional contact investigation. The study population included Mtb culture positive patients from Georgia, Maryland, Massachusetts and Houston, Texas. Mtb isolates were genotyped by CDC's National TB Genotyping Service (NTGS) from January 2006 to October 2010. Mtb cluster investigations (CLIs) were conducted for patients whose isolates matched exactly by spoligotyping and 12-locus MIRU-VNTR. CLIs were carried out in four sequential steps: (1) Public Health Worker (PHW) Interview, (2) Contact Investigation (CI) Evaluation, (3) Public Health Records Review, and (4) CLI TB Patient Interviews. Comparison between patients whose links were identified through the study's CLI interviews (Step 4) and patients whose links were identified earlier in CLI (Steps 1-3) was conducted using logistic regression. Forty-four clusters were randomly selected from the four study sites (401 patients in total). Epidemiologic links were identified for 189/401 (47 %) study patients in a total of 201 linked patient-pairs. The numbers of linked patients identified in each CLI steps were: Step 1 - 105/401 (26.2 %), Step 2 - 15/388 (3.9 %), Step 3 - 41/281 (14.6 %), and Step 4 - 28/119 (30 %). Among the 189 linked patients, 28 (14.8 %) were not identified in previous CI. No epidemiologic links were identified in 13/44 (30 %) clusters. We validated a standardized and practical method to systematically identify epidemiologic links among patients in Mtb genotype clusters, which can be integrated into the TB control and

  17. Chemical abundance gradients from open clusters in the Milky Way disk: results from the APOGEE survey

    CERN Document Server

    Cunha, Katia; Souto, Diogo; Thompson, Benjamin; Zasowski, Gail; Prieto, Carlos Allende; Carrera, Ricardo; Chiappini, Cristina; Donor, John; Garcia-Hernandez, Anibal; Perez, Ana Elia Garcia; Hayden, Michael R; Holtzman, Jon; Jackson, Kelly M; Johnson, Jennifer A; Majewski, Steven R; Meszaros, Szabolcs; Meyer, Brianne; Nidever, David L; O'Connell, Julia; Schiavon, Ricardo P; Schultheis, Mathias; Shetrone, Matthew; Simmons, Audrey; Smith, Verne V; Zamora, Olga

    2016-01-01

    Metallicity gradients provide strong constraints for understanding the chemical evolution of the Galaxy. We report on radial abundance gradients of Fe, Ni, Ca, Si, and Mg obtained from a sample of 304 red-giant members of 29 disk open clusters, mostly concentrated at galactocentric distances between ~8 - 15 kpc, but including two open clusters in the outer disk. The observations are from the APOGEE survey. The chemical abundances were derived automatically by the ASPCAP pipeline and these are part of the SDSS III Data Release 12. The gradients, obtained from least squares fits to the data, are relatively flat, with slopes ranging from -0.026 to -0.033 dex/kpc for the alpha-elements [O/H], [Ca/H], [Si/H] and [Mg/H] and -0.035 dex/kpc and -0.040 dex/kpc for [Fe/H] and [Ni/H], respectively. Our results are not at odds with the possibility that metallicity ([Fe/H]) gradients are steeper in the inner disk (R_GC ~7 - 12 kpc) and flatter towards the outer disk. The open cluster sample studied spans a significant ran...

  18. Photometric and clustering properties of hydrodynamical galaxies in a cosmological volume: results at z = 0

    Science.gov (United States)

    Nuza, Sebastián E.; Dolag, Klaus; Saro, Alexandro

    2010-09-01

    In this work, we present results for the photometric and clustering properties of galaxies that arise in a Λ cold dark matter hydrodynamical simulation of the local Universe. The present-day distribution of matter was constructed to match the observed large-scale pattern of the IRAS 1.2-Jy galaxy survey. Our simulation follows the formation and evolution of galaxies in a cosmological sphere with a volume of ~1303h-3Mpc3 including supernova feedback, galactic winds, photoheating due to a uniform meta-galactic background and chemical enrichment of the gas and stellar populations. However, we do not consider active galactic nuclei. In the simulation, a total of ~20000 galaxies are formed above the resolution limit, and around 60 haloes are more massive than ~1014Msolar. Luminosities of the galaxies are calculated based on a stellar population synthesis model including the attenuation by dust, which is calculated from the cold gas left within the simulated galaxies. Environmental effects such as colour bimodality and differential clustering power of the hydrodynamical galaxies are qualitatively similar to observed trends. Nevertheless, the overcooling present in the simulations leads to too blue and overluminous brightest cluster galaxies (BCGs). To overcome this, we mimic the late-time suppression of star formation in massive haloes by ignoring recently formed stars with the aid of a simple post-processing recipe. In this way we find luminosity functions, both for field and for group/cluster galaxies, in better agreement with observations. Specifically, the BCGs then follow the observed luminosity-halo mass relation. However, in such a case, the colour bimodality is basically lost, pointing towards a more complex interplay of late suppression of star formation than what is given by the simple scheme adopted.

  19. Application of hybrid clustering using parallel k-means algorithm and DIANA algorithm

    Science.gov (United States)

    Umam, Khoirul; Bustamam, Alhadi; Lestari, Dian

    2017-03-01

    DNA is one of the carrier of genetic information of living organisms. Encoding, sequencing, and clustering DNA sequences has become the key jobs and routine in the world of molecular biology, in particular on bioinformatics application. There are two type of clustering, hierarchical clustering and partitioning clustering. In this paper, we combined two type clustering i.e. K-Means (partitioning clustering) and DIANA (hierarchical clustering), therefore it called Hybrid clustering. Application of hybrid clustering using Parallel K-Means algorithm and DIANA algorithm used to clustering DNA sequences of Human Papillomavirus (HPV). The clustering process is started with Collecting DNA sequences of HPV are obtained from NCBI (National Centre for Biotechnology Information), then performing characteristics extraction of DNA sequences. The characteristics extraction result is store in a matrix form, then normalize this matrix using Min-Max normalization and calculate genetic distance using Euclidian Distance. Furthermore, the hybrid clustering is applied by using implementation of Parallel K-Means algorithm and DIANA algorithm. The aim of using Hybrid Clustering is to obtain better clusters result. For validating the resulted clusters, to get optimum number of clusters, we use Davies-Bouldin Index (DBI). In this study, the result of implementation of Parallel K-Means clustering is data clustered become 5 clusters with minimal IDB value is 0.8741, and Hybrid Clustering clustered data become 13 sub-clusters with minimal IDB values = 0.8216, 0.6845, 0.3331, 0.1994 and 0.3952. The IDB value of hybrid clustering less than IBD value of Parallel K-Means clustering only that perform at 1ts stage. Its means clustering using Hybrid Clustering have the better result to clustered DNA sequence of HPV than perform parallel K-Means Clustering only.

  20. Non-Trivial Feature Derivation for Intensifying Feature Detection Using LIDAR Datasets Through Allometric Aggregation Data Analysis Applying Diffused Hierarchical Clustering for Discriminating Agricultural Land Cover in Portions of Northern Mindanao, Philippines

    Science.gov (United States)

    Villar, Ricardo G.; Pelayo, Jigg L.; Mozo, Ray Mari N.; Salig, James B., Jr.; Bantugan, Jojemar

    2016-06-01

    Leaning on the derived results conducted by Central Mindanao University Phil-LiDAR 2.B.11 Image Processing Component, the paper attempts to provides the application of the Light Detection and Ranging (LiDAR) derived products in arriving quality Landcover classification considering the theoretical approach of data analysis principles to minimize the common problems in image classification. These are misclassification of objects and the non-distinguishable interpretation of pixelated features that results to confusion of class objects due to their closely-related spectral resemblance, unbalance saturation of RGB information is a challenged at the same time. Only low density LiDAR point cloud data is exploited in the research denotes as 2 pts/m2 of accuracy which bring forth essential derived information such as textures and matrices (number of returns, intensity textures, nDSM, etc.) in the intention of pursuing the conditions for selection characteristic. A novel approach that takes gain of the idea of object-based image analysis and the principle of allometric relation of two or more observables which are aggregated for each acquisition of datasets for establishing a proportionality function for data-partioning. In separating two or more data sets in distinct regions in a feature space of distributions, non-trivial computations for fitting distribution were employed to formulate the ideal hyperplane. Achieving the distribution computations, allometric relations were evaluated and match with the necessary rotation, scaling and transformation techniques to find applicable border conditions. Thus, a customized hybrid feature was developed and embedded in every object class feature to be used as classifier with employed hierarchical clustering strategy for cross-examining and filtering features. This features are boost using machine learning algorithms as trainable sets of information for a more competent feature detection. The product classification in this

  1. 一种基于分层 AP 的视频关键帧提取方法研究%Research on video key-frame extraction based on hierarchical affinity propagation clustering

    Institute of Scientific and Technical Information of China (English)

    党宏社; 白梅

    2016-01-01

    为从大量的视频资源中高效准确地提取关键帧图像来表达视频的主要内容,针对传统AP聚类方法提取关键帧无法适应大规模图像集的问题,提出一种分层AP的关键帧提取方法。提取所有视频序列的颜色和纹理特征,将待聚类的图像集进行分层,用传统AP聚类方法求取每个图像子集的聚类中心;用得到的聚类中心进行自适应的AP聚类,根据Silhouette指标选取最优的聚类结果,即可得到视频序列的关键帧代表。实验表明,该方法能快速准确地提取视频最优关键帧,在保证保真度指标的同时能提高关键帧提取的压缩比,且适用于不同类型的视频资源。%In order to extract key frames from large‐scale different videos more effectively and accurately ,since traditional AP algorithm is inappropriate to the large‐scale pictures cluste‐ring ,a hierarchical AP method for key frame extraction is proposed .First get the color and texture features of all video sequences ,the pictures set is divided into several subsets ,the tra‐ditional AP is used to obtain the exemplars of each subset ;Then the adaptive AP is imple‐mented on the obtained exemplars ,the key frames of video sequences are extracted according to the index of Silhouette for the best clustering result .The experimental result shows that proposed method is efficient in key‐frame extraction and suitable for all types video re‐sources ,has a high fidelity w hile the compression ratio is improved greatly .

  2. Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata

    Science.gov (United States)

    Diniz, Daniel G.; Silva, Geane O.; Naves, Thaís B.; Fernandes, Taiany N.; Araújo, Sanderson C.; Diniz, José A. P.; de Farias, Luis H. S.; Sosthenes, Marcia C. K.; Diniz, Cristovam G.; Anthony, Daniel C.; da Costa Vasconcelos, Pedro F.; Picanço Diniz, Cristovam W.

    2016-01-01

    It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous. PMID:27047345

  3. The association between content of the elements S, Cl, K, Fe, Cu, Zn and Br in normal and cirrhotic liver tissue from Danes and Greenlandic Inuit examined by dual hierarchical clustering analysis

    DEFF Research Database (Denmark)

    Laursen, Jens; Milman, Nils; Pind, N.;

    2014-01-01

    contents according to calculated similarities, one clustering elements according to correlation coefficients between the element contents, both using Euclidian distance and Ward Procedure. RESULTS: One dendrogram separated subjects in 7 clusters showing no differences in ethnicity, gender or age....... The analysis discriminated between elements in normal and cirrhotic livers. The other dendrogram clustered elements in four clusters: sulphur and chlorine; copper and bromine; potassium and zinc; iron. There were significant correlations between the elements in normal liver samples: S was associated with Cl, K...

  4. 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.

  5. 基于主成分与聚类分析的苹果加工品质评价%Evaluation of apple quality based on principal component and hierarchical cluster analysis

    Institute of Scientific and Technical Information of China (English)

    公丽艳; 孟宪军; 刘乃侨; 毕金峰

    2014-01-01

    The purpose of this study was to investigate the variations in physical and chemical characteristics of apple fruit from 30 varieties grown in the same place using pattern recognition tools. Twenty quality parameters of apple samples (e.g. weight,volume, density, color, hardness, sugar-acid ratio, Vitamin C, etc.) were analyzed. Interrelationships between the parameters and the apple variety were investigated by descriptive statistics, principal component analysis (PCA) and hierarchical cluster analysis (HCA). PCA is a mathematical tool which performs a reduction in data dimensionality and allows the visualisation of underlying structure in experimental data and relationships between data and samples.In hierarchical cluster analysis, samples are grouped on the basis of similarities, without taking into account the information about the class membership. The results obtained following HCA are shown as a dendrogram in which five well-defined clusters are visible. Samples will be grouped in clusters in terms of their nearness or similarity. Cluster analysis uses less information (distances only) than PCA. It is interesting to observe what kind of classification can be made on the basis of distances only. The results showed that density, fruit shape index and water content of 30 apple varieties were not significantly different. The remaining seventeen measurements were investigated by principal component analysis. The first six components represented 83.56% of the total variability on the base of the total variance explained and screen plot of principal component analysis. The first principal component was related to titratable acidity, sugar-acid ratio and solid-acid ratio attributes, which were the taste quality factor. The second principal component was related to L,a, andb attributes, which were the color factor. Following that were sweetness factor, texture factor, quality factor and size factor. The sample score plots visually displayed the relationship between

  6. 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....... The method is flexible and it is possible to find consensus clusters from different clustering algorithms. Thus, the algorithm can be used as a framework to test in a quantitative manner the homogeneity of different clustering algorithms. We compare the method with a number of state-of-the-art clustering...

  7. Cataclysmic variables in Globular clusters: First results on the analysis of the MOCCA simulations database

    CERN Document Server

    Belloni, Diogo; Askar, Abbas; Hypki, Arkadiusz

    2016-01-01

    In this first investigation of the MOCCA database with respect to cataclysmic variables, we found that for models with Kroupa initial distributions, considering the standard value of the efficiency of the common-envelope phase adopted in BSE, no single cataclysmic variable was formed only via binary stellar evolution, i. e., in order to form them, strong dynamical interactions have to take place. Our results also indicate that the population of cataclysmic variables in globular clusters are, mainly, in the last stage of their evolution and observational selection effects can change drastically the expected number and properties of observed cataclysmic variables.

  8. Multi-granularity reconstruction of 3D calamity emergency situations based on visual scale space hierarchical clustering%基于VSSHC算法的灾害应急多粒度三维态势重构

    Institute of Scientific and Technical Information of China (English)

    于海心; 陈杰; 张娟

    2012-01-01

    针对现有灾害应急态势系统的三维地貌实时更新和态势多粒度显示的技术瓶颈,研究并设计了应急三维态势重构系统(3D-ESRS),该系统可进行实时三维地貌更新和多粒度显示态势内容.分析了3D-ESRS的需求和功能,设计了3D-ESRS的基于多智能体(MAS)的系统框架结构,研究了3D-ESRS系统更新地貌和多粒度显示原理与工作流程,构建了基于视觉尺度空间分层聚类(VSSHC)算法的多尺度分类模型.以堰塞湖为例,多粒度显示了水面升高过程,该实验结果表明3D-ESRS与传统基于GIS平台的态势系统相比,可以实时进行三维地貌场景更新,并对场景进行多粒度显示.%A calamity-oriented 3D emergency situation reconstruction system (3D-ESRS) was studied, and its architecture was designed using the multi-agent technique.Moreover, an approach to multi-granularity reconstruction of 3D calamity emergency situations based on the visual scale space hierarchical clustering ( VSSHC) algorithm was proposed for calamity emergency-decision supporting systems to make them realize the real-time presentation of dynamic 3D calamity situations.A simulation platform based on high level architecture (HLA) was established to verify this approach.The simulation results illustrate that this approach is applicable to emergency-decision supporting systems, and compared to the traditional situation display system this 3D-ESRS has the superiority in reconstructing real-time 3D scenario models.

  9. Distance function selection in several clustering algorithrms

    Institute of Scientific and Technical Information of China (English)

    LU Yu

    2004-01-01

    Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical clustering were investigated.Both theoretical analysis and detailed experimental results were given. It is shown that a distance function greatly affects clustering results and can be used to detect the outlier of a cluster by the comparison of such different results and give the shape information of clusters. In practice situation, it is suggested to use different distance function separately, compare the clustering results and pick out the "swing points". And such points may leak out more information for data analysts.

  10. Spectral characterization of hierarchical network modularity and limits of modularity detection.

    Directory of Open Access Journals (Sweden)

    Somwrita Sarkar

    Full Text Available Many real world networks are reported to have hierarchically modular organization. However, there exists no algorithm-independent metric to characterize hierarchical modularity in a complex system. The main results of the paper are a set of methods to address this problem. First, classical results from random matrix theory are used to derive the spectrum of a typical stochastic block model hierarchical modular network form. Second, it is shown that hierarchical modularity can be fingerprinted using the spectrum of its largest eigenvalues and gaps between clusters of closely spaced eigenvalues that are well separated from the bulk distribution of eigenvalues around the origin. Third, some well-known results on fingerprinting non-hierarchical modularity in networks automatically follow as special cases, threreby unifying these previously fragmented results. Finally, using these spectral results, it is found that the limits of detection of modularity can be empirically established by studying the mean values of the largest eigenvalues and the limits of the bulk distribution of eigenvalues for an ensemble of networks. It is shown that even when modularity and hierarchical modularity are present in a weak form in the network, they are impossible to detect, because some of the leading eigenvalues fall within the bulk distribution. This provides a threshold for the detection of modularity. Eigenvalue distributions of some technological, social, and biological networks are studied, and the implications of detecting hierarchical modularity in real world networks are discussed.

  11. The Application of Hierarchical Cluster Analysis to the Prediction of Grain Security of Small Research Areas-A Case Study of Kunshan%谱系聚类法在小区域粮食安全预测中的应用——以昆山市为例

    Institute of Scientific and Technical Information of China (English)

    姚鑫; 杨桂山; 万荣荣

    2011-01-01

    粮食安全对国民经济的可持续发展起着不可替代的基础性作用,小区域由于受政策因素的影响较大,粮食安全相关指标的变化呈一定阶段性,长时间序列的数学规律并不突出,不利于规划工作的展开.论文基于昆山市的研究,提出谱系聚类与数学模型相结合的基本思路,在此基础上推出了聚类结果有效性的量化判定标准并对聚类法运用准则做了深入的探讨.实际数据分析结果表明:昆山的粮食安全相关的社会经济指标变化确实呈明显阶段性;与利用全部时间序列数据建立的模型相比,运用谱系聚类的模型拟合和预测效果都有明显优势;至2015年,昆山市粮食自给率将下降至6%,最小人均耕地面积降低至0.022 hm2.通过进一步的分析、对比及讨论,文章认为,谱系聚类法运用于小区域粮食安全预测,方法可操作性强,结论科学性显著.%Grain security is fundamental to the sustainable development of our society and national economy. As research regions with small area are vulnerable to the impacts of policy changes, indexes related to grain security of these areas often change in the form of stages, which means that the mathematical regularity of long-term datasets is not significant. As a result, it is difficult to implement grain security programming for the future.We put forward a new method of combining hierarchical cluster analysis with traditional mathematical models, and established a quantification standard for the validity judgment of the clustering results. Meanwhile, a criterion for the using of hierarchical cluster analysis was also proposed, but we strongly recommended that mass data from other research areas are needed to calibrate and perfect it.Kunshan ( 1985 -2007 ) was chosen as a study region to prove the new method, because it is small in area but with rapid economic development. The results of analysis showed that: the indexes related to grain security did

  12. ARCS, The Arcminute Radio Cluster-lens Search - I. Selection Criteria and Initial Results

    CERN Document Server

    Phillips, P M; Wilkinson, P N

    2000-01-01

    We present the results of an unbiased radio search for gravitational lensing events with image separations between 15 and 60 arcsec, which would be associated with clusters of galaxies with masses >10^{13-14}M_{\\sun}. A parent population of 1023 extended radio sources stronger than 35 mJy with stellar optical identifications was selected using the FIRST radio catalogue at 1.4 GHz and the APM optical catalogue. The FIRST catalogue was then searched for companions to the parent sources stronger than 7 mJy and with separation in the range 15 to 60 arcsec. Higher resolution observations of the resulting 38 lens candidates were made with the VLA at 1.4 GHz and 5 GHz, and with MERLIN at 5 GHz in order to test the lens hypothesis in each case. None of our targets was found to be a gravitational lens system. These results provide the best current constraint on the lensing rate for this angular scale, but improved calculations of lensing rates from realistic simulations of the clustering of matter on the relevant scal...

  13. Planck intermediate results: IV. the XMM-Newton validation programme for new Planck galaxy clusters

    DEFF Research Database (Denmark)

    Delabrouille, J.; Ganga, K.; Giraud-Héraud, Y.;

    2013-01-01

    -Faint Source Catalogue does not guarantee that the SZ candidate is a bona fide cluster. Nevertheless, most Planck clusters appear in RASS maps, with a significance greater than 2σ being a good indication that the candidate is a real cluster. Candidate validation from association with SDSS galaxy overdensity...

