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Sample records for 1842676957299765latent class cluster

  1. 1842676957299765Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities

    Directory of Open Access Journals (Sweden)

    Meghani Salimah

    2009-01-01

    Full Text Available Abstract Background Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction. Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals' preferences for health states given similar treatments and clinical risks. Methods Using latent class mixture model (LCA, we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups. Results The sample (N = 244 included men with prostate cancer (n = 188 and men at-risk for disease (n = 56. The sample was predominantly white (77%, with mean age of 60 years (SD ± 9.5. Most (85.9% were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC, substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of < .001. The three identified clusters were named high-traders (n = 31, low-traders (n = 116, and no-traders (n = 97. High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment. Low-traders were less likely to trade survival time and accepted risks of treatment. The no-traders were likely to make no trade-offs in any direction favouring the status quo. There was significant difference among the clusters in the importance of sexual activity (Pearson's χ2 = 16.55, P = 0.002; Goodman and Kruskal tau = 0.039, P < 0.001. In

  2. Context-sensitive intra-class clustering

    KAUST Repository

    Yu, Yingwei

    2014-02-01

    This paper describes a new semi-supervised learning algorithm for intra-class clustering (ICC). ICC partitions each class into sub-classes in order to minimize overlap across clusters from different classes. This is achieved by allowing partitioning of a certain class to be assisted by data points from other classes in a context-dependent fashion. The result is that overlap across sub-classes (both within- and across class) is greatly reduced. ICC is particularly useful when combined with algorithms that assume that each class has a unimodal Gaussian distribution (e.g., Linear Discriminant Analysis (LDA), quadratic classifiers), an assumption that is not always true in many real-world situations. ICC can help partition non-Gaussian, multimodal distributions to overcome such a problem. In this sense, ICC works as a preprocessor. Experiments with our ICC algorithm on synthetic data sets and real-world data sets indicated that it can significantly improve the performance of LDA and quadratic classifiers. We expect our approach to be applicable to a broader class of pattern recognition problems where class-conditional densities are significantly non-Gaussian or multi-modal. © 2013 Elsevier Ltd. All rights reserved.

  3. Mutation classes of finite type cluster algebras with principal coefficients

    CERN Document Server

    Seven, Ahmet

    2011-01-01

    In this paper, we prove Conjecture 4.8 of "Cluster algebras IV" by S. Fomin and A. Zelevinsky, stating that the mutation classes of rectangular matrices associated with cluster algebras of finite type are precisely those classes which are finite.

  4. Class Restricted Clustering and Micro-Perturbation for Data Privacy

    OpenAIRE

    Li, Xiao-Bai; Sarkar, Sumit

    2013-01-01

    The extensive use of information technologies by organizations to collect and share personal data has raised strong privacy concerns. To respond to the public’s demand for data privacy, a class of clustering-based data masking techniques is increasingly being used for privacy-preserving data sharing and analytics. Traditional clustering-based approaches for masking numeric attributes, while addressing re-identification risks, typically do not consider the disclosure risk of categorical confid...

  5. Arabic web pages clustering and annotation using semantic class features

    Directory of Open Access Journals (Sweden)

    Hanan M. Alghamdi

    2014-12-01

    Full Text Available To effectively manage the great amount of data on Arabic web pages and to enable the classification of relevant information are very important research problems. Studies on sentiment text mining have been very limited in the Arabic language because they need to involve deep semantic processing. Therefore, in this paper, we aim to retrieve machine-understandable data with the help of a Web content mining technique to detect covert knowledge within these data. We propose an approach to achieve clustering with semantic similarities. This approach comprises integrating k-means document clustering with semantic feature extraction and document vectorization to group Arabic web pages according to semantic similarities and then show the semantic annotation. The document vectorization helps to transform text documents into a semantic class probability distribution or semantic class density. To reach semantic similarities, the approach extracts the semantic class features and integrates them into the similarity weighting schema. The quality of the clustering result has evaluated the use of the purity and the mean intra-cluster distance (MICD evaluation measures. We have evaluated the proposed approach on a set of common Arabic news web pages. We have acquired favorable clustering results that are effective in minimizing the MICD, expanding the purity and lowering the runtime.

  6. Filling the gap: a new class of old star cluster?

    CERN Document Server

    Forbes, Duncan; Usher, Christopher; Strader, Jay; Romanowsky, Aaron; Brodie, Jean; Arnold, Jacob; Spitler, Lee

    2013-01-01

    It is not understood whether long-lived star clusters possess a continuous range of sizes and masses (and hence densities), or if rather, they should be considered as distinct types with different origins. Utilizing the Hubble Space Telescope (HST) to measure sizes, and long exposures on the Keck 10m telescope to obtain distances, we have discovered the first confirmed star clusters that lie within a previously claimed size-luminosity gap dubbed the `avoidance zone' by Hwang et al (2011). The existence of these star clusters extends the range of sizes, masses and densities for star clusters, and argues against current formation models that predict well-defined size-mass relationships (such as stripped nuclei, giant globular clusters or merged star clusters). The red colours of these gap objects suggests that they are not a new class of object but are related to Faint Fuzzies observed in nearby lenticular galaxies. We also report a number of low luminosity UCDs with sizes of up to 50 pc. Future, statistically ...

  7. Building pathway clusters from Random Forests classification using class votes

    Directory of Open Access Journals (Sweden)

    Zhao Hongyu

    2008-02-01

    Full Text Available Abstract Background Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest. Results We propose to build pathway clusters from pathway-based classification methods. The proposed methods allow researchers to identify clusters of pathways sharing similar functions. These pathways may or may not share genes. As an illustration, our approach is applied to three human breast cancer microarray data sets. We found that our methods yielded consistent and interpretable results for these three data sets. We further investigated one of the pathway clusters found using PubMatrix. We found that informative genes in the pathway clusters do have more publications with keywords, like estrogen receptor, compared with informative genes in other top pathways. In addition, using the shortest path analysis in GeneGo's MetaCore and Human Protein Reference Database, we were able to identify the links which connect the pathways without shared genes within the pathway cluster. Conclusion Our proposed pathway clustering methods allow bioinformaticians and biologists to investigate how informative genes within pathways are related to each other and understand possible crosstalk between pathways in a cluster. Therefore, building pathway clusters may lead to a better understanding of molecular mechanisms affecting a trait of interest, and help generate further biological hypotheses from gene expression data.

  8. Parallel unstructured AMR and gigabit networking for Beowulf-class clusters

    Science.gov (United States)

    Norton, C. D.; Cwik, T. A.

    2001-01-01

    The impact of gigabit networking with Myrinet 2000 hardware and MPICH-GM software on a 2-way SMP Beowulf-class cluster for parallel unstructured adaptive mesh refinement using the PYRAMID library is described.

  9. Teleportation of an Arbitrary Two-Particle State via a Single Cluster-Class State

    International Nuclear Information System (INIS)

    Teleportation of an arbitrary two-qubit state with a single partially entangled state, a four-qubit linear cluster-class state, is studied. The case is more practical than previous ones using maximally entangled states as the quantum channel. In order to realize teleportation, we first construct a cluster-basis of 16 orthonormal cluster states. We show that quantum teleportation can be successfully implemented with a certain probability if the receiver can adopt appropriate unitary transformations after receiving the sender's cluster-basis measurement information. In addition, an important conclusion can be obtained that a four-qubit maximally entangled state (cluster state) can be extracted from a single copy of the cluster-class state with the same probability as the teleportation in principle. (general)

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

    CERN Document Server

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

    2003-01-01

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

  11. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Directory of Open Access Journals (Sweden)

    Landfors Mattias

    2010-10-01

    Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that

  12. Cyclist–motorist crash patterns in Denmark: A latent class clustering approach

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2013-01-01

    differentiating the latent classes were speed limit, infrastructure type, road surface conditions, number of lanes, motorized vehicle precrash maneuvers, the availability of a cycle lane, cyclist intoxication, and helmet wearing behavior. After the latent class clustering, the distribution of cyclists’ injury......Objective: The current study aimed at uncovering patterns of cyclist–motorist crashes in Denmark and investigating their prevalence and severity. The importance of implementing clustering techniques for providing a holistic overview of vulnerable road users’ crash patterns derives from the need...

  13. Semi-Automatically Inducing Semantic Classes of Clinical Research Eligibility Criteria Using UMLS and Hierarchical Clustering

    OpenAIRE

    Luo, Zhihui; Johnson, Stephen B.; Weng, Chunhua

    2010-01-01

    This paper presents a novel approach to learning semantic classes of clinical research eligibility criteria. It uses the UMLS Semantic Types to represent semantic features and the Hierarchical Clustering method to group similar eligibility criteria. By establishing a gold standard using two independent raters, we evaluated the coverage and accuracy of the induced semantic classes. On 2,718 random eligibility criteria sentences, the inter-rater classification agreement was 85.73%. In a 10-fold...

  14. Fatal and serious road crashes involving young New Zealand drivers: a latent class clustering approach

    DEFF Research Database (Denmark)

    Weiss, Harold B.; Kaplan, Sigal; Prato, Carlo Giacomo

    2015-01-01

    classification that revealed how the identified clusters contain mostly crashes of a particular class and all the crashes of that class. The results raised three major safety concerns for young drivers that should be addressed: (1) reckless driving and traffic law violations; (2) inattention, error, and hazard...... perception problems; and (3) interaction with road geometry and lighting conditions, especially on high-speed open roads and state highways....

  15. The X-CLASS - redMaPPer galaxy cluster comparison: I. Identification procedures

    CERN Document Server

    Sadibekova, Tatyana; Clerc, Nicolas; Faccioli, Lorenzo; Gastaud, Rene; Fevre, Jean-Paul Le; Rozo, Eduardo; Rykoff, Eli S

    2014-01-01

    We performed a detailed and, for a large part interactive, analysis of the matching output between the X-CLASS and redMaPPer cluster catalogues. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters respectively. X-ray cluster matching rates were analysed as a function of optical richness. In a second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10^{-15} erg s^{-1} cm^{-2} in the [0.5-2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Main results show that neither of the wavebands misses any massive cluster (as coded by X-ray luminosity or optical richness). After correcting for obvious pipeline short-comings (about 10% of the cases both in optical and X-ray), ~50% of the redMaPPer (down to a richness of 20) are found to coinc...

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

    Directory of Open Access Journals (Sweden)

    Rita Ismayilova

    2014-01-01

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

  17. Exploring the Relationship between Autism Spectrum Disorder and Epilepsy Using Latent Class Cluster Analysis

    Science.gov (United States)

    Cuccaro, Michael L.; Tuchman, Roberto F.; Hamilton, Kara L.; Wright, Harry H.; Abramson, Ruth K.; Haines, Jonathan L.; Gilbert, John R.; Pericak-Vance, Margaret

    2012-01-01

    Epilepsy co-occurs frequently in autism spectrum disorders (ASD). Understanding this co-occurrence requires a better understanding of the ASD-epilepsy phenotype (or phenotypes). To address this, we conducted latent class cluster analysis (LCCA) on an ASD dataset (N = 577) which included 64 individuals with epilepsy. We identified a 5-cluster…

  18. Semi-Automatically Inducing Semantic Classes of Clinical Research Eligibility Criteria Using UMLS and Hierarchical Clustering.

    Science.gov (United States)

    Luo, Zhihui; Johnson, Stephen B; Weng, Chunhua

    2010-01-01

    This paper presents a novel approach to learning semantic classes of clinical research eligibility criteria. It uses the UMLS Semantic Types to represent semantic features and the Hierarchical Clustering method to group similar eligibility criteria. By establishing a gold standard using two independent raters, we evaluated the coverage and accuracy of the induced semantic classes. On 2,718 random eligibility criteria sentences, the inter-rater classification agreement was 85.73%. In a 10-fold validation test, the average Precision, Recall and F-score of the classification results of a decision-tree classifier were 87.8%, 88.0%, and 87.7% respectively. Our induced classes well aligned with 16 out of 17 eligibility criteria classes defined by the BRIDGE model. We discuss the potential of this method and our future work. PMID:21347026

  19. Structural variation of the ribosomal gene cluster within the class Insecta

    Energy Technology Data Exchange (ETDEWEB)

    Mukha, D.V.; Sidorenko, A.P.; Lazebnaya, I.V. [Vavilov Institute of General Genetics, Moscow (Russian Federation)] [and others

    1995-09-01

    General estimation of ribosomal DNA variation within the class Insecta is presented. It is shown that, using blot-hybridization, one can detect differences in the structure of the ribosomal gene cluster not only between genera within an order, but also between species within a genera, including sibling species. Structure of the ribosomal gene cluster of the Coccinellidae family (ladybirds) is analyzed. It is shown that cloned highly conservative regions of ribosomal DNA of Tetrahymena pyriformis can be used as probes for analyzing ribosomal genes in insects. 24 refs., 4 figs.

  20. Global Clustering Quality Coefficient Assessing the Efficiency of PCA Class Assignment

    Directory of Open Access Journals (Sweden)

    Mirela Praisler

    2014-01-01

    Full Text Available An essential factor influencing the efficiency of the predictive models built with principal component analysis (PCA is the quality of the data clustering revealed by the score plots. The sensitivity and selectivity of the class assignment are strongly influenced by the relative position of the clusters and by their dispersion. We are proposing a set of indicators inspired from analytical geometry that may be used for an objective quantitative assessment of the data clustering quality as well as a global clustering quality coefficient (GCQC that is a measure of the overall predictive power of the PCA models. The use of these indicators for evaluating the efficiency of the PCA class assignment is illustrated by a comparative study performed for the identification of the preprocessing function that is generating the most efficient PCA system screening for amphetamines based on their GC-FTIR spectra. The GCQC ranking of the tested feature weights is explained based on estimated density distributions and validated by using quadratic discriminant analysis (QDA.

  1. A class of spherical, truncated, anisotropic models for application to globular clusters

    Science.gov (United States)

    de Vita, Ruggero; Bertin, Giuseppe; Zocchi, Alice

    2016-05-01

    Recently, a class of non-truncated, radially anisotropic models (the so-called f(ν)-models), originally constructed in the context of violent relaxation and modelling of elliptical galaxies, has been found to possess interesting qualities in relation to observed and simulated globular clusters. In view of new applications to globular clusters, we improve this class of models along two directions. To make them more suitable for the description of small stellar systems hosted by galaxies, we introduce a "tidal" truncation by means of a procedure that guarantees full continuity of the distribution function. The new fT(ν)-models are shown to provide a better fit to the observed photometric and spectroscopic profiles for a sample of 13 globular clusters studied earlier by means of non-truncated models; interestingly, the best-fit models also perform better with respect to the radial-orbit instability. Then, we design a flexible but simple two-component family of truncated models to study the separate issues of mass segregation and multiple populations. We do not aim at a fully realistic description of globular clusters to compete with the description currently obtained by means of dedicated simulations. The goal here is to try to identify the simplest models, that is, those with the smallest number of free parameters, but still have the capacity to provide a reasonable description for clusters that are evidently beyond the reach of one-component models. With this tool, we aim at identifying the key factors that characterize mass segregation or the presence of multiple populations. To reduce the relevant parameter space, we formulate a few physical arguments based on recent observations and simulations. A first application to two well-studied globular clusters is briefly described and discussed.

  2. NGC 6273: Towards Defining A New Class of Galactic Globular Clusters?

    Science.gov (United States)

    Johnson, Christian I.; Rich, Robert Michael; Pilachowski, Catherine A.; Caldwell, Nelson; Mateo, Mario L.; Ira Bailey, John; Crane, Jeffrey D.

    2016-01-01

    A growing number of observations have found that several Galactic globular clusters exhibit abundance dispersions beyond the well-known light element (anti-)correlations. These clusters tend to be very massive, have >0.1 dex intrinsic metallicity dispersions, have complex sub-giant branch morphologies, and have correlated [Fe/H] and s-process element enhancements. Interestingly, nearly all of these clusters discovered so far have [Fe/H]~-1.7. In this context, we have examined the chemical composition of 18 red giant branch (RGB) stars in the massive, metal-poor Galactic bulge globular cluster NGC 6273 using high signal-to-noise, high resolution (R~27,000) spectra obtained with the Michigan/Magellan Fiber System (M2FS) and MSpec spectrograph mounted on the Magellan-Clay 6.5m telescope at Las Campanas Observatory. We find that the cluster exhibits a metallicity range from [Fe/H]=-1.80 to -1.30 and is composed of two dominant populations separated in [Fe/H] and [La/Fe] abundance. The increase in [La/Eu] as a function of [La/H] suggests that the increase in [La/Fe] with [Fe/H] is due to almost pure s-process enrichment. The most metal-rich star in our sample is not strongly La-enhanced, but is α-poor and may belong to a third "anomalous" stellar population. The two dominant populations exhibit the same [Na/Fe]-[Al/Fe] correlation found in other "normal" globular clusters. Therefore, NGC 6273 joins ω Centauri, M 22, M 2, and NGC 5286 as a possible new class of Galactic globular clusters.

  3. Incremental multi-class semi-supervised clustering regularized by Kalman filtering.

    Science.gov (United States)

    Mehrkanoon, Siamak; Agudelo, Oscar Mauricio; Suykens, Johan A K

    2015-11-01

    This paper introduces an on-line semi-supervised learning algorithm formulated as a regularized kernel spectral clustering (KSC) approach. We consider the case where new data arrive sequentially but only a small fraction of it is labeled. The available labeled data act as prototypes and help to improve the performance of the algorithm to estimate the labels of the unlabeled data points. We adopt a recently proposed multi-class semi-supervised KSC based algorithm (MSS-KSC) and make it applicable for on-line data clustering. Given a few user-labeled data points the initial model is learned and then the class membership of the remaining data points in the current and subsequent time instants are estimated and propagated in an on-line fashion. The update of the memberships is carried out mainly using the out-of-sample extension property of the model. Initially the algorithm is tested on computer-generated data sets, then we show that video segmentation can be cast as a semi-supervised learning problem. Furthermore we show how the tracking capabilities of the Kalman filter can be used to provide the labels of objects in motion and thus regularizing the solution obtained by the MSS-KSC algorithm. In the experiments, we demonstrate the performance of the proposed method on synthetic data sets and real-life videos where the clusters evolve in a smooth fashion over time.

  4. Incremental multi-class semi-supervised clustering regularized by Kalman filtering.

    Science.gov (United States)

    Mehrkanoon, Siamak; Agudelo, Oscar Mauricio; Suykens, Johan A K

    2015-11-01

    This paper introduces an on-line semi-supervised learning algorithm formulated as a regularized kernel spectral clustering (KSC) approach. We consider the case where new data arrive sequentially but only a small fraction of it is labeled. The available labeled data act as prototypes and help to improve the performance of the algorithm to estimate the labels of the unlabeled data points. We adopt a recently proposed multi-class semi-supervised KSC based algorithm (MSS-KSC) and make it applicable for on-line data clustering. Given a few user-labeled data points the initial model is learned and then the class membership of the remaining data points in the current and subsequent time instants are estimated and propagated in an on-line fashion. The update of the memberships is carried out mainly using the out-of-sample extension property of the model. Initially the algorithm is tested on computer-generated data sets, then we show that video segmentation can be cast as a semi-supervised learning problem. Furthermore we show how the tracking capabilities of the Kalman filter can be used to provide the labels of objects in motion and thus regularizing the solution obtained by the MSS-KSC algorithm. In the experiments, we demonstrate the performance of the proposed method on synthetic data sets and real-life videos where the clusters evolve in a smooth fashion over time. PMID:26319050

  5. Inferring noncoding RNA families and classes by means of genome-scale structure-based clustering.

    Directory of Open Access Journals (Sweden)

    Sebastian Will

    2007-04-01

    Full Text Available The RFAM database defines families of ncRNAs by means of sequence similarities that are sufficient to establish homology. In some cases, such as microRNAs and box H/ACA snoRNAs, functional commonalities define classes of RNAs that are characterized by structural similarities, and typically consist of multiple RNA families. Recent advances in high-throughput transcriptomics and comparative genomics have produced very large sets of putative noncoding RNAs and regulatory RNA signals. For many of them, evidence for stabilizing selection acting on their secondary structures has been derived, and at least approximate models of their structures have been computed. The overwhelming majority of these hypothetical RNAs cannot be assigned to established families or classes. We present here a structure-based clustering approach that is capable of extracting putative RNA classes from genome-wide surveys for structured RNAs. The LocARNA (local alignment of RNA tool implements a novel variant of the Sankoff algorithm that is sufficiently fast to deal with several thousand candidate sequences. The method is also robust against false positive predictions, i.e., a contamination of the input data with unstructured or nonconserved sequences. We have successfully tested the LocARNA-based clustering approach on the sequences of the RFAM-seed alignments. Furthermore, we have applied it to a previously published set of 3,332 predicted structured elements in the Ciona intestinalis genome (Missal K, Rose D, Stadler PF (2005 Noncoding RNAs in Ciona intestinalis. Bioinformatics 21 (Supplement 2: i77-i78. In addition to recovering, e.g., tRNAs as a structure-based class, the method identifies several RNA families, including microRNA and snoRNA candidates, and suggests several novel classes of ncRNAs for which to date no representative has been experimentally characterized.

  6. Clustering Educational Digital Library Usage Data: A Comparison of Latent Class Analysis and K-Means Algorithms

    Science.gov (United States)

    Xu, Beijie; Recker, Mimi; Qi, Xiaojun; Flann, Nicholas; Ye, Lei

    2013-01-01

    This article examines clustering as an educational data mining method. In particular, two clustering algorithms, the widely used K-means and the model-based Latent Class Analysis, are compared, using usage data from an educational digital library service, the Instructional Architect (IA.usu.edu). Using a multi-faceted approach and multiple data…

  7. Unsupervised Anomaly Detection Based on Clustering and Multiple One-Class SVM

    Science.gov (United States)

    Song, Jungsuk; Takakura, Hiroki; Okabe, Yasuo; Kwon, Yongjin

    Intrusion detection system (IDS) has played an important role as a device to defend our networks from cyber attacks. However, since it is unable to detect unknown attacks, i.e., 0-day attacks, the ultimate challenge in intrusion detection field is how we can exactly identify such an attack by an automated manner. Over the past few years, several studies on solving these problems have been made on anomaly detection using unsupervised learning techniques such as clustering, one-class support vector machine (SVM), etc. Although they enable one to construct intrusion detection models at low cost and effort, and have capability to detect unforeseen attacks, they still have mainly two problems in intrusion detection: a low detection rate and a high false positive rate. In this paper, we propose a new anomaly detection method based on clustering and multiple one-class SVM in order to improve the detection rate while maintaining a low false positive rate. We evaluated our method using KDD Cup 1999 data set. Evaluation results show that our approach outperforms the existing algorithms reported in the literature; especially in detection of unknown attacks.

  8. A conserved cluster of three PRD-class homeobox genes (homeobrain, rx and orthopedia in the Cnidaria and Protostomia

    Directory of Open Access Journals (Sweden)

    Mazza Maureen E

    2010-07-01

    Full Text Available Abstract Background Homeobox genes are a superclass of transcription factors with diverse developmental regulatory functions, which are found in plants, fungi and animals. In animals, several Antennapedia (ANTP-class homeobox genes reside in extremely ancient gene clusters (for example, the Hox, ParaHox, and NKL clusters and the evolution of these clusters has been implicated in the morphological diversification of animal bodyplans. By contrast, similarly ancient gene clusters have not been reported among the other classes of homeobox genes (that is, the LIM, POU, PRD and SIX classes. Results Using a combination of in silico queries and phylogenetic analyses, we found that a cluster of three PRD-class homeobox genes (Homeobrain (hbn, Rax (rx and Orthopedia (otp is present in cnidarians, insects and mollusks (a partial cluster comprising hbn and rx is present in the placozoan Trichoplax adhaerens. We failed to identify this 'HRO' cluster in deuterostomes; in fact, the Homeobrain gene appears to be missing from the chordate genomes we examined, although it is present in hemichordates and echinoderms. To illuminate the ancestral organization and function of this ancient cluster, we mapped the constituent genes against the assembled genome of a model cnidarian, the sea anemone Nematostella vectensis, and characterized their spatiotemporal expression using in situ hybridization. In N. vectensis, these genes reside in a span of 33 kb with the same gene order as previously reported in insects. Comparisons of genomic sequences and expressed sequence tags revealed the presence of alternative transcripts of Nv-otp and two highly unusual protein-coding polymorphisms in the terminal helix of the Nv-rx homeodomain. A population genetic survey revealed the Rx polymorphisms to be widespread in natural populations. During larval development, all three genes are expressed in the ectoderm, in non-overlapping territories along the oral-aboral axis, with distinct

  9. Cluster exponential synchronization of a class of complex networks with hybrid coupling and time-varying delay

    International Nuclear Information System (INIS)

    This paper deals with the cluster exponential synchronization of a class of complex networks with hybrid coupling and time-varying delay. Through constructing an appropriate Lyapunov—Krasovskii functional and applying the theory of the Kronecker product of matrices and the linear matrix inequality (LMI) technique, several novel sufficient conditions for cluster exponential synchronization are obtained. These cluster exponential synchronization conditions adopt the bounds of both time delay and its derivative, which are less conservative. Finally, the numerical simulations are performed to show the effectiveness of the theoretical results. (general)

  10. Impacts of fast food and food retail environment on overweight and obesity in China: a multilevel latent class cluster approach

    NARCIS (Netherlands)

    Zhang XiaoYong, Xiaoyong; Lans, van der I.A.; Dagevos, H.

    2012-01-01

    Objective To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. Design A multilevel latent class cluster model was applied to

  11. Identifying victims of workplace bullying by integrating traditional estimation approaches into a latent class cluster model.

    Science.gov (United States)

    Leon-Perez, Jose M; Notelaers, Guy; Arenas, Alicia; Munduate, Lourdes; Medina, Francisco J

    2014-05-01

    Research findings underline the negative effects of exposure to bullying behaviors and document the detrimental health effects of being a victim of workplace bullying. While no one disputes its negative consequences, debate continues about the magnitude of this phenomenon since very different prevalence rates of workplace bullying have been reported. Methodological aspects may explain these findings. Our contribution to this debate integrates behavioral and self-labeling estimation methods of workplace bullying into a measurement model that constitutes a bullying typology. Results in the present sample (n = 1,619) revealed that six different groups can be distinguished according to the nature and intensity of reported bullying behaviors. These clusters portray different paths for the workplace bullying process, where negative work-related and person-degrading behaviors are strongly intertwined. The analysis of the external validity showed that integrating previous estimation methods into a single measurement latent class model provides a reliable estimation method of workplace bullying, which may overcome previous flaws. PMID:24257593

  12. Human HLA class I- and HLA class II-restricted cloned cytotoxic T lymphocytes identify a cluster of epitopes on the measles virus fusion protein.

    Science.gov (United States)

    van Binnendijk, R S; Versteeg-van Oosten, J P; Poelen, M C; Brugghe, H F; Hoogerhout, P; Osterhaus, A D; Uytdehaag, F G

    1993-01-01

    The transmembrane fusion (F) glycoprotein of measles virus is an important target antigen of human HLA class I- and class II-restricted cytotoxic T lymphocytes (CTL). Genetically engineered F proteins and nested sets of synthetic peptides spanning the F protein were used to determine sequences of F recognized by a number of F-specific CTL clones. Combined N- and C-terminal deletions of the respective peptides revealed that human HLA class I and HLA class II-restricted CTL efficiently recognize nonapeptides or decapeptides representing epitopes of F. Three distinct sequences recognized by three different HLA class II (DQw1, DR2, and DR4/w53)-restricted CTL clones appear to cluster between amino acids 379 and 466 of F, thus defining an important T-cell epitope area of F. Within this same region, a nonamer peptide of F was found to be recognized by an HLA-B27-restricted CTL clone, as expected on the basis of the structural homology between this peptide and other known HLA-B27 binding peptides. PMID:7680390

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

    Directory of Open Access Journals (Sweden)

    Jarman Andrew P

    2010-12-01

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

  14. Impacts of fast food and food retail environment on overweight and obesity in China: a multilevel latent class cluster approach

    OpenAIRE

    Zhang XiaoYong, Xiaoyong; Lans, van der, A.M.; Dagevos, H.

    2012-01-01

    Objective To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. Design A multilevel latent class cluster model was applied to identify consumer segments based not only on their individual preferences for fast food, salty snack foods, and soft drinks and sugared fruit drinks, but also on the food retail environment at the ...

  15. Genomic sequence analysis of the 238-kb swine segment with a cluster of TRIM and olfactory receptor genes located, but with no class I genes, at the distal end of the SLA class I region.

    Science.gov (United States)

    Ando, Asako; Shigenari, Atsuko; Kulski, Jerzy K; Renard, Christine; Chardon, Patrick; Shiina, Takashi; Inoko, Hidetoshi

    2005-12-01

    Continuous genomic sequence has been previously determined for the swine leukocyte antigen (SLA) class I region from the TNF gene cluster at the border between the major histocompatibility complex (MHC) class III and class I regions to the UBD gene at the telomeric end of the classical class I gene cluster (SLA-1 to SLA-5, SLA-9, SLA-11). To complete the genomic sequence of the entire SLA class I genomic region, we have analyzed the genomic sequences of two BAC clones carrying a continuous 237,633-bp-long segment spanning from the TRIM15 gene to the UBD gene located on the telomeric side of the classical SLA class I gene cluster. Fifteen non-class I genes, including the zinc finger and the tripartite motif (TRIM) ring-finger-related family genes and olfactory receptor genes, were identified in the 238-kilobase (kb) segment, and their location in the segment was similar to their apparent human homologs. In contrast, a human segment (alpha block) spanning about 375 kb from the gene ETF1P1 and from the HLA-J to HLA-F genes was absent from the 238-kb swine segment. We conclude that the gene organization of the MHC non-class I genes located in the telomeric side of the classical SLA class I gene cluster is remarkably similar between the swine and the human segments, although the swine lacks a 375-kb segment corresponding to the human alpha block.

  16. PARTIAL TRAINING METHOD FOR HEURISTIC ALGORITHM OF POSSIBLE CLUSTERIZATION UNDER UNKNOWN NUMBER OF CLASSES

    Directory of Open Access Journals (Sweden)

    D. A. Viattchenin

    2009-01-01

    Full Text Available A method for constructing a subset of labeled objects which is used in a heuristic algorithm of possible  clusterization with partial  training is proposed in the  paper.  The  method  is  based  on  data preprocessing by the heuristic algorithm of possible clusterization using a transitive closure of a fuzzy tolerance. Method efficiency is demonstrated by way of an illustrative example.

  17. Clustering

    Directory of Open Access Journals (Sweden)

    Jinfei Liu

    2013-04-01

    Full Text Available DBSCAN is a well-known density-based clustering algorithm which offers advantages for finding clusters of arbitrary shapes compared to partitioning and hierarchical clustering methods. However, there are few papers studying the DBSCAN algorithm under the privacy preserving distributed data mining model, in which the data is distributed between two or more parties, and the parties cooperate to obtain the clustering results without revealing the data at the individual parties. In this paper, we address the problem of two-party privacy preserving DBSCAN clustering. We first propose two protocols for privacy preserving DBSCAN clustering over horizontally and vertically partitioned data respectively and then extend them to arbitrarily partitioned data. We also provide performance analysis and privacy proof of our solution..

  18. A Mid-Infrared Study of the Class 0 Cluster in LDN 1448

    CERN Document Server

    O'Linger, J A; Ressler, M E; Wolf-Chase, G A

    2005-01-01

    We present ground-based mid-infrared observations of Class 0 protostars in LDN 1448. Of the five known protostars in this cloud, we detected two, L1448N:A and L1448C, at 12.5, 17.9, 20.8, and 24.5 microns, and a third, L1448 IRS 2, at 24.5 microns. We present high-resolution images of the detected sources, and photometry or upper limits for all five Class 0 sources in this cloud. With these data, we are able to augment existing spectral energy distributions (SEDs) for all five objects and place them on an evolutionary status diagram.

  19. Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering

    Directory of Open Access Journals (Sweden)

    Suraj

    2015-01-01

    Full Text Available Transferring the brain computer interface (BCI from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG signal reasons us to look toward evolutionary algorithm (EA. Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA and particle swarm optimization (PSO based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD and desynchronization (ERD feature vector is formed.

  20. Semi Supervised Weighted K-Means Clustering for Multi Class Data Classification

    Directory of Open Access Journals (Sweden)

    Vijaya Geeta Dharmavaram

    2013-01-01

    Full Text Available Supervised Learning techniques require large number of labeled examples to train a classifier model. Research on Semi Supervised Learning is motivated by the availability of unlabeled examples in abundance even in domains with limited number of labeled examples. In such domains semi supervised classifier uses the results of clustering for classifier development since clustering does not rely only on labeled examples as it groups the objects based on their similarities. In this paper, the authors propose a new algorithm for semi supervised classification namely Semi Supervised Weighted K-Means (SSWKM. In this algorithm, the authors suggest the usage of weighted Euclidean distance metric designed as per the purpose of clustering for estimating the proximity between a pair of points and used it for building semi supervised classifier. The authors propose a new approach for estimating the weights of features by appropriately adopting the results of multiple discriminant analysis. The proposed method was then tested on benchmark datasets from UCI repository with varied percentage of labeled examples and found to be consistent and promising.

  1. Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes

    KAUST Repository

    Cannistraci, Carlo

    2010-09-01

    Motivation: Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. Methods: \\'Minimum Curvilinearity\\' (MC) is a principle that-for small datasets-suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Results: Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. Conclusion: MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. © The Author(s) 2010. Published by Oxford University Press.

  2. Interaction of Fanaroff-Riley class II radio jets with a randomly magnetised intra-cluster medium

    CERN Document Server

    Huarte-Espinosa, Martín; Alexander, Paul

    2011-01-01

    A combination of three-dimensional (3D) magnetohydrodynamics (MHD) and synthetic numerical simulations are presented to follow the evolution of a randomly magnetised plasma that models the intra-cluster medium (ICM), under the isolated effects of powerful, light, hypersonic and bipolar Fanaroff-Riley class II (FR II) jets. We prescribe the cluster magnetic field (CMF) as a Gaussian random field with a Kolmogorov-like energy spectrum. Both the power of the jets and the viewing angle that is used for the synthetic Rotation Measure (RM) observations are investigated. We find the model radio sources introduce and amplify fluctuations on the RM statistical properties which we analyse as a function of time as well as the viewing angle. The average RM and the RM standard deviation are increased by the action of the jets. Energetics, RM statistics and magnetic power spectral analysis consistently show that the effects also correlate with the jets' power, and that the lightest, fastest jets produce the strongest chang...

  3. Stellar variability in open clusters. I. A new class of variable stars in NGC 3766

    CERN Document Server

    Mowlavi, N; Saesen, S; Eyer, L

    2013-01-01

    Aims. We analyze the population of periodic variable stars in the open cluster NGC 3766 based on a 7-year multi-band monitoring campaign conducted on the 1.2 m Swiss Euler telescope at La Silla, Chili. Methods. The data reduction, light curve cleaning and period search procedures, combined with the long observation time line, allow us to detect variability amplitudes down to the milli-magnitude level. The variability properties are complemented with the positions in the color-magnitude and color-color diagrams to classify periodic variable stars into distinct variability types. Results. We find a large population (36 stars) of new variable stars between the red edge of slowly pulsating B (SPB) stars and the blue edge of delta Sct stars, a region in the Hertzsprung-Russell (HR) diagram where no pulsation is predicted to occur based on standard stellar models. The bulk of their periods ranges from 0.1 to 0.7 d, with amplitudes between 1 and 4 mmag for the majority of them. About 20% of stars in that region of t...

  4. Differences in the expressed HLA class I alleles effect the differential clustering of HIV type 1-specific T cell responses in infected Chinese and Caucasians

    Institute of Scientific and Technical Information of China (English)

    Yu,XG; Addo,MM; Perkins,BA; Wej,FL; Rathod,A; Geer,SC; Parta,M; Cohen,D; Stone,DR; Russell,CJ; Tanzi,G; Mei,S; Wureel,AG; Frahm,N; Lichterfeld,M; Heath,L; Mullins,JI; Marincola,F; Goulder,PJR; Brander,C; Allen,T; Cao,YZ; Walker,BD; Altfeld,M

    2005-01-01

    China is a region of the world with a rapidly spreading HIV-1 epidemic. Studies providing insights into HIV-1 pathogenesis in infected Chinese are urgently needed to support the design and testing of an effective HIV-1 vaccine for this population. HIV-1-specific T cell responses were characterized in 32 HIV-1-infected individuals of Chinese origin and compared to 34 infected caucasians using 410 overlapping peptides spanning the entire HIV-1 clade B consensus sequence in an IFN-gamma ELISpot assay. All HIV-1 proteins were targeted with similar frequency in both populations and all study subjects recognized at least one overlapping peptide. HIV-1-specific T cell responses clustered in seven different regions of the HIV-1 genome in the Chinese cohort and in nine different regions in the caucasian cohort. The dominant HLA class I alleles expressed in the two populations differed significantly, and differences in epitope clustering pattern were shown to be influenced by differences in class I alleles that restrict immunodominant epitopes. These studies demonstrate that the clustering of HIV-1-specific T cell responses is influenced by the genetic HLA class I background in the study populations. The design and testing of candidate vaccines to fight the rapidly growing HIV-1 epidemic must therefore take the HLA genetics of the population into account as specific regions of the virus can be expected to be differentially targeted in ethnically diverse populations.

  5. Stellar variability in open clusters. II. Discovery of a new period-luminosity relation in a class of fast-rotating pulsating stars in NGC 3766

    CERN Document Server

    Mowlavi, N; Semaan, T; Eggenberger, P; Barblan, F; Eyer, L; Ekström, S; Georgy, C

    2016-01-01

    $Context.$ Pulsating stars are windows to the physics of stars enabling us to see glimpses of their interior. Not all stars pulsate, however. On the main sequence, pulsating stars form an almost continuous sequence in brightness, except for a magnitude range between $\\delta$ Scuti and slowly pulsating B stars. Against all expectations, 36 periodic variables were discovered in 2013 in this luminosity range in the open cluster NGC 3766, the origins of which was a mystery. $Aims.$ We investigate the properties of those new variability class candidates in relation to their stellar rotation rates and stellar multiplicity. $Methods.$ We took multi-epoch spectra over three consecutive nights using ESO's Very Large Telescope. $Results.$ We find that the majority of the new variability class candidates are fast-rotating pulsators that obey a new period-luminosity relation. We argue that the new relation discovered here has a different physical origin to the period-luminosity relations observed for Cepheids. $Conclusio...

  6. Can galaxy clusters, type Ia supernovae and cosmic microwave background ruled out a class of modified gravity theories?

    CERN Document Server

    Holanda, R F L

    2016-01-01

    In this paper we study cosmological signatures of modified gravity theories that can be written as a coupling between a extra scalar field and the electromagnetic part of the usual Lagrangian for the matter fields. In these frameworks all the electromagnetic sector of the theory is affected and variations of fundamental constants, of the cosmic distance duality relation and of the evolution law of the cosmic microwave background radiation (CMB) are expected and are related each other. In order to search these variations we perform jointly analyses with angular diameter distances of galaxy clusters, luminosity distances of type Ia supernovae and $T_{CMB}(z)$ measurements. We obtain tight constraints with no indication of violation of the standard framework.

  7. Stellar variability in open clusters . II. Discovery of a new period-luminosity relation in a class of fast-rotating pulsating stars in NGC 3766

    Science.gov (United States)

    Mowlavi, N.; Saesen, S.; Semaan, T.; Eggenberger, P.; Barblan, F.; Eyer, L.; Ekström, S.; Georgy, C.

    2016-10-01

    Context. Pulsating stars are windows to the physics of stars enabling us to see glimpses of their interior. Not all stars pulsate, however. On the main sequence, pulsating stars form an almost continuous sequence in brightness, except for a magnitude range between δ Scuti and slowly pulsating B stars. Against all expectations, 36 periodic variables were discovered in 2013 in this luminosity range in the open cluster NGC 3766, the origins of which was a mystery. Aims: We investigate the properties of those new variability class candidates in relation to their stellar rotation rates and stellar multiplicity. Methods: We took multi-epoch spectra over three consecutive nights using ESO's Very Large Telescope. Results: We find that the majority of the new variability class candidates are fast-rotating pulsators that obey a new period-luminosity relation. We argue that the new relation discovered here has a different physical origin to the period-luminosity relations observed for Cepheids. Conclusions: We anticipate that our discovery will boost the relatively new field of stellar pulsation in fast-rotating stars, will open new doors for asteroseismology, and will potentially offer a new tool to estimate stellar ages or cosmic distances. Based on observations made with the FLAMES instruments on the VLT/UT2 telescope at the Paranal Observatory, Chile, under the program ID 69.A-0123(A).

  8. A cluster randomized-controlled trial of a classroom-based drama workshop program to improve mental health outcomes among immigrant and refugee youth in special classes.

    Directory of Open Access Journals (Sweden)

    Cécile Rousseau

    Full Text Available The aim of this cluster randomized trial was to evaluate the effectiveness of a school-based theatre intervention program for immigrant and refugee youth in special classes for improving mental health and academic outcomes. The primary hypothesis was that students in the theatre intervention group would report a greater reduction in impairment from symptoms compared to students in the control and tutoring groups.Special classrooms in five multiethnic high schools were randomly assigned to theater intervention (n = 10, tutoring (n = 10 or control status (n = 9, for a total of 477 participants. Students and teachers were non-blinded to group assignment. The primary outcome was impairment from emotional and behavioural symptoms assessed by the Impact Supplement of the Strengths and Difficulties Questionnaire (SDQ completed by the adolescents. The secondary outcomes were the SDQ global scores (teacher and youth reports, impairment assessed by teachers and school performance. The effect of the interventions was assessed through linear mixed effect models which incorporate the correlation between students in the same class, due to the nature of the randomization of the interventions by classroom.The theatre intervention was not associated with a greater reduction in self-reported impairment and symptoms in youth placed in special class because of learning, emotional and behavioural difficulties than a tutoring intervention or a non-active control group. The estimates of the different models show a non-significant decrease in both self-reported and impairment scores in the theatre intervention group for the overall group, but the impairment score decreased significantly for first generation adolescents while it increased for second generation adolescents.The difference between the population of immigrant and refugee youth newcomers studied previously and the sample of this trial may explain some of the differences in the observed impact of

  9. Meaningful Effect Sizes, Intra-Class Correlations, and Proportions of Variance Explained by Covariates for Planning 3 Level Cluster Randomized Experiments in Prevention Science

    Science.gov (United States)

    Dong, Nianbo; Reinke, Wendy M.; Herman, Keith C.; Bradshaw, Catherine P.; Murray, Desiree W.

