WorldWideScience

Sample records for hierarchical clustering results

  1. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

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

  2. Statistical Significance for Hierarchical Clustering

    Science.gov (United States)

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

    2017-01-01

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

  3. Cluster Based Hierarchical Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, Md. Golam; Kabir, M. Hasnat; Rahim, Muhammad Sajjadur; Ullah, Shaikh Enayet

    2012-01-01

    The efficient use of energy source in a sensor node is most desirable criteria for prolong the life time of wireless sensor network. In this paper, we propose a two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP). We introduce a new concept called head-set, consists of one active cluster head and some other associate cluster heads within a cluster. The head-set members are responsible for control and management of the network. Results show that t...

  4. Hierarchical clustering using correlation metric and spatial continuity constraint

    Science.gov (United States)

    Stork, Christopher L.; Brewer, Luke N.

    2012-10-02

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

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

    Science.gov (United States)

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

    2013-10-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

  7. Constructing storyboards based on hierarchical clustering analysis

    Science.gov (United States)

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

    2005-07-01

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

  8. Star Cluster Structure from Hierarchical Star Formation

    Science.gov (United States)

    Grudic, Michael; Hopkins, Philip; Murray, Norman; Lamberts, Astrid; Guszejnov, David; Schmitz, Denise; Boylan-Kolchin, Michael

    2018-01-01

    Young massive star clusters (YMCs) spanning 104-108 M⊙ in mass generally have similar radial surface density profiles, with an outer power-law index typically between -2 and -3. This similarity suggests that they are shaped by scale-free physics at formation. Recent multi-physics MHD simulations of YMC formation have also produced populations of YMCs with this type of surface density profile, allowing us to narrow down the physics necessary to form a YMC with properties as observed. We show that the shallow density profiles of YMCs are a natural result of phase-space mixing that occurs as they assemble from the clumpy, hierarchically-clustered configuration imprinted by the star formation process. We develop physical intuition for this process via analytic arguments and collisionless N-body experiments, elucidating the connection between star formation physics and star cluster structure. This has implications for the early-time structure and evolution of proto-globular clusters, and prospects for simulating their formation in the FIRE cosmological zoom-in simulations.

  9. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

    Science.gov (United States)

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

    2015-01-01

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

  10. Hierarchical Control for Multiple DC Microgrids Clusters

    DEFF Research Database (Denmark)

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

    2014-01-01

    This paper presents a distributed hierarchical control framework to ensure reliable operation of dc Microgrid (MG) clusters. In this hierarchy, primary control is used to regulate the common bus voltage inside each MG locally. An adaptive droop method is proposed for this level which determines...

  11. Robust Pseudo-Hierarchical Support Vector Clustering

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  12. Hierarchical video summarization based on context clustering

    Science.gov (United States)

    Tseng, Belle L.; Smith, John R.

    2003-11-01

    A personalized video summary is dynamically generated in our video personalization and summarization system based on user preference and usage environment. The three-tier personalization system adopts the server-middleware-client architecture in order to maintain, select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. In this paper, the metadata includes visual semantic annotations and automatic speech transcriptions. Our personalization and summarization engine in the middleware selects the optimal set of desired video segments by matching shot annotations and sentence transcripts with user preferences. Besides finding the desired contents, the objective is to present a coherent summary. There are diverse methods for creating summaries, and we focus on the challenges of generating a hierarchical video summary based on context information. In our summarization algorithm, three inputs are used to generate the hierarchical video summary output. These inputs are (1) MPEG-7 metadata descriptions of the contents in the server, (2) user preference and usage environment declarations from the user client, and (3) context information including MPEG-7 controlled term list and classification scheme. In a video sequence, descriptions and relevance scores are assigned to each shot. Based on these shot descriptions, context clustering is performed to collect consecutively similar shots to correspond to hierarchical scene representations. The context clustering is based on the available context information, and may be derived from domain knowledge or rules engines. Finally, the selection of structured video segments to generate the hierarchical summary efficiently balances between scene representation and shot selection.

  13. Technique for fast and efficient hierarchical clustering

    Science.gov (United States)

    Stork, Christopher

    2013-10-08

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

  14. A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis

    Directory of Open Access Journals (Sweden)

    Shaoning Li

    2017-01-01

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

  15. Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering

    Science.gov (United States)

    Zheng, Ming; Sun, Ying; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

    2012-01-01

    Background Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. Method An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. Results Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved. PMID:23173043

  16. A Hierarchical Clustering Methodology for the Estimation of Toxicity

    Science.gov (United States)

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

  17. Inferring hierarchical clustering structures by deterministic annealing

    International Nuclear Information System (INIS)

    Hofmann, T.; Buhmann, J.M.

    1996-01-01

    The unsupervised detection of hierarchical structures is a major topic in unsupervised learning and one of the key questions in data analysis and representation. We propose a novel algorithm for the problem of learning decision trees for data clustering and related problems. In contrast to many other methods based on successive tree growing and pruning, we propose an objective function for tree evaluation and we derive a non-greedy technique for tree growing. Applying the principles of maximum entropy and minimum cross entropy, a deterministic annealing algorithm is derived in a meanfield approximation. This technique allows us to canonically superimpose tree structures and to fit parameters to averaged or open-quote fuzzified close-quote trees

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

    CERN Document Server

    Materne, J

    1978-01-01

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

  19. Clinical fracture risk evaluated by hierarchical agglomerative clustering

    DEFF Research Database (Denmark)

    Kruse, C; Eiken, P; Vestergaard, P

    2017-01-01

    reimbursement, primary healthcare sector use and comorbidity of female subjects were combined. Standardized variable means, Euclidean distances and Ward's D2 method of hierarchical agglomerative clustering (HAC), were used to form the clustering object. K number of clusters was selected with the lowest cluster...

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

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

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

  1. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    Science.gov (United States)

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  2. Hierarchical modeling of cluster size in wildlife surveys

    Science.gov (United States)

    Royle, J. Andrew

    2008-01-01

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

  3. Assessment of surface water quality using hierarchical cluster analysis

    Directory of Open Access Journals (Sweden)

    Dheeraj Kumar Dabgerwal

    2016-02-01

    Full Text Available This study was carried out to assess the physicochemical quality river Varuna inVaranasi,India. Water samples were collected from 10 sites during January-June 2015. Pearson correlation analysis was used to assess the direction and strength of relationship between physicochemical parameters. Hierarchical Cluster analysis was also performed to determine the sources of pollution in the river Varuna. The result showed quite high value of DO, Nitrate, BOD, COD and Total Alkalinity, above the BIS permissible limit. The results of correlation analysis identified key water parameters as pH, electrical conductivity, total alkalinity and nitrate, which influence the concentration of other water parameters. Cluster analysis identified three major clusters of sampling sites out of total 10 sites, according to the similarity in water quality. This study illustrated the usefulness of correlation and cluster analysis for getting better information about the river water quality.International Journal of Environment Vol. 5 (1 2016,  pp: 32-44

  4. Hierarchical clusters of phytoplankton variables in dammed water bodies

    Science.gov (United States)

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

    2017-06-01

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

  5. The identification of credit card encoders by hierarchical cluster analysis of the jitters of magnetic stripes.

    Science.gov (United States)

    Leung, S C; Fung, W K; Wong, K H

    1999-01-01

    The relative bit density variation graphs of 207 specimen credit cards processed by 12 encoding machines were examined first visually, and then classified by means of hierarchical cluster analysis. Twenty-nine credit cards being treated as 'questioned' samples were tested by way of cluster analysis against 'controls' derived from known encoders. It was found that hierarchical cluster analysis provided a high accuracy of identification with all 29 'questioned' samples classified correctly. On the other hand, although visual comparison of jitter graphs was less discriminating, it was nevertheless capable of giving a reasonably accurate result.

  6. Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

    Science.gov (United States)

    Zhong, Qiaoyong; Yang, Chen; Großerüschkamp, Frederik; Kallenbach-Thieltges, Angela; Serocka, Peter; Gerwert, Klaus; Mosig, Axel

    2013-11-20

    Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward's clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

  7. Preliminary results from the hierarchical glitch pipeline

    International Nuclear Information System (INIS)

    Mukherjee, Soma

    2007-01-01

    This paper reports on the preliminary results obtained from the hierarchical glitch classification pipeline on LIGO data. The pipeline that has been under construction for the past year is now complete and end-to-end tested. It is ready to generate analysis results on a daily basis. The details of the pipeline, the classification algorithms employed and the results obtained with one days analysis on the gravitational wave and several auxiliary and environmental channels from all three LIGO detectors are discussed

  8. Unsupervised active learning based on hierarchical graph-theoretic clustering.

    Science.gov (United States)

    Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

    2009-10-01

    Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

  9. Hierarchical clustering of HPV genotype patterns in the ASCUS-LSIL triage study

    Science.gov (United States)

    Wentzensen, Nicolas; Wilson, Lauren E.; Wheeler, Cosette M.; Carreon, Joseph D.; Gravitt, Patti E.; Schiffman, Mark; Castle, Philip E.

    2010-01-01

    Anogenital cancers are associated with about 13 carcinogenic HPV types in a broader group that cause cervical intraepithelial neoplasia (CIN). Multiple concurrent cervical HPV infections are common which complicate the attribution of HPV types to different grades of CIN. Here we report the analysis of HPV genotype patterns in the ASCUS-LSIL triage study using unsupervised hierarchical clustering. Women who underwent colposcopy at baseline (n = 2780) were grouped into 20 disease categories based on histology and cytology. Disease groups and HPV genotypes were clustered using complete linkage. Risk of 2-year cumulative CIN3+, viral load, colposcopic impression, and age were compared between disease groups and major clusters. Hierarchical clustering yielded four major disease clusters: Cluster 1 included all CIN3 histology with abnormal cytology; Cluster 2 included CIN3 histology with normal cytology and combinations with either CIN2 or high-grade squamous intraepithelial lesion (HSIL) cytology; Cluster 3 included older women with normal or low grade histology/cytology and low viral load; Cluster 4 included younger women with low grade histology/cytology, multiple infections, and the highest viral load. Three major groups of HPV genotypes were identified: Group 1 included only HPV16; Group 2 included nine carcinogenic types plus non-carcinogenic HPV53 and HPV66; and Group 3 included non-carcinogenic types plus carcinogenic HPV33 and HPV45. Clustering results suggested that colposcopy missed a prevalent precancer in many women with no biopsy/normal histology and HSIL. This result was confirmed by an elevated 2-year risk of CIN3+ in these groups. Our novel approach to study multiple genotype infections in cervical disease using unsupervised hierarchical clustering can address complex genotype distributions on a population level. PMID:20959485

  10. Communication Base Station Log Analysis Based on Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Zhang Shao-Hua

    2017-01-01

    Full Text Available Communication base stations generate massive data every day, these base station logs play an important value in mining of the business circles. This paper use data mining technology and hierarchical clustering algorithm to group the scope of business circle for the base station by recording the data of these base stations.Through analyzing the data of different business circle based on feature extraction and comparing different business circle category characteristics, which can choose a suitable area for operators of commercial marketing.

  11. Multi-documents summarization based on clustering of learning object using hierarchical clustering

    Science.gov (United States)

    Mustamiin, M.; Budi, I.; Santoso, H. B.

    2018-03-01

    The Open Educational Resources (OER) is a portal of teaching, learning and research resources that is available in public domain and freely accessible. Learning contents or Learning Objects (LO) are granular and can be reused for constructing new learning materials. LO ontology-based searching techniques can be used to search for LO in the Indonesia OER. In this research, LO from search results are used as an ingredient to create new learning materials according to the topic searched by users. Summarizing-based grouping of LO use Hierarchical Agglomerative Clustering (HAC) with the dependency context to the user’s query which has an average value F-Measure of 0.487, while summarizing by K-Means F-Measure only has an average value of 0.336.

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

    Science.gov (United States)

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

    2016-06-01

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

  13. The Hierarchical Clustering of Tax Burden in the EU27

    Directory of Open Access Journals (Sweden)

    Simkova Nikola

    2015-09-01

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

  14. Which, When, and How: Hierarchical Clustering with Human–Machine Cooperation

    Directory of Open Access Journals (Sweden)

    Huanyang Zheng

    2016-12-01

    Full Text Available Human–Machine Cooperations (HMCs can balance the advantages and disadvantages of human computation (accurate but costly and machine computation (cheap but inaccurate. This paper studies HMCs in agglomerative hierarchical clusterings, where the machine can ask the human some questions. The human will return the answers to the machine, and the machine will use these answers to correct errors in its current clustering results. We are interested in the machine’s strategy on handling the question operations, in terms of three problems: (1 Which question should the machine ask? (2 When should the machine ask the question (early or late? (3 How does the machine adjust the clustering result, if the machine’s mistake is found by the human? Based on the insights of these problems, an efficient algorithm is proposed with five implementation variations. Experiments on image clusterings show that the proposed algorithm can improve the clustering accuracy with few question operations.

  15. The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

    Science.gov (United States)

    Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

    2018-04-01

    Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

  16. Analysis of precipitation data in Bangladesh through hierarchical clustering and multidimensional scaling

    Science.gov (United States)

    Rahman, Md. Habibur; Matin, M. A.; Salma, Umma

    2017-12-01

    The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  18. An Energy Efficient Cooperative Hierarchical MIMO Clustering Scheme for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2011-12-01

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

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

    NARCIS (Netherlands)

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

    2011-01-01

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

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

    Science.gov (United States)

    Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

    2017-09-01

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

  1. Merging K-means with hierarchical clustering for identifying general-shaped groups.

    Science.gov (United States)

    Peterson, Anna D; Ghosh, Arka P; Maitra, Ranjan

    2018-01-01

    Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and K -means clustering are two approaches but have different strengths and weaknesses. For instance, hierarchical clustering identifies groups in a tree-like structure but suffers from computational complexity in large datasets while K -means clustering is efficient but designed to identify homogeneous spherically-shaped clusters. We present a hybrid non-parametric clustering approach that amalgamates the two methods to identify general-shaped clusters and that can be applied to larger datasets. Specifically, we first partition the dataset into spherical groups using K -means. We next merge these groups using hierarchical methods with a data-driven distance measure as a stopping criterion. Our proposal has the potential to reveal groups with general shapes and structure in a dataset. We demonstrate good performance on several simulated and real datasets.

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

    Directory of Open Access Journals (Sweden)

    Yuliya Vladimirovna Dubrovskaya

    2016-10-01

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

  3. The Hierarchical Spectral Merger Algorithm: A New Time Series Clustering Procedure

    KAUST Repository

    Euá n, Carolina; Ombao, Hernando; Ortega, Joaquí n

    2018-01-01

    We present a new method for time series clustering which we call the Hierarchical Spectral Merger (HSM) method. This procedure is based on the spectral theory of time series and identifies series that share similar oscillations or waveforms

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

    Science.gov (United States)

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

    2017-07-01

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

  5. Radar Emission Sources Identification Based on Hierarchical Agglomerative Clustering for Large Data Sets

    Directory of Open Access Journals (Sweden)

    Janusz Dudczyk

    2016-01-01

    Full Text Available More advanced recognition methods, which may recognize particular copies of radars of the same type, are called identification. The identification process of radar devices is a more specialized task which requires methods based on the analysis of distinctive features. These features are distinguished from the signals coming from the identified devices. Such a process is called Specific Emitter Identification (SEI. The identification of radar emission sources with the use of classic techniques based on the statistical analysis of basic measurable parameters of a signal such as Radio Frequency, Amplitude, Pulse Width, or Pulse Repetition Interval is not sufficient for SEI problems. This paper presents the method of hierarchical data clustering which is used in the process of radar identification. The Hierarchical Agglomerative Clustering Algorithm (HACA based on Generalized Agglomerative Scheme (GAS implemented and used in the research method is parameterized; therefore, it is possible to compare the results. The results of clustering are presented in dendrograms in this paper. The received results of grouping and identification based on HACA are compared with other SEI methods in order to assess the degree of their usefulness and effectiveness for systems of ESM/ELINT class.

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

    Science.gov (United States)

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

    2017-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Refat Aljumily

    2015-09-01

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

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

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2015-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Susan Worner

    2013-09-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Grasha, K.; Calzetti, D. [Astronomy Department, University of Massachusetts, Amherst, MA 01003 (United States); Adamo, A.; Messa, M. [Dept. of Astronomy, The Oskar Klein Centre, Stockholm University, Stockholm (Sweden); Kim, H. [Gemini Observatory, La Serena (Chile); Elmegreen, B. G. [IBM Research Division, T.J. Watson Research Center, Yorktown Hts., NY (United States); Gouliermis, D. A. [Zentrum für Astronomie der Universität Heidelberg, Institut für Theoretische Astrophysik, Albert-Ueberle-Str. 2, D-69120 Heidelberg (Germany); Dale, D. A. [Dept. of Physics and Astronomy, University of Wyoming, Laramie, WY (United States); Fumagalli, M. [Institute for Computational Cosmology and Centre for Extragalactic Astronomy, Durham University, Durham (United Kingdom); Grebel, E. K.; Shabani, F. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstr. 12-14, D-69120 Heidelberg (Germany); Johnson, K. E. [Dept. of Astronomy, University of Virginia, Charlottesville, VA (United States); Kahre, L. [Dept. of Astronomy, New Mexico State University, Las Cruces, NM (United States); Kennicutt, R. C. [Institute of Astronomy, University of Cambridge, Cambridge (United Kingdom); Pellerin, A. [Dept. of Physics and Astronomy, State University of New York at Geneseo, Geneseo NY (United States); Ryon, J. E.; Ubeda, L. [Space Telescope Science Institute, Baltimore, MD (United States); Smith, L. J. [European Space Agency/Space Telescope Science Institute, Baltimore, MD (United States); Thilker, D., E-mail: kgrasha@astro.umass.edu [Dept. of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD (United States)

    2017-05-10

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

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

    Science.gov (United States)

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

    2017-05-01

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  13. Evaluation of Hierarchical Clustering Algorithms for Document Datasets

    National Research Council Canada - National Science Library

    Zhao, Ying; Karypis, George

    2002-01-01

    Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters...

  14. Hierarchical clustering into groups of human brain regions according to elemental composition

    International Nuclear Information System (INIS)

    Stedman, J.D.; Spyrou, N.M.

    1998-01-01

    Thirteen brain regions were dissected from both hemispheres of fifteen 'normal' ageing subjects (8 females, 7 males) of mean age 79±7 years. Elemental compositions were determined by simultaneous application of particle induced X-ray emission (PIXE) and Rutherford backscattering (RBS) analyses using a 2 MeV, 4 nA proton beam scanned over 4 mm 2 of the sample surface. Elemental concentrations were found to be dependent upon the brain region and hemisphere studied. Hierarchical cluster analysis was applied to group the brain regions according to the sample concentrations of eight elements. The resulting dendrogram is presented and its clusters related to the sample compositions of grey and white matter. (author)

  15. Hierarchical Control for Multiple DC-Microgrids Clusters

    DEFF Research Database (Denmark)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Bilal Jan

    2017-01-01

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

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

    Science.gov (United States)

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

    2014-04-29

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

  18. A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

    Science.gov (United States)

    Takuma, Takehisa; Masugi, Masao

    2009-03-01

    This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

  19. Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination.

    Science.gov (United States)

    Yau, Christopher; Holmes, Chris

    2011-07-01

    We propose a hierarchical Bayesian nonparametric mixture model for clustering when some of the covariates are assumed to be of varying relevance to the clustering problem. This can be thought of as an issue in variable selection for unsupervised learning. We demonstrate that by defining a hierarchical population based nonparametric prior on the cluster locations scaled by the inverse covariance matrices of the likelihood we arrive at a 'sparsity prior' representation which admits a conditionally conjugate prior. This allows us to perform full Gibbs sampling to obtain posterior distributions over parameters of interest including an explicit measure of each covariate's relevance and a distribution over the number of potential clusters present in the data. This also allows for individual cluster specific variable selection. We demonstrate improved inference on a number of canonical problems.

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

    Directory of Open Access Journals (Sweden)

    Reilly John J

    2005-06-01

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

  1. Dynamics of the baryonic component in hierarchical clustering universes

    Science.gov (United States)

    Navarro, Julio

    1993-01-01

    I present self-consistent 3-D simulations of the formation of virialized systems containing both gas and dark matter in a flat universe. A fully Lagrangian code based on the Smoothed Particle Hydrodynamics technique and a tree data structure has been used to evolve regions of comoving radius 2-3 Mpc. Tidal effects are included by coarse-sampling the density of the outer regions up to a radius approx. 20 Mpc. Initial conditions are set at high redshift (z greater than 7) using a standard Cold Dark Matter perturbation spectrum and a baryon mass fraction of 10 percent (omega(sub b) = 0.1). Simulations in which the gas evolves either adiabatically or radiates energy at a rate determined locally by its cooling function were performed. This allows us to investigate with the same set of simulations the importance of radiative losses in the formation of galaxies and the equilibrium structure of virialized systems where cooling is very inefficient. In the absence of radiative losses, the simulations can be rescaled to the density and radius typical of galaxy clusters. A summary of the main results is presented.

  2. Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space

    OpenAIRE

    Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

    2008-01-01

    Motivation: UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. Application: We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without ex...

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

    Directory of Open Access Journals (Sweden)

    Górecki J.

    2017-01-01

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

  4. Assessment of genetic divergence in tomato through agglomerative hierarchical clustering and principal component analysis

    International Nuclear Information System (INIS)

    Iqbal, Q.; Saleem, M.Y.; Hameed, A.; Asghar, M.

    2014-01-01

    For the improvement of qualitative and quantitative traits, existence of variability has prime importance in plant breeding. Data on different morphological and reproductive traits of 47 tomato genotypes were analyzed for correlation,agglomerative hierarchical clustering and principal component analysis (PCA) to select genotypes and traits for future breeding program. Correlation analysis revealed significant positive association between yield and yield components like fruit diameter, single fruit weight and number of fruits plant-1. Principal component (PC) analysis depicted first three PCs with Eigen-value higher than 1 contributing 81.72% of total variability for different traits. The PC-I showed positive factor loadings for all the traits except number of fruits plant-1. The contribution of single fruit weight and fruit diameter was highest in PC-1. Cluster analysis grouped all genotypes into five divergent clusters. The genotypes in cluster-II and cluster-V exhibited uniform maturity and higher yield. The D2 statistics confirmed highest distance between cluster- III and cluster-V while maximum similarity was observed in cluster-II and cluster-III. It is therefore suggested that crosses between genotypes of cluster-II and cluster-V with those of cluster-I and cluster-III may exhibit heterosis in F1 for hybrid breeding and for selection of superior genotypes in succeeding generations for cross breeding programme. (author)

  5. Hierarchical clustering analysis of blood plasma lipidomics profiles from mono- and dizygotic twin families

    NARCIS (Netherlands)

    Draisma, H.H.; Reijmers, T.H.; Meulman, J.J.; Greef, J. van der; Hankemeier, T.; Boomsma, D.I.

    2013-01-01

    Twin and family studies are typically used to elucidate the relative contribution of genetic and environmental variation to phenotypic variation. Here, we apply a quantitative genetic method based on hierarchical clustering, to blood plasma lipidomics data obtained in a healthy cohort consisting of

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

    Science.gov (United States)

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

  7. The use of hierarchical clustering for the design of optimized monitoring networks

    Science.gov (United States)

    Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji

    2018-05-01

    Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different

  8. A study of hierarchical clustering of galaxies in an expanding universe

    Science.gov (United States)

    Porter, D. H.

    The nonlinear hierarchical clustering of galaxies in an Einstein-deSitter (Omega = 1), initially white noise mass fluctuations (n = 0) model universe is investigated and shown to be in contradiction with previous results. The model is done in terms of an 11,000-body numerical simulation. The independent statics of 0.72 million particles are used to simulte the boundary conditions. A new method for integrating the Newtonian N-body gravity equations, which has controllable accuracy, incorporates a recursive center of mass reduction, and regularizes two body encounters is used to do the simulation. The coordinate system used here is well suited for the investigation of galaxy clustering, incorporating the independent positions and velocities of an arbitrary number of particles into a logarithmic hierarchy of center of mass nodes. The boundary for the simulation is created by using this hierarchy to map the independent statics of 0.72 million particles into just 4,000 particles. This method for simulating the boundary conditions also has controllable accuracy.

  9. On the Disruption of Star Clusters in a Hierarchical Interstellar Medium

    Science.gov (United States)

    Elmegreen, Bruce G.; Hunter, Deidre A.

    2010-03-01

    The distribution of the number of clusters as a function of mass M and age T suggests that clusters get eroded or dispersed in a regular way over time, such that the cluster number decreases inversely as an approximate power law with T within each fixed interval of M. This power law is inconsistent with standard dispersal mechanisms such as cluster evaporation and cloud collisions. In the conventional interpretation, it requires the unlikely situation where diverse mechanisms stitch together over time in a way that is independent of environment or M. Here, we consider another model in which the large-scale distribution of gas in each star-forming region plays an important role. We note that star clusters form with positional and temporal correlations in giant cloud complexes, and suggest that these complexes dominate the tidal force and collisional influence on a cluster during its first several hundred million years. Because the cloud complex density decreases regularly with position from the cluster birth site, the harassment and collision rates between the cluster and the cloud pieces decrease regularly with age as the cluster drifts. This decrease is typically a power law of the form required to explain the mass-age distribution. We reproduce this distribution for a variety of cases, including rapid disruption, slow erosion, combinations of these two, cluster-cloud collisions, cluster disruption by hierarchical disassembly, and partial cluster disruption. We also consider apparent cluster mass loss by fading below the surface brightness limit of a survey. In all cases, the observed log M-log T diagram can be reproduced under reasonable assumptions.

  10. ON THE DISRUPTION OF STAR CLUSTERS IN A HIERARCHICAL INTERSTELLAR MEDIUM

    International Nuclear Information System (INIS)

    Elmegreen, Bruce G.; Hunter, Deidre A.

    2010-01-01

    The distribution of the number of clusters as a function of mass M and age T suggests that clusters get eroded or dispersed in a regular way over time, such that the cluster number decreases inversely as an approximate power law with T within each fixed interval of M. This power law is inconsistent with standard dispersal mechanisms such as cluster evaporation and cloud collisions. In the conventional interpretation, it requires the unlikely situation where diverse mechanisms stitch together over time in a way that is independent of environment or M. Here, we consider another model in which the large-scale distribution of gas in each star-forming region plays an important role. We note that star clusters form with positional and temporal correlations in giant cloud complexes, and suggest that these complexes dominate the tidal force and collisional influence on a cluster during its first several hundred million years. Because the cloud complex density decreases regularly with position from the cluster birth site, the harassment and collision rates between the cluster and the cloud pieces decrease regularly with age as the cluster drifts. This decrease is typically a power law of the form required to explain the mass-age distribution. We reproduce this distribution for a variety of cases, including rapid disruption, slow erosion, combinations of these two, cluster-cloud collisions, cluster disruption by hierarchical disassembly, and partial cluster disruption. We also consider apparent cluster mass loss by fading below the surface brightness limit of a survey. In all cases, the observed log M-log T diagram can be reproduced under reasonable assumptions.

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

    Directory of Open Access Journals (Sweden)

    Xiaowei Li

    2017-01-01

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

  12. The Hierarchical Spectral Merger Algorithm: A New Time Series Clustering Procedure

    KAUST Repository

    Euán, Carolina

    2018-04-12

    We present a new method for time series clustering which we call the Hierarchical Spectral Merger (HSM) method. This procedure is based on the spectral theory of time series and identifies series that share similar oscillations or waveforms. The extent of similarity between a pair of time series is measured using the total variation distance between their estimated spectral densities. At each step of the algorithm, every time two clusters merge, a new spectral density is estimated using the whole information present in both clusters, which is representative of all the series in the new cluster. The method is implemented in an R package HSMClust. We present two applications of the HSM method, one to data coming from wave-height measurements in oceanography and the other to electroencefalogram (EEG) data.

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

    Science.gov (United States)

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

    2014-09-30

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

  14. Hierarchical Cluster Analysis of Semicircular Canal and Otolith Deficits in Bilateral Vestibulopathy

    Directory of Open Access Journals (Sweden)

    Alexander A. Tarnutzer

    2018-04-01

    Full Text Available BackgroundGait imbalance and oscillopsia are frequent complaints of bilateral vestibular loss (BLV. Video-head-impulse testing (vHIT of all six semicircular canals (SCCs has demonstrated varying involvement of the different canals. Sparing of anterior-canal function has been linked to aminoglycoside-related vestibulopathy and Menière’s disease. We hypothesized that utricular and saccular impairment [assessed by vestibular-evoked myogenic potentials (VEMPs] may be disease-specific also, possibly facilitating the differential diagnosis.MethodsWe searched our vHIT database (n = 3,271 for patients with bilaterally impaired SCC function who also received ocular VEMPs (oVEMPs and cervical VEMPs (cVEMPs and identified 101 patients. oVEMP/cVEMP latencies above the 95th percentile and peak-to-peak amplitudes below the 5th percentile of normal were considered abnormal. Frequency of impairment of vestibular end organs (horizontal/anterior/posterior SCC, utriculus/sacculus was analyzed with hierarchical cluster analysis and correlated with the underlying etiology.ResultsRates of utricular and saccular loss of function were similar (87.1 vs. 78.2%, p = 0.136, Fisher’s exact test. oVEMP abnormalities were found more frequent in aminoglycoside-related bilateral vestibular loss (BVL compared with Menière’s disease (91.7 vs. 54.6%, p = 0.039. Hierarchical cluster analysis indicated distinct patterns of vestibular end-organ impairment, showing that the results for the same end-organs on both sides are more similar than to other end-organs. Relative sparing of anterior-canal function was reflected in late merging with the other end-organs, emphasizing their distinct state. An anatomically corresponding pattern of SCC/otolith hypofunction was present in 60.4% (oVEMPs vs. horizontal SCCs, 34.7% (oVEMPs vs. anterior SCCs, and 48.5% (cVEMPs vs. posterior SCCs of cases. Average (±1 SD number of damaged sensors was 6.8 ± 2.2 out of 10

  15. Application of hierarchical clustering method to classify of space-time rainfall patterns

    Science.gov (United States)

    Yu, Hwa-Lung; Chang, Tu-Je

    2010-05-01

    Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

  16. Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

    Science.gov (United States)

    Hensman, James; Lawrence, Neil D; Rattray, Magnus

    2013-08-20

    Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

  17. Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Grasha, K.; Calzetti, D. [Astronomy Department, University of Massachusetts, Amherst, MA 01003 (United States); Elmegreen, B. G. [IBM Research Division, T.J. Watson Research Center, Yorktown Heights, NY (United States); Adamo, A.; Messa, M. [Department of Astronomy, The Oskar Klein Centre, Stockholm University, Stockholm (Sweden); Aloisi, A.; Bright, S. N.; Lee, J. C.; Ryon, J. E.; Ubeda, L. [Space Telescope Science Institute, Baltimore, MD (United States); Cook, D. O. [California Institute of Technology, 1200 East California Boulevard, Pasadena, CA (United States); Dale, D. A. [Department of Physics and Astronomy, University of Wyoming, Laramie, WY (United States); Fumagalli, M. [Institute for Computational Cosmology and Centre for Extragalactic Astronomy, Department of Physics, Durham University, Durham (United Kingdom); Gallagher III, J. S. [Department of Astronomy, University of Wisconsin–Madison, Madison, WI (United States); Gouliermis, D. A. [Zentrum für Astronomie der Universität Heidelberg, Institut für Theoretische Astrophysik, Albert-Ueberle-Str. 2, D-69120 Heidelberg (Germany); Grebel, E. K. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstr. 12-14, D-69120, Heidelberg (Germany); Kahre, L. [Department of Astronomy, New Mexico State University, Las Cruces, NM (United States); Kim, H. [Gemini Observatory, La Serena (Chile); Krumholz, M. R., E-mail: kgrasha@astro.umass.edu [Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611 (Australia)

    2017-06-10

    We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25–0.6 power, and that the maximum size over which star formation is physically correlated ranges from ∼200 pc to ∼1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are close to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.

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

    Directory of Open Access Journals (Sweden)

    Kellermann Walter

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Alexander V. Yarkov

    2008-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Farshad Faezy Razi

    2014-06-01

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

  1. K-means clustering for optimal partitioning and dynamic load balancing of parallel hierarchical N-body simulations

    International Nuclear Information System (INIS)

    Marzouk, Youssef M.; Ghoniem, Ahmed F.

    2005-01-01

    A number of complex physical problems can be approached through N-body simulation, from fluid flow at high Reynolds number to gravitational astrophysics and molecular dynamics. In all these applications, direct summation is prohibitively expensive for large N and thus hierarchical methods are employed for fast summation. This work introduces new algorithms, based on k-means clustering, for partitioning parallel hierarchical N-body interactions. We demonstrate that the number of particle-cluster interactions and the order at which they are performed are directly affected by partition geometry. Weighted k-means partitions minimize the sum of clusters' second moments and create well-localized domains, and thus reduce the computational cost of N-body approximations by enabling the use of lower-order approximations and fewer cells. We also introduce compatible techniques for dynamic load balancing, including adaptive scaling of cluster volumes and adaptive redistribution of cluster centroids. We demonstrate the performance of these algorithms by constructing a parallel treecode for vortex particle simulations, based on the serial variable-order Cartesian code developed by Lindsay and Krasny [Journal of Computational Physics 172 (2) (2001) 879-907]. The method is applied to vortex simulations of a transverse jet. Results show outstanding parallel efficiencies even at high concurrencies, with velocity evaluation errors maintained at or below their serial values; on a realistic distribution of 1.2 million vortex particles, we observe a parallel efficiency of 98% on 1024 processors. Excellent load balance is achieved even in the face of several obstacles, such as an irregular, time-evolving particle distribution containing a range of length scales and the continual introduction of new vortex particles throughout the domain. Moreover, results suggest that k-means yields a more efficient partition of the domain than a global oct-tree

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

    Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

    2011-03-01

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

  4. BULGELESS GIANT GALAXIES CHALLENGE OUR PICTURE OF GALAXY FORMATION BY HIERARCHICAL CLUSTERING ,

    International Nuclear Information System (INIS)

    Kormendy, John; Cornell, Mark E.; Drory, Niv; Bender, Ralf

    2010-01-01

    To better understand the prevalence of bulgeless galaxies in the nearby field, we dissect giant Sc-Scd galaxies with Hubble Space Telescope (HST) photometry and Hobby-Eberly Telescope (HET) spectroscopy. We use the HET High Resolution Spectrograph (resolution R ≡ λ/FWHM ≅ 15, 000) to measure stellar velocity dispersions in the nuclear star clusters and (pseudo)bulges of the pure-disk galaxies M 33, M 101, NGC 3338, NGC 3810, NGC 6503, and NGC 6946. The dispersions range from 20 ± 1 km s -1 in the nucleus of M 33 to 78 ± 2 km s -1 in the pseudobulge of NGC 3338. We use HST archive images to measure the brightness profiles of the nuclei and (pseudo)bulges in M 101, NGC 6503, and NGC 6946 and hence to estimate their masses. The results imply small mass-to-light ratios consistent with young stellar populations. These observations lead to two conclusions. (1) Upper limits on the masses of any supermassive black holes are M . ∼ 6 M sun in M 101 and M . ∼ 6 M sun in NGC 6503. (2) We show that the above galaxies contain only tiny pseudobulges that make up ∼ circ > 150 km s -1 , including M 101, NGC 6946, IC 342, and our Galaxy, show no evidence for a classical bulge. Four may contain small classical bulges that contribute 5%-12% of the light of the galaxy. Only four of the 19 giant galaxies are ellipticals or have classical bulges that contribute ∼1/3 of the galaxy light. We conclude that pure-disk galaxies are far from rare. It is hard to understand how bulgeless galaxies could form as the quiescent tail of a distribution of merger histories. Recognition of pseudobulges makes the biggest problem with cold dark matter galaxy formation more acute: How can hierarchical clustering make so many giant, pure-disk galaxies with no evidence for merger-built bulges? Finally, we emphasize that this problem is a strong function of environment: the Virgo cluster is not a puzzle, because more than 2/3 of its stellar mass is in merger remnants.

  5. SDN‐Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra‐Dense Small Cell Networks

    Directory of Open Access Journals (Sweden)

    Guang Yang

    2018-04-01

    Full Text Available Ultra‐dense small cell networks (UD‐SCNs have been identified as a promising scheme for next‐generation wireless networks capable of meeting the ever‐increasing demand for higher transmission rates and better quality of service. However, UD‐SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software‐defined networking (SDN‐based hierarchical agglomerative clustering (SDN‐HAC framework, which leverages SDN to centrally control all sub‐channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non‐cooperative scenarios, respectively.

  6. Dynamical processes in space: Cluster results

    Directory of Open Access Journals (Sweden)

    C. P. Escoubet

    2013-06-01

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

  7. Efficient visible light photocatalytic NO{sub x} removal with cationic Ag clusters-grafted (BiO){sub 2}CO{sub 3} hierarchical superstructures

    Energy Technology Data Exchange (ETDEWEB)

    Feng, Xin [Chongqing Key Laboratory of Catalysis and Functional Organic Molecules, College of Environment and Resources, Engineering Research Center for Waste Oil Recovery Technology and Equipment of Ministry of Education, College of Environment and Resources, Chongqing Technology and Business University, Chongqing 40067 (China); Zhang, Wendong [Department of Scientific Research Management, Chongqing Normal University, Chongqing 401331 (China); Deng, Hua [State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085 (China); Ni, Zilin [Department of Scientific Research Management, Chongqing Normal University, Chongqing 401331 (China); Dong, Fan, E-mail: dfctbu@126.com [Chongqing Key Laboratory of Catalysis and Functional Organic Molecules, College of Environment and Resources, Engineering Research Center for Waste Oil Recovery Technology and Equipment of Ministry of Education, College of Environment and Resources, Chongqing Technology and Business University, Chongqing 40067 (China); Zhang, Yuxin, E-mail: zhangyuxin@cqu.edu.cn [College of Materials Science and Engineering, National Key Laboratory of Fundamental Science of Micro/Nano-Devices and System Technology, Chongqing University, Chongqing 400044 (China)

    2017-01-15

    Graphical abstract: The cationic Ag clusters-grafted (BiO){sub 2}CO{sub 3} hierarchical superstructures exhibits highly enhanced visible light photocatalytic air purification through an interfacial charge transfer process induced by Ag clusters. - Highlights: • Microstructural optimization and surface cluster-grafting were firstly combined. • Cationic Ag clusters were grafted on the surface of (BiO){sub 2}CO{sub 3} superstructures. • The Ag clusters-grafted BHS displayed enhanced visible light photocatalysis. • Direct interfacial charge transfer (IFCT) from BHS to Ag clusters was proposed. • The charge transfer process and the dominant reactive species were revealed. - Abstract: A facile method was developed to graft cationic Ag clusters on (BiO){sub 2}CO{sub 3} hierarchical superstructures (BHS) surface to improve their visible light activity. Significantly, the resultant Ag clusters-grafted BHS displayed a highly enhanced visible light photocatalytic performance for NOx removal due to the direct interfacial charge transfer (IFCT) from BHS to Ag clusters. The chemical and coordination state of the cationic Ag clusters was determined with the extended X-ray absorption fine structure (EXAFS) and a theoretical structure model was proposed for this unique Ag clusters. The charge transfer process and the dominant reactive species (·OH) were revealed on the basis of electron spin resonance (ESR) trapping. A new photocatalysis mechanism of Ag clusters-grafted BHS under visible light involving IFCT process was uncovered. In addition, the cationic Ag clusters-grafted BHS also demonstrated high photochemical and structural stability under repeated photocatalysis runs. The perspective of enhancing photocatalysis through combination of microstructural optimization and IFCT could provide a new avenue for the developing efficient visible light photocatalysts.