  14. Mobility of large clusters on a semiconductor surface: Kinetic Monte Carlo simulation results

    Science.gov (United States)

    M, Esen; A, T. Tüzemen; M, Ozdemir

    2016-01-01

    The mobility of clusters on a semiconductor surface for various values of cluster size is studied as a function of temperature by kinetic Monte Carlo method. The cluster resides on the surface of a square grid. Kinetic processes such as the diffusion of single particles on the surface, their attachment and detachment to/from clusters, diffusion of particles along cluster edges are considered. The clusters considered in this study consist of 150-6000 atoms per cluster on average. A statistical probability of motion to each direction is assigned to each particle where a particle with four nearest neighbors is assumed to be immobile. The mobility of a cluster is found from the root mean square displacement of the center of mass of the cluster as a function of time. It is found that the diffusion coefficient of clusters goes as D = A(T)Nα where N is the average number of particles in the cluster, A(T) is a temperature-dependent constant and α is a parameter with a value of about -0.64 a value of -0.5. The diffusion coefficient is found to change by one order of magnitude as a function of cluster size.

  15. Planck intermediate results. V. Pressure profiles of galaxy clusters from the Sunyaev-Zeldovich effect

    Science.gov (United States)

    Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Balbi, A.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Battaner, E.; Benabed, K.; Benoît, A.; Bernard, J.-P.; Bersanelli, M.; Bhatia, R.; Bikmaev, I.; Bobin, J.; Böhringer, H.; Bonaldi, A.; Bond, J. R.; Borgani, S.; Borrill, J.; Bouchet, F. R.; Bourdin, H.; Brown, M. L.; Burenin, R.; Burigana, C.; Cabella, P.; Cardoso, J.-F.; Carvalho, P.; Castex, G.; Catalano, A.; Cayón, L.; Chamballu, A.; Chiang, L.-Y.; Chon, G.; Christensen, P. R.; Churazov, E.; Clements, D. L.; Colafrancesco, S.; Colombi, S.; Colombo, L. P. L.; Comis, B.; Coulais, A.; Crill, B. P.; Cuttaia, F.; Da Silva, A.; Dahle, H.; Danese, L.; Davis, R. J.; de Bernardis, P.; de Gasperis, G.; de Zotti, G.; Delabrouille, J.; Démoclès, J.; Désert, F.-X.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Dörl, U.; Douspis, M.; Dupac, X.; Efstathiou, G.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Fosalba, P.; Frailis, M.; Franceschi, E.; Frommert, M.; Galeotta, S.; Ganga, K.; Génova-Santos, R. T.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Harrison, D.; Hempel, A.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hurier, G.; Jaffe, T. R.; Jaffe, A. H.; Jagemann, T.; Jones, W. C.; Juvela, M.; Keihänen, E.; Khamitov, I.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lawrence, C. R.; Le Jeune, M.; Leonardi, R.; Liddle, A.; Lilje, P. B.; López-Caniego, M.; Luzzi, G.; Macías-Pérez, J. F.; Maino, D.; Mandolesi, N.; Maris, M.; Marleau, F.; Marshall, D. J.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Mazzotta, P.; Mei, S.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Piffaretti, R.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reach, W. T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Savini, G.; Scott, D.; Smoot, G. F.; Starck, J.-L.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tuovinen, J.; Valenziano, L.; Van Tent, B.; Varis, J.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Welikala, N.; White, S. D. M.; White, M.; Yvon, D.; Zacchei, A.; Zonca, A.

    2013-02-01

    Taking advantage of the all-sky coverage and broadfrequency range of the Planck satellite, we study the Sunyaev-Zeldovich (SZ) and pressure profiles of 62 nearby massive clusters detected at high significance in the 14-month nominal survey. Careful reconstruction of the SZ signal indicates that most clusters are individually detected at least out to R500. By stacking the radial profiles, we have statistically detected the radial SZ signal out to 3 × R500, i.e., at a density contrast of about 50-100, though the dispersion about the mean profile dominates the statistical errors across the whole radial range. Our measurement is fully consistent with previous Planck results on integrated SZ fluxes, further strengthening the agreement between SZ and X-ray measurements inside R500. Correcting for the effects of the Planck beam, we have calculated the corresponding pressure profiles. This new constraint from SZ measurements is consistent with the X-ray constraints from XMM-Newton in the region in which the profiles overlap (i.e., [0.1-1] R500), and is in fairly good agreement with theoretical predictions within the expected dispersion. At larger radii the average pressure profile is slightly flatter than most predictions from numerical simulations. Combining the SZ and X-ray observed profiles into a joint fit to a generalised pressure profile gives best-fit parameters [P0,c500,γ,α,β ] = [6.41,1.81,0.31,1.33,4.13 ] . Using a reasonable hypothesis for the gas temperature in the cluster outskirts we reconstruct from our stacked pressure profile the gas mass fraction profile out to 3 R500. Within the temperature driven uncertainties, our Planck constraints are compatible with the cosmic baryon fraction and expected gas fraction in halos. Appendices are available in electronic form at http://www.aanda.org

  16. Cluster-size distributions for irreversible cooperative filling of lattices. II. Exact one-dimensional results for noncoalescing clusters

    Energy Technology Data Exchange (ETDEWEB)

    Evans, J.W.; Nord, R.S.

    1985-06-01

    We consider processes where the sites of an infinite, uniform, one-dimensional lattice are filled irreversibly and cooperatively, with the rates k/sub i/, depending on the number i = 0,1,2 of filled nearest neighbors. Furthermore, we suppose that filling of sites with both neighbors already filled is forbidden, so k/sub 2/ = 0. Thus, clusters can nucleate and grow, but cannot coalesce. Exact truncation solutions of the corresponding infinite hierarchy of rate equations for subconfiguration probabilities are possible. For the probabilities of filled s-tuples f/sub s/ as a function of coverage, thetaequivalentf/sub 1/, we find that f/sub s//f/sub s+1/ = D(theta)s+C(theta,s), where C(theta,s)/s..-->..0 as s..-->..infinity. This corresponds to faster than exponential decay. Also, if rhoequivalentk/sub 1//k/sub 0/, then one has D(theta)approx.(2rhotheta)/sup -1/ as theta..-->..0. The filled-cluster-size distribution n/sub s/ has the same characteristics. Motivated by the behavior of these families of f/sub s//f/sub s+1/-vs-s curves, we develop the natural extension of f/sub s/ to s< or =0. Explicit values for f/sub s/ and related quantities for ''almost random'' filling, k/sub 0/ = k/sub 1/, are obtained from a direct statistical analysis.

  17. Cluster-size distributions for irreversible cooperative filling of lattices. II. Exact one-dimensional results for noncoalescing clusters

    Science.gov (United States)

    Evans, J. W.; Nord, R. S.

    1985-06-01

    We consider processes where the sites of an infinite, uniform, one-dimensional lattice are filled irreversibly and cooperatively, with the rates ki, depending on the number i=0,1,2 of filled nearest neighbors. Furthermore, we suppose that filling of sites with both neighbors already filled is forbidden, so k2=0. Thus, clusters can nucleate and grow, but cannot coalesce. Exact truncation solutions of the corresponding infinite hierarchy of rate equations for subconfiguration probabilities are possible. For the probabilities of filled s-tuples fs as a function of coverage, θ≡f1, we find that fs/fs+1=D(θ)s+C(θ,s), where C(θ,s)/s-->0 as s-->∞. This corresponds to faster than exponential decay. Also, if ρ≡k1/k0, then one has D(θ)~(2ρθ)-1 as θ-->0. The filled-cluster-size distribution ns has the same characteristics. Motivated by the behavior of these families of fs/fs+1-vs-s curves, we develop the natural extension of fs to s<=0. Explicit values for fs and related quantities for ``almost random'' filling, k0=k1, are obtained from a direct statistical analysis.

  18. Globular Cluster Populations: Results Including S$^4$G Late-Type Galaxies

    CERN Document Server

    Zaritsky, Dennis; Aravena, Manuel; Athanassoula, E; Bosma, Albert; Comerón, Sébastien; Courtois, Helene M; Elmegreen, Bruce G; Elmegreen, Debra M; Erroz-Ferrer, Santiago; Gadotti, Dimitri A; Hinz, Joannah L; Ho, Luis C; Holwerda, Benne; Kim, Taehyun; Knapen, Johan H; Laine, Jarkko; Laurikainen, Eija; Muñoz-Mateos, Juan Carlos; Salo, Heikki; Sheth, Kartik

    2015-01-01

    Using 3.6 and 4.5$\\mu$m images of 73 late-type, edge-on galaxies from the S$^4$G survey, we compare the richness of the globular cluster populations of these galaxies to those of early type galaxies that we measured previously. In general, the galaxies presented here fill in the distribution for galaxies with lower stellar mass, M$_*$, specifically $\\log({\\rm M}_*/{\\rm M}_\\odot) < 10$, overlap the results for early-type galaxies of similar masses, and, by doing so, strengthen the case for a dependence of the number of globular clusters per $10^9\\ {\\rm M}_\\odot$ of galaxy stellar mass, T$_{\\rm N}$, on M$_*$. For $8.5 < \\log ({\\rm M}_*/{\\rm M}_\\odot) < 10.5$ we find the relationship can be satisfactorily described as T$_{\\rm N} = ({\\rm M}_*/10^{6.7})^{-0.56}$ when M$_*$ is expressed in solar masses. The functional form of the relationship is only weakly constrained and extrapolation outside this range is not advised. Our late-type galaxies, in contrast to our early-types, do not show the tendency for l...

  19. Globular Cluster Populations: First Results from S$^4$G Early-Type Galaxies

    CERN Document Server

    Zaritsky, Dennis; Athanassoula, E; Bosma, Albert; Comerón, Sébastien; Elmegreen, Bruce G; Erroz-Ferrer, Santiago; Gadotti, Dimitri A; Hinz, Joannah L; Ho, Luis C; Holwerda, Benne; Knapen, Johan H; Laine, Jarkko; Laurikainen, Eija; Muñoz-Mateos, Juan Carlos; Salo, Heikki; Sheth, Kartik

    2014-01-01

    Using 3.6$\\mu$m images of 97 early-type galaxies, we develop and verify methodology to measure globular cluster populations from the S$^4$G survey images. We find that 1) the ratio, T$_{\\rm N}$, of the number of clusters, N$_{\\rm CL}$, to parent galaxy stellar mass, M$_*$, rises weakly with M$_*$ for early-type galaxies with M$_* > 10^{10}$ M$_\\odot$ when we calculate galaxy masses using a universal stellar initial mass function (IMF), but that the dependence of T$_{\\rm N}$ on M$_*$ is removed entirely once we correct for the recently uncovered systematic variation of IMF with M$_*$, and 2) for M$_* 10^{10}$ M$_\\odot$ and can be as large as $\\sim 0.02$ for less massive galaxies. These are the first results from the S$^4$G sample of galaxies, and will be enhanced by the sample of early-type galaxies now being added to S$^4$G and complemented by the study of later type galaxies within S$^4$G.

  20. KaM_CRK: Clustering and Ranking Knowledge for Reasonable Results Based on Behaviors and Contexts

    Directory of Open Access Journals (Sweden)

    Changhong Hu

    2013-01-01

    Full Text Available A model named KaM_CRK is proposed, which can supply the clustered and ranked knowledge to the users on different contexts. By comparing the attributes of contexts and JANs, our findings indicate that our model can accumulate the JANs, whose attributes are similar with the user’s contexts, together. By applying the KaM_CLU algorithm and Centre rank strategy into the KaM_CRK model, the model boosts a significant promotion on the accuracy of provision of user's knowledge. By analyzing the users' behaviors, the dynamic coefficient BehaviorF is first presented in KaM_CLU. Compared to traditional approaches of K_means and DBSCAN, the KaM_CLU algorithm does not need to initialize the number of clusters. Additionally, its synthetic results are more accurate, reasonable, and fit than other approaches for users. It is known from our evaluation through real data that our strategy performs better on time efficiency and user's satisfaction, which will save by 30% and promote by 5%, respectively.

  1. Planck Intermediate Results. V. Pressure profiles of galaxy clusters from the Sunyaev-Zeldovich effect

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Atrio-Barandela, F; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartlett, J G; Battaner, E; Benabed, K; Benoît, A; Bernard, J -P; Bersanelli, M; Bhatia, R; Böhringer, H; Bonaldi, A; Bond, J R; Borgani, S; Borrill, J; Bouchet, F R; Bourdin, H; Brown, M L; Burigana, C; Cabella, P; Cardoso, J -F; Carvalho, P; Castex, G; Catalano, A; Cayón, L; Chamballu, A; Chiang, L -Y; Chon, G; Christensen, P R; Churazov, E; Clements, D L; Colafrancesco, S; Colombi, S; Colombo, L P L; Comis, B; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Danese, L; Davis, R J; de Bernardis, P; de Gasperis, G; de Zotti, G; Delabrouille, J; Démoclès, J; Désert, F -X; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Dörl, U; Douspis, M; Dupac, X; Efstathiou, G; Ensslin, T A; Eriksen, H K; Finelli, F; Flores-Cacho, I; Forni, O; Fosalba, P; Frailis, M; Franceschi, E; Frommert, M; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Giraud-Héraud, Y; González-Nuevo, J; Górski, K M; Gregorio, A; Gruppuso, A; Hansen, F K; Harrison, D; Hempel, A; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hurier, G; Jaffe, T R; Jaffe, A H; Jagemann, T; Jones, W C; Juvela, M; Keihänen, E; Kisner, T S; Kneissl, R; Knoche, J; Knox, L; Kunz, M; Kurki-Suonio, H; Lagache, G; Lähteenmäki, A; Lamarre, J -M; Lasenby, A; Lawrence, C R; Jeune, M Le; Leonardi, R; Liddle, A; Lilje, P B; LÛpez-Caniego, M; Luzzi, G; Macías-Pérez, J F; Maino, D; Mandolesi, N; Maris, M; Marleau, F; Marshall, D J; Martínez-González, E; Masi, S; Massardi, M; Matarrese, S; Mazzotta, P; Mei, S; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, J A; Naselsky, P; Nati, F; Natoli, P; Nørgaard-Nielsen, H U; Noviello, F; Osborne, S; Pajot, F; Paoletti, D; Pasian, F; Patanchon, G; Perdereau, O; Perotto, L; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Popa, L; Poutanen, T; Pratt, G W; Prunet, S; Puget, J -L; Rachen, J P; Reach, W T; Rebolo, R; Reinecke, M; Remazeilles, M; Renault, C; Ricciardi, S; Riller, T; Ristorcelli, I; Rocha, G; Roman, M; Rosset, C; Rossetti, M; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Savini, G; Scott, D; Smoot, G F; Starck, J -L; Sudiwala, R; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Tuovinen, J; Valenziano, L; Van Tent, B; Varis, J; Vielva, P; Villa, F; Vittorio, N; Wade, L A; Wandelt, B D; Welikala, N; White, S D M; White, M; Yvon, D; Zacchei, A; Zonca, A

    2012-01-01

    Taking advantage of the all-sky coverage and broad frequency range of the Planck satellite, we study the Sunyaev-Zeldovich (SZ) and pressure profiles of 62 nearby massive clusters detected at high significance in the 14-month nominal survey. Careful reconstruction of the SZ signal indicates that most clusters are individually detected at least out to R500. By stacking the radial profiles, we have statistically detected the radial SZ signal out to 3R500, i.e., at a density contrast of about 50-100, though the dispersion about the mean profile dominates the statistical errors across the whole radial range. Our measurement is fully consistent with previous Planck results on integrated SZ fluxes, further strengthening the agreement between SZ and X-ray measurements inside R500. Correcting for the effects of the Planck beam, we have calculated the corresponding pressure profiles. This new constraint from SZ measurements is consistent with the X-ray constraints from xmm in the region in which the profiles overlap (...

  2. 基于多聚类结果融合的轨迹聚类方法%Trajectory Clustering Method Based on Multi-clustering Results Merging

    Institute of Scientific and Technical Information of China (English)

    李静; 张磊; 韩陈寿

    2011-01-01

    针对轨迹聚类结果的不可靠性,提出一种基于多聚类结果融合的轨迹聚类方法MRMTC.对于多聚类器产生的多个聚类代表轨迹,提出了轨迹合并算法,实现了多个聚类代表轨迹的合并.代表轨迹合并算法以平均扫描线距离函数作为共识函数,通过共识函数对代表轨迹间的相似度进行比较,最后合并相似的代表轨迹.实验表明基于融合的轨迹聚类方法,可以获得比单一聚类更有效更稳定的聚类结果.%In view of the unreliable of trajectory clustering results,a trajectory clustering method based on multi-clustering results merging(MRMTC) is proposed in this paper.For the representative trajectories of multi-clustering generated by clustering devices,a trajectory merging algorithm is proposed to merge them.The merging algorithm uses average scan line distance function as consensus function to compare similarities of representative trajectories,and then merges the similar representative trajectories.Finally,experiments results show that the proposed method MRMTC can produce more stable and effective clustering results.

  3. 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

  4. Hierarchical Star Formation in Nearby LEGUS Galaxies

    CERN Document Server

    Elmegreen, Debra Meloy; Adamo, Angela; Aloisi, Alessandra; Andrews, Jennifer; Annibali, Francesca; Bright, Stacey N; Calzetti, Daniela; Cignoni, Michele; Evans, Aaron S; Gallagher, John S; Gouliermis, Dimitrios A; Grebel, Eva K; Hunter, Deidre A; Johnson, Kelsey; Kim, Hwi; Lee, Janice; Sabbi, Elena; Smith, Linda; Thilker, David; Tosi, Monica; Ubeda, Leonardo

    2014-01-01

    Hierarchical structure in ultraviolet images of 12 late-type LEGUS galaxies is studied by determining the numbers and fluxes of nested regions as a function of size from ~1 to ~200 pc, and the number as a function of flux. Two starburst dwarfs, NGC 1705 and NGC 5253, have steeper number-size and flux-size distributions than the others, indicating high fractions of the projected areas filled with star formation. Nine subregions in 7 galaxies have similarly steep number-size slopes, even when the whole galaxies have shallower slopes. The results suggest that hierarchically structured star-forming regions several hundred parsecs or larger represent common unit structures. Small galaxies dominated by only a few of these units tend to be starbursts. The self-similarity of young stellar structures down to parsec scales suggests that star clusters form in the densest parts of a turbulent medium that also forms loose stellar groupings on larger scales. The presence of super star clusters in two of our starburst dwarf...

  5. Evolution of Terrorist Network using Clustered approach: A Case study

    DEFF Research Database (Denmark)

    2011-01-01

    In the paper we present a cluster based approach for terrorist network evolution. We have applied hierarchical agglomerative clustering approach to 9/11 case study. We show that, how individual actors who are initially isolated from each other are converted in small clusters and result in a fully...... evolved network. This method of network evolution can help intelligence security analysts to understand the structure of the network....

  6. Hierarchical method of task assignment for multiple cooperating UAV teams

    Institute of Scientific and Technical Information of China (English)

    Xiaoxuan Hu; Huawei Ma; Qingsong Ye; He Luo

    2015-01-01

    The problem of task assignment for multiple cooperat-ing unmanned aerial vehicle (UAV) teams is considered. Multiple UAVs forming several smal teams are needed to perform attack tasks on a set of predetermined ground targets. A hierarchical task assignment method is presented to address the problem. It breaks the original problem down to three levels of sub-problems: tar-get clustering, cluster al ocation and target assignment. The first two sub-problems are central y solved by using clustering algo-rithms and integer linear programming, respectively, and the third sub-problem is solved in a distributed and paral el manner, using a mixed integer linear programming model and an improved ant colony algorithm. The proposed hierarchical method can reduce the computational complexity of the task assignment problem con-siderably, especial y when the number of tasks or the number of UAVs is large. Experimental results show that this method is feasi-ble and more efficient than non-hierarchical methods.

  7. Selections of data preprocessing methods and similarity metrics for gene cluster analysis

    Institute of Scientific and Technical Information of China (English)

    YANG Chunmei; WAN Baikun; GAO Xiaofeng

    2006-01-01

    Clustering is one of the major exploratory techniques for gene expression data analysis. Only with suitable similarity metrics and when datasets are properly preprocessed, can results of high quality be obtained in cluster analysis. In this study, gene expression datasets with external evaluation criteria were preprocessed as normalization by line, normalization by column or logarithm transformation by base-2, and were subsequently clustered by hierarchical clustering, k-means clustering and self-organizing maps (SOMs) with Pearson correlation coefficient or Euclidean distance as similarity metric. Finally, the quality of clusters was evaluated by adjusted Rand index. The results illustrate that k-means clustering and SOMs have distinct advantages over hierarchical clustering in gene clustering, and SOMs are a bit better than k-means when randomly initialized. It also shows that hierarchical clustering prefers Pearson correlation coefficient as similarity metric and dataset normalized by line. Meanwhile, k-means clustering and SOMs can produce better clusters with Euclidean distance and logarithm transformed datasets. These results will afford valuable reference to the implementation of gene expression cluster analysis.

  8. Planck early results. XI. Calibration of the local galaxy cluster Sunyaev-Zeldovich scaling relations

    DEFF Research Database (Denmark)

    Bucher, M.; Delabrouille, J.; Giraud-Héraud, Y.;

    2011-01-01

    corresponding to a total density contrast of 500. Combining these high quality Planck measurements with deep XMM-Newton X-ray data, we investigate the relations between DA2 Y500, the integrated Compton parameter due to the SZ effect, and the X-ray-derived gas mass M g,500, temperature TX, luminosity LX,500, SZ...... signal analogue YX,500 = Mg,500 × TX, and total mass M500. After correction for the effect of selection bias on the scaling relations, we find results that are in excellent agreement with both X-ray predictions and recently-published ground-based data derived from smaller samples. The present data yield......We present precise Sunyaev-Zeldovich (SZ) effect measurements in the direction of 62 nearby galaxy clusters (z mass, 2 × 1014 M mass...