    2015-01-01

    Cluster randomized experiments are now widely used to examine intervention effects in prevention science. It is meaningful to use empirical benchmarks for interpreting effect size in prevention science. The effect size (i.e., the standardized mean difference, calculated by the difference of the means between the treatment and control groups,…

  10. Deep observations of the Super-CLASS super-cluster at 325 MHz with the GMRT: the low-frequency source catalogue

    CERN Document Server

    Riseley, C J; Hales, C A; Harrison, I; Birkinshaw, M; Battye, R A; Beswick, R J; Brown, M L; Casey, C M; Chapman, S C; Demetroullas, C; Hung, C -L; Jackson, N J; Muxlow, T; Watson, B

    2016-01-01

    We present the results of 325 MHz GMRT observations of a super-cluster field, known to contain five Abell clusters at redshift $z \\sim 0.2$. We achieve a nominal sensitivity of $34\\,\\mu$Jy beam$^{-1}$ toward the phase centre. We compile a catalogue of 3257 sources with flux densities in the range $183\\,\\mu\\rm{Jy}\\,-\\,1.5\\,\\rm{Jy}$ within the entire $\\sim 6.5$ square degree field of view. Subsequently, we use available survey data at other frequencies to derive the spectral index distribution for a sub-sample of these sources, recovering two distinct populations -- a dominant population which exhibit spectral index trends typical of steep-spectrum synchrotron emission, and a smaller population of sources with typically flat or rising spectra. We identify a number of sources with ultra-steep spectra or rising spectra for further analysis, finding two candidate high-redshift radio galaxies and three gigahertz-peaked-spectrum radio sources. Finally, we derive the Euclidean-normalised differential source counts us...

  11. A vision for growing a world-class power technology cluster in a smart, sustainable British Columbia : full report to the Premier's Technology Council

    International Nuclear Information System (INIS)

    This report presents a framework for power technology in British Columbia and the development of new sources of energy while ensuring the sustainable economic growth. It also explores the opportunities present in the power technology sector. A definition of the power technology industry was provided, and market drivers were identified, describing the region's competitive advantage and assets. Five market opportunities were introduced, comprising the report's targeted innovation strategy: remote power solutions; sustainable urban practices; smart transport; smart grid; and large scale clean green power production. An outline of the current energy market in British Columbia was presented with details of research and development in renewable energy sources. Global power demands were also outlined. A regional action plan was presented in order to develop the power technology cluster. Leadership strategies were presented, with economic development goals and working teams geared towards an implementation resource plan. A commercialization strategy was suggested in order to address local demand, commercialization funds, and increasing access and resources. A growth strategy was also presented to assist in the development of access to world markets, create partnerships and assist in branding and collaborations with industry and government. An innovation strategy was outlined, with the aim of developing research initiatives, support centres in key market and technology areas and connecting existing efforts in basic sciences to power technology applications. It was concluded that in order to achieve full implementation of these strategies, a short term task force is necessary to shape overall plans. Additionally, an ongoing vision team, working groups and coordination is necessary to implement overall strategies and subcomponents. Appendices were included with reference to each of the five market opportunities presented in the report. 58 refs

  12. Projection effects in cluster catalogues

    CERN Document Server

    Van Haarlem, M P; White, S D M

    1997-01-01

    We investigate the importance of projection effects in the identification of galaxy clusters in 2D galaxy maps and their effect on the estimation of cluster velocity dispersions. A volume limited galaxy catalogue that was derived from a Standard CDM N-body simulation was used. We select clusters using criteria that match those employed in the construction of real cluster catalogues and find that our mock Abell cluster catalogues are heavily contaminated and incomplete. Over one third (34 per cent) of clusters of richness class R>=1 are miclassifications arising from the projection of one or more clumps onto an intrinsically poor cluster. Conversely, 32 per cent of intrinsically rich clusters are missed from the R>=1 catalogues, mostly because of statistical fluctuations in the background count. Selection by X-ray luminosity rather than optical richness reduces, but does not completely eliminate, these problems. Contamination by unvirialised sub-clumps near a cluster leads to a considerable overestimation of t...

  13. 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...

  14. Learning regularized LDA by clustering.

    Science.gov (United States)

    Pang, Yanwei; Wang, Shuang; Yuan, Yuan

    2014-12-01

    As a supervised dimensionality reduction technique, linear discriminant analysis has a serious overfitting problem when the number of training samples per class is small. The main reason is that the between- and within-class scatter matrices computed from the limited number of training samples deviate greatly from the underlying ones. To overcome the problem without increasing the number of training samples, we propose making use of the structure of the given training data to regularize the between- and within-class scatter matrices by between- and within-cluster scatter matrices, respectively, and simultaneously. The within- and between-cluster matrices are computed from unsupervised clustered data. The within-cluster scatter matrix contributes to encoding the possible variations in intraclasses and the between-cluster scatter matrix is useful for separating extra classes. The contributions are inversely proportional to the number of training samples per class. The advantages of the proposed method become more remarkable as the number of training samples per class decreases. Experimental results on the AR and Feret face databases demonstrate the effectiveness of the proposed method.

  15. Yellow supergiants in open clusters

    International Nuclear Information System (INIS)

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

  16. Isotopic clusters

    International Nuclear Information System (INIS)

    Spectra of isotopically mixed clusters (dimers of SF6) are calculated as well as transition frequencies. The result leads to speculations about the suitability of the laser-cluster fragmentation process for isotope separation. (Auth.)

  17. Organizing MHC Class II Presentation

    Directory of Open Access Journals (Sweden)

    David R Fooksman

    2014-04-01

    Full Text Available Major histocompatibility complex (MHC class II molecules are ligands for CD4+ T cells and are critical for initiating the adaptive immune response. This review is focused on what is currently known about MHC class II organization at the plasma membrane of antigen presenting cells and how this affects antigen presentation to T cells. The organization and diffusion of class II molecules have been measured by a variety of biochemical and microscopic techniques. Membrane lipids and other proteins have been implicated in MHC class II organization and function. However, when compared with the organization of MHC class I or TCR complexes, much less is known about MHC class II. Since clustering of T cell receptors occurs during activation, the organization of MHC molecules prior to recognition and during synapse formation may be critical for antigen presentation.

  18. Meaningful Clusters

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-05-26

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

  19. Graph partitioning advance clustering technique

    CERN Document Server

    Madhulatha, T Soni

    2012-01-01

    Clustering is a common technique for statistical data analysis, Clustering is the process of grouping the data into classes or clusters so that objects within a cluster have high similarity in comparison to one another, but are very dissimilar to objects in other clusters. Dissimilarities are assessed based on the attribute values describing the objects. Often, distance measures are used. Clustering is an unsupervised learning technique, where interesting patterns and structures can be found directly from very large data sets with little or none of the background knowledge. This paper also considers the partitioning of m-dimensional lattice graphs using Fiedler's approach, which requires the determination of the eigenvector belonging to the second smallest Eigenvalue of the Laplacian with K-means partitioning algorithm.

  20. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

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

  1. Cluster Chemistry

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    @@ Cansisting of eight scientists from the State Key Laboratory of Physical Chemistry of Solid Surfaces and Xiamen University, this creative research group is devoted to the research of cluster chemistry and creation of nanomaterials.After three-year hard work, the group scored a series of encouraging progresses in synthesis of clusters with special structures, including novel fullerenes, fullerene-like metal cluster compounds as well as other related nanomaterials, and their properties study.

  2. Finite mutation classes of coloured quivers

    CERN Document Server

    Torkildsen, Hermund André

    2010-01-01

    We consider the general notion of coloured quiver mutation and show that the mutation class of a coloured quiver $Q$, arising from an $m$-cluster tilting object associated with $H$, is finite if and only if $H$ is of finite or tame representation type, or it has at most 2 simples. This generalizes a result known for 1-cluster categories.

  3. Clustering by Pattern Similarity

    Institute of Scientific and Technical Information of China (English)

    Hai-xun Wang; Jian Pei

    2008-01-01

    The task of clustering is to identify classes of similar objects among a set of objects. The definition of similarity varies from one clustering model to another. However, in most of these models the concept of similarity is often based on such metrics as Manhattan distance, Euclidean distance or other Lp distances. In other words, similar objects must have close values in at least a set of dimensions. In this paper, we explore a more general type of similarity. Under the pCluster model we proposed, two objects are similar if they exhibit a coherent pattern on a subset of dimensions. The new similarity concept models a wide range of applications. For instance, in DNA microarray analysis, the expression levels of two genes may rise and fall synchronously in response to a set of environmental stimuli. Although the magnitude of their expression levels may not be close, the patterns they exhibit can be very much alike. Discovery of such clusters of genes is essential in revealing significant connections in gene regulatory networks. E-commerce applications, such as collaborative filtering, can also benefit from the new model, because it is able to capture not only the closeness of values of certain leading indicators but also the closeness of (purchasing, browsing, etc.) patterns exhibited by the customers. In addition to the novel similarity model, this paper also introduces an effective and efficient algorithm to detect such clusters, and we perform tests on several real and synthetic data sets to show its performance.

  4. Fuzzy Clustering

    DEFF Research Database (Denmark)

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

    2000-01-01

    -mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  5. My Class

    Institute of Scientific and Technical Information of China (English)

    赵传怡

    2006-01-01

    My name is Zhao Chuanyi.I am in Class Ten Grade seven.There are 61 students in our class.And 26 are girls and 35 are boys.One is from America.Boys like football and basketball.Girls like singing and dancing.We are all

  6. Word classes

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    2007-01-01

    a parts-of-speech system that includes the categories Verb, Noun, Adjective and Adverb, other languages may use only a subset of these four lexical categories. Furthermore, quite a few languages have a major word class whose members cannot be classified in terms of the categories Verb – Noun – Adjective...

  7. COMPARISON OF PURITY AND ENTROPY OF K-MEANS CLUSTERING AND FUZZY C MEANS CLUSTERING

    Directory of Open Access Journals (Sweden)

    Satya Chaitanya Sripada

    2011-06-01

    Full Text Available Clustering is one the main area in data mining literature. There are various algorithms for clustering. The evaluation of the performance isdone by validation measures. The external validation measures are used to measure the extent to which cluster labels affirm with theexternally given class labels. The aim of this paper is to compare the for K-means and Fuzzy C means clustering using the Purity andEntropy. The data used for evaluating the external measures is medical data.

  8. Class size versus class composition

    DEFF Research Database (Denmark)

    Jones, Sam

    Raising schooling quality in low-income countries is a pressing challenge. Substantial research has considered the impact of cutting class sizes on skills acquisition. Considerably less attention has been given to the extent to which peer effects, which refer to class composition, also may affect...... outcomes. This study uses new microdata from East Africa, incorporating test score data for over 250,000 children, to compare the likely efficacy of these two types of interventions. Endogeneity bias is addressed via fixed effects and instrumental variables techniques. Although these may not fully mitigate...

  9. 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.

  10. Cluster analysis

    CERN Document Server

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

    2011-01-01

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

  11. Cluster editing

    DEFF Research Database (Denmark)

    Böcker, S.; Baumbach, Jan

    2013-01-01

    The Cluster Editing problem asks to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. Although the problem has been proven NP-complete several times, it has nevertheless attracted much research both from the theoretical and the applied side. The...... algorithms for biological problems. © 2013 Springer-Verlag....... problem has been the inspiration for numerous algorithms in bioinformatics, aiming at clustering entities such as genes, proteins, phenotypes, or patients. In this paper, we review exact and heuristic methods that have been proposed for the Cluster Editing problem, and also applications of these...

  12. Attracting higher income class to public transport in socially clustered cities. The case of Caracas. / Atracción del mayor nivel de ingresos al transporte público en las ciudades socialmente segregadas. El caso de Caracas.

    Directory of Open Access Journals (Sweden)

    Flórez, Josefina

    2000-03-01

    Full Text Available In Caracas, as in most socially clustered cities, modal split is highly related to income. High income population is mostly car dependant, while lower income people are captive of public transport. This typical situation is explained by world-wide social values and fashion but also by the fact that new, segregated residential areas for the upper social levels have been located in areas poorly served by public transport, creating a dependency on the private car. It is not surprising that, during the 1970's, a high proportion of Caracas's middle and high-income citizens were systematically using their car even in areas where there was a good offer of public transport. What is more unusual is to realise that, since 1983 when the metro system was inaugurated, there is a new pattern of travel behaviour. The metro has mainly attracted high-income people. Besides the few of them who have transferred from surface to underground public transport, many of the wealthier patrons seem to be regular car users that presently take the metro when it provides a good alternative. Currently, the transit system in Caracas is comprised of four main modes: the metro (since 1983; the "por puesto", which are minibus vehicles of 18 to 32 seats; the jeeps, which are dual traction vehicles of up to 12 seat (most of them serving hilly areas, basically slums; and the bus system, consisting of metro-bus and private operators. CA Metro operates the metro and, since 1987, metro-bus lines, which are bus feeder services to its heavy rail metro operation that extend the cover area of the system into the less central zones of the city. While the metro and metro-bus offer transit services to middle and high income users, the mini-buses and jeeps provide flexible transit service to low income groups. The metro and metro-bus services are more reliable and offer higher quality that mini-buses and jeeps. This higher quality service is one of the main attributes attracting the wealthier

  13. Class distinction

    Science.gov (United States)

    White, M. Catherine

    Typical 101 courses discourage many students from pursuing higher level science and math courses. Introductory classes in science and math serve largely as a filter, screening out all but the most promising students, and leaving the majority of college graduates—including most prospective teachers—with little understanding of how science works, according to a study conducted for the National Science Foundation. Because few teachers, particularly at the elementary level, experience any collegiate science teaching that stresses skills of inquiry and investigation, they simply never learn to use those methods in their teaching, the report states.

  14. M$_1$ - M* correlation in galaxy clusters

    CERN Document Server

    Trevese, D; Appodia, B

    1994-01-01

    Photographic F band photometry of a sample of 36 Abell clusters has been used to study the relation between the magnitude M_1 of the brightest cluster member and the Schechter function parameter M^*. Clusters appear segregated in the M_1-M^* plane according to their Rood \\& Sastry class. We prove on a statistical basis that on average, going from early to late RS classes, M_1 becomes brighter while M^* becomes fainter. The result agrees with the predictions of galactic cannibalism models, never confirmed by previous analyses.

  15. High Dimensional Data Clustering Using Fast Cluster Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Karthikeyan.P

    2014-03-01

    Full Text Available Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. A feature selection algorithm may be evaluated from both the efficiency and effectiveness points of view. While the efficiency concerns the time required to find a subset of features, the effectiveness is related to the quality of the subset of features. Based on these criteria, a fast clustering-based feature selection algorithm (FAST is proposed and experimentally evaluated in this paper. The FAST algorithm works in two steps. In the first step, features are divided into clusters by using graph-theoretic clustering methods. In the second step, the most representative feature that is strongly related to target classes is selected from each cluster to form a subset of features. Features in different clusters are relatively independent; the clustering-based strategy of FAST has a high probability of producing a subset of useful and independent features. To ensure the efficiency of FAST, we adopt the efficient minimum-spanning tree (MST using the Kruskal‟s Algorithm clustering method. The efficiency and effectiveness of the FAST algorithm are evaluated through an empirical study. Index Terms—

  16. Cluster-lensing: A Python Package for Galaxy Clusters & Miscentering

    CERN Document Server

    Ford, Jes

    2016-01-01

    We describe a new open source package for calculating properties of galaxy clusters, including NFW halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density $\\Sigma(R)$ and differential surface mass density $\\Delta\\Sigma(R)$ profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo (Ford 2016). Full documenta...

  17. Validity Index and number of clusters

    Directory of Open Access Journals (Sweden)

    Mohamed Fadhel Saad

    2012-01-01

    Full Text Available Clustering (or cluster analysis has been used widely in pattern recognition, image processing, and data analysis. It aims to organize a collection of data items into c clusters, such that items within a cluster are more similar to each other than they are items in the other clusters. The number of clusters c is the most important parameter, in the sense that the remaining parameters have less influence on the resulting partition. To determine the best number of classes several methods were made, and are called validity index. This paper presents a new validity index for fuzzy clustering called a Modified Partition Coefficient And Exponential Separation (MPCAES index. The efficiency of the proposed MPCAES index is compared with several popular validity indexes. More information about these indexes is acquired in series of numerical comparisons and also real data Iris.

  18. Cluster headache

    Science.gov (United States)

    Doctors do not know exactly what causes cluster headaches. They seem to be related to the body's sudden release of histamine (chemical in the body released during an allergic response) or serotonin (chemical made by nerve cells). A problem in a small area at ...

  19. EM Clustering Analysis of Diabetes Patients Basic Diagnosis Index

    OpenAIRE

    Wu, Cai; Steinbauer, Jeffrey R.; Kuo, Grace M

    2005-01-01

    Cluster analysis can group similar instances into same group. Partitioning cluster assigns classes to samples without known the classes in advance. Most common algorithms are K-means and Expectation Maximization (EM). EM clustering algorithm can find number of distributions of generating data and build “mixture models”. It identifies groups that are either overlapping or varying sizes and shapes. In this project, by using EM in Machine Learning Algorithm in JAVA (WEKA) syste...

  20. Document Clustering based on Topic Maps

    CERN Document Server

    Rafi, Muhammad; Farooq, Amir; 10.5120/1640-2204

    2011-01-01

    Importance of document clustering is now widely acknowledged by researchers for better management, smart navigation, efficient filtering, and concise summarization of large collection of documents like World Wide Web (WWW). The next challenge lies in semantically performing clustering based on the semantic contents of the document. The problem of document clustering has two main components: (1) to represent the document in such a form that inherently captures semantics of the text. This may also help to reduce dimensionality of the document, and (2) to define a similarity measure based on the semantic representation such that it assigns higher numerical values to document pairs which have higher semantic relationship. Feature space of the documents can be very challenging for document clustering. A document may contain multiple topics, it may contain a large set of class-independent general-words, and a handful class-specific core-words. With these features in mind, traditional agglomerative clustering algori...

  1. Regional Innovation Clusters

    Data.gov (United States)

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

  2. Knowledge based cluster ensemble for cancer discovery from biomolecular data.

    Science.gov (United States)

    Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying

    2011-06-01

    The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.

  3. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    The cluster theory attributed to Michael Porter has significantly influenced industrial policies in countries across Europe and North America since the beginning of the 1990s. Institutions such as the EU, OECD and the World Bank and governments in countries such as the UK, France, The Netherlands......, Portugal and New Zealand have adopted the concept. Public sector interventions that aim to support cluster development in industries most often focus upon economic policy goals such as enhanced employment and improved productivity, but rarely emphasise broader societal policy goals relating to e...... a difference in terms of enhancing regional development but the paper also concludes that the interventions tend to follow the development path of the established industry and thus tend to neglect long term sustainable development issues while failing to escape the traditional confines of regional industrial...

  4. Clustering experiments

    CERN Document Server

    Wang, Zhengwei; Tan, Ken; Di, Zengru; Roehner, Bertrand M

    2011-01-01

    It is well known that bees cluster together in cold weather, in the process of swarming (when the ``old'' queen leaves with part of the colony) or absconding (when the queen leaves with all the colony) and in defense against intruders such as wasps or hornets. In this paper we describe a fairly different clustering process which occurs at any temperature and independently of any special stimulus or circumstance. As a matter of fact, this process is about four times faster at 28 degree Celsius than at 15 degrees. Because of its simplicity and low level of ``noise'' we think that this phenomenon can provide a means for exploring the strength of inter-individual attraction between bees or other living organisms. For instance, and at first sight fairly surprisingly, our observations showed that this attraction does also exist between bees belonging to different colonies. As this study is aimed at providing a comparative perspective, we also describe a similar clustering experiment for red fire ants.

  5. Applying Machine Learning to Star Cluster Classification

    Science.gov (United States)

    Fedorenko, Kristina; Grasha, Kathryn; Calzetti, Daniela; Mahadevan, Sridhar

    2016-01-01

    Catalogs describing populations of star clusters are essential in investigating a range of important issues, from star formation to galaxy evolution. Star cluster catalogs are typically created in a two-step process: in the first step, a catalog of sources is automatically produced; in the second step, each of the extracted sources is visually inspected by 3-to-5 human classifiers and assigned a category. Classification by humans is labor-intensive and time consuming, thus it creates a bottleneck, and substantially slows down progress in star cluster research.We seek to automate the process of labeling star clusters (the second step) through applying supervised machine learning techniques. This will provide a fast, objective, and reproducible classification. Our data is HST (WFC3 and ACS) images of galaxies in the distance range of 3.5-12 Mpc, with a few thousand star clusters already classified by humans as a part of the LEGUS (Legacy ExtraGalactic UV Survey) project. The classification is based on 4 labels (Class 1 - symmetric, compact cluster; Class 2 - concentrated object with some degree of asymmetry; Class 3 - multiple peak system, diffuse; and Class 4 - spurious detection). We start by looking at basic machine learning methods such as decision trees. We then proceed to evaluate performance of more advanced techniques, focusing on convolutional neural networks and other Deep Learning methods. We analyze the results, and suggest several directions for further improvement.

  6. Evolution of major histocompatibility complex class I and class II genes in the brown bear

    Directory of Open Access Journals (Sweden)

    Kuduk Katarzyna

    2012-10-01

    Full Text Available Abstract Background Major histocompatibility complex (MHC proteins constitute an essential component of the vertebrate immune response, and are coded by the most polymorphic of the vertebrate genes. Here, we investigated sequence variation and evolution of MHC class I and class II DRB, DQA and DQB genes in the brown bear Ursus arctos to characterise the level of polymorphism, estimate the strength of positive selection acting on them, and assess the extent of gene orthology and trans-species polymorphism in Ursidae. Results We found 37 MHC class I, 16 MHC class II DRB, four DQB and two DQA alleles. We confirmed the expression of several loci: three MHC class I, two DRB, two DQB and one DQA. MHC class I also contained two clusters of non-expressed sequences. MHC class I and DRB allele frequencies differed between northern and southern populations of the Scandinavian brown bear. The rate of nonsynonymous substitutions (dN exceeded the rate of synonymous substitutions (dS at putative antigen binding sites of DRB and DQB loci and, marginally significantly, at MHC class I loci. Models of codon evolution supported positive selection at DRB and MHC class I loci. Both MHC class I and MHC class II sequences showed orthology to gene clusters found in the giant panda Ailuropoda melanoleuca. Conclusions Historical positive selection has acted on MHC class I, class II DRB and DQB, but not on the DQA locus. The signal of historical positive selection on the DRB locus was particularly strong, which may be a general feature of caniforms. The presence of MHC class I pseudogenes may indicate faster gene turnover in this class through the birth-and-death process. South–north population structure at MHC loci probably reflects origin of the populations from separate glacial refugia.

  7. Clustering Analysis on E-commerce Transaction Based on K-means Clustering

    Directory of Open Access Journals (Sweden)

    Xuan HUANG

    2014-02-01

    Full Text Available Based on the density, increment and grid etc, shortcomings like the bad elasticity, weak handling ability of high-dimensional data, sensitive to time sequence of data, bad independence of parameters and weak handling ability of noise are usually existed in clustering algorithm when facing a large number of high-dimensional transaction data. Making experiments by sampling data samples of the 300 mobile phones of Taobao, the following conclusions can be obtained: compared with Single-pass clustering algorithm, the K-means clustering algorithm has a high intra-class dissimilarity and inter-class similarity when analyzing e-commerce transaction. In addition, the K-means clustering algorithm has very high efficiency and strong elasticity when dealing with a large number of data items. However, clustering effects of this algorithm are affected by clustering number and initial positions of clustering center. Therefore, it is easy to show the local optimization for clustering results. Therefore, how to determine clustering number and initial positions of the clustering center of this algorithm is still the important job to be researched in the future.

  8. Globular Cluster Formation in the Virgo Cluster

    CERN Document Server

    Moran, C Corbett; Lake, G

    2014-01-01

    Metal poor globular clusters (MPGCs) are a unique probe of the early universe, in particular the reionization era. Systems of globular clusters in galaxy clusters are particularly interesting as it is in the progenitors of galaxy clusters that the earliest reionizing sources first formed. Although the exact physical origin of globular clusters is still debated, it is generally admitted that globular clusters form in early, rare dark matter peaks (Moore et al. 2006; Boley et al. 2009). We provide a fully numerical analysis of the Virgo cluster globular cluster system by identifying the present day globular cluster system with exactly such early, rare dark matter peaks. A popular hypothesis is that that the observed truncation of blue metal poor globular cluster formation is due to reionization (Spitler et al. 2012; Boley et al. 2009; Brodie & Strader 2006); adopting this view, constraining the formation epoch of MPGCs provides a complementary constraint on the epoch of reionization. By analyzing both the l...

  9. Class Vectors: Embedding representation of Document Classes

    OpenAIRE

    Sachan, Devendra Singh; Kumar, Shailesh

    2015-01-01

    Distributed representations of words and paragraphs as semantic embeddings in high dimensional data are used across a number of Natural Language Understanding tasks such as retrieval, translation, and classification. In this work, we propose "Class Vectors" - a framework for learning a vector per class in the same embedding space as the word and paragraph embeddings. Similarity between these class vectors and word vectors are used as features to classify a document to a class. In experiment o...

  10. SACS: Spitzer Archival Cluster Survey

    Science.gov (United States)

    Stern, Daniel

    on cosmological results from ongoing Sunyaev-Zel'dovich (SZ) and X-ray cluster surveys. The identified clusters will be valuable for both astrophysics and cosmology. In terms of astrophysics, the redshift probed by the MIR color selection targets a key epoch in cluster development, when star formation is shutting down and the galaxies are becoming passive. Massive clusters also distort space-time around them, creating powerful gravitational telescopes that lens the distant universe. This both allows detailed studies of the lensed objects with otherwise unachievable sensitivity, as well as provides a unique probe of the mass distribution in the lensing cluster. In terms of cosmology, clusters are the most massive structures in the universe, and their space density is sensitive to basic cosmological parameters. Clusters identified by this program will become a lasting legacy of Spitzer, providing exciting targets for Chandra, Hubble, James Webb Space Telescope (JWST), Astro-H, Athena, as well as future 30-m class ground-based telescopes (e.g., GMT, ELT, TMT). The upcoming large-scale, space-based surveys of eROSITA, Euclid, and WFIRST all have distant cluster studies as key scientific goals. Our proposed survey will provide new high redshift targets for those satellites, enabling unique, exciting multi-wavelength studies of the Spitzer-selected sample, as well as a training set to identify additional high-redshift clusters outside of the Spitzer footprint.

  11. Clustering of drinker prototype characteristics: what characterizes the typical drinker?

    Science.gov (United States)

    van Lettow, Britt; Vermunt, Jeroen K; de Vries, Hein; Burdorf, Alex; van Empelen, Pepijn

    2013-08-01

    Prototypes (social images) have been shown to influence behaviour, which is likely to depend on the type of image. Prototype evaluation is based on (un)desirable characteristics related to that image. By an elicitation procedure we examined which adjectives are attributed to specific drinker prototypes. In total 149 young Dutch adults (18-25 years of age) provided adjectives for five drinker prototypes: abstainer, moderate drinker, heavy drinker, tipsy, and drunk person. Twenty-three unique adjectives were found. Multilevel latent class cluster analysis revealed six adjective clusters, each with unique and minor overlapping adjectives: 'negative, excessive drinker,' 'moderate, responsible drinker,' 'funny tipsy drinker,' 'determined abstainer cluster,' 'uncontrolled excessive drinker,' and 'elated tipsy cluster.' In addition, four respondent classes were identified. Respondent classes showed differences in their focus on specific adjective clusters. Classes could be labelled 'focus-on-control class,' 'focus-on-hedonism class,' 'contrasting-extremes-prototypes class,' and 'focus-on-elation class.' Respondent classes differed in gender, educational level and drinking behaviour. The results underscore the importance to differentiate between various prototypes and in prototype adjectives among young adults: subgroup differences in prototype salience and relevance are possibly due to differences in adjective labelling. The results provide insights into explaining differences in drinking behaviour and could potentially be used to target and tailor interventions aimed at lowering alcohol consumption among young adults via prototype alteration. PMID:23848388

  12. Does Class Size Matter?

    Science.gov (United States)

    Ehrenberg, Ronald G.; Brewer, Dominic J.; Gamoran, Adam; Willms, J. Douglas

    2001-01-01

    Reports on the significance of class size to student learning. Includes an overview of class size in various countries, the importance of teacher adaptability, and the Asian paradox of large classes allied to high test scores. (MM)

  13. RxClass

    Data.gov (United States)

    U.S. Department of Health & Human Services — The RxClass Browser is a web application for exploring and navigating through the class hierarchies to find the RxNorm drug members associated with each class....

  14. A Virtual Class Calculus

    DEFF Research Database (Denmark)

    Ernst, Erik; Ostermann, Klaus; Cook, William Randall

    2006-01-01

    , not as static components of a class. When used as types, virtual classes depend upon object identity - each object instance introduces a new family of virtual class types. Virtual classes support large scale program composition techniques, including higher-order hierarchies and family polymorphism. The original......Virtual classes are class-valued attributes of objects. Like virtual methods, virtual classes are defined in an object's class and may be redefined within subclasses. They resemble inner classes, which are also defined within a class, but virtual classes are accessed through object instances...... definition of virtual classes in BETA left open the question of static type safety, since some type errors were not caught until runtime. Later the languages Caesar and gbeta have used a more strict static analysis in order to ensure static type safety. However, the existence of a sound, statically typed...

  15. Cluster Decline and Resilience

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark, 1963...... in new resources to the cluster but being quick to withdraw in times of crisis....

  16. Double-partition Quantum Cluster Algebras

    DEFF Research Database (Denmark)

    Jakobsen, Hans Plesner; Zhang, Hechun

    2012-01-01

    A family of quantum cluster algebras is introduced and studied. In general, these algebras are new, but sub-classes have been studied previously by other authors. The algebras are indexed by double parti- tions or double flag varieties. Equivalently, they are indexed by broken lines L. By grouping...... together neighboring mutations into quantum line mutations we can mutate from the cluster algebra of one broken line to another. Compatible pairs can be written down. The algebras are equal to their upper cluster algebras. The variables of the quantum seeds are given by elements of the dual canonical basis....

  17. Issues Challenges and Tools of Clustering Algorithms

    Directory of Open Access Journals (Sweden)

    Parul Agarwal

    2011-05-01

    Full Text Available Clustering is an unsupervised technique of Data Mining. It means grouping similar objects together and separating the dissimilar ones. Each object in the data set is assigned a class label in the clustering process using a distance measure. This paper has captured the problems that are faced in real when clustering algorithms are implemented .It also considers the most extensively used tools which are readily available and support functions which ease the programming. Once algorithms have been implemented, they also need to be tested for its validity. There exist several validation indexes for testing the performance and accuracy which have also been discussed here.

  18. Brightest Cluster Galaxies in the Extended GMRT radio halo cluster sample. Radio properties and cluster dynamics

    CERN Document Server

    Kale, Ruta; Cassano, Rossella; Giacintucci, Simona; Bardelli, sandro; Dallacasa, Daniele; Zucca, Elena

    2015-01-01

    Brightest Cluster Galaxies (BCGs) show exceptional properties over the whole electromagnetic spectrum. Their special location at the centres of galaxy clusters raises the question of the role of the environment on their radio properties. To decouple the effect of the galaxy mass and of the environment in their statistical radio properties, we investigate the possible dependence of the occurrence of radio loudness and of the fractional radio luminosity function on the dynamical state of the hosting cluster. We studied the radio properties of the BCGs in the Extended GMRT Radio Halo Survey (EGRHS). We obtained a statistical sample of 59 BCGs, which was divided into two classes, depending on the dynamical state of the host cluster, i.e. merging (M) and relaxed (R). Among the 59 BCGs, 28 are radio-loud, and 31 are radio--quiet. The radio-loud sources are located favourably located in relaxed clusters (71\\%), while the reverse is true for the radio-quiet BCGs, mostly located in merging systems (81\\%). The fraction...

  19. NEO-FFI personality clusters in trichotillomania.

    Science.gov (United States)

    Keuthen, Nancy J; Tung, Esther S; Tung, Matthew G; Curley, Erin E; Flessner, Christopher A

    2016-05-30

    The purpose of this study was to determine whether personality prototypes exist among hair pullers and if these groups differ in hair pulling (HP) characteristics, clinical correlates, and quality of life. 164 adult hair pullers completed the NEO-Five Factor Inventory (NEO-FFI; Costa and McCrae, 1992) and self-report measures of HP severity, HP style, affective state, and quality of life. A latent class cluster analysis using NEO-FFI scores was performed to separate participants into clusters. Bonferroni-corrected t-tests were used to compare clusters on HP, affective, and quality of life variables. Multiple regression was used to determine which variables significantly predicted quality of life. Two distinct personality prototypes were identified. Cluster 1 (n=96) had higher neuroticism and lower extraversion, agreeableness, and conscientiousness when compared to cluster 2 (n=68). No significant differences in demographics were reported for the two personality clusters. The clusters differed on extent of focused HP, severity of depression, anxiety, and stress, as well as quality of life. Those in cluster 1 endorsed greater depression, anxiety, and stress, and worse quality of life. Additionally, only depression and cluster membership (based on NEO scores) significantly predicted quality of life. PMID:27016621

  20. COOPERATIVE CLUSTERING BASED ON GRID AND DENSITY

    Institute of Scientific and Technical Information of China (English)

    HU Ruifei; YIN Guofu; TAN Ying; CAI Peng

    2006-01-01

    Based on the analysis of features of the grid-based clustering method-clustering in quest(CLIQUE) and density-based clustering method-density-based spatial clustering of applications with noise (DBSCAN), a new clustering algorithm named cooperative clustering based on grid and density(CLGRID) is presented. The new algorithm adopts an equivalent rule of regional inquiry and density unit identification. The central region of one class is calculated by the grid-based method and the margin region by a density-based method. By clustering in two phases and using only a small number of seed objects in representative units to expand the cluster, the frequency of region query can be decreased, and consequently the cost of time is reduced. The new algorithm retains positive features of both grid-based and density-based methods and avoids the difficulty of parameter searching. It can discover clusters of arbitrary shape with high efficiency and is not sensitive to noise. The application of CLGRID on test data sets demonstrates its validity and higher efficiency, which contrast with traditional DBSCAN with R* tree.

  1. Partitional clustering algorithms

    CERN Document Server

    2015-01-01

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

  2. Modernization typologies industrial clusters

    Directory of Open Access Journals (Sweden)

    Karapetian, Eduard

    2011-11-01

    Full Text Available Generalized theoretical approach to the criteria of industrial clusters. On this basis, a detailed typology of industrial cluster structures, which takes into account the peculiarities of the functioning of clusters in the domestic economy.

  3. Factorial PD-Clustering

    CERN Document Server

    Tortora, Cristina; Summa, Mireille Gettler

    2011-01-01

    Factorial clustering methods have been developed in recent years thanks to the improving of computational power. These methods perform a linear transformation of data and a clustering on transformed data optimizing a common criterion. Factorial PD-clustering is based on Probabilistic Distance clustering (PD-clustering). PD-clustering is an iterative, distribution free, probabilistic, clustering method. Factorial PD-clustering make a linear transformation of original variables into a reduced number of orthogonal ones using a common criterion with PD-Clustering. It is demonstrated that Tucker 3 decomposition allows to obtain this transformation. Factorial PD-clustering makes alternatively a Tucker 3 decomposition and a PD-clustering on transformed data until convergence. This method could significantly improve the algorithm performance and allows to work with large dataset, to improve the stability and the robustness of the method.

  4. Possibilistic Exponential Fuzzy Clustering

    Institute of Scientific and Technical Information of China (English)

    Kiatichai Treerattanapitak; Chuleerat Jaruskulchai

    2013-01-01

    Generally,abnormal points (noise and outliers) cause cluster analysis to produce low accuracy especially in fuzzy clustering.These data not only stay in clusters but also deviate the centroids from their true positions.Traditional fuzzy clustering like Fuzzy C-Means (FCM) always assigns data to all clusters which is not reasonable in some circumstances.By reformulating objective function in exponential equation,the algorithm aggressively selects data into the clusters.However noisy data and outliers cannot be properly handled by clustering process therefore they are forced to be included in a cluster because of a general probabilistic constraint that the sum of the membership degrees across all clusters is one.In order to improve this weakness,possibilistic approach relaxes this condition to improve membership assignment.Nevertheless,possibilistic clustering algorithms generally suffer from coincident clusters because their membership equations ignore the distance to other clusters.Although there are some possibilistic clustering approaches that do not generate coincident clusters,most of them require the right combination of multiple parameters for the algorithms to work.In this paper,we theoretically study Possibilistic Exponential Fuzzy Clustering (PXFCM) that integrates possibilistic approach with exponential fuzzy clustering.PXFCM has only one parameter and not only partitions the data but also filters noisy data or detects them as outliers.The comprehensive experiments show that PXFCM produces high accuracy in both clustering results and outlier detection without generating coincident problems.

  5. DYNER: A DYNamic ClustER for Education and Research

    Science.gov (United States)

    Kehagias, Dimitris; Grivas, Michael; Mamalis, Basilis; Pantziou, Grammati

    2006-01-01

    Purpose: The purpose of this paper is to evaluate the use of a non-expensive dynamic computing resource, consisting of a Beowulf class cluster and a NoW, as an educational and research infrastructure. Design/methodology/approach: Clusters, built using commodity-off-the-shelf (COTS) hardware components and free, or commonly used, software, provide…

  6. Gennclus: New Models for General Nonhierarchical Clustering Analysis.

    Science.gov (United States)

    Desarbo, Wayne S.

    1982-01-01

    A general class of nonhierarchical clustering models and associated algorithms for fitting them are presented. These models generalize the Shepard-Arabie Additive clusters model. Two applications are given and extensions to three-way models, nonmetric analyses, and other model specifications are provided. (Author/JKS)

  7. Management of cluster headache

    DEFF Research Database (Denmark)

    Tfelt-Hansen, Peer C; Jensen, Rigmor H

    2012-01-01

    and agitation. Patients may have up to eight attacks per day. Episodic cluster headache (ECH) occurs in clusters of weeks to months duration, whereas chronic cluster headache (CCH) attacks occur for more than 1 year without remissions. Management of cluster headache is divided into acute attack treatment...

  8. Structures of Mn clusters

    Indian Academy of Sciences (India)

    Tina M Briere; Marcel H F Sluiter; Vijay Kumar; Yoshiyuki Kawazoe

    2003-01-01

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

  9. Graded cluster algebras

    OpenAIRE

    Grabowski, Jan

    2015-01-01

    In the cluster algebra literature, the notion of a graded cluster algebra has been implicit since the origin of the subject. In this work, we wish to bring this aspect of cluster algebra theory to the foreground and promote its study. We transfer a definition of Gekhtman, Shapiro and Vainshtein to the algebraic setting, yielding the notion of a multi-graded cluster algebra. We then study gradings for finite type cluster algebras without coefficients, giving a full classification. Translating ...

  10. On Comparison of Clustering Methods for Pharmacoepidemiological Data.

    Science.gov (United States)

    Feuillet, Fanny; Bellanger, Lise; Hardouin, Jean-Benoit; Victorri-Vigneau, Caroline; Sébille, Véronique

    2015-01-01

    The high consumption of psychotropic drugs is a public health problem. Rigorous statistical methods are needed to identify consumption characteristics in post-marketing phase. Agglomerative hierarchical clustering (AHC) and latent class analysis (LCA) can both provide clusters of subjects with similar characteristics. The objective of this study was to compare these two methods in pharmacoepidemiology, on several criteria: number of clusters, concordance, interpretation, and stability over time. From a dataset on bromazepam consumption, the two methods present a good concordance. AHC is a very stable method and it provides homogeneous classes. LCA is an inferential approach and seems to allow identifying more accurately extreme deviant behavior. PMID:24905478

  11. Cool Core Clusters from Cosmological Simulations

    CERN Document Server

    Rasia, E; Murante, G; Planelles, S; Beck, A M; Biffi, V; Ragone-Figueroa, C; Granato, G L; Steinborn, L K; Dolag, K

    2015-01-01

    We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core and non-cool-core clusters. Our simulations include the effects of stellar and AGN feedback and are based on an improved version of the Smoothed-Particle-Hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, our primary diagnostic to classify the degree of cool-coreness of clusters, and on the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of cool-core systems, to nearly flat core isentropic profiles, characteristic of non cool-core systems. Using observational criteria to distinguish between the two classes of...