  8. 3D NEAREST NEIGHBOUR SEARCH USING A CLUSTERED HIERARCHICAL TREE STRUCTURE

    Directory of Open Access Journals (Sweden)

    A. Suhaibah

    2016-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Guo Junqiao

    2008-09-01

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

  10. Implementation of hierarchical clustering using k-mer sparse matrix to analyze MERS-CoV genetic relationship

    Science.gov (United States)

    Bustamam, A.; Ulul, E. D.; Hura, H. F. A.; Siswantining, T.

    2017-07-01

    Hierarchical clustering is one of effective methods in creating a phylogenetic tree based on the distance matrix between DNA (deoxyribonucleic acid) sequences. One of the well-known methods to calculate the distance matrix is k-mer method. Generally, k-mer is more efficient than some distance matrix calculation techniques. The steps of k-mer method are started from creating k-mer sparse matrix, and followed by creating k-mer singular value vectors. The last step is computing the distance amongst vectors. In this paper, we analyze the sequences of MERS-CoV (Middle East Respiratory Syndrome - Coronavirus) DNA by implementing hierarchical clustering using k-mer sparse matrix in order to perform the phylogenetic analysis. Our results show that the ancestor of our MERS-CoV is coming from Egypt. Moreover, we found that the MERS-CoV infection that occurs in one country may not necessarily come from the same country of origin. This suggests that the process of MERS-CoV mutation might not only be influenced by geographical factor.

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

    Science.gov (United States)

    van der Ham, Joris L

    2016-05-19

    Forensic entomologists can use carrion communities' ecological succession data to estimate the postmortem interval (PMI). Permutation tests of hierarchical cluster analyses of these data provide a conceptual method to estimate part of the PMI, the post-colonization interval (post-CI). This multivariate approach produces a baseline of statistically distinct clusters that reflect changes in the carrion community composition during the decomposition process. Carrion community samples of unknown post-CIs are compared with these baseline clusters to estimate the post-CI. In this short communication, I use data from previously published studies to demonstrate the conceptual feasibility of this multivariate approach. Analyses of these data produce series of significantly distinct clusters, which represent carrion communities during 1- to 20-day periods of the decomposition process. For 33 carrion community samples, collected over an 11-day period, this approach correctly estimated the post-CI within an average range of 3.1 days. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  12. A Negative Selection Algorithm Based on Hierarchical Clustering of Self Set and its Application in Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Wen Chen

    2011-08-01

    Full Text Available A negative selection algorithm based on the hierarchical clustering of self set HC-RNSA is introduced in this paper. Several strategies are applied to improve the algorithm performance. First, the self data set is replaced by the self cluster centers to compare with the detector candidates in each cluster level. As the number of self clusters is much less than the self set size, the detector generation efficiency is improved. Second, during the detector generation process, the detector candidates are restricted to the lower coverage space to reduce detector redundancy. In the article, the problem that the distances between antigens coverage to a constant value in the high dimensional space is analyzed, accordingly the Principle Component Analysis (PCA method is used to reduce the data dimension, and the fractional distance function is employed to enhance the distinctiveness between the self and non-self antigens. The detector generation procedure is terminated when the expected non-self coverage is reached. The theory analysis and experimental results demonstrate that the detection rate of HC-RNSA is higher than that of the traditional negative selection algorithms while the false alarm rate and time cost are reduced.

  13. Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space.

    Science.gov (United States)

    Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

    2008-07-01

    UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request.

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

    Directory of Open Access Journals (Sweden)

    M. Safish Mary

    2012-04-01

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

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

    Science.gov (United States)

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

    2014-11-01

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

  16. Clustering, Hierarchical Organization, and the Topography of Abstract and Concrete Nouns

    Directory of Open Access Journals (Sweden)

    Joshua eTroche

    2014-04-01

    Full Text Available The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are disembodied in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N=365 rated target words (n=400 English nouns across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence. Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

  17. Clustering, hierarchical organization, and the topography of abstract and concrete nouns.

    Science.gov (United States)

    Troche, Joshua; Crutch, Sebastian; Reilly, Jamie

    2014-01-01

    The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are "disembodied" in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N = 365) rated target words (n = 400 English nouns) across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence). Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

  18. Hierarchical Controlled Remote State Preparation by Using a Four-Qubit Cluster State

    Science.gov (United States)

    Ma, Peng-Cheng; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang

    2018-06-01

    We propose a scheme for hierarchical controlled remote preparation of an arbitrary single-qubit state via a four-qubit cluster state as the quantum channel. In this scheme, a sender wishes to help three agents to remotely prepare a quantum state, respectively. The three agents are divided into two grades, that is, an agent is in the upper grade and other two agents are in the lower grade. In this process of remote state preparation, the agent of the upper grade only needs the assistance of any one of the other two agents for recovering the sender's original state, while an agent of the lower grade needs the collaboration of all the other two agents. In other words, the agents of two grades have different authorities to reconstruct sender's original state.

  19. Hierarchical Controlled Remote State Preparation by Using a Four-Qubit Cluster State

    Science.gov (United States)

    Ma, Peng-Cheng; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang

    2018-02-01

    We propose a scheme for hierarchical controlled remote preparation of an arbitrary single-qubit state via a four-qubit cluster state as the quantum channel. In this scheme, a sender wishes to help three agents to remotely prepare a quantum state, respectively. The three agents are divided into two grades, that is, an agent is in the upper grade and other two agents are in the lower grade. In this process of remote state preparation, the agent of the upper grade only needs the assistance of any one of the other two agents for recovering the sender's original state, while an agent of the lower grade needs the collaboration of all the other two agents. In other words, the agents of two grades have different authorities to reconstruct sender's original state.

  20. NOVEL CONTEXT-AWARE CLUSTERING WITH HIERARCHICAL ADDRESSING (CCHA) FOR THE INTERNET OF THINGS (IoT)

    DEFF Research Database (Denmark)

    Mahalle, Parikshit N.; Prasad, Neeli R.; Prasad, Ramjee

    2013-01-01

    As computing technology becomes more tightly coupled into dynamic and mobile world of the Internet of Things (IoT), security mechanism becomes more stringent, less flexible and intrusive. Scalability issue in the IoT makes Identity Management (IdM) of ubiquitous things more challenging. Forming ad......-hoc network, interaction between these nomadic devices to provide seamless service extend the need of new identi-ties to the things, addressing and IdM in the IoT. New identities and identifier format to alleviate the perfor-mance issue is introduced in this paper. This paper pre-sents novel Context......-aware Clustering with Hierarchical Addressing (CCHA) scheme for the things with new identifier format. Simulation results shows that CCHA achieves better performance with less energy expendi-ture, less end-to-end delay and more throughput. Results also show that CCHA significantly reduces the failure probability...

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

    DEFF Research Database (Denmark)

    Mi, Jianli; Lock, Nina; Sun, Ting

    2010-01-01

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

  2. An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

    Science.gov (United States)

    Booma, P M; Prabhakaran, S; Dhanalakshmi, R

    2014-01-01

    Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

  3. A data-driven approach to estimating the number of clusters in hierarchical clustering [version 1; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Antoine E. Zambelli

    2016-12-01

    Full Text Available DNA microarray and gene expression problems often require a researcher to perform clustering on their data in a bid to better understand its structure. In cases where the number of clusters is not known, one can resort to hierarchical clustering methods. However, there currently exist very few automated algorithms for determining the true number of clusters in the data. We propose two new methods (mode and maximum difference for estimating the number of clusters in a hierarchical clustering framework to create a fully automated process with no human intervention. These methods are compared to the established elbow and gap statistic algorithms using simulated datasets and the Biobase Gene ExpressionSet. We also explore a data mixing procedure inspired by cross validation techniques. We find that the overall performance of the maximum difference method is comparable or greater to that of the gap statistic in multi-cluster scenarios, and achieves that performance at a fraction of the computational cost. This method also responds well to our mixing procedure, which opens the door to future research. We conclude that both the mode and maximum difference methods warrant further study related to their mixing and cross-validation potential. We particularly recommend the use of the maximum difference method in multi-cluster scenarios given its accuracy and execution times, and present it as an alternative to existing algorithms.

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2014-11-01

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

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

    Directory of Open Access Journals (Sweden)

    I-Hsuan Lin

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

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

    Science.gov (United States)

    Franke, R.

    2016-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Diane G O Saunders

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

  9. Using Hierarchical Time Series Clustering Algorithm and Wavelet Classifier for Biometric Voice Classification

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2012-01-01

    Full Text Available Voice biometrics has a long history in biosecurity applications such as verification and identification based on characteristics of the human voice. The other application called voice classification which has its important role in grouping unlabelled voice samples, however, has not been widely studied in research. Lately voice classification is found useful in phone monitoring, classifying speakers’ gender, ethnicity and emotion states, and so forth. In this paper, a collection of computational algorithms are proposed to support voice classification; the algorithms are a combination of hierarchical clustering, dynamic time wrap transform, discrete wavelet transform, and decision tree. The proposed algorithms are relatively more transparent and interpretable than the existing ones, though many techniques such as Artificial Neural Networks, Support Vector Machine, and Hidden Markov Model (which inherently function like a black box have been applied for voice verification and voice identification. Two datasets, one that is generated synthetically and the other one empirically collected from past voice recognition experiment, are used to verify and demonstrate the effectiveness of our proposed voice classification algorithm.

  10. ESPRIT-Tree: hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time.

    Science.gov (United States)

    Cai, Yunpeng; Sun, Yijun

    2011-08-01

    Taxonomy-independent analysis plays an essential role in microbial community analysis. Hierarchical clustering is one of the most widely employed approaches to finding operational taxonomic units, the basis for many downstream analyses. Most existing algorithms have quadratic space and computational complexities, and thus can be used only for small or medium-scale problems. We propose a new online learning-based algorithm that simultaneously addresses the space and computational issues of prior work. The basic idea is to partition a sequence space into a set of subspaces using a partition tree constructed using a pseudometric, then recursively refine a clustering structure in these subspaces. The technique relies on new methods for fast closest-pair searching and efficient dynamic insertion and deletion of tree nodes. To avoid exhaustive computation of pairwise distances between clusters, we represent each cluster of sequences as a probabilistic sequence, and define a set of operations to align these probabilistic sequences and compute genetic distances between them. We present analyses of space and computational complexity, and demonstrate the effectiveness of our new algorithm using a human gut microbiota data set with over one million sequences. The new algorithm exhibits a quasilinear time and space complexity comparable to greedy heuristic clustering algorithms, while achieving a similar accuracy to the standard hierarchical clustering algorithm.

  11. Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.

    Science.gov (United States)

    Caesar, Lindsay K; Kvalheim, Olav M; Cech, Nadja B

    2018-08-27

    Mass spectral data sets often contain experimental artefacts, and data filtering prior to statistical analysis is crucial to extract reliable information. This is particularly true in untargeted metabolomics analyses, where the analyte(s) of interest are not known a priori. It is often assumed that chemical interferents (i.e. solvent contaminants such as plasticizers) are consistent across samples, and can be removed by background subtraction from blank injections. On the contrary, it is shown here that chemical contaminants may vary in abundance across each injection, potentially leading to their misidentification as relevant sample components. With this metabolomics study, we demonstrate the effectiveness of hierarchical cluster analysis (HCA) of replicate injections (technical replicates) as a methodology to identify chemical interferents and reduce their contaminating contribution to metabolomics models. Pools of metabolites with varying complexity were prepared from the botanical Angelica keiskei Koidzumi and spiked with known metabolites. Each set of pools was analyzed in triplicate and at multiple concentrations using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). Before filtering, HCA failed to cluster replicates in the data sets. To identify contaminant peaks, we developed a filtering process that evaluated the relative peak area variance of each variable within triplicate injections. These interferent peaks were found across all samples, but did not show consistent peak area from injection to injection, even when evaluating the same chemical sample. This filtering process identified 128 ions that appear to originate from the UPLC-MS system. Data sets collected for a high number of pools with comparatively simple chemical composition were highly influenced by these chemical interferents, as were samples that were analyzed at a low concentration. When chemical interferent masses were removed, technical replicates clustered in

  12. Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

    Science.gov (United States)

    Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

    2017-09-23

    This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

  13. Clustering and Bayesian hierarchical modeling for the definition of informative prior distributions in hydrogeology

    Science.gov (United States)

    Cucchi, K.; Kawa, N.; Hesse, F.; Rubin, Y.

    2017-12-01

    In order to reduce uncertainty in the prediction of subsurface flow and transport processes, practitioners should use all data available. However, classic inverse modeling frameworks typically only make use of information contained in in-situ field measurements to provide estimates of hydrogeological parameters. Such hydrogeological information about an aquifer is difficult and costly to acquire. In this data-scarce context, the transfer of ex-situ information coming from previously investigated sites can be critical for improving predictions by better constraining the estimation procedure. Bayesian inverse modeling provides a coherent framework to represent such ex-situ information by virtue of the prior distribution and combine them with in-situ information from the target site. In this study, we present an innovative data-driven approach for defining such informative priors for hydrogeological parameters at the target site. Our approach consists in two steps, both relying on statistical and machine learning methods. The first step is data selection; it consists in selecting sites similar to the target site. We use clustering methods for selecting similar sites based on observable hydrogeological features. The second step is data assimilation; it consists in assimilating data from the selected similar sites into the informative prior. We use a Bayesian hierarchical model to account for inter-site variability and to allow for the assimilation of multiple types of site-specific data. We present the application and validation of the presented methods on an established database of hydrogeological parameters. Data and methods are implemented in the form of an open-source R-package and therefore facilitate easy use by other practitioners.

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

    Directory of Open Access Journals (Sweden)

    Sergio Briguglio

    2003-01-01

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

  15. Assessment of the quality of water by hierarchical cluster and variance analyses of the Koudiat Medouar Watershed, East Algeria

    Science.gov (United States)

    Tiri, Ammar; Lahbari, Noureddine; Boudoukha, Abderrahmane

    2017-12-01

    The assessment of surface water in Koudiat Medouar watershed is very important especially when it comes to pollution of the dam waters by discharges of wastewater from neighboring towns in Oued Timgad, who poured into the basin of the dam, and agricultural lands located along the Oued Reboa. To this end, the multivariable method was used to evaluate the spatial and temporal variation of the water surface quality of the Koudiat Medouar dam, eastern Algeria. The stiff diagram has identified two main hydrochemical facies. The first facies Mg-HCO3 is reflected in the first sampling station (Oued Reboa) and in the second one (Oued Timgad), while the second facies Mg-SO4 is reflected in the third station (Basin Dam). The results obtained by the analysis of variance show that in the three stations all parameters are significant, except for Na, K and HCO3 in the first station (Oued Reboa) and the EC in the second station (Oued Timgad) and at the end NO3 and pH in the third station (Basin Dam). Q-mode hierarchical cluster analysis showed that two main groups in each sampling station. The chemistry of major ions (Mg, Ca, HCO3 and SO4) within the three stations results from anthropogenic impacts and water-rock interaction sources.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-01-17

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

  17. Peringkasan Tweet Berdasarkan Trending Topic Twitter Dengan Pembobotan TF-IDF dan Single Linkage AngglomerativeHierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Annisa Annisa

    2016-10-01

    Full Text Available Trending topic is a feature provided by twitter that informs something widely discussed by users in a particular time. The form of a trending topic is a hashtag and can be selected by clicking. However, the number of tweets for each trending topics can be very large, so it will be difficult if we want to know all the contents. So, in order to make easy when reading the topic, a small number of tweets can be selected as the main idea of the topic. In this study, we applied the Agglomerative Single Linkage Hierarchical Clustering by calculating the TF-IDF value for each word in advance. We used 100 trending topics, where each topic consists of 50 tweets in Indonesian. For testing, we provided 30 trending topics which consist of 2 until 9 sub-topics. The result is that each trending topics can be summarized into shorter text contains 2 until 9 tweets. We were able to summarize 1 trending topics exactly same as the topic summarized by human expert. However, the rest of topics corresponded partially with human expert.

  18. Hierarchical clustering of Alzheimer and 'normal' brains using elemental concentrations and glucose metabolism determined by PIXE, INAA and PET

    International Nuclear Information System (INIS)

    Cutts, D.A.; Spyrou, N.M.

    2001-01-01

    Brain tissue samples, obtained from the Alzheimer Disease Brain Bank, Institute of Psychiatry, London, were taken from both left and right hemispheres of three regions of the cerebrum, namely the frontal, parietal and occipital lobes for both Alzheimer and 'normal' subjects. Trace element concentrations in the frontal lobe were determined for twenty six Alzheimer (15 male, 11 female) and twenty six 'normal' (8 male, 18 female) brain tissue samples. In the parietal lobe ten Alzheimer (2 male, 8 female) and ten 'normal' (8 male, 2 female) samples were taken along with ten Alzheimer (4 male, 6 female) and ten 'normal' (6 male, 4 female) from the occipital lobe. For the frontal lobe trace element concentrations were determined using proton induced X-ray emission (PIXE) analysis while in parietal and occipital regions instrumental neutron activation analysis (INAA) was used. Additionally eighteen Alzheimer (9 male, 9 female) and eighteen age matched 'normal' (8 male, 10 female) living subjects were examined using positron emission tomography (PET) in order to determine regional cerebral metabolic rates of glucose (rCMRGlu). The rCMRGlu of 36 regions of the brain was investigated including frontal, occipital and parietal lobes as in the trace element study. Hierarchical cluster analysis was applied to the trace element and glucose metabolism data to discover which variables in the resulting dendrograms displayed the most significant separation between Alzheimer and 'normal' subjects. (author)

  19. Hierarchical modularization of biochemical pathways using fuzzy-c means clustering.

    Science.gov (United States)

    de Luis Balaguer, Maria A; Williams, Cranos M

    2014-08-01

    Biological systems that are representative of regulatory, metabolic, or signaling pathways can be highly complex. Mathematical models that describe such systems inherit this complexity. As a result, these models can often fail to provide a path toward the intuitive comprehension of these systems. More coarse information that allows a perceptive insight of the system is sometimes needed in combination with the model to understand control hierarchies or lower level functional relationships. In this paper, we present a method to identify relationships between components of dynamic models of biochemical pathways that reside in different functional groups. We find primary relationships and secondary relationships. The secondary relationships reveal connections that are present in the system, which current techniques that only identify primary relationships are unable to show. We also identify how relationships between components dynamically change over time. This results in a method that provides the hierarchy of the relationships among components, which can help us to understand the low level functional structure of the system and to elucidate potential hierarchical control. As a proof of concept, we apply the algorithm to the epidermal growth factor signal transduction pathway, and to the C3 photosynthesis pathway. We identify primary relationships among components that are in agreement with previous computational decomposition studies, and identify secondary relationships that uncover connections among components that current computational approaches were unable to reveal.

  20. An Algorithm for Inspecting Self Check-in Airline Luggage Based on Hierarchical Clustering and Cube-fitting

    Directory of Open Access Journals (Sweden)

    Gao Qingji

    2014-04-01

    Full Text Available Airport passengers are required to put only one baggage each time in the check-in self-service so that the baggage can be detected and identified successfully. In order to automatically get the number of baggage that had been put on the conveyor belt, dual laser rangefinders are used to scan the outer contour of luggage in this paper. The algorithm based on hierarchical clustering and cube-fitting is proposed to inspect the number and dimension of airline luggage. Firstly, the point cloud is projected to vertical direction. By the analysis of one-dimensional clustering, the number and height of luggage will be quickly computed. Secondly, the method of nearest hierarchical clustering is applied to divide the point cloud if the above cannot be distinguished. It can preferably solve the difficult issue like crossing or overlapping pieces of baggage. Finally, the point cloud is projected to the horizontal plane. By rotating point cloud based on the centre, its minimum bounding rectangle (MBR is obtained. The length and width of luggage are got form MBR. Many experiments in different cases have been done to verify the effectiveness of the algorithm.

  1. Self-similar hierarchical energetics in the ICM of massive galaxy clusters

    Science.gov (United States)

    Miniati, Francesco; Beresnyak, Andrey

    Massive galaxy clusters (GC) are filled with a hot, turbulent and magnetised intra-cluster medium (ICM). They are still forming under the action of gravitational instability, which drives supersonic mass accretion flows. These partially dissipate into heat through a complex network of large scale shocks, and partly excite giant turbulent eddies and cascade. Turbulence dissipation not only contributes to heating of the ICM but also amplifies magnetic energy by way of dynamo action. The pattern of gravitational energy turning into kinetic, thermal, turbulent and magnetic is a fundamental feature of GC hydrodynamics but quantitative modelling has remained a challenge. In this contribution we present results from a recent high resolution, fully cosmological numerical simulation of a massive Coma-like galaxy cluster in which the time dependent turbulent motions of the ICM are resolved (Miniati 2014) and their statistical properties are quantified for the first time (Miniati 2015, Beresnyak & Miniati 2015). We combine these results with independent state-of-the art numerical simulations of MHD turbulence (Beresnyak 2012), which shows that in the nonlinear regime of turbulent dynamo (for magnetic Prandtl numbers>~ 1) the growth rate of the magnetic energy corresponds to a fraction CE ~= 4 - 5 × 10-2 of the turbulent dissipation rate. We thus determine without adjustable parameters the thermal, turbulent and magnetic history of giant GC (Miniati & Beresnyak 2015). We find that the energy components of the ICM are ordered according to a permanent hierarchy, in which the sonic Mach number at the turbulent injection scale is of order unity, the beta of the plasma of order forty and the ratio of turbulent injection scale to Alfvén scale is of order one hundred. These dimensionless numbers remain virtually unaltered throughout the cluster's history, despite evolution of each individual component and the drive towards equipartition of the turbulent dynamo, thus revealing a new

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

    International Nuclear Information System (INIS)

    Ellefsen, Karl J.; Smith, David B.

    2016-01-01

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

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

    African Journals Online (AJOL)

    We show that the use of non-hierarchical analysis allows us to interpret the reasoning of students solving different mathematical problems using Algebra, and to separate them into different groups, that can be recognised and characterised by common traits in their answers, without any prior knowledge on the part of the ...

  4. Hierarchical clustering of gene expression patterns in the Eomes + lineage of excitatory neurons during early neocortical development

    Directory of Open Access Journals (Sweden)

    Cameron David A

    2012-08-01

    Full Text Available Abstract Background Cortical neurons display dynamic patterns of gene expression during the coincident processes of differentiation and migration through the developing cerebrum. To identify genes selectively expressed by the Eomes + (Tbr2 lineage of excitatory cortical neurons, GFP-expressing cells from Tg(Eomes::eGFP Gsat embryos were isolated to > 99% purity and profiled. Results We report the identification, validation and spatial grouping of genes selectively expressed within the Eomes + cortical excitatory neuron lineage during early cortical development. In these neurons 475 genes were expressed ≥ 3-fold, and 534 genes ≤ 3-fold, compared to the reference population of neuronal precursors. Of the up-regulated genes, 328 were represented at the Genepaint in situ hybridization database and 317 (97% were validated as having spatial expression patterns consistent with the lineage of differentiating excitatory neurons. A novel approach for quantifying in situ hybridization patterns (QISP across the cerebral wall was developed that allowed the hierarchical clustering of genes into putative co-regulated groups. Forty four candidate genes were identified that show spatial expression with Intermediate Precursor Cells, 49 candidate genes show spatial expression with Multipolar Neurons, while the remaining 224 genes achieved peak expression in the developing cortical plate. Conclusions This analysis of differentiating excitatory neurons revealed the expression patterns of 37 transcription factors, many chemotropic signaling molecules (including the Semaphorin, Netrin and Slit signaling pathways, and unexpected evidence for non-canonical neurotransmitter signaling and changes in mechanisms of glucose metabolism. Over half of the 317 identified genes are associated with neuronal disease making these findings a valuable resource for studies of neurological development and disease.

  5. Chemical Fingerprint and Quantitative Analysis for the Quality Evaluation of Platycladi cacumen by Ultra-performance Liquid Chromatography Coupled with Hierarchical Cluster Analysis.

    Science.gov (United States)

    Shan, Mingqiu; Li, Sam Fong Yau; Yu, Sheng; Qian, Yan; Guo, Shuchen; Zhang, Li; Ding, Anwei

    2018-01-01

    Platycladi cacumen (dried twigs and leaves of Platycladus orientalis (L.) Franco) is a frequently utilized Chinese medicinal herb. To evaluate the quality of the phytomedcine, an ultra-performance liquid chromatographic method with diode array detection was established for chemical fingerprinting and quantitative analysis. In this study, 27 batches of P. cacumen from different regions were collected for analysis. A chemical fingerprint with 20 common peaks was obtained using Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2004A). Among these 20 components, seven flavonoids (myricitrin, isoquercitrin, quercitrin, afzelin, cupressuflavone, amentoflavone and hinokiflavone) were identified and determined simultaneously. In the method validation, the seven analytes showed good regressions (R ≥ 0.9995) within linear ranges and good recoveries from 96.4% to 103.3%. Furthermore, with the contents of these seven flavonoids, hierarchical clustering analysis was applied to distinguish the 27 batches into five groups. The chemometric results showed that these groups were almost consistent with geographical positions and climatic conditions of the production regions. Integrating fingerprint analysis, simultaneous determination and hierarchical clustering analysis, the established method is rapid, sensitive, accurate and readily applicable, and also provides a significant foundation for quality control of P. cacumen efficiently. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

    Science.gov (United States)

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

    2018-03-01

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

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

    African Journals Online (AJOL)

    Apple

    Keywords: algebraic thinking; cluster analysis; mathematics education; quantitative analysis. Introduction. Extensive ..... C1, C2 and C3 represent the three centroids of the three clusters formed. .... 6ALd. All these strategies are algebraic and 'high- ... 1995), of the didactical aspects related to teaching .... Brazil, 18-23 July.

  8. Result diversification based on query-specific cluster ranking

    NARCIS (Netherlands)

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

    2011-01-01

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

  9. Result Diversification Based on Query-Specific Cluster Ranking

    NARCIS (Netherlands)

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

    2011-01-01

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

  10. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    Energy Technology Data Exchange (ETDEWEB)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L., E-mail: prii.ramos@gmail.com, E-mail: camunita@ipen.br, E-mail: alapolli@ipen.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)

    2017-07-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  11. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    International Nuclear Information System (INIS)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L.

    2017-01-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  12. Genome-wide decoding of hierarchical modular structure of transcriptional regulation by cis-element and expression clustering.

    Science.gov (United States)

    Leyfer, Dmitriy; Weng, Zhiping

    2005-09-01

    A holistic approach to the study of cellular processes is identifying both gene-expression changes and regulatory elements promoting such changes. Cellular regulatory processes can be viewed as transcriptional modules (TMs), groups of coexpressed genes regulated by groups of transcription factors (TFs). We set out to devise a method that would identify TMs while avoiding arbitrary thresholds on TM sizes and number. Assuming that gene expression is determined by TFs that bind to the gene's promoter, clustering of genes based on TF binding sites (cis-elements) should create gene groups similar to those obtained by gene expression clustering. Intersections between the expression and cis-element-based gene clusters reveal TMs. Statistical significance assigned to each TM allows identification of regulatory units of any size. Our method correctly identifies the number and sizes of TMs on simulated datasets. We demonstrate that yeast experimental TMs are biologically relevant by comparing them with MIPS and GO categories. Our modules are in statistically significant agreement with TMs from other research groups. This work suggests that there is no preferential division of biological processes into regulatory units; each degree of partitioning exhibits a slice of biological network revealing hierarchical modular organization of transcriptional regulation.

  13. An Analysis of Turkey's PISA 2015 Results Using Two-Level Hierarchical Linear Modelling

    Science.gov (United States)

    Atas, Dogu; Karadag, Özge

    2017-01-01

    In the field of education, most of the data collected are multi-level structured. Cities, city based schools, school based classes and finally students in the classrooms constitute a hierarchical structure. Hierarchical linear models give more accurate results compared to standard models when the data set has a structure going far as individuals,…

  14. Enhancement of Adaptive Cluster Hierarchical Routing Protocol using Distance and Energy for Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Nawar, N.M.; Soliman, S.E.; Kelash, H.M.; Ayad, N.M.

    2014-01-01

    The application of wireless networking is widely used in nuclear applications. This includes reactor control and fire dedication system. This paper is devoted to the application of this concept in the intrusion system of the Radioisotope Production Facility (RPF) of the Egyptian Atomic Energy Authority. This includes the tracking, monitoring and control components of this system. The design and implementation of wireless sensor networks has become a hot area of research due to the extensive use of sensor networks to enable applications that connect the physical world to the virtual world [1-2]. The original LEACH is named a communication protocol (clustering-based); the extended LEACH’s stochastic cluster head selection algorithm by a deterministic component. Depending on the network configuration an increase of network lifetime can be accomplished [3]. The proposed routing mechanisms after enhancement divide the nodes into clusters. A cluster head performs its task which is considerably more energy-intensive than the rest of the nodes inside sensor network. So, nodes rotate tasks at different rounds between a cluster head and other sensors throughout the lifetime of the network to balance the energy dissipation [4-5].The performance improvement when using routing protocol after enhancement of the algorithm which takes into consideration the distance and the remaining energy for choosing the cluster head by obtains from the advertise message. Network Simulator (Ns2 simulator) is used to prove that LEACH after enhancement performs better than the original LEACH protocol in terms of Average Energy, Network Life Time, Delay, Throughput and Overhead.

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

    Czech Academy of Sciences Publication Activity Database

    Górecki, J.; Hofert, M.; Holeňa, Martin

    2017-01-01

    Roč. 5, č. 1 (2017), s. 75-87 ISSN 2300-2298 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : structure determination * agglomerative clustering * Kendall’s tau * Archimedean copula Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

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

    Science.gov (United States)

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

    2016-03-01

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

  17. Experimental results of some cluster tests in NSRR

    International Nuclear Information System (INIS)

    Kobayashi, Shinsho; Ohnishi, Nobuaki; Yoshimura, Tomio; Lussie, W.G.

    1978-01-01

    The NSRR programme is in progress in JAERI using a pulsed reactor to evaluate the behavior of reactor fuels under reactivity accident conditions. This report describes briefly the experimental results and preliminary analysis of two cluster tests. In the cluster configuration of five fuel rods, the power distribution in outer fuel rods are not symmetric due to neutron absorption in central fuel rod. The cladding temperature on the exterior boundaries of the cluster is higher than that in interior. Good agreement was obtained between the calculated and measured cladding temperature histories. In the 3.8$ excess reactivity test, cluster averaged energy deposition of 237 cal/g.UO 2 , cladding melting and deformation were limited to the portions of the fuel rods that were on the exterior boundaries of the cluster. (auth.)

  18. Hierarchical and Complex System Entropy Clustering Analysis Based Validation for Traditional Chinese Medicine Syndrome Patterns of Chronic Atrophic Gastritis.

    Science.gov (United States)

    Zhang, Yin; Liu, Yue; Li, Yannan; Zhao, Xia; Zhuo, Lin; Zhou, Ajian; Zhang, Li; Su, Zeqi; Chen, Cen; Du, Shiyu; Liu, Daming; Ding, Xia

    2018-03-22

    Chronic atrophic gastritis (CAG) is the precancerous stage of gastric carcinoma. Traditional Chinese Medicine (TCM) has been widely used in treating CAG. This study aimed to reveal core pathogenesis of CAG by validating the TCM syndrome patterns and provide evidence for optimization of treatment strategies. This is a cross-sectional study conducted in 4 hospitals in China. Hierarchical clustering analysis (HCA) and complex system entropy clustering analysis (CSECA) were performed, respectively, to achieve syndrome pattern validation. Based on HCA, 15 common factors were assigned to 6 syndrome patterns: liver depression and spleen deficiency and blood stasis in the stomach collateral, internal harassment of phlegm-heat and blood stasis in the stomach collateral, phlegm-turbidity internal obstruction, spleen yang deficiency, internal harassment of phlegm-heat and spleen deficiency, and spleen qi deficiency. By CSECA, 22 common factors were assigned to 7 syndrome patterns: qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency. Combination of qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency may play a crucial role in CAG pathogenesis. In accord with this, treatment strategies by TCM herbal prescriptions should be targeted to regulating qi, activating blood, resolving turbidity, clearing heat, removing toxin, nourishing yin, and warming yang. Further explorations are needed to verify and expand the current conclusions.

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

    Directory of Open Access Journals (Sweden)

    Татьяна Борисовна Шатовская

    2015-03-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-01-15

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

  1. HIERARCHICAL FRAGMENTATION AND JET-LIKE OUTFLOWS IN IRDC G28.34+0.06: A GROWING MASSIVE PROTOSTAR CLUSTER

    International Nuclear Information System (INIS)

    Wang Ke; Wu Yuefang; Zhang Huawei; Zhang Qizhou

    2011-01-01

    We present Submillimeter Array (SMA) λ = 0.88 mm observations of an infrared dark cloud G28.34+0.06. Located in the quiescent southern part of the G28.34 cloud, the region of interest is a massive (>10 3 M sun ) molecular clump P1 with a luminosity of ∼10 3 L sun , where our previous SMA observations at 1.3 mm have revealed a string of five dust cores of 22-64 M sun along the 1 pc IR-dark filament. The cores are well aligned at a position angle (P.A.) of 48 deg. and regularly spaced at an average projected separation of 0.16 pc. The new high-resolution, high-sensitivity 0.88 mm image further resolves the five cores into 10 compact condensations of 1.4-10.6 M sun , with sizes of a few thousand AU. The spatial structure at clump (∼1 pc) and core (∼0.1 pc) scales indicates a hierarchical fragmentation. While the clump fragmentation is consistent with a cylindrical collapse, the observed fragment masses are much larger than the expected thermal Jeans masses. All the cores are driving CO (3-2) outflows up to 38 km s -1 , the majority of which are bipolar, jet-like outflows. The moderate luminosity of the P1 clump sets a limit on the mass of protostars of 3-7 M sun . Because of the large reservoir of dense molecular gas in the immediate medium and ongoing accretion as evident by the jet-like outflows, we speculate that P1 will grow and eventually form a massive star cluster. This study provides a first glimpse of massive, clustered star formation that currently undergoes through an intermediate-mass stage.

  2. A Clustering Routing Protocol for Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Jinke Huang

    2016-01-01

    Full Text Available The dynamic topology of a mobile ad hoc network poses a real challenge in the design of hierarchical routing protocol, which combines proactive with reactive routing protocols and takes advantages of both. And as an essential technique of hierarchical routing protocol, clustering of nodes provides an efficient method of establishing a hierarchical structure in mobile ad hoc networks. In this paper, we designed a novel clustering algorithm and a corresponding hierarchical routing protocol for large-scale mobile ad hoc networks. Each cluster is composed of a cluster head, several cluster gateway nodes, several cluster guest nodes, and other cluster members. The proposed routing protocol uses proactive protocol between nodes within individual clusters and reactive protocol between clusters. Simulation results show that the proposed clustering algorithm and hierarchical routing protocol provide superior performance with several advantages over existing clustering algorithm and routing protocol, respectively.

  3. The Auroral Field-aligned Acceleration - Cluster Results

    Science.gov (United States)

    Vaivads, A.; Cluster Auroral Team

    The four Cluster satellites cross the auroral field lines at altitudes well above most of acceleration region. Thus, the orbit is appropriate for studies of the generator side of this region. We consider the energy transport towards the acceleration region and different mechanisms for generating the potential drop. Using data from Cluster we can also for the first time study the dynamics of the generator on a minute scale. We present data from a few auroral field crossings where Cluster are in conjunction with DMSP satellites. We use electric and magnetic field data to estimate electrostatic po- tential along the satellite orbit, Poynting flux as well as the presence of plasma waves. These we can compare with data from particle and wave instruments on Cluster and on low latitude satellites to try to make a consistent picture of the acceleration region formation in these cases. Preliminary results show close agreement both between in- tegrated potential values at Cluster and electron peak energies at DMSP as well as close agreement between the integrated Poynting flux values at Cluster and the elec- tron energy flux at DMSP. At the end we draw a parallels between auroral electron acceleration and electron acceleration at the magnetopause.

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

    Directory of Open Access Journals (Sweden)

    Omholt Stig W

    2011-06-01

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

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

    Science.gov (United States)

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

    2011-06-01

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

  6. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

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

    Lifescience Database Archive (English)

    Full Text Available List Contact us Gclust Server Clustering results Data detail Data name Clustering results DOI 10.18908/lsdba...se Update History of This Database Site Policy | Contact Us Clustering results - Gclust Server | LSDB Archive ...

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

    Science.gov (United States)

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

    2017-09-01

    The hydrodistilled essential oil obtained from the dried leaves of Myrtus communis, collected in Yemen, was analysed by GC-MS. Forty-one compounds were identified, representing 96.3% of the total oil. The major constituents of essential oil were oxygenated monoterpenoids (87.1%), linalool (29.1%), 1,8-cineole (18.4%), α-terpineol (10.8%), geraniol (7.3%) and linalyl acetate (7.4%). The essential oil was assessed for its antimicrobial activity using a disc diffusion assay and resulted in moderate to potent antibacterial and antifungal activities targeting mainly Bacillus subtilis, Staphylococcus aureus and Candida albicans. The oil moderately reduced the diphenylpicrylhydrazyl radical (IC 50  = 4.2 μL/mL or 4.1 mg/mL). In vitro cytotoxicity evaluation against HT29 (human colonic adenocarcinoma cells) showed that the essential oil exhibited a moderate antitumor effect with IC 50 of 110 ± 4 μg/mL. Hierarchical cluster analysis of M. communis has been carried out based on the chemical compositions of 99 samples reported in the literature, including Yemeni sample.

  9. A rapid ATR-FTIR spectroscopic method for detection of sibutramine adulteration in tea and coffee based on hierarchical cluster and principal component analyses.

    Science.gov (United States)

    Cebi, Nur; Yilmaz, Mustafa Tahsin; Sagdic, Osman

    2017-08-15

    Sibutramine may be illicitly included in herbal slimming foods and supplements marketed as "100% natural" to enhance weight loss. Considering public health and legal regulations, there is an urgent need for effective, rapid and reliable techniques to detect sibutramine in dietetic herbal foods, teas and dietary supplements. This research comprehensively explored, for the first time, detection of sibutramine in green tea, green coffee and mixed herbal tea using ATR-FTIR spectroscopic technique combined with chemometrics. Hierarchical cluster analysis and PCA principle component analysis techniques were employed in spectral range (2746-2656cm -1 ) for classification and discrimination through Euclidian distance and Ward's algorithm. Unadulterated and adulterated samples were classified and discriminated with respect to their sibutramine contents with perfect accuracy without any false prediction. The results suggest that existence of the active substance could be successfully determined at the levels in the range of 0.375-12mg in totally 1.75g of green tea, green coffee and mixed herbal tea by using FTIR-ATR technique combined with chemometrics. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    DEFF Research Database (Denmark)

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

    2001-01-01

    The Whisper instrument yields two data sets: (i) the electron density determined via the relaxation sounder, and (ii) the spectrum of natural plasma emissions in the frequency band 2-80 kHz. Both data sets allow for the three-dimensional exploration of the magnetosphere by the Cluster mission...... the drift velocity of density structures. Wave observations are also of crucial interest for studying small-scale structures, as demonstrated in an example in the fore-shock region. Early results from the Whisper instrument are very encouraging, and demonstrate that the four-point Cluster measurements...... largely overcomes the limited telemetry allocation. The natural emissions are usually related to the plasma frequency, as identified by the sounder, and the combination of an active sounding operation and a passive survey operation provides a time resolution for the total density determination of 2.2 s...