  9. Synthesis of New Dynamic Movement Primitives Through Search in a Hierarchical Database of Example Movements

    Directory of Open Access Journals (Sweden)

    Miha Deniša

    2015-10-01

    Full Text Available This paper presents a novel approach to discovering motor primitives in a hierarchical database of example trajectories. An initial set of example trajectories is obtained by human demonstration. The trajectories are clustered and organized in a binary tree-like hierarchical structure, from which transition graphs at different levels of granularity are constructed. A novel procedure for searching in this hierarchical structure is presented. It can exploit the interdependencies between movements and can discover new series of partial paths. From these partial paths, complete new movements are generated by encoding them as dynamic movement primitives. In this way, the number of example trajectories that must be acquired with the assistance of a human teacher can be reduced. By combining the results of the hierarchical search with statistical generalization techniques, a complete representation of new, not directly demonstrated, movement primitives can be generated.

  10. A Survey of Open Clusters in the u'g'r'i'z' Filter System. 3. Results for the Cluster NGC 188

    Energy Technology Data Exchange (ETDEWEB)

    Fornal, Bartosz; Tucker, Douglas L.; Smith, J.Allyn; Allam, Sahar S.; Rider, Cristin J.; Sung, Hwankyung; /Jagiellonian U. /Fermilab /Austin Peay State U. /Wyoming U. /Johns Hopkins U. /Sejong U.

    2006-11-01

    The authors continue the series of papers describing the results of a photometric survey of open star clusters, primarily in the southern hemisphere, taken in the u'g'r'i'z' filter system. The entire observed sample covered more than 100 clusters, but here they present data only on NGC 188, which is one of the oldest open clusters known in the Milky Way. They fit the Padova theoretical isochrones to the data. Assuming a solar metallicity for NGC 188, they find a distance of 1700 {+-} 100 pc, an age of 7.5 {+-} 0.7 Gyr, and a reddening E(B-V) of 0.025 {+-} 0.005. This yields a distance modulus of 11.23 {+-} 0.14.

  11. Weighted Clustering

    CERN Document Server

    Ackerman, Margareta; Branzei, Simina; Loker, David

    2011-01-01

    In this paper we investigate clustering in the weighted setting, in which every data point is assigned a real valued weight. We conduct a theoretical analysis on the influence of weighted data on standard clustering algorithms in each of the partitional and hierarchical settings, characterising the precise conditions under which such algorithms react to weights, and classifying clustering methods into three broad categories: weight-responsive, weight-considering, and weight-robust. Our analysis raises several interesting questions and can be directly mapped to the classical unweighted setting.

  12. Planck early results. XII. Cluster Sunyaev-Zeldovich optical scaling relations

    DEFF Research Database (Denmark)

    Bucher, M.; Delabrouille, J.; Giraud-Héraud, Y.

    2011-01-01

    We present the Sunyaev-Zeldovich (SZ) signal-to-richness scaling relation (Y500 - N200) for the MaxBCG cluster catalogue. Employing a multi-frequency matched filter on the Planck sky maps, we measure the SZ signal for each cluster by adapting the filter according to weak-lensing calibrated mass-r...

  13. Intermittent thermal plasma acceleration linked to sporadic motions of the magnetopause, first Cluster results

    Directory of Open Access Journals (Sweden)

    J.-A. Sauvaud

    Full Text Available This paper presents the first observations with Cluster of a very dense population of thermal ionospheric ions (H+, He+, O+ locally "accelerated" perpendicularly to the local magnetic field in a region adjacent to the magnetopause and on its magnetospheric side. The observation periods follow a long period of very weak magnetic activity. Recurrent motions of the magnetopause are, in the presented cases, unexpectedly associated with the appearance inside closed field lines of recurrent energy structures of ionospheric ions with energies in the 5 eV to  ~1000 eV range. The heaviest ions were detected with the highest energies. Here, the ion behaviour is interpreted as resulting from local electric field enhancements/decreases which adiabatically enhance/lower the bulk energy of a local dense thermal ion population. This drift effect, which is directly linked to magnetopause motions caused by pressure changes, allows for the thermal ions to overcome the satellite potential and be detected by the suprathermal CIS Cluster experiment. When fast flowing, i.e. when detectable, the density (~ 1 cm-3 of these ions from a terrestrial origin is (in the cases presented here largely higher than the local density of ions from magnetospheric/plasma sheet origin which poses again the question of the relative importance of solar and ionospheric sources for the magnetospheric plasma even during very quiet magnetic conditions.

    Key words. Ionosphere (planetary ionosphere; plasma convection Magnetospheric physics (magnetopause, cusp and boundary layers

  14. Planck 2015 results. XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Aumont, J; Baccigalupi, C; Banday, A J; Barreiro, R B; Bartlett, J G; Bartolo, N; Battaner, E; Battye, R; Benabed, K; Benoît, A; Benoit-Lévy, A; Bernard, J -P; Bersanelli, M; Bielewicz, P; Bonaldi, A; Bonavera, L; Bond, J R; Borrill, J; Bouchet, F R; Bucher, M; Burigana, C; Butler, R C; Calabrese, E; Cardoso, J -F; Catalano, A; Challinor, A; Chamballu, A; Chary, R -R; Chiang, H C; Christensen, P R; Church, S; Clements, D L; Colombi, S; Colombo, L P L; Combet, C; Comis, B; Couchot, F; Coulais, A; Crill, B P; Curto, A; Cuttaia, F; Danese, L; Davies, R D; Davis, R J; de Bernardis, P; de Rosa, A; de Zotti, G; Delabrouille, J; Désert, F -X; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Douspis, M; Ducout, A; Dupac, X; Efstathiou, G; Elsner, F; Enßlin, T A; Eriksen, H K; Falgarone, E; Fergusson, J; Finelli, F; Forni, O; Frailis, M; Fraisse, A A; Franceschi, E; Frejsel, A; Galeotta, S; Galli, S; Ganga, K; Giard, M; Giraud-Héraud, Y; Gjerløw, E; González-Nuevo, J; Górski, K M; Gratton, S; Gregorio, A; Gruppuso, A; Gudmundsson, J E; Hansen, F K; Hanson, D; Harrison, D L; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hornstrup, A; Hovest, W; Huffenberger, K M; Hurier, G; Jaffe, A H; Jaffe, T R; Jones, W C; Juvela, M; Keihänen, E; Keskitalo, R; Kisner, T S; Kneissl, R; Knoche, J; Kunz, M; Kurki-Suonio, H; Lagache, G; Lähteenmäki, A; Lamarre, J -M; Lasenby, A; Lattanzi, M; Lawrence, C R; Leonardi, R; Lesgourgues, J; Levrier, F; Liguori, M; Lilje, P B; Linden-Vørnle, M; López-Caniego, M; Lubin, P M; Macías-Pérez, J F; Maggio, G; Maino, D; Mandolesi, N; Mangilli, A; Martin, P G; Martínez-González, E; Masi, S; Matarrese, S; Mazzotta, P; McGehee, P; Meinhold, P R; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Migliaccio, M; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Moss, A; Munshi, D; Murphy, J A; Naselsky, P; Nati, F; Natoli, P; Netterfield, C B; Nørgaard-Nielsen, H U; Noviello, F; Novikov, D; Novikov, I; Oxborrow, C A; Paci, F; Pagano, L; Pajot, F; Paoletti, D; Partridge, B; Pasian, F; Patanchon, G; Pearson, T J; Perdereau, O; Perotto, L; Perrotta, F; Pettorino, V; Piacentini, F; Piat, M; Pierpaoli, E; Pietrobon, D; Plaszczynski, S; Pointecouteau, E; Polenta, G; Popa, L; Pratt, G W; Prézeau, G; Prunet, S; Puget, J -L; Rachen, J P; Rebolo, R; Reinecke, M; Remazeilles, M; Renault, C; Renzi, A; Ristorcelli, I; Rocha, G; Roman, M; Rosset, C; Rossetti, M; Roudier, G; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Santos, D; Savelainen, M; Savini, G; Scott, D; Seiffert, M D; Shellard, E P S; Spencer, L D; Stolyarov, V; Stompor, R; Sudiwala, R; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Tucci, M; Tuovinen, J; Türler, M; Umana, G; Valenziano, L; Valiviita, J; Van Tent, B; Vielva, P; Villa, F; Wade, L A; Wandelt, B D; Wehus, I K; Weller, J; White, S D M; Yvon, D; Zacchei, A; Zonca, A

    2015-01-01

    We present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise of six, and is more than a factor of two larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing of background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, $1-b$. In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as a third independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of t...

  15. MYStIX First Results: Spatial Structures of Massive Young Stellar Clusters

    CERN Document Server

    Kuhn, Michael A; Feigelson, Eric D; Getman, Konstantin V; Broos, Patrick S; Townsley, Leisa K; Povich, Matthew S; Naylor, Tim; King, Robert R; Busk, Heather A; Luhman, Kevin L

    2012-01-01

    Observations of the spatial distributions of young stars in star-forming regions can be linked to the theory of clustered star formation using spatial statistical methods. The MYStIX project provides rich samples of young stars from the nearest high-mass star-forming regions. Maps of stellar surface density reveal diverse structure and subclustering. Young stellar clusters and subclusters are fit with isothermal spheres and ellipsoids using the Bayesian Information Criterion to estimate the number of subclusters. Clustering is also investigated using Cartwright and Whitworth's Q statistic and the inhomogeneous two-point correlation function. Mass segregation is detected in several cases, in both centrally concentrated and fractally structured star clusters, but a few clusters are not mass segregated.

  16. Different disease subtypes with distinct clinical expression in familial Mediterranean fever: results of a cluster analysis.

    Science.gov (United States)

    Akar, Servet; Solmaz, Dilek; Kasifoglu, Timucin; Bilge, Sule Yasar; Sari, Ismail; Gumus, Zeynep Zehra; Tunca, Mehmet

    2016-02-01

    The aim of this study was to evaluate whether there are clinical subgroups that may have different prognoses among FMF patients. The cumulative clinical features of a large group of FMF patients [1168 patients, 593 (50.8%) male, mean age 35.3 years (s.d. 12.4)] were studied. To analyse our data and identify groups of FMF patients with similar clinical characteristics, a two-step cluster analysis using log-likelihood distance measures was performed. For clustering the FMF patients, we evaluated the following variables: gender, current age, age at symptom onset, age at diagnosis, presence of major clinical features, variables related with therapy and family history for FMF, renal failure and carriage of M694V. Three distinct groups of FMF patients were identified. Cluster 1 was characterized by a high prevalence of arthritis, pleuritis, erysipelas-like erythema (ELE) and febrile myalgia. The dosage of colchicine and the frequency of amyloidosis were lower in cluster 1. Patients in cluster 2 had an earlier age of disease onset and diagnosis. M694V carriage and amyloidosis prevalence were the highest in cluster 2. This group of patients was using the highest dose of colchicine. Patients in cluster 3 had the lowest prevalence of arthritis, ELE and febrile myalgia. The frequencies of M694V carriage and amyloidosis were lower in cluster 3 than the overall FMF patients. Non-response to colchicine was also slightly lower in cluster 3. Patients with FMF can be clustered into distinct patterns of clinical and genetic manifestations and these patterns may have different prognostic significance. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  17. 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...

  18. Collaborative Hierarchical Sparse Modeling

    CERN Document Server

    Sprechmann, Pablo; Sapiro, Guillermo; Eldar, Yonina C

    2010-01-01

    Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the sparsity-inducing property of the Lasso model, at the individual feature level, with the block-sparsity property of the group Lasso model, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the hierarchical Lasso, which shows important practical modeling advantages. We then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level but not necessarily at the lower one. Signals then share the same active groups, or classes, but not necessarily the same active set. This is very well suited for applications such as source separation. An efficient optimization procedure, which guarantees convergence to the global opt...

  19. Plasma convection in the magnetotail lobes: statistical results from Cluster EDI measurements

    Directory of Open Access Journals (Sweden)

    S. Haaland

    2008-08-01

    Full Text Available A major part of the plasma in the Earth's magnetotail is populated through transport of plasma from the solar wind via the magnetotail lobes. In this paper, we present a statistical study of plasma convection in the lobes for different directions of the interplanetary magnetic field and for different geomagnetic disturbance levels. The data set used in this study consists of roughly 340 000 one-minute vector measurements of the plasma convection from the Cluster Electron Drift Instrument (EDI obtained during the period February 2001 to June 2007. The results show that both convection magnitude and direction are largely controlled by the interplanetary magnetic field (IMF. For a southward IMF, there is a strong convection towards the central plasma sheet with convection velocities around 10 km s−1. During periods of northward IMF, the lobe convection is almost stagnant. A By dominated IMF causes a rotation of the convection patterns in the tail with an oppositely directed dawn-dusk component of the convection for the northern and southern lobe. Our results also show that there is an overall persistent duskward component, which is most likely a result of conductivity gradients in the footpoints of the magnetic field lines in the ionosphere.

  20. Planck Early Results: The all-sky Early Sunyaev-Zeldovich cluster sample

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartelmann, M; Bartlett, J G; Battaner, E; Battye, R; Benabed, K; Benoît, A; Bernard, J -P; Bersanelli, M; Bhatia, R; Bock, J J; Bonaldi, A; Bond, J R; Borrill, J; Bouchet, F R; Brown, M L; Bucher, M; Burigana, C; Cabella, P; Cantalupo, C M; Cardoso, J -F; Carvalho, P; Catalano, A; Cayón, L; Challinor, A; Chamballu, A; Chary, R -R; Chiang, L -Y; Chiang, C; Chon, G; Christensen, P R; Churazov, E; Clements, D L; Colafrancesco, S; Colombi, S; Couchot, F; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Danese, L; Davis, R J; de Bernardis, P; de Gasperis, G; de Rosa, A; de Zotti, G; Delabrouille, J; Delouis, J -M; Désert, F -X; Dickinson, C; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Dörl, U; Douspis, M; Dupac, X; Efstathiou, G; Eisenhardt, P; En\\sslin, T A; Feroz, F; Finelli, F; Flores, I; Forni, O; Fosalba, P; Frailis, M; Franceschi, E; Fromenteau, S; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Giardino, G; Giraud-Héraud, Y; González-Nuevo, J; González-Riestra, R; Górski, K M; Grainge, K J B; Gratton, S; Gregorio, A; Gruppuso, A; Harrison, D; Heinämäki, P; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hovest, W; Hoyland, R J; Huffenberger, K M; Hurier, G; Hurley-Walker, N; Jaffe, A H; Jones, W C; Juvela, M; Keihänen, E; Keskitalo, R; Kisner, T S; Kneissl, R; Knox, L; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lasenby, A; Laureijs, R J; Lawrence, C R; Jeune, M Le; Leach, S; Leonardi, R; Li, C; Liddle, A; Lilje, P B; Linden-V\\ornle, M; López-Caniego, M; Lubin, P M; Macías-Pérez, J F; MacTavish, C J; Maffei, B; Maino, D; Mandolesi, N; Mann, R; Maris, M; Marleau, F; Martínez-González, E; Masi, S; Matarrese, S; Matthai, F; Mazzotta, P; Mei, S; Meinhold, P R; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, A; Naselsky, P; Nati, F; Natoli, P; Netterfield, C B; N\\orgaard-Nielsen, H U; Noviello, F; Novikov, D; Novikov, I; Olamie, M; Osborne, S; Pajot, F; Pasian, F; Patanchon, G; Pearson, T J; Perdereau, O; Perotto, L; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Poutanen, T; Pratt, G W; Prézeau, G; Prunet, S; Puget, J -L; Rachen, J P; Reach, W T; Rebolo, R; Reinecke, M; Renault, C; Ricciardi, S; Riller, T; Ristorcelli, I; Rocha, G; Rosset, C; Rubi\; Rusholme, B; Saar, E; Sandri, M; Santos, D; Saunders, R D E; Savini, G; Schaefer, B M; Scott, D; Seiffert, M D; Shellard, P; Smoot, G F; Stanford, A; Starck, J -L; Stivoli, F; Stolyarov, V; Stompor, R; Sudiwala, R; Sunyaev, R; Sutton, D; Sygnet, J -F; Taburet, N; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Torre, J -P; Tristram, M; Tuovinen, J; Valenziano, L; Vibert, L; Vielva, P; Villa, F; Vittorio, N; Wade, L A; Wandelt, B D; Weller, J; White, S D M; White, M; Yvon, D; Zacchei, A; Zonca, A

    2011-01-01

    We present the first all-sky sample of galaxy clusters detected blindly by the Planck satellite through the Sunyaev-Zeldovich (SZ) effect from its six highest frequencies. This Early SZ (ESZ) sample of 189 candidates comprises high signal-to-noise clusters, from 6 to 29. Its high reliability (purity above 95%) is further insured by an extensive validation process based on Planck-internal quality assessments and external cross-identification and follow-up observations. Planck provides the first measured SZ signal for about 80% of the 169 ESZ known clusters. Planck further releases 30 new cluster candidates among which 20 are within the ESZ signal-to-noise selection criterion. Eleven of these 20 ESZ candidates are confirmed using XMM-Newton snapshot observations as new clusters, most of them with disturbed morphologies and low luminosities. The ESZ clusters are mostly at moderate redshifts (86% with z below 0.3) and span over a decade in mass, up to the rarest and most massive clusters with masses above 10^15 M...

  1. Indoleamine Hallucinogens in Cluster Headache: Results of the Clusterbusters Medication Use Survey.

    Science.gov (United States)

    Schindler, Emmanuelle A D; Gottschalk, Christopher H; Weil, Marsha J; Shapiro, Robert E; Wright, Douglas A; Sewell, Richard Andrew

    2015-01-01

    Cluster headache is one of the most debilitating pain syndromes. A significant number of patients are refractory to conventional therapies. The Clusterbusters.org medication use survey sought to characterize the effects of both conventional and alternative medications used in cluster headache. Participants were recruited from cluster headache websites and headache clinics. The final analysis included responses from 496 participants. The survey was modeled after previously published surveys and was available online. Most responses were chosen from a list, though others were free-texted. Conventional abortive and preventative medications were identified and their efficacies agreed with those previously published. The indoleamine hallucinogens, psilocybin, lysergic acid diethylamide, and lysergic acid amide, were comparable to or more efficacious than most conventional medications. These agents were also perceived to shorten/abort a cluster period and bring chronic cluster headache into remission more so than conventional medications. Furthermore, infrequent and non-hallucinogenic doses were reported to be efficacious. Findings provide additional evidence that several indoleamine hallucinogens are rated as effective in treating cluster headache. These data reinforce the need for further investigation of the effects of these and related compounds in cluster headache under experimentally controlled settings.

  2. References for Galaxy Clusters Database

    OpenAIRE

    Kalinkov, M.; Valtchanov, I.; Kuneva, I.

    1998-01-01

    A bibliographic database will be constructed with the purpose to be a general tool for searching references for galaxy clusters. The structure of the database will be completely different from the available now databases as NED, SIMBAD, LEDA. Search based on hierarchical keyword system will be performed through web interfaces from numerous bibliographic sources -- journal articles, preprints, unpublished results and papers, theses, scientific reports. Data from the very beginning of the extra...

  3. Block-based logical hierarchical cluster for distributed multimedia architecture on demand server%基于块的逻辑层次集群:一种分布式多媒体点播服务器的体系结构

    Institute of Scientific and Technical Information of China (English)

    熊旭辉; 余胜生; 周敬利

    2006-01-01

    A structure of logical hierarchical cluster for the distributed multimedia on demand server is proposed. The architecture is mainly composed of the network topology and the resource management of all server nodes. Instead of the physical network hierarchy or the independent management hierarchy, the nodes are organized into a logically hierarchical cluster according to the multimedia block they caches in the midderware layer. The process of a member joining/leaving or the structure adjustment cooperatively implemented by all members is concerned with decentralized maintenance of the logical cluster hierarchy. As the root of each logically hierarchical cluster is randomly mapped into the system, the logical structure of a multimedia block is dynamically expanded across some regions by the two replication policies in different load state respectively. The local load diversion is applied to fine-tune the load of nodes within a local region but belongs to different logical hierarchies. Guaranteed by the dynamic expansion of a logical structure and the load diversion of a local region, the users always select a closest idle node from the logical hierarchy under the condition of topology integration with resource management.

  4. Planck early results. IX. XMM-Newton follow-up for validation of Planck cluster candidates

    DEFF Research Database (Denmark)

    Bucher, M.; Delabrouille, J.; Giraud-Héraud, Y.;

    2011-01-01

    to observe a sample of S/N > 5 candidates. The sensitivity and spatial resolution of XMM-Newton allows unambiguous discrimination between clusters and false candidates. The 4 false candidates have S/N = 4.1. A total of 21 candidates are confirmed as extended X-ray sources. Seventeen are single clusters...... suggest that Planck may have started to reveal a non-negligible population of massive dynamically perturbed objects that is under-represented in X-ray surveys. However, despite their particular properties, these new clusters appear to follow the Y500-YX relation established for X-ray selected objects...