  12. Variable-Voltage Class-E Power Amplifiers

    NARCIS (Netherlands)

    Acar, Mustafa; Annema, Anne Johan; Nauta, Bram

    2007-01-01

    The Class-E power amplifier is widely used due to its high efficiency, resulting from switching at zero voltage and zero slope of the switch voltage. In this paper, we extend general analytical solutions for the Class-E power amplifier to the ideal single-ended Variable-Voltage Class-E (Class-EVV) p

  13. Subpopulation Discovery in Epidemiological Data with Subspace Clustering

    Directory of Open Access Journals (Sweden)

    Niemann Uli

    2014-12-01

    Full Text Available A prerequisite of personalized medicine is the identification of groups of people who share specific risk factors towards an outcome. We investigate the potential of subspace clustering for finding such groups in epidemiological data. We propose a workflow that encompasses clusterability assessment before cluster discovery and quality assessment after learning the clusters. Epidemiological usually do not have a ground truth for the verification of clusters found in subspaces. Hence, we introduce quality assessment through juxtaposition of the learned models to “models-of-randomness”, i.e. models that do not reflect a true cluster structure. On the basis of this workflow, we select subspace clustering methods, compare and discuss their performance. We use a dataset with hepatic steatosis as outcome, but our findings apply on arbitrary epidemiological cohort data that have tenths of variables and exhibit class skew.

  14. A Density Based Dynamic Data Clustering Algorithm based on Incremental Dataset

    Directory of Open Access Journals (Sweden)

    K. R.S. Kumar

    2012-01-01

    Full Text Available Problem statement: Clustering and visualizing high-dimensional dynamic data is a challenging problem. Most of the existing clustering algorithms are based on the static statistical relationship among data. Dynamic clustering is a mechanism to adopt and discover clusters in real time environments. There are many applications such as incremental data mining in data warehousing applications, sensor network, which relies on dynamic data clustering algorithms. Approach: In this work, we present a density based dynamic data clustering algorithm for clustering incremental dataset and compare its performance with full run of normal DBSCAN, Chameleon on the dynamic dataset. Most of the clustering algorithms perform well and will give ideal performance with good accuracy measured with clustering accuracy, which is calculated using the original class labels and the calculated class labels. However, if we measure the performance with a cluster validation metric, then it will give another kind of result. Results: This study addresses the problems of clustering a dynamic dataset in which the data set is increasing in size over time by adding more and more data. So to evaluate the performance of the algorithms, we used Generalized Dunn Index (GDI, Davies-Bouldin index (DB as the cluster validation metric and as well as time taken for clustering. Conclusion: In this study, we have successfully implemented and evaluated the proposed density based dynamic clustering algorithm. The performance of the algorithm was compared with Chameleon and DBSCAN clustering algorithms. The proposed algorithm performed significantly well in terms of clustering accuracy as well as speed.

  15. All about RIKEN Integrated Cluster of Clusters (RICC

    Directory of Open Access Journals (Sweden)

    Maho Nakata

    2012-07-01

    Full Text Available

    This is an introduction to the RIKEN's supercomputer RIKEN Integrated Cluster of Clusters (RICC, that has been in operation since August 2009. The basic concept of the RICC is to "provide an environment with high power computational resources to facilitate research and development for RIKEN's researchers". Based on this concept, we have been operating the RICC system as a (i data analysis environment for experimental researchers, (ii development environment targeting the next-generation supercomputer; i.e., the "K" computer, and (iii GPU (graphics processing unit computers for exploring challenges in developing a future computer environment. The total performance of RICC is 97.94 TFlops, ranking it as the 125th on the Top500 list in Nov. 2011. We prepared four job class accounts, based on the researchers' proposals prior to evaluation by our Review Committee. We also provided backup services to RIKEN's researchers, such as conducting RICC training classes, software installation services, and speed up and visualization support. To encourage affirmative participation and proactive initiation, all the services were free of charge; however, access to RICC was limited to researchers and collaborators of RIKEN. As a result, RICC has been able to maintain a high activity ratio (> 90% since the beginning of its operation.

  16. Semisimple Classes of Semirings

    Institute of Scientific and Technical Information of China (English)

    U. Hebisch; H.J. Weinert

    2002-01-01

    A famous result of Sands states that a class S of associative rings is semisimple if and only if S is regular, coinductive, and extensionally closed. Here,we investigate semisimple classes in a Kurosh-Amitsur radical theory for semirings. We show that such a class S is regular, K-coinductive, and K-extensionally closed. But a characterization of semisimple classes of semirings needs a fourth condition, namely that S is inverse semi-isomorphically closed. We also obtain other characterizations and results for semisimple classes and for subdirect products of semirings.

  17. Loosely coupled class families

    DEFF Research Database (Denmark)

    Ernst, Erik

    2001-01-01

    are expressed using virtual classes seem to be very tightly coupled internally. While clients have achieved the freedom to dynamically use one or the other family, it seems that any given family contains a xed set of classes and we will need to create an entire family of its own just in order to replace one...... of the members with another class. This paper shows how to express class families in such a manner that the classes in these families can be used in many dierent combinations, still enabling family polymorphism and ensuring type safety....

  18. Class, Culture and Politics

    DEFF Research Database (Denmark)

    Harrits, Gitte Sommer

    2013-01-01

    Even though contemporary discussions of class have moved forward towards recognizing a multidimensional concept of class, empirical analyses tend to focus on cultural practices in a rather narrow sense, that is, as practices of cultural consumption or practices of education. As a result......, discussions within political sociology have not yet utilized the merits of a multidimensional conception of class. In light of this, the article suggests a comprehensive Bourdieusian framework for class analysis, integrating culture as both a structural phenomenon co-constitutive of class and as symbolic...

  19. Coupled Two-Way Clustering Analysis of Breast Cancer and Colon Cancer Gene Expression Data

    CERN Document Server

    Getz, G; Kela, I; Domany, E; Notterman, D A; Getz, Gad; Gal, Hilah; Kela, Itai; Domany, Eytan; Notterman, Dan A.

    2003-01-01

    We present and review Coupled Two Way Clustering, a method designed to mine gene expression data. The method identifies submatrices of the total expression matrix, whose clustering analysis reveals partitions of samples (and genes) into biologically relevant classes. We demonstrate, on data from colon and breast cancer, that we are able to identify partitions that elude standard clustering analysis.

  20. Clustering Algorithm Based on Crowding Niche%小生境排挤聚类算法

    Institute of Scientific and Technical Information of China (English)

    业宁; 董逸生

    2003-01-01

    A new clustering algorithm is proposed in this paper, which is based on crowding niche. Homogeneityspontaneous to withstands heterogeneity when organisms are evolving. Contemporary, Individual in same class com-pete each other to strive for limited resource. Individual that has bad fitness will be eliminated. We propose a cluster-ing algorithm based on this idea. Experiment evaluation has proved its efficiency.

  1. What Makes Clusters Decline?

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    2015-01-01

    Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark....... The longitudinal study on the high-tech cluster reveals that technological lock-in and exit of key firms have contributed to decline. Entrepreneurship has a positive effect on the cluster’s adaptive capabilities, while multinational companies have contradicting effects by bringing in new resources to the cluster...

  2. Galaxy Luminosity Functions in WINGS clusters

    CERN Document Server

    Moretti, A; Poggianti, B M; Fasano, G; Varela, J; D'Onofrio, M; Vulcani, B; Cava, A; Fritz, J; Couch, W J; Moles, M; Kjærgaard, P

    2015-01-01

    Using V band photometry of the WINGS survey, we derive galaxy luminosity functions (LF) in nearby clusters. This sample is complete down to Mv=-15.15, and it is homogeneous, thus allowing the study of an unbiased sample of clusters with different characteristics. We constructed the photometric LF for 72 out of the original 76 WINGS clusters, excluding only those without a velocity dispersion estimate. For each cluster we obtained the LF for galaxies in a region of radius=0.5 x r200, and fitted them with single and double Schechter's functions. We also derive the composite LF for the entire sample, and those pertaining to different morphological classes. Finally we derive the spectroscopic cumulative LF for 2009 galaxies that are cluster members. The double Schechter fit parameters are neither correlated with the cluster velocity dispersion, nor with the X-ray luminosity. Our median values of the Schechter's fit slope are, on average, in agreement with measurements of nearby clusters, but are less steep that t...

  3. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

    Science.gov (United States)

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

    2016-01-01

    Galaxy clusters are a rich source of information for examining fundamental astrophysical processes and cosmological parameters, however, employing clusters as cosmological probes requires accurate mass measurements derived from cluster observables. We study dynamical mass measurements of galaxy clusters contaminated by interlopers, and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create a mock catalog from Multidark's publicly-available N-body MDPL1 simulation where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power law scaling relation to infer cluster mass from galaxy line of sight (LOS) velocity dispersion. The presence of interlopers in the catalog produces a wide, flat fractional mass error distribution, with width = 2.13. We employ the Support Distribution Machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement (width = 0.67). Remarkably, SDM applied to contaminated clusters is better able to recover masses than even a scaling relation approach applied to uncontaminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

  4. Star clusters and associations

    International Nuclear Information System (INIS)

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

  5. Niching method using clustering crowding

    Institute of Scientific and Technical Information of China (English)

    GUO Guan-qi; GUI Wei-hua; WU Min; YU Shou-yi

    2005-01-01

    This study analyzes drift phenomena of deterministic crowding and probabilistic crowding by using equivalence class model and expectation proportion equations. It is proved that the replacement errors of deterministic crowding cause the population converging to a single individual, thus resulting in premature stagnation or losing optional optima. And probabilistic crowding can maintain equilibrium multiple subpopulations as the population size is adequate large. An improved niching method using clustering crowding is proposed. By analyzing topology of fitness landscape using hill valley function and extending the search space for similarity analysis, clustering crowding determines the locality of search space more accurately, thus greatly decreasing replacement errors of crowding. The integration of deterministic and probabilistic replacement increases the capacity of both parallel local hill climbing and maintaining multiple subpopulations. The experimental results optimizing various multimodal functions show that,the performances of clustering crowding, such as the number of effective peaks maintained, average peak ratio and global optimum ratio are uniformly superior to those of the evolutionary algorithms using fitness sharing, simple deterministic crowding and probabilistic crowding.

  6. Monopole clusters in Abelian projected gauge theories

    OpenAIRE

    Hart, A.; Teper, M.

    1997-01-01

    We show that the monopole currents which one obtains in the maximally Abelian gauge of SU(2) fall into two quite distinct classes (when the volume is large enough). In each field configuration there is precisely one cluster that permeates the whole lattice volume. It has a current density and a magnetic screening mass that scale and it produces the whole of the string tension. The remaining clusters have a number density that follows an approximate power law proportional to the inverse cube o...

  7. Semantic Analysis of Virtual Classes and Nested Classes

    DEFF Research Database (Denmark)

    Madsen, Ole Lehrmann

    1999-01-01

    Virtual classes and nested classes are distinguishing features of BETA. Nested classes originated from Simula, but until recently they have not been part of main stream object- oriented languages. C++ has a restricted form of nested classes and they were included in Java 1.1. Virtual classes is the...... classes and parameterized classes have been made. Although virtual classes and nested classes have been used in BETA for more than a decade, their implementation has not been published. The purpose of this paper is to contribute to the understanding of virtual classes and nested classes by presenting the...

  8. Class network routing

    Science.gov (United States)

    Bhanot, Gyan; Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

    2009-09-08

    Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

  9. Quantum Annealing for Clustering

    OpenAIRE

    Kurihara, Kenichi; Tanaka, Shu; Miyashita, Seiji

    2014-01-01

    This paper studies quantum annealing (QA) for clustering, which can be seen as an extension of simulated annealing (SA). We derive a QA algorithm for clustering and propose an annealing schedule, which is crucial in practice. Experiments show the proposed QA algorithm finds better clustering assignments than SA. Furthermore, QA is as easy as SA to implement.

  10. Emergence of regional clusters

    DEFF Research Database (Denmark)

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

    2010-01-01

    approach to analyse how successful early firms can lead to formation of clusters. Three key determinants are identified: (1) the geographical dimension of entrepreneurial activity, (2) spinoffs from successful firms and (3) new market opportunities. The chapter studies in great detail the evolution...... of the wireless communications cluster in Northern Denmark and compare it with the evolution of other clusters....

  11. The Durban Auto Cluster

    DEFF Research Database (Denmark)

    Lorentzen, Jochen; Robbins, Glen; Barnes, Justin

    2004-01-01

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

  12. 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.

  13. Final Report of the Evaluation of the 1969-1970 Benjamin Franklin Cluster Program: Programs and Patterns for Disadvantaged High School Students. ESEA Title I.

    Science.gov (United States)

    Hoffman, Louis J.

    The Cluster Program at Benjamin Franklin High School, funded under Title I of the 1965 Elementary Secondary Education Act, is designed to be a school within a school in which 249 ninth grade students attend classes in two separate clusters. Each cluster is formulated such that all students receive instruction from five teachers in classes whose…

  14. ABS 497 Complete Class

    OpenAIRE

    admin

    2015-01-01

    ABS 497 Complete Class   To purchase this material click below link   http://www.assignmentcloud.com/ABS-497/ABS-497-Complete-Class-Guide   For more classes visit   www.assignmentcloud.com   ABS 497 Week 1 Assignment Community Change ABS 497 Week 1 DQ 1 Fabian's Story ABS 497 Week 1 DQ 2 Doug's Story ABS 497 Week 2 DQ 1 Parenting Styles ABS 497 Week 2 DQ 2 Ethnicity and Learning Theory ABS 497 Week 3 ...

  15. Fostering a Middle Class

    Institute of Scientific and Technical Information of China (English)

    YAO BIN

    2011-01-01

    Though there is no official definition of "middle class" in China,the tag has become one few Chinese people believe they deserve anyway.In early August,the Chinese Academy of Social Sciences released a report on China's urban development,saying China had a middle-class population of 230 million in 2009,or 37 percent of its urban residents.It also forecast half of city dwellers in China would be part of the middle class by 2023.

  16. Cluster beam sources. Part 1. Methods of cluster beams generation

    Directory of Open Access Journals (Sweden)

    A.Ju. Karpenko

    2012-10-01

    Full Text Available The short review on cluster beams generation is proposed. The basic types of cluster sources are considered and the processes leading to cluster formation are analyzed. The parameters, that affects the work of cluster sources are presented.

  17. Simultaneous clustering of multiple gene expression and physical interaction datasets.

    Directory of Open Access Journals (Sweden)

    Manikandan Narayanan

    2010-04-01

    Full Text Available Many genome-wide datasets are routinely generated to study different aspects of biological systems, but integrating them to obtain a coherent view of the underlying biology remains a challenge. We propose simultaneous clustering of multiple networks as a framework to integrate large-scale datasets on the interactions among and activities of cellular components. Specifically, we develop an algorithm JointCluster that finds sets of genes that cluster well in multiple networks of interest, such as coexpression networks summarizing correlations among the expression profiles of genes and physical networks describing protein-protein and protein-DNA interactions among genes or gene-products. Our algorithm provides an efficient solution to a well-defined problem of jointly clustering networks, using techniques that permit certain theoretical guarantees on the quality of the detected clustering relative to the optimal clustering. These guarantees coupled with an effective scaling heuristic and the flexibility to handle multiple heterogeneous networks make our method JointCluster an advance over earlier approaches. Simulation results showed JointCluster to be more robust than alternate methods in recovering clusters implanted in networks with high false positive rates. In systematic evaluation of JointCluster and some earlier approaches for combined analysis of the yeast physical network and two gene expression datasets under glucose and ethanol growth conditions, JointCluster discovers clusters that are more consistently enriched for various reference classes capturing different aspects of yeast biology or yield better coverage of the analysed genes. These robust clusters, which are supported across multiple genomic datasets and diverse reference classes, agree with known biology of yeast under these growth conditions, elucidate the genetic control of coordinated transcription, and enable functional predictions for a number of uncharacterized genes.

  18. 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

  19. Networking Options for Beowulf Clusters

    Science.gov (United States)

    Sterling, Thomas L.

    2000-03-01

    Beowulf-class PC clusters have emerged as an important type of high end computing system providing unprecedented price-performance advantage and configuration flexibility. Derived from mass market commodity off-the-shelf hardware and software components, Beowulf systems are being implemented across the country and around the world for a wide array of applications and with diverse structures and scale. Critical to the success and effectiveness of Beowulfs has been the availability of low cost, moderate bandwidth local area networks (LAN) to provide communications channels between PC nodes. From the early days with 10 Mbps Ethernet, system area networking (SAN) has evolved dramatically providing a number of choices of technology and protocol with, in some cases, more than 1 Gbps per channel peak bandwidth. Beowulf systems have been implemented with many of these and in a number of different configurations and topologies. Fast Ethernet, Gigabit Ethernet, Giganet, Myranet, SCI as well as a number of switch nodes are in use. Systems exceeding a thousand processors either have been or are being assembled and commercial vendors are now marketing Beowulf-class systems as turn-key computers. The technology is advancing so rapidly that information even a year old is largely out of date. This presentation will provide an up to date description of the current state-of-the-art in system area networks for Beowulf-class computing and give examples of existing or planned systems employing these technologies.

  20. Clusters in nuclei

    CERN Document Server

    Beck, Christian

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

  1. Unconventional methods for clustering

    Science.gov (United States)

    Kotyrba, Martin

    2016-06-01

    Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is the main task of exploratory data mining and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics. The topic of this paper is one of the modern methods of clustering namely SOM (Self Organising Map). The paper describes the theory needed to understand the principle of clustering and descriptions of algorithm used with clustering in our experiments.

  2. Spatial cluster modelling

    CERN Document Server

    Lawson, Andrew B

    2002-01-01

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

  3. Teaching Large Evening Classes

    Science.gov (United States)

    Wambuguh, Oscar

    2008-01-01

    High enrollments, conflicting student work schedules, and the sheer convenience of once-a-week classes are pushing many colleges to schedule evening courses. Held from 6 to 9 pm or 7 to 10 pm, these classes are typically packed, sometimes with more than 150 students in a large lecture theater. How can faculty effectively teach, control, or even…

  4. Universality classes of inflation

    NARCIS (Netherlands)

    Roest, Diederik

    2014-01-01

    We investigate all single-field, slow-roll inflationary models whose slow-roll parameters scale as 1/N in the limit of a large number of e-folds N. We proof that all such models belong to two universality classes, characterised by a single parameter. One class contains small field models like hillto

  5. DEFINING THE MIDDLE CLASS

    Institute of Scientific and Technical Information of China (English)

    WANG HAIRONG

    2011-01-01

    China's cities housed more than 230 million middle-class residents in 2009ot 37 percent of the urban population,according to the 2011 Blue Book of Cities in China released on August 3.In China's main urban centers,Beijing and Shanghai,the middle class accounted for 46 percent and 38 percent,respectively,of the local population.

  6. Teaching Social Class

    Science.gov (United States)

    Tablante, Courtney B.; Fiske, Susan T.

    2015-01-01

    Discussing socioeconomic status in college classes can be challenging. Both teachers and students feel uncomfortable, yet social class matters more than ever. This is especially true, given increased income inequality in the United States and indications that higher education does not reduce this inequality as much as many people hope. Resources…

  7. The Last Class

    Science.gov (United States)

    Uhl, Christopher

    2005-01-01

    The last class of the semester is like a goodbye. It can be cold and perfunctory or warm and heartfelt. For many years, I erred on the side of "cold and perfunctory." No more. Now my last classes are a time of celebration and ritual as I invite students to focus on qualities such as acceptance and gratitude.

  8. Class in disguise

    DEFF Research Database (Denmark)

    Faber, Stine Thidemann; Prieur, Annick

    This paper asks how class can have importance in one of the worlds’ most equal societies: Denmark. The answer is that class here appears in disguised forms. The field under study is a city, Aalborg, in the midst of transition from a stronghold of industrialism to a post industrial economy...

  9. DEFINING THE MIDDLE CLASS

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Classifying the middle class remains controversial despite its alleged growth China’s cities housed more than 230 million middle-class residents in 2009 or 37 percent of the urban population,according to the 2011 Blue Book of Cities in China released on August 3.

  10. Survey on Text Document Clustering

    OpenAIRE

    M.Thangamani; Dr.P.Thangaraj

    2010-01-01

    Document clustering is also referred as text clustering, and its concept is merely equal to data clustering. It is hardly difficult to find the selective information from an ‘N’number of series information, so that document clustering came into picture. Basically cluster means a group of similar data, document clustering means segregating the data into different groups of similar data. Clustering can be of mathematical, statistical or numerical domain. Clustering is a fundamental data analysi...

  11. A Novel Clustering Algorithm Inspired by Membrane Computing

    Directory of Open Access Journals (Sweden)

    Hong Peng

    2015-01-01

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

  12. Electronic Structure and Geometries of Small Compound Metal Clusters

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-04-14

    During the tenure of the DOE grant DE-FG05-87EI145316 we have concentrated on equilibrium geometries, stability, and the electronic structure of transition metal-carbon clusters (met-cars), clusters designed to mimic the chemistry of atoms, and reactivity of homo-nuclear metal clusters and ions with various reactant molecules. It is difficult to describe all the research the authors have accomplished as they have published 38 papers. In this report, they outline briefly the salient features of their work on the following topics: (1) Designer Clusters: Building Blocks for a New Class of Solids; (2) Atomic Structure, Stability, and Electronic Properties of Metallo-Carbohedrenes; (3) Reactivity of Metal Clusters with H{sub 2} and NO; and (4) Anomalous Spectroscopy of Li{sub 4} Clusters.

  13. Chaotic map clustering algorithm for EEG analysis

    Science.gov (United States)

    Bellotti, R.; De Carlo, F.; Stramaglia, S.

    2004-03-01

    The non-parametric chaotic map clustering algorithm has been applied to the analysis of electroencephalographic signals, in order to recognize the Huntington's disease, one of the most dangerous pathologies of the central nervous system. The performance of the method has been compared with those obtained through parametric algorithms, as K-means and deterministic annealing, and supervised multi-layer perceptron. While supervised neural networks need a training phase, performed by means of data tagged by the genetic test, and the parametric methods require a prior choice of the number of classes to find, the chaotic map clustering gives a natural evidence of the pathological class, without any training or supervision, thus providing a new efficient methodology for the recognition of patterns affected by the Huntington's disease.

  14. Loop groups, Clusters, Dimers and Integrable systems

    CERN Document Server

    Fock, V V

    2014-01-01

    We describe a class of integrable systems on Poisson submanifolds of the affine Poisson-Lie groups $\\widehat{PGL}(N)$, which can be enumerated by cyclically irreducible elements the co-extended affine Weyl groups $(\\widehat{W}\\times \\widehat{W})^\\sharp$. Their phase spaces admit cluster coordinates, whereas the integrals of motion are cluster functions. We show, that this class of integrable systems coincides with the constructed by Goncharov and Kenyon out of dimer models on a two-dimensional torus and classified by the Newton polygons. We construct the correspondence between the Weyl group elements and polygons, demonstrating that each particular integrable model admits infinitely many realisations on the Poisson-Lie groups. We also discuss the particular examples, including the relativistic Toda chains and the Schwartz-Ovsienko-Tabachnikov pentagram map.

  15. Agricultural Clusters in the Netherlands

    NARCIS (Netherlands)

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

    2012-01-01

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

  16. Endogenous Small RNA Clusters in Plants

    Institute of Scientific and Technical Information of China (English)

    Yong-Xin Liu; Meng Wang; Xiu-Jie Wang

    2014-01-01

    In plants, small RNAs (sRNAs) usually refer to non-coding RNAs (ncRNAs) with lengths of 20-24 nucleotides. sRNAs are involved in the regulation of many essential processes related to plant development and environmental responses. sRNAs in plants are mainly grouped into microRNAs (miRNAs) and small interfering RNAs (siRNAs), and the latter can be further classified into trans-acting siRNAs (ta-siRNAs), repeat-associated siRNAs (ra-siRNAs), natural anti-sense siRNAs (nat-siRNAs), etc. Many sRNAs exhibit a clustered distribution pattern in the genome. Here, we summarize the features and functions of cluster-distributed sRNAs, aimed to not only provide a thorough picture of sRNA clusters (SRCs) in plants, but also shed light on the identification of new classes of functional sRNAs.

  17. COOL CORE CLUSTERS FROM COSMOLOGICAL SIMULATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Rasia, E.; Borgani, S.; Murante, G.; Planelles, S.; Biffi, V.; Granato, G. L. [INAF, Osservatorio Astronomico di Trieste, via Tiepolo 11, I-34131, Trieste (Italy); Beck, A. M.; Steinborn, L. K.; Dolag, K. [Universitäts-Sternwarte München, Scheinerstr.1, D-81679 München (Germany); Ragone-Figueroa, C., E-mail: rasia@oats.inaf.it [Instituto de Astronomá Teórica y Experimental (IATE), Consejo Nacional de Investigaciones Cientiíficas y Técnicas de la República Argentina (CONICET), Observatorio Astronómico, Universidad Nacional de Córdoba, Laprida 854, X5000BGR, Córdoba (Argentina)

    2015-11-01

    We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and active galactic nucleus (AGN) feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of CC systems, to nearly flat core isentropic profiles, characteristic of NCC systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and observations. Furthermore, we also find that simulated CC clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic CC structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.

  18. Mapping Cigarettes Similarities using Cluster Analysis Methods

    Directory of Open Access Journals (Sweden)

    Lorentz Jäntschi

    2007-09-01

    Full Text Available The aim of the research was to investigate the relationship and/or occurrences in and between chemical composition information (tar, nicotine, carbon monoxide, market information (brand, manufacturer, price, and public health information (class, health warning as well as clustering of a sample of cigarette data. A number of thirty cigarette brands have been analyzed. Six categorical (cigarette brand, manufacturer, health warnings, class and four continuous (tar, nicotine, carbon monoxide concentrations and package price variables were collected for investigation of chemical composition, market information and public health information. Multiple linear regression and two clusterization techniques have been applied. The study revealed interesting remarks. The carbon monoxide concentration proved to be linked with tar and nicotine concentration. The applied clusterization methods identified groups of cigarette brands that shown similar characteristics. The tar and carbon monoxide concentrations were the main criteria used in clusterization. An analysis of a largest sample could reveal more relevant and useful information regarding the similarities between cigarette brands.

  19. Clustering Categorical Data:A Cluster Ensemble Approach

    Institute of Scientific and Technical Information of China (English)

    He Zengyou(何增友); Xu Xiaofei; Deng Shengchun

    2003-01-01

    Clustering categorical data, an integral part of data mining,has attracted much attention recently. In this paper, the authors formally define the categorical data clustering problem as an optimization problem from the viewpoint of cluster ensemble, and apply cluster ensemble approach for clustering categorical data. Experimental results on real datasets show that better clustering accuracy can be obtained by comparing with existing categorical data clustering algorithms.

  20. Spatial Scan Statistic: Selecting clusters and generating elliptic clusters

    DEFF Research Database (Denmark)

    Christiansen, Lasse Engbo; Andersen, Jens Strodl

    2004-01-01

    The spatial scan statistic is widely used to search for clusters. This paper shows that the usually applied elimination of overlapping clusters to find secondary clusters is sensitive to smooth changes in the shape of the clusters. We present an algorithm for generation of set of confocal elliptic...... clusters. In addition, we propose a new way to present the information in a given set of clusters based on the significance of the clusters....

  1. Cosmology with cluster surveys

    Indian Academy of Sciences (India)

    Subhabrata Majumdar

    2004-10-01

    Surveys of clusters of galaxies provide us with a powerful probe of the density and nature of the dark energy. The red-shift distribution of detected clusters is highly sensitive to the dark energy equation of state parameter . Upcoming Sunyaev–Zel'dovich (SZ) surveys would provide us large yields of clusters to very high red-shifts. Self-calibration of cluster scaling relations, possible for such a huge sample, would be able to constrain systematic biases on mass estimators. Combining cluster red-shift abundance with limited mass follow-up and cluster mass power spectrum can then give constraints on , as well as on 8 and to a few per cents.

  2. CSR in Industrial Clusters

    DEFF Research Database (Denmark)

    Lund-Thomsen, Peter; Pillay, Renginee G.

    2012-01-01

    Purpose – The paper seeks to review the literature on CSR in industrial clusters in developing countries, identifying the main strengths, weaknesses, and gaps in this literature, pointing to future research directions and policy implications in the area of CSR and industrial cluster development...... in this field and their comments incorporated in the final version submitted to Corporate Governance. Findings – The article traces the origins of the debate on industrial clusters and CSR in developing countries back to the early 1990s when clusters began to be seen as an important vehicle for local economic...... development in the South. At the turn of the millennium the industrial cluster debate expanded as clusters were perceived as a potential source of poverty reduction, while their role in promoting CSR among small and medium-sized enterprises began to take shape from 2006 onwards. At present, there is still...

  3. Melting of sodium clusters

    CERN Document Server

    Reyes-Nava, J A; Beltran, M R; Michaelian, K

    2002-01-01

    Thermal stability properties and the melting-like transition of Na_n, n=13-147, clusters are studied through microcanonical molecular dynamics simulations. The metallic bonding in the sodium clusters is mimicked by a many-body Gupta potential based on the second moment approximation of a tight-binding Hamiltonian. The characteristics of the solid-to-liquid transition in the sodium clusters are analyzed by calculating physical quantities like caloric curves, heat capacities, and root-mean-square bond length fluctuations using simulation times of several nanoseconds. Distinct melting mechanisms are obtained for the sodium clusters in the size range investigated. The calculated melting temperatures show an irregular variation with the cluster size, in qualitative agreement with recent experimental results. However, the calculated melting point for the Na_55 cluster is about 40 % lower than the experimental value.

  4. Social Class Dialogues and the Fostering of Class Consciousness

    Science.gov (United States)

    Madden, Meredith

    2015-01-01

    How do critical pedagogies promote undergraduate students' awareness of social class, social class identity, and social class inequalities in education? How do undergraduate students experience class consciousness-raising in the intergroup dialogue classroom? This qualitative study explores undergraduate students' class consciousness-raising in an…

  5. Structures in Galaxy Clusters

    CERN Document Server

    Escalera, E; Girardi, M; Giuricin, G; Mardirossian, F; Mazure, A; Mezzetti, M

    1993-01-01

    The analysis of the presence of substructures in 16 well-sampled clusters of galaxies suggests a stimulating hypothesis: Clusters could be classified as unimodal or bimodal, on the basis of to the sub-clump distribution in the {\\em 3-D} space of positions and velocities. The dynamic study of these clusters shows that their fundamental characteristics, in particular the virial masses, are not severely biased by the presence of subclustering if the system considered is bound.

  6. Cluster Symmetries and Dynamics

    Directory of Open Access Journals (Sweden)

    Freer Martin

    2016-01-01

    Full Text Available Many light nuclei display behaviour that indicates that rather than behaving as an A-body systems, the protons and neutrons condense into clusters. The α-particle is the most obvious example of such clustering. This contribution examines the role of such α-clustering on the structure, symmetries and dynamics of the nuclei 8Be, 12C and 16O, recent experimental measurements and future perspectives.

  7. Clustering Techniques in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Muhammad Ali Masood

    2015-01-01

    Full Text Available Dealing with data means to group information into a set of categories either in order to learn new artifacts or understand new domains. For this purpose researchers have always looked for the hidden patterns in data that can be defined and compared with other known notions based on the similarity or dissimilarity of their attributes according to well-defined rules. Data mining, having the tools of data classification and data clustering, is one of the most powerful techniques to deal with data in such a manner that it can help researchers identify the required information. As a step forward to address this challenge, experts have utilized clustering techniques as a mean of exploring hidden structure and patterns in underlying data. Improved stability, robustness and accuracy of unsupervised data classification in many fields including pattern recognition, machine learning, information retrieval, image analysis and bioinformatics, clustering has proven itself as a reliable tool. To identify the clusters in datasets algorithm are utilized to partition data set into several groups based on the similarity within a group. There is no specific clustering algorithm, but various algorithms are utilized based on domain of data that constitutes a cluster and the level of efficiency required. Clustering techniques are categorized based upon different approaches. This paper is a survey of few clustering techniques out of many in data mining. For the purpose five of the most common clustering techniques out of many have been discussed. The clustering techniques which have been surveyed are: K-medoids, K-means, Fuzzy C-means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN and Self-Organizing Map (SOM clustering.

  8. 15th Cluster workshop

    CERN Document Server

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

    2010-01-01

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

  9. Galaxy Clusters with Chandra

    CERN Document Server

    Forman, W; Markevitch, M L; Vikhlinin, A A; Churazov, E

    2002-01-01

    We discuss Chandra results related to 1) cluster mergers and cold fronts and 2) interactions between relativistic plasma and hot cluster atmospheres. We describe the properties of cold fronts using NGC1404 in the Fornax cluster and A3667 as examples. We discuss multiple surface brightness discontinuities in the cooling flow cluster ZW3146. We review the supersonic merger underway in CL0657. Finally, we summarize the interaction between plasma bubbles produced by AGN and hot gas using M87 and NGC507 as examples.

  10. Management of cluster headache.

    Science.gov (United States)

    Tfelt-Hansen, Peer C; Jensen, Rigmor H

    2012-07-01

    The prevalence of cluster headache is 0.1% and cluster headache is often not diagnosed or misdiagnosed as migraine or sinusitis. In cluster headache there is often a considerable diagnostic delay - an average of 7 years in a population-based survey. Cluster headache is characterized by very severe or severe orbital or periorbital pain with a duration of 15-180 minutes. The cluster headache attacks are accompanied by characteristic associated unilateral symptoms such as tearing, nasal congestion and/or rhinorrhoea, eyelid oedema, miosis and/or ptosis. In addition, there is a sense of restlessness and agitation. Patients may have up to eight attacks per day. Episodic cluster headache (ECH) occurs in clusters of weeks to months duration, whereas chronic cluster headache (CCH) attacks occur for more than 1 year without remissions. Management of cluster headache is divided into acute attack treatment and prophylactic treatment. In ECH and CCH the attacks can be treated with oxygen (12 L/min) or subcutaneous sumatriptan 6 mg. For both oxygen and sumatriptan there are two randomized, placebo-controlled trials demonstrating efficacy. In both ECH and CCH, verapamil is the prophylactic drug of choice. Verapamil 360 mg/day was found to be superior to placebo in one clinical trial. In clinical practice, daily doses of 480-720 mg are mostly used. Thus, the dose of verapamil used in cluster headache treatment may be double the dose used in cardiology, and with the higher doses the PR interval should be checked with an ECG. At the start of a cluster, transitional preventive treatment such as corticosteroids or greater occipital nerve blockade can be given. In CCH and in long-standing clusters of ECH, lithium, methysergide, topiramate, valproic acid and ergotamine tartrate can be used as add-on prophylactic treatment. In drug-resistant CCH, neuromodulation with either occipital nerve stimulation or deep brain stimulation of the hypothalamus is an alternative treatment strategy

  11. Nanophase materials assembled from clusters

    Energy Technology Data Exchange (ETDEWEB)

    Siegel, R.W.

    1992-02-01

    The preparation of metal and ceramic atom clusters by means of the gas-condensation method, followed by their in situ collection and consolidation under high-vacuum conditions, has recently led to the synthesis of a new class of ultrafine-grained materials. These nanophase materials, with typical average grain sizes of 5 to 50 nm and, hence, a large fraction of their atoms in interfaces, exhibit properties that are often considerably improved relative to those of conventional materials. Furthermore, their synthesis and processing characteristics should enable the design of new materials with unique properties. Some examples are ductile ceramics that can be formed and sintered to full density at low temperatures without the need for binding or sintering aids, and metals with dramatically increased strength. The synthesis of these materials is briefly described along with what is presently known of their structure and properties. Their future impact on materials science and technology is also considered.

  12. PSYCH 515 Complete Class

    OpenAIRE

    admin

    2015-01-01

      PSYCH 515 Advanced Abnormal Psychology To purchase this material click on below link http://www.assignmentcloud.com/PSYCH-515/PSYCH-515-Complete-Class-Guide For more details www.assignmentcloud.com

  13. Raradox of class description

    Institute of Scientific and Technical Information of China (English)

    吕光

    2004-01-01

    We have a more active class atmophere, but more passive self-study situations. We are too talktive when we should bury ourselves in books, but too less efficient when we spend too much time. We complain teachers

  14. IELP Class Observation

    Institute of Scientific and Technical Information of China (English)

    陈了了

    2010-01-01

    @@ As an exchange student majoring in English, I am curious about how English is taught to international students here in America. Therefore, I observed an IELP (Intensive English Learning Program) class in Central Connecticut State University where I study.

  15. Teaching Heterogeneous Classes.

    Science.gov (United States)

    Millrood, Radislav

    2002-01-01

    Discusses an approach to teaching heterogeneous English-as-a-Second/Foreign-Language classes. Draws on classroom research data to describe the features of a success-building lesson context. (Author/VWL)

  16. A class in astrobiology

    Science.gov (United States)

    Airieau, S. A.

    1999-09-01

    The goal of this class is to provide basic astrobiology knowledge to upper division science students. The scope is broad and in-depth coverage is not possible in this introductory course. Instead, science students from various branches of academia can acquire a broad basis and understanding of the other fields: astronomy, biology, geology, biochemistry, planetary and space sciences. The class is highly modular and allows instructors to concentrate on or eliminate topics according to their priorities and preferences.

  17. Nordic Walking Classes

    CERN Multimedia

    Fitness Club

    2015-01-01

    Four classes of one hour each are held on Tuesdays. RDV barracks parking at Entrance A, 10 minutes before class time. Spring Course 2015: 05.05/12.05/19.05/26.05 Prices 40 CHF per session + 10 CHF club membership 5 CHF/hour pole rental Check out our schedule and enroll at: https://espace.cern.ch/club-fitness/Lists/Nordic%20Walking/NewForm.aspx? Hope to see you among us! fitness.club@cern.ch

  18. Generalized Fourier transforms classes

    DEFF Research Database (Denmark)

    Berntsen, Svend; Møller, Steen

    2002-01-01

    The Fourier class of integral transforms with kernels $B(\\omega r)$ has by definition inverse transforms with kernel $B(-\\omega r)$. The space of such transforms is explicitly constructed. A slightly more general class of generalized Fourier transforms are introduced. From the general theory foll...... follows that integral transform with kernels which are products of a Bessel and a Hankel function or which is of a certain general hypergeometric type have inverse transforms of the same structure....

  19. Embodying class and gender

    OpenAIRE

    Geers, Alexie

    2015-01-01

    In March 1937, when the first issue of Marie-Claire was published, the images of the female body it presented to its female readers from working-class backgrounds contrasted sharply with those featured in previous magazines. The female bodies are dressed and groomed to seduce and replace the hieratic bodies that presented fashions synonymous with membership in the upper classes. The present essay examines this shift and shows that the visual repertoire employed is borrowed from that of the fe...

  20. Coping With New Challengens for Density-Based Clustering

    OpenAIRE

    Kröger, Peer

    2004-01-01

    Knowledge Discovery in Databases (KDD) is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data. The core step of the KDD process is the application of a Data Mining algorithm in order to produce a particular enumeration of patterns and relationships in large databases. Clustering is one of the major data mining tasks and aims at grouping the data objects into meaningful classes (clusters) such that the similarity of objects wi...

  1. Hydrometeor classification from polarimetric radar measurements: a clustering approach

    OpenAIRE

    Grazioli, Jacopo; Tuia, Devis; Berne, Alexis

    2015-01-01

    A data-driven approach to the classification of hydrometeors from measurements collected with polarimetric weather radars is proposed. In a first step, the optimal number of hydrometeor classes (nopt) that can be reliably identified from a large set of polarimetric data is determined. This is done by means of an unsupervised clustering technique guided by criteria related both to data similarity and to spatial smoothness of the classified images. In a second step, the nopt clusters are assign...

  2. Document Clustering Based on Semi-Supervised Term Clustering

    Directory of Open Access Journals (Sweden)

    Hamid Mahmoodi

    2012-05-01

    Full Text Available The study is conducted to propose a multi-step feature (term selection process and in semi-supervised fashion, provide initial centers for term clusters. Then utilize the fuzzy c-means (FCM clustering algorithm for clustering terms. Finally assign each of documents to closest associated term clusters. While most text clustering algorithms directly use documents for clustering, we propose to first group the terms using FCM algorithm and then cluster documents based on terms clusters. We evaluate effectiveness of our technique on several standard text collections and compare our results with the some classical text clustering algorithms.

  3. Cluster algebras of finite mutation type via unfoldings

    CERN Document Server

    Felikson, Anna; Tumarkin, Pavel

    2010-01-01

    We complete classification of mutation-finite cluster algebras by extending the technique derived by Fomin, Shapiro, and Thurston to skew-symmetrizable case. We show that every mutation-finite skew-symmetrizable matrix admits an unfolding which embeds the mutation class of mutation-finite skew-symmetrizable matrix to the mutation class of some mutation-finite skew-symmetric matrix. In particular, this establishes a correspondence between almost all skew-symmetrizable mutation-finite cluster algebras and triangulated marked bordered surfaces.

  4. Critical exponents from cluster coefficients

    Science.gov (United States)

    Rotman, Z.; Eisenberg, E.

    2009-09-01

    For a large class of repulsive interaction models, the Mayer cluster integrals can be transformed into a tridiagonal real symmetric matrix Rmn , whose elements converge to two constants. This allows for an effective extrapolation of the equation of state for these models. Due to a nearby (nonphysical) singularity on the negative real z axis, standard methods (e.g., Padé approximants based on the cluster integrals expansion) fail to capture the behavior of these models near the ordering transition, and, in particular, do not detect the critical point. A recent work [E. Eisenberg and A. Baram, Proc. Natl. Acad. Sci. U.S.A. 104, 5755 (2007)] has shown that the critical exponents σ and σ' , characterizing the singularity of the density as a function of the activity, can be exactly calculated if the decay of the R matrix elements to their asymptotic constant follows a 1/n2 law. Here we employ renormalization group (RG) arguments to extend this result and analyze cases for which the asymptotic approach of the R matrix elements toward their limiting value is of a more general form. The relevant asymptotic correction terms (in RG sense) are identified, and we then present a corrected exact formula for the critical exponents. We identify the limits of usage of the formula and demonstrate one physical model, which is beyond its range of validity. The formula is validated numerically and then applied to analyze a number of concrete physical models.