  11. Bulgarian clusters under development: Political framework and results

    Directory of Open Access Journals (Sweden)

    Bankova Yovka

    2011-01-01

    Full Text Available The idea of clusters is not new but nowadays clusters are in a highlight again. Through cluster policies the countries aim at raising their national competitiveness. The paper deals with two objectives - discussion and evaluation of the strategic framework for clusters in Bulgaria and an analysis of the state of Bulgarian clusters. The paper presents briefly general issues concerning the national competitiveness and clusters as being one of the possible instruments to achieve a sustainable competitiveness. The practice of the policy in the EU in the field of clusters is the basis for conclusions about the role of the governments. The second part deals with the strategic framework for the cluster initiatives in Bulgaria and with a selection of indicators about the SMEs and clusters in the country. On this basis a conclusion about the development stage of Bulgarian clusters is derived.

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

    DEFF Research Database (Denmark)

    Bartlett, J.G.; Cardoso, J.-F.; Castex, G.

    2013-01-01

    of a fraction of these missing baryons between pairs of galaxy clusters. Methods. Cluster pairs are good candidates for searching for the hotter and denser phase of the intergalactic medium (which is more easily observed through the SZ effect). Using an X-ray catalogue of clusters and the Planck data, we...

  13. A new application of hierarchical cluster analysis to investigate organic peaks in bulk mass spectra obtained with an Aerodyne Aerosol Mass Spectrometer

    Science.gov (United States)

    Middlebrook, A. M.; Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M. L.; Bertman, S. B.

    2006-12-01

    We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel Ronald H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

  14. Hierarchical ordering with partial pairwise hierarchical relationships on the macaque brain data sets.

    Directory of Open Access Journals (Sweden)

    Woosang Lim

    Full Text Available Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical areas. In this paper, we present a new method that discovers hierarchical structures of macaque brain networks by using partial information of pairwise hierarchical relationships. Our method uses a graph-based manifold learning to exploit inherent relationship, and computes pseudo distances of hierarchical levels for every pair of cortical areas. Then, we compute hierarchy levels of all cortical areas by minimizing the sum of squared hierarchical distance errors with the hierarchical information of few cortical areas. We evaluate our method on the macaque brain data sets whose true hierarchical levels are known as the FV91 model. The experimental results show that hierarchy levels computed by our method are similar to the FV91 model, and its errors are much smaller than the errors of hierarchical clustering approaches.

  15. "Analyzing the Longitudinal K-12 Grading Histories of Entire Cohorts of Students: Grades, Data Driven Decision Making, Dropping out and Hierarchical Cluster Analysis"

    Directory of Open Access Journals (Sweden)

    Alex J. Bowers

    2010-05-01

    Full Text Available School personnel currently lack an effective method to pattern and visually interpret disaggregated achievement data collected on students as a means to help inform decision making. This study, through the examination of longitudinal K-12 teacher assigned grading histories for entire cohorts of students from a school district (n=188, demonstrates a novel application of hierarchical cluster analysis and pattern visualization in which all data points collected on every student in a cohort can be patterned, visualized and interpreted to aid in data driven decision making by teachers and administrators. Additionally, as a proof-of-concept study, overall schooling outcomes, such as student dropout or taking a college entrance exam, are identified from the data patterns and compared to past methods of dropout identification as one example of the usefulness of the method. Hierarchical cluster analysis correctly identified over 80% of the students who dropped out using the entire student grade history patterns from either K-12 or K-8.

  16. Ultrathin mesoporous Co_3O_4 nanosheets-constructed hierarchical clusters as high rate capability and long life anode materials for lithium-ion batteries

    International Nuclear Information System (INIS)

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

    2017-01-01

    Graphical abstract: Ultrathin mesoporous Co_3O_4 nanosheets-constructed hierarchical clusters (UMCN-HCs) have been successfully synthesized via a facile hydrothermal method followed by a subsequent thermolysis treatment. When tested as anode materials for LIBs, UMCN-HCs achieve high reversible capacity, good long cycling life, and rate capability. - Highlights: • UMCN-HCs show high capacity, excellent stability, and good rate capability. • UMCN-HCs retain a capacity of 1067 mAh g"−"1 after 100 cycles at 100 mA g"−"1. • UMCN-HCs deliver a capacity of 507 mAh g"−"1 after 500 cycles at 2 A g"−"1. - Abstract: Herein, Ultrathin mesoporous Co_3O_4 nanosheets-constructed hierarchical clusters (UMCN-HCs) have been successfully synthesized via a facile hydrothermal method followed by a subsequent thermolysis treatment at 600 °C in air. The products consist of cluster-like Co_3O_4 microarchitectures, which are assembled by numerous ultrathin mesoporous Co_3O_4 nanosheets. When tested as anode materials for lithium-ion batteries, UMCN-HCs deliver a high reversible capacity of 1067 mAh g"−"1 at a current density of 100 mA g"−"1 after 100 cycles. Even at 2 A g"−"1, a stable capacity as high as 507 mAh g"−"1 can be achieved after 500 cycles. The high reversible capacity, excellent cycling stability, and good rate capability of UMCN-HCs may be attributed to their mesoporous sheet-like nanostructure. The sheet-layered structure of UMCN-HCs may buffer the volume change during the lithiation-delithiation process, and the mesoporous characteristic make lithium-ion transfer more easily at the interface between the active electrode and the electrolyte.

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

    Science.gov (United States)

    2015-01-01

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

  18. First results from the Cluster wideband plasma wave investigation

    Directory of Open Access Journals (Sweden)

    D. A. Gurnett

    2001-09-01

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

  19. First results from the Cluster wideband plasma wave investigation

    Directory of Open Access Journals (Sweden)

    D. A. Gurnett

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

  20. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

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

  1. AN UPDATED CATALOG OF M33 CLUSTERS AND CANDIDATES: UBVRI PHOTOMETRY AND SOME STATISTICAL RESULTS

    International Nuclear Information System (INIS)

    Ma Jun

    2012-01-01

    We present UBVRI photometry for 392 star clusters and candidates in the field of M33, which are selected from the most recent star cluster catalog. In this catalog, the authors listed star clusters' parameters such as cluster positions, magnitudes, colors in the UBVRIJHK s filters, and so on. However, a large fraction of objects in this catalog do not have previously published photometry. Photometry is performed using archival images from the Local Group Galaxies Survey, which covers 0.8 deg 2 along the major axis of M33. Detailed comparisons show that, in general, our photometry is consistent with previous measurements. Positions (right ascension and declination) for some clusters are corrected here. Combined with previous literature, ours constitute a large sample of M33 star clusters. Based on this cluster sample, we present some statistical results: none of the youngest M33 clusters (∼10 7 yr) have masses approaching 10 5 M ☉ ; roughly half the star clusters are consistent with the 10 4 -10 5 M ☉ mass models; the continuous distribution of star clusters along the model line indicates that M33 star clusters have been formed continuously from the epoch of the first star cluster formation until recent times; and there are ∼50 star clusters which are overlapped with the Galactic globular clusters on the color-color diagram, and these clusters are old globular cluster candidates in M33.

  2. On hierarchical solutions to the BBGKY hierarchy

    Science.gov (United States)

    Hamilton, A. J. S.

    1988-01-01

    It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.

  3. CBHRP: A Cluster Based Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, M. G.; Kabir, M. Hasnat; Rahim, M. Sajjadur; Ullah, Sk. Enayet

    2012-01-01

    A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to collect information from target field. On rotation basis, a head-set member receives data from the neighbor nodes and transmits the aggregated results to the distance base station. This protocol ...

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

    Science.gov (United States)

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

    2014-12-01

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

  5. Assessment of Heavy Metal Pollution in Macrophytes, Water and Sediment of a Tropical Wetland System Using Hierarchical Cluster Analysis Technique

    OpenAIRE

    , N. Kumar J.I.; , M. Das; , R. Mukherji; , R.N. Kumar

    2011-01-01

    Heavy metal pollution in aquatic ecosystems is becoming a global phenomenon because these metals are indestructible and most of them have toxic effects on living organisms. Most of the fresh water bodies all over the world are getting contaminated thus declining their suitability. Therefore, monitoring and assessment of such freshwater systems has become an environmental concern. This study aims to elucidate the useful role of the cluster analysis to assess the relationship and interdependenc...

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

    Directory of Open Access Journals (Sweden)

    Pierre Lucena

    2010-04-01

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

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

    OpenAIRE

    L. Billingham; S. J. Schwartz; D. G. Sibeck

    2008-01-01

    We use Cluster magnetic field, thermal ion, and energetic particle observations upstream of the Earth's bow shock to investigate the occurrence patterns of foreshock cavities. Such cavities are thought to form when bundles of magnetic field connect to the quasi-parallel bow shock. Shock-processed suprathermal ions can then stream along the field, back against the flow of the solar wind. These suprathermals enhance the pressure on shock-connected field lines causing them to expand into th...

  8. Clustering Dycom

    KAUST Repository

    Minku, Leandro L.

    2017-10-06

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

  9. Improving the distinguishable cluster results: spin-component scaling

    Science.gov (United States)

    Kats, Daniel

    2018-06-01

    The spin-component scaling is employed in the energy evaluation to improve the distinguishable cluster approach. SCS-DCSD reaction energies reproduce reference values with a root-mean-squared deviation well below 1 kcal/mol, the interaction energies are three to five times more accurate than DCSD, and molecular systems with a large amount of static electron correlation are still described reasonably well. SCS-DCSD represents a pragmatic approach to achieve chemical accuracy with a simple method without triples, which can also be applied to multi-configurational molecular systems.

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

    Directory of Open Access Journals (Sweden)

    L. Billingham

    2008-11-01

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

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

    Directory of Open Access Journals (Sweden)

    L. Billingham

    2008-11-01

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

  12. Hydrothermal synthesis and photoluminescent properties of hierarchical GdPO4·H2O:Ln3+ (Ln3+ = Eu3+, Ce3+, Tb3+) flower-like clusters

    Science.gov (United States)

    Amurisana, Bao.; Zhiqiang, Song.; Haschaolu, O.; Yi, Chen; Tegus, O.

    2018-02-01

    3D hierarchical GdPO4·H2O:Ln3+ (Ln3+ = Eu3+, Ce3+, Tb3+) flower clusters were successfully prepared on glass slide substrate by a simple, economical hydrothermal process with the assistance of disodium ethylenediaminetetraacetic acid (Na2H2L, where L4- = (CH2COO)2N(CH2)2N(CH2COO)24-). In this process, Na2H2L was used as both a chelating agent and a structure-director. The hierarchical flower clusters have an average diameter of 7-12 μm and are composed of well-aligned microrods. The influence of the molar ratio of Na2H2L/Gd3+ and reaction time on the morphology was systematically studied. A possible crystal growth and formation mechanism of hierarchical flower clusters is proposed based on the evolution of morphology as a function of reaction time. The self-assembled GdPO4·H2O:Ln3+ superstructures exhibit strong orange-red (Eu3+, 5D0 → 7F1), green (Tb3+, 5D4 → 7F5) and near ultraviolet emissions (Ce3+, 5d → 7F5/2) under ultraviolet excitation, respectively. This study may provide a new channel for building hierarchically superstructued oxide micro/nanomaterials with optical and new properties.

  13. Clustering of resting state networks.

    Directory of Open Access Journals (Sweden)

    Megan H Lee

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

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

    International Nuclear Information System (INIS)

    Weratschnig, J.M.

    2009-01-01

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

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

    OpenAIRE

    Wang, Yunli; Pan, Youlian

    2014-01-01

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

  16. Anti-inflammatory and anti-angiogenic activities in vitro of eight diterpenes from Daphne genkwa based on hierarchical cluster and principal component analysis.

    Science.gov (United States)

    Wang, Ling; Lan, Xin-Yi; Ji, Jun; Zhang, Chun-Feng; Li, Fei; Wang, Chong-Zhi; Yuan, Chun-Su

    2018-06-01

    Rheumatoid arthritis (RA) is one of the most prevalent chronic inflammatory and angiogenic diseases. The aim of this study was to evaluate the anti-inflammatory and anti-angiogenic activities in vitro of eight diterpenoids isolated from Daphne genkwa. LC-MS was used to identify diterpenes isolated from D. genkwa. The anti-inflammatory and anti-angiogenic activities of eight diterpenoids were evaluated on LPS-induced macrophage RAW264.7 cells and TNF-α-stimulated human umbilical vein endothelial cells (HUVECs) using hierarchical cluster analysis (HCA) and principal component analysis (PCA). The eight diterpenes isolated from D. genkwa were identified as yuanhuaphnin, isoyuanhuacine, 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl, yuanhuagine, isoyuanhuadine, yuanhuadine, yuanhuaoate C and yuanhuacine. All the eight diterpenes significantly down-regulated the excessive secretion of TNF-α, IL-6, IL-1β and NO in LPS-induced RAW264.7 macrophages. However, only 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl markedly reduced production of VEGF, MMP-3, ICAM and VCAM in TNF-α-stimulated HUVECs. HCA obtained 4 clusters, containing 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl, isoyuanhuacine, isoyuanhuadine and five other compounds. PCA showed that the ranking of diterpenes sorted by efficacy from highest to lowest was 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl, yuanhuaphnin, isoyuanhuacine, yuanhuacine, yuanhuaoate C, yuanhuagine, isoyuanhuadine, yuanhuadine. In conclusion, eight diterpenes isolated from D. genkwa showed different levels of activity in LPS-induced RAW264.7 cells and TNF-α-stimulated HUVECs. The comprehensive evaluation of activity by HCA and PCA indicated that of the eight diterpenes, 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl was the best, and can be developed as a new drug for RA therapy.

  17. Simultaneous determination of 19 flavonoids in commercial trollflowers by using high-performance liquid chromatography and classification of samples by hierarchical clustering analysis.

    Science.gov (United States)

    Song, Zhiling; Hashi, Yuki; Sun, Hongyang; Liang, Yi; Lan, Yuexiang; Wang, Hong; Chen, Shizhong

    2013-12-01

    The flowers of Trollius species, named Jin Lianhua in Chinese, are widely used traditional Chinese herbs with vital biological activity that has been used for several decades in China to treat upper respiratory infections, pharyngitis, tonsillitis, and bronchitis. We developed a rapid and reliable method for simultaneous quantitative analysis of 19 flavonoids in trollflowers by using high-performance liquid chromatography (HPLC). Chromatography was performed on Inertsil ODS-3 C18 column, with gradient elution methanol-acetonitrile-water with 0.02% (v/v) formic acid. Content determination was used to evaluate the quality of commercial trollflowers from different regions in China, while three Trollius species (Trollius chinensis Bunge, Trollius ledebouri Reichb, Trollius buddae Schipcz) were explicitly distinguished by using hierarchical clustering analysis. The linearity, precision, accuracy, limit of detection, and limit of quantification were validated for the quantification method, which proved sensitive, accurate and reproducible indicating that the proposed approach was applicable for the routine analysis and quality control of trollflowers. © 2013.

  18. Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis

    Science.gov (United States)

    Arráez Román, David; Gómez Caravaca, Ana María; Zarrouk, Mokhtar

    2018-01-01

    The olive plant has been extensively studied for its nutritional value, whereas its leaves have been specifically recognized as a processing by-product. Leaves are considered by-products of olive farming, representing a significant material arriving to the olive mill. They have been considered for centuries as an important herbal remedy in Mediterranean countries. Their beneficial properties are generally attributed to the presence of a range of phytochemicals such as secoiridoids, triterpenes, lignans, and flavonoids. With the aim to study the impact of geographical location on the phenolic compounds, Olea europaea leaves were handpicked from the Tunisian cultivar “Chemlali” from nine regions in the north, center, and south of Tunisia. The ground leaves were then extracted with methanol : water 80% (v/v) and analyzed by using high-performance liquid chromatography coupled to electrospray time of flight and ion trap mass spectrometry analyzers. A total of 38 compounds could be identified. Their contents showed significant variation among samples from different regions. Hierarchical cluster analysis was applied to highlight similarities in the phytochemical composition observed between the samples of different regions. PMID:29725553

  19. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Kuczyńska, Donata, E-mail: donatakuczynska@gmail.com [Faculty of Materials Science and Engineering, Warsaw University of Technology, Warsaw (Poland); Kwaśniak, Piotr [Faculty of Materials Science and Engineering, Warsaw University of Technology, Warsaw (Poland); Marczak, Jan [Military University of Technology, Institute of Optoelectronics, Warsaw (Poland); Bonarski, Jan [Institute of Metallurgy and Materials Science, Polish Academy of Sciences, Cracow (Poland); Smolik, Jerzy [Institute for Sustainable Technology–National Research Institute, Radom (Poland); Garbacz, Halina [Faculty of Materials Science and Engineering, Warsaw University of Technology, Warsaw (Poland)

    2016-12-30

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

  1. 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...

  2. A new approach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure.

    Science.gov (United States)

    Balzer, Laura B; Zheng, Wenjing; van der Laan, Mark J; Petersen, Maya L

    2018-01-01

    We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and population effects of interventions with proven individual-level efficacy. In these settings, individual-level outcomes are correlated due to shared cluster-level factors, including the exposure, as well as social or biological interactions between individuals. To flexibly and efficiently estimate the effect of a cluster-level exposure, we present two targeted maximum likelihood estimators (TMLEs). The first TMLE is developed under a non-parametric causal model, which allows for arbitrary interactions between individuals within a cluster. These interactions include direct transmission of the outcome (i.e. contagion) and influence of one individual's covariates on another's outcome (i.e. covariate interference). The second TMLE is developed under a causal sub-model assuming the cluster-level and individual-specific covariates are sufficient to control for confounding. Simulations compare the alternative estimators and illustrate the potential gains from pairing individual-level risk factors and outcomes during estimation, while avoiding unwarranted assumptions. Our results suggest that estimation under the sub-model can result in bias and misleading inference in an observational setting. Incorporating working assumptions during estimation is more robust than assuming they hold in the underlying causal model. We illustrate our approach with an application to HIV prevention and treatment.

  3. Explaining DAMPE results by dark matter with hierarchical lepton-specific Yukawa interactions

    Science.gov (United States)

    Liu, Guoli; Wang, Fei; Wang, Wenyu; Yang, Jin-Min

    2018-02-01

    We propose to interpret the DAMPE electron excess at 1.5 TeV through scalar or Dirac fermion dark matter (DM) annihilation with doubly charged scalar mediators that have lepton-specific Yukawa couplings. The hierarchy of such lepton-specific Yukawa couplings is generated through the Froggatt-Nielsen mechanism, so that the dark matter annihilation products can be dominantly electrons. Stringent constraints from LEP2 on intermediate vector boson production can be evaded in our scenarios. In the case of scalar DM, we discuss one scenario with DM annihilating directly to leptons and another scenario with DM annihilating to scalar mediators followed by their decays. We also discuss the Breit-Wigner resonant enhancement and the Sommerfeld enhancement in the case where the s-wave annihilation process is small or helicity-suppressed. With both types of enhancement, constraints on the parameters can be relaxed and new ways for model building can be opened in explaining the DAMPE results. Supported by National Natural Science Foundation of China (11105124, 11105125, 11375001, 11675147, 11675242), the Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences (Y5KF121CJ1), the Innovation Talent project of Henan Province (15HASTIT017), the Young-Talent Foundation of Zhengzhou University, the CAS Center for Excellence in Particle Physics (CCEPP), the CAS Key Research Program of Frontier Sciences and a Key R&D Program of Ministry of Science and Technology of China (2017YFA0402200-04)

  4. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

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

  5. Hierarchical silica particles by dynamic multicomponent assembly

    DEFF Research Database (Denmark)

    Wu, Z. W.; Hu, Q. Y.; Pang, J. B.

    2005-01-01

    Abstract: Aerosol-assisted assembly of mesoporous silica particles with hierarchically controllable pore structure has been prepared using cetyltrimethylammonium bromide (CTAB) and poly(propylene oxide) (PPO, H[OCH(CH3)CH2],OH) as co-templates. Addition of the hydrophobic PPO significantly...... influences the delicate hydrophilic-hydrophobic balance in the well-studied CTAB-silicate co-assembling system, resulting in various mesostructures (such as hexagonal, lamellar, and hierarchical structure). The co-assembly of CTAB, silicate clusters, and a low-molecular-weight PPO (average M-n 425) results...... in a uniform lamellar structure, while the use of a high-molecular-weight PPO (average M-n 2000), which is more hydrophobic, leads to the formation of hierarchical pore structure that contains meso-meso or meso-macro pore structure. The role of PPO additives on the mesostructure evolution in the CTAB...

  6. Imaging of lipids in atherosclerotic lesion in aorta from ApoE/LDLR-/- mice by FT-IR spectroscopy and Hierarchical Cluster Analysis.

    Science.gov (United States)

    P Wrobel, Tomasz; Mateuszuk, Lukasz; Chlopicki, Stefan; Malek, Kamilla; Baranska, Malgorzata

    2011-12-21

    Spectroscopy-based approaches can provide an insight into the biochemical composition of a tissue sample. In the present work Fourier transform infrared (FT-IR) spectroscopy was used to develop a reliable methodology to study the content of free fatty acids, triglycerides, cholesteryl esters as well as cholesterol in aorta from mice with atherosclerosis (ApoE/LDLR(-/-) mice). In particular, distribution and concentration of palmitic, oleic and linoleic acid derivatives were analyzed. Spectral analysis of pure compounds allowed for clear discrimination between free fatty acids and other similar moieties based on the carbonyl band position (1699-1710 cm(-1) range). In order to distinguish cholesteryl esters from triglycerides a ratio of carbonyl band to signal at 1010 cm(-1) was used. Imaging of lipids in atherosclerotic aortic lesions in ApoE/LDLR(-/-) mice was followed by Hierarchical Cluster Analysis (HCA). The aorta from C57Bl/6J control mice (fed with chow diet) was used for comparison. The measurements were completed with an FT-IR spectrometer equipped with a 128 × 128 FPA detector. In cross-section of aorta from ApoE/LDLR(-/-) mice a region of atherosclerotic plaque was clearly identified by HCA, which was later divided into 2 sub-regions, one characterized by the higher content of cholesterol, while the other by higher contents of cholesteryl esters. HCA of tissues deposited on normal microscopic glass, hence limited to the 2200-3800 cm(-1) spectral range, also identified a region of atherosclerotic plaque. Importantly, this region correlates with the area stained by standard histological staining for atherosclerotic plaque (Oil Red O). In conclusion, the use of FT-IR and HCA may provide a novel tool for qualitative and quantitative analysis of contents and distribution of lipids in atherosclerotic plaque.

  7. Prediction of the fate of Hg and other contaminants in soil around a former chlor-alkali plant using Fuzzy Hierarchical Cross-Clustering approach.

    Science.gov (United States)

    Frenţiu, Tiberiu; Ponta, Michaela; Sârbu, Costel

    2015-11-01

    An associative simultaneous fuzzy divisive hierarchical algorithm was used to predict the fate of Hg and other contaminants in soil around a former chlor-alkali plant. The algorithm was applied on several natural and anthropogenic characteristics of soil including water leachable, mobile, semi-mobile, non-mobile fractions and total Hg, Al, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Sr, Zn, water leachable fraction of Cl(-), NO3(-) and SO4(2)(-), pH and total organic carbon. The cross-classification algorithm provided a divisive fuzzy partition of the soil samples and associated characteristics. Soils outside the perimeter of the former chlor-alkali plant were clustered based on the natural characteristics and total Hg. In contaminated zones Hg speciation becomes relevant and the assessment of species distribution is necessary. The descending order of concentration of Hg species in the test site was semi-mobile>mobile>non-mobile>water-leachable. Physico-chemical features responsible for similarities or differences between uncontaminated soil samples or contaminated with Hg, Cu, Zn, Ba and NO3(-) were also highlighted. Other characteristics of the contaminated soil were found to be Ca, sulfate, Na and chloride, some of which with influence on Hg fate. The presence of Ca and sulfate in soil induced a higher water leachability of Hg, while Cu had an opposite effect by forming amalgam. The used algorithm provided an in-deep understanding of processes involving Hg species and allowed to make prediction of the fate of Hg and contaminants linked to chlor-alkali-industry. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    G. Paschmann

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

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

  9. Quantitative Analysis and Comparison of Four Major Flavonol Glycosides in the Leaves of Toona sinensis (A. Juss.) Roemer (Chinese Toon) from Various Origins by High-Performance Liquid Chromatography-Diode Array Detector and Hierarchical Clustering Analysis

    Science.gov (United States)

    Sun, Xiaoxiang; Zhang, Liting; Cao, Yaqi; Gu, Qinying; Yang, Huan; Tam, James P.

    2016-01-01

    Background: Toona sinensis (A. Juss.) Roemer is an endemic species of Toona genus native to Asian area. Its dried leaves are applied in the treatment of many diseases; however, few investigations have been reported for the quantitative analysis and comparison of major bioactive flavonol glycosides in the leaves harvested from various origins. Objective: To quantitatively analyze four major flavonol glycosides including rutinoside, quercetin-3-O-β-D-glucoside, quercetin-3-O-α-L-rhamnoside, and kaempferol-3-O-α-L-rhamnoside in the leaves from different production sites and classify them according to the content of these glycosides. Materials and Methods: A high-performance liquid chromatography-diode array detector (HPLC-DAD) method for their simultaneous determination was developed and validated for linearity, precision, accuracy, stability, and repeatability. Moreover, the method established was then employed to explore the difference in the content of these four glycosides in raw materials. Finally, a hierarchical clustering analysis was performed to classify 11 voucher specimens. Results: The separation was performed on a Waters XBridge Shield RP18 column (150 mm × 4.6 mm, 3.5 μm) kept at 35°C, and acetonitrile and H2O containing 0.30% trifluoroacetic acid as mobile phase was driven at 1.0 mL/min during the analysis. Ten microliters of solution were injected and 254 nm was selected to monitor the separation. A strong linear relationship between the peak area and concentration of four analytes was observed. And, the method was also validated to be repeatable, stable, precise, and accurate. Conclusion: An efficient and reliable HPLC-DAD method was established and applied in the assays for the samples from 11 origins successfully. Moreover, the content of those flavonol glycosides varied much among different batches, and the flavonoids could be considered as biomarkers to control the quality of Chinese Toon. SUMMARY Four major flavonol glycosides in the leaves

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

    Science.gov (United States)

    Laursen, Jens; Milman, Nils; Pind, Niels; Pedersen, Henrik; Mulvad, Gert

    2014-01-01

    Meta-analysis of previous studies evaluating associations between content of elements sulphur (S), chlorine (Cl), potassium (K), iron (Fe), copper (Cu), zinc (Zn) and bromine (Br) in normal and cirrhotic autopsy liver tissue samples. Normal liver samples from 45 Greenlandic Inuit, median age 60 years and from 71 Danes, median age 61 years. Cirrhotic liver samples from 27 Danes, median age 71 years. Element content was measured using X-ray fluorescence spectrometry. Dual hierarchical clustering analysis, creating a dual dendrogram, one clustering element contents according to calculated similarities, one clustering elements according to correlation coefficients between the element contents, both using Euclidian distance and Ward Procedure. One dendrogram separated subjects in 7 clusters showing no differences in ethnicity, gender or age. The analysis discriminated between elements in normal and cirrhotic livers. The other dendrogram clustered elements in four clusters: sulphur and chlorine; copper and bromine; potassium and zinc; iron. There were significant correlations between the elements in normal liver samples: S was associated with Cl, K, Br and Zn; Cl with S and Br; K with S, Br and Zn; Cu with Br. Zn with S and K. Br with S, Cl, K and Cu. Fe did not show significant associations with any other element. In contrast to simple statistical methods, which analyses content of elements separately one by one, dual hierarchical clustering analysis incorporates all elements at the same time and can be used to examine the linkage and interplay between multiple elements in tissue samples. Copyright © 2013 Elsevier GmbH. All rights reserved.

  11. The cluster burn up programme CCC and a comparison of its results with NPD experiments

    International Nuclear Information System (INIS)

    Hoejerup, C.F.

    1976-10-01

    A brief description is given of the computer programme CCC, which can be used for rod/rod cluster burn up calculations. A comparison of CCC results with some Canadian measurements on NPD fuel is also included. (author)

  12. Clustering of near clusters versus cluster compactness

    International Nuclear Information System (INIS)

    Yu Gao; Yipeng Jing

    1989-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  14. clusters

    Indian Academy of Sciences (India)

    2017-09-27

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

  15. clusters

    Indian Academy of Sciences (India)

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

  16. Measuring age differences among globular clusters having similar metallicities - A new method and first results

    International Nuclear Information System (INIS)

    Vandenberg, D.A.; Bolte, M.; Stetson, P.B.

    1990-01-01

    A color-difference technique for estimating the relative ages of globular clusters with similar chemical compositions on the basis of their CM diagrams is described and demonstrated. The theoretical basis and implementation of the procedure are explained, and results for groups of globular clusters with m/H = about -2, -1.6, and -1.3, and for two special cases (Palomar 12 and NGC 5139) are presented in extensive tables and graphs and discussed in detail. It is found that the more metal-deficient globular clusters are nearly coeval (differences less than 0.5 Gyr), whereas the most metal-rich globular clusters exhibit significant age differences (about 2 Gyr). This result is shown to contradict Galactic evolution models postulating halo collapse in less than a few times 100 Myr. 77 refs

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

    DEFF Research Database (Denmark)

    Laursen, Jens; Milman, Nils; Pind, Niels

    2014-01-01

    contents according to calculated similarities, one clustering elements according to correlation coefficients between the element contents, both using Euclidian distance and Ward Procedure. RESULTS: One dendrogram separated subjects in 7 clusters showing no differences in ethnicity, gender or age...

  18. Staff Distress Improves by Treating Pain in Nursing Home Patients With Dementia: Results From a Cluster-Randomized Controlled Trial.

    Science.gov (United States)

    Aasmul, Irene; Husebo, Bettina Sandgathe; Flo, Elisabeth

    2016-12-01

    Most people with dementia develop neuropsychiatric symptoms (NPSs), which are distressing for their carers. Untreated pain may increase the prevalence and severity of NPSs and thereby staff burden. We investigated the association between NPSs and the impact of individual pain treatment on distress in nursing home staff. Nursing home (NH) units were cluster-randomized to an intervention group (33 NH units; n = 175) or control group (27 NH units; n = 177). Patients in the intervention group received individual pain treatment for eight weeks, followed by a four-week washout period; control groups received care as usual. Staff informants (n = 138) used the Neuropsychiatric Inventory-NH version (including caregiver distress) as primary outcome to assess their own distress. Other outcomes were pain (Mobilization-Observation-Behavior-Intensity-Dementia-2 Pain Scale) and cognitive functioning (Mini-Mental State Examination). Using hierarchical regression analysis, all NPS items at baseline were associated with staff distress (P pain treatment reduced staff distress in the intervention group compared to control group especially in regard to agitation-related symptoms and apathy. Furthermore, our results indicated a multifactorial model of staff distress, in which enhanced knowledge and understanding of NPSs and pain in people with advanced dementia may play an important role. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Clustering analysis

    International Nuclear Information System (INIS)

    Romli

    1997-01-01

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

  20. Hierarchical Neural Regression Models for Customer Churn Prediction

    Directory of Open Access Journals (Sweden)

    Golshan Mohammadi

    2013-01-01

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

  1. The Extended Northern ROSAT Galaxy Cluster Survey (NORAS II). I. Survey Construction and First Results

    Energy Technology Data Exchange (ETDEWEB)

    Böhringer, Hans; Chon, Gayoung; Trümper, Joachim [Max-Planck-Institut für Extraterrestrische Physik, D-85748 Garching (Germany); Retzlaff, Jörg [ESO, D-85748 Garching (Germany); Meisenheimer, Klaus [Max-Planck-Institut für Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Schartel, Norbert [ESAC, Camino Bajo del Castillo, Villanueva de la Cañada, E-28692 Madrid (Spain)

    2017-05-01

    As the largest, clearly defined building blocks of our universe, galaxy clusters are interesting astrophysical laboratories and important probes for cosmology. X-ray surveys for galaxy clusters provide one of the best ways to characterize the population of galaxy clusters. We provide a description of the construction of the NORAS II galaxy cluster survey based on X-ray data from the northern part of the ROSAT All-Sky Survey. NORAS II extends the NORAS survey down to a flux limit of 1.8 × 10{sup −12} erg s{sup −1} cm{sup −2} (0.1–2.4 keV), increasing the sample size by about a factor of two. The NORAS II cluster survey now reaches the same quality and depth as its counterpart, the southern REFLEX II survey, allowing us to combine the two complementary surveys. The paper provides information on the determination of the cluster X-ray parameters, the identification process of the X-ray sources, the statistics of the survey, and the construction of the survey selection function, which we provide in numerical format. Currently NORAS II contains 860 clusters with a median redshift of z  = 0.102. We provide a number of statistical functions, including the log N –log S and the X-ray luminosity function and compare these to the results from the complementary REFLEX II survey. Using the NORAS II sample to constrain the cosmological parameters, σ {sub 8} and Ω{sub m}, yields results perfectly consistent with those of REFLEX II. Overall, the results show that the two hemisphere samples, NORAS II and REFLEX II, can be combined without problems into an all-sky sample, just excluding the zone of avoidance.

  2. The Extended Northern ROSAT Galaxy Cluster Survey (NORAS II). I. Survey Construction and First Results

    International Nuclear Information System (INIS)

    Böhringer, Hans; Chon, Gayoung; Trümper, Joachim; Retzlaff, Jörg; Meisenheimer, Klaus; Schartel, Norbert

    2017-01-01

    As the largest, clearly defined building blocks of our universe, galaxy clusters are interesting astrophysical laboratories and important probes for cosmology. X-ray surveys for galaxy clusters provide one of the best ways to characterize the population of galaxy clusters. We provide a description of the construction of the NORAS II galaxy cluster survey based on X-ray data from the northern part of the ROSAT All-Sky Survey. NORAS II extends the NORAS survey down to a flux limit of 1.8 × 10 −12 erg s −1 cm −2 (0.1–2.4 keV), increasing the sample size by about a factor of two. The NORAS II cluster survey now reaches the same quality and depth as its counterpart, the southern REFLEX II survey, allowing us to combine the two complementary surveys. The paper provides information on the determination of the cluster X-ray parameters, the identification process of the X-ray sources, the statistics of the survey, and the construction of the survey selection function, which we provide in numerical format. Currently NORAS II contains 860 clusters with a median redshift of z  = 0.102. We provide a number of statistical functions, including the log N –log S and the X-ray luminosity function and compare these to the results from the complementary REFLEX II survey. Using the NORAS II sample to constrain the cosmological parameters, σ 8 and Ω m , yields results perfectly consistent with those of REFLEX II. Overall, the results show that the two hemisphere samples, NORAS II and REFLEX II, can be combined without problems into an all-sky sample, just excluding the zone of avoidance.

  3. Au55, a stable glassy cluster: results of ab initio calculations

    Directory of Open Access Journals (Sweden)

    Dieter Vollath

    2017-10-01

    Full Text Available Structure and properties of small nanoparticles are still under discussion. Moreover, some thermodynamic properties and the structural behavior still remain partially unknown. One of the best investigated nanoparticles is the Au55 cluster, which has been analyzed experimentally and theoretically. However, up to now, the results of these studies are still inconsistent. Consequently, we have carried out the present ab initio study of the Au55 cluster, using up-to-date computational concepts, in order to clarify these issues. Our calculations have confirmed the experimental result that the thermodynamically most stable structure is not crystalline, but it is glassy. The non-crystalline structure of this cluster was validated by comparison of the coordination numbers with those of a crystalline cluster. It was found that, in contrast to bulk materials, glass formation is connected to an energy release that is close to the melting enthalpy of bulk gold. Additionally, the surface energy of this cluster was calculated using two different theoretical approaches resulting in values close to the surface energy for bulk gold. It shall be emphasized that it is now possible to give a confidence interval for the value of the surface energy.

  4. Ecosystem health pattern analysis of urban clusters based on emergy synthesis: Results and implication for management

    International Nuclear Information System (INIS)

    Su, Meirong; Fath, Brian D.; Yang, Zhifeng; Chen, Bin; Liu, Gengyuan

    2013-01-01

    The evaluation of ecosystem health in urban clusters will help establish effective management that promotes sustainable regional development. To standardize the application of emergy synthesis and set pair analysis (EM–SPA) in ecosystem health assessment, a procedure for using EM–SPA models was established in this paper by combining the ability of emergy synthesis to reflect health status from a biophysical perspective with the ability of set pair analysis to describe extensive relationships among different variables. Based on the EM–SPA model, the relative health levels of selected urban clusters and their related ecosystem health patterns were characterized. The health states of three typical Chinese urban clusters – Jing-Jin-Tang, Yangtze River Delta, and Pearl River Delta – were investigated using the model. The results showed that the health status of the Pearl River Delta was relatively good; the health for the Yangtze River Delta was poor. As for the specific health characteristics, the Pearl River Delta and Yangtze River Delta urban clusters were relatively strong in Vigor, Resilience, and Urban ecosystem service function maintenance, while the Jing-Jin-Tang was relatively strong in organizational structure and environmental impact. Guidelines for managing these different urban clusters were put forward based on the analysis of the results of this study. - Highlights: • The use of integrated emergy synthesis and set pair analysis model was standardized. • The integrated model was applied on the scale of an urban cluster. • Health patterns of different urban clusters were compared. • Policy suggestions were provided based on the health pattern analysis

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

    Science.gov (United States)

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

    2017-01-01

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

  6. Tune Your Brown Clustering, Please

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  7. Hierarchical video summarization

    Science.gov (United States)

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

    1998-12-01

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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    We present the final results from the XMM-Newton validation follow-up of new Planck galaxy cluster candidates. We observed 15 new candidates, detected with signal-to-noise ratios between 4.0 and 6.1 in the 15.5-month nominal Planck survey. The candidates were selected using ancillary data flags d...

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

    CERN Document Server

    Gonzalez Blanco Gonzalez, Genoveva

    2016-01-01

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

  10. Tractography segmentation using a hierarchical Dirichlet processes mixture model.

    Science.gov (United States)

    Wang, Xiaogang; Grimson, W Eric L; Westin, Carl-Fredrik

    2011-01-01

    In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. The number of clusters is automatically learned driven by data with a Dirichlet process (DP) prior instead of being manually specified. After the models of bundles have been learned from training data without supervision, they can be used as priors to cluster/classify fibers of new subjects for comparison across subjects. When clustering fibers of new subjects, new clusters can be created for structures not observed in the training data. Our approach does not require computing pairwise distances between fibers and can cluster a huge set of fibers across multiple subjects. We present results on several data sets, the largest of which has more than 120,000 fibers. Copyright © 2010 Elsevier Inc. All rights reserved.

  11. Chimera states in networks of logistic maps with hierarchical connectivities

    Science.gov (United States)

    zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

    2018-04-01

    Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

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

    NARCIS (Netherlands)

    Vuurpijl, L.; Schomaker, L.

    2000-01-01

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

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

    DEFF Research Database (Denmark)

    Grotkjær, Thomas; Winther, Ole; Regenberg, Birgitte

    2006-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-02-01

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

  15. The Case for a Hierarchical Cosmology

    Science.gov (United States)

    Vaucouleurs, G. de

    1970-01-01

    The development of modern theoretical cosmology is presented and some questionable assumptions of orthodox cosmology are pointed out. Suggests that recent observations indicate that hierarchical clustering is a basic factor in cosmology. The implications of hierarchical models of the universe are considered. Bibliography. (LC)

  16. Discovering hierarchical structure in normal relational data

    DEFF Research Database (Denmark)

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

    2014-01-01

    -parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional...