  5. Planck intermediate results. XLIII. The spectral energy distribution of dust in clusters of galaxies

    CERN Document Server

    Adam, R; Aghanim, N; Ashdown, M; Aumont, J; Baccigalupi, C; Barreiro, R B; Bartolo, N; Battaner, E; Benabed, K; Benoit-Lévy, A; Bersanelli, M; Bielewicz, P; Bikmaev, I; Bonaldi, A; Bond, J R; Borrill, J; Bouchet, F R; Burenin, R; Burigana, C; Calabrese, E; Cardoso, J -F; Catalano, A; Chiang, H C; Christensen, P R; Churazov, E; Colombo, L P L; Combet, C; Comis, B; Couchot, F; Crill, B P; Curto, A; Cuttaia, F; Danese, L; Davis, R J; de Bernardis, P; de Rosa, A; de Zotti, G; Delabrouille, J; Désert, F -X; Diego, J M; Dole, H; Doré, O; Douspis, M; Ducout, A; Dupac, X; Elsner, F; Enßlin, T A; Finelli, F; Forni, O; Frailis, M; Fraisse, A A; Franceschi, E; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Giraud-Héraud, Y; Gjerløw, E; González-Nuevo, J; Gregorio, A; Gruppuso, A; Gudmundsson, J E; Hansen, F K; Harrison, D L; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Hornstrup, A; Hovest, W; Hurier, G; Jaffe, A H; Jaffe, T R; Jones, W C; Keihänen, E; Keskitalo, R; Khamitov, I; Kisner, T S; Kneissl, R; Knoche, J; Kunz, M; Kurki-Suonio, H; Lagache, G; Lähteenmäki, A; Lamarre, J -M; Lasenby, A; Lattanzi, M; Lawrence, C R; Leonardi, R; Levrier, F; Liguori, M; Lilje, P B; Linden-Vørnle, M; López-Caniego, M; Macías-Pérez, J F; Maffei, B; Maggio, G; Mandolesi, N; Mangilli, A; Maris, M; Martin, P G; Martínez-González, E; Masi, S; Matarrese, S; Melchiorri, A; Mennella, A; Migliaccio, M; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, J A; Naselsky, P; Nati, F; Natoli, P; Nørgaard-Nielsen, H U; Novikov, D; Novikov, I; Oxborrow, C A; Pagano, L; Pajot, F; Paoletti, D; Pasian, F; Perdereau, O; Perotto, L; Pettorino, V; Piacentini, F; Piat, M; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Pratt, G W; Prunet, S; Puget, J -L; Rachen, J P; Rebolo, R; Reinecke, M; Remazeilles, M; Renault, C; Renzi, A; Ristorcelli, I; Rocha, G; Rosset, C; Rossetti, M; Roudier, G; Rubiño-Martín, J A; Rusholme, B; Santos, D; Savelainen, M; Savini, G; Scott, D; Stolyarov, V; Stompor, R; Sudiwala, R; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Tucci, M; Valenziano, L; Valiviita, J; Van Tent, F; Vielva, P; Villa, F; Wade, L A; Wehus, I K; Yvon, D; Zacchei, A; Zonca, A

    2016-01-01

    Although infrared (IR) overall dust emission from clusters of galaxies has been statistically detected using data from the Infrared Astronomical Satellite (IRAS), it has not been possible to sample the spectral energy distribution (SED) of this emission over its peak, and thus to break the degeneracy between dust temperature and mass. By complementing the IRAS spectral coverage with Planck satellite data from 100 to 857 GHz, we provide new constraints on the IR spectrum of thermal dust emission in clusters of galaxies. We achieve this by using a stacking approach for a sample of several hundred objects from the Planck cluster sample; this procedure averages out fluctuations from the IR sky, allowing us to reach a significant detection of the faint cluster contribution. We also use the large frequency range probed by Planck, together with component-separation techniques, to remove the contamination from both cosmic microwave background anisotropies and the thermal Sunyaev-Zeldovich effect (tSZ) signal, which d...

  6. Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

    DEFF Research Database (Denmark)

    Ade, P. A R; Aghanim, N.; Arnaud, M.;

    2016-01-01

    because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. Improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses...

  7. Finite Population Correction for Two-Level Hierarchical Linear Models.

    Science.gov (United States)

    Lai, Mark H C; Kwok, Oi-Man; Hsiao, Yu-Yu; Cao, Qian

    2017-03-16

    The research literature has paid little attention to the issue of finite population at a higher level in hierarchical linear modeling. In this article, we propose a method to obtain finite-population-adjusted standard errors of Level-1 and Level-2 fixed effects in 2-level hierarchical linear models. When the finite population at Level-2 is incorrectly assumed as being infinite, the standard errors of the fixed effects are overestimated, resulting in lower statistical power and wider confidence intervals. The impact of ignoring finite population correction is illustrated by using both a real data example and a simulation study with a random intercept model and a random slope model. Simulation results indicated that the bias in the unadjusted fixed-effect standard errors was substantial when the Level-2 sample size exceeded 10% of the Level-2 population size; the bias increased with a larger intraclass correlation, a larger number of clusters, and a larger average cluster size. We also found that the proposed adjustment produced unbiased standard errors, particularly when the number of clusters was at least 30 and the average cluster size was at least 10. We encourage researchers to consider the characteristics of the target population for their studies and adjust for finite population when appropriate. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. The Cluster Magnetic Field Investigation: overview of in-flight performance and initial results

    OpenAIRE

    A. Balogh; Carr, C. M.; Acuña, M. H.; M. W. Dunlop; Beek, T. J.; Brown, P.; Fornacon, K.-H.; Georgescu, E.; Glassmeier, K.-H.; Harris, J.; Musmann, G.; Oddy, T.; Schwingenschuh, K.

    2001-01-01

    The accurate measurement of the magnetic field along the orbits of the four Cluster spacecraft is a primary objective of the mission. The magnetic field is a key constituent of the plasma in and around the magnetosphere, and it plays an active role in all physical processes that define the structure and dynamics of magnetospheric phenomena on all scales. With the four-point measurements on Cluster, it has become possible to study the three-dimensional aspects of space plasma ...

  9. First results from the VIMOS-IFU survey of gravitationally lensing clusters at z~0.2

    CERN Document Server

    Covone, G; Soucail, G; Jullo, E; Richard, J; Covone, Giovanni; Kneib, Jean-Paul; Soucail, Genevieve; Jullo, Eric; Richard, Johan

    2006-01-01

    We present the on-going observational program of a VIMOS Integral Field Unit survey of the central regions of massive, gravitational lensing galaxy clusters at redshift z~0.2. We have observed six clusters using the low-resolution blue grism (R about 200), and the spectroscopic survey is complemented by a wealth of photometric data, including Hubble Space Telescope optical data and near infrared VLT data. The principal scientific aims of this project are: the study of the high-z lensed galaxies, the transformation and evolution of galaxies in cluster cores and the use of multiple images to constrain cosmography. We briefly report here on the first results from this project on the clusters Abell 2667 and Abell 68.

  10. Hierarchical architecture of active knits

    Science.gov (United States)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-12-01

    Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm.

  11. 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.

  12. Planck Early Results: Calibration of the local galaxy cluster Sunyaev-Zeldovich scaling relations

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartelmann, M; Bartlett, J G; Battaner, E; Benabed, K; Benoît, A; Bernard, J -P; Bersanelli, M; Bhatia, R; Bock, J J; Bonaldi, A; Bond, J R; Borrill, J; Bouchet, F R; Bourdin, H; Brown, M L; Bucher, M; Burigana, C; Cabella, P; Cardoso, J -F; Catalano, A; Cayón, L; Challinor, A; Chamballu, A; Chiang, L -Y; Chiang, C; Chon, G; Christensen, P R; Churazov, E; Clements, D L; Colafrancesco, S; Colombi, S; Couchot, F; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Danese, L; de Bernardis, P; de Gasperis, G; de Rosa, A; de Zotti, G; Delabrouille, J; Delouis, J -M; Désert, F -X; Diego, J M; Dolag, K; Donzelli, S; Doré, O; Dörl, U; Douspis, M; Dupac, X; Efstathiou, G; En\\sslin, T A; Finelli, F; Flores, I; Forni, O; Frailis, M; Franceschi, E; Fromenteau, S; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Giardino, G; Giraud-Héraud, Y; González-Nuevo, J; Górski, K M; Gratton, S; Gregorio, A; Gruppuso, A; Harrison, D; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hovest, W; Hoyland, R J; Huffenberger, K M; Jaffe, A H; Jones, W C; Juvela, M; Keihänen, E; Keskitalo, R; Kisner, T S; Kneissl, R; Knox, L; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lanoux, J; Lasenby, A; Laureijs, R J; Lawrence, C R; Leach, S; Leonardi, R; Liddle, A; Lilje, P B; Linden-V\\ornle, M; López-Caniego, M; Lubin, P M; Macías-Pérez, J F; MacTavish, C J; Maffei, B; Maino, D; Mandolesi, N; Mann, R; Maris, M; Marleau, F; Martínez-González, E; Masi, S; Matarrese, S; Matthai, F; Mazzotta, P; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, A; Naselsky, P; Natoli, P; Netterfield, C B; N\\orgaard-Nielsen, H U; Noviello, F; Novikov, D; Novikov, I; Osborne, S; Pajot, F; Pasian, F; Patanchon, G; Perdereau, O; Perotto, L; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Poutanen, T; Pratt, G W; Prézeau, G; Prunet, S; Puget, J -L; Rachen, J P; Rebolo, R; Reinecke, M; Renault, C; Ricciardi, S; Riller, T; Ristorcelli, I; Rocha, G; Rosset, C; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Santos, D; Savini, G; Schaefer, B M; Scott, D; Seiffert, M D; Shellard, P; Smoot, G F; Starck, J -L; Stivoli, F; Stolyarov, V; Sudiwala, R; Sunyaev, R; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Torre, J -P; Tristram, M; Tuovinen, J; Valenziano, L; Vibert, L; Vielva, P; Villa, F; Vittorio, N; Wade, L A; Wandelt, B D; White, S D M; White, M; Yvon, D; Zacchei, A; Zonca, A

    2011-01-01

    We present precise Sunyaev-Zeldovich (SZ) effect measurements in the direction of 62 nearby galaxy clusters (z <0.5) detected at high signal-to-noise in the first Planck all-sky dataset. The sample spans approximately a decade in total mass, 10^14 < M_500 < 10^15, where M_500 is the mass corresponding to a total density contrast of 500. Combining these high quality Planck measurements with deep XMM-Newton X-ray data, we investigate the relations between D_A^2 Y_500, the integrated Compton parameter due to the SZ effect, and the X-ray-derived gas mass M_g,500, temperature T_X, luminosity L_X, SZ signal analogue Y_X,500 = M_g,500 * T_X, and total mass M_500. After correction for the effect of selection bias on the scaling relations, we find results that are in excellent agreement with both X-ray predictions and recently-published ground-based data derived from smaller samples. The present data yield an exceptionally robust, high-quality local reference, and illustrate Planck's unique capabilities for a...

  13. [The attitude of German veterinarians towards farm animal welfare: results of a cluster analysis].

    Science.gov (United States)

    Heise, Heinke; Kemper, Nicole; Theuvsen, Ludwig

    2016-01-01

    In recent years the issue of animal welfare in intensive livestock production systems has been subjected to increasing criticism from the broad public. Some groups in society ask for higher animal welfare standards and there is an increas- ing number of consumers who prefer meat from more animal friendly husbandry systems. An intense social debate on animal welfare has flared up in the recent past. Veterinarians are considered as experts for the assessment of animal welfare. Nevertheless they are rarely consulted in the current debate. Therefore, only little is known about their attitude towards animal welfare in livestock farming. Even for Germany, there is so far no comprehensive analysis about their atti- tudes towards animal welfare and animal welfare programs. In the present study, 433 veterinarians were questioned via an online survey. The results show that veterinarians have a very differentiated perception of the issue animal welfare. Four groups (clusters) which have different attitudes towards livestock farming, voluntary animal welfare programs, farm size and the effects of national animal welfare standards were identified.

  14. Photometric and clustering properties of hydrodynamical galaxies in a cosmological volume: results at z=0

    CERN Document Server

    Nuza, S E; Saro, A

    2010-01-01

    In this work, we present results for the photometric and clustering properties of galaxies that arise in a LambdaCDM hydrodynamical simulation of the local Universe. The present-day distribution of matter was constructed to match the observed large scale pattern of the IRAS 1.2-Jy galaxy survey. Our simulation follows the formation and evolution of galaxies in a cosmological sphere with a volume of ~130^3 (Mpc/h)^3 including supernova feedback, galactic winds, photoheating due to an uniform meta-galactic background and chemical enrichment of the gas and stellar populations. However, we do not consider AGNs. In the simulation, a total of ~20000 galaxies are formed above the resolution limit, and around 60 haloes are more massive than ~10^14 M_sun. Luminosities of the galaxies are calculated based on a stellar population synthesis model including the attenuation by dust, which is calculated from the cold gas left within the simulated galaxies. Environmental effects like colour bi-modality and differential clust...

  15. Data clustering theory, algorithms, and applications

    CERN Document Server

    Gan, Guojun; Wu, Jianhong

    2007-01-01

    Cluster analysis is an unsupervised process that divides a set of objects into homogeneous groups. This book starts with basic information on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50 clustering algorithms in groups according to some specific baseline methodologies such as hierarchical, center-based, and search-based methods. As a result, readers and users can easily identify an appropriate algorithm for their applications and compare novel ideas with existing results. The book also provides examples of clustering applications to illustrate the advantages and shortcomings of different clustering architectures and algorithms. Application areas include pattern recognition, artificial intelligence, information technology, image processing, biology, psychology, and marketing. Readers also learn how to perform cluster analysis with the C/C++ and MATLAB® programming languages.

  16. Investigating nurses' knowledge, attitudes, and skills patterns towards clinical management system: results of a cluster analysis.

    Science.gov (United States)

    Chan, M F

    2006-09-01

    To determine whether definable subtypes exist within a cohort of Hong Kong nurses as related to the clinical management system use in their clinical practices based on their knowledge, attitudes, skills, and background factors. Data were collected using a structured questionnaire. The sample of 242 registered nurses was recruited from three hospitals in Hong Kong. The study employs personal and demographic variables, knowledge, attitudes, and skills scale. A cluster analysis yielded two clusters. Each cluster represents a different profile of Hong Kong nurses on the clinical management system use in their clinical practices. The first group (Cluster 1) was labeled 'lower attitudes, less skilful and average knowledge' group, and represented 55.4% of the total respondents. The second group (Cluster 2) was labeled as 'positive attitudes, good knowledge but less skilful'. They comprised almost 44.6% of this nursing sample. Cluster 2 had more older nurses, the majority were educated to the baccalaureate or above level, with more than 10 years working experience, and they held a more senior ranking then Cluster 1. A clear profile of Hong Kong nurses may benefit healthcare professionals in making appropriate education or assistance to prompt the use of the clinical management system by nurses an officially recognized profession. The findings were useful in determining nurse-users' specific needs and their preferences for modification of the clinical management system. Such findings should be used to formulate strategies to encourage nurses to resolve actual problems following computer training and to increase the depth and breadth of nurses' knowledge, attitudes, and skills toward such system.

  17. Planck 2015 results. XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

    Science.gov (United States)

    Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Weller, J.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zonca, A.

    2016-09-01

    We present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing of background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. Improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.

  18. Hierarchical Parallelization of Gene Differential Association Analysis

    Directory of Open Access Journals (Sweden)

    Dwarkadas Sandhya

    2011-09-01

    Full Text Available Abstract Background Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Results Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. Conclusions The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels.

  19. Galaxy Cluster Mass Reconstruction Project: I. Methods and first results on galaxy-based techniques

    CERN Document Server

    Old, L; Pearce, F R; Croton, D; Muldrew, S I; Muñoz-Cuartas, J C; Gifford, D; Gray, M E; von der Linden, A; Mamon, G A; Merrifield, M R; Müller, V; Pearson, R J; Ponman, T J; Saro, A; Sepp, T; Sifón, C; Tempel, E; Tundo, E; Wang, Y O; Wojtak, R

    2014-01-01

    This paper is the first in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our primary aim is to test the performance of these cluster mass estimation techniques on a diverse set of models that will increase in complexity. We begin by providing participating methods with data from a simple model that delivers idealised clusters, enabling us to quantify the underlying scatter intrinsic to these mass estimation techniques. The mock catalogue is based on a Halo Occupation Distribution (HOD) model that assumes spherical Navarro, Frenk and White (NFW) haloes truncated at R_200, with no substructure nor colour segregation, and with isotropic, isothermal Maxwellian velocities. We find that, above 10^14 M_solar, recovered cluster masses are correlated with the true underlying cluster mass with an intrinsic scatter of typically a factor of two. Below 10^14 M_solar, the scatter rises as the nu...

  20. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...

  1. Synchronization patterns: from network motifs to hierarchical networks

    Science.gov (United States)

    Krishnagopal, Sanjukta; Lehnert, Judith; Poel, Winnie; Zakharova, Anna; Schöll, Eckehard

    2017-03-01

    We investigate complex synchronization patterns such as cluster synchronization and partial amplitude death in networks of coupled Stuart-Landau oscillators with fractal connectivities. The study of fractal or self-similar topology is motivated by the network of neurons in the brain. This fractal property is well represented in hierarchical networks, for which we present three different models. In addition, we introduce an analytical eigensolution method and provide a comprehensive picture of the interplay of network topology and the corresponding network dynamics, thus allowing us to predict the dynamics of arbitrarily large hierarchical networks simply by analysing small network motifs. We also show that oscillation death can be induced in these networks, even if the coupling is symmetric, contrary to previous understanding of oscillation death. Our results show that there is a direct correlation between topology and dynamics: hierarchical networks exhibit the corresponding hierarchical dynamics. This helps bridge the gap between mesoscale motifs and macroscopic networks. This article is part of the themed issue 'Horizons of cybernetical physics'.

  2. Finding "Problem Types" in Judgments of Problem-Similarity: Comparison of Cluster Analysis with Subject Protocols.

    Science.gov (United States)

    Herring, Richard D.

    Literature in mathematic problem-solving suggests that learners store information in memory which helps them solve stereotyped algebra word problems. Cluster analysis has been used as an exploratory tool to infer the types of problems which have common representations in memory. This study compares the results of a hierarchical cluster analysis of…

  3. Dumb-bell galaxies in southern clusters: Catalog and preliminary statistical results

    Science.gov (United States)

    Vettolani, G.; Gregorini, L.; Parma, P.; Deruiter, H. R.

    1990-01-01

    The dominant galaxy of a rich cluster is often an object whose formation and evolution is closely connected to the dynamics of the cluster itself. Hoessel (1980) and Schneider et al. (1983) estimate that 50 percent of the dominant galaxies are either of the dumb-bell type or have companions at projected distances less than 20 kpc, which is far in excess of the number expected from chance projection (see also Rood and Leir 1979). Presently there is no complete sample of these objects, with the exception of the listing of dumb-bell galaxies in BM type I and I-II clusters in the Abell statistical sample of Rood and Leir (1979). Recent dynamical studies of dumb-bell galaxies in clusters (Valentijn and Casertano, 1988) still suffer from inhomogeneity of the sample. The fact that it is a mixture of optically and radio selected objects may have introduced an unknown biases, for instance if the probability of radio emission is enhanced by the presence of close companions (Stocke, 1978, Heckman et al. 1985, Vettolani and Gregorini 1988) a bias could be present in their velocity distribution. However, this situation is bound to improve: a new sample of Abell clusters in the Southern Hemisphere has been constructed (Abell et al., 1988 hereafter ACO), which has several advantages over the original northern catalog. The plate material (IIIaJ plates) is of better quality and reaches fainter magnitudes. This makes it possible to classify the cluster types with a higher degree of accuracy, as well as to fainter magnitudes. The authors therefore decided to reconsider the whole problem constructing a new sample of dumb-bell galaxies homogeneously selected from the ACO survey. Details of the classification criteria are given.

  4. Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

    Energy Technology Data Exchange (ETDEWEB)

    Abbott, T.M.C.; et al.