  5. Solving Data Clustering with the Hybrid PSO

    Directory of Open Access Journals (Sweden)

    Li Qi

    2013-05-01

    Full Text Available Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. The term “clustering” is used in several research communities to describe methods for grouping of unlabeled data. These communities have different terminologies and assumptions for the components of the clustering process and the context in which clustering is used. This paper looks into the use of Particle Swarm Optimization (PSO for cluster analysis. In standard PSO the non-oscillatory route can quickly cause a particle to stagnate and also it may prematurely converge on suboptimal solutions that are not even guaranteed to local optimal solution. In this paper a modification strategy is proposed for the particle swarm optimization (PSO algorithm and applied in the data sets. This paper provides a method for particles to steer clear off from local stagnation and the local search is applied to improve the goodness of fitting. The effectiveness of this concept is demonstrated by cluster analysis. Results show that the model provides enhanced performance and maintains more diversity in the swarm and thereby allows the particles to be robust to trace the changing environment.

  6. From collisions to clusters

    DEFF Research Database (Denmark)

    Loukonen, Ville; Bork, Nicolai; Vehkamaki, Hanna

    2014-01-01

    to overcome the possible initial non-optimal collision orientations. No post-collisional cluster break up is observed. The reasons for the efficient clustering are (i) the proton transfer reaction which takes place in each of the collision simulations and (ii) the subsequent competition over the proton...

  7. Cost-Effective Clustering

    CERN Document Server

    Gottlieb, S

    2001-01-01

    Small Beowulf clusters can effectively serve as personal or group supercomputers. In such an environment, a cluster can be optimally designed for a specific problem (or a small set of codes). We discuss how theoretical analysis of the code and benchmarking on similar hardware lead to optimal systems.

  8. Coma cluster of galaxies

    Science.gov (United States)

    1999-01-01

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

  9. Clustering Text Data Streams

    Institute of Scientific and Technical Information of China (English)

    Yu-Bao Liu; Jia-Rong Cai; Jian Yin; Ada Wai-Chee Fu

    2008-01-01

    Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organization and topic detection and tracing etc. However, most methods are similarity-based approaches and only use the TF*IDF scheme to represent the semantics of text data and often lead to poor clustering quality. Recently, researchers argue that semantic smoothing model is more efficient than the existing TF.IDF scheme for improving text clustering quality. However, the existing semantic smoothing model is not suitable for dynamic text data context. In this paper, we extend the semantic smoothing model into text data streams context firstly. Based on the extended model, we then present two online clustering algorithms OCTS and OCTSM for the clustering of massive text data streams. In both algorithms, we also present a new cluster statistics structure named cluster profile which can capture the semantics of text data streams dynamically and at the same time speed up the clustering process. Some efficient implementations for our algorithms are also given. Finally, we present a series of experimental results illustrating the effectiveness of our technique.

  10. Brightest Cluster Galaxy Identification

    Science.gov (United States)

    Leisman, Luke; Haarsma, D. B.; Sebald, D. A.; ACCEPT Team

    2011-01-01

    Brightest cluster galaxies (BCGs) play an important role in several fields of astronomical research. The literature includes many different methods and criteria for identifying the BCG in the cluster, such as choosing the brightest galaxy, the galaxy nearest the X-ray peak, or the galaxy with the most extended profile. Here we examine a sample of 75 clusters from the Archive of Chandra Cluster Entropy Profile Tables (ACCEPT) and the Sloan Digital Sky Survey (SDSS), measuring masked magnitudes and profiles for BCG candidates in each cluster. We first identified galaxies by hand; in 15% of clusters at least one team member selected a different galaxy than the others.We also applied 6 other identification methods to the ACCEPT sample; in 30% of clusters at least one of these methods selected a different galaxy than the other methods. We then developed an algorithm that weighs brightness, profile, and proximity to the X-ray peak and centroid. This algorithm incorporates the advantages of by-hand identification (weighing multiple properties) and automated selection (repeatable and consistent). The BCG population chosen by the algorithm is more uniform in its properties than populations selected by other methods, particularly in the relation between absolute magnitude (a proxy for galaxy mass) and average gas temperature (a proxy for cluster mass). This work supported by a Barry M. Goldwater Scholarship and a Sid Jansma Summer Research Fellowship.

  11. Blue emitting undecaplatinum clusters

    Science.gov (United States)

    Chakraborty, Indranath; Bhuin, Radha Gobinda; Bhat, Shridevi; Pradeep, T.

    2014-07-01

    A blue luminescent 11-atom platinum cluster showing step-like optical features and the absence of plasmon absorption was synthesized. The cluster was purified using high performance liquid chromatography (HPLC). Electrospray ionization (ESI) and matrix assisted laser desorption ionization (MALDI) mass spectrometry (MS) suggest a composition, Pt11(BBS)8, which was confirmed by a range of other experimental tools. The cluster is highly stable and compatible with many organic solvents.A blue luminescent 11-atom platinum cluster showing step-like optical features and the absence of plasmon absorption was synthesized. The cluster was purified using high performance liquid chromatography (HPLC). Electrospray ionization (ESI) and matrix assisted laser desorption ionization (MALDI) mass spectrometry (MS) suggest a composition, Pt11(BBS)8, which was confirmed by a range of other experimental tools. The cluster is highly stable and compatible with many organic solvents. Electronic supplementary information (ESI) available: Details of experimental procedures, instrumentation, chromatogram of the crude cluster; SEM/EDAX, DLS, PXRD, TEM, FT-IR, and XPS of the isolated Pt11 cluster; UV/Vis, MALDI MS and SEM/EDAX of isolated 2 and 3; and 195Pt NMR of the K2PtCl6 standard. See DOI: 10.1039/c4nr02778g

  12. Social class and body weight among Chinese urban adults: the role of the middle classes in the nutrition transition.

    Science.gov (United States)

    Bonnefond, Céline; Clément, Matthieu

    2014-07-01

    While a plethoric empirical literature addresses the relationship between socio-economic status and body weight, little is known about the influence of social class on nutritional outcomes, particularly in developing countries. The purpose of this article is to contribute to the analysis of the social determinants of adult body weight in urban China by taking into account the influence of social class. More specifically, we propose to analyse the position of the Chinese urban middle class in terms of being overweight or obese. The empirical investigations conducted as part of this research are based on a sample of 1320 households and 2841 adults from the China Health and Nutrition Survey for 2009. For the first step, we combine an economic approach and a sociological approach to identify social classes at household level. First, households with an annual per capita income between 10,000 Yuan and the 95th income percentile are considered as members of the middle class. Second, we strengthen the characterization of the middle class using information on education and employment. By applying clustering methods, we identify four groups: the elderly and inactive middle class, the old middle class, the lower middle class and the new middle class. For the second step, we implement an econometric analysis to assess the influence of social class on adult body mass index and on the probability of being overweight or obese. We use multinomial treatment regressions to deal with the endogeneity of the social class variable. Our results show that among the four subgroups of the urban middle class, the new middle class is the only one to be relatively well-protected against obesity. We suggest that this group plays a special role in adopting healthier food consumption habits and seems to be at a more advanced stage of the nutrition transition. PMID:24788113

  13. Investigation of Cluster and Cluster Queuing System

    OpenAIRE

    Halifu, Saerda

    2008-01-01

    Cluster became main platform as parallel and distributed computing structure for high performance computing. Following the development of high performance computer architecture more and more different branches of natural science benefit fromhuge and efficient computational power. For instance bio-informatics, climate science, computational physics, computational chemistry, marine science, etc. Efficient and reliable computing powermay not only expending demand of existing high performance com...

  14. The Cluster Substructure - Alignment Connection

    CERN Document Server

    Plionis, M

    2002-01-01

    Using the APM cluster data we investigate whether the dynamical status of clusters is related to the large-scale structure of the Universe. We find that cluster substructure is strongly correlated with the tendency of clusters to be aligned with their nearest neighbour and in general with the nearby clusters that belong to the same supercluster. Furthermore, dynamically young clusters are more clustered than the overall cluster population. These are strong indications that cluster develop in a hierarchical fashion by anisotropy merging along the large-scale filamentary superclusters within which they are embedded.

  15. Job Oriented Monitoring Clusters

    Directory of Open Access Journals (Sweden)

    Vijayalaxmi Cigala,

    2011-03-01

    Full Text Available There has been a lot of development in the field of clusters and grids. Recently, the use of clusters has been on rise in every possible field. This paper proposes a system that monitors jobs onlarge computational clusters. Monitoring jobs is essential to understand how jobs are being executed. This helps us in understanding the complete life cycle of the jobs being executed on large clusters. Also, this paper describes how the information obtained by monitoring the jobs would help in increasing the overall throughput of clusters. Heuristics help in efficient job distribution among the computational nodes, thereby accomplishing fair job distribution policy. The proposed system would be capable of loadbalancing among the computational nodes, detecting failures, taking corrective actions after failure detection, job monitoring, system resource monitoring, etc.

  16. Pulsars in Globular Clusters

    CERN Document Server

    Camilo, F; Camilo, Fernando; Rasio, Frederic A.

    2005-01-01

    More than 100 radio pulsars have been detected in 24 globular clusters. The largest observed samples are in Terzan 5 and 47 Tucanae, which together contain 45 pulsars. Accurate timing solutions, including positions in the cluster, are known for many of these pulsars. Here we provide an observational overview of some properties of pulsars in globular clusters, as well as properties of the globular clusters with detected pulsars. The many recent detections also provide a new opportunity to re-examine theoretically the formation and evolution of recycled pulsars in globular clusters. Our brief review considers the most important dynamical interaction and binary evolution processes: collisions, exchange interactions, mass transfer, and common-envelope phases.

  17. Mathematical classification and clustering

    CERN Document Server

    Mirkin, Boris

    1996-01-01

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

  18. On TPC cluster reconstruction

    CERN Document Server

    Dydak, F; Nefedov, Y; Wotschack, J; Zhemchugov, A

    2004-01-01

    For a bias-free momentum measurement of TPC tracks, the correct determination of cluster positions is mandatory. We argue in particular that (i) the reconstruction of the entire longitudinal signal shape in view of longitudinal diffusion, electronic pulse shaping, and track inclination is important both for the polar angle reconstruction and for optimum r phi resolution; and that (ii) self-crosstalk of pad signals calls for special measures for the reconstruction of the z coordinate. The problem of 'shadow clusters' is resolved. Algorithms are presented for accepting clusters as 'good' clusters, and for the reconstruction of the r phi and z cluster coordinates, including provisions for 'bad' pads and pads next to sector boundaries, respectively.

  19. Cool Cluster Correctly Correlated

    Energy Technology Data Exchange (ETDEWEB)

    Sergey Aleksandrovich Varganov

    2005-12-17

    Atomic clusters are unique objects, which occupy an intermediate position between atoms and condensed matter systems. For a long time it was thought that physical and chemical properties of atomic dusters monotonically change with increasing size of the cluster from a single atom to a condensed matter system. However, recently it has become clear that many properties of atomic clusters can change drastically with the size of the clusters. Because physical and chemical properties of clusters can be adjusted simply by changing the cluster's size, different applications of atomic clusters were proposed. One example is the catalytic activity of clusters of specific sizes in different chemical reactions. Another example is a potential application of atomic clusters in microelectronics, where their band gaps can be adjusted by simply changing cluster sizes. In recent years significant advances in experimental techniques allow one to synthesize and study atomic clusters of specified sizes. However, the interpretation of the results is often difficult. The theoretical methods are frequently used to help in interpretation of complex experimental data. Most of the theoretical approaches have been based on empirical or semiempirical methods. These methods allow one to study large and small dusters using the same approximations. However, since empirical and semiempirical methods rely on simple models with many parameters, it is often difficult to estimate the quantitative and even qualitative accuracy of the results. On the other hand, because of significant advances in quantum chemical methods and computer capabilities, it is now possible to do high quality ab-initio calculations not only on systems of few atoms but on clusters of practical interest as well. In addition to accurate results for specific clusters, such methods can be used for benchmarking of different empirical and semiempirical approaches. The atomic clusters studied in this work contain from a few atoms

  20. Cluster ion beam evaporation

    International Nuclear Information System (INIS)

    Cluster ions can be made by the supercooling due to adiabatic expansion of substances to be vaporized which are ejected from a nozzle. This paper is described on the recent progress of studies concerning the cluster beam. The technique of cluster ion beam has been applied for the studies of thermonuclear plasma, the fabrication of thin films, crystal growth and electronic devices. The density of cluster ion beam is larger than that of atomic ion beam, and the formation of thin films can be easily done in high vacuum. This method is also useful for epitaxial growth. Metallic vapour cluster beam was made by the help of jetting rare gas beam. Various beam sources were developed. The characteristics of these sources were measured and analyzed. (Kato, T.)

  1. Concurrent conditional clustering of multiple networks: COCONETS.

    Directory of Open Access Journals (Sweden)

    Sabrina Kleessen

    Full Text Available The accumulation of high-throughput data from different experiments has facilitated the extraction of condition-specific networks over the same set of biological entities. Comparing and contrasting of such multiple biological networks is in the center of differential network biology, aiming at determining general and condition-specific responses captured in the network structure (i.e., included associations between the network components. We provide a novel way for comparison of multiple networks based on determining network clustering (i.e., partition into communities which is optimal across the set of networks with respect to a given cluster quality measure. To this end, we formulate the optimization-based problem of concurrent conditional clustering of multiple networks, termed COCONETS, based on the modularity. The solution to this problem is a clustering which depends on all considered networks and pinpoints their preserved substructures. We present theoretical results for special classes of networks to demonstrate the implications of conditionality captured by the COCONETS formulation. As the problem can be shown to be intractable, we extend an existing efficient greedy heuristic and applied it to determine concurrent conditional clusters on coexpression networks extracted from publically available time-resolved transcriptomics data of Escherichia coli under five stresses as well as on metabolite correlation networks from metabolomics data set from Arabidopsis thaliana exposed to eight environmental conditions. We demonstrate that the investigation of the differences between the clustering based on all networks with that obtained from a subset of networks can be used to quantify the specificity of biological responses. While a comparison of the Escherichia coli coexpression networks based on seminal properties does not pinpoint biologically relevant differences, the common network substructures extracted by COCONETS are supported by

  2. Two steps in the evolution of Antennapedia-class vertebrate homeobox genes.

    OpenAIRE

    Kappen, C. (Christian); Schughart, K; Ruddle, F H

    1989-01-01

    Antennapedia-class vertebrate homeobox genes have been classified with regard to their chromosomal locations and nucleotide sequence similarities within the 183-base-pair homeobox domain. The results of these comparisons support the view that in mammals and most likely the vertebrates, four clusters of homeobox genes exist that were created by duplications of an entire primordial gene cluster. We present evidence that this primordial cluster arose by local gene duplications of homeoboxes that...

  3. Issues,Challenges and Tools of Clustering Algorithms

    CERN Document Server

    Agarwal, Parul; Biswas, Ranjit

    2011-01-01

    Clustering is an unsupervised technique of Data Mining. It means grouping similar objects together and separating the dissimilar ones. Each object in the data set is assigned a class label in the clustering process using a distance measure. This paper has captured the problems that are faced in real when clustering algorithms are implemented .It also considers the most extensively used tools which are readily available and support functions which ease the programming. Once algorithms have been implemented, they also need to be tested for its validity. There exist several validation indexes for testing the performance and accuracy which have also been discussed here.

  4. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

    CERN Document Server

    Ntampaka, M; Sutherland, D J; Fromenteau, S; Poczos, B; Schneider, J

    2015-01-01

    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark's publicly-available N-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power law scaling relation to infer cluster mass from galaxy line of sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with width = 0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (width = 2.13). We employ the Support Distribution Machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to...

  5. Comparison between optical and X-ray cluster detection methods

    CERN Document Server

    Basilakos, S; Georgakakis, A; Georgantopoulos, I; Gaga, T; Kolokotronis, V G; Stewart, G C

    2003-01-01

    In this work we present combined optical and X-ray cluster detection methods in an area near the North Galactic Pole area, previously covered by the SDSS and 2dF optical surveys. The same area has been covered by shallow ($\\sim 1.8$ deg$^{2}$) XMM-{\\em Newton} observations. The optical cluster detection procedure is based on merging two independent selection methods - a smoothing+percolation technique, and a Matched Filter Algorithm. The X-ray cluster detection is based on a wavelet-based algorithm, incorporated in the SAS v.5.2 package. The final optical sample counts 9 candidate clusters with richness of more than 20 galaxies, corresponding roughly to APM richness class. Three, of our optically detected clusters are also detected in our X-ray survey.

  6. Fuzzy Document Clustering Approach using WordNet Lexical Categories

    Science.gov (United States)

    Gharib, Tarek F.; Fouad, Mohammed M.; Aref, Mostafa M.

    Text mining refers generally to the process of extracting interesting information and knowledge from unstructured text. This area is growing rapidly mainly because of the strong need for analysing the huge and large amount of textual data that reside on internal file systems and the Web. Text document clustering provides an effective navigation mechanism to organize this large amount of data by grouping their documents into a small number of meaningful classes. In this paper we proposed a fuzzy text document clustering approach using WordNet lexical categories and Fuzzy c-Means algorithm. Some experiments are performed to compare efficiency of the proposed approach with the recently reported approaches. Experimental results show that Fuzzy clustering leads to great performance results. Fuzzy c-means algorithm overcomes other classical clustering algorithms like k-means and bisecting k-means in both clustering quality and running time efficiency.

  7. Translation in ESL Classes

    Directory of Open Access Journals (Sweden)

    Nagy Imola Katalin

    2015-12-01

    Full Text Available The problem of translation in foreign language classes cannot be dealt with unless we attempt to make an overview of what translation meant for language teaching in different periods of language pedagogy. From the translation-oriented grammar-translation method through the complete ban on translation and mother tongue during the times of the audio-lingual approaches, we have come today to reconsider the role and status of translation in ESL classes. This article attempts to advocate for translation as a useful ESL class activity, which can completely fulfil the requirements of communicativeness. We also attempt to identify some activities and games, which rely on translation in some books published in the 1990s and the 2000s.

  8. Class hierarchy method to find Change-Proneness

    Directory of Open Access Journals (Sweden)

    Malan V.Gaikwad

    2011-01-01

    Full Text Available Finding Proneness of software is necessary to identify fault prone and change prone classes at earlier stages of development, so that those classes can be given special attention. Also to improves the quality and reliability of the software. For corrective and adaptive maintenance we require to make changes during the software evolution.As such changes cluster around number of key components in software, it is important to analyze the frequency of changes in individual classes and also to identify and show related changes in multiple classes. Early detection of fault prone and change prone classes can enables the developers and experts to spend their valuable time and resources on these areas of software. Prediction of change-prone and fault prone classes of a software is an active topic in the area of software engineering. Such prediction can be used to predict changes to different classes of a system from one release of software to the next release. Identifying the change-prone and fault prone classes in advance can helps to focus attention on these classes.In this paper we are focusing on finding dependency of software that can be chieved by estimating the proneness of Object Oriented Software. Two main types of proneness are associated with OO software. Fault Proneness and Change Proneness.

  9. Talking Class in Tehroon

    DEFF Research Database (Denmark)

    Elling, Rasmus Christian; Rezakhani, Khodadad

    2016-01-01

    Persian, like any other language, is laced with references to class, both blatant and subtle. With idioms and metaphors, Iranians can identify and situate others, and thus themselves, within hierarchies of social status and privilege, both real and imagined. Some class-related terms can be traced...... back to medieval times, whereas others are of modern vintage, the linguistic legacy of television shows, pop songs, social media memes or street vernacular. Every day, it seems, an infectious set of phrases appears that make yesterday’s seem embarrassingly antiquated....

  10. MIDDLE CLASS MOVEMENTS

    OpenAIRE

    Dr. K. Sravana Kumar

    2016-01-01

                The middle class is placed between labour and capital. It neither directly awns the means of production that pumps out the surplus generated by wage labour power, nor does it, by its own labour, produce the surplus which has use and exchange value. Broadly speaking, this class consists of the petty bourgeoisie and the white-collar workers. The former are either self-employed or involved in the distribution of commodities and t...

  11. Class Actions in Denmark

    DEFF Research Database (Denmark)

    Werlauff, Erik

    2009-01-01

    The article deals with the relatively new Danish Act on Class Action (Danish: gruppesøgsmål) which was suggested by The Permanent Council on Civil procedure (Retsplejerådet) of which the article's author is a member. The operability of the new provisions is illustrated through some wellknown Dani...... cases: Hafnia case (investment prospectus), and Danish Eternit (roof elements) where the existence of Danish provisions on class actions might have made a difference, and the article also deals with the delicate questions of opt-in and opt-out....

  12. Residues of Chern classes

    OpenAIRE

    Suwa, Tatsuo; 諏訪, 立雄

    2003-01-01

    If we have a finite number of sections of a complex vector bundle E over a manifold M, certain Chern classes of E are localized at the singular set S, i.e., the set of points where the sections fail to be linearly independent. When S is compact, the localizations define the residues at each connected component of S by the Alexander duality. If M itself is compact, the sum of the residues is equal to the Poincaré dual of the corresponding Chern class. This type of theory is also developed for ...

  13. Residues of Chern classes

    OpenAIRE

    Suwa, Tatsuo

    2003-01-01

    If we have a finite number of sections of a complex vector bundle $E$ over a manifold $M$ , certain Chern classes of $E$ are localized at the singular set $S$ , i.e., the set of points where the sections fail to be linearly independent. When $S$ is compact, the localizations define the residues at each connected component of $S$ by the Alexander duality. If $M$ itself is compact, the sum of the residues is equal to the Poincaré dual of the corresponding Chern class. This type of theory is als...

  14. Textile Industrial Clusters in China

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    "National Textile Industry Cluster Development Seminar" convened, held by China National Textile and Apparel Council, 23 cities and towns were awarded as China’s Textile Industry Cluster Pilot District. By far, China’s textile industrial clusters have grown

  15. Spanning Tree Based Attribute Clustering

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Jorge, Cordero Hernandez

    2009-01-01

    inconsistent edges from a maximum spanning tree by starting appropriate initial modes, therefore generating stable clusters. It discovers sound clusters through simple graph operations and achieves significant computational savings. We compare the Star Discovery algorithm against earlier attribute clustering...

  16. Cluster knockout reactions

    Indian Academy of Sciences (India)

    Arun K Jain; B N Joshi

    2014-04-01

    Cluster knockout reactions are expected to reveal the amount of clustering (such as that of , d and even of heavier clusters such as 12C, 16O etc.) in the target nucleus. In simple terms, incident medium high-energy nuclear projectile interacts strongly with the cluster (present in the target nucleus) as if it were existing as a free entity. Theoretically, the relatively softer interactions of the two outgoing particles with the residual nucleus lead to optical distortions and are treated in terms of distorted wave (DW) formalism. The long-range projectile–cluster interaction is accounted for, in terms of the finite range (FR) direct reaction formalism, as against the more commonly adopted zero-range (ZR) distorted wave impulse approximation (DWIA) formalism. Comparison of the DWIA calculations with the observed data provide information about the momentum distribution and the clustering spectroscopic factor of the target nucleus. Interesting results and some recent advancements in the area of (, 2) reactions and heavy cluster knockout reactions are discussed. Importance of the finite-range vertex and the final-state interactions are brought out.

  17. Software-Defined Cluster

    Institute of Scientific and Technical Information of China (English)

    聂华; 杨晓君; 刘淘英

    2015-01-01

    The cluster architecture has played an important role in high-end computing for the past 20 years. With the advent of Internet services, big data, and cloud computing, traditional clusters face three challenges: 1) providing flexible system balance among computing, memory, and I/O capabilities;2) reducing resource pooling overheads;and 3) addressing low performance-power efficiency. This position paper proposes a software-defined cluster (SDC) architecture to deal with these challenges. The SDC architecture inherits two features of traditional cluster: its architecture is multicomputer and it has loosely-coupled interconnect. SDC provides two new mechanisms: global I/O space (GIO) and hardware-supported native access (HNA) to remote devices. Application software can define a virtual cluster best suited to its needs from resources pools provided by a physical cluster, and traditional cluster ecosystems need no modification. We also discuss a prototype design and implementation of a 32-processor cloud server utilizing the SDC architecture.

  18. Extending Beowulf Clusters

    Science.gov (United States)

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

    2003-01-01

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

  19. Cluster Management Institutionalization

    DEFF Research Database (Denmark)

    Normann, Leo; Agger Nielsen, Jeppe

    2015-01-01

    institutionalism together with a longitudinal case-based inquiry into how cluster management has entered and penetrated the management practices of day care in Denmark. We demonstrate how cluster management became widely adopted in the day care field not only because of its intrinsic properties but also because...... legitimized at the field level, then spread, and finally translated into action in the adopting organizations. Instead, we observed entangled field and organizational-level processes. Accordingly, we argue that cluster management institutionalization is most readily understood by simultaneously investigating...

  20. Introduction to cluster dynamics

    CERN Document Server

    Reinhard, Paul-Gerhard

    2008-01-01

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

  1. Dwarfs in Coma Cluster

    Science.gov (United States)

    2007-01-01

    [figure removed for brevity, see original site] Click on image for larger poster version This false-color mosaic of the central region of the Coma cluster combines infrared and visible-light images to reveal thousands of faint objects (green). Follow-up observations showed that many of these objects, which appear here as faint green smudges, are dwarf galaxies belonging to the cluster. Two large elliptical galaxies, NGC 4889 and NGC 4874, dominate the cluster's center. The mosaic combines visible-light data from the Sloan Digital Sky Survey (color coded blue) with long- and short-wavelength infrared views (red and green, respectively) from NASA's Spitzer Space Telescope.

  2. Raspberry Pi super cluster

    CERN Document Server

    Dennis, Andrew K

    2013-01-01

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

  3. Partially supervised speaker clustering.

    Science.gov (United States)

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

    2012-05-01

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

  4. Clustering in nuclear environment

    International Nuclear Information System (INIS)

    The properties of few-body clusters (mass number A ≤ 4) are modified if they are immersed in a nuclear medium. In particular, Pauli blocking that reflects the antisymmetrization of the many-body wave function is responsible for the medium modification of light clusters and the dissolution with increasing density. A more consistent description is given with takes also the contribution of correlations in the continuum into account. The relation between cluster formation in warm dense matter and in nuclear structure is discussed

  5. Multiple populations in the Sagittarius nuclear cluster M 54 and in other anomalous globular clusters

    Science.gov (United States)

    Milone, A. P.

    2016-08-01

    M 54 is the central cluster of the Sagittarius dwarf galaxy. This stellar system is now in process of being disrupted by the tidal interaction with the Milky Way and represents one of the building blocks of the Galactic Halo. Recent discoveries, based on the synergy of photometry and spectroscopy have revealed that the color-magnitude diagram (CMD) of some massive, anomalous, Globular Clusters (GCs) host stellar populations with different content of heavy elements. In this paper, I use multi-wavelength Hubble Space Telescope (HST) photometry to detect and characterize multiple stellar populations in M 54. I provide empirical evidence that this GC shares photometric and spectroscopic similarities with the class of anomalous GCs. These findings make it tempting to speculate that, similarly to Sagittarius nuclear cluster M 54, other anomalous GCs were born in an extra-Galactic environment.

  6. Multiple populations in the Sagittarius nuclear cluster M54 and in other anomalous globular clusters

    CERN Document Server

    Milone, A P

    2015-01-01

    M54 is the central cluster of the Sagittarius dwarf galaxy. This stellar system is now in process of being disrupted by the tidal interaction with the Milky Way and represents one of the building blocks of the Galactic Halo. Recent discoveries, based on the synergy of photometry and spectroscopy have revealed that the color-magnitude diagram of some massive, anomalous, Globular Clusters (GCs) host stellar populations with different content of heavy elements.In this paper, I use multi-wavelength Hubble Space Telescope photometry to detect and characterize multiple stellar populations in M54. I provide empirical evidence that this GC shares photometric and spectroscopic similarities with the class of anomalous GCs. These findings make it tempting to speculate that, similarly to Sagittarius nuclear cluster M54, other anomalous GCs were born in an extra-Galactic environment.

  7. Combining cluster number counts and galaxy clustering

    Science.gov (United States)

    Lacasa, Fabien; Rosenfeld, Rogerio

    2016-08-01

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

  8. Reference class forecasting

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent

    Underbudgettering og budgetoverskridelser forekommer i et flertal af større bygge- og anlægsprojekter. Problemet skyldes optimisme og/eller strategisk misinformation i budgetteringsprocessen. Reference class forecasting (RCF) er en prognosemetode, som er udviklet for at reducere eller eliminere...

  9. Fostering a Middle Class

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Though there is no official definition of "middle class" in China, the tag has become one few Chinese people believe they deserve anyway.In early August, the Chinese Academy of Social Sciences released a report on China’s urban development,

  10. Openers for Biology Classes.

    Science.gov (United States)

    Gridley, C. Robert R.

    This teaching guide contains 200 activities that are suitable for openers and demonstrations in biology classes. Details are provided regarding the use of these activities. Some of the broad topics under which the activities are organized include algae, amphibians, bacteria, biologists, crustaceans, dinosaurs, ecology, evolution, flowering plants,…

  11. Teaching Very Large Classes

    Science.gov (United States)

    DeRogatis, Amy; Honerkamp, Kenneth; McDaniel, Justin; Medine, Carolyn; Nyitray, Vivian-Lee; Pearson, Thomas

    2014-01-01

    The editor of "Teaching Theology and Religion" facilitated this reflective conversation with five teachers who have extensive experience and success teaching extremely large classes (150 students or more). In the course of the conversation these professors exchange and analyze the effectiveness of several active learning strategies they…

  12. Adeus à classe trabalhadora?

    Directory of Open Access Journals (Sweden)

    Geoff Eley

    2013-12-01

    Full Text Available No início da década de 1980, a política centrada em classes da tradição socialista estava em crise, e comentadores importantes adotaram tons apocalípticos. No final da década, a esquerda permanecia profundamente dividida entre os advogados da mudança e os defensores da fé. Em meados dos anos 1990, os primeiros tinham, de modo geral, ganhado a batalha. O artigo busca apresentar essa mudança contemporânea não como a 'morte da classe', mas como o desa­parecimento de um tipo particular de ­sociedade de classes, marcado pelo ­processo de formação da classe trabalhadora entre os anos 1880 e 1940 e pelo alinhamento político daí resultante, atingindo seu apogeu na construção social-democrata do acordo do pós-guerra. Quando mudanças de longo prazo na economia se combinaram com o ataque ao keynesianismo na política de recessão a partir de meados da década de 1970, a unidade da classe trabalhadora deixou de estar disponível da forma antiga e bastante utilizada, como o terreno natural da política de esquerda. Enquanto uma coletividade dominante da classe trabalhadora entrou em declínio, outra se corporificou de modo lento e desigual para tomar o lugar daquela. Mas a unidade operacional dessa nova agregação da classe trabalhadora ainda está, em grande parte, em formação. Para recuperar a eficácia política da tradição socialista, alguma nova visão de agência política coletiva será necessária, uma visão imaginativamente ajustada às condições emergentes da produção e acumulação capitalista no início do século XXI.

  13. Class Generation for Numerical Wind Atlases

    DEFF Research Database (Denmark)

    Cutler, N.J.; Jørgensen, B.H.; Ersbøll, Bjarne Kjær;

    2006-01-01

    A new optimised clustering method is presented for generating wind classes for mesoscale modelling to produce numerical wind atlases. It is compared with the existing method of dividing the data in 12 to 16 sectors, 3 to 7 wind-speed bins and dividing again according to the stability of the atmos......A new optimised clustering method is presented for generating wind classes for mesoscale modelling to produce numerical wind atlases. It is compared with the existing method of dividing the data in 12 to 16 sectors, 3 to 7 wind-speed bins and dividing again according to the stability...... of the atmosphere. Wind atlases are typically produced using many years of on-site wind observations at many locations. Numerical wind atlases are the result of mesoscale model integrations based on synoptic scale wind climates and can be produced in a number of hours of computation. 40 years of twice daily NCEP...... by optimising the representation of the data and by automating the procedure more. The Karlsruhe Atmospheric Mesoscale Model (KAMM) is combined with the WAsP analysis to produce numerical wind atlases for two sites, Ireland and Egypt. The model results are compared with wind atlases made from measurements...

  14. An Improved Fuzzy c-Means Clustering Algorithm Based on Shadowed Sets and PSO

    Directory of Open Access Journals (Sweden)

    Jian Zhang

    2014-01-01

    Full Text Available To organize the wide variety of data sets automatically and acquire accurate classification, this paper presents a modified fuzzy c-means algorithm (SP-FCM based on particle swarm optimization (PSO and shadowed sets to perform feature clustering. SP-FCM introduces the global search property of PSO to deal with the problem of premature convergence of conventional fuzzy clustering, utilizes vagueness balance property of shadowed sets to handle overlapping among clusters, and models uncertainty in class boundaries. This new method uses Xie-Beni index as cluster validity and automatically finds the optimal cluster number within a specific range with cluster partitions that provide compact and well-separated clusters. Experiments show that the proposed approach significantly improves the clustering effect.

  15. Evolution of clustered storage

    CERN Document Server

    CERN. Geneva; Van de Vyvre, Pierre

    2007-01-01

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

  16. Dynamic Bayesian clustering.

    Science.gov (United States)

    Fowler, Anna; Menon, Vilas; Heard, Nicholas A

    2013-10-01

    Clusters of time series data may change location and memberships over time; in gene expression data, this occurs as groups of genes or samples respond differently to stimuli or experimental conditions at different times. In order to uncover this underlying temporal structure, we consider dynamic clusters with time-dependent parameters which split and merge over time, enabling cluster memberships to change. These interesting time-dependent structures are useful in understanding the development of organisms or complex organs, and could not be identified using traditional clustering methods. In cell cycle data, these time-dependent structure may provide links between genes and stages of the cell cycle, whilst in developmental data sets they may highlight key developmental transitions. PMID:24131050

  17. Internal Cluster Structure

    CERN Document Server

    Bartelmann, Matthias; Meneghetti, Massimo; Schmidt, Robert

    2013-01-01

    The core structure of galaxy clusters is fundamentally important. Even though self-gravitating systems have no stable equilibrium state due to their negative heat capacity, numerical simulations find density profiles which are universal in the sense that they are fairly flat within a scale radius and gradually steepen farther outward, asymptotically approaching a logarithmic slope of $\\approx-3$ near the virial radius. We argue that the reason for the formation of this profile is not satisfactorily understood. The ratio between the virial radius and the scale radius, the so-called concentration, is found in simulations to be closely related to the mass and the redshift and low for cluster-sized haloes, but observed to be substantially higher at least in a subset of observed clusters. Haloes formed from cold dark matter should furthermore be richly substructured. We review theoretical and observational aspects of cluster cores here, discuss modifications by baryonic physics and observables that can provide bet...

  18. GEANT4 distributed computing for compact clusters

    Energy Technology Data Exchange (ETDEWEB)

    Harrawood, Brian P., E-mail: brian.harrawood@duke.edu; Agasthya, Greeshma A.; Lakshmanan, Manu N.; Raterman, Gretchen; Kapadia, Anuj J.

    2014-11-11

    A new technique for distribution of GEANT4 processes is introduced to simplify running a simulation in a parallel environment such as a tightly coupled computer cluster. Using a new C++ class derived from the GEANT4 toolkit, multiple runs forming a single simulation are managed across a local network of computers with a simple inter-node communication protocol. The class is integrated with the GEANT4 toolkit and is designed to scale from a single symmetric multiprocessing (SMP) machine to compact clusters ranging in size from tens to thousands of nodes. User designed ‘work tickets’ are distributed to clients using a client–server work flow model to specify the parameters for each individual run of the simulation. The new g4DistributedRunManager class was developed and well tested in the course of our Neutron Stimulated Emission Computed Tomography (NSECT) experiments. It will be useful for anyone running GEANT4 for large discrete data sets such as covering a range of angles in computed tomography, calculating dose delivery with multiple fractions or simply speeding the through-put of a single model.

  19. Finnish Mobile Gaming Cluster

    OpenAIRE

    Masira, Elijah; Chowdhury, Nafis Ahmed

    2014-01-01

    Abstract The Finnish mobile gaming cluster is one of the most promising industries that have been growing significantly in the past few years to become a substantial cultural export product / service of Finland. The main objective of this research was to gain a persuasive understanding about the emergence of the mobile gaming cluster in Finland and explore the factors behind its success. The literature review centers on M. E Porter’s publications on competitiveness and other publication...

  20. Clustering audiology data

    OpenAIRE

    Anwar, Naveed; Oakes, Michael; Wermter, Stefan; Heinrich, Stefan

    2010-01-01

    In this paper we describe new results of statistical and neural data mining of audiology patient records, with the ultimate aim of looking for factors influencing which patients would most benefit from being fitted with a hearing aid. We describe how a combination of neural and statistical techniques can usefully subdivide a set of patients into clusters, based on their hearing thresholds at six different frequencies, and then label the clusters with meaningful text labels. In our first exper...

  1. Industry clusters and SMEs

    OpenAIRE

    Arnoud Muizer; Gert Jan Hospers

    1999-01-01

    Studie naar de rol van clusters van bedrijven in de economie. Clusters van bedrijven krijgen een groeiende aandacht op alle bestuurlijke niveaus. De achterliggende gedachte is dat samenwerking tussen bedrijven op technologisch gebied leidt tot de creatie van extra toegevoegde waarde, niet alleen voor de samenwerkingspartners zelf, maar ook voor de lokale, regionale en nationale economie. In de studie wordt een clusterdefinitie gepresenteerd en een raamwerk dat als basis kan dienen voor nader ...

  2. Centroid Based Text Clustering

    Directory of Open Access Journals (Sweden)

    Priti Maheshwari

    2010-09-01

    Full Text Available Web mining is a burgeoning new field that attempts to glean meaningful information from natural language text. Web mining refers generally to the process of extracting interesting information and knowledge from unstructured text. Text clustering is one of the important Web mining functionalities. Text clustering is the task in which texts are classified into groups of similar objects based on their contents. Current research in the area of Web mining is tacklesproblems of text data representation, classification, clustering, information extraction or the search for and modeling of hidden patterns. In this paper we propose for mining large document collections it is necessary to pre-process the web documents and store the information in a data structure, which is more appropriate for further processing than a plain web file. In this paper we developed a php-mySql based utility to convert unstructured web documents into structured tabular representation by preprocessing, indexing .We apply centroid based web clustering method on preprocessed data. We apply three methods for clustering. Finally we proposed a method that can increase accuracy based on clustering ofdocuments.

  3. Galaxy cluster's rotation

    CERN Document Server

    Manolopoulou, Maria

    2016-01-01

    We study the possible rotation of cluster galaxies, developing, testing and applying a novel algorithm which identifies rotation, if such does exits, as well as its rotational centre, its axis orientation, rotational velocity amplitude and, finally, the clockwise or counterclockwise direction of rotation on the plane of the sky. To validate our algorithms we construct realistic Monte-Carlo mock rotating clusters and confirm that our method provides robust indications of rotation. We then apply our methodology on a sample of Abell clusters with z<~0.1 with member galaxies selected from the SDSS DR10 spectroscopic database. We find that ~35% of our clusters are rotating when using a set of strict criteria, while loosening the criteria we find this fraction increasing to ~48%. We correlate our rotation indicators with the cluster dynamical state, provided either by their Bautz-Morgan type or by their X-ray isophotal shape and find for those clusters showing rotation that the significance and strength of their...

  4. Cluster bomb ocular injuries

    Directory of Open Access Journals (Sweden)

    Ahmad M Mansour

    2012-01-01

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

  5. Packing of protein structures in clusters with magic numbers

    DEFF Research Database (Denmark)

    Lindgård, Per-Anker; Bohr, Henrik

    1997-01-01

    Recently we have proposed a model for folding proteins into packed `clusters'. We have constructed a local homology measure for protein fold classes by projecting consecutively secondary structures onto a lattice. Taking into account hydrophobic forces we have found a mechanism for formation of...... abundances. In this paper we demonstrate that the results are robust to variations in the coordination number of the model....

  6. Assessment of Rotationally-Invariant Clustering Using Streamlet Tractography

    DEFF Research Database (Denmark)

    Liptrot, Matthew George; Lauze, Francois Bernard

    We present a novel visualisation-based strategy for the assessment of a recently proposed clustering technique for raw DWI volumes which derives rotationally-invariant metrics to classify voxels. The validity of the division of all brain tissue voxels into such classes was assessed using...

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  9. Analysis & Prediction of Sales Data in SAP-ERP System using Clustering Algorithms

    OpenAIRE

    Sastry, S. Hanumanth; Babu, Prof. M. S. Prasada

    2013-01-01

    Clustering is an important data mining technique where we will be interested in maximizing intracluster distance and also minimizing intercluster distance. We have utilized clustering techniques for detecting deviation in product sales and also to identify and compare sales over a particular period of time. Clustering is suited to group items that seem to fall naturally together, when there is no specified class for any new item. We have utilizedannual sales data of a steel major to analyze S...

  10. A hypergraph-based model for graph clustering: application to image indexing

    OpenAIRE

    Jouili, Salim; Tabbone, Salvatore

    2009-01-01

    Version finale disponible : www.springerlink.com International audience In this paper, we introduce a prototype-based clustering algorithm dealing with graphs. We propose a hypergraph-based model for graph data sets by allowing clusters overlapping. More precisely, in this representation one graph can be assigned to more than one cluster. Using the concept of the graph median and a given threshold, the proposed algorithm detects automatically the number of classes in the graph database....