  17. Modular networks with hierarchical organization

    Indian Academy of Sciences (India)

    Several networks occurring in real life have modular structures that are arranged in a hierarchical fashion. In this paper, we have proposed a model for such networks, using a stochastic generation method. Using this model we show that, the scaling relation between the clustering and degree of the nodes is not a necessary ...

  18. Female cluster headache in the United States of America: what are the gender differences? Results from the United States Cluster Headache Survey.

    Science.gov (United States)

    Rozen, Todd D; Fishman, Royce S

    2012-06-15

    To present results from the United States Cluster Headache Survey regarding gender differences in cluster headache demographics, clinical characteristics, diagnostic delay, triggers, treatment response and personal burden. Very few studies have looked at the gender differences in cluster headache presentation. The United States Cluster Headache Survey is the largest study of cluster headache sufferers ever completed in the United States and it is also the largest study of female cluster headache patients ever presented. The total survey consisted of 187 multiple choice questions which dealt with various issues related to cluster headache including: demographics, clinical characteristics, concomitant medical conditions, family history, triggers, smoking history, diagnosis, treatment response and personal burden. A group of questions were specifically targeted to female cluster headache patients. The survey was placed on a website from October to December 2008. For all survey responders the diagnosis of cluster headache needed to be made by a neurologist but there was no validation of the headache diagnosis by the authors. 1134 individuals completed the survey (816 male, 318 female). Key Points that define the differences between female and male cluster headache include: a. Age of onset: women develop cluster headache at an earlier age than men and are more likely to develop a second peak of cluster headache onset after 50 years of age. b. Family history: woman cluster headache sufferers are more likely to have a family history of both cluster headache and migraine and have an increased familial risk of Parkinson's disease. c. Comorbid conditions: female cluster headaches sufferers are significantly more likely to experience depression and have asthma than males. d. Aura issues: aura with cluster headache is equally common in both sexes, but aura duration is shorter in women. Women are much more likely to experience sensory, language and brainstem auras. e. Pain

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

    Science.gov (United States)

    Girola Schneider, R.

    2017-07-01

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

  20. Cardiometabolic risk clustering in spinal cord injury: results of exploratory factor analysis.

    Science.gov (United States)

    Libin, Alexander; Tinsley, Emily A; Nash, Mark S; Mendez, Armando J; Burns, Patricia; Elrod, Matt; Hamm, Larry F; Groah, Suzanne L

    2013-01-01

    Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. One hundred twenty-one subjects (mean 37 ± 12 years; range, 18-73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3-factor model in persons with paraplegia (65.4% variance) and a 4-factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism.

  1. Cluster evolution

    International Nuclear Information System (INIS)

    Schaeffer, R.

    1987-01-01

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

  2. 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.

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

    Science.gov (United States)

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

    2017-08-31

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

  4. WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results.

    Science.gov (United States)

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

    2011-01-17

    Cluster analysis methods have been extensively researched, but the adoption of new methods is often hindered by technical barriers in their implementation and use. WebGimm is a free cluster analysis web-service, and an open source general purpose clustering web-server infrastructure designed to facilitate easy deployment of integrated cluster analysis servers based on clustering and functional annotation algorithms implemented in R. Integrated functional analyses and interactive browsing of both, clustering structure and functional annotations provides a complete analytical environment for cluster analysis and interpretation of results. The Java Web Start client-based interface is modeled after the familiar cluster/treeview packages making its use intuitive to a wide array of biomedical researchers. For biomedical researchers, WebGimm provides an avenue to access state of the art clustering procedures. For Bioinformatics methods developers, WebGimm offers a convenient avenue to deploy their newly developed clustering methods. WebGimm server, software and manuals can be freely accessed at http://ClusterAnalysis.org/.

  5. Nested and Hierarchical Archimax copulas

    KAUST Repository

    Hofert, Marius; Huser, Raphaë l; Prasad, Avinash

    2017-01-01

    The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

  6. Nested and Hierarchical Archimax copulas

    KAUST Repository

    Hofert, Marius

    2017-07-03

    The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

  7. Grouping and clustering of maize Lancaster germplasm inbreds according to the results of SNP-analysis

    Directory of Open Access Journals (Sweden)

    K. V. Derkach

    2017-08-01

    Full Text Available The objective of this article is the grouping and clustering of maize inbred lines based on the results of SNP-genotyping for the verification of a separate cluster of Lancaster germplasm inbred lines. As material for the study, we used 91 maize (Zea mays L. inbred lines, including 31 Lancaster germplasm lines and 60 inbred lines of other germplasms (23 Iodent inbreds, 15 Reid inbreds, 7 Lacon inbreds, 12 Mix inbreds and 3 exotic inbreds. The majority of the given inbred lines are included in the Dnipro breeding programme. The SNP-genotyping of these inbred lines was conducted using BDI-III panel of 384 SNP-markers developed by BioDiagnostics, Inc. (USA on the base of Illumina VeraCode Bead Plate. The SNP-markers of this panel are biallelic and are located on all 10 maize chromosomes. Their range of conductivity was >0.6. The SNP-analysis was made in completely automated regime on Illumina BeadStation equipment at BioDiagnostics, Inc. (USA. A principal component analysis was applied to group a general set of 91 inbreds according to allelic states of SNP-markers and to identify a cluster of Lancaster inbreds. The clustering and determining hierarchy in 31 Lancaster germplasm inbreds used quantitative cluster analysis. The share of monomorphic markers in the studied set of 91 inbred lines equaled 0.7%, and the share of dimorphic markers equaled 99.3%. Minor allele frequency (MAF > 0.2 was observed for 80.6% of dimorphic markers, the average index of shift of gene diversity equaled 0.2984, PIC on average reached 0.3144. The index of gene diversity of markers varied from 0.1701 to 0.1901, pairwise genetic distances between inbred lines ranged from 0.0316–0.8000, the frequencies of major alleles of SNP-markers were within 0.5085–0.9821, and the frequencies of minor alleles were within 0.0179–0.4915. The average homozygosity of inbred lines was 98.8%. The principal component analysis of SNP-distances confirmed the isolation of the Lancaster

  8. Quantum annealing for combinatorial clustering

    Science.gov (United States)

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

    2018-02-01

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

  9. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, Michael [Iowa State Univ., Ames, IA (United States)

    1993-07-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  11. z ~ 7-10 Galaxies Behind Lensing Clusters: Contrast with Field Search Results

    Science.gov (United States)

    Bouwens, Rychard J.; Illingworth, Garth D.; Bradley, Larry D.; Ford, Holland; Franx, Marijn; Zheng, Wei; Broadhurst, Tom; Coe, Dan; Jee, M. James

    2009-01-01

    We conduct a search for z gsim 7 dropout galaxies behind 11 massive lensing clusters using 21 arcmin2 of deep Hubble Space Telescope NICMOS, ACS, and WFPC2 image data. In total, over this entire area, we find only one robust z ~ 7 z-dropout candidate (previously reported around Abell 1689). Four less robust z-dropout and J-dropout candidates are also found. The nature of the four weaker candidates could not be precisely determined due to the limited depth of the available optical data, but detailed simulations suggest that all four are likely to be low-redshift interlopers. By contrast, we estimate that our robust candidate A1689-zD1 has dropouts and 0.3 z ~ 9 J-dropouts over our cluster search area, in reasonable agreement with our observational results, given the small numbers. The number of z gsim 7 candidates we find in the present search is much lower than that which has been reported in several previous studies of the prevalence of z gsim 7 galaxies behind lensing clusters. To understand these differences, we examined z gsim 7 candidates in other studies and conclude that only a small fraction are likely to be z gsim 7 galaxies. Our findings support models that show that gravitational lensing from clusters is of the most value for detecting galaxies at magnitudes brighter than L* (H lsim 27) where the LF is expected to be very steep. Use of these clusters to constrain the faint-end slope or determine the full LF is likely of less value due to the shallower effective slope measured for the LF at fainter magnitudes, as well as significant uncertainties introduced from modeling both the gravitational lensing and incompleteness. Based on observations made with the NASA/ESA Hubble Space Telescope, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with programs #5352, 5935, 6488, 8249, 8882, 9289, 9452, 9717, 10150, 10154, 10200, 10325, 10504, 10863, 10996.

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

    Directory of Open Access Journals (Sweden)

    Maria Åström

    2012-06-01

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

  13. IDENTIFYING REGIONAL CLUSTER MANAGEMENT POTENTIALS EMPIRICAL RESULTS FROM THREE NORTH RHINEWESTPHALIAN REGIONS

    OpenAIRE

    Rudiger Hamm; Christiane Goebel

    2010-01-01

    The development and support of clusters is an issue that became quite popular by players dealing with regional economic policy. But before a regional development agency can start to implement a cluster-oriented strategy there a two question that have to be answered: 1. What are the regional fields of competence (cluster potentials) that fulfill the requirements for a cluster-oriented regional development policy? 2. If you find such regional fields of competence, are the enterprises willing to...

  14. Ultrathin mesoporous Co{sub 3}O{sub 4} nanosheets-constructed hierarchical clusters as high rate capability and long life anode materials for lithium-ion batteries

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Shengming [Key Laboratory of Functional Inorganic Materials Chemistry, Ministry of Education, School of Chemistry, Chemical Engineering and Materials, Heilongjiang University, Heilongjiang, Harbin 150080 (China); Xia, Tian, E-mail: xiatian@hlju.edu.cn [Key Laboratory of Functional Inorganic Materials Chemistry, Ministry of Education, School of Chemistry, Chemical Engineering and Materials, Heilongjiang University, Heilongjiang, Harbin 150080 (China); Wang, Jingping [Key Laboratory of Superlight Material and Surface Technology, Ministry of Education, College of Materials Science and Chemical Engineering, Harbin Engineering University, Heilongjiang, Harbin 150001 (China); Lu, Feifei [Key Laboratory of Functional Inorganic Materials Chemistry, Ministry of Education, School of Chemistry, Chemical Engineering and Materials, Heilongjiang University, Heilongjiang, Harbin 150080 (China); Xu, Chunbo [Key Laboratory of Superlight Material and Surface Technology, Ministry of Education, College of Materials Science and Chemical Engineering, Harbin Engineering University, Heilongjiang, Harbin 150001 (China); Zhang, Xianfa; Huo, Lihua [Key Laboratory of Functional Inorganic Materials Chemistry, Ministry of Education, School of Chemistry, Chemical Engineering and Materials, Heilongjiang University, Heilongjiang, Harbin 150080 (China); Zhao, Hui, E-mail: zhaohui98@yahoo.com [Key Laboratory of Functional Inorganic Materials Chemistry, Ministry of Education, School of Chemistry, Chemical Engineering and Materials, Heilongjiang University, Heilongjiang, Harbin 150080 (China)

    2017-06-01

    Graphical abstract: Ultrathin mesoporous Co{sub 3}O{sub 4} nanosheets-constructed hierarchical clusters (UMCN-HCs) have been successfully synthesized via a facile hydrothermal method followed by a subsequent thermolysis treatment. When tested as anode materials for LIBs, UMCN-HCs achieve high reversible capacity, good long cycling life, and rate capability. - Highlights: • UMCN-HCs show high capacity, excellent stability, and good rate capability. • UMCN-HCs retain a capacity of 1067 mAh g{sup −1} after 100 cycles at 100 mA g{sup −1}. • UMCN-HCs deliver a capacity of 507 mAh g{sup −1} after 500 cycles at 2 A g{sup −1}. - Abstract: Herein, Ultrathin mesoporous Co{sub 3}O{sub 4} nanosheets-constructed hierarchical clusters (UMCN-HCs) have been successfully synthesized via a facile hydrothermal method followed by a subsequent thermolysis treatment at 600 °C in air. The products consist of cluster-like Co{sub 3}O{sub 4} microarchitectures, which are assembled by numerous ultrathin mesoporous Co{sub 3}O{sub 4} nanosheets. When tested as anode materials for lithium-ion batteries, UMCN-HCs deliver a high reversible capacity of 1067 mAh g{sup −1} at a current density of 100 mA g{sup −1} after 100 cycles. Even at 2 A g{sup −1}, a stable capacity as high as 507 mAh g{sup −1} can be achieved after 500 cycles. The high reversible capacity, excellent cycling stability, and good rate capability of UMCN-HCs may be attributed to their mesoporous sheet-like nanostructure. The sheet-layered structure of UMCN-HCs may buffer the volume change during the lithiation-delithiation process, and the mesoporous characteristic make lithium-ion transfer more easily at the interface between the active electrode and the electrolyte.

  15. 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

  16. Interpreting results of cluster surveys in emergency settings: is the LQAS test the best option?

    Science.gov (United States)

    Bilukha, Oleg O; Blanton, Curtis

    2008-12-09

    Cluster surveys are commonly used in humanitarian emergencies to measure health and nutrition indicators. Deitchler et al. have proposed to use Lot Quality Assurance Sampling (LQAS) hypothesis testing in cluster surveys to classify the prevalence of global acute malnutrition as exceeding or not exceeding the pre-established thresholds. Field practitioners and decision-makers must clearly understand the meaning and implications of using this test in interpreting survey results to make programmatic decisions. We demonstrate that the LQAS test--as proposed by Deitchler et al.--is prone to producing false-positive results and thus is likely to suggest interventions in situations where interventions may not be needed. As an alternative, to provide more useful information for decision-making, we suggest reporting the probability of an indicator's exceeding the threshold as a direct measure of "risk". Such probability can be easily determined in field settings by using a simple spreadsheet calculator. The "risk" of exceeding the threshold can then be considered in the context of other aggravating and protective factors to make informed programmatic decisions.

  17. Interpreting results of cluster surveys in emergency settings: is the LQAS test the best option?

    Directory of Open Access Journals (Sweden)

    Blanton Curtis

    2008-12-01

    Full Text Available Abstract Cluster surveys are commonly used in humanitarian emergencies to measure health and nutrition indicators. Deitchler et al. have proposed to use Lot Quality Assurance Sampling (LQAS hypothesis testing in cluster surveys to classify the prevalence of global acute malnutrition as exceeding or not exceeding the pre-established thresholds. Field practitioners and decision-makers must clearly understand the meaning and implications of using this test in interpreting survey results to make programmatic decisions. We demonstrate that the LQAS test–as proposed by Deitchler et al. – is prone to producing false-positive results and thus is likely to suggest interventions in situations where interventions may not be needed. As an alternative, to provide more useful information for decision-making, we suggest reporting the probability of an indicator's exceeding the threshold as a direct measure of "risk". Such probability can be easily determined in field settings by using a simple spreadsheet calculator. The "risk" of exceeding the threshold can then be considered in the context of other aggravating and protective factors to make informed programmatic decisions.

  18. Competitive cluster growth in complex networks.

    Science.gov (United States)

    Moreira, André A; Paula, Demétrius R; Costa Filho, Raimundo N; Andrade, José S

    2006-06-01

    In this work we propose an idealized model for competitive cluster growth in complex networks. Each cluster can be thought of as a fraction of a community that shares some common opinion. Our results show that the cluster size distribution depends on the particular choice for the topology of the network of contacts among the agents. As an application, we show that the cluster size distributions obtained when the growth process is performed on hierarchical networks, e.g., the Apollonian network, have a scaling form similar to what has been observed for the distribution of a number of votes in an electoral process. We suggest that this similarity may be due to the fact that social networks involved in the electoral process may also possess an underlining hierarchical structure.

  19. A Multidimensional and Multimembership Clustering Method for Social Networks and Its Application in Customer Relationship Management

    Directory of Open Access Journals (Sweden)

    Peixin Zhao

    2013-01-01

    Full Text Available Community detection in social networks plays an important role in cluster analysis. Many traditional techniques for one-dimensional problems have been proven inadequate for high-dimensional or mixed type datasets due to the data sparseness and attribute redundancy. In this paper we propose a graph-based clustering method for multidimensional datasets. This novel method has two distinguished features: nonbinary hierarchical tree and the multi-membership clusters. The nonbinary hierarchical tree clearly highlights meaningful clusters, while the multimembership feature may provide more useful service strategies. Experimental results on the customer relationship management confirm the effectiveness of the new method.

  20. Motivational Interviewing for Workers with Disabling Musculoskeletal Disorders: Results of a Cluster Randomized Control Trial.

    Science.gov (United States)

    Park, Joanne; Esmail, Shaniff; Rayani, Fahreen; Norris, Colleen M; Gross, Douglas P

    2018-06-01

    Purpose Although functional restoration programs appear effective in assisting injured workers to return-to-work (RTW) after a work related musculoskeletal (MSK) disorder, the addition of Motivational Interviewing (MI) to these programs may result in higher RTW. Methods We conducted a cluster randomized controlled trial with claimants attending an occupational rehabilitation facility from November 17, 2014 to June 30, 2015. Six clinicians provided MI in addition to the standard functional restoration program and formed an intervention group. Six clinicians continued to provide the standard functional restoration program based on graded activity, therapeutic exercise, and workplace accommodations. Independent t tests and chi square analysis were used to compare groups. Multivariable logistic regression was used to obtain the odds ratio of claimants' confirmed RTW status at time of program discharge. Results 728 workers' compensation claimants with MSK disorders were entered into 1 of 12 therapist clusters (MI group = 367, control group = 361). Claimants were predominantly employed (72.7%), males (63.2%), with moderate levels of pain and disability (mean pain VAS = 5.0/10 and mean Pain Disability Index = 48/70). Claimants were stratified based on job attachment status. The proportion of successful RTW at program discharge was 12.1% higher for unemployed workers in the intervention group (intervention group 21.6 vs. 9.5% in control, p = 0.03) and 3.0% higher for job attached workers compared to the control group (intervention group 97.1 vs. 94.1% in control, p = 0.10). Adherence to MI was mixed, but RTW was significantly higher among MI-adherent clinicians. The odds ratio for unemployed claimants was 2.64 (0.69-10.14) and 2.50 (0.68-9.14) for employed claimants after adjusting for age, sex, pain intensity, perceived disability, and therapist cluster. Conclusion MI in addition to routine functional restoration is more effective than routine

  1. Status and results from the decay spectroscopy project EURICA (Euroball-RIKEN cluster array)

    Energy Technology Data Exchange (ETDEWEB)

    Söderström, P.-A., E-mail: pasoder@ribf.riken.jp; Doornenbal, P.; Nishimura, S.; Baba, H.; Isobe, T.; Kiss, G. [RIKEN Nishina Center, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan); Lorusso, G. [RIKEN Nishina Center, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan); National Physical Laboratory, Teddington, Middlesex, TW11 0LW (United Kingdom); Wu, J. [RIKEN Nishina Center, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan); School of Physics, Peking University, Beijing 100871 (China); Xu, Z. Y. [Department of Physics, University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); KU Leuven, Instituut voor Kern-en Stralingsfysica, 3001 Leuven (Belgium); Benzoni, G. [Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Via Celoria 16, 20133 Milano (Italy); Browne, F. [RIKEN Nishina Center, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan); School of Computing, Engineering and Mathematics, University of Brighton, Brighton BN2 4JG (United Kingdom); Gey, G. [RIKEN Nishina Center, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan); LPSC, Université Grenoble-Alpes, CNRS/IN2P3, F-38026 Grenoble Cedex (France); ILL, 38042 Grenoble Cedex (France); Research Center for Nuclear Physics (RCNP), Osaka University, Ibaraki, Osaka 567-0047 (Japan); Jungclaus, A. [Instituto de Estructura de la Materia, CSIC, E-28006 Madrid (Spain); Kojouharov, I.; Kurz, N.; Schaffner, H. [GSI Helmholtzzentrum für Schwerionenforschung GmbH, 64291 Darmstadt (Germany); Lubos, D. [RIKEN Nishina Center, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan); Physik Department E12, Technische Universität München, D-85748 Garching (Germany); Moschner, K. [RIKEN Nishina Center, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan); IKP, University of Cologne, D-50937 Cologne (Germany); and others

    2016-07-07

    β- and isomer-decay spectroscopy are sensitive probes of nuclear structure, and are often the only techniques capable of providing data for exotic nuclei that are produced with very low rates. Decay properties of exotic nuclei are also essential to model astrophysical events responsible for the evolution of the universe such as the rp- and r-processes. The EURICA project (EUROBALL RIKEN Cluster Array) has been launched in 2012 with the goal of performing spectroscopy of very exotic nuclei. Since 2012, five experimental campaigns have been successfully completed using fragmentation of {sup 124}Xe beam and in-flight-fission of {sup 238}U beam. In these proceedings we will introduce the experimental setup and highlight some key recent results around {sup 78}Ni, {sup 132}Sn, and {sup 110}Zn published during 2014 and 2015.

  2. The Globular Clusters of the Galactic Bulge: Results from Multiwavelength Follow-up Imaging

    Science.gov (United States)

    Cohen, Roger; Geisler, Doug; Mauro, Francesco; Alonso Garcia, Javier; Hempel, Maren; Sarajedini, Ata

    2018-01-01

    The Galactic globular clusters (GGCs) located towards the bulge of the Milky Way suffer from severe total and differential extinction and high field star densities. They have therefore been systematically excluded from deep, large-scale homogenous GGC surveys, and will present a challenge for Gaia. Meanwhile, existing observations of bulge GGCs have revealed tantalizing hints that they hold clues to Galactic formation and evolution not found elsewhere. Therefore, in order to better characterize these poorly studied stellar systems and place them in the context of their optically well-studied counterparts, we have undertaken imaging programs at optical and near-infrared wavelengths. We describe these programs and present a variety of results, including self-consistent measurement of bulge GGC ages and structural parameters. The limitations imposed by spatially variable extinction and extinction law are highlighted, along with the complimentary nature of forthcoming facilities, allowing us to finally complete our picture of the Milky Way GGC system.

  3. Performance quantification of clustering algorithms for false positive removal in fMRI by ROC curves

    Directory of Open Access Journals (Sweden)

    André Salles Cunha Peres

    Full Text Available Abstract Introduction Functional magnetic resonance imaging (fMRI is a non-invasive technique that allows the detection of specific cerebral functions in humans based on hemodynamic changes. The contrast changes are about 5%, making visual inspection impossible. Thus, statistic strategies are applied to infer which brain region is engaged in a task. However, the traditional methods like general linear model and cross-correlation utilize voxel-wise calculation, introducing a lot of false-positive data. So, in this work we tested post-processing cluster algorithms to diminish the false-positives. Methods In this study, three clustering algorithms (the hierarchical cluster, k-means and self-organizing maps were tested and compared for false-positive removal in the post-processing of cross-correlation analyses. Results Our results showed that the hierarchical cluster presented the best performance to remove the false positives in fMRI, being 2.3 times more accurate than k-means, and 1.9 times more accurate than self-organizing maps. Conclusion The hierarchical cluster presented the best performance in false-positive removal because it uses the inconsistency coefficient threshold, while k-means and self-organizing maps utilize a priori cluster number (centroids and neurons number; thus, the hierarchical cluster avoids clustering scattered voxels, as the inconsistency coefficient threshold allows only the voxels to be clustered that are at a minimum distance to some cluster.

  4. Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots.

    Science.gov (United States)

    Hagiwara, Yoshinobu; Inoue, Masakazu; Kobayashi, Hiroyoshi; Taniguchi, Tadahiro

    2018-01-01

    In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., "I am in my home" and "I am in front of the table," a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

  5. Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots

    Directory of Open Access Journals (Sweden)

    Yoshinobu Hagiwara

    2018-03-01

    Full Text Available In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., “I am in my home” and “I am in front of the table,” a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA. Object recognition results using convolutional neural network (CNN, hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL, and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

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

    DEFF Research Database (Denmark)

    Poutanen, T.; Natoli, P.; Polenta, G.

    2011-01-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    We present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck clus...

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

    Directory of Open Access Journals (Sweden)

    J.-A. Sauvaud

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

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

  9. Aero thermal test results obtained on the n. C 5 EL 4 Cluster in the atmospheric pressure cell

    International Nuclear Information System (INIS)

    Gasc, B.

    1964-01-01

    In the framework of thermal studies on the EL-4 cluster, the full-scale tests at atmospheric pressure are designed to permit measurement of local values of the wall temperature, of the velocity and of the temperature in the fluid. The experimental results, obtained with the help of an original measuring apparatus, make it possible to follow the changes in these values along the cluster and to predict in much detail the in-pile thermal behaviour. In particular it is shown that changes in the wall temperature along the cluster are greatly influenced by disruption of the flow caused by grids and supports. (author) [fr

  10. Distribution of shallow very low frequency earthquakes in the eastern Nankai trough influenced by a subducted oceanic ridge: Results from cluster analysis applied to ocean bottom seismographs

    Science.gov (United States)

    To, A.; Obana, K.; Araki, E.

    2016-12-01

    The activity of very low frequency earthquakes (VLFEs) in the shallow accretionary prism of the eastern Nankai trough has been observed frequently in the past. In this study, we investigated the distribution of VLFEs that occurred in October 2015, which were recorded by an array of broadband ocean bottom seismometers (BBOBSs) of DONET1 network. The size of the network is much wider (>80 km) compared to previous BBOBS networks that were used for close-in observations of VLFEs; therefore the new dataset provides a broader overview of the VLFE distribution of this region. We first located the detected events using conventional methods such as the envelope correlation method. However, the results seemed to be largely scattered due to noise and the effect of 3D structures that could not be properly handled. Then, we introduced hierarchal clustering analysis, based on measured travel time patterns among stations obtained for each event. The analyses enabled the assessment of relative locations among events. Finally, the locations of event-clusters were estimated, instead of individual events, so that the obtained locations seemed less scattered. The obtained results indicate that the VLFE distribution is strongly influenced by a subducted ridge (Park et al., 2003) that exists beneath the northeastern side of the DONET1 network. Though the VLFEs are distributed from an area near the outer ridge toward the trench axis in the region with a smooth plate boundary, they are clustered at a shallow depth near the outer ridge in the region of the rough plate boundary. The VLFEs are clustered on the landward side of the peak of the subducted ridge; this could be explained by an elevated pore pressure in the region caused by the low-permeability oceanic ridge that may clog the up-dip pathway of the fluid along the decollement zone. The along-strike variation of the stress state, inferred from the VLFE distribution, should be an important factor in assessing the strain release

  11. Interactive visual exploration and refinement of cluster assignments.

    Science.gov (United States)

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

    2017-09-12

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

  12. Cluster-cluster clustering

    International Nuclear Information System (INIS)

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

    1985-01-01

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

  13. Data clustering theory, algorithms, and applications

    CERN Document Server

    Gan, Guojun; Wu, Jianhong

    2007-01-01

    Cluster analysis is an unsupervised process that divides a set of objects into homogeneous groups. This book starts with basic information on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50 clustering algorithms in groups according to some specific baseline methodologies such as hierarchical, center-based, and search-based methods. As a result, readers and users can easily identify an appropriate algorithm for their applications and compare novel ideas with existing results. The book also provides examples of clustering applications to illustrate the advantages and shortcomings of different clustering architectures and algorithms. Application areas include pattern recognition, artificial intelligence, information technology, image processing, biology, psychology, and marketing. Readers also learn how to perform cluster analysis with the C/C++ and MATLAB® programming languages.

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

    Directory of Open Access Journals (Sweden)

    S. Haaland

    2008-08-01

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

  15. Baryon Distribution in Galaxy Clusters as a Result of Sedimentation of Helium Nuclei.

    Science.gov (United States)

    Qin; Wu

    2000-01-20

    Heavy particles in galaxy clusters tend to be more centrally concentrated than light ones according to the Boltzmann distribution. An estimate of the drift velocity suggests that it is possible that the helium nuclei may have entirely or partially sedimented into the cluster core within the Hubble time. We demonstrate this scenario using the Navarro-Frenk-White profile as the dark matter distribution of clusters and assuming that the intracluster gas is isothermal and in hydrostatic equilibrium. We find that a greater fraction of baryonic matter is distributed at small radii than at large radii, which challenges the prevailing claim that the baryon fraction increases monotonically with cluster radius. It shows that the conventional mass estimate using X-ray measurements of intracluster gas along with a constant mean molecular weight may have underestimated the total cluster mass by approximately 20%, which in turn leads to an overestimate of the total baryon fraction by the same percentage. Additionally, it is pointed out that the sedimentation of helium nuclei toward cluster cores may at least partially account for the sharp peaks in the central X-ray emissions observed in some clusters.

  16. Hierarchical sets: analyzing pangenome structure through scalable set visualizations

    Science.gov (United States)

    2017-01-01

    Abstract Motivation: The increase in available microbial genome sequences has resulted in an increase in the size of the pangenomes being analyzed. Current pangenome visualizations are not intended for the pangenome sizes possible today and new approaches are necessary in order to convert the increase in available information to increase in knowledge. As the pangenome data structure is essentially a collection of sets we explore the potential for scalable set visualization as a tool for pangenome analysis. Results: We present a new hierarchical clustering algorithm based on set arithmetics that optimizes the intersection sizes along the branches. The intersection and union sizes along the hierarchy are visualized using a composite dendrogram and icicle plot, which, in pangenome context, shows the evolution of pangenome and core size along the evolutionary hierarchy. Outlying elements, i.e. elements whose presence pattern do not correspond with the hierarchy, can be visualized using hierarchical edge bundles. When applied to pangenome data this plot shows putative horizontal gene transfers between the genomes and can highlight relationships between genomes that is not represented by the hierarchy. We illustrate the utility of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. Availability and Implementation: The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https://cran.r-project.org/web/packages/hierarchicalSets) Contact: thomasp85@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28130242

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    of candidates previously confirmed with XMM-Newton. The X-ray and optical redshifts for a total of 20 clusters are found to be in excellent agreement. We also show that useful lower limits can be put on cluster redshifts using X-ray data only via the use of the Y-X vs. Y-SZ and X-ray flux F-X vs. Y-SZ relations....

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

    Science.gov (United States)

    Heise, Heinke; Kemper, Nicole; Theuvsen, Ludwig

    2016-01-01

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

  19. Hierarchical architecture of active knits

    International Nuclear Information System (INIS)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-01-01

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

  20. Evolution of cluster X-ray luminosities and radii: Results from the 160 square degree rosat survey

    DEFF Research Database (Denmark)

    Vikhlinin, A.; McNamara, B.R.; Forman, W.

    1998-01-01

    We searched for cluster X-ray luminosity and radius evolution using our sample of 203 galaxy clusters detected in the 160 deg(2) survey with the ROSAT PSPC (Vikhlinin et al.). With such a large area survey, it is possible, for the first time with ROSAT, to test the evolution of luminous clusters, L......-X > 3 x 10(44) ergs s(-1) in the 0.5-2 keV band. We detect a factor of 3-4 deficit of such luminous clusters at z > 0.3 compared with the present. The evolution is much weaker or absent at modestly lower luminosities, (1-3) x 10(44) ergs s(-1). At still lower luminosities, we find no evolution from...... the analysis of the log N-log S relation. The results in the two upper L, bins are in agreement with the Einstein Extended Medium-Sensitivity Survey evolution result (Gioia et al.; Henry ct al.), which was obtained using a completely independent cluster sample. The low-L-X results are in agreement with other...

  1. Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

    Energy Technology Data Exchange (ETDEWEB)

    Abbott, T.M.C.; et al.

    2017-08-04

    We present cosmological results from a combined analysis of galaxy clustering and weak gravitational lensing, using 1321 deg$^2$ of $griz$ imaging data from the first year of the Dark Energy Survey (DES Y1). We combine three two-point functions: (i) the cosmic shear correlation function of 26 million source galaxies in four redshift bins, (ii) the galaxy angular autocorrelation function of 650,000 luminous red galaxies in five redshift bins, and (iii) the galaxy-shear cross-correlation of luminous red galaxy positions and source galaxy shears. To demonstrate the robustness of these results, we use independent pairs of galaxy shape, photometric redshift estimation and validation, and likelihood analysis pipelines. To prevent confirmation bias, the bulk of the analysis was carried out while blind to the true results; we describe an extensive suite of systematics checks performed and passed during this blinded phase. The data are modeled in flat $\\Lambda$CDM and $w$CDM cosmologies, marginalizing over 20 nuisance parameters, varying 6 (for $\\Lambda$CDM) or 7 (for $w$CDM) cosmological parameters including the neutrino mass density and including the 457 $\\times$ 457 element analytic covariance matrix. We find consistent cosmological results from these three two-point functions, and from their combination obtain $S_8 \\equiv \\sigma_8 (\\Omega_m/0.3)^{0.5} = 0.783^{+0.021}_{-0.025}$ and $\\Omega_m = 0.264^{+0.032}_{-0.019}$ for $\\Lambda$CDM for $w$CDM, we find $S_8 = 0.794^{+0.029}_{-0.027}$, $\\Omega_m = 0.279^{+0.043}_{-0.022}$, and $w=-0.80^{+0.20}_{-0.22}$ at 68% CL. The precision of these DES Y1 results rivals that from the Planck cosmic microwave background measurements, allowing a comparison of structure in the very early and late Universe on equal terms. Although the DES Y1 best-fit values for $S_8$ and $\\Omega_m$ are lower than the central values from Planck ...

  2. Cluster as a wave telescope – first results from the fluxgate magnetometer

    Directory of Open Access Journals (Sweden)

    K.-H. Glassmeier

    Full Text Available The four Cluster spacecraft provide an excellent opportunity to study spatial structures in the magnetosphere and adjacent regions. Propagating waves are amongst the interesting structures and for the first time, Cluster will allow one to measure the wave vector of low-frequency fluctuations in a space plasma. Based on a generalized minimum variance analysis wave vector estimates will be determined in the terrestrial magnetosheath and the near-Earth solar wind. The virtue and weakness of the wave telescope technique used is discussed in detail.

    Key words. Electromagnetics (wave propagation – Magnetospheric physics (MHD waves and instabilities; plasma waves and instabilities

  3. Cluster as a wave telescope – first results from the fluxgate magnetometer

    Directory of Open Access Journals (Sweden)

    K.-H. Glassmeier

    2001-09-01

    Full Text Available The four Cluster spacecraft provide an excellent opportunity to study spatial structures in the magnetosphere and adjacent regions. Propagating waves are amongst the interesting structures and for the first time, Cluster will allow one to measure the wave vector of low-frequency fluctuations in a space plasma. Based on a generalized minimum variance analysis wave vector estimates will be determined in the terrestrial magnetosheath and the near-Earth solar wind. The virtue and weakness of the wave telescope technique used is discussed in detail.Key words. Electromagnetics (wave propagation – Magnetospheric physics (MHD waves and instabilities; plasma waves and instabilities

  4. Planck intermediate results. X. Physics of the hot gas in the Coma cluster

    DEFF Research Database (Denmark)

    Planck Collaboration,; Ade, P. A. R.; Aghanim, N.

    2013-01-01

    We present an analysis of Planck satellite data on the Coma Cluster observed via the Sunyaev-Zeldovich effect. Planck is able, for the first time, to detect SZ emission up to r ~ 3 X R_500. We test previously proposed models for the pressure distribution in clusters against the azimuthally averaged...... data. We find that the Arnaud et al. universal pressure profile does not fit Coma, and that their pressure profile for merging systems provides a good fit of the data only at rR_500 than the mean pressure profile predicted by the simulations. The Planck image shows significant local steepening of the y...

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

    DEFF Research Database (Denmark)

    Poutanen, T.; Natoli, P.; Polenta, G.

    2011-01-01

    We present the XMM-Newton follow-up for confirmation of Planck cluster candidates. Twenty-five candidates have been observed to date using snapshot (∼10 ks) exposures, ten as part of a pilot programme to sample a low range of signal-to-noise ratios (4

  6. Planck intermediate results: III. the relation between galaxy cluster mass and Sunyaev-Zeldovich signal

    DEFF Research Database (Denmark)

    Bartlett, J.G.; Bucher, M.; Cardoso, J.-F.

    2013-01-01

    We examine the relation between the galaxy cluster mass M and Sunyaev-Zeldovich (SZ) effect signal DA2 Y500 for a sample of 19 objects for which weak lensing (WL) mass measurements obtained from Subaru Telescope data are available in the literature. Hydrostatic X-ray masses are derived from XMM-N...

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

    DEFF Research Database (Denmark)

    Poutanen, T.; Natoli, P.; Polenta, G.

    2011-01-01

    We present precise Sunyaev-Zeldovich (SZ) effect measurements in the direction of 62 nearby galaxy clusters (z <0.5) detected at high signal-to-noise in the first Planck all-sky data set. The sample spans approximately a decade in total mass, 2 × 1014 M

  8. Planck 2013 results. XX. Cosmology from Sunyaev-Zeldovich cluster counts

    DEFF Research Database (Denmark)

    Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.

    2013-01-01

    We present constraints on cosmological parameters using number counts as a function of redshift for a sub-sample of 189 galaxy clusters from the Planck SZ (PSZ) catalogue. The PSZ is selected through the signature of the Sunyaev-Zeldovich (SZ) effect, and the sub-sample used here has a signal-to-...

  9. Planck intermediate results: XLIII. Spectral energy distribution of dust in clusters of galaxies

    DEFF Research Database (Denmark)

    Adam, R.; Ade, P. A R; Aghanim, N.

    2016-01-01

    Although infrared (IR) overall dust emission from clusters of galaxies has been statistically detected using data from the Infrared Astronomical Satellite (IRAS), it has not been possible to sample the spectral energy distribution (SED) of this emission over its peak, and thus to break the degene...

  10. Planck early results. VIII. The all-sky early Sunyaev-Zeldovich cluster sample

    DEFF Research Database (Denmark)

    Poutanen, T.; Natoli, P.; Polenta, G.

    2011-01-01

    We present the first all-sky sample of galaxy clusters detected blindly by the Planck satellite through the Sunyaev-Zeldovich (SZ) effect from its six highest frequencies. This early SZ (ESZ) sample is comprised of 189 candidates, which have a high signal-to-noise ratio ranging from 6 to 29. Its ...

  11. First results from the IllustrisTNG simulations: matter and galaxy clustering

    Science.gov (United States)

    Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill

    2018-03-01

    Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.

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

    Directory of Open Access Journals (Sweden)

    Ahmed Abdullah

    2015-06-01

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

  13. Relation between financial market structure and the real economy: comparison between clustering methods.

    Science.gov (United States)

    Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T

    2015-01-01

    We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  14. Relation between financial market structure and the real economy: comparison between clustering methods.

    Directory of Open Access Journals (Sweden)

    Nicoló Musmeci

    Full Text Available We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  15. Brightest Cluster Galaxies in REXCESS Clusters

    Science.gov (United States)

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

    2009-01-01

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

  16. Hierarchical Sets: Analyzing Pangenome Structure through Scalable Set Visualizations

    DEFF Research Database (Denmark)

    Pedersen, Thomas Lin

    2017-01-01

    of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https...

  17. Automated tetraploid genotype calling by hierarchical clustering

    Science.gov (United States)

    SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, however, the relationship between signal intensity and allele dosage must be inferred independently for each marker. We developed an improved computational method to automate this process, ...