    2017-08-04

    We present cosmological results from a combined analysis of galaxy clustering and weak gravitational lensing, using 1321 deg$^2$ of $griz$ imaging data from the first year of the Dark Energy Survey (DES Y1). We combine three two-point functions: (i) the cosmic shear correlation function of 26 million source galaxies in four redshift bins, (ii) the galaxy angular autocorrelation function of 650,000 luminous red galaxies in five redshift bins, and (iii) the galaxy-shear cross-correlation of luminous red galaxy positions and source galaxy shears. To demonstrate the robustness of these results, we use independent pairs of galaxy shape, photometric redshift estimation and validation, and likelihood analysis pipelines. To prevent confirmation bias, the bulk of the analysis was carried out while blind to the true results; we describe an extensive suite of systematics checks performed and passed during this blinded phase. The data are modeled in flat $\\Lambda$CDM and $w$CDM cosmologies, marginalizing over 20 nuisance parameters, varying 6 (for $\\Lambda$CDM) or 7 (for $w$CDM) cosmological parameters including the neutrino mass density and including the 457 $\\times$ 457 element analytic covariance matrix. We find consistent cosmological results from these three two-point functions, and from their combination obtain $S_8 \\equiv \\sigma_8 (\\Omega_m/0.3)^{0.5} = 0.783^{+0.021}_{-0.025}$ and $\\Omega_m = 0.264^{+0.032}_{-0.019}$ for $\\Lambda$CDM for $w$CDM, we find $S_8 = 0.794^{+0.029}_{-0.027}$, $\\Omega_m = 0.279^{+0.043}_{-0.022}$, and $w=-0.80^{+0.20}_{-0.22}$ at 68% CL. The precision of these DES Y1 results rivals that from the Planck cosmic microwave background measurements, allowing a comparison of structure in the very early and late Universe on equal terms. Although the DES Y1 best-fit values for $S_8$ and $\\Omega_m$ are lower than the central values from Planck ...

  5. Planck 2013 results. XX. Cosmology from Sunyaev-Zeldovich cluster counts

    DEFF Research Database (Denmark)

    Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.;

    2013-01-01

    We present constraints on cosmological parameters using number counts as a function of redshift for a sub-sample of 189 galaxy clusters from the Planck SZ (PSZ) catalogue. The PSZ is selected through the signature of the Sunyaev-Zeldovich (SZ) effect, and the sub-sample used here has a signal...... spectrum amplitude σ8 and matter density parameter Ωm in a flat ΛCDM model. We test the robustness of our estimates and find that possible biases in the Y–M relation and the halo mass function are larger than the statistical uncertainties from the cluster sample. Assuming the X-ray determined mass...

  6. Cluster as a wave telescope – first results from the fluxgate magnetometer

    Directory of Open Access Journals (Sweden)

    K.-H. Glassmeier

    Full Text Available The four Cluster spacecraft provide an excellent opportunity to study spatial structures in the magnetosphere and adjacent regions. Propagating waves are amongst the interesting structures and for the first time, Cluster will allow one to measure the wave vector of low-frequency fluctuations in a space plasma. Based on a generalized minimum variance analysis wave vector estimates will be determined in the terrestrial magnetosheath and the near-Earth solar wind. The virtue and weakness of the wave telescope technique used is discussed in detail.

    Key words. Electromagnetics (wave propagation – Magnetospheric physics (MHD waves and instabilities; plasma waves and instabilities

  7. Planck early results. IX. XMM-Newton follow-up for validation of Planck cluster candidates

    DEFF Research Database (Denmark)

    Bucher, M.; Delabrouille, J.; Giraud-Héraud, Y.

    2011-01-01

    We present the XMM-Newton follow-up for confirmation of Planck cluster candidates. Twenty-five candidates have been observed to date using snapshot (∼10 ks) exposures, ten as part of a pilot programme to sample a low range of signal-to-noise ratios (4 ... of variable quality). The new clusters span the redshift range 0.09 ≲ z ≲ 0.54, with a median redshift of z ∼ 0.37. A first determination is made of their X-ray properties including the characteristic size, which is used to improve the estimate of the SZ Compton parameter, Y 500. The follow-up validation...

  8. Hierarchical Multiagent Reinforcement Learning

    Science.gov (United States)

    2004-01-25

    In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In

  9. Hierarchical Ring Network Design Using Branch-and-Price

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Stidsen, Thomas K.

    2005-01-01

    We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed l...... for jointly solving the clustering problem, the metro ring design problem and the routing problem. Computational results are given for networks with up to 36 nodes.......We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed...... link establishment costs and the link capacity costs into account. Hierarchical ring network design problems combines the following optimization problems: Clustering, hub selection, metro ring design, federal ring design and routing problems. In this paper a branch-and-price algorithm is presented...

  10. Fall injuries in Baghdad from 2003 to 2014: results of a randomized household cluster survey

    Science.gov (United States)

    Stewart, Barclay T; Lafta, Riyadh; Shatari, Sahar A Esa Al; Cherewick, Megan; Flaxman, Abraham; Hagopian, Amy; Burnham, Gilbert; Kushner, Adam L

    2015-01-01

    Introduction Falls incur nearly 35 million disability-adjusted life-years annually; 75% of which occur in low- and middle-income countries. The epidemiology of civilian injuries during conflict is relatively unknown, yet important for planning prevention initiatives, health policy and humanitarian assistance. This study aimed to determine the death and disability and household consequences of fall injuries in post-invasion Baghdad. Methods A two-stage, cluster randomized, community-based household survey was performed in May of 2014 to determine the civilian burden of injury from 2003 to 2014 in Baghdad. In addition to questions about household member death, households were interviewed regarding injury specifics, healthcare required, disability, relatedness to conflict and resultant financial hardship. Results Nine hundred households totaling 5,148 individuals were interviewed. There were 138 fall injuries (25% of all injuries reported); fall was the most common mechanism of civilian injury in Baghdad. The rate of serious fall injuries increased from 78 to 466 per 100,000 persons in 2003 and 2013, respectively. Fall was the most common mechanism among the injured elderly (i.e. ≥65 years; 15/24 elderly unintentional injuries; 63%). However, 46 fall injuries were children aged injuries) and 77 were respondents aged 15 - 64 years (36%). Respondents who spent significant time within the home (i.e. unemployed, retired, homemaker) had three times greater odds of having suffered a fall injury than student referents (aOR 3.34; 95%CI 1.30 – 8.60). Almost 80% of fall injured were left with life-limiting disability. Affected households often borrowed substantial sums of money (34 households; 30% of affected households) and/or suffered food insecurity after a family member's fall (52; 46%). Conclusion Falls were the most common cause of civilian injury in Baghdad. In part due to the effect of prolonged insecurity on a fragile health system, many injuries resulted in life

  11. Generation of hierarchically correlated multivariate symbolic sequences

    CERN Document Server

    Tumminello, Mi; Mantegna, R N

    2008-01-01

    We introduce an algorithm to generate multivariate series of symbols from a finite alphabet with a given hierarchical structure of similarities. The target hierarchical structure of similarities is arbitrary, for instance the one obtained by some hierarchical clustering procedure as applied to an empirical matrix of Hamming distances. The algorithm can be interpreted as the finite alphabet equivalent of the recently introduced hierarchically nested factor model (M. Tumminello et al. EPL 78 (3) 30006 (2007)). The algorithm is based on a generating mechanism that is different from the one used in the mutation rate approach. We apply the proposed methodology for investigating the relationship between the bootstrap value associated with a node of a phylogeny and the probability of finding that node in the true phylogeny.

  12. Hitomi results on the Perseus cluster thermodynamics, elemental abundances, and emission processes

    Science.gov (United States)

    Markevitch, Maxim L.; Hitomi Collaboration

    2017-01-01

    Hitomi SXS spectrum of the Perseus cluster above E=2 keV is a treasure trove of emission lines, most of them seen for the first time from a diffuse source such as the plasma atmosphere of a galaxy cluster. Several trace elements are detected for the first time in the intracluster medium, lines from several key elements, such as S/Ar and Fe/Ni, are disentangled, and sensitivity to faint lines is dramatically higher compared to previous, lower-resolution cluster studies. This allows us to determine accurate relative abundances of heavy elements, a sensitive test for sources of enrichment of the intergalactic medium. For many elements, lines from multiple ions are observed, as well as multiple transitions from the same ion, providing plasma temperature diagnostics previously unavailable for clusters. The brightest line -- the resonant component of the Fe He-alpha triplet -- is found to be affected by resonant scattering. For the most prominent ions, very high-level transitions are observed, placing constraints on such emission mechanisms as charge exchange with cold gas. Finally, we do not observe a previously reported 3.5 keV emission line from the Perseus core and place an upper limit on it.

  13. Planck intermediate results. X. Physics of the hot gas in the Coma cluster

    NARCIS (Netherlands)

    Planck Collaboration, [No Value; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Balbi, A.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Battaner, E.; Benabed, K.; Benoît, A.; Bernard, J.-P.; Bersanelli, M.; Bikmaev, I.; Böhringer, H.; Bonaldi, A.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bourdin, H.; Brown, M. L.; Brown, S. D.; Burenin, R.; Burigana, C.; Cabella, P.; Cardoso, J.-F.; Carvalho, P.; Catalano, A.; Cayón, L.; Chiang, L.-Y.; Chon, G.; Christensen, P. R.; Churazov, E.; Clements, D. L.; Colafrancesco, S.; Colombo, L. P. L.; Coulais, A.; Crill, B. P.; Cuttaia, F.; Da Silva, A.; Dahle, H.; Danese, L.; Davis, R. J.; de Bernardis, P.; de Gasperis, G.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Démoclès, J.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Dörl, U.; Douspis, M.; Dupac, X.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Frailis, M.; Franceschi, E.; Frommert, M.; Galeotta, S.; Ganga, K.; Génova-Santos, R. T.; Giard, M.; Gilfanov, M.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Harrison, D.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, T. R.; Jagemann, T.; Jones, W. C.; Juvela, M.; Keihänen, E.; Khamitov, I.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lawrence, C. R.; Le Jeune, M.; Leonardi, R.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Maino, D.; Mandolesi, N.; Maris, M.; Marleau, F.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Mei, S.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Natoli, P.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Pajot, F.; Paoletti, D.; Perdereau, O.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Piffaretti, R.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Rubiño-Martín, J. A.; Rudnick, L.; Rusholme, B.; Sandri, M.; Savini, G.; Schaefer, B. M.; Scott, D.; Smoot, G. F.; Stivoli, F.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Van Tent, B.; Varis, J.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Welikala, N.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zaroubi, S.; Zonca, A.

    2013-01-01

    We present an analysis of Planck satellite data on the Coma cluster observed via the Sunyaev-Zeldovich effect. Thanks to its great sensitivity, Planck is able, for the first time, to detect SZ emission up to r ≈ 3 × R500. We test previously proposed spherically symmetric models for the pressure dist

  14. Structure analysis of large argon clusters from gas-phase electron diffraction data: some recent results

    NARCIS (Netherlands)

    Waal, van de B.W.

    1999-01-01

    An up-to-date overview of recent developments in the structure elucidation of large ArN-clusters (103

  15. Planck early results: XMM-Newton follow-up for validation of Planck cluster candidates

    CERN Document Server

    Aghanim, N; Ashdown, M; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartelmann, M; Bartlett, J G; Battaner, E; Benabed, K; Benoît, A; Bernard, J -P; Bersanelli, M; Bhatia, R; Bock, J J; Bonaldi, A; Bond, J R; Borrill, J; Bouchet, F R; Brown, M L; Bucher, M; Burigana, C; Cabella, P; Cardoso, J -F; Catalano, A; Cayòn, L; Challinor, A; Chamballu, A; Chary, R R; Chiang, L Y; Chiang, C; Chon, G; Christensen, P R; Churazov, E; Clements, D L; Colafrancesco, S; Colombi, S; Couchot, F; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Danese, L; de Bernardis, P; de Gasperis, G; de Rosa, A; de Zotti, G; Delabrouille, J; Delouis, J -M; Désert, F -X; Diego, J M; Dolag, K; Donzelli, S; Doré, O; Dörl, U; Douspis, M; Dupac, X; Efstathiou, G; Ensslin, T A; Finelli, F; Flores, I; Forni, O; Frailis, M; Franceschi, E; Fromenteau, S; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Giardino, G; Giraud-Héraud, Y; González-Nuevo, J; Górski, K M; Gratton, S; Gregorio, A; Gruppuso, A; Harrison, D; Henrot-Versillé, S; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hovest, W; Hoyland, R J; Huffenberger, K M; Jaffe, A H; Jones, W C; Juvela, M; Keihänen, E; Keskitalo, R; Kisner, T S; Kneissl, R; Knox, L; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lasenby, A; Laureijs, R J; Lawrence, C R; Leach, S; Leonardi, R; Linden-Vornle, M; López-Caniego, M; Lubin, P M; Macías-Pérez, J -F; MacTavish, C J; Maffei, B; Maino, D; Mandolesi, N; Mann, R; Maris, M; Marleau, F; Martínez-González, E; Masi, S; Matarrese, S; Matthai, F; Mazzotta, P; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, A; Naselsky, P; Natoli, P; Netterfield, C B; Norgaard-Nielsen, H U; Noviello, F; Novikov, D; Novikov, I; Osborne, S; Pajot, F; Pasian, F; Patanchon, G; Perdereau, O; Perotto, L; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Poutanen, T; Pratt, G W; Prézeau, G; Prunet, S; Puget, J -L; Rebolo, R; Reinecke, M; Renault, C; Ricciardi, S; Riller, T; Ristorcelli, I; Rocha, G; Rosset, C; Rubiõo-Martín, J A; Rusholme, B; Sandri, M; Santos, D; Schaefer, B M; Scott, D; Seiffert, M D; Smoot, G F; Starck, J -L; Stivoli, F; Stolyarov, V; Sunyaev, R; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Tuovinen, J; Valenziano, L; Vibert, L; Vielva, P; Villa, F; Vittorio, N; Wandelt, B D; White, S D M; White, M; Yvon, D; Zacchei, A; Zonca, A

    2011-01-01

    We present the XMM-Newton follow-up for validation of Planck cluster candidates. Twenty-five candidates have been observed to date using snapshot (~10 ksec) exposures: ten as part of a pilot programme to sample a low range of signal-to-noise ratios (45 candidates. The sensitivity and spatial resolution of XMM-Newton allows unambiguous discrimination between clusters and false candidates. A total of 21 candidates are confirmed as extended X-ray sources. Seventeen are single clusters, the majority of which are found to have highly irregular and disturbed morphologies. The remaining four sources are multiple systems, including the unexpected discovery of a supercluster at z=0.45. For most of the sources we are able to derive a redshift estimate from the X-ray Fe K line (albeit of variable quality). The new clusters span the redshift range 0.09 <~ z <~ 0.54 with a median redshift of z ~ 0.37. A first estimate is made of their X-ray properties including the characteristic size, which is used to improve the S...

  16. First results from SAPAC: towards a 3D-picture of the Fornax cluster core

    CERN Document Server

    Jerjen, L P D H

    2006-01-01

    A sophisticated SBF analysis package has been developed, designed to measure distances of early-type galaxies by means of surface brightness fluctuations of unresolved stars. This suite of programs called SAPAC is made readily available to the astronomical community for extensive testing with the long-term goal to provide the necessary tools for systematic distance surveys of early-type galaxies using modern optical/NIR telescopes equipped with wide-field cameras. We discuss the technical and scientific concepts of SAPAC and demonstrate its capabilities by analysing deep B and R-band CCD images of 10 dwarf elliptical (dE) galaxy candidates in the Fornax cluster obtained with FORS1 at the VLT. All candidates are confirmed as cluster members. We then turn our attention to the innermost region of the Fornax cluster. A total of 29 early-type galaxies closer than three cluster core radii (2 degrees) from the central galaxy NGC1399 have radial velocities and SBF distances. Their Hubble diagram exhibits a pronounced...

  17. Planck intermediate results : X. Physics of the hot gas in the Coma cluster

    NARCIS (Netherlands)

    Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Balbi, A.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Battaner, E.; Benabed, K.; Benoit, A.; Bernard, J. -P.; Bersanelli, M.; Bikmaev, I.; Boehringer, H.; Bonaldi, A.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bourdin, H.; Brown, M. L.; Brown, S. D.; Burenin, R.; Burigana, C.; Cabella, P.; Cardoso, J. -F.; Carvalho, P.; Catalano, A.; Cayon, L.; Chiang, L. -Y; Chon, G.; Christensen, P. R.; Churazov, E.; Clements, D. L.; Colafrancesco, S.; Colombo, L. P. L.; Coulais, A.; Crill, B. P.; Cuttaia, F.; Da Silva, A.; Dahle, H.; Danese, L.; Davis, R. J.; de Bernardis, P.; de Gasperis, G.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Democles, J.; Desert, F. -X.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Dore, O.; Doerl, U.; Douspis, M.; Dupac, X.; Ensslin, T. A.; Eriksen, H. K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Frailis, M.; Franceschi, E.; Frommert, M.; Galeotta, S.; Ganga, K.; Genova-Santos, R. T.; Giard, M.; Gilfanov, M.; Gonzalez-Nuevo, J.; Gorski, K. M.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Harrison, D.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, T. R.; Jagemann, T.; Jones, W. C.; Juvela, M.; Keihanen, E.; Khamitov, I.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lahteenmaki, A.; Lamarre, J. -M.; Lasenby, A.; Lawrence, C. R.; Le Jeune, M.; Leonardi, R.; Lilje, P. B.; Linden-Vornle, M.; Lopez-Caniego, M.; Lubin, P. M.; Macias-Perez, J. F.; Maffei, B.; Maino, D.; Mandolesi, N.; Maris, M.; Marleau, F.; Martinez-Gonzalez, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Mei, S.; Melchiorri, A.; Melin, J. -B.; Mendes, L.; Mennella, A.; Mitra, S.; Miville-Deschenes, M. -A.; Moneti, A.; Montier, L.; Morgante, G.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Natoli, P.; Norgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Pajot, F.; Paoletti, D.; Perdereau, O.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Piffaretti, R.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prunet, S.; Puget, J. -L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Rubino-Martin, J. A.; Rudnick, L.; Rusholme, B.; Sandri, M.; Savini, G.; Schaefer, B. M.; Scott, D.; Smoot, G. F.; Stivoli, F.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A. -S.; Sygnet, J. -F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tuovinen, J.; Tuerler, M.; Umana, G.; Valenziano, L.; Van Tent, B.; Varis, J.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Welikala, N.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zaroubi, S.; Zonca, A.

    2013-01-01

    We present an analysis of Planck satellite data on the Coma cluster observed via the Sunyaev-Zeldovich effect. Thanks to its great sensitivity, Planck is able, for the first time, to detect SZ emission up to r approximate to 3 x R-500. We test previously proposed spherically symmetric models for the

  18. Testing intermediate-age stellar evolution models with VLT photometry of LMC clusters. III. Padova results

    CERN Document Server

    Bertelli, G; Girardi, L; Chiosi, C; Zoccali, M; Gallart, C

    2002-01-01

    The color-magnitude diagrams (CMDs) of three intermediate-age LMC clusters, NGC 2173, SL556 and NGC2155 are analyzed to determine their age and metallicity basing on Padova stellar models. Synthetic CMDs are compared with cluster data. The best match is obtained using two fitting functions based on star counts in the different bins of the cluster CMD. Two different criteria are used. One of them takes into account the uncertainties in the color of the red clump stars. Given the uncertainties on the experimental values of the clusters metallicity, we provide a set of acceptable solutions. They define the correspondent values of metallicity, age, reddening and distance modulus (for the assumed IMF). The comparison with Padova models suggests for NGC 2173 a prolonged star formation (spanning a period of about 0.3 Gyr), beginning 1.7 Gyr and ending 1.4 Gyr ago. The metallicity Z is in the range 0.0016 $-$ 0.003. Contrary to what suggested for NGC 2173 a period of extended star formation was not required to fit th...

  19. Planck intermediate results: V. Pressure profiles of galaxy clusters from the Sunyaev-Zeldovich effect

    DEFF Research Database (Denmark)

    Castex, G.; Delabrouille, J.; Ganga, K.;

    2013-01-01

    Taking advantage of the all-sky coverage and broadfrequency range of the Planck satellite, we study the Sunyaev-Zeldovich (SZ) and pressure profiles of 62 nearby massive clusters detected at high significance in the 14-month nominal survey. Careful reconstruction of the SZ signal indicates that m...

  20. Planck intermediate results: XLIII. Spectral energy distribution of dust in clusters of galaxies

    DEFF Research Database (Denmark)

    Adam, R.; Ade, P. A R; Aghanim, N.;

    2016-01-01

    Although infrared (IR) overall dust emission from clusters of galaxies has been statistically detected using data from the Infrared Astronomical Satellite (IRAS), it has not been possible to sample the spectral energy distribution (SED) of this emission over its peak, and thus to break the degene...

  1. Planck early results. XI. Calibration of the local galaxy cluster Sunyaev-Zeldovich scaling relations

    DEFF Research Database (Denmark)

    Bucher, M.; Delabrouille, J.; Giraud-Héraud, Y.;

    2011-01-01

    We present precise Sunyaev-Zeldovich (SZ) effect measurements in the direction of 62 nearby galaxy clusters (z <0.5) detected at high signal-to-noise in the first Planck all-sky data set. The sample spans approximately a decade in total mass, 2 × 1014 M

  2. Planck early results. VIII. The all-sky early Sunyaev-Zeldovich cluster sample

    DEFF Research Database (Denmark)

    Bucher, M.; Delabrouille, J.; Giraud-Héraud, Y.;

    2011-01-01

    We present the first all-sky sample of galaxy clusters detected blindly by the Planck satellite through the Sunyaev-Zeldovich (SZ) effect from its six highest frequencies. This early SZ (ESZ) sample is comprised of 189 candidates, which have a high signal-to-noise ratio ranging from 6 to 29. Its ...