  11. Sparse Subspace Clustering: Algorithm, Theory, and Applications

    CERN Document Server

    Elhamifar, Ehsan

    2012-01-01

    In many real-world problems, we are dealing with collections of high-dimensional data, such as images, videos, text and web documents, DNA microarray data, and more. Often, high-dimensional data lie close to low-dimensional structures corresponding to several classes or categories of the data. In this paper, we propose and study an algorithm, called Sparse Subspace Clustering, to cluster data points that lie in a union of low-dimensional subspaces. The key idea is that, among infinitely many possible representations of a data point in terms of other points, a sparse representation corresponds to selecting a few points that come from the same subspace. This motivates solving a sparse optimization program whose solution is used in a spectral clustering framework to infer the clustering of the data into subspaces. As solving the sparse optimization program is NP-hard, we consider its convex relaxation and show that, under appropriate conditions on the arrangement of the subspaces and the distribution of the data...

  12. A New Clustering Algorithm for Face Classification

    Directory of Open Access Journals (Sweden)

    Shaker K. Ali

    2016-06-01

    Full Text Available In This paper, we proposed new clustering algorithm depend on other clustering algorithm ideas. The proposed algorithm idea is based on getting distance matrix, then the exclusion of the matrix points which will be clustered by saving the location (row, column of these points and determine the minimum distance of these points which will be belongs the group (class and keep the other points which are not clustering yet. The propose algorithm is applied to image data base of the human face with different environment (direction, angles... etc.. These data are collected from different resource (ORL site and real images collected from random sample of Thi_Qar city population in lraq. Our algorithm has been implemented on three types of distance to calculate the minimum distance between points (Euclidean, Correlation and Minkowski distance .The efficiency ratio of proposed algorithm has varied according to the data base and threshold, the efficiency of our algorithm is exceeded (96%. Matlab (2014 has been used in this work.

  13. Advanced Low Energy Adaptive Clustering Hierarchy

    Directory of Open Access Journals (Sweden)

    Ezzati Abdellah,

    2010-10-01

    Full Text Available The use of Wireless Sensor Networks (WSNs is anticipated to bring enormous changes in data gathering, processing and dissemination for different environments and applications. However, a WSN is a power constrained system, since nodes run on limited power batteries which shorten its lifespan. Prolonging the network lifetime depends on efficient management of sensing node energy resource. Hierarchicalrouting protocols are best known in regard to energy efficiency. By using a clustering technique hierarchical routing protocols greatly minimize energy consumed in collecting and disseminating data. Low Energy Adaptive Clustering Hierarchy (LEACH is one of the undamental protocols in this class. In this paper we propose Advanced LEACH (A-LEACH, a heterogeneous-energy protocol to decrease probability of failure nodes and to prolong the time interval before the death of the first node (we refer to as stability period and increasing the lifetime in heterogeneous WSNs, which is crucial for many applications.

  14. World Class Facilities Management

    DEFF Research Database (Denmark)

    Malmstrøm, Ole Emil; Jensen, Per Anker

    2013-01-01

    Alle der med entusiasme arbejder med Facilities Management drømmer om at levere World Class. DFM drømmer om at skabe rammer og baggrund for, at vi i Danmark kan bryste os at være blandt de førende på verdensplan. Her samles op på, hvor tæt vi er på at nå drømmemålet.......Alle der med entusiasme arbejder med Facilities Management drømmer om at levere World Class. DFM drømmer om at skabe rammer og baggrund for, at vi i Danmark kan bryste os at være blandt de førende på verdensplan. Her samles op på, hvor tæt vi er på at nå drømmemålet....

  15. The rotation of Galaxy Clusters

    OpenAIRE

    Tovmassian, Hrant M.

    2015-01-01

    The method for detection of the galaxy cluster rotation based on the study of distribution of member galaxies with velocities lower and higher of the cluster mean velocity over the cluster image is proposed. The search for rotation is made for flat clusters with $a/b>1.8$ and BMI type clusters which are expected to be rotating. For comparison there were studied also round clusters and clusters of NBMI type, the second by brightness galaxy in which does not differ significantly from the cluste...

  16. Discriminant non-stationary signal features' clustering using hard and fuzzy cluster labeling

    Science.gov (United States)

    Ghoraani, Behnaz; Krishnan, Sridhar

    2012-12-01

    Current approaches to improve the pattern recognition performance mainly focus on either extracting non-stationary and discriminant features of each class, or employing complex and nonlinear feature classifiers. However, little attention has been paid to the integration of these two approaches. Combining non-stationary feature analysis with complex feature classifiers, this article presents a novel direction to enhance the discriminatory power of pattern recognition methods. This approach, which is based on a fusion of non-stationary feature analysis with clustering techniques, proposes an algorithm to adaptively identify the feature vectors according to their importance in representing the patterns of discrimination. Non-stationary feature vectors are extracted using a non-stationary method based on time-frequency distribution and non-negative matrix factorization. The clustering algorithms including the K-means and self-organizing tree maps are utilized as unsupervised clustering methods followed by a supervised labeling. Two labeling methods are introduced: hard and fuzzy labeling. The article covers in detail the formulation of the proposed discriminant feature clustering method. Experiments performed with pathological speech classification, T-wave alternans evaluation from the surface electrocardiogram, audio scene analysis, and telemonitoring of Parkinson's disease problems produced desirable results. The outcome demonstrates the benefits of non-stationary feature fusion with clustering methods for complex data analysis where existing approaches do not exhibit a high performance.

  17. Stellar populations in star clusters

    CERN Document Server

    Li, Chengyuan; Deng, Licai

    2016-01-01

    Stellar populations contain the most important information about star clus- ter formation and evolution. Until several decades ago, star clusters were believed to be ideal laboratories for studies of simple stellar populations (SSPs). However, discoveries of multiple stellar populations in Galactic globular clusters have expanded our view on stellar populations in star clusters. They have simultaneously generated a number of controversies, particularly as to whether young star clusters may have the same origin as old globular clusters. In addition, extensive studies have revealed that the SSP scenario does not seem to hold for some intermediate-age and young star clusters either, thus making the origin of multiple stellar populations in star clusters even more complicated. Stellar population anomalies in numerous star clusters are well-documented, implying that the notion of star clusters as true SSPs faces serious challenges. In this review, we focus on stellar populations in massive clusters with different ...

  18. Single-Seed Cascades on Clustered Networks

    CERN Document Server

    McSweeney, John K

    2015-01-01

    We consider a dynamic network cascade process developed by Watts applied to a random networks with a specified amount of clustering, belonging to a class of random networks developed by Newman. We adapt existing tree-based methods to formulate an appropriate two-type branching process to describe the spread of a cascade started with a single active node, and obtain a fixed-point equation to implicitly express the extinction probability of such a cascade. In so doing, we also recover a special case of a formula of Hackett et al. giving conditions for certain extinction of the cascade.

  19. Clustering in bubbly liquids

    Science.gov (United States)

    Figueroa, Bernardo; Zenit, Roberto

    2004-11-01

    We are conducting experiments to determine the amount of clustering that occurs when small gas bubbles ascend in clean water. In particular, we are interested in flows for which the liquid motion around the bubbles can be described, with a certain degree of accuracy, using potential flow theory. This model is applicable for the case of bubbly liquids in which the Reynolds number is large and the Weber number is small. To clearly observe the formation of bubble clusters we propose the use of a Hele-Shaw-type channel. In this thin channel the bubbles cannot overlap in the depth direction, therefore the identification of bubble clusters cannot be misinterpreted. Direct video image analysis is performed to calculate the velocity and size of the bubbles, as well as the formation of clusters. Although the walls do affect the motion of the bubbles, the clustering phenomena does occur and has the same qualitative behavior as in fully three-dimensional flows. A series of preliminary measurements are presented. A brief discussion of our plans to perform PIV measurements to obtain the liquid velocity fields is also presented.

  20. The spatial structure of young stellar clusters

    Science.gov (United States)

    Kuhn, Michael A.

    . This apparent contradiction may be evidence of more rapid dynamical evolution accelerated by the merger of subclusters. Overall, 142 subclusters of young stars are found in the 17 MSFRs using the statistical "finite-mixture model" cluster analysis method, and the intrinsic stellar populations for these clusters are inferred using "initial mass functions" and "X-ray luminosity functions." Four structural classes are seen in MSFR: linear chains of subclusters, clumpy structures, core-halo structures, and simple isolated clusters. The subclusters do follow the structure of the molecular clouds, but do not appear to be coeval with each other. There is strong evidence in the subcluster properties for gas expulsion and subcluster expansion (e.g., the density ~ radius and age ~ radius relations), and evidence that is consistent with subcluster mergers (e.g., the ellipticity distribution and the number ~ density relation). The cluster analysis provides evidence to support hierarchical models of stellar cluster formation, which have been theorized to explain mass segregation and dynamical relaxation in very young clusters. The ~1 Myr age spreads in the subclusters of a MSFR appear to require slower star-formation in giant molecular clouds with continually driven turbulence, rather than clouds with rapidly decaying turbulence. And, the diverse range of stellar surface density environment in MSFRs will have implications for models of cluster survival after gas removal.

  1. Class Participation: Promoting In-Class Student Engagement

    Science.gov (United States)

    O'Connor, Kevin J.

    2013-01-01

    Class participation has long been valued by faculty members interested in engaging students in the learning process. This paper discusses class participation and shares participation techniques that promote active student engagement during class meetings. Emphasis is placed on techniques that invite a larger number of students into a course's…

  2. Class Action and Class Settlement in a European Perspective

    DEFF Research Database (Denmark)

    Werlauff, Erik

    2013-01-01

    The article analyses the options for introducing common European rules on class action lawsuits with an opt-out-model in individual cases. An analysis is made of how the risks of misuse of class actions can be prevented. The article considers the Dutch rules on class settlements (the WCAM procedure...

  3. Clusters in Light Nuclei

    CERN Document Server

    Beck, C; Zafra, A Sanchez i; Thummerer, S; Azaiez, F; Bednarczyk, P; Courtin, S; Curien, D; Dorvaux, O; Goasduff, A; ~Lebhertz, D; Nourreddine, A; ~Rousseau, M; Salsac, M -D; von Oertzen, W; Gebauer, B; Wheldon, C; Kokalova, Tz; Efimov, G; Zherebchevsky, V; Schulz, Ch; Bohlen, H G; Kamanin, D; de Angelis, G; Gadea, A; Lenzi, S; Napoli, D R; Szilner, S; Milin, M; Catford, W N; Jenkins, D G; Royer, G

    2010-01-01

    A great deal of research work has been undertaken in the alpha-clustering study since the pioneering discovery, half a century ago, of 12C+12C molecular resonances. Our knowledge of the field of the physics of nuclear molecules has increased considerably 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. In this work, the occurence of "exotic" shapes in light N=Z alpha-like nuclei is investigated. Various approaches of superdeformed and hyperdeformed bands associated with quasimolecular resonant structures are presented. Results on clustering aspects are also discussed for light neutron-rich Oxygen isotopes.

  4. Vanadogermanate cluster anions.

    Science.gov (United States)

    Whitfield, T; Wang, X; Jacobson, A J

    2003-06-16

    Three novel vanadogermanate cluster anions have been synthesized by hydrothermal reactions. The cluster anions are derived from the (V(18)O(42)) Keggin cluster shell by substitution of V=O(2+) "caps" by Ge(2)O(OH)(2)(4+) species. In Cs(8)[Ge(4)V(16)O(42)(OH)(4)].4.7H(2)O, 1, (monoclinic, space group C2/c (No. 15), Z = 8, a = 44.513(2) A, b = 12.7632(7) A, c = 22.923(1) A, beta = 101.376(1) degrees ) and (pipH(2))(4)(pipH)(4)[Ge(8)V(14)O(50).(H(2)O)] (pip = C(4)N(2)H(10)), 2 (tetragonal, space group P4(2)/nnm (No. 134), Z = 2, a = 14.9950(7) A, c = 18.408(1) A), two and four VO(2+) caps are replaced, respectively, and each cluster anion encapsulates a water molecule. In K(5)H(8)Ge(8)V(12)SO(52).10H(2)O, 3, (tetragonal, space group I4/m (No. 87), Z = 2, a = 15.573(1) A, c = 10.963(1) A), four VO(2+) caps are replaced by Ge(2)O(OH)(2)(4+) species, and an additional two are omitted. The cluster ion in 3 contains a sulfate anion disordered over two positions. The cluster anions are analogous to the vanadoarsenate anions [V(18)(-)(n)()As(2)(n)()O(42)(X)](m)(-) (X = SO(3), SO(4), Cl; n = 3, 4) previously reported. PMID:12793808

  5. Fractal clusters and intermittency in relativistic heavy ion collisions

    CERN Document Server

    Antoniou, Nikos G; Diakonos, F K

    2000-01-01

    We investigate the formation of particle clusters (pions) associated with the chiral QCD phase transition in thermodynamic equilibrium. The geometry of these clusters at the critical point (T=T/sub c/) turns out to be fractal reflecting the self similar structure of the density fluctuations of the produced pions. The fractal dimension of the "critical" clusters is related to the critical exponents characterizing the phase transition. We examine the possibility to observe such pion clusters in relativistic heavy ion collisions. A Monte Carlo simulation of the critical system in 3D is performed leading to a typical set of "critical" events. Factorial moment analysis of the rapidity and transverse momentum distribution for these events shows a characteristic intermittency pattern. Mini-jet like structures arise in a azimuth angle rapidity lego plot. These features allow for a unique identification of the class of "critical events" in an event by event analysis in current and future experiments with relativistic ...

  6. Achieving Order through CHAOS: the LLNL HPC Linux Cluster Experience

    Energy Technology Data Exchange (ETDEWEB)

    Braby, R L; Garlick, J E; Goldstone, R J

    2003-05-02

    Since fall 2001, Livermore Computing at Lawrence Livermore National Laboratory has deployed 11 Intel IA-32-based Linux clusters ranging in size up to 1154 nodes. All provide a common programming model and implement a similar cluster architecture. Hardware components are carefully selected for performance, usability, manageability, and reliability and are then integrated and supported using a strategy that evolved from practical experience. Livermore Computing Linux clusters run a common software environment that is developed and maintained in-house while drawing components and additional support from the open source community and industrial partnerships. The environment is based on Red Hat Linux and adds kernel modifications, cluster system management, monitoring and failure detection, resource management, authentication and access control, development environment, and parallel file system. The overall strategy has been successful and demonstrates that world-class high-performance computing resources can be built and maintained using commodity off-the-shelf hardware and open source software.

  7. Refractory chronic cluster headache

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  8. Kinematics of Clustering

    CERN Document Server

    Wang, Steven; Metcalfe, Guy; Wu, Jie

    2014-01-01

    The dynamical system for inertial particles in fluid flow has both attracting and repelling regions, the interplay of which can localize particles. In laminar flow experiments we find that particles, initially moving throughout the fluid domain, can undergo an instability and cluster into subdomains of the fluid when the flow Reynolds number exceeds a critical value that depends on particle and fluid inertia. We derive an expression for the instability boundary and for a universal curve that describes the clustering rate for all particles.

  9. South Asian Cluster

    Directory of Open Access Journals (Sweden)

    Ionel Sergiu Pirju

    2014-12-01

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

  10. Cluster's last stand?

    OpenAIRE

    Lockwood, Mike

    1997-01-01

    On 4 June last year the first attempt to make three-dimensional measurements in space was lost when the Ariane 5 rocket veered off course and self-destructed, 39 s into its maiden flight. On board were four identical spacecraft which made up Cluster,a mission that the European Space Agency called a “cornerstone” of its Horizon 2000 scientific programme. A full description of the Cluster satellites is given in a special issue of Space Science Reviews (Escoubet et al. 1997). Their loss de...

  11. Clustering Game Behavior Data

    DEFF Research Database (Denmark)

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

    2015-01-01

    and other techniques for player profiling and play style analysis have, therefore, become popular in the nascent field of game analytics. However, the proper use of clustering techniques requires expertise and an understanding of games is essential to evaluate results. With this paper, we address game data...... scientists and present a review and tutorial focusing on the application of clustering techniques to mine behavioral game data. Several algorithms are reviewed and examples of their application shown. Key topics such as feature normalization are discussed and open problems in the context of game analytics...

  12. An Emerge Approach in Inter Cluster Similarity for Quality Clusters

    Directory of Open Access Journals (Sweden)

    H. Venkateswara Reddy

    2013-04-01

    Full Text Available Relationship between the datasets is one most important issue in recent years. The recent methods are based mostly on the numerical data, but these methods are not suitable for real time data such as web pages, business transactions etc., which are known as Categorical data. It is difficult to find relationship in categorical data. In this paper, a new approach is proposed for finding the relationshipbetween the categorical data, hence to find relationship between the clusters. The main aim is to identify the quality clusters based on the relationship between clusters. If there is no relationship between clusters then those clusters are treated as quality clusters.

  13. An "expanded" class perspective

    DEFF Research Database (Denmark)

    Steur, Luisa Johanna

    2014-01-01

    Following the police raid on the ‘Muthanga’ land occupation by Adivasi (‘indigenous’) activists in Kerala, India, in February 2003, intense public debate erupted about the fate of Adivasis in this ‘model’ development state. Most commentators saw the land occupation either as the fight...... capitalist relations, the exact social processes under which they were having to make a living, and what had only recently—and still largely ambiguously—made them ready to identify themselves politically as ‘Adivasi’. Demonstrating the usefulness of ethnographic curiosity driven by an ‘expanded’ class...

  14. The Class of '34

    OpenAIRE

    Cairney, Richard

    1995-01-01

    The Great Depression raged, governments were beleaguered, the unemployment rate stood at 30%, scurvy stalked the poor and no one was immune to contagious diseases such as scarlet fever, polio and measles when the University of Alberta School of Medicine's Class of '34 graduated. For four alumni who recently gathered in Edmonton—Drs. Morley Hodgson, Melvin Gaudin, John McLurg and Edmund Cairns—their 60th-anniversary reunion was a time to recall the changes they have witnessed in medicine, incl...

  15. Mining Java Class Naming Conventions

    OpenAIRE

    Butler, Simon; Wermelinger, Michel; Yu, Yijun; Sharp, Helen

    2011-01-01

    Class names represent the concepts implemented in object-oriented source code and are key elements in program comprehension and, thus, software maintenance. Programming conventions often state that class names should be noun-phrases, but there is little further guidance for developers on the composition of class names. Other researchers have observed that the majority of Java class identifier names are composed of one or more nouns preceded, optionally, by one or more adjectives. However, no ...

  16. Combining cluster number counts and galaxy clustering

    CERN Document Server

    Lacasa, Fabien

    2016-01-01

    We present a detailed modelling of the joint covariance matrix between cluster number counts and the galaxy angular power spectrum. To this end, we use a Halo Model framework complemented by a Halo Occupation Distribution model (HOD), and we work in full-sky. We demonstrate the importance of accounting for non-Gaussianity to produce accurate covariance predictions, as the Gaussian part of the covariance can in fact become subdominant in certain configurations. We discuss in particular the case of the super-sample covariance (SSC), including the effects of galaxy shot-noise, halo second order bias and non-local bias, and demonstrating interesting mathematical properties. Using the joint covariance matrix and a Fisher matrix methodology, we examine the prospects of combining these two probes to constrain cosmological and HOD parameters. We find that the combination indeed results in noticeable better constraints, in particular because the cross-covariance introduces a synergy between the probes on small scales....

  17. Localized attack on clustering networks

    CERN Document Server

    Dong, Gaogao; Du, Ruijin; Shao, Shuai; Stanley, H Eugene; Shlomo, Havlin

    2016-01-01

    Clustering network is one of which complex network attracting plenty of scholars to discuss and study the structures and cascading process. We primarily analyzed the effect of clustering coefficient to other various of the single clustering network under localized attack. These network models including double clustering network and star-like NON with clustering and random regular (RR) NON of ER networks with clustering are made up of at least two networks among which exist interdependent relation among whose degree of dependence is measured by coupling strength. We show both analytically and numerically, how the coupling strength and clustering coefficient effect the percolation threshold, size of giant component, critical coupling point where the behavior of phase transition changes from second order to first order with the increase of coupling strength between the networks. Last, we study the two types of clustering network: one type is same with double clustering network in which each subnetwork satisfies ...

  18. An Analysis of Particle Swarm Optimization with Data Clustering-Technique for Optimization in Data Mining

    Directory of Open Access Journals (Sweden)

    Amreen Khan,

    2010-07-01

    Full Text Available Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. Clustering aims at representing large datasets by a fewer number of prototypes or clusters. It brings simplicity in modeling data and thus plays a central role in the process of knowledge discovery and data mining. Data mining tasks require fast and accurate partitioning of huge datasets, which may come with a variety of attributes or features. This imposes severe computational requirements on the relevant clustering techniques. A family of bio-inspired algorithms, well-known as Swarm Intelligence (SI has recently emerged that meets these requirements and has successfully been applied to a number ofreal world clustering problems. This paper looks into the use ofParticle Swarm Optimization for cluster analysis. The effectiveness of Fuzzy C-means clustering provides enhanced performance and maintains more diversity in the swarm and also allows the particles to be robust to trace the changing environment.

  19. All quiet in Globular Clusters

    CERN Document Server

    Dobrotka, A; Menou, K; Dobrotka, Andrej; Lasota, Jean-Pierre; Menou, Kristen

    2006-01-01

    Cataclysmic Variables (CVs) should be present in large numbers in Globular Clusters (GCs). Numerous low-luminosity X-ray sources identified over the past few years as candidate CVs in GCs support this notion. Yet, very few "cataclysms," the characteristic feature of this class of objects in the field, have been observed in GCs. We address this discrepancy here, within the framework of the standard Disk Instability Model for CV outbursts. We argue that the paucity of outbursts in GCs is probably not a direct consequence of the donors' low metallicities. We present diagnostics based on outburst properties allowing tests of the hypothesis that rare cataclysms are entirely due to lower mass transfer rates in GCs relative to the field, and we argue against this explanation. Instead, we propose that a combination of low mass transfer rates (>~ 10^14-15 g/s) and moderately strong white dwarf magnetic moments (>~ 10^30 G cm^3) stabilize CV disks in GCs and thus prevent most of them from experiencing frequent outburst...

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

    Directory of Open Access Journals (Sweden)

    FANG, W.

    2012-02-01

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

  1. 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.

  2. Reconciling Virtual Classes with Genericity

    DEFF Research Database (Denmark)

    Ernst, Erik

    2006-01-01

    classes. As a result, a kind of type parameters have been introduced, but they are simple and only used where they excel. Conversely, final definitions of virtual classes have been re- moved from the language, thus making virtual classes more flexible. The result- ing language presents a clearer and more...

  3. Team Learning in Large Classes.

    Science.gov (United States)

    Roueche, Suanne D., Ed.

    1984-01-01

    Information and suggestions are provided on the use of team learning in large college classes. Introductory material discusses the negative cycle of student-teacher interaction that may be provoked by large classes, and the use of permanent, heterogeneous, six- or seven-member student learning groups as the central focus of class activity as a…

  4. Lab classes in chemistry learning an artificial intelligence view

    OpenAIRE

    Figueiredo, Margarida; Esteves, M. Lurdes; Neves, José; Vicente, Henrique (Orientador)

    2014-01-01

    The teaching methodology used in lab classes in Chemistry Learning was studied for a cohort of 702 students in the 10th grade of Portuguese Secondary Schools. The k-Means Clustering Method, with k values ranging between 2 (two) and 4 (four), was used in order to segment the data. Decision Trees were used for the development of explanatory models of the segmentation. The results obtained showed that the majority of the answerers considered that experimentation is central on Chemistry learning....

  5. PVM Support for Clusters

    Science.gov (United States)

    Springer, P.

    2000-01-01

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

  6. Evolution of Galaxy Clustering

    OpenAIRE

    Bagla, J. S.

    1997-01-01

    We show that the galaxy correlation function does not evolve in proportion with the correlation function of the underlying mass distribution. Earliest galaxies cluster very strongly and the amplitude of the galaxy correlation function decreases from this large value. This continues till the average peaks have collapsed, after which, the galaxy correlation function does not evolve very strongly.

  7. Fuzzy clustering of mechanisms

    Indian Academy of Sciences (India)

    Amitabha Ghosh; Dilip Kumar Pratihar; M V V Amarnath; Guenter Dittrich; Jorg Mueller

    2012-10-01

    During the course of development of Mechanical Engineering, a large number of mechanisms (that is, linkages to perform various types of tasks) have been conceived and developed. Quite a few atlases and catalogues were prepared by the designers of machines and mechanical systems. However, often it is felt that a clustering technique for handling the list of large number of mechanisms can be very useful,if it is developed based on a scientific principle. In this paper, it has been shown that the concept of fuzzy sets can be conveniently used for this purpose, if an adequate number of properly chosen attributes (also called characteristics) are identified. Using two clustering techniques, the mechanisms have been classified in the present work and in future, it may be extended to develop an expert system, which can automate type synthesis phase of mechanical design. To the best of the authors’ knowledge, this type of clustering of mechanisms has not been attempted before. Thus, this is the first attempt to cluster the mechanisms based on some quantitative measures. It may help the engineers to carry out type synthesis of the mechanisms.

  8. Clustering under Perturbation Resilience

    CERN Document Server

    Balcan, Maria Florina

    2011-01-01

    Recently, Bilu and Linial \\cite{BL} formalized an implicit assumption often made when choosing a clustering objective: that the optimum clustering to the objective should be preserved under small multiplicative perturbations to distances between points. They showed that for max-cut clustering it is possible to circumvent NP-hardness and obtain polynomial-time algorithms for instances resilient to large (factor $O(\\sqrt{n})$) perturbations, and subsequently Awasthi et al. \\cite{ABS10} considered center-based objectives, giving algorithms for instances resilient to O(1) factor perturbations. In this paper, we greatly advance this line of work. For the $k$-median objective, we present an algorithm that can optimally cluster instances resilient to $(1 + \\sqrt{2})$-factor perturbations, solving an open problem of Awasthi et al.\\cite{ABS10}. We additionally give algorithms for a more relaxed assumption in which we allow the optimal solution to change in a small $\\epsilon$ fraction of the points after perturbation. ...

  9. Clustering high dimensional data

    DEFF Research Database (Denmark)

    Assent, Ira

    2012-01-01

    High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known to...

  10. Detecting alternative graph clusterings.

    Science.gov (United States)

    Mandala, Supreet; Kumara, Soundar; Yao, Tao

    2012-07-01

    The problem of graph clustering or community detection has enjoyed a lot of attention in complex networks literature. A quality function, modularity, quantifies the strength of clustering and on maximization yields sensible partitions. However, in most real world networks, there are an exponentially large number of near-optimal partitions with some being very different from each other. Therefore, picking an optimal clustering among the alternatives does not provide complete information about network topology. To tackle this problem, we propose a graph perturbation scheme which can be used to identify an ensemble of near-optimal and diverse clusterings. We establish analytical properties of modularity function under the perturbation which ensures diversity. Our approach is algorithm independent and therefore can leverage any of the existing modularity maximizing algorithms. We numerically show that our methodology can systematically identify very different partitions on several existing data sets. The knowledge of diverse partitions sheds more light into the topological organization and helps gain a more complete understanding of the underlying complex network.

  11. Galactic Open Clusters

    CERN Document Server

    Von Hippel, T

    2005-01-01

    The study of open clusters has a classic feel to it since the subject predates anyone alive today. Despite the age of this topic, I show via an ADS search that its relevance and importance in astronomy has grown faster in the last few decades than astronomy in general. This is surely due to both technical reasons and the interconnection of the field of stellar evolution to many branches of astronomy. In this review, I outline what we know today about open clusters and what they have taught us about a range of topics from stellar evolution to Galactic structure to stellar disk dissipation timescales. I argue that the most important astrophysics we have learned from open clusters is stellar evolution and that its most important product has been reasonably precise stellar ages. I discuss where open cluster research is likely to go in the next few years, as well as in the era of 20m telescopes, SIM, and GAIA. Age will continue to be of wide relevance in astronomy, from cosmology to planet formation timescales, an...

  12. Disentangling Porterian Clusters

    DEFF Research Database (Denmark)

    Jagtfelt, Tue

    intertwined and that Porter’s consciously paradigmatic textbook very likely gained worldwide influence due to two interrelated factors. The first factor is the deliberately holistic gestalt figure propounded in Nations, which prompted scientific communities to pursue cluster research; the second factor...

  13. Curriculum Guide Construction Cluster.

    Science.gov (United States)

    Kline, Ken

    As part of a model construction cluster curriculum development project, this guide was developed and implemented in the Beaverton (Oregon) School District. The curriculum guide contains 16 units covering the following topics: introduction to construction jobs; safety and first aid; blueprint readings; basic mathematics; site work; framing; roofing…

  14. Data clustering algorithms and applications

    CERN Document Server

    Aggarwal, Charu C

    2013-01-01

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

  15. The open cluster NGC 7142: interstellar extinction, distance and age

    CERN Document Server

    Straizys, V; Boyle, R P; Zdanavicius, K; Zdanavicius, J; Laugalys, V; Kazlauskas, A

    2013-01-01

    The results of medium-band photometry of 1037 stars in the area of old open cluster NGC 7142 down to V = 20.1 mag in the Vilnius seven-colour system are presented. Photometric results are used to classify in spectral and luminosity classes about 80 percent of stars down to V = 18.5 mag, to identify cluster members, to determine the main cluster parameters and to investigate the interstellar extinction in this direction. The average extinction A_V of the cluster is about 1.1 mag, E(B-V) = 0.35, and its distance is 2.3 kpc (the distance modulus 11.8 mag). The age of the cluster, 3.0 Gyr, is estimated from the intrinsic colour-magnitude diagram with individual dereddening of each star and the Padova isochrones. The surface distribution of the extinction is shown. The reddening of the eclipsing variable V375 Cep is found to be close to the average reddening of the cluster. Probably, the cluster contains five red clump giants, two asymptotic branch stars and four blue stragglers.

  16. Abelian Non-Global Logarithms from Soft Gluon Clustering

    CERN Document Server

    Kelley, Randall; Zuberi, Saba

    2012-01-01

    Most recombination-style jet algorithms cluster soft gluons in a complex way. This leads to correlations in the soft gluon phase space and introduces logarithmic corrections to jet cross sections. The leading Abelian clustering logarithms occur at least at next-to leading logarithm (NLL) in the exponent of the distribution, and we show that new clustering effects contributing at NLL likely arise at each order. Therefore we find that it is unlikely that clustering logs can be resummed to NLL. Clustering logarithms make the anti-kT algorithm theoretically preferred, for which they are power suppressed. They can arise in Abelian and non-Abelian terms, and we calculate the Abelian clustering logarithms at two loops for the jet mass distribution using the Cambridge/Aachen and kT algorithms, including jet radius dependence, which extends previous results. We find that previously identified logarithms from clustering effects can be naturally thought of as a class of non-global logarithms (NGLs), which have tradition...

  17. Quartile Clustering: A quartile based technique for Generating Meaningful Clusters

    CERN Document Server

    Goswami, Saptarsi

    2012-01-01

    Clustering is one of the main tasks in exploratory data analysis and descriptive statistics where the main objective is partitioning observations in groups. Clustering has a broad range of application in varied domains like climate, business, information retrieval, biology, psychology, to name a few. A variety of methods and algorithms have been developed for clustering tasks in the last few decades. We observe that most of these algorithms define a cluster in terms of value of the attributes, density, distance etc. However these definitions fail to attach a clear meaning/semantics to the generated clusters. We argue that clusters having understandable and distinct semantics defined in terms of quartiles/halves are more appealing to business analysts than the clusters defined by data boundaries or prototypes. On the samepremise, we propose our new algorithm named as quartile clustering technique. Through a series of experiments we establish efficacy of this algorithm. We demonstrate that the quartile clusteri...

  18. Kohonen Maps Combined to K-means in a Two Level Strategy for Time Series ClusteringApplication to Meteorological and Electricity Load data

    OpenAIRE

    Tarek, Khadir M.; Sofiane, Khdairia; Farouk, Benabbas

    2010-01-01

    Time series analysis using Kohonen maps, allows a rough visual identification of the different existing classes. The K-Means algorithm comes as a complement for better class clustering and a clear frontiers definition when validated using different types of indices. Using a two stage clustering procedure seems to be more efficient than a direct clustering approach involving only SOM or K-means algorithms from an applicative and results view points. The obtained classification is also more com...

  19. Estimation and Model Selection for Model-Based Clustering with the Conditional Classification Likelihood

    CERN Document Server

    Baudry, Jean-Patrick

    2012-01-01

    The Integrated Completed Likelihood (ICL) criterion has been proposed by Biernacki et al. (2000) in the model-based clustering framework to select a relevant number of classes and has been used by statisticians in various application areas. A theoretical study of this criterion is proposed. A contrast related to the clustering objective is introduced: the conditional classification likelihood. This yields an estimator and a model selection criteria class. The properties of these new procedures are studied and ICL is proved to be an approximation of one of these criteria. We oppose these results to the current leading point of view about ICL, that it would not be consistent. Moreover these results give insights into the class notion underlying ICL and feed a reflection on the class notion in clustering. General results on penalized minimum contrast criteria and on mixture models are derived, which are interesting in their own right.

  20. The luminosity function of cluster galaxies relations among M$_{1}$, M* and the morphological type

    CERN Document Server

    Trevese, D; Appodia, B

    1996-01-01

    A study of the luminosity function of 36 Abell clusters of galaxies has been carried out using photographic plates obtained with the Palomar 1.2 m Schmidt telescope. The relation between the magnitude M_1 of the brightest cluster member and the Schechter function parameter M* has been analyzed. A positive correlation between M* and M_1 is found. However clusters appear segregated in the M_1-M* plane according to their Rood & Sastry class in such a way that on average M_1 becomes brighter while M* becomes fainter going from late to early Rood & Sastry and also Bautz & Morgan classes. Also a partial correlation analysis involving the magnitude M_10 of the 10th brightest galaxy, shows a negative intrinsic correlation between M_1 and M*. These results agree with the cannibalism model for the formation of brightest cluster members, and provide new constraints for theories of cluster formation and evolution.

  1. The Rotation of Galaxy Clusters

    Science.gov (United States)

    Tovmassian, H. M.

    2015-09-01

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

  2. The rotation of Galaxy Clusters

    CERN Document Server

    Tovmassian, Hrant M

    2015-01-01

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

  3. Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

    Directory of Open Access Journals (Sweden)

    Jeban Ganesalingam

    Full Text Available BACKGROUND: Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS: Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS: The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001. CONCLUSION: The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

  4. Class Discovery in Galaxy Classification

    CERN Document Server

    Bazell, D; Bazell, David; Miller, David J.

    2004-01-01

    In recent years, automated, supervised classification techniques have been fruitfully applied to labeling and organizing large astronomical databases. These methods require off-line classifier training, based on labeled examples from each of the (known) object classes. In practice, only a small batch of labeled examples, hand-labeled by a human expert, may be available for training. Moreover, there may be no labeled examples for some classes present in the data, i.e. the database may contain several unknown classes. Unknown classes may be present due to 1) uncertainty in or lack of knowledge of the measurement process, 2) an inability to adequately ``survey'' a massive database to assess its content (classes), and/or 3) an incomplete scientific hypothesis. In recent work, new class discovery in mixed labeled/unlabeled data was formally posed, with a proposed solution based on mixture models. In this work we investigate this approach, propose a competing technique suitable for class discovery in neural network...

  5. Be phenomenon in open clusters: Results from a survey of emission-line stars in young open clusters

    CERN Document Server

    Mathew, Blesson; Bhatt, Bhuwan Chandra

    2008-01-01

    Emission-line stars in young open clusters are identified to study their properties, as a function of age, spectral type and their evolutionary state. 207 open star clusters were observed using slitless spectroscopy method and 157 emission stars were identified in 42 clusters. We have found 54 new emission-line stars in 24 open clusters, out of which 19 clusters are found to house emission stars for the first time. About 20% clusters harbour emission stars. The fraction of clusters housing emission stars is maximum in both the 0--10 and 20--30 Myr age bin ($\\sim$ 40% each) and in the other age bins, this fraction ranges between 10% -- 25%, upto 80 Myr. We have used optical colour magnitude diagram (CMD) along with Near-IR Colour-Colour diagram (NIR CCDm) to classify the emission stars into Classical Be (CBe) stars and Herbig Be (HBe) stars. Most of the emission stars in our survey belong to CBe class ($\\sim$ 92%) while a few are HBe stars ($\\sim$ 6%) and HAe stars ($\\sim$1%). The CBe stars are located all alo...

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

    NARCIS (Netherlands)

    Deng, Y.; Qian, X.; Blöte, H.W.J.

    2009-01-01

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

  7. Merging Galaxy Cluster Abell 2255 in Mid-Infrared

    CERN Document Server

    Shim, Hyunjin; Lee, Hyung Mok; Lee, Myung Gyoon; Kim, Seong Jin; Hwang, Ho Seong; Hwang, Narae; Ko, Jongwan; Lee, Jong Chul; Lim, Sungsoon; Matsuhara, Hideo; Seo, Hyunjong; Wada, Takehiko; Goto, Tomotsugu

    2010-01-01

    We present the mid-infrared (MIR) observation of a nearby galaxy cluster, Abell 2255 by the AKARI space telescope. Using the AKARI's continuous wavelength coverage between 3-24 micron and the wide field of view, we investigate the properties of cluster member galaxies to see how the infall of the galaxies, the cluster substructures, and the cluster-cluster merger influence their evolution. We show that the excess of MIR (11 micron) flux is a good indicator to discriminate galaxies at different evolutionary stages, and divide galaxies into three classes accordingly : strong MIR-excess (N3-S11>0.2) galaxies that include both unobscured and obscured star-forming galaxies, weak MIR-excess (-2.05 Gyr) galaxies where the MIR emission arises mainly from the circumstellar dust around AGB stars, and intermediate MIR-excess (-1.2classes that are less than a few Gyrs old past the prime star formation activity. With the MIR-excess diagnostics, we investigate how local and cl...

  8. Network class superposition analyses.

    Science.gov (United States)

    Pearson, Carl A B; Zeng, Chen; Simha, Rahul

    2013-01-01

    Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30) for the yeast cell cycle process), considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses. PMID:23565141

  9. Anticancer properties of distinct antimalarial drug classes.

    Directory of Open Access Journals (Sweden)

    Rob Hooft van Huijsduijnen

    Full Text Available We have tested five distinct classes of established and experimental antimalarial drugs for their anticancer potential, using a panel of 91 human cancer lines. Three classes of drugs: artemisinins, synthetic peroxides and DHFR (dihydrofolate reductase inhibitors effected potent inhibition of proliferation with IC50s in the nM- low µM range, whereas a DHODH (dihydroorotate dehydrogenase and a putative kinase inhibitor displayed no activity. Furthermore, significant synergies were identified with erlotinib, imatinib, cisplatin, dasatinib and vincristine. Cluster analysis of the antimalarials based on their differential inhibition of the various cancer lines clearly segregated the synthetic peroxides OZ277 and OZ439 from the artemisinin cluster that included artesunate, dihydroartemisinin and artemisone, and from the DHFR inhibitors pyrimethamine and P218 (a parasite DHFR inhibitor, emphasizing their shared mode of action. In order to further understand the basis of the selectivity of these compounds against different cancers, microarray-based gene expression data for 85 of the used cell lines were generated. For each compound, distinct sets of genes were identified whose expression significantly correlated with compound sensitivity. Several of the antimalarials tested in this study have well-established and excellent safety profiles with a plasma exposure, when conservatively used in malaria, that is well above the IC50s that we identified in this study. Given their unique mode of action and potential for unique synergies with established anticancer drugs, our results provide a strong basis to further explore the potential application of these compounds in cancer in pre-clinical or and clinical settings.

  10. Eclipsing binaries in open clusters

    DEFF Research Database (Denmark)

    Southworth, John; Clausen, J.V.

    2006-01-01

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

  11. Radio observations of Planck clusters

    CERN Document Server

    Kale, Ruta

    2012-01-01

    Recently, a number of new galaxy clusters have been detected by the ESA-Planck satellite, the South Pole Telescope and the Atacama Cosmology Telescope using the Sunyaev-Zeldovich effect. Several of the newly detected clusters are massive, merging systems with disturbed morphology in the X-ray surface brightness. Diffuse radio sources in clusters, called giant radio halos and relics, are direct probes of cosmic rays and magnetic fields in the intra-cluster medium. These radio sources are found to occur mainly in massive merging clusters. Thus, the new SZ-discovered clusters are good candidates to search for new radio halos and relics. We have initiated radio observations of the clusters detected by Planck with the Giant Metrewave Radio Telescope. These observations have already led to the detection of a radio halo in PLCKG171.9-40.7, the first giant halo discovered in one of the new Planck clusters.

  12. The Evolution of Cluster Substructure

    CERN Document Server

    Jeltema, T E; Bautz, M W; Buote, D A; Jeltema, Tesla E.; Canizares, Claude R.; Bautz, Mark W.; Buote, David A.

    2003-01-01

    Using Chandra archival data, we have begun a study to quantify the evolution of cluster morphology with redshift. To quantify cluster morphology, we use the power ratio method developed by Buote and Tsai (1995). Power ratios are constructed from moments of the two-dimensional gravitational potential and are, therefore, related to a cluster's dynamical state. Our sample will include around 50 clusters from the Chandra archive with redshifts between 0.11 and 1.1. These clusters were selected from two fairly complete flux-limited X-ray surveys (the ROSAT Bright Cluster Sample and the Einstein Medium Sensitivity Survey), and additional high-redshift clusters were selected from recent ROSAT flux-limited surveys. Here we present preliminary results from the first 15 clusters in this sample. Of these, eight have redshifts below 0.5, and seven have redshifts above 0.5.