  18. Planck 2013 results. XX. Cosmology from Sunyaev-Zeldovich cluster counts

    CERN Document Server

    Ade, P.A.R.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A.J.; Barreiro, R.B.; Barrena, R.; Bartlett, J.G.; Battaner, E.; Battye, R.; Benabed, K.; Benoit, A.; Benoit-Levy, A.; Bernard, J.P.; Bersanelli, M.; Bielewicz, P.; Bikmaev, I.; Blanchard, A.; Bobin, J.; Bock, J.J.; Bohringer, H.; Bonaldi, A.; Bond, J.R.; Borrill, J.; Bouchet, F.R.; Bourdin, H.; Bridges, M.; Brown, M.L.; Bucher, M.; Burenin, R.; Burigana, C.; Butler, R.C.; Cardoso, J.F.; Carvalho, P.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.R.; Chiang, L.Y.; Chiang, H.C.; Chon, G.; Christensen, P.R.; Church, S.; Clements, D.L.; Colombi, S.; Colombo, L.P.L.; Couchot, F.; Coulais, A.; Crill, B.P.; Curto, A.; Cuttaia, F.; Da Silva, A.; Dahle, H.; Danese, L.; Davies, R.D.; Davis, R.J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.M.; Democles, J.; Desert, F.X.; Dickinson, C.; Diego, J.M.; Dolag, K.; Dole, H.; Donzelli, S.; Dore, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Ensslin, T.A.; Eriksen, H.K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Frailis, M.; Franceschi, E.; Fromenteau, S.; Galeotta, S.; Ganga, K.; Genova-Santos, R.T.; Giard, M.; Giardino, G.; Giraud-Heraud, Y.; Gonzalez-Nuevo, J.; Gorski, K.M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F.K.; Hanson, D.; Harrison, D.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Herranz, D.; Hildebrandt, S.R.; Hivon, E.; Hobson, M.; Holmes, W.A.; Hornstrup, A.; Hovest, W.; Huffenberger, K.M.; Hurier, G.; Jaffe, T.R.; Jaffe, A.H.; Jones, W.C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Khamitov, I.; Kisner, T.S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lahteenmaki, A.; Lamarre, J.M.; Lasenby, A.; Laureijs, R.J.; Lawrence, C.R.; Leahy, J.P.; Leonardi, R.; Leon-Tavares, J.; Lesgourgues, J.; Liddle, A.; Liguori, M.; Lilje, P.B.; Linden-Vornle, M.; Lopez-Caniego, M.; Lubin, P.M.; Macias-Perez, J.F.; Maffei, B.; Maino, D.; Mandolesi, N.; Marcos-Caballero, A.; Maris, M.; Marshall, D.J.; Martin, P.G.; Martinez-Gonzalez, E.; Masi, S.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Meinhold, P.R.; Melchiorri, A.; Melin, J.B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschenes, M.A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C.B.; Norgaard-Nielsen, H.U.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C.A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G.W.; Prezeau, G.; Prunet, S.; Puget, J.L.; Rachen, J.P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Roudier, G.; Rowan-Robinson, M.; Rubino-Martin, J.A.; Rusholme, B.; Sandri, M.; Santos, D.; Savini, G.; Scott, D.; Seiffert, M.D.; Shellard, E.P.S.; Spencer, L.D.; Starck, J.L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.S.; Sygnet, J.F.; Tauber, J.A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Turler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L.A.; Wandelt, B.D.; Weller, J.; White, M.; White, S.D.M.; Yvon, D.; Zacchei, A.; Zonca, A.

    2014-01-01

    We present constraints on cosmological parameters using number counts as a function of redshift for a sub-sample of 189 galaxy clusters from the Planck SZ (PSZ) catalogue. The PSZ is selected through the signature of the Sunyaev--Zeldovich (SZ) effect, and the sub-sample used here has a signal-to-noise threshold of seven, with each object confirmed as a cluster and all but one with a redshift estimate. We discuss the completeness of the sample and our construction of a likelihood analysis. Using a relation between mass $M$ and SZ signal $Y$ calibrated to X-ray measurements, we derive constraints on the power spectrum amplitude $\\sigma_8$ and matter density parameter $\\Omega_{\\mathrm{m}}$ in a flat $\\Lambda$CDM model. We test the robustness of our estimates and find that possible biases in the $Y$--$M$ relation and the halo mass function are larger than the statistical uncertainties from the cluster sample. Assuming the X-ray determined mass to be biased low relative to the true mass by between zero and 30%, m...

  19. First results from the RAPID imaging energetic particle spectrometer on board Cluster

    Directory of Open Access Journals (Sweden)

    B. Wilken

    Full Text Available The advanced energetic particle spectrometer RAPID on board Cluster can provide a complete description of the relevant particle parameters velocity, V , and atomic mass, A, over an energy range from 30 keV up to 1.5 MeV. We present the first measurements taken by RAPID during the commissioning and the early operating phases. The orbit on 14 January 2001, when Cluster was travelling from a perigee near dawn northward across the pole towards an apogee in the solar wind, is used to demonstrate the capabilities of RAPID in investigating a wide variety of particle populations. RAPID, with its unique capability of measuring the complete angular distribution of energetic particles, allows for the simultaneous measurements of local density gradients, as reflected in the anisotropies of 90° particles and the remote sensing of changes in the distant field line topology, as manifested in the variations of loss cone properties. A detailed discussion of angle-angle plots shows considerable differences in the structure of the boundaries between the open and closed field lines on the nightside fraction of the pass and the magnetopause crossing. The 3 March 2001 encounter of Cluster with an FTE just outside the magnetosphere is used to show the first structural plasma investigations of an FTE by energetic multi-spacecraft observations.

    Key words. Magnetospheric physics (energetic particles, trapped; magnetopause, cusp and boundary layers; magnetosheath

  20. First results from the RAPID imaging energetic particle spectrometer on board Cluster

    Directory of Open Access Journals (Sweden)

    B. Wilken

    2001-09-01

    Full Text Available The advanced energetic particle spectrometer RAPID on board Cluster can provide a complete description of the relevant particle parameters velocity, V , and atomic mass, A, over an energy range from 30 keV up to 1.5 MeV. We present the first measurements taken by RAPID during the commissioning and the early operating phases. The orbit on 14 January 2001, when Cluster was travelling from a perigee near dawn northward across the pole towards an apogee in the solar wind, is used to demonstrate the capabilities of RAPID in investigating a wide variety of particle populations. RAPID, with its unique capability of measuring the complete angular distribution of energetic particles, allows for the simultaneous measurements of local density gradients, as reflected in the anisotropies of 90° particles and the remote sensing of changes in the distant field line topology, as manifested in the variations of loss cone properties. A detailed discussion of angle-angle plots shows considerable differences in the structure of the boundaries between the open and closed field lines on the nightside fraction of the pass and the magnetopause crossing. The 3 March 2001 encounter of Cluster with an FTE just outside the magnetosphere is used to show the first structural plasma investigations of an FTE by energetic multi-spacecraft observations.Key words. Magnetospheric physics (energetic particles, trapped; magnetopause, cusp and boundary layers; magnetosheath

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

    DEFF Research Database (Denmark)

    Bartlett, J.G.; Cardoso, J.-F.; Castex, G.

    2013-01-01

    that most clusters are individually detected at least out to R500. By stacking the radial profiles, we have statistically detected the radial SZ signal out to 3 × R500, i.e., at a density contrast of about 50-100, though the dispersion about the mean profile dominates the statistical errors across the whole......Taking advantage of the all-sky coverage and broadfrequency range of the Planck satellite, we study the Sunyaev-Zeldovich (SZ) and pressure profiles of 62 nearby massive clusters detected at high significance in the 14-month nominal survey. Careful reconstruction of the SZ signal indicates...... flatter than most predictions from numerical simulations. Combining the SZ and X-ray observed profiles into a joint fit to a generalised pressure profile gives best-fit parameters [P0,c500,γ, α,β] = [6.41,1.81,0.31,1.33,4.13]. Using a reasonable hypothesis for the gas temperature in the cluster outskirts...

  2. Why do ultrasoft repulsive particles cluster and crystallize? Analytical results from density-functional theory.

    Science.gov (United States)

    Likos, Christos N; Mladek, Bianca M; Gottwald, Dieter; Kahl, Gerhard

    2007-06-14

    We demonstrate the accuracy of the hypernetted chain closure and of the mean-field approximation for the calculation of the fluid-state properties of systems interacting by means of bounded and positive pair potentials with oscillating Fourier transforms. Subsequently, we prove the validity of a bilinear, random-phase density functional for arbitrary inhomogeneous phases of the same systems. On the basis of this functional, we calculate analytically the freezing parameters of the latter. We demonstrate explicitly that the stable crystals feature a lattice constant that is independent of density and whose value is dictated by the position of the negative minimum of the Fourier transform of the pair potential. This property is equivalent with the existence of clusters, whose population scales proportionally to the density. We establish that regardless of the form of the interaction potential and of the location on the freezing line, all cluster crystals have a universal Lindemann ratio Lf=0.189 at freezing. We further make an explicit link between the aforementioned density functional and the harmonic theory of crystals. This allows us to establish an equivalence between the emergence of clusters and the existence of negative Fourier components of the interaction potential. Finally, we make a connection between the class of models at hand and the system of infinite-dimensional hard spheres, when the limits of interaction steepness and space dimension are both taken to infinity in a particularly described fashion.

  3. New Heterogeneous Clustering Protocol for Prolonging Wireless Sensor Networks Lifetime

    Directory of Open Access Journals (Sweden)

    Md. Golam Rashed

    2014-06-01

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

  4. Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

    Directory of Open Access Journals (Sweden)

    Mohammad Nur Shodiq

    2016-03-01

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

  5. Study on distributed re-clustering algorithm for moblie wireless sensor networks

    Directory of Open Access Journals (Sweden)

    XU Chaojie

    2016-04-01

    Full Text Available In mobile wireless sensor networks,node mobility influences the topology of the hierarchically clustered network,thus affects packet delivery ratio and energy consumption of communications in clusters.To reduce the influence of node mobility,a distributed re-clustering algorithm is proposed in this paper.In this algorithm,basing on the clustered network,nodes estimate their current locations with particle algorithm and predict the most possible locations of next time basing on the mobility model.Each boundary node of a cluster periodically estimates the need for re-clustering and re-cluster itself to the optimal cluster through communicating with the cluster headers when needed.The simulation results indicate that,with small re-clustering periods,the proposed algorithm can be effective to keep appropriate communication distance and outperforms existing schemes on packet delivery ratio and energy consumption.

  6. Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

    Science.gov (United States)

    Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

    2012-11-01

    This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

  7. Inadequacy of ethical conduct and reporting of stepped wedge cluster randomized trials: Results from a systematic review.

    Science.gov (United States)

    Taljaard, Monica; Hemming, Karla; Shah, Lena; Giraudeau, Bruno; Grimshaw, Jeremy M; Weijer, Charles

    2017-08-01

    Background/aims The use of the stepped wedge cluster randomized design is rapidly increasing. This design is commonly used to evaluate health policy and service delivery interventions. Stepped wedge cluster randomized trials have unique characteristics that complicate their ethical interpretation. The 2012 Ottawa Statement provides comprehensive guidance on the ethical design and conduct of cluster randomized trials, and the 2010 CONSORT extension for cluster randomized trials provides guidelines for reporting. Our aims were to assess the adequacy of the ethical conduct and reporting of stepped wedge trials to date, focusing on research ethics review and informed consent. Methods We conducted a systematic review of stepped wedge cluster randomized trials in health research published up to 2014 in English language journals. We extracted details of study intervention and data collection procedures, as well as reporting of research ethics review and informed consent. Two reviewers independently extracted data from each trial; discrepancies were resolved through discussion. We identified the presence of any research participants at the cluster level and the individual level. We assessed ethical conduct by tabulating reporting of research ethics review and informed consent against the presence of research participants. Results Of 32 identified stepped wedge trials, only 24 (75%) reported review by a research ethics committee, and only 16 (50%) reported informed consent from any research participants-yet, all trials included research participants at some level. In the subgroup of 20 trials with research participants at cluster level, only 4 (20%) reported informed consent from such participants; in 26 trials with individual-level research participants, only 15 (58%) reported their informed consent. Interventions (regardless of whether targeting cluster- or individual-level participants) were delivered at the group level in more than two-thirds of trials; nine trials (28

  8. Polar cap ion beams during periods of northward IMF: Cluster statistical results

    Directory of Open Access Journals (Sweden)

    R. Maggiolo

    2011-05-01

    Full Text Available Above the polar caps and during prolonged periods of northward IMF, the Cluster satellites detect upward accelerated ion beams with energies up to a few keV. They are associated with converging electric field structures indicating that the acceleration is caused by a quasi-static field-aligned electric field that can extend to altitudes higher than 7 RE (Maggiolo et al., 2006; Teste et al., 2007. Using the AMDA science analysis service provided by the Centre de Données de la Physique des Plasmas, we have been able to extract about 200 events of accelerated upgoing ion beams above the polar caps from the Cluster database. Most of these observations are taken at altitudes lower than 7 RE and in the Northern Hemisphere. We investigate the statistical properties of these ion beams. We analyze their geometry, the properties of the plasma populations and of the electric field inside and around the beams, as well as their dependence on solar wind and IMF conditions. We show that ~40 % of the ion beams are collocated with a relatively hot and isotropic plasma population. The density and temperature of the isotropic population are highly variable but suggest that this plasma originates from the plasma sheet. The ion beam properties do not change significantly when the isotropic, hot background population is present. Furthermore, during one single polar cap crossing by Cluster it is possible to detect upgoing ion beams both with and without an accompanying isotropic component. The analysis of the variation of the IMF BZ component prior to the detection of the beams indicates that the delay between a northward/southward turning of IMF and the appearance/disappearance of the beams is respectively ~2 h and 20 min. The observed electrodynamic characteristics of high altitude polar cap ion beams suggest that they are closely connected to polar cap auroral arcs. We discuss the implications of these Cluster observations above the polar cap on the magnetospheric

  9. Isotopic clusters

    International Nuclear Information System (INIS)

    Geraedts, J.M.P.

    1983-01-01

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

  10. A Cluster Analysis of Personality Style in Adults with ADHD

    Science.gov (United States)

    Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

    2008-01-01

    Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

  11. Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

    Directory of Open Access Journals (Sweden)

    Yimei Wang

    2018-04-01

    Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

  12. The effect of different position of grape clusters on the bearing shoot on production results of Cabernet Sauvignon clones

    Directory of Open Access Journals (Sweden)

    Čoloveić Ana

    2014-01-01

    Full Text Available In this paper the differences were examined between clones of Cabernet sauvignon (clones ISV-F-V5, ISV-F-V6 and R5, i.e. the difference between uvological properties of grape clusters and grape berries, based on the different positions on the bearing shoot. Tests were conducted at the experimental field of the Faculty of Agriculture 'Radmilovac'. Standard ampelographic methods were used in numerous analyses of grape yield, as well as uvological properties of clones. All data were statistically analyzed and processed by the method of two-factor analysis of variance with repeated measuring of one factor (height and Tukey HSD test. Analysis of variance showed no significant differences between clones. The best results were achieved with grape clusters positioned in the base of bearing shoot. The first positioned grape clusters on the bearing shoot had the highest share in the total grape yield, the highest amount of sugar, and the highest positioned grape clusters had higher content of total acids. The differences determined between examined clones were in regard to productivity and quality of grapes which reflected also on production value.

  13. Planck intermediate results XL. The Sunyaev-Zeldovich signal from the Virgo cluster

    DEFF Research Database (Denmark)

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

    2016-01-01

    The Virgo cluster is the largest Sunyaev-Zeldovich (SZ) source in the sky, both in terms of angular size and total integrated flux. Planck's wide angular scale and frequency coverage, together with its high sensitivity, enable a detailed study of this big object through the SZ effect. Virgo is well...... and a constrained simulation of the environment of Virgo. Planck data suggest that significant amounts of low-density plasma surround Virgo, out to twice the virial radius. We find the SZ signal in the outskirts of Virgo to be consistent with a simple model that extrapolates the inferred pressure at lower radii...... warm/hot intergalactic medium. Taking the lack of symmetry of Virgo into account, we find that a prolate model is favoured by the combination of SZ and X-ray data, in agreement with predictions. Finally, based on the combination of the same SZ and X-ray data, we constrain the total amount of gas...

  14. First Cluster results of the magnetic field structure of the mid- and high-altitude cusps

    Directory of Open Access Journals (Sweden)

    P. J. Cargill

    Full Text Available Magnetic field measurements from the four Cluster spacecraft from the mid- and high-altitude cusp are presented. Cluster underwent two encounters with the mid-altitude cusp during its commissioning phase (24 August 2000. Evidence for field-aligned currents (FACs was seen in the data from all three operating spacecraft from northern and southern cusps. The extent of the FACs was of the order of 1 RE in the X-direction, and at least 300 km in the Y-direction. However, fine-scale field structures with scales of the order of the spacecraft separation (300 km were observed within the FACs. In the northern crossing, two of the spacecraft appeared to lie along the same magnetic field line, and observed very well matched signals. However, the third spacecraft showed evidence for structuring transverse to the field on scales of a few hundred km. A crossing of the high-altitude cusp from 13 February 2001 is presented. It is revealed to be a highly dynamic structure with the boundaries moving with velocities ranging from a few km/s to tens of km/s, and having structure on timescales ranging from less than one minute up to several minutes. The cusp proper is associated with the presence of a very disordered magnetic field, which is entirely different from the magnetosheath turbulence.

    Key words. Magnetospheric physics (current systems; magnetopause, cusp, and boundary layers – Space plasma physics (discontinuities

  15. Hierarchical structure of the European countries based on debts as a percentage of GDP during the 2000-2011 period

    Science.gov (United States)

    Kantar, Ersin; Deviren, Bayram; Keskin, Mustafa

    2014-11-01

    We investigate hierarchical structures of the European countries by using debt as a percentage of Gross Domestic Product (GDP) of the countries as they change over a certain period of time. We obtain the topological properties among the countries based on debt as a percentage of GDP of European countries over the period 2000-2011 by using the concept of hierarchical structure methods (minimal spanning tree, (MST) and hierarchical tree, (HT)). This period is also divided into two sub-periods related to 2004 enlargement of the European Union, namely 2000-2004 and 2005-2011, in order to test various time-window and observe the temporal evolution. The bootstrap techniques is applied to see a value of statistical reliability of the links of the MSTs and HTs. The clustering linkage procedure is also used to observe the cluster structure more clearly. From the structural topologies of these trees, we identify different clusters of countries according to their level of debts. Our results show that by the debt crisis, the less and most affected Eurozone’s economies are formed as a cluster with each other in the MSTs and hierarchical trees.

  16. Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

    Science.gov (United States)

    Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

    2017-07-19

    Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

  17. Hierarchical MAS based control strategy for microgrid

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Z.; Li, T.; Huang, M.; Shi, J.; Yang, J.; Yu, J. [School of Information Science and Engineering, Yunnan University, Kunming 650091 (China); Xiao, Z. [School of Electrical and Electronic Engineering, Nanyang Technological University, Western Catchment Area, 639798 (Singapore); Wu, W. [Communication Branch of Yunnan Power Grid Corporation, Kunming, Yunnan 650217 (China)

    2010-09-15

    Microgrids have become a hot topic driven by the dual pressures of environmental protection concerns and the energy crisis. In this paper, a challenge for the distributed control of a modern electric grid incorporating clusters of residential microgrids is elaborated and a hierarchical multi-agent system (MAS) is proposed as a solution. The issues of how to realize the hierarchical MAS and how to improve coordination and control strategies are discussed. Based on MATLAB and ZEUS platforms, bilateral switching between grid-connected mode and island mode is performed under control of the proposed MAS to enhance and support its effectiveness. (authors)

  18. Planck intermediate results: XL. The Sunyaev-Zeldovich signal from the Virgo cluster

    International Nuclear Information System (INIS)

    Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.

    2016-01-01

    The Virgo cluster is the largest Sunyaev-Zeldovich (SZ) source in the sky, both in terms of angular size and total integrated flux. Planck’s wide angular scale and frequency coverage, together with its high sensitivity, enable a detailed study of this big object through the SZ effect. Virgo is well resolved by Planck, showing an elongated structure that correlates well with the morphology observed from X-rays, but extends beyond the observed X-ray signal. We find good agreement between the SZ signal (or Compton parameter, y_c) observed by Planck and the expected signal inferred from X-ray observations and simple analytical models. Owing to its proximity to us, the gas beyond the virial radius in Virgo can be studied with unprecedented sensitivity by integrating the SZ signal over tens of square degrees. In this paper, we study the signal in the outskirts of Virgo and compare it with analytical models and a constrained simulation of the environment of Virgo. Planck data suggest that significant amounts of low-density plasma surround Virgo, out to twice the virial radius. We find the SZ signal in the outskirts of Virgo to be consistent with a simple model that extrapolates the inferred pressure at lower radii, while assuming that the temperature stays in the keV range beyond the virial radius. The observed signal is also consistent with simulations and points to a shallow pressure profile in the outskirts of the cluster. This reservoir of gas at large radii can be linked with the hottest phase of the elusivewarm/hot intergalactic medium. Taking the lack of symmetry of Virgo into account, we find that a prolate model is favoured by the combination of SZ and X-ray data, in agreement with predictions. In conclusion, based on the combination of the same SZ and X-ray data, we constrain the total amount of gas in Virgo. Under the hypothesis that the abundance of baryons in Virgo is representative of the cosmic average, we also infer a distance for Virgo of approximately

  19. Dietary habits and physical activity: Results from cluster analysis and market basket analysis.

    Science.gov (United States)

    Liew, Hui-Peng

    2018-01-01

    The prevalence of obesity remains a major public health concern and there has been a significant increase in childhood obesity in the USA. This study seeks to uncover the major patterns of dietary habits in relation to physical activity, together with students' opinions about the quality of food in the school's cafeteria and vending machines. The empirical work of this study is based on the 2011 Healthy School Program (HSP) Evaluation. HSP assesses the demographic characteristics as well as the dietary habits and exercise patterns of a representative sample of elementary, middle, and high school students in the USA. Findings suggest that students assigned to different clusters have different eating habits, exercise patterns, weight status, weight management, and opinions about the quality of food in the school's cafeteria and vending machines. There is great variation in dietary profiles and lifestyle behaviors among students who identified themselves as either overweight or unsure about their weight status. Findings from this study may inform future interventions regarding how to promote student's healthy food choices when they are still in school. Health promotion initiatives should specifically target students with persistently unhealthier dietary profiles.

  20. Energy Balance 4 Kids with Play: Results from a Two-Year Cluster-Randomized Trial.

    Science.gov (United States)

    Madsen, Kristine; Linchey, Jennifer; Gerstein, Dana; Ross, Michelle; Myers, Esther; Brown, Katie; Crawford, Patricia

    2015-08-01

    Identifying sustainable approaches to improving the physical activity (PA) and nutrition environments in schools is an important public health goal. This study examined the impact of Energy Balance for Kids with Play (EB4K with Play), a school-based intervention developed by the Academy of Nutrition and Dietetics Foundation and Playworks, on students' PA, dietary habits and knowledge, and weight status over 2 years. This cluster-randomized, controlled trial took place in four intervention and two control schools over 2 years (n=879; third- to fifth-grade students). PA (fourth and fifth grades only), dietary knowledge and behaviors, school policies, and BMI z-score were assessed at baseline (fall 2011), midpoint (spring 2012), and endpoint (fall 2012 for accelerometers; spring 2013 for all other outcomes). At endpoint, there were no group differences in change in PA or dietary behaviors, although BMI z-score decreased overall by -0.07 (p=0.05). Students' dietary knowledge significantly increased, as did the amount of vegetables schools served. Post-hoc analyses stratified by grade revealed that, relative to control students, fourth-grade intervention students reduced school-day sedentary time by 15 minutes (p=0.023) and third-grade intervention students reduced BMI z-score by -0.2 (0.05; pchildren's dietary knowledge and may improve weight status and decrease sedentary behaviors among younger children. Future iterations should examine programming specific for different age groups.

  1. Processing of hierarchical syntactic structure in music.

    Science.gov (United States)

    Koelsch, Stefan; Rohrmeier, Martin; Torrecuso, Renzo; Jentschke, Sebastian

    2013-09-17

    Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions in which the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with long-distance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

  2. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    OpenAIRE

    Chih-Yu Wen; Ying-Chih Chen

    2009-01-01

    This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show t...

  3. Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

    Science.gov (United States)

    Tilton, James C.

    2003-01-01

    A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic

  4. UVA-induced DNA double-strand breaks result from the repair of clustered oxidative DNA damages

    Science.gov (United States)

    Greinert, R.; Volkmer, B.; Henning, S.; Breitbart, E. W.; Greulich, K. O.; Cardoso, M. C.; Rapp, Alexander

    2012-01-01

    UVA (320–400 nm) represents the main spectral component of solar UV radiation, induces pre-mutagenic DNA lesions and is classified as Class I carcinogen. Recently, discussion arose whether UVA induces DNA double-strand breaks (dsbs). Only few reports link the induction of dsbs to UVA exposure and the underlying mechanisms are poorly understood. Using the Comet-assay and γH2AX as markers for dsb formation, we demonstrate the dose-dependent dsb induction by UVA in G1-synchronized human keratinocytes (HaCaT) and primary human skin fibroblasts. The number of γH2AX foci increases when a UVA dose is applied in fractions (split dose), with a 2-h recovery period between fractions. The presence of the anti-oxidant Naringin reduces dsb formation significantly. Using an FPG-modified Comet-assay as well as warm and cold repair incubation, we show that dsbs arise partially during repair of bi-stranded, oxidative, clustered DNA lesions. We also demonstrate that on stretched chromatin fibres, 8-oxo-G and abasic sites occur in clusters. This suggests a replication-independent formation of UVA-induced dsbs through clustered single-strand breaks via locally generated reactive oxygen species. Since UVA is the main component of solar UV exposure and is used for artificial UV exposure, our results shine new light on the aetiology of skin cancer. PMID:22941639

  5. Residential patterns in older homeless adults: Results of a cluster analysis.

    Science.gov (United States)

    Lee, Christopher Thomas; Guzman, David; Ponath, Claudia; Tieu, Lina; Riley, Elise; Kushel, Margot

    2016-03-01

    Adults aged 50 and older make up half of individuals experiencing homelessness and have high rates of morbidity and mortality. They may have different life trajectories and reside in different environments than do younger homeless adults. Although the environmental risks associated with homelessness are substantial, the environments in which older homeless individuals live have not been well characterized. We classified living environments and identified associated factors in a sample of older homeless adults. From July 2013 to June 2014, we recruited a community-based sample of 350 homeless men and women aged fifty and older in Oakland, California. We administered structured interviews including assessments of health, history of homelessness, social support, and life course. Participants used a recall procedure to describe where they stayed in the prior six months. We performed cluster analysis to classify residential venues and used multinomial logistic regression to identify individual factors prior to the onset of homelessness as well as the duration of unstable housing associated with living in them. We generated four residential groups describing those who were unsheltered (n = 162), cohabited unstably with friends and family (n = 57), resided in multiple institutional settings (shelters, jails, transitional housing) (n = 88), or lived primarily in rental housing (recently homeless) (n = 43). Compared to those who were unsheltered, having social support when last stably housed was significantly associated with cohabiting and institution use. Cohabiters and renters were significantly more likely to be women and have experienced a shorter duration of homelessness. Cohabiters were significantly more likely than unsheltered participants to have experienced abuse prior to losing stable housing. Pre-homeless social support appears to protect against street homelessness while low levels of social support may increase the risk for becoming homeless immediately after

  6. Hierarchical functional modularity in the resting-state human brain.

    Science.gov (United States)

    Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien

    2009-07-01

    Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

  7. [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.

  8. Characterisation of microcalcification clusters on 2D digital mammography (FFDM) and digital breast tomosynthesis (DBT): does DBT underestimate microcalcification clusters? Results of a multicentre study

    International Nuclear Information System (INIS)

    Tagliafico, Alberto; Mariscotti, Giovanna; Durando, Manuela; Stevanin, Carmen; Tagliafico, Giulio; Martino, Lucia; Bignotti, Bianca; Calabrese, Massimo; Houssami, Nehmat

    2015-01-01

    To compare DBT and FFDM in the classification of microcalcification clusters (MCs) using BI-RADS. This Institutional Review Board-approved study was undertaken in three centres. A total of 107 MCs evaluated with both DBT and FFDM were randomised for prospective reading by six experienced breast radiologists and classified using BI-RADS. The benign/malignant ratio of MC was 66/41. Of 11/107 discordant results, DBT classified MCs as R2 whereas FFDM classified them as R3 in 9 and R4 in 2. Three of these (3/107 = 2.8 %) were malignant; 8 (7.5 %) were nonmalignant and were correctly classified as R2 on DBT but incorrectly classified as R3 on FFDM. Estimated sensitivity and specificity, respectively, were 100 % (95 % CI: 91 % to 100 %) and 94.6 % (95 % CI: 86.7 % to 98.5 %) for FFDM and 91.1 % (95 % CI: 78.8 % to 97.5 %) and 100 % (95 % CI: 94.8 % to 100 %) for DBT. Overall intra- and interobserver agreements were 0.75 (95 % CI: 0.61-0.84) and 0.73 (95 % CI: 0.62-0.78). Most MCs are scored similarly on FFDM and DBT. Although a minority (11/107) of MCs are classified differently on FFDM (benign MC classified as R3) and DBT (malignant MC classified as R2), this may have clinical relevance. (orig.)

  9. Characterisation of microcalcification clusters on 2D digital mammography (FFDM) and digital breast tomosynthesis (DBT): does DBT underestimate microcalcification clusters? Results of a multicentre study

    Energy Technology Data Exchange (ETDEWEB)

    Tagliafico, Alberto [University of Genoa, Institute of Anatomy, Department of Experimental Medicine (DIMES), Genoa (Italy); Mariscotti, Giovanna; Durando, Manuela [Azienda Ospedaliero-Universitaria Citta della Salute e della Scienza di Torino, Radiology University of Torino, Department of Diagnostic Imaging and Radiotherapy, Torino (Italy); Stevanin, Carmen [Ospedale Regionale di Bolzano, Bolzano (Italy); Tagliafico, Giulio [Istituto di Matematica Applicata e Tecnologie Informatiche, CNR-IMATI, Consiglio Nazionale delle Ricerche, Genova (Italy); Martino, Lucia; Bignotti, Bianca [University of Genoa, Department of Health Sciences (DISSAL), Genoa (Italy); Calabrese, Massimo [IRCCS AOU San Martino-IST, Department of Breast Radiology, Genova (Italy); Houssami, Nehmat [University of Sydney, Screening and Test Evaluation Program (STEP), School of Public Health, Sydney Medical School, Sydney (Australia)

    2015-01-15

    To compare DBT and FFDM in the classification of microcalcification clusters (MCs) using BI-RADS. This Institutional Review Board-approved study was undertaken in three centres. A total of 107 MCs evaluated with both DBT and FFDM were randomised for prospective reading by six experienced breast radiologists and classified using BI-RADS. The benign/malignant ratio of MC was 66/41. Of 11/107 discordant results, DBT classified MCs as R2 whereas FFDM classified them as R3 in 9 and R4 in 2. Three of these (3/107 = 2.8 %) were malignant; 8 (7.5 %) were nonmalignant and were correctly classified as R2 on DBT but incorrectly classified as R3 on FFDM. Estimated sensitivity and specificity, respectively, were 100 % (95 % CI: 91 % to 100 %) and 94.6 % (95 % CI: 86.7 % to 98.5 %) for FFDM and 91.1 % (95 % CI: 78.8 % to 97.5 %) and 100 % (95 % CI: 94.8 % to 100 %) for DBT. Overall intra- and interobserver agreements were 0.75 (95 % CI: 0.61-0.84) and 0.73 (95 % CI: 0.62-0.78). Most MCs are scored similarly on FFDM and DBT. Although a minority (11/107) of MCs are classified differently on FFDM (benign MC classified as R3) and DBT (malignant MC classified as R2), this may have clinical relevance. (orig.)

  10. Efficacy of an internet-based learning module and small-group debriefing on trainees' attitudes and communication skills toward patients with substance use disorders: results of a cluster randomized controlled trial.

    Science.gov (United States)

    Lanken, Paul N; Novack, Dennis H; Daetwyler, Christof; Gallop, Robert; Landis, J Richard; Lapin, Jennifer; Subramaniam, Geetha A; Schindler, Barbara A

    2015-03-01

    To examine whether an Internet-based learning module and small-group debriefing can improve medical trainees' attitudes and communication skills toward patients with substance use disorders (SUDs). In 2011-2012, 129 internal and family medicine residents and 370 medical students at two medical schools participated in a cluster randomized controlled trial, which assessed the effect of adding a two-part intervention to the SUDs curricula. The intervention included a self-directed, media-rich Internet-based learning module and a small-group, faculty-led debriefing. Primary study outcomes were changes in self-assessed attitudes in the intervention group (I-group) compared with those in the control group (C-group) (i.e., a difference of differences). For residents, the authors used real-time, Web-based interviews of standardized patients to assess changes in communication skills. Statistical analyses, conducted separately for residents and students, included hierarchical linear modeling, adjusted for site, participant type, cluster, and individual scores at baseline. The authors found no significant differences between the I- and C-groups in attitudes for residents or students at baseline. Compared with those in the C-group, residents, but not students, in the I-group had more positive attitudes toward treatment efficacy and self-efficacy at follow-up (Pcommunication skills toward patients with SUDs among residents. Enhanced attitudes and skills may result in improved care for these patients.

  11. Impact of an automated email notification system for results of tests pending at discharge: a cluster-randomized controlled trial.

    Science.gov (United States)

    Dalal, Anuj K; Roy, Christopher L; Poon, Eric G; Williams, Deborah H; Nolido, Nyryan; Yoon, Cathy; Budris, Jonas; Gandhi, Tejal; Bates, David W; Schnipper, Jeffrey L

    2014-01-01

    Physician awareness of the results of tests pending at discharge (TPADs) is poor. We developed an automated system that notifies responsible physicians of TPAD results via secure, network email. We sought to evaluate the impact of this system on self-reported awareness of TPAD results by responsible physicians, a necessary intermediary step to improve management of TPAD results. We conducted a cluster-randomized controlled trial at a major hospital affiliated with an integrated healthcare delivery network in Boston, Massachusetts. Adult patients with TPADs who were discharged from inpatient general medicine and cardiology services were assigned to the intervention or usual care arm if their inpatient attending physician and primary care physician (PCP) were both randomized to the same study arm. Patients of physicians randomized to discordant study arms were excluded. We surveyed these physicians 72 h after all TPAD results were finalized. The primary outcome was awareness of TPAD results by attending physicians. Secondary outcomes included awareness of TPAD results by PCPs, awareness of actionable TPAD results, and provider satisfaction. We analyzed data on 441 patients. We sent 441 surveys to attending physicians and 353 surveys to PCPs and received 275 and 152 responses from 83 different attending physicians and 112 different PCPs, respectively (attending physician survey response rate of 63%). Intervention attending physicians and PCPs were significantly more aware of TPAD results (76% vs 38%, adjusted/clustered OR 6.30 (95% CI 3.02 to 13.16), pemail notification represents a promising strategy for managing TPAD results, potentially mitigating an unresolved patient safety concern. ClinicalTrials.gov (NCT01153451).

  12. K-nearest uphill clustering in the protein structure space

    KAUST Repository

    Cui, Xuefeng

    2016-08-26

    The protein structure classification problem, which is to assign a protein structure to a cluster of similar proteins, is one of the most fundamental problems in the construction and application of the protein structure space. Early manually curated protein structure classifications (e.g., SCOP and CATH) are very successful, but recently suffer the slow updating problem because of the increased throughput of newly solved protein structures. Thus, fully automatic methods to cluster proteins in the protein structure space have been designed and developed. In this study, we observed that the SCOP superfamilies are highly consistent with clustering trees representing hierarchical clustering procedures, but the tree cutting is very challenging and becomes the bottleneck of clustering accuracy. To overcome this challenge, we proposed a novel density-based K-nearest uphill clustering method that effectively eliminates noisy pairwise protein structure similarities and identifies density peaks as cluster centers. Specifically, the density peaks are identified based on K-nearest uphills (i.e., proteins with higher densities) and K-nearest neighbors. To our knowledge, this is the first attempt to apply and develop density-based clustering methods in the protein structure space. Our results show that our density-based clustering method outperforms the state-of-the-art clustering methods previously applied to the problem. Moreover, we observed that computational methods and human experts could produce highly similar clusters at high precision values, while computational methods also suggest to split some large superfamilies into smaller clusters. © 2016 Elsevier B.V.

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

    Science.gov (United States)

    Alexander, Nathan; Woetzel, Nils; Meiler, Jens

    2011-02-01

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

  14. Clustering of health-related behaviors among early and mid-adolescents in Tuscany: results from a representative cross-sectional study.

    Science.gov (United States)

    Lazzeri, Giacomo; Panatto, Donatella; Domnich, Alexander; Arata, Lucia; Pammolli, Andrea; Simi, Rita; Giacchi, Mariano Vincenzo; Amicizia, Daniela; Gasparini, Roberto

    2018-03-01

    A huge amount of literature suggests that adolescents' health-related behaviors tend to occur in clusters, and the understanding of such behavioral clustering may have direct implications for the effective tailoring of health-promotion interventions. Despite the usefulness of analyzing clustering, Italian data on this topic are scant. This study aimed to evaluate the clustering patterns of health-related behaviors. The present study is based on data from the Health Behaviors in School-aged Children (HBSC) study conducted in Tuscany in 2010, which involved 3291 11-, 13- and 15-year olds. To aggregate students' data on 22 health-related behaviors, factor analysis and subsequent cluster analysis were performed. Factor analysis revealed eight factors, which were dubbed in accordance with their main traits: 'Alcohol drinking', 'Smoking', 'Physical activity', 'Screen time', 'Signs & symptoms', 'Healthy eating', 'Violence' and 'Sweet tooth'. These factors explained 67% of variance and underwent cluster analysis. A six-cluster κ-means solution was established with a 93.8% level of classification validity. The between-cluster differences in both mean age and gender distribution were highly statistically significant. Health-compromising behaviors are common among Tuscan teens and occur in distinct clusters. These results may be used by schools, health-promotion authorities and other stakeholders to design and implement tailored preventive interventions in Tuscany.

  15. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  16. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  17. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  18. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-01-01

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  19. Revisiting the variation of clustering coefficient of biological networks suggests new modular structure

    Directory of Open Access Journals (Sweden)

    Hao Dapeng

    2012-05-01

    Full Text Available Abstract Background A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling. Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. Results We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn’t show dependence of degree. Conclusions Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to “deterministic model” of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.

  20. Preliminary results from a simulated laboratory experiment or an encounter of cluster satellite probes with a reconnection layer

    Science.gov (United States)

    Yamada, M.; Ren, Y.; Ji, H.; Gerhardt, S.; Darfman, S.

    2006-12-01

    With the recent upgrade of the MRX (Magnetic Reconnection Experiment) device[1], our experimental operation allows us to carry out a jog experiment in which a current sheet can be moved swiftly across an inserted probe assembly. A cluster of probes with variable distances can be inserted into a known desired position in the MRX device. This setup can be similar to the situation in which a cluster of satellites encounters a rapidly moving reconnection layer. If necessary, we can create a neutral sheet where the density of one side is significantly higher than the other, as is the case for the magnetopause. A variable guide field will be applied to study its effect on reconnection. We proposed[2] to document basic patterns of data during a simulated encounter of the MRX reconnection layer with the four-probe mock-up system and compare them with data acquired from past satellites. Relative position of the MMS satellites in the magnetosphere can then be determined. Optimum cluster configuration or distance between the four satellites can be determined for various diagnostics or research missions. The relationship of magnetic fluctuations[3] with the observed out-of- plane quadrupole field, a characteristic signature of the Hall MHD, can be also studied in this series of experiments. In this paper, results from a preliminary experiment will be presented. These experiments utilize effectively the unique MRX ability to accurately know the location of diagnostics with respect to the moving reconnection layer. Supported by DoE, NASA, NSF. [1] M. Yamada et al, Phys. Plasmas 13, 052119 (2006), [2] M.Yamada et al, MMS-IDS proposal (2006), [3] H. Ji et al, Phys. Rev. Letts. 92, 115001 (2004)

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    We present the results of approximately three years of observations of Planck Sunyaev-Zeldovich (SZ) sources with the Russian-Turkish 1.5m telescope (RTT150), as a part of the optical follow-up programme undertaken by the Planck collaboration. During this time period approximately 20% of all dark...