  3. An Approach to Assembly Sequence Plannning Based on Hierarchical Strategy and Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    Niu Xinwen; Ding Han; Xiong Youlun

    2001-01-01

    Using group and subassembly cluster methods, the hierarchical structure of a product is.generated automatically, which largely reduces the complexity of planning. Based on genetic algofithn the optimal of assembly sequence of each stracture level can be obtained by sequence-bysequence search. As a result, a better assembly sequence of the product can be generated by combining the assembly sequences of all hierarchical structures, which provides more parallelism and flexibility for assembly operations. An industrial example is solved by this new approach.

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

    DEFF Research Database (Denmark)

    Zong, Yu; Xu, Guandong; Jin, Pin

    2011-01-01

    algorithm for Tags (APPECT). The main steps of APPECT are: (1) we execute the K-means algorithm on a tag similarity matrix for M times and collect a set of tag clustering results Z={C1,C2,…,Cm}; (2) we form the approximate backbone of Z by executing a greedy search; (3) we fix the approximate backbone...... 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...

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

    DEFF Research Database (Denmark)

    Zong, Yu; Xu, Guandong; Jin, Pin

    2011-01-01

    algorithm for Tags (APPECT). The main steps of APPECT are: (1) we execute the K-means algorithm on a tag similarity matrix for M times and collect a set of tag clustering results Z={C1,C2,…,Cm}; (2) we form the approximate backbone of Z by executing a greedy search; (3) we fix the approximate backbone...... 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...

  6. Cluster-cluster clustering

    Science.gov (United States)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.

    1985-01-01

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

  7. Cluster-cluster clustering

    Energy Technology Data Exchange (ETDEWEB)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.

    1985-08-01

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

  8. Organizing Search Results with a Reference Map.

    Science.gov (United States)

    Nocaj, A; Brandes, U

    2012-12-01

    We propose a method to highlight query hits in hierarchically clustered collections of interrelated items such as digital libraries or knowledge bases. The method is based on the idea that organizing search results similarly to their arrangement on a fixed reference map facilitates orientation and assessment by preserving a user's mental map. Here, the reference map is built from an MDS layout of the items in a Voronoi treemap representing their hierarchical clustering, and we use techniques from dynamic graph layout to align query results with the map. The approach is illustrated on an archive of newspaper articles.

  9. Relation between financial market structure and the real economy: comparison between clustering methods.

    Directory of Open Access Journals (Sweden)

    Nicoló Musmeci

    Full Text Available We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  10. Relation between financial market structure and the real economy: comparison between clustering methods.

    Science.gov (United States)

    Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T

    2015-01-01

    We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  11. Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

    Science.gov (United States)

    Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

    2012-11-01

    This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

  12. An emergency clinical pathway for stroke patients – results of a cluster randomised trial (isrctn41456865

    Directory of Open Access Journals (Sweden)

    Ferri Marica

    2009-01-01

    Full Text Available Abstract Background Emergency Clinical Pathways (ECP for stroke have never been tested in randomized controlled trials (RCTs. Objective To evaluate the effectiveness of an ECP for stroke patients in Latium (Italy emergency system. Methods cluster-RCT designed to compare stroke patient referrals by Emergency Medical Service (EMS and Emergency Room (ER health professionals trained in the ECP, with those of non-trained EMS and ER controls. Primary outcome measure was the proportion of eligible (aged ≤ 80 and symptom onset ≤ 6 hours stroke patients referred to a stroke unit (SU. Intention to treat (ITT and per-protocol (PP analyses were performed, and risk ratios (RR adjusted by age, gender and area, were calculated. Results 2656 patients in the intervention arm and 2239 in the control arm required assistance; 78.3% of the former and 80.6% of the latter were admitted to hospitals, and respectively 74.8% and 78.3% were confirmed strokes. Of the eligible confirmed strokes, 106/434 (24.4% in the intervention arm and 43/328 (13.1% in the control arm were referred to the SU in the ITT analysis (RR = 2.01; 95% CI: 0.79–4.00, and respectively 105/243 (43.2% and 43/311 (13.8% in the PP analysis (RR = 3.21; 95%CI: 1.62–4.98. Of patients suitable for i.v. thrombolysis, 15/175 (8.6% in the intervention arm and 2/115 (1.7% in the control arm received thrombolysis (p = 0.02 in the ITT analysis, and respectively 15/99 (15.1% and 2/107 (1.9%(p = 0.001 in the PP analysis. Conclusion Our data suggest potenti efficiency and feasibility of an ECP. The integration of EMS and ERs with SU networks for organised acute stroke care is feasible and may ameliorate the quality of care for stroke patients. Trial registration Current Controlled Trials (ISRCTN41456865.

  13. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    CERN Document Server

    Perotti, Juan Ignacio; Caldarelli, Guido

    2015-01-01

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\\it hierarchical mutual information}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\\it normalized} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies, and on the hierarchical ...

  14. Lifestyle health behaviors of Hong Kong Chinese: results of a cluster analysis.

    Science.gov (United States)

    Chan, Choi Wan; Leung, Sau Fong

    2015-04-01

    Sociodemographics affect health through pathways of lifestyle choices. Using data from a survey of 467 Hong Kong Chinese, this study aims to examine the prevalence of their lifestyle behaviors, identify profiles based on their sociodemographic and lifestyle variables, and compare differences among the profile groups. Two-step cluster analysis was used to identify natural profile groups within the data set: only 37% of the participants engaged in regular physical exercises, and less than 50% monitored their dietary intake carefully. The analysis yields 2 clusters, representing a "healthy" and a "less-healthy" lifestyle group. The "less-healthy" group was predominantly male, younger, employed, and had high-to-middle levels of education. The findings reveal the lifestyle behavior patterns and sociodemographic characteristics of a high-risk group, which are essential to provide knowledge for the planning of health promotion activities. © 2014 APJPH.

  15. Testing spectral models for stellar populations with star clusters: II. Results

    CERN Document Server

    Delgado, Rosa M Gonzalez

    2009-01-01

    High spectral resolution evolutionary synthesis models have become a routinely used ingredient in extragalactic work, and as such deserve thorough testing. Star clusters are ideal laboratories for such tests. This paper applies the spectral fitting methodology outlined in Paper I to a sample of clusters, mainly from the Magellanic Clouds and spanning a wide range in age and metallicity, fitting their integrated light spectra with a suite of modern evolutionary synthesis models for single stellar population. The combinations of model plus spectral library employed in this investigation are Galaxev/STELIB, Vazdekis/MILES, SED@/GRANADA, and Galaxev/MILES+GRANADA, which provide a representative sample of models currently available for spectral fitting work. A series of empirical tests are performed with these models, comparing the quality of the spectral fits and the values of age, metallicity and extinction obtained with each of them. A comparison is also made between the properties derived from these spectral f...

  16. Planck intermediate results. X. Physics of the hot gas in the Coma cluster

    DEFF Research Database (Denmark)

    Planck Collaboration,; Ade, P. A. R.; Aghanim, N.

    2013-01-01

    .05+0.25-0.02 in the West and Southeast, respectively. Finally, we find that the y and radio-synchrotron signals are quasi-linearly correlated on Mpc scales with small intrinsic scatter. This implies either that the energy density of cosmic-ray electrons is relatively constant throughout the cluster, or that the magnetic...... fields fall off much more slowly with radius than previously thought....

  17. First results from the RAPID imaging energetic particle spectrometer on board Cluster

    Directory of Open Access Journals (Sweden)

    B. Wilken

    Full Text Available The advanced energetic particle spectrometer RAPID on board Cluster can provide a complete description of the relevant particle parameters velocity, V , and atomic mass, A, over an energy range from 30 keV up to 1.5 MeV. We present the first measurements taken by RAPID during the commissioning and the early operating phases. The orbit on 14 January 2001, when Cluster was travelling from a perigee near dawn northward across the pole towards an apogee in the solar wind, is used to demonstrate the capabilities of RAPID in investigating a wide variety of particle populations. RAPID, with its unique capability of measuring the complete angular distribution of energetic particles, allows for the simultaneous measurements of local density gradients, as reflected in the anisotropies of 90° particles and the remote sensing of changes in the distant field line topology, as manifested in the variations of loss cone properties. A detailed discussion of angle-angle plots shows considerable differences in the structure of the boundaries between the open and closed field lines on the nightside fraction of the pass and the magnetopause crossing. The 3 March 2001 encounter of Cluster with an FTE just outside the magnetosphere is used to show the first structural plasma investigations of an FTE by energetic multi-spacecraft observations.

    Key words. Magnetospheric physics (energetic particles, trapped; magnetopause, cusp and boundary layers; magnetosheath

  18. The Bullet Cluster revisited: New results from new constraints and improved strong lensing modeling technique

    CERN Document Server

    Paraficz, D; Richard, J; Morandi, A; Limousin, M; Jullo, E

    2012-01-01

    We present a new detailed parametric strong lensing mass reconstruction of the Bullet Cluster (1E 0657-56) at z=0.296, based on new WFC3 and ACS HST imaging and VLT/FORS2 spectroscopy. The strong lensing constraints undergone deep revision, there are 14 (6 new and 8 previously known) multiply imaged systems, of which 3 have spectroscopically confirmed redshifts (including 2 newly measured). The reconstructed mass distribution includes explicitly for the first time the combination of 3 mass components: i) the intra-cluster gas mass derived from X-ray observation, ii) the cluster galaxies modeled by their Fundamental Plane (elliptical) and Tully-Fisher (spiral) scaling relations and iii) dark matter. The best model has an average rms value of 0.158" between the predicted and measured image positions for the 14 multiple images considered. The derived mass model confirms the spacial offset between the X-ray gas and dark matter peaks. The galaxy halos to total mass fraction is found to be f_s=11+/-5% for a total m...

  19. Binary Frequencies in a Sample of Globular Clusters. I. Methodology and Initial Results

    CERN Document Server

    Ji, Jun

    2013-01-01

    Binary stars are thought to be a controlling factor in globular cluster evolution, since they can heat the environmental stars by converting their binding energy to kinetic energy during dynamical interactions. Through such interaction, the binaries determine the time until core collapse. To test predictions of this model, we have determined binary fractions for 35 clusters. Here we present our methodology with a representative globular cluster NGC 4590. We use HST archival ACS data in the F606W and F814W bands and apply PSF-fitting photometry to obtain high quality color-magnitude diagrams. We formulate the star superposition effect as a Poisson probability distribution function, with parameters optimized through Monte-Carlo simulations. A model-independent binary fraction of (6.2 +- 0.3)% is obtained by counting stars that extend to the red side of the residual color distribution after accounting for the photometric errors and the star superposition effect. A model-dependent binary fraction is obtained by c...

  20. Planck 2013 results. XX. Cosmology from Sunyaev-Zeldovich cluster counts

    CERN Document Server

    Ade, P.A.R.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A.J.; Barreiro, R.B.; Barrena, R.; Bartlett, J.G.; Battaner, E.; Battye, R.; Benabed, K.; Benoit, A.; Benoit-Levy, A.; Bernard, J.P.; Bersanelli, M.; Bielewicz, P.; Bikmaev, I.; Blanchard, A.; Bobin, J.; Bock, J.J.; Bohringer, H.; Bonaldi, A.; Bond, J.R.; Borrill, J.; Bouchet, F.R.; Bourdin, H.; Bridges, M.; Brown, M.L.; Bucher, M.; Burenin, R.; Burigana, C.; Butler, R.C.; Cardoso, J.F.; Carvalho, P.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.R.; Chiang, L.Y.; Chiang, H.C.; Chon, G.; Christensen, P.R.; Church, S.; Clements, D.L.; Colombi, S.; Colombo, L.P.L.; Couchot, F.; Coulais, A.; Crill, B.P.; Curto, A.; Cuttaia, F.; Da Silva, A.; Dahle, H.; Danese, L.; Davies, R.D.; Davis, R.J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.M.; Democles, J.; Desert, F.X.; Dickinson, C.; Diego, J.M.; Dolag, K.; Dole, H.; Donzelli, S.; Dore, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Ensslin, T.A.; Eriksen, H.K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Frailis, M.; Franceschi, E.; Fromenteau, S.; Galeotta, S.; Ganga, K.; Genova-Santos, R.T.; Giard, M.; Giardino, G.; Giraud-Heraud, Y.; Gonzalez-Nuevo, J.; Gorski, K.M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F.K.; Hanson, D.; Harrison, D.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Herranz, D.; Hildebrandt, S.R.; Hivon, E.; Hobson, M.; Holmes, W.A.; Hornstrup, A.; Hovest, W.; Huffenberger, K.M.; Hurier, G.; Jaffe, T.R.; Jaffe, A.H.; Jones, W.C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Khamitov, I.; Kisner, T.S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lahteenmaki, A.; Lamarre, J.M.; Lasenby, A.; Laureijs, R.J.; Lawrence, C.R.; Leahy, J.P.; Leonardi, R.; Leon-Tavares, J.; Lesgourgues, J.; Liddle, A.; Liguori, M.; Lilje, P.B.; Linden-Vornle, M.; Lopez-Caniego, M.; Lubin, P.M.; Macias-Perez, J.F.; Maffei, B.; Maino, D.; Mandolesi, N.; Marcos-Caballero, A.; Maris, M.; Marshall, D.J.; Martin, P.G.; Martinez-Gonzalez, E.; Masi, S.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Meinhold, P.R.; Melchiorri, A.; Melin, J.B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschenes, M.A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C.B.; Norgaard-Nielsen, H.U.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C.A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G.W.; Prezeau, G.; Prunet, S.; Puget, J.L.; Rachen, J.P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Roudier, G.; Rowan-Robinson, M.; Rubino-Martin, J.A.; Rusholme, B.; Sandri, M.; Santos, D.; Savini, G.; Scott, D.; Seiffert, M.D.; Shellard, E.P.S.; Spencer, L.D.; Starck, J.L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.S.; Sygnet, J.F.; Tauber, J.A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Turler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L.A.; Wandelt, B.D.; Weller, J.; White, M.; White, S.D.M.; Yvon, D.; Zacchei, A.; Zonca, A.

    2014-01-01

    We present constraints on cosmological parameters using number counts as a function of redshift for a sub-sample of 189 galaxy clusters from the Planck SZ (PSZ) catalogue. The PSZ is selected through the signature of the Sunyaev--Zeldovich (SZ) effect, and the sub-sample used here has a signal-to-noise threshold of seven, with each object confirmed as a cluster and all but one with a redshift estimate. We discuss the completeness of the sample and our construction of a likelihood analysis. Using a relation between mass $M$ and SZ signal $Y$ calibrated to X-ray measurements, we derive constraints on the power spectrum amplitude $\\sigma_8$ and matter density parameter $\\Omega_{\\mathrm{m}}$ in a flat $\\Lambda$CDM model. We test the robustness of our estimates and find that possible biases in the $Y$--$M$ relation and the halo mass function are larger than the statistical uncertainties from the cluster sample. Assuming the X-ray determined mass to be biased low relative to the true mass by between zero and 30%, m...

  1. Planck Intermediate Results. X. Physics of the hot gas in the Coma cluster

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Atrio-Barandela, F; Aumont, J; Baccigalupi, C; Balbi, A; Banday, A J; Barreiro, R B; Bartlett, J G; Battaner, E; Benabed, K; Benoît, A; Bernard, J -P; Bersanelli, M; Bonaldi, A; Bond, J R; Borrill, J; Bouchet, F R; Bourdin, H; Brown, M L; Burigana, C; Cabella, P; Cardoso, J -F; Carvalho, P; Catalano, A; Cayón, L; Chiang, L -Y; Chon, G; Christensen, P R; Churazov, E; Clements, D L; Colafrancesco, S; Colombo, L P L; Coulais, A; Crill, B P; Cuttaia, F; Da Silva, A; Dahle, H; Danese, L; Davis, R J; de Bernardis, P; de Gasperis, G; de Rosa, A; de Zotti, G; Delabrouille, J; Désert, F -X; Dickinson, C; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Dörl, U; Douspis, M; Dupac, X; Enßlin, T A; Eriksen, H K; Finelli, F; Flores-Cacho, I; Forni, O; Frailis, M; Franceschi, E; Frommert, M; Galeotta, S; Ganga, K; Génova-Santos, R T; Giard, M; Gilfanov, M; González-Nuevo, J; Górski, K M; Gregorio, A; Gruppuso, A; Hansen, F K; Harrison, D; Henrot-Versillé, S; Hernández-Monteagudo, C; Hildebrandt, S R; Hivon, E; Hobson, M; Holmes, W A; Hornstrup, A; Hovest, W; Huffenberger, K M; Hurier, G; Jaffe, T R; Jagemann, T; Jones, W C; Juvela, M; Keihänen, E; Kneissl, R; Knoche, J; Knox, L; Kunz, M; Kurki-Suonio, H; Lagache, G; Lähteenmäki, A; Lasenby, A; Lawrence, C R; Jeune, M Le; Leonardi, R; Lilje, P B; Linden-Vørnle, M; López-Caniego, M; Lubin, P M; Macías-Pérez, J F; Maffei, B; Maino, D; Mandolesi, N; Maris, M; Marleau, F; Martínez-González, E; Masi, S; Massardi, M; Matarrese, S; Matthai, F; Mazzotta, P; Mei, S; Melchiorri, A; Melin, J -B; Mendes, L; Mennella, A; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Munshi, D; Murphy, J A; Naselsky, P; Natoli, P; Nørgaard-Nielsen, H U; Noviello, F; Osborne, S; Pajot, F; Paoletti, D; Perdereau, O; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Popa, L; Poutanen, T; Pratt, G W; Prunet, S; Puget, J -L; Rachen, J P; Rebolo, R; Reinecke, M; Remazeilles, M; Renault, C; Ricciardi, S; Riller, T; Rocha, G; Roman, M; Rosset, C; Rossetti, M; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Savini, G; Schaefer, B M; Scott, D; Smoot, G F; Stivoli, F; Sudiwala, R; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Tuovinen, J; Türler, M; Umana, G; Valenziano, L; Van Tent, B; Varis, J; Vielva, P; Villa, F; Vittorio, N; Wade, L A; Wandelt, B D; Welikala, N; White, S D M; Yvon, D; Zacchei, A; Zaroubi, S; Zonca, A

    2012-01-01

    We present an analysis of Planck satellite data on the Coma Cluster observed via the Sunyaev-Zeldovich effect. Planck is able, for the first time, to detect SZ emission up to r ~ 3 X R_500. We test previously proposed models for the pressure distribution in clusters against the azimuthally averaged data. We find that the Arnaud et al. universal pressure profile does not fit Coma, and that their pressure profile for merging systems provides a good fit of the data only at rR_500 than the mean pressure profile predicted by the simulations. The Planck image shows significant local steepening of the y profile in two regions about half a degree to the west and to the south-east of the cluster centre. These features are consistent with the presence of shock fronts at these radii, and indeed the western feature was previously noticed in the ROSAT PSPC mosaic by Markevitch (2000) as well as in the radio. Using Planck y profiles extracted from corresponding sectors we find pressure jumps of 4.5+2.5-0.1 and 4.9+0.7-0.2 ...

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

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

    Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem-ical 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 sim-ilarity 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 iden-tification 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 clus-tering 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/.

  3. Evolution of cluster X-ray luminosities and radii: Results from the 160 square degree rosat survey

    DEFF Research Database (Denmark)

    Vikhlinin, A.; McNamara, B.R.; Forman, W.

    1998-01-01

    -X > 3 x 10(44) ergs s(-1) in the 0.5-2 keV band. We detect a factor of 3-4 deficit of such luminous clusters at z > 0.3 compared with the present. The evolution is much weaker or absent at modestly lower luminosities, (1-3) x 10(44) ergs s(-1). At still lower luminosities, we find no evolution from...... the analysis of the log N-log S relation. The results in the two upper L, bins are in agreement with the Einstein Extended Medium-Sensitivity Survey evolution result (Gioia et al.; Henry ct al.), which was obtained using a completely independent cluster sample. The low-L-X results are in agreement with other...... ROSAT surveys (e.g., Rosati et al.; Jones et al.). We also compare the distribution of core radii of nearby and distant (z > 0.4) luminous (with equivalent temperatures of 4-7 keV) clusters and detect no evolution. The ratio of average core radius for z similar to 0.5 and z clusters is 0.9 +/- 0...

  4. Hierarchical topic modeling with nested hierarchical Dirichlet process

    Institute of Scientific and Technical Information of China (English)

    Yi-qun DING; Shan-ping LI; Zhen ZHANG; Bin SHEN

    2009-01-01

    This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonparametric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as welt as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more free-grained topic relationships compared to the hierarchical latent Dirichlet allocation model.

  5. Hierarchical structure of the countries based on electricity consumption and economic growth

    Science.gov (United States)

    Kantar, Ersin; Aslan, Alper; Deviren, Bayram; Keskin, Mustafa

    2016-07-01

    We investigate the hierarchical structures of countries based on electricity consumption and economic growth by using the real amounts of their consumption over a certain time period. We use electricity consumption data to detect the topological properties of 64 countries from 1971 to 2008. These countries are divided into three clusters: low income group, middle income group and high income group countries. Firstly, a relationship between electricity consumption and economic growth is investigated by using the concept of hierarchical structure methods (minimal spanning tree (MST) and hierarchical tree (HT)). Secondly, we perform bootstrap techniques to investigate a value of the statistical reliability to the links of the MST. Finally, we use a clustering linkage procedure in order to observe the cluster structure more clearly. The results of the structural topologies of these trees are as follows: (i) we identified different clusters of countries according to their geographical location and economic growth, (ii) we found a strong relation between energy consumption and economic growth for all the income groups considered in this study and (iii) the results are in good agreement with the causal relationship between electricity consumption and economic growth.