  13. Augmented mixed models for clustered proportion data.

    Science.gov (United States)

    Bandyopadhyay, Dipankar; Galvis, Diana M; Lachos, Victor H

    2014-12-01

    Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

  14. Monopole clusters in Abelian projected gauge theories

    CERN Document Server

    Hart, A

    1998-01-01

    We show that the monopole currents which one obtains in the maximally Abelian gauge of SU(2) fall into two quite distinct classes (when the volume is large enough). In each field configuration there is precisely one cluster that permeates the whole lattice volume. It has a current density and a magnetic screening mass that scale and it produces the whole of the string tension. The remaining clusters have a number density that follows an approximate power law proportional to the inverse cube of l where l is the length of the monopole world line in lattice units. These clusters are localised in space-time with radii which vary as the square root of l. In terms of the radius r these `lumps' have a scale-invariant distribution proportional to (dr/r . 1/{r^4}). Moreover they appear not to contribute at all to the string tension. The fact that they are scale-invariant at small distances would seem to rule out an instanton origin.

  15. Endogenous Small RNA Clusters in Plants

    Directory of Open Access Journals (Sweden)

    Yong-Xin Liu

    2014-04-01

    Full Text Available In plants, small RNAs (sRNAs usually refer to non-coding RNAs (ncRNAs with lengths of 20–24 nucleotides. sRNAs are involved in the regulation of many essential processes related to plant development and environmental responses. sRNAs in plants are mainly grouped into microRNAs (miRNAs and small interfering RNAs (siRNAs, and the latter can be further classified into trans-acting siRNAs (ta-siRNAs, repeat-associated siRNAs (ra-siRNAs, natural anti-sense siRNAs (nat-siRNAs, etc. Many sRNAs exhibit a clustered distribution pattern in the genome. Here, we summarize the features and functions of cluster-distributed sRNAs, aimed to not only provide a thorough picture of sRNA clusters (SRCs in plants, but also shed light on the identification of new classes of functional sRNAs.

  16. Textile Industrial Clusters in China

    Institute of Scientific and Technical Information of China (English)

    Nie Ting

    2010-01-01

    @@ "National Textile Industry Cluster Development Seminar" convened,held by China National Textile and Apparel Council,23 cities and towns were awarded as China's Textile Industry Cluster Pilot District.By far,China's textile industrial clusters have grown to 164,which indicate a quick and gorgeous development.These textile industrial clusters have a great impact on the local economy and even the whole national textile industry's development.

  17. [Cluster analysis in biomedical researches].

    Science.gov (United States)

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

    2013-01-01

    Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research. PMID:24640781

  18. Clustering analysis using Swarm Intelligence

    OpenAIRE

    Farmani, Mohammad Reza

    2016-01-01

    This thesis is concerned with the application of the swarm intelligence methods in clustering analysis of datasets. The main objectives of the thesis are ∙ Take the advantage of a novel evolutionary algorithm, called artificial bee colony, to improve the capability of K-means in finding global optimum clusters in nonlinear partitional clustering problems. ∙ Consider partitional clustering as an optimization problem and an improved antbased algorithm, named Opposition-Based A...

  19. Defining Clusters of Related Industries

    OpenAIRE

    Mercedes Delgado; Porter, Michael E.; Scott Stern

    2014-01-01

    Clusters are geographic concentrations of industries related by knowledge, skills, inputs, demand, and/or other linkages. A growing body of empirical literature has shown the positive impact of clusters on regional and industry performance, including job creation, patenting, and new business formation. There is an increasing need for cluster-based data to support research, facilitate comparisons of clusters across regions, and support policymakers and practitioners in defining regional strate...

  20. Practical Introduction to Clustering Data

    CERN Document Server

    Hartmann, Alexander K

    2016-01-01

    Data clustering is an approach to seek for structure in sets of complex data, i.e., sets of "objects". The main objective is to identify groups of objects which are similar to each other, e.g., for classification. Here, an introduction to clustering is given and three basic approaches are introduced: the k-means algorithm, neighbour-based clustering, and an agglomerative clustering method. For all cases, C source code examples are given, allowing for an easy implementation.

  1. The Assembly of Galaxy Clusters

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-05-16

    We study the formation of fifty-three galaxy cluster-size dark matter halos (M = 10{sup 14.0-14.76} M{sub {circle_dot}}) formed within a pair of cosmological {Lambda}CDM N-body simulations, and track the accretion histories of cluster subhalos with masses large enough to host {approx} 0.1L{sub *} galaxies. By associating subhalos with cluster galaxies, we find the majority of galaxies in clusters experience no 'pre-processing' in the group environment prior to their accretion into the cluster. On average, {approx} 70% of cluster galaxies fall into the cluster potential directly from the field, with no luminous companions in their host halos at the time of accretion; and less than {approx} 12% are accreted as members of groups with five or more galaxies. Moreover, we find that cluster galaxies are significantly less likely to have experienced a merger in the recent past ({approx}< 6 Gyr) than a field halo of the same mass. These results suggest that local, cluster processes like ram-pressure stripping, galaxy harassment, or strangulation play the dominant role in explaining the difference between cluster and field populations at a fixed stellar mass; and that pre-evolution or past merging in the group environment is of secondary importance for setting cluster galaxy properties for most clusters. The accretion times for z = 0 cluster members are quite extended, with {approx} 20% incorporated into the cluster halo more than 7 Gyr ago and {approx} 20% within the last 2 Gyr. By comparing the observed morphological fractions in cluster and field populations, we estimate an approximate time-scale for late-type to early-type transformation within the cluster environment to be {approx} 6 Gyr.

  2. Massive star clusters in galaxies

    CERN Document Server

    Harris, William E

    2009-01-01

    The ensemble of all star clusters in a galaxy constitutes its star cluster system. In this review, the focus of the discussion is on the ability of star clusters, particularly the systems of old massive globular clusters (GCSs), to mark the early evolutionary history of galaxies. I review current themes and key findings in GCS research, and highlight some of the outstanding questions that are emerging from recent work.

  3. Applying Data Clustering Feature to Speed Up Ant Colony Optimization

    OpenAIRE

    Chao-Yang Pang; Ben-Qiong Hu; Jie Zhang; Wei Hu; Zheng-Chao Shan

    2013-01-01

    Ant colony optimization (ACO) is often used to solve optimization problems, such as traveling salesman problem (TSP). When it is applied to TSP, its runtime is proportional to the squared size of problem $N$ so as to look less efficient. The following statistical feature is observed during the authors’ long-term gene data analysis using ACO: when the data size $N$ becomes big, local clustering appears frequently. That is, some data cluster tightly in a small area and form a class, and the cor...

  4. On clusters and clustering from atoms to fractals

    CERN Document Server

    Reynolds, PJ

    1993-01-01

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

  5. Recovery Rate of Clustering Algorithms

    NARCIS (Netherlands)

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

    2009-01-01

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

  6. Analytical Approximations to Galaxy Clustering

    OpenAIRE

    Mo, H. J.

    1997-01-01

    We discuss some recent progress in constructing analytic approximations to the galaxy clustering. We show that successful models can be constructed for the clustering of both dark matter and dark matter haloes. Our understanding of galaxy clustering and galaxy biasing can be greatly enhanced by these models.

  7. Geographic Projection of Cluster Composites

    NARCIS (Netherlands)

    Nerbonne, J.; Bosveld-de Smet, L.M.; Kleiweg, P.; Blackwell, A.; Marriott, K.; Shimojima, A.

    2004-01-01

    A composite cluster map displays a fuzzy categorisation of geographic areas. It combines information from several sources to provide a visualisation of the significance of cluster borders. The basic technique renders the chance that two neighbouring locations are members of different clusters as the

  8. Programming with MPI on clusters

    International Nuclear Information System (INIS)

    The authors discuss the current state of development for the key aspects of MPI programming on clusters. These aspects are the evolution of the MPI Standard itself, developments in cluster hardware and system software that directly affect MPI implementations, and supporting software that facilitates the use of MPI on scalable clusters. In each case we give a brief background and summarize the current status

  9. Adaptive Clustering of Hypermedia Documents.

    Science.gov (United States)

    Johnson, Andrew; Fotouhi, Farshad

    1996-01-01

    Discussion of hypermedia systems focuses on a comparison of two types of adaptive algorithm (genetic algorithm and neural network) in clustering hypermedia documents. These clusters allow the user to index into the nodes to find needed information more quickly, since clustering is "personalized" based on the user's paths rather than representing…

  10. Merging Galaxy Cluster A2255 in Mid-infrared

    Science.gov (United States)

    Shim, Hyunjin; Im, Myungshin; Lee, Hyung Mok; Lee, Myung Gyoon; Kim, Seong Jin; Hwang, Ho Seong; Hwang, Narae; Ko, Jongwan; Lee, Jong Chul; Lim, Sungsoon; Matsuhara, Hideo; Seo, Hyunjong; Wada, Takehiko; Goto, Tomotsugu

    2011-01-01

    We present the mid-infrared (MIR) observation of a nearby galaxy cluster, A2255, by the AKARI space telescope. Using AKARI's continuous wavelength coverage between 3 and 24 μm and the wide field of view, we investigate the properties of cluster member galaxies to see how the infall of the galaxies, the cluster substructures, and the cluster-cluster merger influence their evolution. We show that the excess of MIR (~11 μm) flux is a good indicator for discriminating galaxies at different evolutionary stages and for dividing galaxies into three classes accordingly: strong MIR-excess (N3 - S11>0.2) galaxies that include both unobscured and obscured star-forming galaxies; weak MIR-excess (-2.0 S11 5 Gyr) galaxies where the MIR emission arises mainly from the circumstellar dust around AGB stars; and intermediate MIR-excess (-1.2 S11 < 0.2) galaxies in between the two classes that are less than a few Gyr old past the prime star formation activity. With the MIR-excess diagnostics, we investigate how local and cluster-scale environments affect the individual galaxies. We derive the total star formation rate (SFR) and the specific SFR of A2255 using the strong MIR-excess galaxies. The dust-free, total SFR of A2255 is ~130 M sun yr-1, which is consistent with the SFRs of other clusters of galaxies at similar redshifts and with similar masses. We find no strong evidence that supports enhanced star formation either inside the cluster or in the substructure region, suggesting that the infall or the cluster merging activities tend to suppress star formation. The intermediate MIR-excess galaxies, representing galaxies in transition from star-forming galaxies to quiescent galaxies, are located preferentially at the medium density region or cluster substructures with higher surface density of galaxies. Our findings suggest that galaxies are being transformed from star-forming galaxies into red, quiescent galaxies from the infall region through near the core which can be explained

  11. Focused Crawling of the Deep Web Using Service Class Descriptions

    Energy Technology Data Exchange (ETDEWEB)

    Rocco, D; Liu, L; Critchlow, T

    2004-06-21

    Dynamic Web data sources--sometimes known collectively as the Deep Web--increase the utility of the Web by providing intuitive access to data repositories anywhere that Web access is available. Deep Web services provide access to real-time information, like entertainment event listings, or present a Web interface to large databases or other data repositories. Recent studies suggest that the size and growth rate of the dynamic Web greatly exceed that of the static Web, yet dynamic content is often ignored by existing search engine indexers owing to the technical challenges that arise when attempting to search the Deep Web. To address these challenges, we present DynaBot, a service-centric crawler for discovering and clustering Deep Web sources offering dynamic content. DynaBot has three unique characteristics. First, DynaBot utilizes a service class model of the Web implemented through the construction of service class descriptions (SCDs). Second, DynaBot employs a modular, self-tuning system architecture for focused crawling of the DeepWeb using service class descriptions. Third, DynaBot incorporates methods and algorithms for efficient probing of the Deep Web and for discovering and clustering Deep Web sources and services through SCD-based service matching analysis. Our experimental results demonstrate the effectiveness of the service class discovery, probing, and matching algorithms and suggest techniques for efficiently managing service discovery in the face of the immense scale of the Deep Web.

  12. Detection and Analysis of Clones in UML Class Models

    Directory of Open Access Journals (Sweden)

    Dhavleesh Rattan

    2015-07-01

    Full Text Available It is quite frequent to copy and paste code fragments in software development. The copied source code is called a software clone and the activity is referred to as code cloning. The presence of code clones hamper maintenance and may lead to bug propagation. Now-a-days, model driven development has become a standard industry practice. Duplicate parts in models i.e. model clones pose similar challenges as in source code. This paper presents an approach to detect clones in Unified Modeling Language class models. The core of our technique is the construction of a labeled, ranked tree corresponding to the UML class model where attributes with their data types and methods with their signatures are represented as subtrees. By grouping and clustering of repeating subtrees, the tool is able to detect duplications in a UML class model at different levels of granularity i.e. complete class diagram, attributes with their data types and methods with their signatures across the model and cluster of such attributes/methods. We propose a new classification of model clones with the objective of detecting exact and meaningful clones. Empirical evaluation of the tool using open source reverse engineered and forward designed models show some interesting and relevant clones which provide useful insights into software modeling practice.

  13. Detection and Analysis of Clones in UML Class Models

    Directory of Open Access Journals (Sweden)

    Dhavleesh Rattan

    2016-01-01

    Full Text Available It is quite frequent to copy and paste code fragments in software development. The copied source code is called a software clone and the activity is referred to as code cloning. The presence of code clones hamper maintenance and may lead to bug propagation. Now-a-days, model driven development has become a standard industry practice. Duplicate parts in models i.e. model clones pose similar challenges as in source code. This paper presents an approach to detect clones in Unified Modeling Language class models. The core of our technique is the construction of a labeled, ranked tree corresponding to the UML class model where attributes with their data types and methods with their signatures are represented as subtrees. By grouping and clustering of repeating subtrees, the tool is able to detect duplications in a UML class model at different levels of granularity i.e. complete class diagram, attributes with their data types and methods with their signatures across the model and cluster of such attributes/methods. We propose a new classification of model clones with the objective of detecting exact and meaningful clones. Empirical evaluation of the tool using open source reverse engineered and forward designed models show some interesting and relevant clones which provide useful insights into software modeling practice.

  14. Binaries in globular clusters

    Science.gov (United States)

    Hut, Piet; Mcmillan, Steve; Goodman, Jeremy; Mateo, Mario; Phinney, E. S.; Pryor, Carlton; Richer, Harvey B.; Verbunt, Frank; Weinberg, Martin

    1992-01-01

    Recent observations have shown that globular clusters contain a substantial number of binaries most of which are believed to be primordial. We discuss different successful optical search techniques, based on radial-velocity variables, photometric variables, and the positions of stars in the color-magnitude diagram. In addition, we review searches in other wavelengths, which have turned up low-mass X-ray binaries and more recently a variety of radio pulsars. On the theoretical side, we give an overview of the different physical mechanisms through which individual binaries evolve. We discuss the various simulation techniques which recently have been employed to study the effects of a primordial binary population, and the fascinating interplay between stellar evolution and stellar dynamics which drives globular-cluster evolution.

  15. Di - lambpha cluster states

    International Nuclear Information System (INIS)

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

  16. Outskirts of Galaxy Clusters

    CERN Document Server

    Reiprich, Thomas H; Ettori, Stefano; Israel, Holger; Lovisari, Lorenzo; Molendi, Silvano; Pointecouteau, Etienne; Roncarelli, Mauro

    2013-01-01

    Until recently, only about 10% of the total intracluster gas volume had been studied with high accuracy, leaving a vast region essentially unexplored. This is now changing and a wide area of hot gas physics and chemistry awaits discovery in galaxy cluster outskirts. Also, robust large-scale total mass profiles and maps are within reach. First observational and theoretical results in this emerging field have been achieved in recent years with sometimes surprising findings. Here, we summarize and illustrate the relevant underlying physical and chemical processes and review the recent progress in X-ray, Sunyaev--Zel'dovich, and weak gravitational lensing observations of cluster outskirts, including also brief discussions of technical challenges and possible future improvements.

  17. Are megaquakes clustered?

    CERN Document Server

    Daub, Eric G; Guyer, Robert A; Johnson, Paul A

    2012-01-01

    We study statistical properties of the number of large earthquakes over the past century. We analyze the cumulative distribution of the number of earthquakes with magnitude larger than threshold M in time interval T, and quantify the statistical significance of these results by simulating a large number of synthetic random catalogs. We find that in general, the earthquake record cannot be distinguished from a process that is random in time. This conclusion holds whether aftershocks are removed or not, except at magnitudes below M = 7.3. At long time intervals (T = 2-5 years), we find that statistically significant clustering is present in the catalog for lower magnitude thresholds (M = 7-7.2). However, this clustering is due to a large number of earthquakes on record in the early part of the 20th century, when magnitudes are less certain.

  18. Tailoring and Scaling Energetic Aluminum Clusters into Cluster Assembled Materials

    Science.gov (United States)

    Smith, Jordan Cesar

    As matter decreases in size the importance of a single atom increases exponentially. The properties of clusters, molecules with less than 100 atoms, will change drastically with the addition or removal of a single atom. Clusters have been shown to have properties that mimic other elements and properties that are completely unique. Cluster assemblies could enable the tailoring of precise properties in materials, providing cheap replacements for expensive elements, or novel materials for new applications. Aluminum clusters show great potential use in many applications including energy and catalysis. This work is focused on gaining a better understanding of how geometry and electronic structure affect aluminum cluster reactivity and how useful clusters might be successfully assembled into materials. The effects of doping aluminum cluster ions with boron atoms are reported and show that the addition of a single boron atom usually stabilizes the cluster while adding more boron atoms results in a breaking of symmetry and destabilization. A new analytical technique, matrix isolation cavity ring-down spectroscopy (MICRDS) was developed to help bridge the gap between gas phase cluster studies and condensed phase cluster materials. Molecules are trapped in an inert matrix and studied using cavity ring-down spectroscopy. MICRDS has the potential to also combine clusters into small stable units that would maintain their advantageous gas phase properties.

  19. Clusters and entrepreneurship

    OpenAIRE

    Delgado, Mercedes; Porter, Michael E.; Stern, Scott, 1969-

    2010-01-01

    This article examines the role of regional clusters in regional entrepreneurship. We focus on the distinct influences of convergence and agglomeration on growth in the number of start-up firms as well as in employment in these new firms in a given region-industry. While reversion to the mean and diminishing returns to entrepreneurship at the region-industry level can result in a convergence effect, the presence of complementary economic activity creates externalities that enhance incentives a...

  20. Clusters, Governance and Sustainability

    OpenAIRE

    Neto, Paulo; Serrano, Maria Manuel

    2010-01-01

    One of the most important aspects of current economical and social reality of each local and regional territory, and very much determinative for its economic development potential, is the nature of its territorial organization of the productive processes, as well as, the characteristics, and sophistication level, of the enterprise strategies that are functioning in it. This paper seeks to contribute to the ongoing discussion on the role of clusters as engines of economic and social developmen...

  1. Astrophysics of galaxy clusters

    Science.gov (United States)

    Ettori, Stefano

    2016-07-01

    As the nodes of the cosmic web, clusters of galaxies trace the large-scale distribution of matter in the Universe. They are thus privileged sites in which to investigate the complex physics of structure formation. However, the complete story of how these structures grow, and how they dissipate the gravitational and non-thermal components of their energy budget over cosmic time, is still beyond our grasp. Most of the baryons gravitationally bound to the cluster's halo is in the form of a diffuse, hot, metal-enriched plasma that radiates primarily in the X-ray band. X-ray observations of the evolving cluster population provide a unique opportunity to address such fundamental open questions as: How do hot diffuse baryons accrete and dynamically evolve in dark matter potentials? How and when was the energy that we observe in the ICM generated and distributed? Where and when are heavy elements produced and how are they circulated? We will present the ongoing activities to define the strategy on how an X-ray observatory with large collecting area and an unprecedented combination of high spectral and angular resolution, such as Athena, can address these questions.

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

    Directory of Open Access Journals (Sweden)

    Gulcin Salıngan

    2012-07-01

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

  3. Cluster headache after orbital exenteration.

    Science.gov (United States)

    Evers, S; Sörös, P; Brilla, R; Gerding, H; Husstedt, I W

    1997-10-01

    A 37-year-old man developed an ipsilateral headache which fulfilled the criteria for cluster headache after orbital extenteration because of a traumatic lesion of the bulb. The headache could be treated successfully by drugs usually applied in the therapy of cluster headache. Six similar cases of cluster headache after orbital exenteration could be identified in the literature suggesting that the eye itself is not necessarily part of the pathogenesis of cluster headache. We hypothesize that orbital exenteration can cause cluster headache by lesions of sympathetic structures. Possibly, these mechanisms are similar to those of sympathetic reflex dystrophy (Sudeck-Leriche syndrome) causing pain of the limbs. PMID:9350391

  4. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

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

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  5. Multiscale hierarchical support vector clustering

    Science.gov (United States)

    Hansen, Michael Saas; Holm, David Alberg; Sjöstrand, Karl; Ley, Carsten Dan; Rowland, Ian John; Larsen, Rasmus

    2008-03-01

    Clustering is the preferred choice of method in many applications, and support vector clustering (SVC) has proven efficient for clustering noisy and high-dimensional data sets. A method for multiscale support vector clustering is demonstrated, using the recently emerged method for fast calculation of the entire regularization path of the support vector domain description. The method is illustrated on artificially generated examples, and applied for detecting blood vessels from high resolution time series of magnetic resonance imaging data. The obtained results are robust while the need for parameter estimation is reduced, compared to support vector clustering.

  6. Silicon clusters: Chemistry and structure

    Energy Technology Data Exchange (ETDEWEB)

    Jarrold, M.F.; Ray, U.; Ijiri, Y. (AT and T Bell Labs., Murray Hill, NJ (USA))

    1991-01-01

    The chemical reactions of size selected silicon cluster ions (containing up to 70 atoms) have been studied with a number of different reagents using injected ion drift tube techniques. Both kinetic and equilibrium measurements have been performed as a function of temperature, and the influence of cluster annealing on chemical reactivity explored. Unlike metal clusters, where bulk behavior appears to be approached with around 30 atoms, large silicon clusters (n up to 70) are much less reactive than bulk silicon surfaces. These results suggest that the clusters in the size range examined here are not small crystals of bulk silicon, but have compact, high coordination number structures with few dangling bonds. (orig.).

  7. Experiencing a Flipped Mathematics Class

    OpenAIRE

    Larsen, A. Judy

    2013-01-01

    The flipped classroom is an old concept that has recently been redefined through the emergence of new technologies that allow teachers to deliver content out of class time. As such, various approaches for implementation exist. Most prominently, teachers are able to use class time in a student-centered manner, which allows students to experience the classroom in diverse ways. This study focuses on describing these experiences in a particular flipped adult upgrading mathematics class. Students ...

  8. Class Differences in Cohabitation Processes

    OpenAIRE

    Sassler, Sharon; Miller, Amanda J.

    2011-01-01

    Despite the burgeoning cohabitation literature, research has failed to examine social class variation in processes of forming and advancing such unions. Drawing upon in-depth interviews with 122 working- and middle-class cohabitors, we examine the duration between dating and moving in together, reasons for cohabiting, and subsequent plans. Transitions to cohabitation are more rapid among the working class. Respondents often cohabited for practical reasons—out of financial necessity, because i...

  9. The Development of Nanotechnological Clusters as the Elements of Nanoindustrial Infrastructure: European Experience

    Directory of Open Access Journals (Sweden)

    Beloglazova Svetlana Anatolyevna

    2015-05-01

    Full Text Available The international experience in managing innovative development of regions shows that at this level of global economic system there is an objective process of synthesis of scientific, industrial, economic and social policies in the form of peculiar entities, named clusters, which helps to create favorable environment for appearance and expansion of innovations. Development strategies of advanced countries embody the identification of key competencies of regions and creation of nanotechnological clusters in order to stimulate innovation. Such clusters are intended to develop the methods for nanotechnology application, create new types of business activities, and provide world-class quality. The importance of implementation of nanotechnological cluster policy being a factor of sustainable development of economic systems at micro-, meso- and macro- levels determines the necessity to consider the experience of successful nanotechnological clusters in Italy and France: the cluster of nanotechnologies in the Veneto region, which is the largest and most competitive cluster in Italy, generating up to 9.3 % of the Italy’s GDP, and the Minalogic cluster in the French region Grenoble, being included in the top 5 largest micro and nanotechnological clusters of the world while Grenoble is in the top 15 most innovative regions in the world. The author defines the largest cluster members, describes key areas and key measures of government and non-government support, analyzes economic performance of clusters and describes their impact on the economy of a region and a country as a whole.

  10. Predicting Acoustics in Class Rooms

    DEFF Research Database (Denmark)

    Christensen, Claus Lynge; Rindel, Jens Holger

    2005-01-01

    Typical class rooms have fairly simple geometries, even so room acoustics in this type of room is difficult to predict using today's room acoustic computer modeling software. The reasons why acoustics of class rooms are harder to predict than acoustics of complicated concert halls might be explai......Typical class rooms have fairly simple geometries, even so room acoustics in this type of room is difficult to predict using today's room acoustic computer modeling software. The reasons why acoustics of class rooms are harder to predict than acoustics of complicated concert halls might...... with surface scattering is presented. Each of the two scattering effects is modeled as frequency dependent functions....

  11. Clustering Methodologies for Software Engineering

    Directory of Open Access Journals (Sweden)

    Mark Shtern

    2012-01-01

    Full Text Available The size and complexity of industrial strength software systems are constantly increasing. This means that the task of managing a large software project is becoming even more challenging, especially in light of high turnover of experienced personnel. Software clustering approaches can help with the task of understanding large, complex software systems by automatically decomposing them into smaller, easier-to-manage subsystems. The main objective of this paper is to identify important research directions in the area of software clustering that require further attention in order to develop more effective and efficient clustering methodologies for software engineering. To that end, we first present the state of the art in software clustering research. We discuss the clustering methods that have received the most attention from the research community and outline their strengths and weaknesses. Our paper describes each phase of a clustering algorithm separately. We also present the most important approaches for evaluating the effectiveness of software clustering.

  12. Statistics of sunspot group clusters

    Directory of Open Access Journals (Sweden)

    Getko Ryszarda

    2013-03-01

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

  13. Type Families with Class, Type Classes with Family

    DEFF Research Database (Denmark)

    Serrano, Alejandro; Hage, Jurriaan; Bahr, Patrick

    2015-01-01

    Type classes and type families are key ingredients in Haskell programming. Type classes were introduced to deal with ad-hoc polymorphism, although with the introduction of functional dependencies, their use expanded to type-level programming. Type families also allow encoding type-level functions...

  14. Color Image Segmentation Method Based on Improved Spectral Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Dong Qin

    2014-08-01

    Full Text Available Contraposing to the features of image data with high sparsity of and the problems on determination of clustering numbers, we try to put forward an color image segmentation algorithm, combined with semi-supervised machine learning technology and spectral graph theory. By the research of related theories and methods of spectral clustering algorithms, we introduce information entropy conception to design a method which can automatically optimize the scale parameter value. So it avoids the unstability in clustering result of the scale parameter input manually. In addition, we try to excavate available priori information existing in large number of non-generic data and apply semi-supervised algorithm to improve the clustering performance for rare class. We also use added tag data to compute similar matrix and perform clustering through FKCM algorithms. By the simulation of standard dataset and image segmentation, the experiments demonstrate our algorithm has overcome the defects of traditional spectral clustering methods, which are sensitive to outliers and easy to fall into local optimum, and also poor in the convergence rate

  15. Digital Doping in Magic-Sized CdSe Clusters.

    Science.gov (United States)

    Muckel, Franziska; Yang, Jiwoong; Lorenz, Severin; Baek, Woonhyuk; Chang, Hogeun; Hyeon, Taeghwan; Bacher, Gerd; Fainblat, Rachel

    2016-07-26

    Magic-sized semiconductor clusters represent an exciting class of materials located at the boundary between quantum dots and molecules. It is expected that replacing single atoms of the host crystal with individual dopants in a one-by-one fashion can lead to unique modifications of the material properties. Here, we demonstrate the dependence of the magneto-optical response of (CdSe)13 clusters on the discrete number of Mn(2+) ion dopants. Using time-of-flight mass spectrometry, we are able to distinguish undoped, monodoped, and bidoped cluster species, allowing for an extraction of the relative amount of each species for a specific average doping concentration. A giant magneto-optical response is observed up to room temperature with clear evidence that exclusively monodoped clusters are magneto-optically active, whereas the Mn(2+) ions in bidoped clusters couple antiferromagnetically and are magneto-optically passive. Mn(2+)-doped clusters therefore represent a system where magneto-optical functionality is caused by solitary dopants, which might be beneficial for future solotronic applications. PMID:27420556

  16. Convex clustering: an attractive alternative to hierarchical clustering.

    Directory of Open Access Journals (Sweden)

    Gary K Chen

    2015-05-01

    Full Text Available 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/.

  17. Web Fuzzy Clustering and a Case Study

    Institute of Scientific and Technical Information of China (English)

    LIU Mao-fu; HE Jing; HE Yan-xiang; HU Hui-jun

    2004-01-01

    We combine the web usage mining and fuzzy clustering and give the concept of web fuzzy clustering, and then put forward the web fuzzy clustering processing model which is discussed in detail. Web fuzzy clustering can be used in the web users clustering and web pages clustering. In the end, a case study is given and the result has proved the feasibility of using web fuzzy clustering in web pages clustering.

  18. CCABC: Cyclic Cellular Automata Based Clustering For Energy Conservation in Sensor Networks

    CERN Document Server

    Banerjee, Indrajit; Rahaman, Hafizur

    2011-01-01

    Sensor network has been recognized as the most significant technology for next century. Despites of its potential application, wireless sensor network encounters resource restriction such as low power, reduced bandwidth and specially limited power sources. This work proposes an efficient technique for the conservation of energy in a wireless sensor network (WSN) by forming an effective cluster of the network nodes distributed over a wide range of geographical area. The clustering scheme is developed around a specified class of cellular automata (CA) referred to as the modified cyclic cellular automata (mCCA). It sets a number of nodes in stand-by mode at an instance of time without compromising the area of network coverage and thereby conserves the battery power. The proposed scheme also determines an effective cluster size where the inter-cluster and intra-cluster communication cost is minimum. The simulation results establish that the cyclic cellular automata based clustering for energy conservation in sens...

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

  1. The Latent Class Model as a Measurement Model for Situational Judgment Tests

    Directory of Open Access Journals (Sweden)

    Frank Rijmen

    2011-11-01

    Full Text Available In a situational judgment test, it is often debatable what constitutes a correct answer to a situation. There is currently a multitude of scoring procedures. Establishing a measurement model can guide the selection of a scoring rule. It is argued that the latent class model is a good candidate for a measurement model. Two latent class models are applied to the Managing Emotions subtest of the Mayer, Salovey, Caruso Emotional Intelligence Test: a plain-vanilla latent class model, and a second-order latent class model that takes into account the clustering of several possible reactions within each hypothetical scenario of the situational judgment test. The results for both models indicated that there were three subgroups characterised by the degree to which differentiation occurred between possible reactions in terms of perceived effectiveness. Furthermore, the results for the second-order model indicated a moderate cluster effect.

  2. Apply Local Clustering Method to Improve the Running Speed of Ant Colony Optimization

    CERN Document Server

    Pang, Chao-Yang; Li, Xia; Hu, Be-Qiong

    2009-01-01

    Ant Colony Optimization (ACO) has time complexity O(t*m*N*N), and its typical application is to solve Traveling Salesman Problem (TSP), where t, m, and N denotes the iteration number, number of ants, number of cities respectively. Cutting down running time is one of study focuses, and one way is to decrease parameter t and N, especially N. For this focus, the following method is presented in this paper. Firstly, design a novel clustering algorithm named Special Local Clustering algorithm (SLC), then apply it to classify all cities into compact classes, where compact class is the class that all cities in this class cluster tightly in a small region. Secondly, let ACO act on every class to get a local TSP route. Thirdly, all local TSP routes are jointed to form solution. Fourthly, the inaccuracy of solution caused by clustering is eliminated. Simulation shows that the presented method improves the running speed of ACO by 200 factors at least. And this high speed is benefit from two factors. One is that class ha...

  3. Hydrometeor classification from polarimetric radar measurements: a clustering approach

    OpenAIRE

    Grazioli, J.; D. Tuia; Berne, A.

    2014-01-01

    A data-driven approach to the classification of hydrometeors from measurements collected with polarimetric weather radars is proposed. In a first step, the optimal number nopt of hydrometeor classes that can be reliably identified from a large set of polarimetric data is determined. This is done by means of an unsupervised clustering technique guided by criteria related both to data similarity and to spatial smoothness of the classified images. In a second s...

  4. Hydrometeor classification from polarimetric radar measurements: a clustering approach

    OpenAIRE

    Grazioli, J.; D. Tuia; Berne, A.

    2015-01-01

    A data-driven approach to the classification of hydrometeors from measurements collected with polarimetric weather radars is proposed. In a first step, the optimal number of hydrometeor classes (nopt) that can be reliably identified from a large set of polarimetric data is determined. This is done by means of an unsupervised clustering technique guided by criteria related both to data similarity and to spatial smoothness of the classified images. In a s...

  5. Vetoed jet clustering: The mass-jump algorithm

    CERN Document Server

    Stoll, Martin

    2014-01-01

    A new class of jet clustering algorithms is introduced. A criterion inspired by successful mass-drop taggers is applied which prevents the recombination of two hard prongs if they experience a substantial jump in jet mass. This veto effectively results in jets with variable radius in dense environments. Differences to existing methods are investigated and it is shown for boosted top quarks that the new algorithm has beneficial properties which can lead to improved tagging purity.

  6. Hydrophilic carbon clusters as therapeutic, high capacity antioxidants

    OpenAIRE

    Samuel, Errol L. G.; Duong, MyLinh T.; Bitner, Brittany R.; Marcano, Daniela C.; James M. Tour; Kent, Thomas A

    2014-01-01

    Oxidative stress reflects an excessive accumulation of reactive oxygen species (ROS) and is a hallmark of several acute and chronic human pathologies. While many antioxidants have been investigated, the majority have demonstrated poor efficacy in clinical trials. Here, we discuss limitations of current antioxidants and describe a new class of nanoparticle antioxidants, poly(ethylene glycol)-functionalized hydrophilic carbon clusters (PEG-HCCs). PEG-HCCs show high capacity to annihilate ROS su...

  7. Hadoop cluster deployment

    CERN Document Server

    Zburivsky, Danil

    2013-01-01

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

  8. Convex Decomposition Based Cluster Labeling Method for Support Vector Clustering

    Institute of Scientific and Technical Information of China (English)

    Yuan Ping; Ying-Jie Tian; Ya-Jian Zhou; Yi-Xian Yang

    2012-01-01

    Support vector clustering (SVC) is an important boundary-based clustering algorithm in multiple applications for its capability of handling arbitrary cluster shapes. However,SVC's popularity is degraded by its highly intensive time complexity and poor label performance.To overcome such problems,we present a novel efficient and robust convex decomposition based cluster labeling (CDCL) method based on the topological property of dataset.The CDCL decomposes the implicit cluster into convex hulls and each one is comprised by a subset of support vectors (SVs).According to a robust algorithm applied in the nearest neighboring convex hulls,the adjacency matrix of convex hulls is built up for finding the connected components; and the remaining data points would be assigned the label of the nearest convex hull appropriately.The approach's validation is guaranteed by geometric proofs.Time complexity analysis and comparative experiments suggest that CDCL improves both the efficiency and clustering quality significantly.

  9. The Paradox of Paperless Classes.

    Science.gov (United States)

    Lackie, Paula

    1998-01-01

    Describes paperless classes developed at Carleton College that augment traditional classes by giving students and faculty the ability to share digital course-related materials via the campus computer network. Presents a case study of a managerial economics course, and includes problems with various aspects of the course and solutions. (LRW)

  10. Class Differences in Cohabitation Processes

    Science.gov (United States)

    Sassler, Sharon; Miller, Amanda J.

    2011-01-01

    Despite the burgeoning cohabitation literature, research has failed to examine social class variation in processes of forming and advancing such unions. Drawing upon in-depth interviews with 122 working- and middle-class cohabitors, we examine the duration between dating and moving in together, reasons for cohabiting, and subsequent plans.…

  11. A Touch of...Class!

    Science.gov (United States)

    Netten, Joan W., Ed.

    1984-01-01

    A collection of ideas for class activities in elementary and secondary language classes includes a vocabulary review exercise and games of memory, counting, vocabulary, flashcard tic-tac-toe, dice, trashcans, questioning, and spelling. Some are designed specifically for French. (MSE)

  12. Social Class and the Extracurriculum

    Science.gov (United States)

    Barratt, Will

    2012-01-01

    Social class is a powerful and often unrecognized influence on student participation in the extracurriculum. Spontaneous student-created extracurricular experiences depend on students affiliating and interacting with each other; student social class is a powerful influence on student affiliations. Students tend to exercise consciousness of kind-…

  13. Class, Identity, and Teacher Education

    Science.gov (United States)

    Van Galen, Jane A.

    2010-01-01

    This paper explores the possibilities of working with White, working-class teacher education students to explore the "complex social trajectory" (Reay in Women's Stud Int Forum 20(2):225-233, 1997a, p. 19) of class border crossing as they progress through college. Through analysis of a course that I have developed, "Education and the American…

  14. Dynamic class methods in Java

    OpenAIRE

    Heinlein, Christian

    2005-01-01

    The concept of dynamic class methods in Java, constituting a specialization of a general new programming language concept called dynamic routines, is introduced and applied to a simple case study. Its advantages over standard object-oriented programming techniques including design patterns are demonstrated. Furthermore, an implementation of dynamic class methods as a precompiler-based language extension to Java is described.

  15. Relations among tautological classes revisited

    DEFF Research Database (Denmark)

    Randal-Williams, Oscar

    2012-01-01

    We give a simple generalisation of a theorem of Morita (1989) [10] and [11], which leads to a great number of relations among tautological classes on moduli spaces of Riemann surfaces......We give a simple generalisation of a theorem of Morita (1989) [10] and [11], which leads to a great number of relations among tautological classes on moduli spaces of Riemann surfaces...

  16. Tautological Classes on Projective Towers

    CERN Document Server

    Negut, Andrei

    2011-01-01

    When one has a tower of projective bundles over an algebraic variety and wishes to compute the push-forward of any cohomology class down this tower, one needs to recursively compute the Segre classes corresponding to each level. In this paper, we give a closed combinatorial formula that encodes this recursive procedure.

  17. Clustering and Classification via Cluster-Weighted Factor Analyzers

    OpenAIRE

    Subedi, Sanjeena; PUNZO, ANTONIO; Ingrassia, Salvatore; McNicholas, Paul D.

    2012-01-01

    In model-based clustering and classification, the cluster-weighted model constitutes a convenient approach when the random vector of interest constitutes a response variable Y and a set p of explanatory variables X. However, its applicability may be limited when p is high. To overcome this problem, this paper assumes a latent factor structure for X in each mixture component. This leads to the cluster-weighted factor analyzers (CWFA) model. By imposing constraints on the variance of Y and the ...

  18. A Gamblers Clustering Based on Their Favorite Gambling Activity.

    Science.gov (United States)

    Challet-Bouju, Gaëlle; Hardouin, Jean-Benoit; Renard, Noëlle; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Gorsane, Mohamed-Ali; Vénisse, Jean-Luc; Grall-Bronnec, Marie

    2015-12-01

    The objective of this study was to identify profiles of gamblers to explain the choice of preferred gambling activity among both problem and non-problem gamblers. 628 non-problem and problem gamblers were assessed with a structured interview including "healthy" (sociodemographic characteristics, gambling habits and personality profile assessed with the Temperament and Character Inventory-125) and "pathological" [diagnosis of pathological gambling, gambling-related cognitions (GRCs) and psychiatric comorbidity] variables. We performed a two-step cluster analysis based solely on "healthy" variables to identify gamblers' profiles which typically reflect the choice of preferred gambling activity. The obtained classes were then described using both "healthy" and "pathological" variables, by comparing each class to the rest of the sample. Clusters were generated. Class 1 (Electronic Gaming Machines gamblers) showed high cooperativeness, a lower level of GRC about strategy and more depressive disorders. Class 2 (games with deferred results gamblers) were high novelty seekers and showed a higher level of GRC about strategy and more addictive disorders. Class 3 (roulette gamblers) were more often high rollers and showed a higher level of GRC about strategy and more manic or hypomanic episodes and more obsessive-compulsive disorders. Class 4 (instant lottery gamblers) showed a lower tendency to suicide attempts. Class 5 (scratch cards gamblers) were high harm avoiders and showed a lower overall level of GRC and more panic attacks and eating disorders. The preference for one particular gambling activity may concern different profiles of gamblers. This study highlights the importance of considering the pair gambler-game rather than one or the other separately, and may provide support for future research on gambling and preventive actions directed toward a particular game. PMID:25192752

  19. Collisions of relativistic clusters and the formation of black holes

    International Nuclear Information System (INIS)

    We perform numerical simulations of head-on collisions of relativistic clusters. The cluster particles interact only gravitationally, and so satisfy the collisionless Boltzmann equation in general relativity. We construct and follow the evolution of three classes of initial configurations: spheres of particles at rest; spheres of particles boosted towards each other; and spheres of particles in circular orbits about their respective centers. In the first two cases, the spheres implode towards their centers and may form black holes before colliding. These scenarios thus can be used to study the head-on collision of two black holes. In the third case the clusters are initially in equilibrium and cannot implode. In this case collision from rest leads either to coalescence and virialization, or collapse to a black hole. This scenario is the collisionless analog of colliding neutron stars in relativistic hydrodynamics

  20. A HYBRID HEURISTIC ALGORITHM FOR THE CLUSTERED TRAVELING SALESMAN PROBLEM

    Directory of Open Access Journals (Sweden)

    Mário Mestria

    2016-04-01

    Full Text Available ABSTRACT This paper proposes a hybrid heuristic algorithm, based on the metaheuristics Greedy Randomized Adaptive Search Procedure, Iterated Local Search and Variable Neighborhood Descent, to solve the Clustered Traveling Salesman Problem (CTSP. Hybrid Heuristic algorithm uses several variable neighborhood structures combining the intensification (using local search operators and diversification (constructive heuristic and perturbation routine. In the CTSP, the vertices are partitioned into clusters and all vertices of each cluster have to be visited contiguously. The CTSP is -hard since it includes the well-known Traveling Salesman Problem (TSP as a special case. Our hybrid heuristic is compared with three heuristics from the literature and an exact method. Computational experiments are reported for different classes of instances. Experimental results show that the proposed hybrid heuristic obtains competitive results within reasonable computational time.