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

    Directory of Open Access Journals (Sweden)

    Shawkat K. Guirguis

    2017-01-01

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

  3. Revisiting the variation of clustering coefficient of biological networks suggests new modular structure.

    Science.gov (United States)

    Hao, Dapeng; Ren, Cong; Li, Chuanxing

    2012-05-01

    A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling). Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn't show dependence of degree. Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to "deterministic model" of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.

  4. Hierarchical Linked Views

    Energy Technology Data Exchange (ETDEWEB)

    Erbacher, Robert; Frincke, Deb

    2007-07-02

    Coordinated views have proven critical to the development of effective visualization environments. This results from the fact that a single view or representation of the data cannot show all of the intricacies of a given data set. Additionally, users will often need to correlate more data parameters than can effectively be integrated into a single visual display. Typically, development of multiple-linked views results in an adhoc configuration of views and associated interactions. The hierarchical model we are proposing is geared towards more effective organization of such environments and the views they encompass. At the same time, this model can effectively integrate much of the prior work on interactive and visual frameworks. Additionally, we expand the concept of views to incorporate perceptual views. This is related to the fact that visual displays can have information encoded at various levels of focus. Thus, a global view of the display provides overall trends of the data while focusing in on individual elements provides detailed specifics. By integrating interaction and perception into a single model, we show how one impacts the other. Typically, interaction and perception are considered separately, however, when interaction is being considered at a fundamental level and allowed to direct/modify the visualization directly we must consider them simultaneously and how they impact one another.

  5. Comparative analysis of clustering methods for gene expression time course data

    Directory of Open Access Journals (Sweden)

    Ivan G. Costa

    2004-01-01

    Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

  6. Cluster Headache Clinical Phenotypes: Tobacco Nonexposed (Never Smoker and No Parental Secondary Smoke Exposure as a Child) versus Tobacco-Exposed: Results from the United States Cluster Headache Survey.

    Science.gov (United States)

    Rozen, Todd D

    2018-05-01

    To present results from the United States Cluster Headache Survey comparing the clinical presentation of tobacco nonexposed and tobacco-exposed cluster headache patients. Cluster headache is uniquely tied to a personal history of tobacco usage/cigarette smoking and, if the individual cluster headache sufferer did not smoke, it has been shown that their parent(s) typically did and that individual had significant secondary smoke exposure as a child. The true nontobacco exposed (no personal or secondary exposure) cluster headache sufferer has never been fully studied. The United States Cluster Headache Survey consisted of 187 multiple choice questions related to cluster headache including: patient demographics, clinical headache characteristics, family history, triggers, smoking history (personal and secondary), and headache-related disability. The survey was placed on a website from October through December 2008. One thousand one hundred thirty-four individuals completed the survey. One hundred thirty-three subjects or 12% of the surveyed population had no personal smoking/tobacco use history and no secondary smoke exposure as an infant/child, thus a nontobacco exposed population. In the nonexposed population, there were 87 males and 46 females with a gender ratio of 1.9:1. Episodic cluster headache occurred in 80% of nonexposed subjects. One thousand and one survey responders or 88% were tobacco-exposed (729 males and 272 females) with a gender ratio of 2.7:1. Eighty-three percent had a personal smoking history, while only 17% just had parents who smoked with secondary smoke exposure. Eighty-five percent of smokers had double exposure with a personal smoking history and secondary exposure as a child. Nonexposed cluster headache subjects are significantly more likely to develop cluster headache at ages 40 years and younger, while the exposed sufferers are significantly more likely to develop cluster headache at 40 years of age and older. Nonexposed patients have a

  7. Prevalence of cluster headache in the Republic of Georgia: results of a population-based study and methodological considerations

    DEFF Research Database (Denmark)

    Katsarava, Z; Dzagnidze, A; Kukava, M

    2009-01-01

    We present a study of the general-population prevalence of cluster headache in the Republic of Georgia and discuss the advantages and challenges of different methodological approaches. In a community-based survey, specially trained medical residents visited 500 adjacent households in the capital...... with possible cluster headache, who were then personally interviewed by one of two headache-experienced neurologists. Cluster headache was confirmed in one subject. The prevalence of cluster headache was therefore estimated to be 87/100,000 (95% confidence interval

  8. Hierarchical Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Di Lu

    2018-01-01

    Full Text Available The Internet of Things (IoT generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA. It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.

  9. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  10. Examination of Clustering in Eutectic Microstrcture

    Directory of Open Access Journals (Sweden)

    Bortnyik K.

    2017-06-01

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

  11. A hybrid clustering approach to recognition of protein families in 114 microbial genomes

    Directory of Open Access Journals (Sweden)

    Gogarten J Peter

    2004-04-01

    Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

  12. Hierarchical decision making for flood risk reduction

    DEFF Research Database (Denmark)

    Custer, Rocco; Nishijima, Kazuyoshi

    2013-01-01

    . In current practice, structures are often optimized individually without considering benefits of having a hierarchy of protection structures. It is here argued, that the joint consideration of hierarchically integrated protection structures is beneficial. A hierarchical decision model is utilized to analyze...... and compare the benefit of large upstream protection structures and local downstream protection structures in regard to epistemic uncertainty parameters. Results suggest that epistemic uncertainty influences the outcome of the decision model and that, depending on the magnitude of epistemic uncertainty...

  13. Calculations of light scattering matrices for stochastic ensembles of nanosphere clusters

    International Nuclear Information System (INIS)

    Bunkin, N.F.; Shkirin, A.V.; Suyazov, N.V.; Starosvetskiy, A.V.

    2013-01-01

    Results of the calculation of the light scattering matrices for systems of stochastic nanosphere clusters are presented. A mathematical model of spherical particle clustering with allowance for cluster–cluster aggregation is used. The fractal properties of cluster structures are explored at different values of the model parameter that governs cluster–cluster interaction. General properties of the light scattering matrices of nanosphere-cluster ensembles as dependent on their mean fractal dimension have been found. The scattering-matrix calculations were performed for finite samples of 10 3 random clusters, made up of polydisperse spherical nanoparticles, having lognormal size distribution with the effective radius 50 nm and effective variance 0.02; the mean number of monomers in a cluster and its standard deviation were set to 500 and 70, respectively. The implemented computation environment, modeling the scattering matrices for overall sequences of clusters, is based upon T-matrix program code for a given single cluster of spheres, which was developed in [1]. The ensemble-averaged results have been compared with orientation-averaged ones calculated for individual clusters. -- Highlights: ► We suggested a hierarchical model of cluster growth allowing for cluster–cluster aggregation. ► We analyzed the light scattering by whole ensembles of nanosphere clusters. ► We studied the evolution of the light scattering matrix when changing the fractal dimension

  14. Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

    Science.gov (United States)

    Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

    2018-04-27

    Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

  15. Planck early results. X. Statistical analysis of Sunyaev-Zeldovich scaling relations for X-ray galaxy clusters

    DEFF Research Database (Denmark)

    Poutanen, T.; Natoli, P.; Polenta, G.

    2011-01-01

    All-sky data from the Planck survey and the Meta-Catalogue of X-ray detected Clusters of galaxies (MCXC) are combined to investigate the relationship between the thermal Sunyaev-Zeldovich (SZ) signal and X-ray luminosity. The sample comprises ~1600 X-ray clusters with redshifts up to ~1 and spans...

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

    International Nuclear Information System (INIS)

    Iijima, Nobukazu

    2010-01-01

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

  17. XML documents cluster research based on frequent subpatterns

    Science.gov (United States)

    Ding, Tienan; Li, Wei; Li, Xiongfei

    2015-12-01

    XML data is widely used in the information exchange field of Internet, and XML document data clustering is the hot research topic. In the XML document clustering process, measure differences between two XML documents is time costly, and impact the efficiency of XML document clustering. This paper proposed an XML documents clustering method based on frequent patterns of XML document dataset, first proposed a coding tree structure for encoding the XML document, and translate frequent pattern mining from XML documents into frequent pattern mining from string. Further, using the cosine similarity calculation method and cohesive hierarchical clustering method for XML document dataset by frequent patterns. Because of frequent patterns are subsets of the original XML document data, so the time consumption of XML document similarity measure is reduced. The experiment runs on synthetic dataset and the real datasets, the experimental result shows that our method is efficient.

  18. Coherence-based Time Series Clustering for Brain Connectivity Visualization

    KAUST Repository

    Euan, Carolina

    2017-11-19

    We develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels that display high level of coordination as measured by

  19. Coherence-based Time Series Clustering for Brain Connectivity Visualization

    KAUST Repository

    Euan, Carolina; Sun, Ying; Ombao, Hernando

    2017-01-01

    We develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels that display high level of coordination as measured by

  20. Hierarchical analysis of dependency in metabolic networks.

    Science.gov (United States)

    Gagneur, Julien; Jackson, David B; Casari, Georg

    2003-05-22

    Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size. We introduce a hierarchical representation that emphasizes the gross organization of metabolic networks in largely independent pathways and sub-systems at several levels of independence. The approach highlights the coupling of different pathways and the shared compounds responsible for those couplings. By assessing our results on Escherichia coli (E.coli metabolic reactions, Genetic Circuits Research Group, University of California, San Diego, http://gcrg.ucsd.edu/organisms/ecoli.html, 'model v 1.01. reactions') against accepted biochemical annotations, we provide the first systematic synopsis of an organism's metabolism. Comparison with operons of E.coli shows that low-level clusters are reflected in genome organization and gene regulation. Source code, data sets and supplementary information are available at http://www.mas.ecp.fr/labo/equipe/gagneur/hierarchy/hierarchy.html

  1. Hierarchical wave functions revisited

    International Nuclear Information System (INIS)

    Li Dingping.

    1997-11-01

    We study the hierarchical wave functions on a sphere and on a torus. We simplify some wave functions on a sphere or a torus using the analytic properties of wave functions. The open question, the construction of the wave function for quasi electron excitation on a torus, is also solved in this paper. (author)

  2. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

    Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-07

    Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

  3. The Hierarchical Perspective

    Directory of Open Access Journals (Sweden)

    Daniel Sofron

    2015-05-01

    Full Text Available This paper is focused on the hierarchical perspective, one of the methods for representing space that was used before the discovery of the Renaissance linear perspective. The hierarchical perspective has a more or less pronounced scientific character and its study offers us a clear image of the way the representatives of the cultures that developed it used to perceive the sensitive reality. This type of perspective is an original method of representing three-dimensional space on a flat surface, which characterises the art of Ancient Egypt and much of the art of the Middle Ages, being identified in the Eastern European Byzantine art, as well as in the Western European Pre-Romanesque and Romanesque art. At the same time, the hierarchical perspective is also present in naive painting and infantile drawing. Reminiscences of this method can be recognised also in the works of some precursors of the Italian Renaissance. The hierarchical perspective can be viewed as a subjective ranking criterion, according to which the elements are visually represented by taking into account their relevance within the image while perception is ignored. This paper aims to show how the main objective of the artists of those times was not to faithfully represent the objective reality, but rather to emphasize the essence of the world and its perennial aspects. This may represent a possible explanation for the refusal of perspective in the Egyptian, Romanesque and Byzantine painting, characterised by a marked two-dimensionality.

  4. Cluster fusion-fission dynamics in the Singapore stock exchange

    Science.gov (United States)

    Teh, Boon Kin; Cheong, Siew Ann

    2015-10-01

    In this paper, we investigate how the cross-correlations between stocks in the Singapore stock exchange (SGX) evolve over 2008 and 2009 within overlapping one-month time windows. In particular, we examine how these cross-correlations change before, during, and after the Sep-Oct 2008 Lehman Brothers Crisis. To do this, we extend the complete-linkage hierarchical clustering algorithm, to obtain robust clusters of stocks with stronger intracluster correlations, and weaker intercluster correlations. After we identify the robust clusters in all time windows, we visualize how these change in the form of a fusion-fission diagram. Such a diagram depicts graphically how the cluster sizes evolve, the exchange of stocks between clusters, as well as how strongly the clusters mix. From the fusion-fission diagram, we see a giant cluster growing and disintegrating in the SGX, up till the Lehman Brothers Crisis in September 2008 and the market crashes of October 2008. After the Lehman Brothers Crisis, clusters in the SGX remain small for few months before giant clusters emerge once again. In the aftermath of the crisis, we also find strong mixing of component stocks between clusters. As a result, the correlation between initially strongly-correlated pairs of stocks decay exponentially with average life time of about a month. These observations impact strongly how portfolios and trading strategies should be formulated.

  5. A local adaptive algorithm for emerging scale-free hierarchical networks

    International Nuclear Information System (INIS)

    Gomez Portillo, I J; Gleiser, P M

    2010-01-01

    In this work we study a growing network model with chaotic dynamical units that evolves using a local adaptive rewiring algorithm. Using numerical simulations we show that the model allows for the emergence of hierarchical networks. First, we show that the networks that emerge with the algorithm present a wide degree distribution that can be fitted by a power law function, and thus are scale-free networks. Using the LaNet-vi visualization tool we present a graphical representation that reveals a central core formed only by hubs, and also show the presence of a preferential attachment mechanism. In order to present a quantitative analysis of the hierarchical structure we analyze the clustering coefficient. In particular, we show that as the network grows the clustering becomes independent of system size, and also presents a power law decay as a function of the degree. Finally, we compare our results with a similar version of the model that has continuous non-linear phase oscillators as dynamical units. The results show that local interactions play a fundamental role in the emergence of hierarchical networks.

  6. Energy Aware Cluster Based Routing Scheme For Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Roy Sohini

    2015-09-01

    Full Text Available Wireless Sensor Network (WSN has emerged as an important supplement to the modern wireless communication systems due to its wide range of applications. The recent researches are facing the various challenges of the sensor network more gracefully. However, energy efficiency has still remained a matter of concern for the researches. Meeting the countless security needs, timely data delivery and taking a quick action, efficient route selection and multi-path routing etc. can only be achieved at the cost of energy. Hierarchical routing is more useful in this regard. The proposed algorithm Energy Aware Cluster Based Routing Scheme (EACBRS aims at conserving energy with the help of hierarchical routing by calculating the optimum number of cluster heads for the network, selecting energy-efficient route to the sink and by offering congestion control. Simulation results prove that EACBRS performs better than existing hierarchical routing algorithms like Distributed Energy-Efficient Clustering (DEEC algorithm for heterogeneous wireless sensor networks and Energy Efficient Heterogeneous Clustered scheme for Wireless Sensor Network (EEHC.

  7. [Work-Related Medical Rehabilitation in Cancer Rehabilitation - Short-Term Results from a Cluster-Randomized Multicenter-Trial].

    Science.gov (United States)

    Wienert, Julian; Bethge, Matthias

    2018-05-25

    Rehabilitation programs that support return to work become increasingly relevant for cancer survivors. In Germany, such programs were established as work-related medical rehabilitation (WMR). The study investigated whether WMR leads to better results compared to medical rehabilitation (MR). We report effects on secondary outcomes when the rehabilitation program was completed. Clusters of participants were randomly assigned to WMR or MR. Patients of working age and an elevated risk of not returning to work were included. The grade of implementation was assessed by dose delivered and dose received. Study outcomes were assessed using scales measuring functioning and symptoms, coping with illness as well as self-reported work ability. Treatment effects were estimated using mixed linear models. From 232 planned randomized intervention groups, 165 (71%) were realized. In total, 476 patients were included. Mean age of participants was 50.7 years (SD=7.3). Most frequent primary diagnoses were malignant neoplasms of the breast. Participants in the WMR program reported significantly better outcomes regarding quality of life (SMD=0.17-0.25), fatigue (SMD=0.18-0.27), coping with illness (SMD=0.17-0.22), and self-reported work-ability (SMD=0.16) compared to participants in MR program (all p<0.05). The results indicate a positive effect in favor of WMR for cancer patients with an elevated risk of not returning to work at the end of their treatment. © Georg Thieme Verlag KG Stuttgart · New York.

  8. Long term effectiveness on prescribing of two multifaceted educational interventions: results of two large scale randomized cluster trials.

    Directory of Open Access Journals (Sweden)

    Nicola Magrini

    Full Text Available INTRODUCTION: Information on benefits and risks of drugs is a key element affecting doctors' prescribing decisions. Outreach visits promoting independent information have proved moderately effective in changing prescribing behaviours. OBJECTIVES: Testing the short and long-term effectiveness on general practitioners' prescribing of small groups meetings led by pharmacists. METHODS: Two cluster open randomised controlled trials (RCTs were carried out in a large scale NHS setting. Ad hoc prepared evidence based material were used considering a therapeutic area approach--TEA, with information materials on osteoporosis or prostatic hyperplasia--and a single drug oriented approach--SIDRO, with information materials on me-too drugs of 2 different classes: barnidipine or prulifloxacin. In each study, all 115 Primary Care Groups in a Northern Italy area (2.2 million inhabitants, 1737 general practitioners were randomised to educational small groups meetings, in which available evidence was provided together with drug utilization data and clinical scenarios. Main outcomes were changes in the six-months prescription of targeted drugs. Longer term results (24 and 48 months were also evaluated. RESULTS: In the TEA trial, one of the four primary outcomes showed a reduction (prescription of alfuzosin compared to tamsulosin and terazosin in benign prostatic hyperplasia: prescribing ratio -8.5%, p = 0.03. Another primary outcome (prescription of risedronate showed a reduction at 24 and 48 months (-7.6%, p = 0.02; and -9,8%, p = 0.03, but not at six months (-5.1%, p = 0.36. In the SIDRO trial both primary outcomes showed a statistically significant reduction (prescription of barnidipine -9.8%, p = 0.02; prescription of prulifloxacin -11.1%, p = 0.04, which persisted or increased over time. INTERPRETATION: These two cluster RCTs showed the large scale feasibility of a complex educational program in a NHS setting, and its potentially

  9. Evaluating Hierarchical Structure in Music Annotations.

    Science.gov (United States)

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  10. Evaluating Hierarchical Structure in Music Annotations

    Directory of Open Access Journals (Sweden)

    Brian McFee

    2017-08-01

    Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  11. Hierarchical screening for multiple mental disorders.

    Science.gov (United States)

    Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J

    2013-10-01

    There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.

  12. Hierarchical drivers of reef-fish metacommunity structure.

    Science.gov (United States)

    MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

    2009-01-01

    multiple spatial scales; and (3) inter-atoll connectedness was poorly correlated with the nonrandom clustering of reef-fish species. These results demonstrate the importance of modeling hierarchical data and processes in understanding reef-fish metacommunity structure.

  13. Hierarchical structure in the distribution of galaxies

    International Nuclear Information System (INIS)

    Schulman, L.S.; Seiden, P.E.; Technion - Israel Institute of Technology, Haifa; IBM Thomas J. Watson Research Center, Yorktown Heights, NY)

    1986-01-01

    The distribution of galaxies has a hierarchical structure with power-law correlations. This is usually thought to arise from gravity alone acting on an originally uniform distributioon. If, however, the original process of galaxy formation occurs through the stimulated birth of one galaxy due to a nearby recently formed galaxy, and if this process occurs near its percolation threshold, then a hierarchical structure with power-law correlations arises at the time of galaxy formation. If subsequent gravitational evolution within an expanding cosmology is such as to retain power-law correlations, the initial r exp -1 dropoff can steepen to the observed r exp -1.8. The distribution of galaxies obtained by this process produces clustering and voids, as observed. 23 references

  14. Open source clustering software.

    Science.gov (United States)

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

    2004-06-12

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

  15. OMERACT-based fibromyalgia symptom subgroups: an exploratory cluster analysis.

    Science.gov (United States)

    Vincent, Ann; Hoskin, Tanya L; Whipple, Mary O; Clauw, Daniel J; Barton, Debra L; Benzo, Roberto P; Williams, David A

    2014-10-16

    The aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains. Female patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire-Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria. A total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P FIQ-R total scores (P = 0.0004)). In our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.

  16. Measuring human rights violations in a conflict-affected country: results from a nationwide cluster survey in Central African Republic

    Directory of Open Access Journals (Sweden)

    Roberts Les

    2011-03-01

    Full Text Available Abstract Background Measuring human rights violations is particularly challenging during or after armed conflict. A recent nationwide survey in the Central African Republic produced estimates of rates of grave violations against children and adults affected by armed conflict, using an approach known as the "Neighborhood Method". Methods In June and July, 2009, a random household survey was conducted based on population estimates from the 2003 national census. Clusters were assigned systematically proportional to population size. Respondents in randomly selected households were interviewed regarding incidents of killing, intentional injury, recruitment into armed groups, abduction, sexual abuse and rape between January 1, 2008 and the date of interview, occurring in their homes' and those of their three closest neighbors. Results Sixty of the selected 69 clusters were surveyed. In total, 599 women were interviewed about events in 2,370 households representing 13,669 persons. Estimates of annual rates of each violation occurring per 1000 people in each of two strata are provided for children between the ages of five and 17, adults 18 years of age and older and the entire population five years and older, along with a combined and weighted national rate. The national rates for children age five to 17 were estimated to be 0.98/1000/year (95% CI: 0.18 - 1.78 for recruitment, 2.56/1000/year (95% CI: 1.50 - 3.62 for abduction, 1.13/1000/year (95% CI: 0.33 - 1.93 for intentional injury, 10.72/1000 girls/year (95% CI: 7.40 - 14.04 for rape, and 4.80/1000 girls/year (95% CI: 2.61 - 6.00 for sexual abuse. No reports of any violation against a person under the age of five were recorded and there were no reports of rape or sexual abuse of males. No children were reported to have been killed during the recall period. Rape and abduction were the most frequently reported events. Conclusions The population-based figures greatly augment existing information on

  17. FADS1 FADS2 gene cluster, PUFA intake and blood lipids in children: results from the GINIplus and LISAplus studies.

    Directory of Open Access Journals (Sweden)

    Marie Standl

    Full Text Available BACKGROUND: Elevated cholesterol levels in children can be a risk factor for cardiovascular diseases in later life. In adults, it has been shown that blood lipid levels are strongly influenced by polymorphisms in the fatty acid desaturase (FADS gene cluster in addition to nutritional and other exogenous and endogenous determinants. Our aim was to investigate whether lipid levels are determined by the FADS genotype already in children and whether this association interacts with dietary intake of n-3 fatty acids. METHODS: The analysis was based on data of 2006 children from two German prospective birth cohort studies. Total cholesterol, HDL, LDL and triglycerides were measured at 10 years of age. Six single nucleotide polymorphisms (SNPs of the FADS gene cluster were genotyped. Dietary n-3 fatty acid intake was assessed by food frequency questionnaire. Linear regression modeling was used to assess the association between lipid levels, n-3 fatty acid intake and FADS genotype. RESULTS: Individuals carrying the homozygous minor allele had lower levels of total cholesterol [means ratio (MR ranging from 0.96 (p = 0.0093 to 0.98 (p = 0.2949, depending on SNPs] and LDL [MR between 0.94 (p = 0.0179 and 0.97 (p = 0.2963] compared to homozygous major allele carriers. Carriers of the heterozygous allele showed lower HDL levels [β between -0.04 (p = 0.0074 to -0.01 (p = 0.3318] and higher triglyceride levels [MR ranging from 1.06 (p = 0.0065 to 1.07 (p = 0.0028] compared to homozygous major allele carriers. A higher n-3 PUFA intake was associated with higher concentrations of total cholesterol, LDL, HDL and lower triglyceride levels, but these associations did not interact with the FADS1 FADS2 genotype. CONCLUSION: Total cholesterol, HDL, LDL and triglyceride concentrations may be influenced by the FADS1 FADS2 genotype already in 10 year old children. Genetically determined blood lipid levels during childhood might

  18. Deletion of the MBII-85 snoRNA gene cluster in mice results in postnatal growth retardation.

    Directory of Open Access Journals (Sweden)

    Boris V Skryabin

    2007-12-01

    Full Text Available Prader-Willi syndrome (PWS [MIM 176270] is a neurogenetic disorder characterized by decreased fetal activity, muscular hypotonia, failure to thrive, short stature, obesity, mental retardation, and hypogonadotropic hypogonadism. It is caused by the loss of function of one or more imprinted, paternally expressed genes on the proximal long arm of chromosome 15. Several potential PWS mouse models involving the orthologous region on chromosome 7C exist. Based on the analysis of deletions in the mouse and gene expression in PWS patients with chromosomal translocations, a critical region (PWScr for neonatal lethality, failure to thrive, and growth retardation was narrowed to the locus containing a cluster of neuronally expressed MBII-85 small nucleolar RNA (snoRNA genes. Here, we report the deletion of PWScr. Mice carrying the maternally inherited allele (PWScr(m-/p+ are indistinguishable from wild-type littermates. All those with the paternally inherited allele (PWScr(m+/p- consistently display postnatal growth retardation, with about 15% postnatal lethality in C57BL/6, but not FVB/N crosses. This is the first example in a multicellular organism of genetic deletion of a C/D box snoRNA gene resulting in a pronounced phenotype.

  19. Determinants of child maltreatment in Nepal: Results from the 2014 Nepal multiple indicator cluster survey (the 2014 NMICS).

    Science.gov (United States)

    Atteraya, Madhu Sudhan; Ebrahim, Nasser B; Gnawali, Shreejana

    2018-02-01

    We examined the prevalence of child maltreatment as measured by the level of physical (moderate to severe) and emotional abuse and child labor, and the associated household level determinants of child maltreatment in Nepal. We used a nationally representative data set from the fifth round of the Nepal Multiple Indicator Cluster Survey (the 2014 NMICS). The main independent variables were household level characteristics. Dependent variables included child experience of moderate to severe physical abuse, emotional abuse, and child labor (domestic work and economic activities). Bivariate analyses and logistic regressions were used to examine the associations between independent and dependent variables. The results showed that nearly half of the children (49.8%) had experienced moderate physical abuse, 21.5% experienced severe physical abuse, and 77.3% experienced emotional abuse. About 27% of the children had engaged in domestic work and 46.7% in various economic activities. At bivariate level, educational level of household's head and household wealth status had shown significant statistical association with child maltreatment (pchild labor. In general, child maltreatment is a neglected social issue in Nepal and the high rates of child maltreatment calls for mass awareness programs focusing on parents, and involving all stakeholders including governments, local, and international organizations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Results of a lay health education intervention to increase colorectal cancer screening among Filipino Americans: A cluster randomized controlled trial.

    Science.gov (United States)

    Cuaresma, Charlene F; Sy, Angela U; Nguyen, Tung T; Ho, Reginald C S; Gildengorin, Ginny L; Tsoh, Janice Y; Jo, Angela M; Tong, Elisa K; Kagawa-Singer, Marjorie; Stewart, Susan L

    2018-04-01

    Filipino colorectal cancer (CRC) screening rates fall below Healthy People 2020 goals. In this study, the authors explore whether a lay health educator (LHE) approach can increase CRC screening among Filipino Americans ages 50 to 75 years in Hawai'i. A cluster randomized controlled trial from 2012 through 2015 compared an intervention, which consisted of LHEs delivering 2 education sessions and 2 telephone follow-up calls on CRC screening plus a CRC brochure versus an attention control, in which 2 lectures and 2 follow-up calls on nutrition and physical activity plus a CRC brochure were provided. The primary outcome was change in self-reported ever receipt of CRC screening at 6 months. Among 304 participants (77% women, 86% had > 10 years of residence in the United States), the proportion of participants who reported ever having received CRC screening increased significantly in the intervention group (from 80% to 89%; P = .0003), but not in the control group (from 73% to 74%; P = .60). After covariate adjustment, there was a significant intervention effect (odds ratio, 1.9; 95% confidence interval, 1.0-3.5). There was no intervention effect on up-to-date screening. This first randomized controlled trial for CRC screening among Hawai'i's Filipinos used an LHE intervention with mixed, but promising, results. Cancer 2018;124:1535-42. © 2018 American Cancer Society. © 2018 American Cancer Society.

  1. The Effects of Skill Training on Social Workers' Professional Competences in Norway: Results of a Cluster-Randomised Study

    Science.gov (United States)

    Malmberg-Heimonen, Ira; Natland, Sidsel; Tøge, Anne Grete; Hansen, Helle Cathrine

    2016-01-01

    Using a cluster-randomised design, this study analyses the effects of a government-administered skill training programme for social workers in Norway. The training programme aims to improve social workers' professional competences by enhancing and systematising follow-up work directed towards longer-term unemployed clients in the following areas: encountering the user, system-oriented efforts and administrative work. The main tools and techniques of the programme are based on motivational interviewing and appreciative inquiry. The data comprise responses to baseline and eighteen-month follow-up questionnaires administered to all social workers (n = 99) in eighteen participating Labour and Welfare offices randomised into experimental and control groups. The findings indicate that the skill training programme positively affected the social workers' evaluations of their professional competences and quality of work supervision received. The acquisition and mastering of combinations of specific tools and techniques, a comprehensive supervision structure and the opportunity to adapt the learned skills to local conditions were important in explaining the results. PMID:27559232

  2. A new clustering algorithm for scanning electron microscope images

    Science.gov (United States)

    Yousef, Amr; Duraisamy, Prakash; Karim, Mohammad

    2016-04-01

    A scanning electron microscope (SEM) is a type of electron microscope that produces images of a sample by scanning it with a focused beam of electrons. The electrons interact with the sample atoms, producing various signals that are collected by detectors. The gathered signals contain information about the sample's surface topography and composition. The electron beam is generally scanned in a raster scan pattern, and the beam's position is combined with the detected signal to produce an image. The most common configuration for an SEM produces a single value per pixel, with the results usually rendered as grayscale images. The captured images may be produced with insufficient brightness, anomalous contrast, jagged edges, and poor quality due to low signal-to-noise ratio, grained topography and poor surface details. The segmentation of the SEM images is a tackling problems in the presence of the previously mentioned distortions. In this paper, we are stressing on the clustering of these type of images. In that sense, we evaluate the performance of the well-known unsupervised clustering and classification techniques such as connectivity based clustering (hierarchical clustering), centroid-based clustering, distribution-based clustering and density-based clustering. Furthermore, we propose a new spatial fuzzy clustering technique that works efficiently on this type of images and compare its results against these regular techniques in terms of clustering validation metrics.

  3. A Simple Hierarchical Pooling Data Structure for Loop Closure

    Science.gov (United States)

    2016-10-16

    performance empirically on the KITTI [9], Oxford [6] and TUM RGB- D [29] datasets, as well as demonstrate extensions to general image retrieval on the...of a BoW where each word is an element of a dictionary of descriptors obtained off-line by hierarchical k-means clustering, with each word weighted by...to the inverse docu- ment frequency. This standard pipeline, with different clustering procedures to generate the dictionary and different features

  4. Hierarchical species distribution models

    Science.gov (United States)

    Hefley, Trevor J.; Hooten, Mevin B.

    2016-01-01

    Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

  5. Bayesian nonparametric hierarchical modeling.

    Science.gov (United States)

    Dunson, David B

    2009-04-01

    In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

  6. Complex networks as an emerging property of hierarchical preferential attachment

    Science.gov (United States)

    Hébert-Dufresne, Laurent; Laurence, Edward; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

    2015-12-01

    Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

  7. Descriptive analysis of factors that influence economical results in the furniture cluster of Bento Gonçalves

    Directory of Open Access Journals (Sweden)

    Miguel Afonso Sellitto

    2014-12-01

    Full Text Available The purpose of this article is to analyze factors that can influence the competitiveness of companies in the furniture cluster of Bento Gonçalves, Rio Grande do Sul. By a literature review, we identify four factors that can influence competition in clusters: the region's productivity, innovation, relationship with suppliers, and cooperation between companies. The research method is the single case study. The research techniques are the review of specific bibliographic and documentation of the studied cluster, and interviews with experts of the cluster. The main findings are: the cluster has high productivity, mainly by hi-tech machinery employed by the main companies; innovation is permanent and motivated by the imposition to medium and short companies of business goals by the main companies; the relationship with suppliers is problematic regarding the large-scale vendors by the lack of the practice of collective purchases in the area; and cooperation between enterprises is small, by the culture of the region that don´t appreciate depending on resources available outside the companies. Such factors can contribute to produce hypotheses for further research.

  8. Hierarchal scalar and vector tetrahedra

    International Nuclear Information System (INIS)

    Webb, J.P.; Forghani, B.

    1993-01-01

    A new set of scalar and vector tetrahedral finite elements are presented. The elements are hierarchal, allowing mixing of polynomial orders; scalar orders up to 3 and vector orders up to 2 are defined. The vector elements impose tangential continuity on the field but not normal continuity, making them suitable for representing the vector electric or magnetic field. Further, the scalar and vector elements are such that they can easily be used in the same mesh, a requirement of many quasi-static formulations. Results are presented for two 50 Hz problems: the Bath Cube, and TEAM Problem 7

  9. Hierarchically Structured Electrospun Fibers

    Science.gov (United States)

    2013-01-07

    in the natural lotus and silver ragwort leaves. Figure 4. Examples of electrospun bio-mimics of natural hierarchical structures. (A) Lotus leaf...B) pillared poly(methyl methacrylate) (PMMA) electrospun fiber mimic; (C) silver ragwort leaf; (D) electrospun fiber mimic made from nylon 6 and...domains containing the protein in the surrounding EVA fibers [115]. A wide variety of core-shell fibers have been generated, including PCL/ gelatin

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

    Science.gov (United States)

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

    2017-06-01

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

  11. Canonical PSO Based K-Means Clustering Approach for Real Datasets.

    Science.gov (United States)

    Dey, Lopamudra; Chakraborty, Sanjay

    2014-01-01

    "Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.

  12. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

    Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

  13. HUBBLE SPACE TELESCOPE PROPER MOTION (HSTPROMO) CATALOGS OF GALACTIC GLOBULAR CLUSTERS. I. SAMPLE SELECTION, DATA REDUCTION, AND NGC 7078 RESULTS

    Energy Technology Data Exchange (ETDEWEB)

    Bellini, A.; Anderson, J.; Van der Marel, R. P.; Watkins, L. L. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); King, I. R. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Bianchini, P. [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Chanamé, J. [Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Macul 782-0436, Santiago (Chile); Chandar, R. [Department of Physics and Astronomy, The University of Toledo, 2801 West Bancroft Street, Toledo, OH 43606 (United States); Cool, A. M. [Department of Physics and Astronomy, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA 94132 (United States); Ferraro, F. R.; Massari, D. [Dipartimento di Fisica e Astronomia, Università di Bologna, via Ranzani 1, I-40127 Bologna (Italy); Ford, H., E-mail: bellini@stsci.edu [Department of Physics and Astronomy, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States)

    2014-12-20

    We present the first study of high-precision internal proper motions (PMs) in a large sample of globular clusters, based on Hubble Space Telescope (HST) data obtained over the past decade with the ACS/WFC, ACS/HRC, and WFC3/UVIS instruments. We determine PMs for over 1.3 million stars in the central regions of 22 clusters, with a median number of ∼60,000 stars per cluster. These PMs have the potential to significantly advance our understanding of the internal kinematics of globular clusters by extending past line-of-sight (LOS) velocity measurements to two- or three-dimensional velocities, lower stellar masses, and larger sample sizes. We describe the reduction pipeline that we developed to derive homogeneous PMs from the very heterogeneous archival data. We demonstrate the quality of the measurements through extensive Monte Carlo simulations. We also discuss the PM errors introduced by various systematic effects and the techniques that we have developed to correct or remove them to the extent possible. We provide in electronic form the catalog for NGC 7078 (M 15), which consists of 77,837 stars in the central 2.'4. We validate the catalog by comparison with existing PM measurements and LOS velocities and use it to study the dependence of the velocity dispersion on radius, stellar magnitude (or mass) along the main sequence, and direction in the plane of the sky (radial or tangential). Subsequent papers in this series will explore a range of applications in globular-cluster science and will also present the PM catalogs for the other sample clusters.

  14. Intracluster age gradients in numerous young stellar clusters

    Science.gov (United States)

    Getman, K. V.; Feigelson, E. D.; Kuhn, M. A.; Bate, M. R.; Broos, P. S.; Garmire, G. P.

    2018-05-01

    The pace and pattern of star formation leading to rich young stellar clusters is quite uncertain. In this context, we analyse the spatial distribution of ages within 19 young (median t ≲ 3 Myr on the Siess et al. time-scale), morphologically simple, isolated, and relatively rich stellar clusters. Our analysis is based on young stellar object (YSO) samples from the Massive Young Star-Forming Complex Study in Infrared and X-ray and Star Formation in Nearby Clouds surveys, and a new estimator of pre-main sequence (PMS) stellar ages, AgeJX, derived from X-ray and near-infrared photometric data. Median cluster ages are computed within four annular subregions of the clusters. We confirm and extend the earlier result of Getman et al. (2014): 80 per cent of the clusters show age trends where stars in cluster cores are younger than in outer regions. Our cluster stacking analyses establish the existence of an age gradient to high statistical significance in several ways. Time-scales vary with the choice of PMS evolutionary model; the inferred median age gradient across the studied clusters ranges from 0.75 to 1.5 Myr pc-1. The empirical finding reported in the present study - late or continuing formation of stars in the cores of star clusters with older stars dispersed in the outer regions - has a strong foundation with other observational studies and with the astrophysical models like the global hierarchical collapse model of Vázquez-Semadeni et al.

  15. 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...

  16. [Effects of daily physical exercise at school on cardiovascular risk--results of a 2-year cluster-randomized study].

    Science.gov (United States)

    Walther, C; Mende, M; Gaede, L; Müller, U; Machalica, K; Schuler, G

    2011-11-01

    It was the aim of this study to measure the effects over two years of daily sport activity during the school-day on their physical fitness (primary endpoint), motor coordination and blood pressure (secondary endpoints). A total of 232 children from eleven different 6 (th) grade classes were enrolled after informed parental consent. Their mean age was 11.1  ±  0.6 years. Six classes were randomly assigned for intervention (n=141), five as control (n=91). Those of the intervention cohort undertook, for five days weekly during the school year one hour of regulated sport exercise, including 15 min of endurance training. The pupils of the control group undertook customary sport activity (two hours a week). Anthropometric data were recorded and maximal oxygen uptake measured in each pupil, as well as blood pressure and motor coordination at the beginning and at the end of each of the two years of the study. The data were analyzed using the cluster randomization method. Maximal oxygen uptake (VO (2)max) had improved among the intervention group after two years, compared with the controls (3.12 m/kg/min, 95% confindence interval [CI] 0.06-6.19), while improvement in motor coordination just failed to reach statistical significance (3.06, 95% CI -0.17-6.29). There was no significant difference in systolic and diastolic blood pressure, but a downward trend in the prevalence of overweight and obesity from 12.1% to 7.8% in the intervention group. The results indicate that daily physical exercise during school hours should be given greater importance. But it will require a long-term trial to determine whether promotion of increased physical activity at school influences the prevalence of cardiovascular risk factors when the pupils reach adulthood. © Georg Thieme Verlag KG Stuttgart · New York.