  6. Static Correctness of Hierarchical Procedures

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff

    1990-01-01

    A system of hierarchical, fully recursive types in a truly imperative language allows program fragments written for small types to be reused for all larger types. To exploit this property to enable type-safe hierarchical procedures, it is necessary to impose a static requirement on procedure calls....... We introduce an example language and prove the existence of a sound requirement which preserves static correctness while allowing hierarchical procedures. This requirement is further shown to be optimal, in the sense that it imposes as few restrictions as possible. This establishes the theoretical...... basis for a general type hierarchy with static type checking, which enables first-order polymorphism combined with multiple inheritance and specialization in a language with assignments. We extend the results to include opaque types. An opaque version of a type is different from the original but has...

  7. New Heterogeneous Clustering Protocol for Prolonging Wireless Sensor Networks Lifetime

    Directory of Open Access Journals (Sweden)

    Md. Golam Rashed

    2014-06-01

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

  8. GALEX Ultraviolet Photometry of Globular Clusters in M31: Three Year Results and a Catalog

    CERN Document Server

    Rey, S C; Sohn, S T; Yoon, S J; Chung, C; Yi, S K; Lee, Y W; Rhee, J; Bianchi, L; Madore, B F; Lee, K; Barlow, T A; Forster, K; Friedman, P G; Martin, D C; Morrissey, P; Neff, S G; Schiminovich, D; Seibert, M; Small, T; Wyder, T K; Donas, J; Heckman, T M; Milliard, B; Szalay, A S; Welsh, B Y; Rey, Soo-Chang; Sohn, Sangmo T.; Yoon, Suk-Jin; Chung, Chul; Yi, Sukyoung K.; Lee, Young-Wook; Rhee, Jaehyon; Bianchi, Luciana; Madore, Barry F.; Lee, Kyungsook; Barlow, Tom A.; Forster, Karl; Friedman, Peter G.; Morrissey, Patrick; Neff, Susan G.; Schiminovich, David; Seibert, Mark; Small, Todd; Wyder, Ted K.; Donas, Jose; Heckman, Timothy M.; Milliard, Bruno; Szalay, Alex S.; Welsh, Barry Y.

    2006-01-01

    We present ultraviolet (UV) photometry of M31 globular clusters (GCs) found in 23 Galaxy Evolution Explorer (GALEX) images covering the entirety of M31. We detect 485 and 273 GCs (and GC candidates) in the near-ultraviolet (NUV; 2267 A) and far-ultraviolet (FUV; 1516 A), respectively. Comparing M31 data with those of Galactic GCs in the UV with the aid of population models, we find that the age ranges of old GCs in M31 and the Galactic halo are similar. Three metal-rich ([Fe/H]>-1) GCs in M31 produce significant FUV flux making their FUV-V colors unusually blue for their metallicities. These are thought to be analogs of the two peculiar Galactic GCs NGC 6388 and NGC 6441 with extended blue HB stars. Based on the models incorporating helium enriched subpopulations in addition to the majority of the population that have a normal helium abundance, we suggest that even small fraction of super-helium-rich subpopulations in GCs can reproduce the observed UV bright metal-rich GCs. Young clusters in M31 show distinct...

  9. Gene ordering in partitive clustering using microarray expressions.

    Science.gov (United States)

    Ray, Shubhra Sankar; Bandyopadhyay, Sanghamitra; Pal, Sankar K

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions.Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  10. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    Shubhra Sankar Ray; Sanghamitra Bandyopadhyay; Sankar K Pal

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions. Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  11. Automated tetraploid genotype calling by hierarchical clustering

    Science.gov (United States)

    SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, however, the relationship between signal intensity and allele dosage must be inferred independently for each marker. We developed an improved computational method to automate this process, ...

  12. Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

    Directory of Open Access Journals (Sweden)

    Mohammad Nur Shodiq

    2016-03-01

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

  13. A Cluster Analysis of Personality Style in Adults with ADHD

    Science.gov (United States)

    Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

    2008-01-01

    Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

  14. A Cluster Analysis of Personality Style in Adults with ADHD

    Science.gov (United States)

    Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

    2008-01-01

    Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

  15. Hierarchical Star Formation Across Galactic Disks

    Science.gov (United States)

    Gouliermis, Dimitrios

    2016-09-01

    Most stars form in clusters. This fact has emerged from the finding that "embedded clusters account for the 70 - 90% fraction of all stars formed in Giant Molecular Clouds (GMCs)." While this is the case at scales of few 10 parsecs, typical for GMCs, a look at star-forming galaxies in the Local Group (LG) shows significant populations of enormous loose complexes of early-type stars extending at scales from few 100 to few 1000 parsecs. The fact that these stellar complexes host extremely large numbers of loosely distributed massive blue stars implies either that stars form also in an unbound fashion or they are immediately dislocated from their original compact birthplaces or both. The Legacy Extra-Galactic UV Survey (LEGUS) has produced remarkable collections of resolved early-type stars in 50 star-forming LG galaxies, suited for testing ideas about recent star formation. I will present results from our ongoing project on star formation across LEGUS disk galaxies. We characterize the global clustering behavior of the massive young stars in order to understand the morphology of star formation over galactic scales. This morphology appears to be self-similar with fractal dimensions comparable to those of the molecular interstellar medium, apparently driven by large-scale turbulence. Our clustering analysis reveals compact stellar systems nested in larger looser concentrations, which themselves are the dense parts of unbound complexes and super-structures, giving evidence of hierarchical star formation up to galactic scales. We investigate the structural and star formation parameters demographics of the star-forming complexes revealed at various levels of compactness. I will discuss the outcome of our correlation and regression analyses on these parameters in an attempt to understand the link between galactic disk dynamics and morphological structure in spiral and ring galaxies of the local universe.

  16. Bayesian Mass Estimates of the Milky Way: Including measurement uncertainties with hierarchical Bayes

    CERN Document Server

    Eadie, Gwendolyn; Harris, William

    2016-01-01

    We present a hierarchical Bayesian method for estimating the total mass and mass profile of the Milky Way Galaxy. The new hierarchical Bayesian approach further improves the framework presented by Eadie, Harris, & Widrow (2015) and Eadie & Harris (2016) and builds upon the preliminary reports by Eadie et al (2015a,c). The method uses a distribution function $f(\\mathcal{E},L)$ to model the galaxy and kinematic data from satellite objects such as globular clusters to trace the Galaxy's gravitational potential. A major advantage of the method is that it not only includes complete and incomplete data simultaneously in the analysis, but also incorporates measurement uncertainties in a coherent and meaningful way. We first test the hierarchical Bayesian framework, which includes measurement uncertainties, using the same data and power-law model assumed in Eadie & Harris (2016), and find the results are similar but more strongly constrained. Next, we take advantage of the new statistical framework and in...

  17. Joint Hierarchical Category Structure Learning and Large-Scale Image Classification

    Science.gov (United States)

    Qu, Yanyun; Lin, Li; Shen, Fumin; Lu, Chang; Wu, Yang; Xie, Yuan; Tao, Dacheng

    2017-09-01

    We investigate the scalable image classification problem with a large number of categories. Hierarchical visual data structures are helpful for improving the efficiency and performance of large-scale multi-class classification. We propose a novel image classification method based on learning hierarchical inter-class structures. Specifically, we first design a fast algorithm to compute the similarity metric between categories, based on which a visual tree is constructed by hierarchical spectral clustering. Using the learned visual tree, a test sample label is efficiently predicted by searching for the best path over the entire tree. The proposed method is extensively evaluated on the ILSVRC2010 and Caltech 256 benchmark datasets. Experimental results show that our method obtains significantly better category hierarchies than other state-of-the-art visual tree-based methods and, therefore, much more accurate classification.

  18. Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

    Science.gov (United States)

    Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

    2017-07-19

    Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

  19. LoCuSS: First Results from Strong-lensing Analysis of 20 Massive Galaxy Clusters at z~0.2

    CERN Document Server

    Richard, Johan; Kneib, Jean-Paul; Ellis, Richard; Sanderson, Alastair; Pei, Liuyi; Targett, Thomas; Sand, David; Swinbank, Mark; Dannerbauer, Helmut; Mazzotta, Pascuale; Limousin, Marceau; Egami, Eiichi; Jullo, Eric; Hamilton-Morris, Victoria; Moran, Sean

    2009-01-01

    We present a statistical analysis of a sample of 20 strong lensing clusters drawn from the Local Cluster Substructure Survey (LoCuSS), based on high resolution Hubble Space Telescope imaging of the cluster cores and follow-up spectroscopic observations using the Keck-I telescope. We use detailed parameterized models of the mass distribution in the cluster cores, to measure the total cluster mass and fraction of that mass associated with substructures within R=1.16+/-0.28; (ii) we detect an X-ray/lensing mass discrepancy of =1.3 at 3 sigma significance -- clusters with larger substructure fractions displaying greater mass discrepancies, and thus greater departures from hydrostatic equilibrium; (iii) cluster substructure fraction is also correlated with the slope of the gas density profile on small scales, implying a connection between cluster-cluster mergers and gas cooling. Overall our results are consistent with the view that cluster-cluster mergers play a prominent role in shaping the properties of cluster ...

  20. Planck intermediate results XL. The Sunyaev-Zeldovich signal from the Virgo cluster

    DEFF Research Database (Denmark)

    Ade, P. A. R.; Aghanim, N.; Arnaud, M.

    2016-01-01

    -ray observations and simple analytical models. Owing to its proximity to us, the gas beyond the virial radius in Virgo can be studied with unprecedented sensitivity by integrating the SZ signal over tens of square degrees. We study the signal in the outskirts of Virgo and compare it with analytical models...... and a constrained simulation of the environment of Virgo. Planck data suggest that significant amounts of low-density plasma surround Virgo, out to twice the virial radius. We find the SZ signal in the outskirts of Virgo to be consistent with a simple model that extrapolates the inferred pressure at lower radii......, while assuming that the temperature stays in the keV range beyond the virial radius. The observed signal is also consistent with simulations and points to a shallow pressure profile in the outskirts of the cluster. This reservoir of gas at large radii can be linked with the hottest phase of the elusive...

  1. First Cluster results of the magnetic field structure of the mid- and high-altitude cusps

    Directory of Open Access Journals (Sweden)

    P. J. Cargill

    Full Text Available Magnetic field measurements from the four Cluster spacecraft from the mid- and high-altitude cusp are presented. Cluster underwent two encounters with the mid-altitude cusp during its commissioning phase (24 August 2000. Evidence for field-aligned currents (FACs was seen in the data from all three operating spacecraft from northern and southern cusps. The extent of the FACs was of the order of 1 RE in the X-direction, and at least 300 km in the Y-direction. However, fine-scale field structures with scales of the order of the spacecraft separation (300 km were observed within the FACs. In the northern crossing, two of the spacecraft appeared to lie along the same magnetic field line, and observed very well matched signals. However, the third spacecraft showed evidence for structuring transverse to the field on scales of a few hundred km. A crossing of the high-altitude cusp from 13 February 2001 is presented. It is revealed to be a highly dynamic structure with the boundaries moving with velocities ranging from a few km/s to tens of km/s, and having structure on timescales ranging from less than one minute up to several minutes. The cusp proper is associated with the presence of a very disordered magnetic field, which is entirely different from the magnetosheath turbulence.

    Key words. Magnetospheric physics (current systems; magnetopause, cusp, and boundary layers – Space plasma physics (discontinuities

  2. Comparative Study of K-means and Robust Clustering

    Directory of Open Access Journals (Sweden)

    Shashi Sharma

    2013-09-01

    Full Text Available Data mining is the mechanism of implementing patterns in large amount of data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. Clustering is the very big area in which grouping of same type of objects in data mining. Clustering has divided into different categories – partitioned clustering and hierarchical clustering. In this paper we study two types of clustering first is Kmeans which is part of partitioned clustering. Kmeans clustering generates a specific number of disjoint, flat (non-hierarchical clusters. Second clustering is robust clustering which is part of hierarchical clustering. This clustering uses Jaccard coefficient instead of using the distance measures to find the similarity between the data or documents to classify the clusters. We show comparison between Kmeans clustering and robust clustering which is better for categorical data.

  3. A spatial analysis of hierarchical waste transport structures under growing demand.

    Science.gov (United States)

    Tanguy, Audrey; Glaus, Mathias; Laforest, Valérie; Villot, Jonathan; Hausler, Robert

    2016-10-01

    The design of waste management systems rarely accounts for the spatio-temporal evolution of the demand. However, recent studies suggest that this evolution affects the planning of waste management activities like the choice and location of treatment facilities. As a result, the transport structure could also be affected by these changes. The objective of this paper is to study the influence of the spatio-temporal evolution of the demand on the strategic planning of a waste transport structure. More particularly this study aims at evaluating the effect of varying spatial parameters on the economic performance of hierarchical structures (with one transfer station). To this end, three consecutive generations of three different spatial distributions were tested for hierarchical and non-hierarchical transport structures based on costs minimization. Results showed that a hierarchical structure is economically viable for large and clustered spatial distributions. The distance parameter was decisive but the loading ratio of trucks and the formation of clusters of sources also impacted the attractiveness of the transfer station. Thus the territories' morphology should influence strategies as regards to the installation of transfer stations. The use of spatial-explicit tools such as the transport model presented in this work that take into account the territory's evolution are needed to help waste managers in the strategic planning of waste transport structures.

  4. Quasar Evolution Driven by Galaxy Encounters in Hierarchical Structures

    CERN Document Server

    Menci, N; Fontana, A; Giallongo, E; Poli, F; Vittorini, V

    2003-01-01

    We link the evolution of the galaxies in the hierarchical clustering scenario with the changing accretion rates of cold gas onto the central massive black holes that power the quasars. We base on galaxy interactions as main triggers of accretion; the related scaling laws are taken up from Cavaliere & Vittorini (2000), and grafted to a semi-analytic code for galaxy formation. As a result, at high $z$ the protogalaxies grow rapidly by hierarchical merging; meanwhile, much fresh gas is imported and also destabilized, so the holes are fueled at their full Eddington rates. At lower $z$ the galactic dynamical events are mostly encounters in hierarchically growing groups; now the refueling peters out, as the residual gas is exhausted while the destabilizing encounters dwindle. So, with no parameter tuning other than needed for stellar observables, our model uniquely produces at $z>3$ a rise, and at $z\\lesssim 2.5 $ a decline of the bright quasar population as steep as observed. In addition, our results closely f...

  5. Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

    Science.gov (United States)

    Tilton, James C.

    2003-01-01

    A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic

  6. The Nature and Nurture of Star Clusters

    CERN Document Server

    Elmegreen, Bruce G

    2009-01-01

    Star clusters have hierarchical patterns in space and time, suggesting formation processes in the densest regions of a turbulent interstellar medium. Clusters also have hierarchical substructure when they are young, which makes them all look like the inner mixed parts of a pervasive stellar hierarchy. Young field stars share this distribution, presumably because some of them came from dissolved clusters and others formed in a dispersed fashion in the same gas. The fraction of star formation that ends up in clusters is apparently not constant, but may increase with interstellar pressure. Hierarchical structure explains why stars form in clusters and why many of these clusters are self-bound. It also explains the cluster mass function. Halo globular clusters share many properties of disk clusters, including what appears to be an upper cluster cutoff mass. However, halo globulars are self-enriched and often connected with dwarf galaxy streams. The mass function of halo globulars could have initially been like th...

  7. Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms

    OpenAIRE

    Arampatzis, Giorgos; Katsoulakis, Markos A.; Plechac, Petr; Taufer, Michela; Xu, Lifan

    2011-01-01

    We present a mathematical framework for constructing and analyzing parallel algorithms for lattice Kinetic Monte Carlo (KMC) simulations. The resulting algorithms have the capacity to simulate a wide range of spatio-temporal scales in spatially distributed, non-equilibrium physiochemical processes with complex chemistry and transport micro-mechanisms. The algorithms can be tailored to specific hierarchical parallel architectures such as multi-core processors or clusters of Graphical Processin...

  8. Planck intermediate results. XL. The Sunyaev-Zeldovich signal from the Virgo cluster

    CERN Document Server

    Ade, P A R; Arnaud, M; Ashdown, M; Aumont, J; Baccigalupi, C; Banday, A J; Barreiro, R B; Bartolo, N; Battaner, E; Benabed, K; Benoit-Lévy, A; Bernard, J -P; Bersanelli, M; Bielewicz, P; Bonaldi, A; Bonavera, L; Bond, J R; Borrill, J; Bouchet, F R; Burigana, C; Butler, R C; Calabrese, E; Cardoso, J -F; Catalano, A; Chamballu, A; Chiang, H C; Christensen, P R; Churazov, E; Clements, D L; Colombo, L P L; Combet, C; Comis, B; Couchot, F; Coulais, A; Crill, B P; Curto, A; Cuttaia, F; Danese, L; Davies, R D; Davis, R J; de Bernardis, P; de Rosa, A; de Zotti, G; Delabrouille, J; Dickinson, C; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Doré, O; Douspis, M; Ducout, A; Dupac, X; Efstathiou, G; Elsner, F; Enßlin, T A; Eriksen, H K; Finelli, F; Forni, O; Frailis, M; Fraisse, A A; Franceschi, E; Galeotta, S; Galli, S; Ganga, K; Giard, M; Giraud-Héraud, Y; Gjerløw, E; González-Nuevo, J; Górski, K M; Gregorio, A; Gruppuso, A; Gudmundsson, J E; Hansen, F K; Harrison, D L; Helou, G; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Hornstrup, A; Hovest, W; Huffenberger, K M; Hurier, G; Jaffe, A H; Jaffe, T R; Jones, W C; Keihänen, E; Keskitalo, R; Kisner, T S; Kneissl, R; Knoche, J; Kunz, M; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lasenby, A; Lattanzi, M; Lawrence, C R; Leonardi, R; Levrier, F; Liguori, M; Lilje, P B; Linden-Vørnle, M; López-Caniego, M; Lubin, P M; Macías-Pérez, J F; Maffei, B; Maggio, G; Maino, D; Mandolesi, N; Mangilli, A; Marcos-Caballero, A; Maris, M; Martin, P G; Martínez-González, E; Masi, S; Matarrese, S; Mazzotta, P; Meinhold, P R; Melchiorri, A; Mennella, A; Migliaccio, M; Mitra, S; Miville-Deschênes, M -A; Moneti, A; Montier, L; Morgante, G; Mortlock, D; Munshi, D; Murphy, J A; Naselsky, P; Nati, F; Natoli, P; Noviello, F; Novikov, D; Novikov, I; Oppermann, N; Oxborrow, C A; Pagano, L; Pajot, F; Paoletti, D; Pasian, F; Pearson, T J; Perdereau, O; Perotto, L; Pettorino, V; Piacentini, F; Piat, M; Pierpaoli, E; Plaszczynski, S; Pointecouteau, E; Polenta, G; Ponthieu, N; Pratt, G W; Prunet, S; Puget, J -L; Rachen, J P; Reinecke, M; Remazeilles, M; Renault, C; Renzi, A; Ristorcelli, I; Rocha, G; Rosset, C; Rossetti, M; Roudier, G; Rubiño-Martín, J A; Rusholme, B; Sandri, M; Santos, D; Savelainen, M; Savini, G; Schaefer, B M; Scott, D; Soler, J D; Stolyarov, V; Stompor, R; Sudiwala, R; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Sygnet, J -F; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Tucci, M; Umana, G; Valenziano, L; Valiviita, J; Van Tent, B; Vielva, P; Villa, F; Wade, L A; Wandelt, B D; Wehus, I K; Weller, J; Yvon, D; Zacchei, A; Zonca, A

    2015-01-01

    The Virgo cluster is the largest Sunyaev-Zeldovich (SZ) source in the sky, both in terms of angular size and total integrated flux. Planck's wide angular scale and frequency coverage, together with its high sensitivity, allow a detailed study of this large object through the SZ effect. Virgo is well resolved by Planck, showing an elongated structure, which correlates well with the morphology observed from X-rays, but extends beyond the observed X-ray signal. We find a good agreement between the SZ signal (or Compton paranmeter, y_c) observed by Planck and the expected signal inferred from X-ray observations and simple analytical models. Due to its proximity to us, the gas beyond the virial radius can be studied with unprecedented sensitivity by integrating the SZ signal over tens of square degrees. We study the signal in the outskirts of Virgo and compare it with analytical models and a constrained simulation of the environment of Virgo. Planck data suggest that significant amounts of low-density plasma surro...