  1. Polymorphism in magic-sized Au144(SR)60 clusters

    Science.gov (United States)

    Jensen, Kirsten M. Ø.; Juhas, Pavol; Tofanelli, Marcus A.; Heinecke, Christine L.; Vaughan, Gavin; Ackerson, Christopher J.; Billinge, Simon J. L.

    2016-06-01

    Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. Here we present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. The study reveals structural polymorphism in these archetypal nanoclusters. In addition to confirming the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. The discovery of polymorphism may open up a new dimension in nanoscale engineering.

  2. Acupuncture for episodic cluster headache: a trigeminal approach.

    Science.gov (United States)

    Hayhoe, Simon

    2016-02-01

    Following evidence that acupuncture is clinically feasible and cost-effective in the treatment of headache, the UK National Institute for Health and Care Excellence recommends acupuncture as prophylactic treatment for migraine and tension headache. There has thus been expectation that other forms of headache should benefit also. Unfortunately, acupuncture has not generally been successful for cluster headache. This may be due to acupuncturists approaching the problem as one of severe migraine. In fact, cluster headache is classed as a trigeminal autonomic cephalgia. In this case report, episodic cluster headache is treated in the same way as has been shown effective for trigeminal neuralgia. Acupuncture is applied to the contralateral side at points appropriate for stimulating branches of the trigeminal nerve. Thus, ST2 is used for the infraorbital nerve, BL2 and Yuyao for the supratrochlear and supraorbital nerves, and Taiyang for the temporal branch of the zygomatic nerve. PMID:26846705

  3. Detecting Clusters in Spatially Repetitive Point Event Data Sets

    Directory of Open Access Journals (Sweden)

    Allan Brimicombe

    2007-07-01

    Full Text Available The analysis of point event patterns has a long tradition. Of particular interest are patterns of clustering or ‘hot spots’ and such cluster detection lies at the heart of spatial data mining. Certain classes of point event patterns have a significant proportion of the data having a tendency towards exact spatial repetitiveness. Examples are crime and traffic accidents. Spatial superimposition of point events challenges many existing approaches to cluster detection. In this paper a variable resolution approach, Geo-ProZones, is applied to residential burglary data exhibiting a high level of repeat victimisation. This is coupled with robust normalisation as a means of consistently defining and visualising the ‘hot spots’.

  4. Ultracompact Generation of Continuous-Variable Cluster States

    CERN Document Server

    Menicucci, N C; Pfister, O; Zaidi, H; Flammia, Steven T.; Menicucci, Nicolas C.; Pfister, Olivier; Zaidi, Hussain

    2007-01-01

    We show that any continuous-variable (CV) cluster state with a bipartite graph -- a class that includes computationally universal graphs -- can be generated with a single multimode squeezing Hamiltonian acting on the vacuum. Any such Hamiltonian can, in principle, be implemented optically using a single optical parametric oscillator (OPO) based on a multiply phasematched nonlinear crystal pumped by an O(N^2)-mode field. This is in contrast to the equally resource-efficient scheme proposed in quant-ph/0610119, which requires N single-mode OPOs plus a network of O(N^2) beam splitters. The method proposed here is an essential step toward the efficient experimental creation of large-scale CV cluster states. As an illustration, we detail the experimental creation of a four-mode square CV cluster state from a single OPO.

  5. First class models from linear and nonlinear second class constraints

    CERN Document Server

    Dehghani, Mehdi; Monemzadeh, Majid; Abarghooeinejad, Salman

    2014-01-01

    Two models with linear and nonlinear second class constraints are considered and gauged by embedding in an extended phase space. These models are the free non-relativistic particle on a hyperplane and hyper sphere in configuration space. For the first model we construct its gauged corresponding by the condition of converting second class system to first class one, directly. In contrast the first class system related to the free particle on hyper sphere is derived by the BFT embedding procedure, where its steps are infinite. We give a practical formula for gauging linear and some of the nonlinear second class systems, based on the simplified BFT method. As a result of the gauging two models, we show that in the conversion of second class to the first class constraints the minimum number of phase space degrees of freedom for both systems is a pair of phase space coordinate. This pair for first system is a coordinate and its momentum conjugate, but Poisson structure of embedded non-relativistic particle on hyper...

  6. Density functional study of the bonding in small silicon clusters

    International Nuclear Information System (INIS)

    We report the ground electronic state, equilibrium geometry, vibrational frequencies, and binding energy for various isomers of Sin(n = 2--8) obtained with the linear combination of atomic orbitals-density functional method. We used both a local density approximation approach and one with gradient corrections. Our local density approximation results concerning the relative stability of electronic states and isomers are in agreement with Hartree--Fock and Moller--Plesset (MP2) calculations [K. Raghavachari and C. M. Rohlfing, J. Chem. Phys. 89, 2219 (1988)]. The binding energies calculated with the gradient corrected functional are in good agreement with experiment (Si2 and Si3) and with the best theoretical estimates. Our analysis of the bonding reveals two limiting modes of bonding and classes of silicon clusters. One class of clusters is characterized by relatively large s atomic populations and a large number of weak bonds, while the other class of clusters is characterized by relatively small s atomic populations and a small number of strong bonds

  7. Sequential clustering of star formation in IC 1396

    CERN Document Server

    Huang, Ya Fang

    2012-01-01

    We present in this paper a comprehensive study of the H II region IC 1396 and its star formation activity, in which multi-wavelength data ranging from the optical to the near- and far-infrared were employed. The surface density distribution of all the 2MASS sources with certain detection toward IC 1396 indicates the existence of a compact cluster spatially consistent with the position of the exciting source of the H II region, HD 206267. The spatial distribution of the infrared excessive emission sources selected based on archived 2MASS data reveals the existence of four sub-clusters in this region. One is in association with the open cluster Trumpler 37. The other three are found to be spatially coincident with the bright rims of the H II region. All the excessive emission sources in the near infrared are cross-identified with the AKARI IRC data, an analysis of the spectral energy distributions (SEDs) of the resultant sample leads to the identification of 8 CLASS I, 15 CLASS II and 15 CLASS III sources in IC...

  8. Brightest Cluster Galaxies and Core Gas Density in REXCESS Clusters

    CERN Document Server

    Haarsma, D B; Donahue, M; Bruch, S; Boehringer, H; Croston, J H; Pratt, G W; Voit, G M; Arnaud, M; Pierini, D

    2009-01-01

    We investigate the relationship between brightest cluster galaxies (BCGs) and their host clusters using a sample of nearby galaxy clusters from the Representative XMM-Newton Cluster Structure Survey (REXCESS). The sample was imaged with the Southern Observatory for Astrophysical Research (SOAR) in R band to investigate the mass of the old stellar population. Using a metric radius of 12h^-1 kpc, we find that the BCG luminosity depends weakly on overall cluster mass as L_BCG \\propto M_cl^0.18+-0.07, consistent with previous work. We found that 90% of the BCGs are located within 0.035 R_500 of the peak of the X-ray emission, including all of the cool core (CC) clusters. We also found an unexpected correlation between the BCG metric luminosity and the core gas density for non-cool core (non-CC) clusters, following a power law of n_e \\propto L_BCG^2.7+-0.4 (where n_e is measured at 0.008 R_500). The correlation is not easily explained by star formation (which is weak in non-CC clusters) or overall cluster mass (wh...

  9. 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.

  10. Applying Data Clustering Feature to Speed Up Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Chao-Yang Pang

    2014-01-01

    Full Text Available Ant colony optimization (ACO is often used to solve optimization problems, such as traveling salesman problem (TSP. When it is applied to TSP, its runtime is proportional to the squared size of problem N so as to look less efficient. The following statistical feature is observed during the authors’ long-term gene data analysis using ACO: when the data size N becomes big, local clustering appears frequently. That is, some data cluster tightly in a small area and form a class, and the correlation between different classes is weak. And this feature makes the idea of divide and rule feasible for the estimate of solution of TSP. In this paper an improved ACO algorithm is presented, which firstly divided all data into local clusters and calculated small TSP routes and then assembled a big TSP route with them. Simulation shows that the presented method improves the running speed of ACO by 200 factors under the condition that data set holds feature of local clustering.

  11. Early massive clusters and the bouncing coupled dark energy

    Science.gov (United States)

    Baldi, Marco

    2012-02-01

    The abundance of the most massive objects in the Universe at different epochs is a very sensitive probe of the cosmic background evolution and of the growth history of density perturbations, and could provide a powerful tool to distinguish between a cosmological constant and a dynamical dark energy field. In particular, the recent detection of very massive clusters of galaxies at high redshifts has attracted significant interest as a possible indication of a failure of the standard Λ cold dark matter model. Several attempts have been made in order to explain such detections in the context of non-Gaussian scenarios or interacting dark energy models, showing that both these alternative cosmologies predict an enhanced number density of massive clusters at high redshifts, possibly alleviating the tension. However, all the models proposed so far also overpredict the abundance of massive clusters at the present epoch, and are therefore in contrast with observational bounds on the low-redshift halo mass function. In this paper we present for the first time a new class of interacting dark energy models that simultaneously account for an enhanced number density of massive clusters at high redshifts and for both the standard cluster abundance at the present time and the standard power spectrum normalization at cosmic microwave background (CMB). The key feature of this new class of models is the 'bounce' of the dark energy scalar field on the cosmological constant barrier at relatively recent epochs. We present the background and linear perturbations evolution of the model, showing that the standard amplitude of density perturbations is recovered both at CMB and at the present time, and we demonstrate by means of large N-body simulations that our scenario predicts an enhanced number of massive clusters at high redshifts without affecting the present halo abundance. Such behaviour could not arise in non-Gaussian models, and is therefore a characteristic feature of the

  12. Decaying neutrinos in galaxy clusters

    Science.gov (United States)

    Melott, Adrian L.; Splinter, Randall J.; Persic, Massimo; Salucci, Paolo

    1994-01-01

    Davidsen et al. (1991) have argued that the failure to detect UV photons from the dark matter (DM) in cluster A665 excludes the decaying neutrino hypothesis. Sciama et al. (1993) argued that because of high central concentration the DM in that cluster must be baryonic. We study the DM profile in clusters of galaxies simulated using the Harrison-Zel'dovich spectrum of density fluctuations, and an amplitude previously derived from numerical simulations (Melott 1984b; Anninos et al. 1991) and in agreement with microwave background fluctuations (Smoot et al. 1992). We find that with this amplitude normalization cluster neutrino DM densities are comparable to observed cluster DM values. We conclude that given this normalization, the cluster DM should be at least largely composed of neutrinos. The constraint of Davidsen et al. can be somewhat weakened by the presence of baryonic DM; but it cannot be eliminated given our assumptions.

  13. Cosmology with clusters of galaxies

    CERN Document Server

    Bahcall, Neta A

    1995-01-01

    Rich clusters of galaxies, the largest virialized systems known, provide a powerful tool for the study of cosmology. Some of the fundamental questions that can be addressed with clusters of galaxies include: how did galaxies and large-scale structure form and evolve? What is the amount, composition and distribution of matter in the universe? I review some of the studies utilizing clusters of galaxies to investigare, among others: - The dark matter on clusters scale and the mean mass-density of the universe; - The large-scale structure of the universe; - The peculiar velocity field on large scales; - The mass-function of groups and clusters of galaxies; - The constraints placed on specific cosmological models using the cluster data.

  14. Cluster synchronization in oscillatory networks

    Science.gov (United States)

    Belykh, Vladimir N.; Osipov, Grigory V.; Petrov, Valentin S.; Suykens, Johan A. K.; Vandewalle, Joos

    2008-09-01

    Synchronous behavior in networks of coupled oscillators is a commonly observed phenomenon attracting a growing interest in physics, biology, communication, and other fields of science and technology. Besides global synchronization, one can also observe splitting of the full network into several clusters of mutually synchronized oscillators. In this paper, we study the conditions for such cluster partitioning into ensembles for the case of identical chaotic systems. We focus mainly on the existence and the stability of unique unconditional clusters whose rise does not depend on the origin of the other clusters. Also, conditional clusters in arrays of globally nonsymmetrically coupled identical chaotic oscillators are investigated. The design problem of organizing clusters into a given configuration is discussed.

  15. Active matter clusters at interfaces

    CERN Document Server

    Copenhagen, Katherine

    2016-01-01

    Collective and directed motility or swarming is an emergent phenomenon displayed by many self-organized assemblies of active biological matter such as clusters of embryonic cells during tissue development, cancerous cells during tumor formation and metastasis, colonies of bacteria in a biofilm, or even flocks of birds and schools of fish at the macro-scale. Such clusters typically encounter very heterogeneous environments. What happens when a cluster encounters an interface between two different environments has implications for its function and fate. Here we study this problem by using a mathematical model of a cluster that treats it as a single cohesive unit that moves in two dimensions by exerting a force/torque per unit area whose magnitude depends on the nature of the local environment. We find that low speed (overdamped) clusters encountering an interface with a moderate difference in properties can lead to refraction or even total internal reflection of the cluster. For large speeds (underdamped), wher...

  16. Clustering and rule-based classifications of chemical structures evaluated in the biological activity space.

    Science.gov (United States)

    Schuffenhauer, Ansgar; Brown, Nathan; Ertl, Peter; Jenkins, Jeremy L; Selzer, Paul; Hamon, Jacques

    2007-01-01

    Classification methods for data sets of molecules according to their chemical structure were evaluated for their biological relevance, including rule-based, scaffold-oriented classification methods and clustering based on molecular descriptors. Three data sets resulting from uniformly determined in vitro biological profiling experiments were classified according to their chemical structures, and the results were compared in a Pareto analysis with the number of classes and their average spread in the profile space as two concurrent objectives which were to be minimized. It has been found that no classification method is overall superior to all other studied methods, but there is a general trend that rule-based, scaffold-oriented methods are the better choice if classes with homogeneous biological activity are required, but a large number of clusters can be tolerated. On the other hand, clustering based on chemical fingerprints is superior if fewer and larger classes are required, and some loss of homogeneity in biological activity can be accepted.

  17. External Defect classification of Citrus Fruit Images using Linear Discriminant Analysis Clustering and ANN classifiers

    Directory of Open Access Journals (Sweden)

    K.Vijayarekha

    2012-12-01

    Full Text Available Linear Discriminant Analysis (LDA is one technique for transforming raw data into a new feature space in which classification can be carried out more robustly. It is useful where the within-class frequencies are unequal. This method maximizes the ratio of between-class variance to the within-class variance in any particular data set and the maximal separability is guaranteed. LDA clustering models are used to classify object into different category. This study makes use of LDA for clustering the features obtained for the citrus fruit images taken in five different domains. Sub-windows of size 40x40 are cropped from the citrus fruit images having defects such as pitting, splitting and stem end rot. Features are extracted in four domains such as statistical features, fourier transform based features, discrete wavelet transform based features and stationary wavelet transform based features. The results of clustering and classification using LDA and ANN classifiers are reported

  18. Fuzzy K-mean Clustering Via Random Forest For Intrusiion Detection System

    Directory of Open Access Journals (Sweden)

    Kusum bharti

    2010-09-01

    Full Text Available Due to continuous growth of the internet technology, there is need to establish security mechanism. So for achieving this objective various NIDS has been propsed. Datamining is one of the most effective techniques used for intrusion detection. This work evaluates the performance of unsupervised learning techniques over benchmark intrusion detection datasets. The model generation is computation intensive, hence to reduce the time required for model generation various feature selection algorithm has been used. Problems with k-mean clustering are hard cluster to class assignment, class dominance, and null classproblems. From experimental results it is observed that for 2 class datasets filtered fuzzy random forest dataset gives the better results. It is having 99.2% precision and 100% recall, So it can be summarize that proposed statistical model is giving better performance better results than existing clustering algorithm.

  19. Bacterial chemoreceptors of different length classes signal independently.

    Science.gov (United States)

    Herrera Seitz, M Karina; Frank, Vered; Massazza, Diego A; Vaknin, Ady; Studdert, Claudia A

    2014-08-01

    Bacterial chemoreceptors sense environmental stimuli and govern cell movement by transmitting the information to the flagellar motors. The highly conserved cytoplasmic domain of chemoreceptors consists in an alpha-helical hairpin that forms in the homodimer a coiled-coil four-helix bundle. Several classes of chemoreceptors that differ in the length of the coiled-coil structure were characterized. Many bacterial species code for chemoreceptors that belong to different classes, but how these receptors are organized and function in the same cell remains an open question. E. coli cells normally code for single class chemoreceptors that form extended arrays based on trimers of dimers interconnected by the coupling protein CheW and the kinase CheA. This structure promotes effective coupling between the different receptors in the modulation of the kinase activity. In this work, we engineered functional derivatives of the Tsr chemoreceptor of E. coli that mimic receptors whose cytoplasmic domain is longer by two heptads. We found that these long Tsr receptors did not efficiently mix with the native receptors and appeared to function independently. Our results suggest that the assembly of membrane-bound receptors of different specificities into mixed clusters is dictated by the length-class to which the receptors belong, ensuring cooperative function only between receptors of the same class.

  20. Connecting Remote Clusters with ATM

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-10-01

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

  1. Relativistic Effect in Galaxy Clustering

    OpenAIRE

    Yoo, Jaiyul

    2014-01-01

    The general relativistic description of galaxy clustering provides a complete and unified treatment of all the effects in galaxy clustering such as the redshift-space distortion, gravitational lensing, Sachs-Wolfe effects, and their relativistic effects. In particular, the relativistic description resolves the gauge issues in the standard Newtonian description of galaxy clustering by providing the gauge-invariant expression for the observed galaxy number density. The relativistic effect in ga...

  2. Light cluster production at NICA

    CERN Document Server

    Bastian, N -U; Blaschke, D; Danielewicz, P; Ivanov, Yu B; Karpenko, Iu; Röpke, G; Rogachevsky, O; Wolter, H H

    2016-01-01

    Light cluster production at the NICA accelerator complex offers unique possibilities to use these states as "rare probes" of in-medium characteristics such as phase space occupation and early flow. In order to explain this statement, in this contribution theoretical considerations from the nuclear statistical equilibrium model and from a quantum statistical model of cluster production are supplemented with a discussion of a transport model for light cluster formation and with results from hydrodynamic simulations combined with the coalescence model.

  3. Cluster banding heat source model

    Institute of Scientific and Technical Information of China (English)

    Zhang Liguo; Ji Shude; Yang Jianguo; Fang Hongyuan; Li Yafan

    2006-01-01

    Concept of cluster banding heat source model is put forward for the problem of overmany increment steps in the process of numerical simulation of large welding structures, and expression of cluster banding heat source model is deduced based on energy conservation law.Because the expression of cluster banding heat source model deduced is suitable for random weld width, quantitative analysis of welding stress field for large welding structures which have regular welds can be made quickly.

  4. Synchronization in complex clustered networks

    Institute of Scientific and Technical Information of China (English)

    HUANG Liang; LAI Ying-Cheng; Kwangho PARK; WANG Xingang; LAI Choy Heng; Robert A. GATENBY

    2007-01-01

    Synchronization in complex networks has been an active area of research in recent years. While much effort has been devoted to networks with the small-world and scale-free topology, structurally they are often assumed to have a single, densely connected component. Recently it has also become apparent that many networks in social, biological, and tech-nological systems are clustered, as characterized by a number (or a hierarchy) of sparsely linked clusters, each with dense and complex internal connections. Synchronization is funda-mental to the dynamics and functions of complex clustered networks, but this problem has just begun to be addressed. This paper reviews some progress in this direction by focus-ing on the interplay between the clustered topology and net-work synchronizability. In particular, there are two parame-ters characterizing a clustered network: the intra-cluster and the inter-cluster link density. Our goal is to clarify the roles of these parameters in shaping network synchronizability. By using theoretical analysis and direct numerical simulations of oscillator networks, it is demonstrated that clustered net-works with random inter-cluster links are more synchroniz-able, and synchronization can be optimized when inter-cluster and intra-cluster links match. The latter result has one coun-terintuitive implication: more links, if placed improperly, can actually lead to destruction of synchronization, even though such links tend to decrease the average network distance. It is hoped that this review will help attract attention to the fun-damental problem of clustered structures/synchronization in network science.

  5. Cluster headache and intracranial aneurysm

    OpenAIRE

    Valença, Marcelo Moraes; Andrade-Valença, Luciana P. A.; Martins, Carolina; de Aragão, Maria Fátima Vasco; Batista, Laécio Leitão; Peres, Mario Fernando Prieto; da Silva, Wilson Farias

    2007-01-01

    In the present study we describe the cases of two patients with cluster-like headache related to intracranial carotid artery aneurysm. One of these patients responded to verapamil prescription with headache resolution. In both cases the surgical clipping of the aneurysm resolved the cluster pain. These findings strongly suggest a pathophysiological link between the two conditions. The authors discuss the potential pathophysiological mechanisms underlying cluster-like headache due to intracran...

  6. Collective thermoregulation in bee clusters

    OpenAIRE

    Ocko, Samuel A; Mahadevan, L.

    2014-01-01

    Swarming is an essential part of honeybee behaviour, wherein thousands of bees cling onto each other to form a dense cluster that may be exposed to the environment for several days. This cluster has the ability to maintain its core temperature actively without a central controller, and raises the question of how this is achieved. We suggest that the swarm cluster is akin to an active porous structure whose functional requirement is to adjust to outside conditions by varying its porosity to co...

  7. Knowledge Evolution in Industrial Clusters

    OpenAIRE

    Langfeng Wang; Qunhong Shen

    2009-01-01

    Character of knowledge management conducted in industrial clusters is different from entity of enterpresis and socail public deparment because of distinction in management objection. Many scholars was attracted to reseach knowledge management for enterprises, knowledge management in industrial clusters lack durable study in depth. This paper seeks to lay out an organizational foundation to a theory of industrial clusters and present the necessary, factors, process and characters of knowledge ...

  8. AUTOMATED TEXT CLUSTERING OF NEWSPAPER AND SCIENTIFIC TEXTS IN BRAZILIAN PORTUGUESE: ANALYSIS AND COMPARISON OF METHODS

    Directory of Open Access Journals (Sweden)

    Alexandre Ribeiro Afonso

    2014-10-01

    Full Text Available This article reports the findings of an empirical study about Automated Text Clustering applied to scientific articles and newspaper texts in Brazilian Portuguese, the objective was to find the most effective computational method able to cluster the input of texts in their original groups. The study covered four experiments, each experiment had four procedures: 1. Corpus Selections (a set of texts is selected for clustering, 2. Word Class Selections (Nouns, Verbs and Adjectives are chosen from each text by using specific algorithms, 3. Filtering Algorithms (a set of terms is selected from the results of the preview stage, a semantic weight is also inserted for each term and an index is generated for each text, 4. Clustering Algorithms (the clustering algorithms Simple K-Means, sIB and EM are applied to the indexes. After those procedures, clustering correctness and clustering time statistical results were collected. The sIB clustering algorithm is the best choice for both scientific and newspaper corpus, under the condition that the sIB clustering algorithm asks for the number of clusters as input before running (for the newspaper corpus, 68.9% correctness in 1 minute and for the scientific corpus, 77.8% correctness in 1 minute. The EM clustering algorithm additionally guesses the number of clusters without user intervention, but its best case is less than 53% correctness. Considering the experiments carried out, the results of human text classification and automated clustering are distant; it was also observed that the clustering correctness results vary according to the number of input texts and their topics.

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

    Science.gov (United States)

    Schaefer, Andreas; Daniell, James; Wenzel, Friedemann

    2016-04-01

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

  10. Brightest Cluster Galaxies and Core Gas Density in REXCESS Clusters

    Science.gov (United States)

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

    2010-04-01

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

  11. A Spitzer Survey of Young Stellar Clusters within One Kiloparsec of the Sun: Cluster Core Extraction and Basic Structural Analysis

    CERN Document Server

    Gutermuth, R A; Myers, P C; Allen, L E; Pipher, J L; Fazio, G G

    2009-01-01

    We present a uniform mid-infrared imaging and photometric survey of 36 young, nearby, star-forming clusters and groups using {\\it Spitzer} IRAC and MIPS. We have confidently identified and classified 2548 young stellar objects using recently established mid-infrared color-based methods. We have devised and applied a new algorithm for the isolation of local surface density enhancements from point source distributions, enabling us to extract the overdense cores of the observed star forming regions for further analysis. We have compiled several basic structural measurements of these cluster cores from the data, such as mean surface densities of sources, cluster core radii, and aspect ratios, in order to characterize the ranges for these quantities. We find that a typical cluster core is 0.39 pc in radius, has 26 members with infrared excess in a ratio of Class II to Class I sources of 3.7, is embedded in a $A_K$=0.8 mag cloud clump, and has a surface density of 60 pc$^{-2}$. We examine the nearest neighbor dista...

  12. Active matter clusters at interfaces.

    Science.gov (United States)

    Copenhagen, Katherine; Gopinathan, Ajay

    2016-03-01

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

  13. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    Benacquista Matthew J.

    2006-02-01

    Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing 10^4 - 10^7 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker-Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  14. Mechanical Resonance of embedded cluster

    CERN Document Server

    Wen, Z; Wen, Zhenying; Zhao, Hong

    2004-01-01

    Embedded clusters, which are embedded in bulk materials and different from the surroundings in structures, should be common in materials. This paper studies resonance of such clusters. This work is stimulated by a recent experimental observation that some localized clusters behavior like fluid at the mesoscopic scale in many solid materials [Science in China(Series B). 46, 176 (2003)]. We argue that the phenomenon is just a vivid illustration of resonance of embedded clusters, driven by ubiquitous microwaves. Because the underlying mechanism is fundamental and embedded structures are usual, the phenomenon would have great significance in material physics.

  15. Optical properties of cluster plasma

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-03-01

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

  16. Privacy-preserving distributed clustering

    DEFF Research Database (Denmark)

    Erkin, Zekeriya; Veugen, Thijs; Toft, Tomas;

    2013-01-01

    Clustering is a very important tool in data mining and is widely used in on-line services for medical, financial and social environments. The main goal in clustering is to create sets of similar objects in a data set. The data set to be used for clustering can be owned by a single entity, or in s...... provider with computations. Experimental results clearly indicate that the work we present is an efficient way of deploying a privacy-preserving clustering algorithm in a distributed manner....

  17. Active matter clusters at interfaces.

    Directory of Open Access Journals (Sweden)

    Katherine eCopenhagen

    2016-03-01

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

  18. Integrative cluster analysis in bioinformatics

    CERN Document Server

    Abu-Jamous, Basel; Nandi, Asoke K

    2015-01-01

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

  19. Nanophase materials assembled from atomic clusters

    Energy Technology Data Exchange (ETDEWEB)

    Siegel, R.W.

    1989-09-01

    The preparation of atomic clusters of metals and ceramics by means of the gas-condensation method, followed by their in situ consolidation under high-vacuum conditions, has recently led to the synthesis of a new class of ultrafine-grained materials for which their physics is intimately coupled with their application. These nanophase materials, with 2 to 20 nm grain sizes, appear to have properties that are often rather different from conventional materials, and also processing characteristics that are greatly improved. The nanophase synthesis method described here should enable the design of materials heretofore unavailable, with improved or unique properties, based upon an understanding of the physics of these new materials. 23 refs., 8 figs.

  20. Statistical significance for hierarchical clustering in genetic association and microarray expression studies

    Directory of Open Access Journals (Sweden)

    Yang Yaning

    2003-12-01

    Full Text Available Abstract Background With the increasing amount of data generated in molecular genetics laboratories, it is often difficult to make sense of results because of the vast number of different outcomes or variables studied. Examples include expression levels for large numbers of genes and haplotypes at large numbers of loci. It is then natural to group observations into smaller numbers of classes that allow for an easier overview and interpretation of the data. This grouping is often carried out in multiple steps with the aid of hierarchical cluster analysis, each step leading to a smaller number of classes by combining similar observations or classes. At each step, either implicitly or explicitly, researchers tend to interpret results and eventually focus on that set of classes providing the "best" (most significant result. While this approach makes sense, the overall statistical significance of the experiment must include the clustering process, which modifies the grouping structure of the data and often removes variation. Results For hierarchically clustered data, we propose considering the strongest result or, equivalently, the smallest p-value as the experiment-wise statistic of interest and evaluating its significance level for a global assessment of statistical significance. We apply our approach to datasets from haplotype association and microarray expression studies where hierarchical clustering has been used. Conclusion In all of the cases we examine, we find that relying on one set of classes in the course of clustering leads to significance levels that are too small when compared with the significance level associated with an overall statistic that incorporates the process of clustering. In other words, relying on one step of clustering may furnish a formally significant result while the overall experiment is not significant.

  1. Class in Metropolitan India: The Rise of the Middle Classes

    OpenAIRE

    Mooij, Jos; Lama-Rewal, S.T.

    2009-01-01

    textabstractIt is almost a cliché to say that India’s appearance and image (internationally as well as self-image) have changed dramatically in the last fifteen years. Instead of being associated with rural poverty, India is now associated with high rates of economic growth, a booming Information Technology (IT) sector and, particularly, an increasingly expanding middle class that consumes and behaves like elites and middle classes elsewhere in the world. Considering that cities concentrate m...

  2. AutoClass: A Bayesian Approach to Classification

    Science.gov (United States)

    Stutz, John; Cheeseman, Peter; Hanson, Robin; Taylor, Will; Lum, Henry, Jr. (Technical Monitor)

    1994-01-01

    We describe a Bayesian approach to the untutored discovery of classes in a set of cases, sometimes called finite mixture separation or clustering. The main difference between clustering and our approach is that we search for the "best" set of class descriptions rather than grouping the cases themselves. We describe our classes in terms of a probability distribution or density function, and the locally maximal posterior probability valued function parameters. We rate our classifications with an approximate joint probability of the data and functional form, marginalizing over the parameters. Approximation is necessitated by the computational complexity of the joint probability. Thus, we marginalize w.r.t. local maxima in the parameter space. We discuss the rationale behind our approach to classification. We give the mathematical development for the basic mixture model and describe the approximations needed for computational tractability. We instantiate the basic model with the discrete Dirichlet distribution and multivariant Gaussian density likelihoods. Then we show some results for both constructed and actual data.

  3. New Ramsey Classes from Old

    CERN Document Server

    Bodirsky, Manuel

    2012-01-01

    Let C_1 and C_2 be strong amalgamation classes of finite structures, with disjoint finite signatures sigma and tau. Then C_1 wedge C_2 denotes the class of all finite (sigma cup tau)-structures whose sigma-reduct is from C_1 and whose tau-reduct is from C_2. We prove that when C_1 and C_2 are Ramsey, then C_1 wedge C_2 is also Ramsey. We also discuss variations of this statement, and give several examples of new Ramsey classes derived from those general results.

  4. Lipschitz classes on local fields

    Institute of Scientific and Technical Information of China (English)

    Wei-yi SU; Guo-xiang CHEN

    2007-01-01

    The Lipschitz class Lipα on a local field K is defined in this note, and the equivalent relationship between the Lipschitz class Lipα and the Holder type space Cα (K) is proved. Then, those important characteristics on the Euclidean space Rn and the local field K are compared, so that one may interpret the essential differences between the analyses on Rn and K. Finally, the Cantor type fractal function (V)(x) is showed in the Lipschitz class Lip (m, K), m < ln2/ln3.

  5. Management of Classes with Breaches of Discipline

    Institute of Scientific and Technical Information of China (English)

    陈海军

    2009-01-01

    As an only child is pampered and spoiled by parents, the contemporary student easily breaches class discipline. Class management appears more concerned than ever because breaches of class discipline have great impact on teaching. The author clarifies the necessity to study the management of classes with breaches of class discipline, numerates the phenomena of breaches of class discipline, precisely analyzes the causes from teachers and students and especially submits several measures to effectively prevent breaches of class discipline.

  6. CBVANET: A Cluster Based Vehicular Adhoc Network Model for Simple Highway Communication

    OpenAIRE

    Ramakrishnan, B; Dr. R. S. Rajesh; R.S. Shaji

    2011-01-01

    VANET is a special class of Mobile Ad hoc Network. VANET is mainly used to model communication in a Vehicular environment where the vehicles are considered as VANET nodes with wireless links. In this paper an attempt has been made to create a new cluster model for efficient communication among the VANET nodes. For this purpose, taking the Simple Highway Vehicular model concept into consideration, a clustering model has been created. The proposed mobility model is called simple highway mobili...

  7. Hydrometeor classification from polarimetric radar measurements: a clustering approach

    Directory of Open Access Journals (Sweden)

    J. Grazioli

    2015-01-01

    Full Text Available A data-driven approach to the classification of hydrometeors from measurements collected with polarimetric weather radars is proposed. In a first step, the optimal number of hydrometeor classes (nopt that can be reliably identified from a large set of polarimetric data is determined. This is done by means of an unsupervised clustering technique guided by criteria related both to data similarity and to spatial smoothness of the classified images. In a second step, the nopt clusters are assigned to the appropriate hydrometeor class by means of human interpretation and comparisons with the output of other classification techniques. The main innovation in the proposed method is the unsupervised part: the hydrometeor classes are not defined a priori, but they are learned from data. The approach is applied to data collected by an X-band polarimetric weather radar during two field campaigns (from which about 50 precipitation events are used in the present study. Seven hydrometeor classes (nopt = 7 have been found in the data set, and they have been identified as light rain (LR, rain (RN, heavy rain (HR, melting snow (MS, ice crystals/small aggregates (CR, aggregates (AG, and rimed-ice particles (RI.

  8. Hydrometeor classification from polarimetric radar measurements: a clustering approach

    Science.gov (United States)

    Grazioli, J.; Tuia, D.; Berne, A.

    2015-01-01

    A data-driven approach to the classification of hydrometeors from measurements collected with polarimetric weather radars is proposed. In a first step, the optimal number of hydrometeor classes (nopt) that can be reliably identified from a large set of polarimetric data is determined. This is done by means of an unsupervised clustering technique guided by criteria related both to data similarity and to spatial smoothness of the classified images. In a second step, the nopt clusters are assigned to the appropriate hydrometeor class by means of human interpretation and comparisons with the output of other classification techniques. The main innovation in the proposed method is the unsupervised part: the hydrometeor classes are not defined a priori, but they are learned from data. The approach is applied to data collected by an X-band polarimetric weather radar during two field campaigns (from which about 50 precipitation events are used in the present study). Seven hydrometeor classes (nopt = 7) have been found in the data set, and they have been identified as light rain (LR), rain (RN), heavy rain (HR), melting snow (MS), ice crystals/small aggregates (CR), aggregates (AG), and rimed-ice particles (RI).

  9. Hydrometeor classification from polarimetric radar measurements: a clustering approach

    Directory of Open Access Journals (Sweden)

    J. Grazioli

    2014-08-01

    Full Text Available A data-driven approach to the classification of hydrometeors from measurements collected with polarimetric weather radars is proposed. In a first step, the optimal number nopt of hydrometeor classes that can be reliably identified from a large set of polarimetric data is determined. This is done by means of an unsupervised clustering technique guided by criteria related both to data similarity and to spatial smoothness of the classified images. In a second step, the nopt clusters are assigned to the appropriate hydrometeor class by means of human interpretation and comparisons with the output of other classification techniques. The main innovation in the proposed method is the unsupervised part: the hydrometeor classes are not defined a-priori, but they are learned from data. The proposed approach is applied to data collected by an X-band polarimetric weather radar during two field campaigns (totalling about 3000 h of precipitation. Seven hydrometeor classes have been found in the data set and they have been associated to drizzle (DZ, light rain (LR, heavy rain (HR, melting snow (MS, ice crystals/small aggregates (CR, aggregates (AG, rimed particles (RI.

  10. The Confucian Asian cluster

    Directory of Open Access Journals (Sweden)

    Ionel Sergiu Pirju

    2013-11-01

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

  11. Generalized analytical design equations for variable slope class-e power amplifiers

    NARCIS (Netherlands)

    Acar, Mustafa; Annema, Anne Johan; Nauta, Bram

    2006-01-01

    The Class-E power amplifier is widely used because of its high efficiency, resulting from switching at zero voltage and zero slope of the switch voltage. In this paper, we extend our general analytical solutions for the Class-E power amplifier to the ideal single-ended Variable Slope Class-E (Class-

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

    KAUST Repository

    Wong, Kachun

    2014-10-01

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

  13. Meaningful Clustered Forest: an Automatic and Robust Clustering Algorithm

    CERN Document Server

    Tepper, Mariano; Almansa, Andrés

    2011-01-01

    We propose a new clustering method that can be regarded as a numerical method to compute the proximity gestalt. The method analyzes edge length statistics in the MST of the dataset and provides an a contrario cluster detection criterion. The approach is fully parametric on the chosen distance and can detect arbitrarily shaped clusters. The method is also automatic, in the sense that only a single parameter is left to the user. This parameter has an intuitive interpretation as it controls the expected number of false detections. We show that the iterative application of our method can (1) provide robustness to noise and (2) solve a masking phenomenon in which a highly populated and salient cluster dominates the scene and inhibits the detection of less-populated, but still salient, clusters.

  14. A cluster randomized control field trial of the ABRACADABRA web-based reading technology: replication and extension of basic findings

    OpenAIRE

    Piquette, Noella A.; Savage, Robert S.; Abrami, Philip C.

    2014-01-01

    The present paper reports a cluster randomized control trial evaluation of teaching using ABRACADABRA (ABRA), an evidence-based and web-based literacy intervention (http://abralite.concordia.ca) with 107 kindergarten and 96 grade 1 children in 24 classes (12 intervention 12 control classes) from all 12 elementary schools in one school district in Canada. Children in the intervention condition received 10–12 h of whole class instruction using ABRA between pre- and post-test. Hierarchical linea...

  15. Probing the structure and dynamics of cage-like clusters: from water to Met-Cars

    International Nuclear Information System (INIS)

    Our recent work on metal compounds led to the discovery of a new class of metal-carbon clusters which are of finite size and have specific geometry, but exhibit varying electronic character because of the different metals of which they can be comprised. We term these metallo-carbohedrenes or Met-Cars for short. This paper reviews the progress made in elucidating the structures if these two classes of clusters which seem to be quite different, but have some interesting common features involving structural considerations. (orig.)

  16. Class attendance and university performance

    OpenAIRE

    Hoffmann, Anna-Lena; Lerche, Katharina

    2016-01-01

    Using survey data collected at Göttingen University, Germany, this paper evaluates the effect of attending the lecture and/or tutorial on the grade achieved in two basic courses in business administration and economics. The analysis shows that going to class has no significant impact on student performance in most specifications. Although the identification of a causal effect may not be possible with the data at hand, the results suggest that, in the given framework, attending class and study...

  17. Whole Class Laboratories: More Examples

    Science.gov (United States)

    Kouh, Minjoon

    2016-03-01

    Typically, introductory physics courses are taught with a combination of lectures and laboratories in which students have opportunities to discover the natural laws through hands-on activities in small groups. This article reports the use of Google Drive, a free online document-sharing tool, in physics laboratories for pooling experimental data from the whole class. This pedagogical method was reported earlier, and the present article offers a few more examples of such "whole class" laboratories.

  18. Less than a Class Set

    Science.gov (United States)

    Bennett, Kristin Redington

    2012-01-01

    The iPad holds amazing potential for classroom use. Just a few--or even only one--is enough to get results. Having a class set promotes traditional, whole-class instruction, but fewer iPads facilitate individualized and tailored instruction. In this article, the author discusses the potential of the iPad and suggests ways to put the iPad to use in…

  19. Internet service classes under competition

    OpenAIRE

    Gibbens, R.; R. Mason; Steinberg, Richard

    2000-01-01

    This paper analyzes competition between two Internet service providers (ISPs), either or both of which may choose to offer multiple service classes. In the model analyzed, a social planner who maximizes the total benefit from network usage and a profit maximizing monopolist will both form multiple service classes; but two networks competing to maximize profits will not. The reason is that a competition effect always outweighs a segmentation effect. Networks wish to offer multiple service clas...

  20. A cluster analysis on students' perceived motivational climate. Implications on psycho-social variables.

    Science.gov (United States)

    Fernandez-Rio, Javier; Méndez-Giménez, Antonio; Cecchini Estrada, Jose A

    2014-01-01

    The aim of this study was to examine how students' perceptions of the class climate influence their basic psychological needs, motivational regulations, social goals and outcomes such as boredom, enjoyment, effort, and pressure/tension. 507 (267 males, 240 females) secondary education students agreed to participate. They completed a questionnaire that included the Spanish validated versions of Perceived Motivational Climate in Sport Questionnaire (PMCSQ-2), Basic Psychological Needs in Exercise (BPNES), Perceived Locus of Causality (PLOC), Social Goal Scale-Physical Education (SGS-PE), and several subscales of the IMI. A hierarchical cluster analysis uncovered four independent class climate profiles that were confirmed by a K-Means cluster analysis: "high ego", "low ego-task", "high ego-medium task", and "high task". Several MANOVAs were performed using these clusters as independent variables and the different outcomes as dependent variables (p responsibility and relationship, as well as low levels of amotivation, boredom and pressure/tension. Students' perceptions of a performance class climate made the positive scores decrease significantly. Cluster 3 revealed that a mastery oriented class structure undermines the negative behavioral and psychological effects of a performance class climate. This finding supports the buffering hypothesis of the achievement goal theory. PMID:25012581

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

    International Nuclear Information System (INIS)

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

  2. Effective FCM noise clustering algorithms in medical images.

    Science.gov (United States)

    Kannan, S R; Devi, R; Ramathilagam, S; Takezawa, K

    2013-02-01

    The main motivation of this paper is to introduce a class of robust non-Euclidean distance measures for the original data space to derive new objective function and thus clustering the non-Euclidean structures in data to enhance the robustness of the original clustering algorithms to reduce noise and outliers. The new objective functions of proposed algorithms are realized by incorporating the noise clustering concept into the entropy based fuzzy C-means algorithm with suitable noise distance which is employed to take the information about noisy data in the clustering process. This paper presents initial cluster prototypes using prototype initialization method, so that this work tries to obtain the final result with less number of iterations. To evaluate the performance of the proposed methods in reducing the noise level, experimental work has been carried out with a synthetic image which is corrupted by Gaussian noise. The superiority of the proposed methods has been examined through the experimental study on medical images. The experimental results show that the proposed algorithms perform significantly better than the standard existing algorithms. The accurate classification percentage of the proposed fuzzy C-means segmentation method is obtained using silhouette validity index.