  17. Sex Differences in Civilian Injury in Baghdad From 2003 to 2014: Results of a Randomized Household Cluster Survey.

    Science.gov (United States)

    Shaak, Kyle; Lafta, Riyadh; Stewart, Barclay T; Fowler, Thomas R; Al-Shatari, Sahar A Esa; Burnham, Gilbert; Cherewick, Megan; Wren, Sherry M; Groen, Reinou S; Kushner, Adam L

    2018-06-01

    To examine sex differences in injury mechanisms, injury-related death, injury-related disability, and associated financial consequences in Baghdad since the 2003 invasion of Iraq to inform prevention initiatives, health policy, and relief planning. Reliable estimates of injury burden among civilians during conflict are lacking, particularly among vulnerable subpopulations, such as women. A 2-stage, cluster randomized, community-based household survey was conducted in May 2014 to determine the civilian burden of injury in Baghdad since 2003. Households were surveyed regarding injury mechanisms, healthcare required, disability, deaths, connection to conflict, and resultant financial hardship. We surveyed 900 households (5148 individuals), reporting 553 injuries, 162 (29%) of which were injuries among women. The mean age of injury was higher among women compared with men (34 ± 21.3 vs 27 ± 16.5 years; P < 0.001). More women than men were injured while in the home [104 (64%) vs 82 (21%); P < 0.001]. Fewer women than men died from injuries [11 (6.8%) vs 77 (20%); P < 0.001]; however, women were more likely than men to live with reduced function [101 (63%) vs 192 (49%); P = 0.005]. Of intentional injuries, women had higher rates of injury by shell fragments (41% vs 26%); more men were injured by gunshots [76 (41%) vs 6 (17.6%); P = .011). Women experienced fewer injuries than men in postinvasion Baghdad, but were more likely to suffer disability after injury. Efforts to improve conditions for injured women should focus on mitigating financial and provisional hardships, providing counseling services, and ensuring access to rehabilitation services.

  18. Stability of glassy hierarchical networks

    Science.gov (United States)

    Zamani, M.; Camargo-Forero, L.; Vicsek, T.

    2018-02-01

    The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

  19. Statistical measures of galaxy clustering

    International Nuclear Information System (INIS)

    Porter, D.H.

    1988-01-01

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

  20. Hierarchical capillary adhesion of microcantilevers or hairs

    International Nuclear Information System (INIS)

    Liu Jianlin; Feng Xiqiao; Xia Re; Zhao Hongping

    2007-01-01

    As a result of capillary forces, animal hairs, carbon nanotubes or nanowires of a periodically or randomly distributed array often assemble into hierarchical structures. In this paper, the energy method is adopted to analyse the capillary adhesion of microsized hairs, which are modelled as clamped microcantilevers wetted by liquids. The critical conditions for capillary adhesion of two hairs, three hairs or two bundles of hairs are derived in terms of Young's contact angle, elastic modulus and geometric sizes of the beams. Then, the hierarchical capillary adhesion of hairs is addressed. It is found that for multiple hairs or microcantilevers, the system tends to take a hierarchical structure as a result of the minimization of the total potential energy of the system. The level number of structural hierarchy increases with the increase in the number of hairs if they are sufficiently long. Additionally, we performed experiments to verify our theoretical solutions for the adhesion of microbeams

  1. Relevant Subspace Clustering

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

    2009-01-01

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

  2. A qualitative multi-attribute model for the selection of the private hydropower plant investments in Turkey: By foundation of the search results clustering engine (Carrot2), hydropower plant clustering, DEXi and DEXiTree

    Energy Technology Data Exchange (ETDEWEB)

    Saracoglu, B.O.

    2016-07-01

    The electricity demand in Turkey has been increasing for a while. Hydropower is one of the major electricity generation types to compensate this electricity demand in Turkey. Private investors (domestic and foreign) in the hydropower electricity generation sector have been looking for the most appropriate and satisfactory new private hydropower investment (PHPI) options and opportunities in Turkey. This study aims to present a qualitative multi-attribute decision making (MADM) model, that is easy, straightforward, and fast for the selection of the most satisfactory reasonable PHPI options during the very early investment stages (data and information poorness on projects). The data and information of the PHPI options was gathered from the official records on the official websites. A wide and deep literature review was conducted for the MADM models and for the hydropower industry. The attributes of the model were identified, selected, clustered and evaluated by the expert decision maker (EDM) opinion and by help of an open source search results clustering engine (Carrot2) (helpful for also comprehension). The PHPI options were clustered according to their installed capacities main property to analyze the options in the most appropriate, decidable, informative, understandable and meaningful way. A simple clustering algorithm for the PHPI options was executed in the current study. A template model for the selection of the most satisfactory PHPI options was built in the DEXi (Decision EXpert for Education) and the DEXiTree software. The basic attributes for the selection of the PHPI options were presented and afterwards the aggregate attributes were defined by the bottom-up structuring for the early investment stages. The attributes were also analyzed by help of Carrot2. The most satisfactory PHPI options in Turkey in the big options data set were selected for each PHPI options cluster by the EDM evaluations in the DEXi. (Author)

  3. Cluster observations of the high-latitude magnetopause and cusp: initial results from the CIS ion instruments

    Directory of Open Access Journals (Sweden)

    J. M. Bosqued

    2001-09-01

    Full Text Available Launched on an elliptical high inclination orbit (apogee: 19.6 RE since January 2001 the Cluster satellites have been conducting the first detailed three-dimensional studies of the high-latitude dayside magnetosphere, including the exterior cusp, neighbouring boundary layers and magnetopause regions. Cluster satellites carry the CIS ion spectrometers that provide high-precision, 3D distributions of low-energy (<35 keV/e ions every 4 s. This paper presents the first two observations of the cusp and/or magnetopause behaviour made under different interplanetary magnetic field (IMF conditions. Flow directions, 3D distribution functions, density profiles and ion composition profiles are analyzed to demonstrate the high variability of high-latitude regions. In the first crossing analyzed (26 January 2001, dusk side, IMF-BZ < 0, multiple, isolated boundary layer, magnetopause and magnetosheath encounters clearly occurred on a quasi-steady basis for ~ 2 hours. CIS ion instruments show systematic accelerated flows in the current layer and adjacent boundary layers on the Earthward side of the magnetopause. Multi-point analysis of the magnetopause, combining magnetic and plasma data from the four Cluster spacecraft, demonstrates that oscillatory outward-inward motions occur with a normal speed of the order of ± 40 km/s; the thickness of the high-latitude current layer is evaluated to be of the order of 900–1000 km. Alfvénic accelerated flows and D-shaped distributions are convincing signatures of a magnetic reconnection occurring equatorward of the Cluster satellites. Moreover, the internal magnetic and plasma structure of a flux transfer event (FTE is analyzed in detail; its size along the magnetopause surface is ~ 12 000 km and it convects with a velocity of ~ 200 km/s. The second event analyzed (2 February 2001 corresponds to the first Cluster pass within the cusp when the IMF-BZ component was northward directed. The analysis of relevant CIS plasma

  4. Cluster observations of the high-latitude magnetopause and cusp: initial results from the CIS ion instruments

    Directory of Open Access Journals (Sweden)

    J. M. Bosqued

    Full Text Available Launched on an elliptical high inclination orbit (apogee: 19.6 RE since January 2001 the Cluster satellites have been conducting the first detailed three-dimensional studies of the high-latitude dayside magnetosphere, including the exterior cusp, neighbouring boundary layers and magnetopause regions. Cluster satellites carry the CIS ion spectrometers that provide high-precision, 3D distributions of low-energy (<35 keV/e ions every 4 s. This paper presents the first two observations of the cusp and/or magnetopause behaviour made under different interplanetary magnetic field (IMF conditions. Flow directions, 3D distribution functions, density profiles and ion composition profiles are analyzed to demonstrate the high variability of high-latitude regions. In the first crossing analyzed (26 January 2001, dusk side, IMF-BZ < 0, multiple, isolated boundary layer, magnetopause and magnetosheath encounters clearly occurred on a quasi-steady basis for ~ 2 hours. CIS ion instruments show systematic accelerated flows in the current layer and adjacent boundary layers on the Earthward side of the magnetopause. Multi-point analysis of the magnetopause, combining magnetic and plasma data from the four Cluster spacecraft, demonstrates that oscillatory outward-inward motions occur with a normal speed of the order of ± 40 km/s; the thickness of the high-latitude current layer is evaluated to be of the order of 900–1000 km. Alfvénic accelerated flows and D-shaped distributions are convincing signatures of a magnetic reconnection occurring equatorward of the Cluster satellites. Moreover, the internal magnetic and plasma structure of a flux transfer event (FTE is analyzed in detail; its size along the magnetopause surface is ~ 12 000 km and it convects with a velocity of ~ 200 km/s. The second event analyzed (2 February 2001 corresponds to the first Cluster pass within the cusp when the IMF-BZ component was northward directed. The analysis of

  5. Analysis hierarchical model for discrete event systems

    Science.gov (United States)

    Ciortea, E. M.

    2015-11-01

    The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

  6. Self-assembled biomimetic superhydrophobic hierarchical arrays.

    Science.gov (United States)

    Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

    2013-09-01

    Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. Context updates are hierarchical

    Directory of Open Access Journals (Sweden)

    Anton Karl Ingason

    2016-10-01

    Full Text Available This squib studies the order in which elements are added to the shared context of interlocutors in a conversation. It focuses on context updates within one hierarchical structure and argues that structurally higher elements are entered into the context before lower elements, even if the structurally higher elements are pronounced after the lower elements. The crucial data are drawn from a comparison of relative clauses in two head-initial languages, English and Icelandic, and two head-final languages, Korean and Japanese. The findings have consequences for any theory of a dynamic semantics.

  8. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chih-Yu Wen

    2009-05-01

    Full Text Available This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

  9. Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

    Science.gov (United States)

    Wen, Chih-Yu; Chen, Ying-Chih

    2009-01-01

    This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

  10. Evaluation of the Web-Based Computer-Tailored FATaintPHAT Intervention to Promote Energy Balance Among Adolescents Results From a School Cluster Randomized Trial

    NARCIS (Netherlands)

    Ezendam, N.P.M.; Brug, J.; Oenema, A.

    2012-01-01

    Objective: To evaluate the short- and long-term results of FATaintPHAT, a Web-based computer-tailored intervention aiming to increase physical activity, decrease sedentary behavior, and promote healthy eating to contribute to the prevention of excessive weight gain among adolescents. Design: Cluster

  11. Behavioural graded activity results in better exercise adherence and more physical activity than usual care in people with osteoarthritis: a cluster-randomised trial

    NARCIS (Netherlands)

    Pisters, M.F.; Veenhof, C.; de Bakker, D.H.; Schellevis, F.G.; Dekker, J.

    2010-01-01

    Question: Does behavioural graded activity result in better exercise adherence and more physical activity than usual care in people with osteoarthritis of the hip or knee? Design: Analysis of secondary outcomes of a cluster-randomised trial with concealed allocation, assessor blinding, and

  12. Extension of mixture-of-experts networks for binary classification of hierarchical data.

    Science.gov (United States)

    Ng, Shu-Kay; McLachlan, Geoffrey J

    2007-09-01

    For many applied problems in the context of medically relevant artificial intelligence, the data collected exhibit a hierarchical or clustered structure. Ignoring the interdependence between hierarchical data can result in misleading classification. In this paper, we extend the mechanism for mixture-of-experts (ME) networks for binary classification of hierarchical data. Another extension is to quantify cluster-specific information on data hierarchy by random effects via the generalized linear mixed-effects model (GLMM). The extension of ME networks is implemented by allowing for correlation in the hierarchical data in both the gating and expert networks via the GLMM. The proposed model is illustrated using a real thyroid disease data set. In our study, we consider 7652 thyroid diagnosis records from 1984 to early 1987 with complete information on 20 attribute values. We obtain 10 independent random splits of the data into a training set and a test set in the proportions 85% and 15%. The test sets are used to assess the generalization performance of the proposed model, based on the percentage of misclassifications. For comparison, the results obtained from the ME network with independence assumption are also included. With the thyroid disease data, the misclassification rate on test sets for the extended ME network is 8.9%, compared to 13.9% for the ME network. In addition, based on model selection methods described in Section 2, a network with two experts is selected. These two expert networks can be considered as modeling two groups of patients with high and low incidence rates. Significant variation among the predicted cluster-specific random effects is detected in the patient group with low incidence rate. It is shown that the extended ME network outperforms the ME network for binary classification of hierarchical data. With the thyroid disease data, useful information on the relative log odds of patients with diagnosed conditions at different periods can be

  13. Hierarchically nested river landform sequences

    Science.gov (United States)

    Pasternack, G. B.; Weber, M. D.; Brown, R. A.; Baig, D.

    2017-12-01

    River corridors exhibit landforms nested within landforms repeatedly down spatial scales. In this study we developed, tested, and implemented a new way to create river classifications by mapping domains of fluvial processes with respect to the hierarchical organization of topographic complexity that drives fluvial dynamism. We tested this approach on flow convergence routing, a morphodynamic mechanism with different states depending on the structure of nondimensional topographic variability. Five nondimensional landform types with unique functionality (nozzle, wide bar, normal channel, constricted pool, and oversized) represent this process at any flow. When this typology is nested at base flow, bankfull, and floodprone scales it creates a system with up to 125 functional types. This shows how a single mechanism produces complex dynamism via nesting. Given the classification, we answered nine specific scientific questions to investigate the abundance, sequencing, and hierarchical nesting of these new landform types using a 35-km gravel/cobble river segment of the Yuba River in California. The nested structure of flow convergence routing landforms found in this study revealed that bankfull landforms are nested within specific floodprone valley landform types, and these types control bankfull morphodynamics during moderate to large floods. As a result, this study calls into question the prevailing theory that the bankfull channel of a gravel/cobble river is controlled by in-channel, bankfull, and/or small flood flows. Such flows are too small to initiate widespread sediment transport in a gravel/cobble river with topographic complexity.

  14. Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

    Science.gov (United States)

    Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

    2016-01-01

    Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.

  15. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

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

    2012-01-01

    Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose...... a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  16. Clustering of correlated networks

    OpenAIRE

    Dorogovtsev, S. N.

    2003-01-01

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

  17. Static and dynamic friction of hierarchical surfaces.

    Science.gov (United States)

    Costagliola, Gianluca; Bosia, Federico; Pugno, Nicola M

    2016-12-01

    Hierarchical structures are very common in nature, but only recently have they been systematically studied in materials science, in order to understand the specific effects they can have on the mechanical properties of various systems. Structural hierarchy provides a way to tune and optimize macroscopic mechanical properties starting from simple base constituents and new materials are nowadays designed exploiting this possibility. This can be true also in the field of tribology. In this paper we study the effect of hierarchical patterned surfaces on the static and dynamic friction coefficients of an elastic material. Our results are obtained by means of numerical simulations using a one-dimensional spring-block model, which has previously been used to investigate various aspects of friction. Despite the simplicity of the model, we highlight some possible mechanisms that explain how hierarchical structures can significantly modify the friction coefficients of a material, providing a means to achieve tunability.

  18. Deep hierarchical attention network for video description

    Science.gov (United States)

    Li, Shuohao; Tang, Min; Zhang, Jun

    2018-03-01

    Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

  19. A qualitative multi-attribute model for the selection of the private hydropower plant investments in Turkey: By foundation of the search results clustering engine (Carrot2, hydropower plant clustering, DEXi and DEXiTree

    Directory of Open Access Journals (Sweden)

    Burak Omer Saracoglu

    2016-03-01

    Full Text Available Purpose: The electricity demand in Turkey has been increasing for a while. Hydropower is one of the major electricity generation types to compensate this electricity demand in Turkey. Private investors (domestic and foreign in the hydropower electricity generation sector have been looking for the most appropriate and satisfactory new private hydropower investment (PHPI options and opportunities in Turkey. This study aims to present a qualitative multi-attribute decision making (MADM model, that is easy, straightforward, and fast for the selection of the most satisfactory reasonable PHPI options during the very early investment stages (data and information poorness on projects. Design/methodology/approach: The data and information of the PHPI options was gathered from the official records on the official websites. A wide and deep literature review was conducted for the MADM models and for the hydropower industry. The attributes of the model were identified, selected, clustered and evaluated by the expert decision maker (EDM opinion and by help of an open source search results clustering engine (Carrot2 (helpful for also comprehension. The PHPI options were clustered according to their installed capacities main property to analyze the options in the most appropriate, decidable, informative, understandable and meaningful way. A simple clustering algorithm for the PHPI options was executed in the current study. A template model for the selection of the most satisfactory PHPI options was built in the DEXi (Decision EXpert for Education and the DEXiTree software. Findings: The basic attributes for the selection of the PHPI options were presented and afterwards the aggregate attributes were defined by the bottom-up structuring for the early investment stages. The attributes were also analyzed by help of Carrot2. The most satisfactory PHPI options in Turkey in the big options data set were selected for each PHPI options cluster by the EDM evaluations in

  20. Hierarchical quark mass matrices

    International Nuclear Information System (INIS)

    Rasin, A.

    1998-02-01

    I define a set of conditions that the most general hierarchical Yukawa mass matrices have to satisfy so that the leading rotations in the diagonalization matrix are a pair of (2,3) and (1,2) rotations. In addition to Fritzsch structures, examples of such hierarchical structures include also matrices with (1,3) elements of the same order or even much larger than the (1,2) elements. Such matrices can be obtained in the framework of a flavor theory. To leading order, the values of the angle in the (2,3) plane (s 23 ) and the angle in the (1,2) plane (s 12 ) do not depend on the order in which they are taken when diagonalizing. We find that any of the Cabbibo-Kobayashi-Maskawa matrix parametrizations that consist of at least one (1,2) and one (2,3) rotation may be suitable. In the particular case when the s 13 diagonalization angles are sufficiently small compared to the product s 12 s 23 , two special CKM parametrizations emerge: the R 12 R 23 R 12 parametrization follows with s 23 taken before the s 12 rotation, and vice versa for the R 23 R 12 R 23 parametrization. (author)

  1. Hierarchical partial order ranking

    International Nuclear Information System (INIS)

    Carlsen, Lars

    2008-01-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

  2. Fast gene ontology based clustering for microarray experiments.

    Science.gov (United States)

    Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

    2008-11-21

    Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

  3. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2004-01-01

    Full Text Available An unsupervised data clustering method, called the local maximum clustering (LMC method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the -mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999.

  4. Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies

    Science.gov (United States)

    Kocakaplan, Yusuf; Deviren, Bayram; Keskin, Mustafa

    2012-12-01

    We have examined the hierarchical structures of correlations networks among Turkey’s exports and imports by currencies for the 1996-2010 periods, using the concept of a minimal spanning tree (MST) and hierarchical tree (HT) which depend on the concept of ultrametricity. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial markets. We derived a hierarchical organization and build the MSTs and HTs during the 1996-2001 and 2002-2010 periods. The reason for studying two different sub-periods, namely 1996-2001 and 2002-2010, is that the Euro (EUR) came into use in 2001, and some countries have made their exports and imports with Turkey via the EUR since 2002, and in order to test various time-windows and observe temporal evolution. We have carried out bootstrap analysis to associate a value of the statistical reliability to the links of the MSTs and HTs. We have also used the average linkage cluster analysis (ALCA) to observe the cluster structure more clearly. Moreover, we have obtained the bidimensional minimal spanning tree (BMST) due to economic trade being a bidimensional problem. From the structural topologies of these trees, we have identified different clusters of currencies according to their proximity and economic ties. Our results show that some currencies are more important within the network, due to a tighter connection with other currencies. We have also found that the obtained currencies play a key role for Turkey’s exports and imports and have important implications for the design of portfolio and investment strategies.

  5. Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

    Directory of Open Access Journals (Sweden)

    Olszewski Kellen L

    2007-07-01

    Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

  6. Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

    Science.gov (United States)

    Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina

    2018-05-01

    Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.

  7. Militarization, human rights violations and community responses as determinants of health in southeastern Myanmar: results of a cluster survey.

    Science.gov (United States)

    Davis, William W; Mullany, Luke C; Schissler, Matt; Albert, Saw; Beyrer, Chris

    2015-01-01

    The Myanmar army and ethnic armed groups agreed to a preliminary ceasefire in 2012, but a heavy military presence remains in southeastern Myanmar. Qualitative data suggested this militarization can result in human rights abuses in the absence of armed engagements between the parties, and that rural ethnic civilians use a variety of self-protection strategies to avoid these abuses or reduce their negative impacts. We used data from a household survey to determine prevalence of select self-protection activities and to examine exposure to armed groups, human rights violations and self-protection activities as determinants of health in southeastern Myanmar. Data collected from 463 households via a two-stage cluster survey of conflict-affected areas in eastern Myanmar in January 2012, were analyzed using logistic regression models to identify associations between exposure to state and non-state armed groups, village self-protection, human rights abuses and health outcomes. Close proximity to a military base was associated with human rights abuses (PRR 1.30, 95 % CI: 1.14-1.48), inadequate food production (PRR 1.08, 95 % CI: 1.03-1.13), inability to access health care (PRR 1.29, 95 % CI: 1.04-1.60) and diarrhea (PRR 1.15, 95 % CI: 1.05-1.27. Direct exposure to armed groups was associated with household hunger (PRR1.71, 95 % CI: 1.30-2.23). Among households that reported no human rights abuses, risk of household hunger (PRR 5.64, 95 % CI: 1.88-16.91), inadequate food production (PRR 1.95, 95 % CI: 1.11-3.41) and diarrhea (PRR 2.53, 95 % CI: 1.45-4.42) increased when neighbors' households reported experiencing human rights abuses. Households in villages that reported negotiating with the Myanmar army had lower risk of human rights violations (PRR 0.91, 95 % CI: 0.85-0.98), household hunger (PRR 0.85, 95 % CI: 0.74-0.96), inadequate food production (PRR 0.93, 95 % CI:0.89-0.98) and diarrhea (PRR 0.89, 95 % CI:0.82-0.97). Stratified analysis suggests that self

  8. The path to glory is paved with hierarchy: When hierarchical differentiation increases group effectiveness.

    NARCIS (Netherlands)

    Ronay, R.D.; Greenaway, K; Anicich, E.M; Galinsky, A.D.

    2012-01-01

    Two experiments examined the psychological and biological antecedents of hierarchical differentiation and the resulting consequences for productivity and conflict within small groups. In Experiment 1, which used a priming manipulation, hierarchically differentiated groups (i.e., groups comprising 1

  9. Transmutations across hierarchical levels

    International Nuclear Information System (INIS)

    O'Neill, R.V.

    1977-01-01

    The development of large-scale ecological models depends implicitly on a concept known as hierarchy theory which views biological systems in a series of hierarchical levels (i.e., organism, population, trophic level, ecosystem). The theory states that an explanation of a biological phenomenon is provided when it is shown to be the consequence of the activities of the system's components, which are themselves systems in the next lower level of the hierarchy. Thus, the behavior of a population is explained by the behavior of the organisms in the population. The initial step in any modeling project is, therefore, to identify the system components and the interactions between them. A series of examples of transmutations in aquatic and terrestrial ecosystems are presented to show how and why changes occur. The types of changes are summarized and possible implications of transmutation for hierarchy theory, for the modeler, and for the ecological theoretician are discussed

  10. Trees and Hierarchical Structures

    CERN Document Server

    Haeseler, Arndt

    1990-01-01

    The "raison d'etre" of hierarchical dustering theory stems from one basic phe­ nomenon: This is the notorious non-transitivity of similarity relations. In spite of the fact that very often two objects may be quite similar to a third without being that similar to each other, one still wants to dassify objects according to their similarity. This should be achieved by grouping them into a hierarchy of non-overlapping dusters such that any two objects in ~ne duster appear to be more related to each other than they are to objects outside this duster. In everyday life, as well as in essentially every field of scientific investigation, there is an urge to reduce complexity by recognizing and establishing reasonable das­ sification schemes. Unfortunately, this is counterbalanced by the experience of seemingly unavoidable deadlocks caused by the existence of sequences of objects, each comparatively similar to the next, but the last rather different from the first.

  11. Optimisation by hierarchical search

    Science.gov (United States)

    Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

    2015-03-01

    Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

  12. Spatial-area selective retrieval of multiple object-place associations in a hierarchical cognitive map formed by theta phase coding.

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    2009-06-01

    The human cognitive map is known to be hierarchically organized consisting of a set of perceptually clustered landmarks. Patient studies have demonstrated that these cognitive maps are maintained by the hippocampus, while the neural dynamics are still poorly understood. The authors have shown that the neural dynamic "theta phase precession" observed in the rodent hippocampus may be capable of forming hierarchical cognitive maps in humans. In the model, a visual input sequence consisting of object and scene features in the central and peripheral visual fields, respectively, results in the formation of a hierarchical cognitive map for object-place associations. Surprisingly, it is possible for such a complex memory structure to be formed in a few seconds. In this paper, we evaluate the memory retrieval of object-place associations in the hierarchical network formed by theta phase precession. The results show that multiple object-place associations can be retrieved with the initial cue of a scene input. Importantly, according to the wide-to-narrow unidirectional connections among scene units, the spatial area for object-place retrieval can be controlled by the spatial area of the initial cue input. These results indicate that the hierarchical cognitive maps have computational advantages on a spatial-area selective retrieval of multiple object-place associations. Theta phase precession dynamics is suggested as a fundamental neural mechanism of the human cognitive map.

  13. Multicollinearity in hierarchical linear models.

    Science.gov (United States)

    Yu, Han; Jiang, Shanhe; Land, Kenneth C

    2015-09-01

    This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Silver Films with Hierarchical Chirality.

    Science.gov (United States)

    Ma, Liguo; Cao, Yuanyuan; Duan, Yingying; Han, Lu; Che, Shunai

    2017-07-17

    Physical fabrication of chiral metallic films usually results in singular or large-sized chirality, restricting the optical asymmetric responses to long electromagnetic wavelengths. The chiral molecule-induced formation of silver films prepared chemically on a copper substrate through a redox reaction is presented. Three levels of chirality were identified: primary twisted nanoflakes with atomic crystal lattices, secondary helical stacking of these nanoflakes to form nanoplates, and tertiary micrometer-sized circinates consisting of chiral arranged nanoplates. The chiral Ag films exhibited multiple plasmonic absorption- and scattering-based optical activities at UV/Vis wavelengths based on their hierarchical chirality. The Ag films showed chiral selectivity for amino acids in catalytic electrochemical reactions, which originated from their primary atomic crystal lattices. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

    Directory of Open Access Journals (Sweden)

    Jun Ren

    2014-01-01

    Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

  16. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

    2012-01-01

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

  17. clusterMaker: a multi-algorithm clustering plugin for Cytoscape

    Directory of Open Access Journals (Sweden)

    Morris John H

    2011-11-01

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

  18. Evolution of galaxy cluster scaling and structural properties from XMM observations: probing the physics of structure formation

    International Nuclear Information System (INIS)

    Anokhin, Sergey

    2008-01-01

    Clusters of galaxies are the largest gravitationally bound objects in the Universe. It is possible to study the hierarchical structure formation based on these youngest objects in the Universe. In order to complete the results found with hot clusters, we choose the cold distant galaxy clusters selected from The Southern SHARC catalogue. In the same time, we studied archived galaxy clusters to test the theory and treatment analysis. To study these weak cluster of galaxies, we optimized our treatment analysis: in particular, searching for the best background subtraction and modeling it for our surface brightness profile and spectra. Our results are in a good agreement with Scaling Relation obtained from hot galaxy clusters. (author) [fr

  19. Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring.

    Science.gov (United States)

    Durston, Kirk K; Chiu, David Ky; Wong, Andrew Kc; Li, Gary Cl

    2012-07-13

    Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Our results

  20. Relative Expression of Vitamin D Hydroxylases, CYP27B1 and CYP24A1, and of Cyclooxygenase-2 and Heterogeneity of Human Colorectal Cancer in Relation to Age, Gender, Tumor Location, and Malignancy: Results from Factor and Cluster Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Brozek, Wolfgang, E-mail: wolfgang.brozek@gmx.at; Manhardt, Teresa; Kállay, Enikö; Peterlik, Meinrad; Cross, Heide S. [Department of Pathophysiology, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna (Austria)

    2012-07-26

    Previous studies on the significance of vitamin D insufficiency and chronic inflammation in colorectal cancer development clearly indicated that maintenance of cellular homeostasis in the large intestinal epithelium requires balanced interaction of 1,25-(OH){sub 2}D{sub 3} and prostaglandin cellular signaling networks. The present study addresses the question how colorectal cancer pathogenesis depends on alterations of activities of vitamin D hydroxylases, i.e., CYP27B1-encoded 25-hydroxyvitamin D-1α-hydroxylase and CYP24A1-encoded 25-hydroxyvitamin D-24-hydroxylase, and inflammation-induced cyclooxygenase-2 (COX-2). Data from 105 cancer patients on CYP27B1, VDR, CYP24A1, and COX-2 mRNA expression in relation to tumor grade, anatomical location, gender and age were fit into a multivariate model of exploratory factor analysis. Nearly identical results were obtained by the principal factor and the maximum likelihood method, and these were confirmed by hierarchical cluster analysis: Within the eight mutually dependent variables studied four independent constellations were found that identify different features of colorectal cancer pathogenesis: (i) Escape of COX-2 activity from restraints by the CYP27B1/VDR system can initiate cancer growth anywhere in the colorectum regardless of age and gender; (ii) variations in COX-2 expression are mainly responsible for differences in cancer incidence in relation to tumor location; (iii) advancing age has a strong gender-specific influence on cancer incidence; (iv) progression from well differentiated to undifferentiated cancer is solely associated with a rise in CYP24A1 expression.

  1. Relative Expression of Vitamin D Hydroxylases, CYP27B1 and CYP24A1, and of Cyclooxygenase-2 and Heterogeneity of Human Colorectal Cancer in Relation to Age, Gender, Tumor Location, and Malignancy: Results from Factor and Cluster Analysis

    International Nuclear Information System (INIS)

    Brozek, Wolfgang; Manhardt, Teresa; Kállay, Enikö; Peterlik, Meinrad; Cross, Heide S.

    2012-01-01

    Previous studies on the significance of vitamin D insufficiency and chronic inflammation in colorectal cancer development clearly indicated that maintenance of cellular homeostasis in the large intestinal epithelium requires balanced interaction of 1,25-(OH) 2 D 3 and prostaglandin cellular signaling networks. The present study addresses the question how colorectal cancer pathogenesis depends on alterations of activities of vitamin D hydroxylases, i.e., CYP27B1-encoded 25-hydroxyvitamin D-1α-hydroxylase and CYP24A1-encoded 25-hydroxyvitamin D-24-hydroxylase, and inflammation-induced cyclooxygenase-2 (COX-2). Data from 105 cancer patients on CYP27B1, VDR, CYP24A1, and COX-2 mRNA expression in relation to tumor grade, anatomical location, gender and age were fit into a multivariate model of exploratory factor analysis. Nearly identical results were obtained by the principal factor and the maximum likelihood method, and these were confirmed by hierarchical cluster analysis: Within the eight mutually dependent variables studied four independent constellations were found that identify different features of colorectal cancer pathogenesis: (i) Escape of COX-2 activity from restraints by the CYP27B1/VDR system can initiate cancer growth anywhere in the colorectum regardless of age and gender; (ii) variations in COX-2 expression are mainly responsible for differences in cancer incidence in relation to tumor location; (iii) advancing age has a strong gender-specific influence on cancer incidence; (iv) progression from well differentiated to undifferentiated cancer is solely associated with a rise in CYP24A1 expression

  2. Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

    Directory of Open Access Journals (Sweden)

    Zahra Sharafi

    2017-01-01

    Full Text Available Background. The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods. The ordinal logistic regression (OLR and hierarchical ordinal logistic regression (HOLR were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™ 4.0 collected from 576 healthy school children were analyzed. Results. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

  3. Rotasi Varimax dan Median Hirarki Cluster Pada Program Raskin di Kabupaten Lombok Barat

    Directory of Open Access Journals (Sweden)

    Desy Komalasari

    2015-11-01

    Full Text Available The granting rice program for poor households (Raskin is one of the West Lombok regency government programs for village poverty. The effectiveness of the program relating to 14 criteria for the poor households Raskin recipients (RTS-PM. The 14 criteria have been grouped into several factors using varimax rotation factor analysis, while the RTS-PM have been grouped using hierarchical median cluster analysis. Four factors obtained based on the analysis. First factor was the house existence, the second factor was the financial ability, the third factor was the house existing facilities, and the four factor was the education of the household head and the purchasing power of clothing. The clustering results using hierarchical median cluster analysis formed 3 clusters. The first cluster contains the RTS-PM which have been grouped into first factor; the second cluster contains the RTS-PM which have been grouped into second and third factor; and the third cluster contains the RTS-PM which have been grouped into fourth factor.

  4. Rotasi Varimax dan Median Hirarki Cluster Pada Program Raskin di Kabupaten Lombok Barat

    Directory of Open Access Journals (Sweden)

    Desy Komalasari

    2015-06-01

    Full Text Available The granting rice program for poor households (Raskin is one of the West Lombok regency government programs for village poverty. The effectiveness of the program relating to 14 criteria for the poor households Raskin recipients (RTS-PM. The 14 criteria have been grouped into several factors using varimax rotation factor analysis, while the RTS-PM have been grouped using hierarchical median cluster analysis. Four factors obtained based on the analysis. First factor was the house existence, the second factor was the financial ability, the third factor was the house existing facilities, and the four factor was the education of the household head and the purchasing power of clothing. The clustering results using hierarchical median cluster analysis formed 3 clusters. The first cluster contains the RTS-PM which have been grouped into first factor; the second cluster contains the RTS-PM which have been grouped into second and third factor; and the third cluster contains the RTS-PM which have been grouped into fourth factor.

  5. Hierarchical Context Modeling for Video Event Recognition.

    Science.gov (United States)

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

    Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

  6. Clusters of Tourism Consumers in Romania

    Directory of Open Access Journals (Sweden)

    Pelau Corina

    2018-03-01

    Full Text Available The analysis and determination of typologies of tourism consumers has been a major concern for scientists, specialists and companies as well. Knowing the demographic and motivational factors that determine consumers to buy tourism products can have a major impact on the marketing strategy by a more efficient targeting of customers. This article presents the results of a research that aims to determine the factors which influence the buying decision for tourism products and the clusters of consumers resulted from these factors. 90 persons have been surveyed pursuing the determination of the most important factors for buying a tourism product and the correlation between them. The factor analysis and the cluster analysis have been applied with the help of the SPSS program. The results of the factor analysis group the items into six factors. In a second phase, the consumers have been divided into three categories based on a hierarchical Ward cluster analysis. The three clusters have been defined and analyzed and recommendations for the future research have been given.

  7. First results from the IllustrisTNG simulations: the stellar mass content of groups and clusters of galaxies

    Science.gov (United States)

    Pillepich, Annalisa; Nelson, Dylan; Hernquist, Lars; Springel, Volker; Pakmor, Rüdiger; Torrey, Paul; Weinberger, Rainer; Genel, Shy; Naiman, Jill P.; Marinacci, Federico; Vogelsberger, Mark

    2018-03-01

    The IllustrisTNG project is a new suite of cosmological magnetohydrodynamical simulations of galaxy formation performed with the AREPO code and updated models for feedback physics. Here, we introduce the first two simulations of the series, TNG100 and TNG300, and quantify the stellar mass content of about 4000 massive galaxy groups and clusters (1013 ≤ M200c/M⊙ ≤ 1015) at recent times (z ≤ 1). The richest clusters have half of their total stellar mass bound to satellite galaxies, with the other half being associated with the central galaxy and the diffuse intracluster light. Haloes more massive than about 5 × 1014 M⊙ have more diffuse stellar mass outside 100 kpc than within 100 kpc, with power-law slopes of the radial mass density distribution as shallow as the dark matter's ( - 3.5 ≲ α3D ≲ -3). Total halo mass is a very good predictor of stellar mass, and vice versa: at z = 0, the 3D stellar mass measured within 30 kpc scales as ∝(M500c)0.49 with a ˜0.12 dex scatter. This is possibly too steep in comparison to the available observational constraints, even though the abundance of The Next Generation less-massive galaxies ( ≲ 1011 M⊙ in stars) is in good agreement with the measured galaxy stellar mass functions at recent epochs. The 3D sizes of massive galaxies fall too on a tight (˜0.16 dex scatter) power-law relation with halo mass, with r^stars_0.5 ∝ (M_200c)^{0.53}. Even more fundamentally, halo mass alone is a good predictor for the whole stellar mass profiles beyond the inner few kiloparsecs, and we show how on average these can be precisely recovered given a single-mass measurement of the galaxy or its halo.

  8. Clustering Dycom

    KAUST Repository

    Minku, Leandro L.; Hou, Siqing

    2017-01-01

    baseline WC model is also included in the analysis. Results: Clustering Dycom with K-Means can potentially help to split the CC projects, managing to achieve similar or better predictive performance than Dycom. However, K-Means still requires the number

  9. Clustering User Behavior in Scientific Collections

    OpenAIRE

    Blixhavn, Øystein Hoel

    2014-01-01

    This master thesis looks at how clustering techniques can be appliedto a collection of scientific documents. Approximately one year of serverlogs from the CERN Document Server (CDS) are analyzed and preprocessed.Based on the findings of this analysis, and a review of thecurrent state of the art, three different clustering methods are selectedfor further work: Simple k-Means, Hierarchical Agglomerative Clustering(HAC) and Graph Partitioning. In addition, a custom, agglomerativeclustering algor...

  10. Eigenspaces of networks reveal the overlapping and hierarchical community structure more precisely

    International Nuclear Information System (INIS)

    Ma, Xiaoke; Gao, Lin; Yong, Xuerong

    2010-01-01

    Identifying community structure is fundamental for revealing the structure–functionality relationship in complex networks, and spectral algorithms have been shown to be powerful for this purpose. In a traditional spectral algorithm, each vertex of a network is embedded into a spectral space by making use of the eigenvectors of the adjacency matrix or Laplacian matrix of the graph. In this paper, a novel spectral approach for revealing the overlapping and hierarchical community structure of complex networks is proposed by not only using the eigenvalues and eigenvectors but also the properties of eigenspaces of the networks involved. This gives us a better characterization of community. We first show that the communicability between a pair of vertices can be rewritten in term of eigenspaces of a network. An agglomerative clustering algorithm is then presented to discover the hierarchical communities using the communicability matrix. Finally, these overlapping vertices are discovered with the corresponding eigenspaces, based on the fact that the vertices more densely connected amongst one another are more likely to be linked through short cycles. Compared with the traditional spectral algorithms, our algorithm can identify both the overlapping and hierarchical community without increasing the time complexity O(n 3 ), where n is the size of the network. Furthermore, our algorithm can also distinguish the overlapping vertices from bridges. The method is tested by applying it to some computer-generated and real-world networks. The experimental results indicate that our algorithm can reveal community structure more precisely than the traditional spectral approaches

  11. A CLUSTER IN THE MAKING: ALMA REVEALS THE INITIAL CONDITIONS FOR HIGH-MASS CLUSTER FORMATION

    International Nuclear Information System (INIS)

    Rathborne, J. M.; Contreras, Y.; Longmore, S. N.; Bastian, N.; Jackson, J. M.; Alves, J. F.; Bally, J.; Foster, J. B.; Garay, G.; Kruijssen, J. M. D.; Testi, L.; Walsh, A. J.