  9. Planck intermediate results. III. The relation between galaxy cluster mass and Sunyaev-Zeldovich signal

    CERN Document Server

    Aghanim, N; Ashdown, M; Atrio-Barandela, F; Aumont, J; Balbi, A; Banday, A J; Barreiro, R B; Bartlett, J G; Battaner, E; Battye, R; Bernard, J -P; Bersanelli, M; Bhatia, R; Bikmaev, I; Böhringer, H; Bonaldi, A; Bond, J R; Borgani, S; Borrill, J; Bourdin, H; Brown, M L; Bucher, M; Burenin, R; Burigana, C; Butler, R C; Cabella, P; Cardoso, J -F; Carvalho, P; Chamballu, A; Chiang, L -Y; Chon, G; Clements, D L; Colafrancesco, S; Cuttaia, F; Da Silva, A; Dahle, H; Davis, R J; de Bernardis, P; de Gasperis, G; Delabrouille, J; Démoclès, J; Désert, F -X; Diego, J M; Dolag, K; Dole, H; Donzelli, S; Douspis, M; Dupac, X; Efstathiou, G; Enßlin, T A; Eriksen, H K; Finelli, F; Flores-Cacho, I; Forni, O; Frailis, M; Franceschi, E; Frommert, M; Ganga, K; Génova-Santos, R T; Giard, M; Giraud-Héraud, Y; González-Nuevo, J; Górski, K M; Gruppuso, A; Hansen, F K; Harrison, D; Hernández-Monteagudo, C; Herranz, D; Hildebrandt, S R; Hivon, E; Hobson, M; Huffenberger, K M; Hurier, G; Jagemann, T; Juvela, M; Keihänen, E; Khamitov, I; Kneissl, R; Knoche, J; Kunz, M; Kurki-Suonio, H; Lagache, G; Lamarre, J -M; Lasenby, A; Lawrence, C R; Jeune, M Le; Leach, S; Leonardi, R; Liddle, A; Lilje, P B; Linden-Vørnle, M; López-Caniego, M; Luzzi, G; Macías-Pérez, J F; Maino, D; Mandolesi, N; Marleau, F; Marshall, D J; Martínez-González, E; Masi, S; Matarrese, S; Matthai, F; Mazzotta, P; Melchiorri, A; Melin, J -B; Mendes, L; Miville-Deschênes, M -A; Montier, L; Morgante, G; Munshi, D; Natoli, P; Noviello, F; Osborne, S; Pajot, F; Paoletti, D; Pearson, T J; Perdereau, O; Perrotta, F; Piacentini, F; Piat, M; Pierpaoli, E; Piffaretti, R; Platania, P; Pointecouteau, E; Polenta, G; Ponthieu, N; Popa, L; Poutanen, T; Pratt, G W; Puget, J -L; Rachen, J P; Rebolo, R; Reinecke, M; Remazeilles, M; Renault, C; Ricciardi, S; Ristorcelli, I; Rocha, G; Rosset, C; Rossetti, M; Rubiño-Martín, J A; Rusholme, B; Savini, G; Starck, J -L; Stivoli, F; Stolyarov, V; Sunyaev, R; Sutton, D; Suur-Uski, A -S; Tauber, J A; Terenzi, L; Toffolatti, L; Tomasi, M; Tristram, M; Valenziano, L; Van Tent, B; Vielva, P; Villa, F; Vittorio, N; Weller, J; White, S D M; Zacchei, A; Zonca, A

    2012-01-01

    We examine the relation between the galaxy cluster mass M and Sunyaev-Zeldovich (SZ) effect signal D_A^2 Y for a sample of nineteen objects for which weak lensing (WL) mass measurements obtained from Subaru Telescope data are available in the literature. Hydrostatic X-ray masses (HE) are derived from XMM-Newton archive data and the SZ effect signal is measured from Planck all-sky survey data. We find an M_WL-D_A^2 Y relation that is consistent in slope and normalisation with previous determinations using weak lensing masses; however, there is a normalisation offset with respect to previous measures based on hydrostatic X-ray mass-proxy relations. We verify that our SZ effect measurements are in excellent agreement with previous determinations from Planck data. At odds with expectations, for the present sample, the hydrostatic X-ray masses at R_500 are on average 22 +/- 8 per cent larger than the corresponding weak lensing masses. We show that the mass discrepancy is driven by a difference in mass concentratio...

  10. Clustering in the Phase Space of Dark Matter Haloes. I. Results from the Aquarius simulations

    CERN Document Server

    Zavala, Jesus

    2013-01-01

    We present a novel perspective on the clustering of dark matter in phase space by defining the particle phase space average density (P2SAD) as a two-dimensional extension of the two-point correlation function averaged within a certain volume in phase space. This statistics is a very sensitive measure of cold small scale (sub)structure of dark matter haloes. By analysing the structure of P2SAD in Milky-Way-size haloes using the high resolution Aquarius simulations, we find it to be nearly universal at small scales (i.e. small separations in phase space), in the regime dominated by gravitationally bound substructures. This remarkable universality occurs across time and in regions of substantially different ambient densities (by nearly four orders of magnitude), with typical variations in P2SAD of a factor of a few. The maximum variations occur in regions where resolved substructures have been strongly disrupted (e.g. near the halo centre). The universality is also preserved across haloes of similar mass but div...

  11. A neural signature of hierarchical reinforcement learning.

    Science.gov (United States)

    Ribas-Fernandes, José J F; Solway, Alec; Diuk, Carlos; McGuire, Joseph T; Barto, Andrew G; Niv, Yael; Botvinick, Matthew M

    2011-07-28

    Human behavior displays hierarchical structure: simple actions cohere into subtask sequences, which work together to accomplish overall task goals. Although the neural substrates of such hierarchy have been the target of increasing research, they remain poorly understood. We propose that the computations supporting hierarchical behavior may relate to those in hierarchical reinforcement learning (HRL), a machine-learning framework that extends reinforcement-learning mechanisms into hierarchical domains. To test this, we leveraged a distinctive prediction arising from HRL. In ordinary reinforcement learning, reward prediction errors are computed when there is an unanticipated change in the prospects for accomplishing overall task goals. HRL entails that prediction errors should also occur in relation to task subgoals. In three neuroimaging studies we observed neural responses consistent with such subgoal-related reward prediction errors, within structures previously implicated in reinforcement learning. The results reported support the relevance of HRL to the neural processes underlying hierarchical behavior.

  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. Associative Hierarchical Random Fields.

    Science.gov (United States)

    Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

    2014-06-01

    This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.

  14. A hierarchical linear model for tree height prediction.

    Science.gov (United States)

    Vicente J. Monleon

    2003-01-01

    Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data...

  15. A HIERARCHICAL INTRUSION DETECTION ARCHITECTURE FOR WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    Hossein Jadidoleslamy

    2011-10-01

    Full Text Available Networks protection against different types of attacks is one of most important posed issue into the network andinformation security application domains. This problem on Wireless Sensor Networks (WSNs, in attention to theirspecial properties, has more importance. Now, there are some of proposed architectures and guide lines to protectWireless Sensor Networks (WSNs against different types of intrusions; but any one of them do not has acomprehensive view to this problem and they are usually designed and implemented in single-purpose; but, theproposed design in this paper tries to has been a comprehensive view to this issue by presenting a complete andcomprehensive Intrusion Detection Architecture (IDA. The main contribution of this architecture is its hierarchicalstructure; i.e., it is designed and applicable, in one or two levels, consistent to the application domain and itsrequired security level. Focus of this paper is on the clustering WSNs, designing and deploying Cluster-basedIntrusion Detection System (CIDS on cluster-heads and Wireless Sensor Network wide level Intrusion DetectionSystem (WSNIDS on the central server. Suppositions of the WSN and Intrusion Detection Architecture (IDA are:static and heterogeneous network, hierarchical and clustering structure, clusters' overlapping and using hierarchicalrouting protocol such as LEACH, but along with minor changes. Finally, the proposed idea has been verified bydesigning a questionnaire, representing it to some (about 50 people experts and then, analyzing and evaluating itsacquired results.

  16. Hierarchical organization of brain functional network during visual task

    CERN Document Server

    Zhuo, Zhao; Fu, Zhong-Qian; Zhang, Jie

    2011-01-01

    In this paper, the brain functional networks derived from high-resolution synchronous EEG time series during visual task are generated by calculating the phase synchronization among the time series. The hierarchical modular organizations of these networks are systematically investigated by the fast Girvan-Newman algorithm. At the same time, the spatially adjacent electrodes (corresponding to EEG channels) are clustered into functional groups based on anatomical parcellation of brain cortex, and this clustering information are compared to that of the functional network. The results show that the modular architectures of brain functional network are in coincidence with that from the anatomical structures over different levels of hierarchy, which suggests that population of neurons performing the same function excite and inhibit in identical rhythms. The structure-function relationship further reveals that the correlations among EEG time series in the same functional group are much stronger than those in differe...

  17. Residential patterns in older homeless adults: Results of a cluster analysis.

    Science.gov (United States)

    Lee, Christopher Thomas; Guzman, David; Ponath, Claudia; Tieu, Lina; Riley, Elise; Kushel, Margot

    2016-03-01

    Adults aged 50 and older make up half of individuals experiencing homelessness and have high rates of morbidity and mortality. They may have different life trajectories and reside in different environments than do younger homeless adults. Although the environmental risks associated with homelessness are substantial, the environments in which older homeless individuals live have not been well characterized. We classified living environments and identified associated factors in a sample of older homeless adults. From July 2013 to June 2014, we recruited a community-based sample of 350 homeless men and women aged fifty and older in Oakland, California. We administered structured interviews including assessments of health, history of homelessness, social support, and life course. Participants used a recall procedure to describe where they stayed in the prior six months. We performed cluster analysis to classify residential venues and used multinomial logistic regression to identify individual factors prior to the onset of homelessness as well as the duration of unstable housing associated with living in them. We generated four residential groups describing those who were unsheltered (n = 162), cohabited unstably with friends and family (n = 57), resided in multiple institutional settings (shelters, jails, transitional housing) (n = 88), or lived primarily in rental housing (recently homeless) (n = 43). Compared to those who were unsheltered, having social support when last stably housed was significantly associated with cohabiting and institution use. Cohabiters and renters were significantly more likely to be women and have experienced a shorter duration of homelessness. Cohabiters were significantly more likely than unsheltered participants to have experienced abuse prior to losing stable housing. Pre-homeless social support appears to protect against street homelessness while low levels of social support may increase the risk for becoming homeless immediately after

  18. Investigation on IMCP based clustering in LTE-M communication for smart metering applications

    National Research Council Canada - National Science Library

    Kartik Vishal Deshpande; A. Rajesh

    2017-01-01

    .... This paper investigates the proposed Improved M2M Clustering Process (IMCP) based clustering technique and it is compared with two well-known clustering algorithms, namely, Low Energy Adaptive Clustering Hierarchical (LEACH...

  19. Study on Cluster Analysis Used with Laser-Induced Breakdown Spectroscopy

    Science.gov (United States)

    He, Li'ao; Wang, Qianqian; Zhao, Yu; Liu, Li; Peng, Zhong

    2016-06-01

    Supervised learning methods (eg. PLS-DA, SVM, etc.) have been widely used with laser-induced breakdown spectroscopy (LIBS) to classify materials; however, it may induce a low correct classification rate if a test sample type is not included in the training dataset. Unsupervised cluster analysis methods (hierarchical clustering analysis, K-means clustering analysis, and iterative self-organizing data analysis technique) are investigated in plastics classification based on the line intensities of LIBS emission in this paper. The results of hierarchical clustering analysis using four different similarity measuring methods (single linkage, complete linkage, unweighted pair-group average, and weighted pair-group average) are compared. In K-means clustering analysis, four kinds of choosing initial centers methods are applied in our case and their results are compared. The classification results of hierarchical clustering analysis, K-means clustering analysis, and ISODATA are analyzed. The experiment results demonstrated cluster analysis methods can be applied to plastics discrimination with LIBS. supported by Beijing Natural Science Foundation of China (No. 4132063)

  20. Memory Stacking in Hierarchical Networks.

    Science.gov (United States)

    Westö, Johan; May, Patrick J C; Tiitinen, Hannu

    2016-02-01

    Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

  1. Human performance in monitoring and controlling hierarchical large-scale systems

    Energy Technology Data Exchange (ETDEWEB)

    Henneman, R.L.; Rouse, W.B.

    1984-03-01

    Human performance in monitoring and controlling activities in a hierarchical large-scale network, such as a communications system, is considered. A scenario is described that is used in an experiment to examine three factors affecting humans functioning as network supervisor: cluster size (number of elements per display page), number of levels of pages in the hierarchy, and failure rate per element. It is indicated by the results that increasing cluster size improves performance, increasing number of levels degrades performance, and failure rate affects only subjects strategies.

  2. Constructing Product Ontologies with an Improved Conceptual Clustering Algorithm

    Institute of Scientific and Technical Information of China (English)

    曹大军; 徐良贤

    2002-01-01

    In a distributed eMarketplace, recommended product ontologies are required for trading between buyers and sellers. Conceptual clustering can be employed to build dynamic recommended product ontologies. Traditional methods of conceptual clustering (e. g. COBWEB or Cluster/2) do not take heterogeneous attributes of a concept into account.Moreover, the result of these methods is clusters other than recommended concepts. A center recommendation clustering algorithm is provided. According to the values of heterogeneous attributes, recommended product names can be selected at the clusters, which are produced by this algorithm. This algorithm can also create the hierarchical relations between product names. The definitions of product names given by all participants are collected in a distributed eMarketplace.Recommended product ontologies are built. These ontologies include relations and definitions of product names, which come from different participants in the distributed eMarketplace. Finally a case is given to illustrate this method. The result shows that this method is feasible.

  3. Hierarchical models and chaotic spin glasses

    Science.gov (United States)

    Berker, A. Nihat; McKay, Susan R.

    1984-09-01

    Renormalization-group studies in position space have led to the discovery of hierarchical models which are exactly solvable, exhibiting nonclassical critical behavior at finite temperature. Position-space renormalization-group approximations that had been widely and successfully used are in fact alternatively applicable as exact solutions of hierarchical models, this realizability guaranteeing important physical requirements. For example, a hierarchized version of the Sierpiriski gasket is presented, corresponding to a renormalization-group approximation which has quantitatively yielded the multicritical phase diagrams of submonolayers on graphite. Hierarchical models are now being studied directly as a testing ground for new concepts. For example, with the introduction of frustration, chaotic renormalization-group trajectories were obtained for the first time. Thus, strong and weak correlations are randomly intermingled at successive length scales, and a new microscopic picture and mechanism for a spin glass emerges. An upper critical dimension occurs via a boundary crisis mechanism in cluster-hierarchical variants developed to have well-behaved susceptibilities.

  4. Periodic ordering of clusters and stripes in a two-dimensional lattice model. II. Results of Monte Carlo simulation.

    Science.gov (United States)

    Almarza, N G; Pȩkalski, J; Ciach, A

    2014-04-28

    The triangular lattice model with nearest-neighbor attraction and third-neighbor repulsion, introduced by Pȩkalski, Ciach, and Almarza [J. Chem. Phys. 140, 114701 (2014)] is studied by Monte Carlo simulation. Introduction of appropriate order parameters allowed us to construct a phase diagram, where different phases with patterns made of clusters, bubbles or stripes are thermodynamically stable. We observe, in particular, two distinct lamellar phases-the less ordered one with global orientational order and the more ordered one with both orientational and translational order. Our results concern spontaneous pattern formation on solid surfaces, fluid interfaces or membranes that is driven by competing interactions between adsorbing particles or molecules.

  5. Characterisation of microcalcification clusters on 2D digital mammography (FFDM) and digital breast tomosynthesis (DBT): does DBT underestimate microcalcification clusters? Results of a multicentre study

    Energy Technology Data Exchange (ETDEWEB)

    Tagliafico, Alberto [University of Genoa, Institute of Anatomy, Department of Experimental Medicine (DIMES), Genoa (Italy); Mariscotti, Giovanna; Durando, Manuela [Azienda Ospedaliero-Universitaria Citta della Salute e della Scienza di Torino, Radiology University of Torino, Department of Diagnostic Imaging and Radiotherapy, Torino (Italy); Stevanin, Carmen [Ospedale Regionale di Bolzano, Bolzano (Italy); Tagliafico, Giulio [Istituto di Matematica Applicata e Tecnologie Informatiche, CNR-IMATI, Consiglio Nazionale delle Ricerche, Genova (Italy); Martino, Lucia; Bignotti, Bianca [University of Genoa, Department of Health Sciences (DISSAL), Genoa (Italy); Calabrese, Massimo [IRCCS AOU San Martino-IST, Department of Breast Radiology, Genova (Italy); Houssami, Nehmat [University of Sydney, Screening and Test Evaluation Program (STEP), School of Public Health, Sydney Medical School, Sydney (Australia)

    2015-01-15

    To compare DBT and FFDM in the classification of microcalcification clusters (MCs) using BI-RADS. This Institutional Review Board-approved study was undertaken in three centres. A total of 107 MCs evaluated with both DBT and FFDM were randomised for prospective reading by six experienced breast radiologists and classified using BI-RADS. The benign/malignant ratio of MC was 66/41. Of 11/107 discordant results, DBT classified MCs as R2 whereas FFDM classified them as R3 in 9 and R4 in 2. Three of these (3/107 = 2.8 %) were malignant; 8 (7.5 %) were nonmalignant and were correctly classified as R2 on DBT but incorrectly classified as R3 on FFDM. Estimated sensitivity and specificity, respectively, were 100 % (95 % CI: 91 % to 100 %) and 94.6 % (95 % CI: 86.7 % to 98.5 %) for FFDM and 91.1 % (95 % CI: 78.8 % to 97.5 %) and 100 % (95 % CI: 94.8 % to 100 %) for DBT. Overall intra- and interobserver agreements were 0.75 (95 % CI: 0.61-0.84) and 0.73 (95 % CI: 0.62-0.78). Most MCs are scored similarly on FFDM and DBT. Although a minority (11/107) of MCs are classified differently on FFDM (benign MC classified as R3) and DBT (malignant MC classified as R2), this may have clinical relevance. (orig.)

  6. Hierarchical auxetic mechanical metamaterials.

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I; Azzopardi, Keith M; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N

    2015-02-11

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  7. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  8. Hierarchical Auxetic Mechanical Metamaterials

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

    2015-02-01

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  9. Applied Bayesian Hierarchical Methods

    CERN Document Server

    Congdon, Peter D

    2010-01-01

    Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.

  10. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  11. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  12. Impact of an automated email notification system for results of tests pending at discharge: a cluster-randomized controlled trial.

    Science.gov (United States)

    Dalal, Anuj K; Roy, Christopher L; Poon, Eric G; Williams, Deborah H; Nolido, Nyryan; Yoon, Cathy; Budris, Jonas; Gandhi, Tejal; Bates, David W; Schnipper, Jeffrey L

    2014-01-01

    Physician awareness of the results of tests pending at discharge (TPADs) is poor. We developed an automated system that notifies responsible physicians of TPAD results via secure, network email. We sought to evaluate the impact of this system on self-reported awareness of TPAD results by responsible physicians, a necessary intermediary step to improve management of TPAD results. We conducted a cluster-randomized controlled trial at a major hospital affiliated with an integrated healthcare delivery network in Boston, Massachusetts. Adult patients with TPADs who were discharged from inpatient general medicine and cardiology services were assigned to the intervention or usual care arm if their inpatient attending physician and primary care physician (PCP) were both randomized to the same study arm. Patients of physicians randomized to discordant study arms were excluded. We surveyed these physicians 72 h after all TPAD results were finalized. The primary outcome was awareness of TPAD results by attending physicians. Secondary outcomes included awareness of TPAD results by PCPs, awareness of actionable TPAD results, and provider satisfaction. We analyzed data on 441 patients. We sent 441 surveys to attending physicians and 353 surveys to PCPs and received 275 and 152 responses from 83 different attending physicians and 112 different PCPs, respectively (attending physician survey response rate of 63%). Intervention attending physicians and PCPs were significantly more aware of TPAD results (76% vs 38%, adjusted/clustered OR 6.30 (95% CI 3.02 to 13.16), pemail notification represents a promising strategy for managing TPAD results, potentially mitigating an unresolved patient safety concern. ClinicalTrials.gov (NCT01153451).

  13. Interrupted time-series analysis yielded an effect estimate concordant with the cluster-randomized controlled trial result.

    Science.gov (United States)

    Fretheim, Atle; Soumerai, Stephen B; Zhang, Fang; Oxman, Andrew D; Ross-Degnan, Dennis

    2013-08-01

    We reanalyzed the data from a cluster-randomized controlled trial (C-RCT) of a quality improvement intervention for prescribing antihypertensive medication. Our objective was to estimate the effectiveness of the intervention using both interrupted time-series (ITS) and RCT methods, and to compare the findings. We first conducted an ITS analysis using data only from the intervention arm of the trial because our main objective was to compare the findings from an ITS analysis with the findings from the C-RCT. We used segmented regression methods to estimate changes in level or slope coincident with the intervention, controlling for baseline trend. We analyzed the C-RCT data using generalized estimating equations. Last, we estimated the intervention effect by including data from both study groups and by conducting a controlled ITS analysis of the difference between the slope and level changes in the intervention and control groups. The estimates of absolute change resulting from the intervention were ITS analysis, 11.5% (95% confidence interval [CI]: 9.5, 13.5); C-RCT, 9.0% (95% CI: 4.9, 13.1); and the controlled ITS analysis, 14.0% (95% CI: 8.6, 19.4). ITS analysis can provide an effect estimate that is concordant with the results of a cluster-randomiz