  3. Phase classification by mean shift clustering of multispectral materials images.

    Science.gov (United States)

    Martins, Diego Schmaedech; Josa, Victor M Galván; Castellano, Gustavo; da Costa, José A T Borges

    2013-10-01

    A mean-shift clustering (MSC) algorithm is introduced as a valuable alternative to perform materials phase classification from multispectral images. As opposed to other multivariate statistical techniques, such as factor analysis or principal component analysis (PCA), clustering techniques directly assign a class label to each pixel, so that their outputs are phase segmented images, i.e., there is no need for an additional segmentation algorithm. On the other hand, as compared to other clustering procedures and classification methods, such as segmentation by thresholding of multiple spectral components, MSC has the advantages of not requiring previous knowledge of the number of data clusters and not assuming any shape for these clusters, i.e., neither the number nor the composition of the phases must be previously known. This makes MSC a particularly useful tool for exploratory research, assisting phase identification of unknown samples. Visualization and interpretation of the results are also simplified, since the information content of the output image does not depend on the particular choice of the content of the color channels.We applied MSC to the analysis of two sets of X-ray maps acquired in scanning electron microscopes equipped with energy-dispersive detection systems. Our results indicate that MSC is capable of detecting additional phases, not clearly identified through PCA or multiple thresholding, with a very low empirical reject rate.

  4. CLASSING APPROACH TO ANALYZING THE INVESTMENT SPACE OF SILK INDUSTRY OF UZBEKISTAN

    OpenAIRE

    Madjidov, Shakhrukh; Ibragimova, Sabokhat

    2015-01-01

    In the article the results of verification were brought which were dedicated for cluster approach and analyzing the investment space of silk industry of Uzbekistan. In particular the purpose of investment’s direction to the main capital of silk industry in corresponding class while proceeding from closeness to manual forces and raw material resources.

  5. The JVAS/CLASS search for 6-arcsec to 15-arcsec image separation lensing

    NARCIS (Netherlands)

    Phillips, PM; Browne, IWA; Jackson, NJ; Wilkinson, PN; Mao, S; Rusin, D; Marlow, DR; Snellen, [No Value; Neeser, M

    2001-01-01

    The Jodrell Bank-VLA Astrometric Survey (JVAS) and the Cosmic Lens All Sky Survey (CLASS) have been systematically searched for multiple gravitational imaging of sources with image separations between 6 arcsec and 15 arcsec, associated with galaxy group and cluster lensing masses. The radio and opti

  6. Covering #SAE: A Mobile Reporting Class's Changing Patterns of Interaction on Twitter over Time

    Science.gov (United States)

    Jones, Julie

    2015-01-01

    This study examined the social network that emerged on Twitter surrounding a mobile reporting class as they covered a national breaking news event. The work introduces pedagogical strategies that enhance students' learning opportunities. Through NodeXL and social network cluster analysis, six groups emerged from the Twitter interactions tied to…

  7. The Relationship of Academic Self-Efficacy to Class Participation and Exam Performance

    Science.gov (United States)

    Galyon, Charles E.; Blondin, Carolyn A.; Yaw, Jared S.; Nalls, Meagan L.; Williams, Robert L.

    2012-01-01

    This study examined the relationship of academic self-efficacy to engagement in class discussion and performance on major course exams among students (N = 165) in an undergraduate human development course. Cluster analysis was used to identify three levels of academic self-efficacy: high (n = 34), medium (n = 91), and low (n = 40). Results…

  8. A latent class distance association model for cross-classified data with a categorical response variable

    NARCIS (Netherlands)

    Vera, J.F.; Rooij, M. de; Heiser, W.J.

    2014-01-01

    In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single ou

  9. Tune Your Brown Clustering, Please

    DEFF Research Database (Denmark)

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

    2015-01-01

    unexplored. Accordingly, we present information for practitioners on the behaviour of Brown clustering in order to assist hyper-parametre tuning, in the form of a theoretical model of Brown clustering utility. This model is then evaluated empirically in two sequence labelling tasks over two text types. We...

  10. Bayesian Agglomerative Clustering with Coalescents

    OpenAIRE

    Teh, Yee Whye; Daumé III, Hal; Roy, Daniel

    2009-01-01

    We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman's coalescent. We develop novel greedy and sequential Monte Carlo inferences which operate in a bottom-up agglomerative fashion. We show experimentally the superiority of our algorithms over others, and demonstrate our approach in document clustering and phylolinguistics.

  11. FunGeneClusterS

    DEFF Research Database (Denmark)

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

    2016-01-01

    Secondary metabolites of fungi are receiving an increasing amount of interest due to their prolific bioactivities and the fact that fungal biosynthesis of secondary metabolites often occurs from co-regulated and co-located gene clusters. This makes the gene clusters attractive for synthetic biology...

  12. Chemical exposure and leukemia clusters

    International Nuclear Information System (INIS)

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

  13. The Nordic Mobile Telecommunication Cluster

    DEFF Research Database (Denmark)

    Jørgensen, Ulrik

    2000-01-01

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

  14. Cold fronts in galaxy clusters

    CERN Document Server

    Ghizzardi, Simona; Molendi, Silvano

    2010-01-01

    Cold fronts have been observed in a large number of galaxy clusters. Understanding their nature and origin is of primary importance for the investigation of the internal dynamics of clusters. To gain insight on the nature of these features, we carry out a statistical investigation of their occurrence in a sample of galaxy clusters observed with XMM-Newton and we correlate their presence with different cluster properties. We have selected a sample of 45 clusters starting from the B55 flux limited sample by Edge et al. (1990) and performed a systematic search of cold fronts. We find that a large fraction of clusters host at least one cold front. Cold fronts are easily detected in all systems that are manifestly undergoing a merger event in the plane of the sky while the presence of such features in the remaining clusters is related to the presence of a steep entropy gradient, in agreement with theoretical expectations. Assuming that cold fronts in cool core clusters are triggered by minor merger events, we esti...

  15. Inferring modules from human protein interactome classes

    Directory of Open Access Journals (Sweden)

    Chaurasia Gautam

    2010-07-01

    Full Text Available Abstract Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features. Results We examined this issue based on the analysis of modules detected by network clustering methods applied to both integrated and individual (disaggregated data sources, which we call interactome classes. Due to class diversity, we deal with variable dependencies of data features arising from structural specificities and biases, but also from possible overlaps. Since highly connected regions of the human interactome may point to potential protein complexes, we have focused on the concept of modularity, and elucidated the detection power of module extraction algorithms by independent validations based on GO, MIPS and KEGG. From the combination of protein interactions with gene expressions, a confidence scoring scheme has been proposed before proceeding via GO with further classification in permanent and transient modules. Conclusions Disaggregated interactomes are shown to be informative for inferring modularity, thus contributing to perform an effective integrative analysis. Validation of the extracted modules by multiple annotation allows for the assessment of confidence measures assigned to the modules in a protein pathway context. Notably, the proposed multilayer confidence scheme can be used for network calibration by enabling a transition from unweighted to weighted interactomes based on biological evidence.

  16. A New Complete Class Complexity Metric

    OpenAIRE

    Singh, Vinay; Bhattacherjee, Vandana

    2014-01-01

    Software complexity metrics is essential for minimizing the cost of software maintenance. Package level and System level complexity cannot be measured without class level complexity. This research addresses the class complexity metrics. This paper studies the existing class complexity metrics and proposes a new class complexity metric CCC (Complete class complexity metric). The CCC metric is then analytically evaluated by Weyuker's property.

  17. An Exact Relaxation of Clustering

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    2009-01-01

    of clustering problems such as the K-means objective and pairwise clustering as well as graph partition problems, e.g., for community detection in complex networks. In particular we show that a relaxation to the simplex can be given for which the extreme solutions are stable hard assignment solutions and vice......Continuous relaxation of hard assignment clustering problems can lead to better solutions than greedy iterative refinement algorithms. However, the validity of existing relaxations is contingent on problem specific fuzzy parameters that quantify the level of similarity between the original...... versa. Based on the new relaxation we derive the SR-clustering algorithm that has the same complexity as traditional greedy iterative refinement algorithms but leading to significantly better partitions of the data. A Matlab implementation of the SR-clustering algorithm is available for download....

  18. Protonated water clusters in TPC's

    Science.gov (United States)

    Kaya, Yunus; Kalkan, Yalçın; Veenhof, Rob

    2016-07-01

    Water vapour is added to the ALICE TPC gas to enhance its stability. These polar molecules create large protonated water clusters around a H+ core. In this context, the reactions H3O+(H2 O) n - 1 +H2 O →H3O+(H2O)n (n=1-9) were studied in the gas phase. Structures for these clusters are suggested and the most stable structures for each cluster size are shown. The thermodynamic parameters Δ Hn-1,n0, Δ Gn-1,n0, Δ Sn-1,n0 and equilibrium constants K n - 1 , n for the reaction were calculated to determine the size of the water clusters. The results are close to experimental data found in the literature. Protonated water clusters at stp have a size of 6-9 which corresponds to a mass of 127.1 - 181.2 g / mole.

  19. The inner Galactic globular clusters

    Directory of Open Access Journals (Sweden)

    Mateo M.

    2013-03-01

    Full Text Available Galactic globular clusters located towards the inner regions of the Milky Way have been historically neglected, mainly due to the difficulties caused by the presence of an elevated extinction by foreground dust, and high field star densities along the lines of sight where most of them lie. To overcome these difficulties we have developed a new method to map the differential extinction suffered by these clusters, which was successfully applied to a sample of moderately-extincted, luminous, extended, inner Galactic globular clusters observed in the optical, for which we have been able to determine more accurate physical parameters. For the most extincted inner Galactic globular clusters, near-infrared wavelengths provide a more suitable window for their study. The VVV survey, which is currently observing the central regions of the Milky Way at these wavelengths, will provide a comprehensive view, from the inner regions out to their tidal radii and beyond, of most of these globular clusters.

  20. Seven poor clusters of galaxies

    Science.gov (United States)

    Beers, T. C.; Geller, M. J.; Huchra, J. P.; Latham, D. W.; Davis, R. J.

    1984-01-01

    The measurement of 83 new redshifts from galaxies in the region of seven of the poor clusters of galaxies identified by Morgan et al (1975) and Albert et al (1977) has been followed by an estimation of cluster masses through the application of both the virial theorem and the projected mas method. For each system, these two estimates are consistent. For the two clusters with highest X-ray luminosities, the line-of-sight velocity dispersions are about 700 km/sec, while for the five other clusters, the dispersions are of the order of less than about 370 km/sec. The D or cD galaxy in each poor cluster is at the kinematic center of each system.

  1. Sequential clustering of star formations in IC 1396

    International Nuclear Information System (INIS)

    We present a comprehensive study of the H II region IC 1396 and its star forming activity, in which multi-wavelength data ranging from the optical to the near- and far-infrared were employed. The surface density distribution of all the 2MASS sources with a certain detection toward IC 1396 indicates the existence of a compact cluster spatially consistent with the position of the exciting source of the H II region, HD 206267. The spatial distribution of the sources with excessive infrared emission, selected based on archived 2MASS data, reveals the existence of four sub-clusters in this region. One is associated with the open cluster Trumpler 37. The other three are found to be spatially coincident with the bright rims of the H II region. All the sources with excessive emission in the near infrared are cross-identified with AKARI IRC data. An analysis of the spectral energy distributions (SEDs) of the resultant sample leads to the identification of eight CLASS I, 15 CLASS II and 15 CLASS III sources in IC 1396. Optical identification of the sample sources with R magnitudes brighter than 17 mag corroborates the results from the SED analysis. Based on the spatial distribution of the infrared young stellar objects at different evolutionary stages, the surrounding sub-clusters located in the bright rims are believed to be younger than the central one. This is consistent with a scenario of sequential star formation in this region. Imaging data of a dark patch in IC 1396 by Herschel SPIRE, on the other hand, indicate the presence of two far-infrared cores in LDN 1111, which are likely to be a new generation of protostellar objects in formation. So we infer that the star formation process in this H II region was not continuous but rather episodic

  2. Sequential clustering of star formations in IC 1396

    Institute of Scientific and Technical Information of China (English)

    Ya-Fang Huang; Jin-Zeng Li

    2013-01-01

    We present a comprehensive study of the H Ⅱ region IC 1396 and its star forming activity,in which multi-wavelength data ranging from the optical to the nearand far-infrared were employed.The surface density distribution of all the 2MASS sources with a certain detection toward IC 1396 indicates the existence of a compact cluster spatially consistent with the position of the exciting source of the H Ⅱ region,HD 206267.The spatial distribution of the sources with excessive infrared emission,selected based on archived 2MASS data,reveals the existence of four sub-clusters in this region.One is associated with the open cluster Trumpler 37.The other three are found to be spatially coincident with the bright rims of the H Ⅱ region.All the sources with excessive emission in the near infrared are cross-identified with AKARI IRC data.An analysis of the spectral energy distributions (SEDs) of the resultant sample leads to the identification of eight CLASS I,15 CLASS Ⅱ and 15 CLASS Ⅲ sources in IC 1396.Optical identification of the sample sources with R magnitudes brighter than 17 mag corroborates the results from the SED analysis.Based on the spatial distribution of the infrared young stellar objects at different evolutionary stages,the surrounding sub-clusters located in the bright rims are believed to be younger than the central one.This is consistent with a scenario of sequential star formation in this region.Imaging data of a dark patch in IC 1396 by Herschel SPIRE,on the other hand,indicate the presence of two far-infrared cores in LDN 1111,which are likely to be a new generation of protostellar objects in formation.So we infer that the star formation process in this H Ⅱ region was not continuous but rather episodic.

  3. Sequential clustering of star formations in IC 1396

    Science.gov (United States)

    Huang, Ya-Fang; Li, Jin-Zeng

    2013-05-01

    We present a comprehensive study of the H II region IC 1396 and its star forming activity, in which multi-wavelength data ranging from the optical to the near- and far-infrared were employed. The surface density distribution of all the 2MASS sources with a certain detection toward IC 1396 indicates the existence of a compact cluster spatially consistent with the position of the exciting source of the H II region, HD 206267. The spatial distribution of the sources with excessive infrared emission, selected based on archived 2MASS data, reveals the existence of four sub-clusters in this region. One is associated with the open cluster Trumpler 37. The other three are found to be spatially coincident with the bright rims of the H II region. All the sources with excessive emission in the near infrared are cross-identified with AKARI IRC data. An analysis of the spectral energy distributions (SEDs) of the resultant sample leads to the identification of eight CLASS I, 15 CLASS II and 15 CLASS III sources in IC 1396. Optical identification of the sample sources with R magnitudes brighter than 17 mag corroborates the results from the SED analysis. Based on the spatial distribution of the infrared young stellar objects at different evolutionary stages, the surrounding sub-clusters located in the bright rims are believed to be younger than the central one. This is consistent with a scenario of sequential star formation in this region. Imaging data of a dark patch in IC 1396 by Herschel SPIRE, on the other hand, indicate the presence of two far-infrared cores in LDN 1111, which are likely to be a new generation of protostellar objects in formation. So we infer that the star formation process in this H II region was not continuous but rather episodic.

  4. The Intersection between Out-of-class Language Learning Strategies and In-class Activities

    Directory of Open Access Journals (Sweden)

    Noor Saazai Mat Saad

    2013-07-01

    Full Text Available Studies on out-of-class language learning strategies (OCLLSs are usually divorced from the activities in class. Thus, this study addresses the connection of the two entities. The participants in this study were nine international postgraduate students who were undergoing their English language proficiency course in an institution in Malaysia.  Data were gathered through their weekly online postings on Google + and interview during the course. The data from the students were triangulated with the information found in the pro forma of the modules and interview with the lecturers. Atlas ti was used to manage the data.  It was discovered that the type of assessment set by lecturers for the course determined the use of OCLLSs. Findings show that firstly, more OCLLS were used in completing assignments than preparing for quizzes/tests. Thus, from the 3 modules; it was found that students employed more strategies for oral communication and writing rather than for reading.  Secondly, the OCLLSs used could form a 'strategy chain or cluster' for the tasks of preparing for oral presentation and completing writing assignments. Lastly, there was evidence of technology dependency on some of the main OCLLSs.  

  5. Classes subalternas, lutas de classe e hegemonia: uma abordagem gramsciana Subaltern classes, class struggles and hegemony: a gramscian approach

    Directory of Open Access Journals (Sweden)

    Ivete Simionatto

    2009-06-01

    Full Text Available O artigo procura resgatar, no pensamento de Antonio Gramsci, a concepção de classes subalternas e a sua relação com outras categorias, especialmente, o Estado, a sociedade civil e a hegemonia, como suportes da luta de classes na realidade contemporânea. Aborda, ainda, as relações entre classes subalternas, senso comum e ideologia, bem como as formas de superação tematizadas por Gramsci, através da cultura e da filosofia da práxis. Nesse sentido, num movimento de totalidade, busca recuperar a discussão das classes subalternas, a partir da original formulação gramsciana no âmbito do marxismo, mediante a interação dialética entre estrutura e superestrutura, economia e política. Além do resgate conceitual, apontam-se alguns elementos como subsídios à discussão das formas de subalternidade presentes na realidade contemporânea e as possibilidades de fortalecimento das lutas de tais camadas de classe, sobretudo em momentos de forte desmobilização da participação popular.This article sought to revive the concept of subaltern classes and their relation with other categories, particularly the State, civil society and hegemony in the thinking of Antonio Gramsci, as a support for contemporary class struggles. It also analyzes the relations between subaltern classes, common sense and ideology, as well as the forms of "overcoming" conceptualized by Gramsci, through the culture and philosophy of praxis. The paper revives the discussion of the subaltern classes, based on the original Gramscian formulation in the realm of Marxism, through the dialectic interaction between structure and superstructure, economy and politics. In addition to the conceptual revival, it indicates some elements that can support the discussion of the forms of subalternity found in contemporary reality and the possibilities for strengthening the struggles of these class layers, above all in moments of strong demobilization of popular participation.

  6. EFFECTIVENESS OF OPINION INFLUENCE APPROACHES IN HIGHLY CLUSTERED ONLINE SOCIAL NETWORKS

    OpenAIRE

    MELISSA FALETRA; NATHAN PALMER; Marshall, Jeffrey S.

    2014-01-01

    A mathematical model was developed for opinion propagation on online social networks using a scale-free network with an adjustable clustering coefficient. Connected nodes influence each other when the difference between their opinion values is less than a threshold value. The model is used to examine effectiveness of three different approaches for influencing public opinion. The approaches examined include (1) a "Class", defined as an approach (such as a class or book) that greatly influences...

  7. MHC class I loci of the Bar-Headed goose (Anser indicus

    Directory of Open Access Journals (Sweden)

    Qinglong Liang

    2010-01-01

    Full Text Available MHC class I proteins mediate functions in anti-pathogen defense. MHC diversity has already been investigated by many studies in model avian species, but here we chose the bar-headed goose, a worldwide migrant bird, as a non-model avian species. Sequences from exons encoding the peptide-binding region (PBR of MHC class I molecules were isolated from liver genomic DNA, to investigate variation in these genes. These are the first MHC class I partial sequences of the bar-headed goose to be reported. A preliminary analysis suggests the presence of at least four MHC class I genes, which share great similarity with those of the goose and duck. A phylogenetic analysis of bar-headed goose, goose and duck MHC class I sequences using the NJ method supports the idea that they all cluster within the anseriforms clade.

  8. Spatial dependence clusters in the estimation of forest structural parameters

    Science.gov (United States)

    Wulder, Michael Albert

    1999-12-01

    parameter of crown closure is successfully estimated from image clusters, yet the grouping of trees into clusters causes mixed results when estimating stem counts. The assignment of a cover class of each cluster is also undertaken. The knowledge of cluster cover class has also enabled the estimation of leaf area index. Further, spatial information alone may be used to estimate LAI under described conditions.

  9. Active FEL-Klystrons As Formers of Femto-Second Clusters of Electromagnetic Field. General Description

    Directory of Open Access Journals (Sweden)

    A.Ju. Brusnik

    2010-01-01

    Full Text Available A qualitative physical and technological substantiation of the creation possibility of a new class of Femto-second Free Electron Lasers (FFELs (active cluster FEL-klystrons is given in the article. The concept of “electromagnetic field” cluster is introduced. Apart from that, the main difference between the concepts “the electromagnetic cluster” and “the radio-pulse” (which is well-known in radio-physics is formulated. The concept of “cluster electromagnetic wave” is also discussed. A general approach to designing the proposed active cluster FEL-klystrons is formulated. The description of a principal design scheme of the active cluster FEL-klystrons and their key technological basis are discussed.

  10. Hidden symmetries of finite-size clusters with periodic boundary conditions

    Energy Technology Data Exchange (ETDEWEB)

    Freericks, J.K.; Falicov, L.M. (Department of Physics, University of California, Berkeley, California (USA) Materials Sciences Division, Lawrence Berkeley Laboratory, Berkeley, California (USA))

    1991-08-15

    Finite-size clusters with periodic boundary conditions resemble isolated clusters for a small number of sites, and infinite lattices for a large number of sites. The transition from a self-contained system to an infinite lattice passes through an intermediate region with increased (hidden) symmetry. In this high-symmetry region irreducible representations of the space group may stick together to form higher-dimensional representations of the complete symmetry group. This transition is examined for a class of simple-, body-centered-, and face-centered-cubic lattice clusters and the two-dimensional square lattice cluster. The implications of an enlarged symmetry group are also studied for a model of strongly correlated electrons interacting on eight-site clusters.

  11. Clustering of landforms using self-organizing maps (SOM) in the west of Fars province

    Science.gov (United States)

    Mokarram, Marzieh; Sathyamoorthy, Dinesh

    2016-06-01

    The aim of this study is to cluster landforms in the west of the Fars province, Iran using self-organizing maps (SOM). In SOM, according to qualitative data, the clustering tendencies of landforms were investigated using six morphometric parameters, which were slope, profile, plan, elevation, curvature and aspect. First, topographic position index (TPI) was used to prepare the landform classification map. The results of SOM showed that there were five classes for landform classification in the study area. Cluster 5 corresponds to high slope, high elevation but with different of concavity and convexity that consist of ridge landforms. Cluster 3 corresponds to flat areas, possibly plantation areas, in medium elevation and almost flat terrain. Clusters 1, 2 and 4 correspond to channels with different slope conditions.

  12. AutoClass@IJM: a powerful tool for Bayesian classification of heterogeneous data in biology.

    Science.gov (United States)

    Achcar, Fiona; Camadro, Jean-Michel; Mestivier, Denis

    2009-07-01

    Recently, several theoretical and applied studies have shown that unsupervised Bayesian classification systems are of particular relevance for biological studies. However, these systems have not yet fully reached the biological community mainly because there are few freely available dedicated computer programs, and Bayesian clustering algorithms are known to be time consuming, which limits their usefulness when using personal computers. To overcome these limitations, we developed AutoClass@IJM, a computational resource with a web interface to AutoClass, a powerful unsupervised Bayesian classification system developed by the Ames Research Center at N.A.S.A. AutoClass has many powerful features with broad applications in biological sciences: (i) it determines the number of classes automatically, (ii) it allows the user to mix discrete and real valued data, (iii) it handles missing values. End users upload their data sets through our web interface; computations are then queued in our cluster server. When the clustering is completed, an URL to the results is sent back to the user by e-mail. AutoClass@IJM is freely available at: http://ytat2.ijm.univ-paris-diderot.fr/AutoclassAtIJM.html.

  13. EGRET upper limits on the high-energy gamma-ray emission of galaxy clusters

    CERN Document Server

    Reimer, O; Sreekumar, P; Mattox, J R

    2003-01-01

    We report EGRET upper limits on the high-energy gamma-ray emission from clusters of galaxies. EGRET observations between 1991 and 2000 were analyzed at positions of 58 individual clusters from a flux-limited sample of nearby X-ray bright galaxy clusters. Subsequently, a coadded image from individual galaxy clusters has been analyzed using an adequately adapted diffuse gamma-ray foreground model. The resulting 2 sigma upper limit for the average cluster is \\~ 6 x 10^{-9} cm^{-2} s^{-1} for E > 100 MeV. Implications of the non--detection of prominent individual clusters and of the general inability to detect the X-ray brightest galaxy clusters as a class of gamma-ray emitters are discussed. We compare our results with model predictions on the high-energy gamma-ray emission from galaxy clusters as well as with recent claims of an association between unidentified or unresolved gamma-ray sources and Abell clusters of galaxies and find these contradictory.

  14. Structure of Dark Matter and Baryons in AMIBA SZE Galaxy Clusters (II)

    Science.gov (United States)

    Ho, Paul

    2010-01-01

    We propose deep BR_cz' imaging with Suprime-Cam of several hot X-ray (> 8 keV) clusters of galaxies for which Sunyaev-Zel'dovich effect (SZE) observations are underway at 3mm with the Array for Microwave Background Anisotropy (AMiBA) and superb resolution HST/ACS strong lensing (SL) data are readily available. Joint weak lensing (WL), SL, multicolor imaging, and SZE observations, combined with archival X-ray data, will probe in a model-independent manner the structure of dark matter, member galaxies, and the hot cluster gas in rich cluster environments. Our targets are composed of a class of the most massive clusters at moderate redshifts (0.2 <~ z <~ 0.7), allowing us to derive reliable WL shape measurements and thus accurate mass profiles out to the cluster virial radius. Our proposal aims to (1) map out the mass distribution in clusters via WL techniques, and compare with the distributions of hot and cold baryonic components, (2) make an accurate determination of the cluster mass profile from a joint WL+SL analysis, (3) derive cluster gas-mass fraction profiles free from the hydrostatic equilibrium assumption, and (4) examine directly the cluster mass vs. SZE observable relation, which will provide an important basis for cosmological tests with upcoming blind SZE surveys.

  15. Radio Bubbles in Clusters

    CERN Document Server

    Dunn, R J H; Taylor, G B

    2005-01-01

    We extend our earlier work on cluster cores with distinct radio bubbles, adding more active bubbles, i.e. those with Ghz radio emission, to our sample, and also investigating ``ghost bubbles,'' i.e. those without GHz radio emission. We have determined k, which is the ratio of the total particle energy to that of the electrons radiating between 10 MHz and 10 GHz. Constraints on the ages of the active bubbles confirm that the ratio of the energy factor, k, to the volume filling factor, f lies within the range 1 < k/f < 1000. In the assumption that there is pressure equilibrium between the radio-emitting plasma and the surrounding thermal X-ray gas, none of the radio lobes has equipartition between the relativistic particles and the magnetic field. A Monte-Carlo simulation of the data led to the conclusion that there are not enough bubbles present in the current sample to be able to determine the shape of the population. An analysis of the ghost bubbles in our sample showed that on the whole they have high...

  16. High Power Wideband Class-E Power Amplifier

    OpenAIRE

    Ortega González, Francisco Javier

    2010-01-01

    This letter shows a high-power, high-efficiency, wideband Class-E RF power amplifier designed upon the load admittance synthesis concept and built using an uncomplicated low-loss load network with a low loss wideband admittance transformer as the main component. It uses a power Silicon LDMOS transistor to provide up to 145 W at 28 V peak power, up to 86% drain efficiency over 35% fractional bandwidth (from 85 to 120 MHz) and 15.6 dB gain at peak power without any adjustments. These are clear ...

  17. Classe social, Estado e ideologia Social class, State and ideology

    Directory of Open Access Journals (Sweden)

    Leopoldo Waizbort

    1998-05-01

    Full Text Available O texto reproduz uma aula para concurso junto ao Departamento de Sociologia da FFLCH-USP na qual tentei articular o tríptico classe social, Estado e ideologia, tendo em mente a situação contemporânea empírica e teórica dos três conceitos.This text reproduces a lecture given in the scope of an examination at the Sociology Department of the FFLCH-USP. For the presentation I have tried to articulate the three concepts "social class", "State" and "ideology", by taking into consideration their actual empirical and theoretical situation.

  18. THE EXTENDED VIRGO CLUSTER CATALOG

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-01-01

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

  19. Psychiatric comorbidity among adults with schizophrenia: a latent class analysis.

    Science.gov (United States)

    Tsai, Jack; Rosenheck, Robert A

    2013-11-30

    Schizophrenia is a severe mental illness that often co-occurs with and can be exacerbated by other psychiatric conditions. There have not been adequate efforts to examine schizophrenia and psychiatric comorbidity beyond pairwise examination using clusters of diagnoses. This study used latent class analysis to characterize patterns of 5-year psychiatric comorbidity among a national sample of adults with schizophrenia. Baseline data from 1446 adults with schizophrenia across 57 sites in the United States were analyzed. Three latent classes were identified labeled Solely Schizophrenia, Comorbid Anxiety and Depressive Disorders with Schizophrenia, and Comorbid Addiction and Schizophrenia. Adults in the Solely Schizophrenia class had significantly better mental health than those in the two comorbid classes, but poorer illness and treatment insight than those with comorbid anxiety and depressive disorders. These results suggest that addiction and schizophrenia may represent a separate latent profile from depression, anxiety, and schizophrenia. More research is needed on how treatment can take advantage of the greater insight possessed by those with schizophrenia and comorbid anxiety and depression.

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

    Science.gov (United States)

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

    2014-01-01

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

  1. Second generation stellar disks in Globular Clusters and cluster ellipticities

    CERN Document Server

    Mastrobuono-Battisti, Alessandra

    2015-01-01

    Globular clusters (GCs) and Nuclear Stellar Clusters (NSCs) are typically composed by several stellar generations, characterized by different ages and chemical compositions. The youngest populations in NSCs appear to reside in disk-like structures, as observed in our Galaxy and in M31. Gas infall followed by formation of second generation (SG) stars in GCs may similarly form disk-like structures in the clusters nuclei. Here we explore this possibility and follow the long term evolution of stellar disks embedded in GCs, and study their affects on the evolution of the clusters. We study disks with different masses by means of detailed N-body simulations and explore their morphological and kinematic signatures on the GC structures. We find that as a second generation disk relaxes, the old, first generation, stellar population flattens and becomes more radially anisotropic, making the GC structure become more elliptical. The second generation stellar population is characterized by a lower velocity dispersion, and...

  2. Herschel photometry of brightest cluster galaxies in cooling flow clusters

    CERN Document Server

    Edge, A C; Mittal, R; Allen, S W; Baum, S A; Boehringer, H; Bregman, J N; Bremer, M N; Combes, F; Crawford, C S; Donahue, M; Egami, E; Fabian, A C; Hamer, S L; Hatch, N A; Jaffe, W; Johnstone, R M; McNamara, B R; O'Dea, C P; Popesso, P; Quillen, A C; Salome, P; Sarazin, C L; Voit, G M; Wilman, R J; Wise, M W

    2010-01-01

    The dust destruction timescales in the cores of clusters of galaxies are relatively short given their high central gas densities. However, substantial mid-infrared and sub-mm emission has been detected in many brightest cluster galaxies. In this letter we present Herschel PACS and SPIRE photometry of the brightest cluster galaxy in three strong cooling flow clusters, A1068, A2597 and Zw3146. This photometry indicates that a substantial mass of cold dust is present (>3 x 10^7 Mo) at temperatures significantly lower (20-28K) than previously thought based on limited MIR and/or sub-mm results. The mass and temperature of the dust appear to match those of the cold gas traced by CO with a gas-to-dust ratio of 80-120.

  3. Fast Online Clustering with Randomized Skeleton Sets

    OpenAIRE

    Choromanski, Krzysztof; Kumar, Sanjiv; Liu, Xiaofeng

    2015-01-01

    We present a new fast online clustering algorithm that reliably recovers arbitrary-shaped data clusters in high throughout data streams. Unlike the existing state-of-the-art online clustering methods based on k-means or k-medoid, it does not make any restrictive generative assumptions. In addition, in contrast to existing nonparametric clustering techniques such as DBScan or DenStream, it gives provable theoretical guarantees. To achieve fast clustering, we propose to represent each cluster b...

  4. Dynamics and Shape of Brightest Cluster Galaxies

    CERN Document Server

    Andernach, H; Coziol, R; Tago, E

    2006-01-01

    We identified Brightest Cluster Members (BCM) on DSS images of 1083 Abell clusters, derived their individual and host cluster redshifts from literature and determined the BCM ellipticity. Half the BCMs move at a speed higher than 37 % of the cluster velocity dispersion sigma_{cl}, suggesting that most BCMs are part of substructures falling into the main cluster. Both, the BCM's velocity offset in units of sigma_{cl}, and BCM ellipticity, weakly decrease with cluster richness.

  5. Dynamical Processes in Globular Clusters

    CERN Document Server

    McMillan, Stephen L W

    2014-01-01

    Globular clusters are among the most congested stellar systems in the Universe. Internal dynamical evolution drives them toward states of high central density, while simultaneously concentrating the most massive stars and binary systems in their cores. As a result, these clusters are expected to be sites of frequent close encounters and physical collisions between stars and binaries, making them efficient factories for the production of interesting and observable astrophysical exotica. I describe some elements of the competition among stellar dynamics, stellar evolution, and other processes that control globular cluster dynamics, with particular emphasis on pathways that may lead to the formation of blue stragglers.

  6. Cluster de ventiladores em Catanduva.

    Directory of Open Access Journals (Sweden)

    Luciana M. Onusic

    2005-04-01

    Full Text Available Este trabalho apresenta os resultados de um levantamento feito na cidade de Catanduva sobre a indústria de ventiladores nela instalada. É, inicialmente, apresentado o conceito de cluster, para, em seguida, serem apresentadas as características do setor de ventiladores de Catanduva, fazendo uma comparação desse setor com o conceito de cluster. Diversos aspectos mostram o interesse em considerar o setor como um cluster e são feitas sugestões para seu aprimoramento.

  7. Towards a Class Struggle Anthropology

    Directory of Open Access Journals (Sweden)

    Charles R. Menzies

    2007-05-01

    Full Text Available Dancing between review and argument this paper lays out a foundation for a class-struggle anthropology -that is, an anthropological practice that can be linked to the ultimate goal of achieving a classless society. To this end we will review those anthropologists who have gone before us, pulling out those works of theirs that we see as critical in (rebuilding a class-struggle anthropology. As part of this process we discuss the relationship between what has stood as Marxist anthropology in North America, the idea of socialism, the political development of the world working class during nine decades since the October Revolution, and the challenges of intellectual continuity in the face of differing generational experiences of Marxist anthropologists. Ultimately we argue that a progressive anthropology necessarily involves political activism in our work, communities, and schools.

  8. Universality class in conformal inflation

    Energy Technology Data Exchange (ETDEWEB)

    Kallosh, Renata; Linde, Andrei, E-mail: kallosh@stanford.edu, E-mail: alinde@stanford.edu [Department of Physics and SITP, Stanford University, Stanford, California 94305 (United States)

    2013-07-01

    We develop a new class of chaotic inflation models with spontaneously broken conformal invariance. Observational consequences of a broad class of such models are stable with respect to strong deformations of the scalar potential. This universality is a critical phenomenon near the point of enhanced symmetry, SO(1,1), in case of conformal inflation. It appears because of the exponential stretching of the moduli space and the resulting exponential flattening of scalar potentials upon switching from the Jordan frame to the Einstein frame in this class of models. This result resembles stretching and flattening of inhomogeneities during inflationary expansion. It has a simple interpretation in terms of velocity versus rapidity near the Kähler cone in the moduli space, similar to the light cone of special theory of relativity. This effect makes inflation possible even in the models with very steep potentials. We describe conformal and superconformal versions of this cosmological attractor mechanism.

  9. PHAT Stellar Cluster Survey. II. Andromeda Project Cluster Catalog

    CERN Document Server

    Johnson, L Clifton; Dalcanton, Julianne J; Wallace, Matthew L; Simpson, Robert J; Lintott, Chris J; Kapadia, Amit; Skillman, Evan D; Caldwell, Nelson; Fouesneau, Morgan; Weisz, Daniel R; Williams, Benjamin F; Beerman, Lori C; Gouliermis, Dimitrios A; Sarajedini, Ata

    2015-01-01

    We construct a stellar cluster catalog for the Panchromatic Hubble Andromeda Treasury (PHAT) survey using image classifications collected from the Andromeda Project citizen science website. We identify 2,753 clusters and 2,270 background galaxies within ~0.5 deg$^2$ of PHAT imaging searched, or ~400 kpc$^2$ in deprojected area at the distance of the Andromeda galaxy (M31). These identifications result from 1.82 million classifications of ~20,000 individual images (totaling ~7 gigapixels) by tens of thousands of volunteers. We show that our crowd-sourced approach, which collects >80 classifications per image, provides a robust, repeatable method of cluster identification. The high spatial resolution Hubble Space Telescope images resolve individual stars in each cluster and are instrumental in the factor of ~6 increase in the number of clusters known within the survey footprint. We measure integrated photometry in six filter passbands, ranging from the near-UV to the near-IR. PHAT clusters span a range of ~8 ma...

  10. Seminal Quality Prediction Using Clustering-Based Decision Forests

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-08-01

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

  11. Survey and Analysis of University Clustering

    Directory of Open Access Journals (Sweden)

    Srinatha Karur

    2013-07-01

    Full Text Available This paper gives on Clustering of Universities in the world with respect to their country policies OR local polices OR continent level polices with sub aims. So clustering method can generally apply when objective is specifically mentioned. For general objectives clusters are available in the form of logical or physical groups without networks. In this paper we emphasis on only University Clusters directly or University Clusters with some other clusters. Data miming methods are used for useful for Sampling Analysis and Clustering of Universities and Colleges with respect to local clusters [1] pp 1.

  12. A Clustering Graph Generator

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-10-26

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

  13. Active Learning in Large Classes

    DEFF Research Database (Denmark)

    Gørtz, Inge Li

    2011-01-01

    teaching large classes (more than 50 students), and describe how we successfully have in a second semester course in the Bachelor of Engineering (BEng) and Bachelor of Science Engineering (BSc Eng) program at the Technical University of Denmark (DTU). Approximately 200 students is attending...... the lectures in the course. The main idea is to use inductive, case-based learning, with many small exercises/ discussions during the lectures. We describe a framework for the lectures, that most lectures in the class were based on. The framework contains the conceive, design, and implement stage from the CDIO...

  14. A library of function classes

    International Nuclear Information System (INIS)

    We have written a library of function classes in C++, which is distributed as part of the CLHEP foundation class libraries for High Energy Physics. The main goals of the library are to provide objects having all the mathematical behavior of functions, and to provide a mechanism for parameterizing these functions. Our functions support all the normal function operations such as addition, subtraction, multiplication, division, composition, et. cetera. The library allows programmers to compose complicated one-or multi-dimensional functions with great economy and natural semantics

  15. On uniqueness of characteristic classes

    DEFF Research Database (Denmark)

    Feliu, Elisenda

    2011-01-01

    We give an axiomatic characterization of maps from algebraic K-theory. The results apply to a large class of maps from algebraic K-theory to any suitable cohomology theory or to algebraic K-theory. In particular, we obtain comparison theorems for the Chern character and Chern classes and for the...... Adams operations and ¿-operations on higher algebraic K-theory. We show that the Adams operations and ¿-operations defined by Grayson agree with the ones defined by Gillet and Soulé....

  16. Moran sets and Moran classes

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The purpose of this survey is to present Moran sets and Moran classes which generalize the classical selfsimilar sets from the following points: ( i ) The placements of the basic sets at each step of the constructions can be arbitrary; (ii) the contraction ratios may be different at each step; and (iii) the lower limit of the contraction ratios permits zero. In this discussion we will present geometrical properties and results of dimensions of these sets and classes,and discuss conformal Moran sets and random Moran sets as well.``

  17. Enzymatic Browning: a practical class

    Directory of Open Access Journals (Sweden)

    Maria Teresa Pedrosa Silva Clerici

    2014-10-01

    Full Text Available This paper presents a practical class about the enzymes polyphenol oxidases, which have been shown to be responsible for the enzymatic browning of fruits and vegetables. Vegetables samples were submitted to enzymatic inactivation process with chemical reagents, as well as by bleaching methods of applying heat by conventional oven and microwave oven. Process efficiency was assessed qualitatively by both observing the guaiacol peroxidase activity and after the storage period under refrigeration or freezing. The practical results obtained in this class allow exploring multidisciplinary knowledge in food science, with practical applications in everyday life.

  18. 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.

  19. Magnetic Bubbles in Galaxy Clusters

    OpenAIRE

    McNamara, B. R.

    2003-01-01

    I discuss Chandra X-ray Observatory measurements of cavities in galaxy clusters and their implications for heating the intracluster gas. The emerging paradigm for cooling flows has important implications for understanding self-regulated galaxy formation.

  20. Clustering of financial time series

    Science.gov (United States)

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

    2013-05-01

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