    2015-01-01

    G0.253+0.016 is a molecular clump that appears to be on the verge of forming a high-mass cluster: its extremely low dust temperature, high mass, and high density, combined with its lack of prevalent star formation, make it an excellent candidate for an Arches-like cluster in a very early stage of formation. Here we present new Atacama Large Millimeter/Sub-millimeter Array observations of its small-scale (∼0.07 pc) 3 mm dust continuum and molecular line emission from 17 different species that probe a range of distinct physical and chemical conditions. The data reveal a complex network of emission features with a complicated velocity structure: there is emission on all spatial scales, the morphology of which ranges from small, compact regions to extended, filamentary structures that are seen in both emission and absorption. The dust column density is well traced by molecules with higher excitation energies and critical densities, consistent with a clump that has a denser interior. A statistical analysis supports the idea that turbulence shapes the observed gas structure within G0.253+0.016. We find a clear break in the turbulent power spectrum derived from the optically thin dust continuum emission at a spatial scale of ∼0.1 pc, which may correspond to the spatial scale at which gravity has overcome the thermal pressure. We suggest that G0.253+0.016 is on the verge of forming a cluster from hierarchical, filamentary structures that arise from a highly turbulent medium. Although the stellar distribution within high-mass Arches-like clusters is compact, centrally condensed, and smooth, the observed gas distribution within G0.253+0.016 is extended, with no high-mass central concentration, and has a complex, hierarchical structure. If this clump gives rise to a high-mass cluster and its stars are formed from this initially hierarchical gas structure, then the resulting cluster must evolve into a centrally condensed structure via a dynamical process

  12. A new hierarchical method to find community structure in networks

    Science.gov (United States)

    Saoud, Bilal; Moussaoui, Abdelouahab

    2018-04-01

    Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

  13. CATCHprofiles: Clustering and Alignment Tool for ChIP Profiles

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  14. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    David Meunier

    2009-10-01

    Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  15. Forecasting building energy consumption with hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system

    Energy Technology Data Exchange (ETDEWEB)

    Li, Kangji [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China); School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013 (China); Su, Hongye [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China)

    2010-11-15

    There are several ways to forecast building energy consumption, varying from simple regression to models based on physical principles. In this paper, a new method, namely, the hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model is developed. In this model, hierarchical structure decreases the rule base dimension. Both clustering and rule base parameters are optimized by GAs and neural networks (NNs). The model is applied to predict a hotel's daily air conditioning consumption for a period over 3 months. The results obtained by the proposed model are presented and compared with regular method of NNs, which indicates that GA-HANFIS model possesses better performance than NNs in terms of their forecasting accuracy. (author)

  16. A Link-Based Cluster Ensemble Approach For Improved Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    P.Balaji

    2015-01-01

    Full Text Available Abstract It is difficult from possibilities to select a most suitable effective way of clustering algorithm and its dataset for a defined set of gene expression data because we have a huge number of ways and huge number of gene expressions. At present many researchers are preferring to use hierarchical clustering in different forms this is no more totally optimal. Cluster ensemble research can solve this type of problem by automatically merging multiple data partitions from a wide range of different clusterings of any dimensions to improve both the quality and robustness of the clustering result. But we have many existing ensemble approaches using an association matrix to condense sample-cluster and co-occurrence statistics and relations within the ensemble are encapsulated only at raw level while the existing among clusters are totally discriminated. Finding these missing associations can greatly expand the capability of those ensemble methodologies for microarray data clustering. We propose general K-means cluster ensemble approach for the clustering of general categorical data into required number of partitions.

  17. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

    The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

  18. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

  19. Clustering Methods Application for Customer Segmentation to Manage Advertisement Campaign

    Directory of Open Access Journals (Sweden)

    Maciej Kutera

    2010-10-01

    Full Text Available Clustering methods are recently so advanced elaborated algorithms for large collection data analysis that they have been already included today to data mining methods. Clustering methods are nowadays larger and larger group of methods, very quickly evolving and having more and more various applications. In the article, our research concerning usefulness of clustering methods in customer segmentation to manage advertisement campaign is presented. We introduce results obtained by using four selected methods which have been chosen because their peculiarities suggested their applicability to our purposes. One of the analyzed method k-means clustering with random selected initial cluster seeds gave very good results in customer segmentation to manage advertisement campaign and these results were presented in details in the article. In contrast one of the methods (hierarchical average linkage was found useless in customer segmentation. Further investigations concerning benefits of clustering methods in customer segmentation to manage advertisement campaign is worth continuing, particularly that finding solutions in this field can give measurable profits for marketing activity.

  20. Integration of family planning services into HIV care clinics: Results one year after a cluster randomized controlled trial in Kenya.

    Directory of Open Access Journals (Sweden)

    Craig R Cohen

    Full Text Available To determine if integration of family planning (FP and HIV services led to increased use of more effective contraception (i.e. hormonal and permanent methods, and intrauterine devices and decreased pregnancy rates.Cohort analysis following cluster randomized trial, when the Kenya Ministry of Health led integration of the remaining control (delayed integration sites and oversaw integrated services at the original intervention (early integration sites.Eighteen health facilities in Kenya.Women aged 18-45 receiving care: 5682 encounters at baseline, and 11628 encounters during the fourth quarter of year 2."One-stop shop" approach to integrating FP and HIV services.Use of more effective contraceptive methods and incident pregnancy across two years of follow-up.Following integration of FP and HIV services at the six delayed integration clinics, use of more effective contraception increased from 31.7% to 44.2% of encounters (+12.5%; Prevalence ratio (PR = 1.39 (1.19-1.63. Among the twelve early integration sites, the proportion of encounters at which women used more effective contraceptive methods was sustained from the end of the first to the second year of follow-up (37.5% vs. 37.0%. Pregnancy incidence including all 18 integrated sites in year two declined in comparison to the control arm in year one (rate ratio: 0.72; 95% CI 0.60-0.87.Integration of FP services into HIV clinics led to a sustained increase in the use of more effective contraceptives and decrease in pregnancy incidence 24 months following implementation of the integrated service model.ClinicalTrials.gov NCT01001507.

  1. Topology of the correlation networks among major currencies using hierarchical structure methods

    Science.gov (United States)

    Keskin, Mustafa; Deviren, Bayram; Kocakaplan, Yusuf

    2011-02-01

    We studied the topology of correlation networks among 34 major currencies using the concept of a minimal spanning tree and hierarchical tree for the full years of 2007-2008 when major economic turbulence occurred. We used the USD (US Dollar) and the TL (Turkish Lira) as numeraires in which the USD was the major currency and the TL was the minor currency. We derived a hierarchical organization and constructed minimal spanning trees (MSTs) and hierarchical trees (HTs) for the full years of 2007, 2008 and for the 2007-2008 period. We performed a technique to associate a value of reliability to the links of MSTs and HTs by using bootstrap replicas of data. We also used the average linkage cluster analysis for obtaining the hierarchical trees in the case of the TL as the numeraire. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial data. We illustrated how the minimal spanning trees and their related hierarchical trees developed over a period of time. From these trees we identified different clusters of currencies according to their proximity and economic ties. The clustered structure of the currencies and the key currency in each cluster were obtained and we found that the clusters matched nicely with the geographical regions of corresponding countries in the world such as Asia or Europe. As expected the key currencies were generally those showing major economic activity.

  2. Intercalating graphene with clusters of Fe3O4 nanocrystals for electrochemical supercapacitors

    Science.gov (United States)

    Ke, Qingqing; Tang, Chunhua; Liu, Yanqiong; Liu, Huajun; Wang, John

    2014-04-01

    A hierarchical nanostructure consisting of graphene sheets intercalated by clusters of Fe3O4 nanocystals is developed for high-performance supercapacitor electrode. Here we show that the negatively charged graphene oxide (GO) and positively charged Fe3O4 clusters enable a strong electrostatic interaction, generating a hierarchical 3D nanostructure, which gives rise to the intercalated composites through a rational hydrothermal process. The electrocapacitive behavior of the resultant composites is systematically investigated by cyclic voltammeter and galvanostatic charge-discharge techniques, where a positive synergistic effect between graphene and Fe3O4 clusters is identified. A maximum specific capacitance of 169 F g-1 is achieved in the Fe3O4 clusters decorated with effectively reduced graphene oxide (Fe3O4-rGO-12h), which is much higher than those of rGO (101 F g-1) and Fe3O4 (68 F g-1) at the current density of 1 Ag-1. Moreover, this intercalated hierarchical nanostructure demonstrates a good capacitance retention, retaining over 88% of the initial capacity after 1000 cycles.

  3. A study of hierarchical structure on South China industrial electricity-consumption correlation

    Science.gov (United States)

    Yao, Can-Zhong; Lin, Ji-Nan; Liu, Xiao-Feng

    2016-02-01

    Based on industrial electricity-consumption data of five southern provinces of China from 2005 to 2013, we study the industrial correlation mechanism with MST (minimal spanning tree) and HT (hierarchical tree) models. First, we comparatively analyze the industrial electricity-consumption correlation structure in pre-crisis and after-crisis period using MST model and Bootstrap technique of statistical reliability test of links. Results exhibit that all industrial electricity-consumption trees of five southern provinces of China in pre-crisis and after-crisis time are in formation of chain, and the "center-periphery structure" of those chain-like trees is consistent with industrial specialization in classical industrial chain theory. Additionally, the industrial structure of some provinces is reorganized and transferred in pre-crisis and after-crisis time. Further, the comparative analysis with hierarchical tree and Bootstrap technique demonstrates that as for both observations of GD and overall NF, the industrial electricity-consumption correlation is non-significant clustered in pre-crisis period, whereas it turns significant clustered in after-crisis time. Therefore we propose that in perspective of electricity-consumption, their industrial structures are directed to optimized organization and global correlation. Finally, the analysis of distance of HTs verifies that industrial reorganization and development may strengthen market integration, coordination and correlation of industrial production. Except GZ, other four provinces have a shorter distance of industrial electricity-consumption correlation in after-crisis period, revealing a better performance of regional specialization and integration.

  4. 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

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

    Science.gov (United States)

    2010-01-01

    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 background correction is

  6. Self Organizing Maps to efficiently cluster and functionally interpret protein conformational ensembles

    Directory of Open Access Journals (Sweden)

    Fabio Stella

    2013-09-01

    Full Text Available An approach that combines Self-Organizing maps, hierarchical clustering and network components is presented, aimed at comparing protein conformational ensembles obtained from multiple Molecular Dynamic simulations. As a first result the original ensembles can be summarized by using only the representative conformations of the clusters obtained. In addition the network components analysis allows to discover and interpret the dynamic behavior of the conformations won by each neuron. The results showed the ability of this approach to efficiently derive a functional interpretation of the protein dynamics described by the original conformational ensemble, highlighting its potential as a support for protein engineering.

  7. Community risk factors for ocular Chlamydia infection in Niger: pre-treatment results from a cluster-randomized trachoma trial.

    Directory of Open Access Journals (Sweden)

    Abdou Amza

    Full Text Available Trachoma control programs utilize mass azithromycin distributions to treat ocular Chlamydia trachomatis as part of an effort to eliminate this disease world-wide. But it remains unclear what the community-level risk factors are for infection.This cluster-randomized, controlled trial entered 48 randomly selected communities in a 2×2 factorial design evaluating the effect of different treatment frequencies and treatment coverage levels. A pretreatment census and examination established the prevalence of risk factors for clinical trachoma and ocular chlamydia infection including years of education of household head, distance to primary water source, presence of household latrine, and facial cleanliness (ocular discharge, nasal discharge, and presence of facial flies. Univariate and multivariate associations were tested using linear regression and Bayes model averaging.There were a total of 24,536 participants (4,484 children aged 0-5 years in 6,235 households in the study. Before treatment in May to July 2010, the community-level prevalence of active trachoma (TF or TI utilizing the World Health Organization [WHO] grading system was 26.0% (95% CI: 21.9% to 30.0% and the mean community-level prevalence of chlamydia infection by Amplicor PCR was 20.7% (95% CI: 16.5% to 24.9% in children aged 0-5 years. Univariate analysis showed that nasal discharge (0.29, 95% CI: 0.04 to 0.54; P = 0.03, presence of flies on the face (0.40, 95% CI: 0.17 to 0.64; P = 0.001, and years of formal education completed by the head of household (0.07, 95% CI: 0.07 to 0.13; P = 0.03 were independent risk factors for chlamydia infection. In multivariate analysis, facial flies (0.26, 95% CI: 0.02 to 0.49; P = 0.03 and years of formal education completed by the head of household (0.06, 95% CI: 0.008 to 0.11; P = 0.02 were associated risk factors for ocular chlamydial infection.We have found that the presence of facial flies and years of education of the head

  8. Reduced in-hospital mortality for heart failure with clinical pathways: the results of a cluster randomised controlled trial.

    Science.gov (United States)

    Panella, M; Marchisio, S; Demarchi, M L; Manzoli, L; Di Stanislao, F

    2009-10-01

    Hospital treatment of heart failure (HF) frequently does not follow published guidelines, potentially contributing to HF high morbidity, mortality and economic cost. The Experimental Prospective Study on the Effectiveness and Efficiency of the Implementation of Clinical Pathways was undertaken to determine how clinical pathways (CP) for hospital treatment of HF affected care variability, guidelines adherence, in-hospital mortality and outcomes at discharge. Methods/ Two-arm, cluster-randomised trial. Fourteen community hospitals were randomised either to the experimental arm (CP: appropriate therapeutic guidelines use, new organisation and procedures, patient education) or to the control arm (usual care). The main outcome was in-hospital mortality; secondary outcomes were length and appropriateness of the stay, rate of unscheduled readmissions, customer satisfaction, usage of diagnostic and therapeutic procedures during hospital stay and quality indicators at discharge. All outcomes were measured using validated instruments available in literature. In-hospital mortality was 5.6% in the experimental arm (n = 12); 15.4% in controls (n = 33, p = 0.001). In CP and usual care groups, the mean rates of unscheduled readmissions were 7.9% and 13.9%, respectively. Adjusting for age, smoking, New York Heart Association score, hypertension and source of referral, patients in the CP group, as compared to controls, had a significantly lower risk of in-hospital death (OR 0.18; 95% CI 0.07 to 0.46) and unscheduled readmissions (OR 0.42; 95% CI 0.20 to 0.87). No differences were found between CP and control with respect to the appropriateness of the stay, costs and patient's satisfaction. Except for electrocardiography, all recommended diagnostic procedures were used more in the CP group. Similarly, pharmaceuticals use was significantly greater in CP, with the exception of diuretics and anti-platelets agents. The introduction of a specifically tailored CP for the hospital

  9. Cluster headache

    Science.gov (United States)

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

  10. SU-E-J-98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis

    International Nuclear Information System (INIS)

    Harmon, S; Wendelberger, B; Jeraj, R

    2014-01-01

    Purpose: Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET-imaging features, assessed with various clustering algorithms. Methods: [ 18 F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in-house segmentation algorithm combining gradient and region-growing techniques; resulting ROIs were used to extract 54 PET-based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC-associated genes-ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K-means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets. Results: Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JI mean = 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full-gene set (JI =1) for all values of K, and the agreement between the GOI set and the full-gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K-means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JI range : 0.2301–1). Conclusion: Using commonly-used clustering algorithms, we found

  11. SU-E-J-98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Harmon, S; Wendelberger, B [University of Wisconsin-Madison, Madison, WI (United States); Jeraj, R [University of Wisconsin-Madison, Madison, WI (United States); University of Ljubljana (Slovenia)

    2014-06-01

    Purpose: Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET-imaging features, assessed with various clustering algorithms. Methods: [{sup 18}F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in-house segmentation algorithm combining gradient and region-growing techniques; resulting ROIs were used to extract 54 PET-based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC-associated genes-ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K-means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets. Results: Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JI{sub mean}= 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full-gene set (JI =1) for all values of K, and the agreement between the GOI set and the full-gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K-means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JI{sub range}: 0.2301–1). Conclusion: Using commonly-used clustering algorithms

  12. Not all stars form in clusters - measuring the kinematics of OB associations with Gaia

    Science.gov (United States)

    Ward, Jacob L.; Kruijssen, J. M. Diederik

    2018-04-01

    It is often stated that star clusters are the fundamental units of star formation and that most (if not all) stars form in dense stellar clusters. In this monolithic formation scenario, low-density OB associations are formed from the expansion of gravitationally bound clusters following gas expulsion due to stellar feedback. N-body simulations of this process show that OB associations formed this way retain signs of expansion and elevated radial anisotropy over tens of Myr. However, recent theoretical and observational studies suggest that star formation is a hierarchical process, following the fractal nature of natal molecular clouds and allowing the formation of large-scale associations in situ. We distinguish between these two scenarios by characterizing the kinematics of OB associations using the Tycho-Gaia Astrometric Solution catalogue. To this end, we quantify four key kinematic diagnostics: the number ratio of stars with positive radial velocities to those with negative radial velocities, the median radial velocity, the median radial velocity normalized by the tangential velocity, and the radial anisotropy parameter. Each quantity presents a useful diagnostic of whether the association was more compact in the past. We compare these diagnostics to models representing random motion and the expanding products of monolithic cluster formation. None of these diagnostics show evidence of expansion, either from a single cluster or multiple clusters, and the observed kinematics are better represented by a random velocity distribution. This result favours the hierarchical star formation model in which a minority of stars forms in bound clusters and large-scale, hierarchically structured associations are formed in situ.

  13. Robustness of Multiple Clustering Algorithms on Hyperspectral Images

    National Research Council Canada - National Science Library

    Williams, Jason P

    2007-01-01

    .... Various clustering algorithms were employed, including a hierarchical method, ISODATA, K-means, and X-means, and were used on a simple two dimensional dataset in order to discover potential problems with the algorithms...

  14. DOCUMENT REPRESENTATION FOR CLUSTERING OF SCIENTIFIC ABSTRACTS

    Directory of Open Access Journals (Sweden)

    S. V. Popova

    2014-01-01

    Full Text Available The key issue of the present paper is clustering of narrow-domain short texts, such as scientific abstracts. The work is based on the observations made when improving the performance of key phrase extraction algorithm. An extended stop-words list was used that was built automatically for the purposes of key phrase extraction and gave the possibility for a considerable quality enhancement of the phrases extracted from scientific publications. A description of the stop- words list creation procedure is given. The main objective is to investigate the possibilities to increase the performance and/or speed of clustering by the above-mentioned list of stop-words as well as information about lexeme parts of speech. In the latter case a vocabulary is applied for the document representation, which contains not all the words that occurred in the collection, but only nouns and adjectives or their sequences encountered in the documents. Two base clustering algorithms are applied: k-means and hierarchical clustering (average agglomerative method. The results show that the use of an extended stop-words list and adjective-noun document representation makes it possible to improve the performance and speed of k-means clustering. In a similar case for average agglomerative method a decline in performance quality may be observed. It is shown that the use of adjective-noun sequences for document representation lowers the clustering quality for both algorithms and can be justified only when a considerable reduction of feature space dimensionality is necessary.

  15. A Hierarchical Agency Model of Deposit Insurance

    OpenAIRE

    Jonathan Carroll; Shino Takayama

    2010-01-01

    This paper develops a hierarchical agency model of deposit insurance. The main purpose is to undertake a game theoretic analysis of the consequences of deposit insurance schemes and their effects on monitoring incentives for banks. Using this simple framework, we analyze both risk- independent and risk-dependent premium schemes along with reserve requirement constraints. The results provide policymakers with not only a better understanding of the effects of deposit insurance on welfare and th...

  16. Application of cluster analysis to geochemical compositional data for identifying ore-related geochemical anomalies

    Science.gov (United States)

    Zhou, Shuguang; Zhou, Kefa; Wang, Jinlin; Yang, Genfang; Wang, Shanshan

    2017-12-01

    Cluster analysis is a well-known technique that is used to analyze various types of data. In this study, cluster analysis is applied to geochemical data that describe 1444 stream sediment samples collected in northwestern Xinjiang with a sample spacing of approximately 2 km. Three algorithms (the hierarchical, k-means, and fuzzy c-means algorithms) and six data transformation methods (the z-score standardization, ZST; the logarithmic transformation, LT; the additive log-ratio transformation, ALT; the centered log-ratio transformation, CLT; the isometric log-ratio transformation, ILT; and no transformation, NT) are compared in terms of their effects on the cluster analysis of the geochemical compositional data. The study shows that, on the one hand, the ZST does not affect the results of column- or variable-based (R-type) cluster analysis, whereas the other methods, including the LT, the ALT, and the CLT, have substantial effects on the results. On the other hand, the results of the row- or observation-based (Q-type) cluster analysis obtained from the geochemical data after applying NT and the ZST are relatively poor. However, we derive some improved results from the geochemical data after applying the CLT, the ILT, the LT, and the ALT. Moreover, the k-means and fuzzy c-means clustering algorithms are more reliable than the hierarchical algorithm when they are used to cluster the geochemical data. We apply cluster analysis to the geochemical data to explore for Au deposits within the study area, and we obtain a good correlation between the results retrieved by combining the CLT or the ILT with the k-means or fuzzy c-means algorithms and the potential zones of Au mineralization. Therefore, we suggest that the combination of the CLT or the ILT with the k-means or fuzzy c-means algorithms is an effective tool to identify potential zones of mineralization from geochemical data.

  17. Energy Aware Clustering Algorithms for Wireless Sensor Networks

    Science.gov (United States)

    Rakhshan, Noushin; Rafsanjani, Marjan Kuchaki; Liu, Chenglian

    2011-09-01

    The sensor nodes deployed in wireless sensor networks (WSNs) are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. In wireless sensor networks, hierarchical network structures have the advantage of providing scalable and energy efficient solutions. In this paper, we investigate different clustering algorithms for WSNs and also compare these clustering algorithms based on metrics such as clustering distribution, cluster's load balancing, Cluster Head's (CH) selection strategy, CH's role rotation, node mobility, clusters overlapping, intra-cluster communications, reliability, security and location awareness.

  18. Planck early results. XXVI. Detection with Planck and confirmation by XMM-Newton of PLCK G266.6-27.3, an exceptionally X-ray luminous and massive galaxy cluster at z ~ 1

    DEFF Research Database (Denmark)

    Lähteenmäki, A.; Poutanen, T.; Natoli, P.

    2011-01-01

    We present first results on PLCKG266.6-27.3, a galaxy cluster candidate detected at a signal-to-noise ratio of 5 in the Planck All Sky survey. An XMM-Newton validation observation has allowed us to confirm that the candidate isa bona fide galaxy cluster. With these X-ray data we measure an accurate...

  19. Comparisons of Flow Patterns over a Hierarchical and a Non-hierarchical Surface in Relation to Biofouling Control

    Directory of Open Access Journals (Sweden)

    Bin Ahmad Fawzan Mohammed Ridha

    2018-01-01

    Full Text Available Biofouling can be defined as unwanted deposition and development of organisms on submerged surfaces. It is a major problem as it causes water contamination, infrastructures damage and increase in maintenance and operational cost especially in the shipping industry. There are a few methods that can prevent this problem. One of the most effective methods which is using chemicals particularly Tributyltin has been banned due to adverse effects on the environment. One of the non-toxic methods found to be effective is surface modification which involves altering the surface topography so that it becomes a low-fouling or a non-stick surface to biofouling organisms. Current literature suggested that non-hierarchical topographies has lower antifouling performance compared to hierarchical topographies. It is still unclear if the effects of the flow on these topographies could have aided in their antifouling properties. This research will use Computational Fluid Dynamics (CFD simulations to study the flow on these two topographies which also involves comparison study of the topographies used. According to the results obtained, it is shown that hierarchical topography has higher antifouling performance compared to non-hierarchical topography. This is because the fluid characteristics at the hierarchical topography is more favorable in controlling biofouling. In addition, hierarchical topography has higher wall shear stress distribution compared to non-hierarchical topography

  20. Parallel hierarchical global illumination

    Energy Technology Data Exchange (ETDEWEB)

    Snell, Quinn O. [Iowa State Univ., Ames, IA (United States)

    1997-10-08

    Solving the global illumination problem is equivalent to determining the intensity of every wavelength of light in all directions at every point in a given scene. The complexity of the problem has led researchers to use approximation methods for solving the problem on serial computers. Rather than using an approximation method, such as backward ray tracing or radiosity, the authors have chosen to solve the Rendering Equation by direct simulation of light transport from the light sources. This paper presents an algorithm that solves the Rendering Equation to any desired accuracy, and can be run in parallel on distributed memory or shared memory computer systems with excellent scaling properties. It appears superior in both speed and physical correctness to recent published methods involving bidirectional ray tracing or hybrid treatments of diffuse and specular surfaces. Like progressive radiosity methods, it dynamically refines the geometry decomposition where required, but does so without the excessive storage requirements for ray histories. The algorithm, called Photon, produces a scene which converges to the global illumination solution. This amounts to a huge task for a 1997-vintage serial computer, but using the power of a parallel supercomputer significantly reduces the time required to generate a solution. Currently, Photon can be run on most parallel environments from a shared memory multiprocessor to a parallel supercomputer, as well as on clusters of heterogeneous workstations.

  1. Hierarchical clustering of RGB surface water images based on MIA ...

    African Journals Online (AJOL)

    2009-11-25

    Nov 25, 2009 ... similar water-related images within a testing database of 126 RGB images. .... consequently treated by SVD-based PCA and the PCA outputs partitioned into .... green. Other colours, mostly brown and grey, dominate in.

  2. The Case for A Hierarchal System Model for Linux Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Seager, M; Gorda, B

    2009-06-05

    The computer industry today is no longer driven, as it was in the 40s, 50s and 60s, by High-performance computing requirements. Rather, HPC systems, especially Leadership class systems, sit on top of a pyramid investment mode. Figure 1 shows a representative pyramid investment model for systems hardware. At the base of the pyramid is the huge investment (order 10s of Billions of US Dollars per year) in semiconductor fabrication and process technologies. These costs, which are approximately doubling with every generation, are funded from investments multiple markets: enterprise, desktops, games, embedded and specialized devices. Over and above these base technology investments are investments for critical technology elements such as microprocessor, chipsets and memory ASIC components. Investments for these components are spread across the same markets as the base semiconductor processes investments. These second tier investments are approximately half the size of the lower level of the pyramid. The next technology investment layer up, tier 3, is more focused on scalable computing systems such as those needed for HPC and other markets. These tier 3 technology elements include networking (SAN, WAN and LAN), interconnects and large scalable SMP designs. Above these is tier 4 are relatively small investments necessary to build very large, scalable systems high-end or Leadership class systems. Primary among these are the specialized network designs of vertically integrated systems, etc.

  3. Generating Clustered Journal Maps : An Automated System for Hierarchical Classification

    NARCIS (Netherlands)

    Leydesdorff, L.; Bornmann, L.; Wagner, C.S.

    2017-01-01

    Journal maps and classifications for 11,359 journals listed in the combined Journal Citation Reports 2015 of the Science and Social Sciences Citation Indexes are provided at https://leydesdorff.github.io/journals/ and http://www.leydesdorff.net/jcr15. A routine using VOSviewer for integrating the

  4. Exploitation of Clustering Techniques in Transactional Healthcare Data

    Directory of Open Access Journals (Sweden)

    Naeem Ahmad Mahoto

    2014-03-01

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

  5. Synchronous Firefly Algorithm for Cluster Head Selection in WSN

    Directory of Open Access Journals (Sweden)

    Madhusudhanan Baskaran

    2015-01-01

    Full Text Available Wireless Sensor Network (WSN consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC.

  6. Application of hierarchical matrices for partial inverse

    KAUST Repository

    Litvinenko, Alexander

    2013-11-26

    In this work we combine hierarchical matrix techniques (Hackbusch, 1999) and domain decomposition methods to obtain fast and efficient algorithms for the solution of multiscale problems. This combination results in the hierarchical domain decomposition (HDD) method, which can be applied for solution multi-scale problems. Multiscale problems are problems that require the use of different length scales. Using only the finest scale is very expensive, if not impossible, in computational time and memory. Domain decomposition methods decompose the complete problem into smaller systems of equations corresponding to boundary value problems in subdomains. Then fast solvers can be applied to each subdomain. Subproblems in subdomains are independent, much smaller and require less computational resources as the initial problem.

  7. Quantum Ising model on hierarchical structures

    International Nuclear Information System (INIS)

    Lin Zhifang; Tao Ruibao.

    1989-11-01

    A quantum Ising chain with both the exchange couplings and the transverse fields arranged in a hierarchical way is considered. Exact analytical results for the critical line and energy gap are obtained. It is shown that when R 1 not= R 2 , where R 1 and R 2 are the hierarchical parameters for the exchange couplings and the transverse fields, respectively, the system undergoes a phase transition in a different universality class from the pure quantum Ising chain with R 1 =R 2 =1. On the other hand, when R 1 =R 2 =R, there exists a critical value R c dependent on the furcating number of the hierarchy. In case of R > R c , the system is shown to exhibit as Ising-like critical point with the critical behaviour the same as in the pure case, while for R c the system belongs to another universality class. (author). 19 refs, 2 figs

  8. Hierarchical State Machines as Modular Horn Clauses

    Directory of Open Access Journals (Sweden)

    Pierre-Loïc Garoche

    2016-07-01

    Full Text Available In model based development, embedded systems are modeled using a mix of dataflow formalism, that capture the flow of computation, and hierarchical state machines, that capture the modal behavior of the system. For safety analysis, existing approaches rely on a compilation scheme that transform the original model (dataflow and state machines into a pure dataflow formalism. Such compilation often result in loss of important structural information that capture the modal behaviour of the system. In previous work we have developed a compilation technique from a dataflow formalism into modular Horn clauses. In this paper, we present a novel technique that faithfully compile hierarchical state machines into modular Horn clauses. Our compilation technique preserves the structural and modal behavior of the system, making the safety analysis of such models more tractable.

  9. Clusters of Galaxies

    Science.gov (United States)

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

    1981-09-01

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

  10. Formation of stable products from cluster-cluster collisions

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  11. Clustering cliques for graph-based summarization of the biomedical research literature

    DEFF Research Database (Denmark)

    Zhang, Han; Fiszman, Marcelo; Shin, Dongwook

    2013-01-01

    Background: Graph-based notions are increasingly used in biomedical data mining and knowledge discovery tasks. In this paper, we present a clique-clustering method to automatically summarize graphs of semantic predications produced from PubMed citations (titles and abstracts).Results: Sem......Rep is used to extract semantic predications from the citations returned by a PubMed search. Cliques were identified from frequently occurring predications with highly connected arguments filtered by degree centrality. Themes contained in the summary were identified with a hierarchical clustering algorithm...

  12. A Genetic Algorithm That Exchanges Neighboring Centers for Fuzzy c-Means Clustering

    Science.gov (United States)

    Chahine, Firas Safwan

    2012-01-01

    Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major…

  13. Clustering Suicide Attempters: Impulsive-Ambivalent, Well-Planned, or Frequent.

    Science.gov (United States)

    Lopez-Castroman, Jorge; Nogue, Erika; Guillaume, Sebastien; Picot, Marie Christine; Courtet, Philippe

    2016-06-01

    Attempts to predict suicidal behavior within high-risk populations have so far shown insufficient accuracy. Although several psychosocial and clinical features have been consistently associated with suicide attempts, investigations of latent structure in well-characterized populations of suicide attempters are lacking. We analyzed a sample of 1,009 hospitalized suicide attempters that were recruited between 1999 and 2012. Eleven clinically relevant items related to the characteristics of suicidal behavior were submitted to a Hierarchical Ascendant Classification. Phenotypic profiles were compared between the resulting clusters. A decisional tree was constructed to facilitate the differentiation of individuals classified within the first 2 clusters. Most individuals were included in a cluster characterized by less lethal means and planning ("impulse-ambivalent"). A second cluster featured more carefully planned attempts ("well-planned"), more alcohol or drug use before the attempt, and more precautions to avoid interruptions. Finally, a small, third cluster included individuals reporting more attempts ("frequent"), more often serious or violent attempts, and an earlier age at first attempt. Differences across clusters by demographic and clinical characteristics were also found, particularly with the third cluster whose participants had experienced high levels of childhood abuse. Cluster analysis consistently supported 3 distinct clusters of individuals with specific features in their suicidal behaviors and phenotypic profiles that could help clinicians to better focus prevention strategies. © Copyright 2016 Physicians Postgraduate Press, Inc.

  14. Clustering approaches to identifying gene expression patterns from DNA microarray data.

    Science.gov (United States)

    Do, Jin Hwan; Choi, Dong-Kug

    2008-04-30

    The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

  15. False Immunohistochemical Results for Herpesviridae and Other Clusters of Differentiation Due To Biotin Intranuclear Inclusions in the Gestational Endometrium

    Directory of Open Access Journals (Sweden)

    Francesco Rivasi

    2014-02-01

    Conclusions. Immunohistochemical investigations of the gestational endometrium (particularly in pregnancies near to term may yield false results for several herpes viruses, as well as for other immunohistochemical reactions obtained using the ABC method without prior biotin inactivation. [J Interdiscipl Histopathol 2014; 2(1.000: 32-37

  16. IDENTIFICAÇÃO DE CLUSTERS INTERNACIONAIS COM BASE NAS DIMENSÕES CULTURAIS DE HOFSTEDE. / Identification of international clusters based on the hofstede’s cultural dimensions

    Directory of Open Access Journals (Sweden)

    Valderí de Castro Alcântara1

    2012-08-01

    , K-Means Cluster Analysis and Discriminant Analysis to determine and validate groupings of countries based on Hofstede’s cultural dimensions (Distance Index, Individualism, Masculinity and Uncertainty Avoidance Index. The results led to four clusters: Cluster 1 - countries with masculine culture and individualistic; Cluster 2 - collectivistic and uncertainty averse; Cluster 3 - feminine culture and low hierarchical distance and Cluster 4 - culturewith high hierarchical distance and propensity to uncertainty.

  17. A validation of direct grey Dancoff factors results for cylindrical cells in cluster geometry by the Monte Carlo method

    International Nuclear Information System (INIS)

    Rodrigues, Leticia Jenisch; Bogado, Sergio; Vilhena, Marco T.

    2008-01-01

    The WIMS code is a well known and one of the most used codes to handle nuclear core physics calculations. Recently, the PIJM module of the WIMS code was modified in order to allow the calculation of Grey Dancoff factors, for partially absorbing materials, using the alternative definition in terms of escape and collision probabilities. Grey Dancoff factors for the Canadian CANDU-37 and CANFLEX assemblies were calculated with PIJM at five symmetrically distinct fuel pin positions. The results, obtained via Direct Method, i.e., by direct calculation of escape and collision probabilities, were satisfactory when compared with the ones of literature. On the other hand, the PIJMC module was developed to calculate escape and collision probabilities using Monte Carlo method. Modifications in this module were performed to determine Black Dancoff factors, considering perfectly absorbing fuel rods. In this work, we proceed further in the task of validating the Direct Method by the Monte Carlo approach. To this end, the PIJMC routine is modified to compute Grey Dancoff factors using the cited alternative definition. Results are reported for the mentioned CANDU-37 and CANFLEX assemblies obtained with PIJMC, at the same fuel pin positions as with PIJM. A good agreement is observed between the results from the Monte Carlo and Direct methods

  18. Efficacy and effectiveness of an rVSV-vectored vaccine expressing Ebola surface glycoprotein: interim results from the Guinea ring vaccination cluster-randomised trial.

    Science.gov (United States)

    Henao-Restrepo, Ana Maria; Longini, Ira M; Egger, Matthias; Dean, Natalie E; Edmunds, W John; Camacho, Anton; Carroll, Miles W; Doumbia, Moussa; Draguez, Bertrand; Duraffour, Sophie; Enwere, Godwin; Grais, Rebecca; Gunther, Stephan; Hossmann, Stefanie; Kondé, Mandy Kader; Kone, Souleymane; Kuisma, Eeva; Levine, Myron M; Mandal, Sema; Norheim, Gunnstein; Riveros, Ximena; Soumah, Aboubacar; Trelle, Sven; Vicari, Andrea S; Watson, Conall H; Kéïta, Sakoba; Kieny, Marie Paule; Røttingen, John-Arne

    2015-08-29

    A recombinant, replication-competent vesicular stomatitis virus-based vaccine expressing a surface glycoprotein of Zaire Ebolavirus (rVSV-ZEBOV) is a promising Ebola vaccine candidate. We report the results of an interim analysis of a trial of rVSV-ZEBOV in Guinea, west Africa. For this open-label, cluster-randomised ring vaccination trial, suspected cases of Ebola virus disease in Basse-Guinée (Guinea, west Africa) were independently ascertained by Ebola response teams as part of a national surveillance system. After laboratory confirmation of a new case, clusters of all contacts and contacts of contacts were defined and randomly allocated 1:1 to immediate vaccination or delayed (21 days later) vaccination with rVSV-ZEBOV (one dose of 2 × 10(7) plaque-forming units, administered intramuscularly in the deltoid muscle). Adults (age ≥18 years) who were not pregnant or breastfeeding were eligible for vaccination. Block randomisation was used, with randomly varying blocks, stratified by location (urban vs rural) and size of rings (≤20 vs >20 individuals). The study is open label and masking of participants and field teams to the time of vaccination is not possible, but Ebola response teams and laboratory workers were unaware of allocation to immediate or delayed vaccination. Taking into account the incubation period of the virus of about 10 days, the prespecified primary outcome was laboratory-confirmed Ebola virus disease with onset of symptoms at least 10 days after randomisation. The primary analysis was per protocol and compared the incidence of Ebola virus disease in eligible and vaccinated individuals in immediate vaccination clusters with the incidence in eligible individuals in delayed vaccination clusters. This trial is registered with the Pan African Clinical Trials Registry, number PACTR201503001057193. Between April 1, 2015, and July 20, 2015, 90 clusters, with a total population of 7651 people were included in the planned interim analysis. 48 of

  19. Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes.

    Science.gov (United States)

    Kello, Christopher T; Bella, Simone Dalla; Médé, Butovens; Balasubramaniam, Ramesh

    2017-10-01

    Humans talk, sing and play music. Some species of birds and whales sing long and complex songs. All these behaviours and sounds exhibit hierarchical structure-syllables and notes are positioned within words and musical phrases, words and motives in sentences and musical phrases, and so on. We developed a new method to measure and compare hierarchical temporal structures in speech, song and music. The method identifies temporal events as peaks in the sound amplitude envelope, and quantifies event clustering across a range of timescales using Allan factor (AF) variance. AF variances were analysed and compared for over 200 different recordings from more than 16 different categories of signals, including recordings of speech in different contexts and languages, musical compositions and performances from different genres. Non-human vocalizations from two bird species and two types of marine mammals were also analysed for comparison. The resulting patterns of AF variance across timescales were distinct to each of four natural categories of complex sound: speech, popular music, classical music and complex animal vocalizations. Comparisons within and across categories indicated that nested clustering in longer timescales was more prominent when prosodic variation was greater, and when sounds came from interactions among individuals, including interactions between speakers, musicians, and even killer whales. Nested clustering also was more prominent for music compared with speech, and reflected beat structure for popular music and self-similarity across timescales for classical music. In summary, hierarchical temporal structures reflect the behavioural and social processes underlying complex vocalizations and musical performances. © 2017 The Author(s).

  20. Deliberate change without hierarchical influence?

    DEFF Research Database (Denmark)

    Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

    2017-01-01

    reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

  1. Hierarchical unilamellar vesicles of controlled compositional heterogeneity.

    Directory of Open Access Journals (Sweden)

    Maik Hadorn

    Full Text Available Eukaryotic life contains hierarchical vesicular architectures (i.e. organelles that are crucial for material production and trafficking, information storage and access, as well as energy production. In order to perform specific tasks, these compartments differ among each other in their membrane composition and their internal cargo and also differ from the cell membrane and the cytosol. Man-made structures that reproduce this nested architecture not only offer a deeper understanding of the functionalities and evolution of organelle-bearing eukaryotic life but also allow the engineering of novel biomimetic technologies. Here, we show the newly developed vesicle-in-water-in-oil emulsion transfer preparation technique to result in giant unilamellar vesicles internally compartmentalized by unilamellar vesicles of different membrane composition and internal cargo, i.e. hierarchical unilamellar vesicles of controlled compositional heterogeneity. The compartmentalized giant unilamellar vesicles were subsequently isolated by a separation step exploiting the heterogeneity of the membrane composition and the encapsulated cargo. Due to the controlled, efficient, and technically straightforward character of the new preparation technique, this study allows the hierarchical fabrication of compartmentalized giant unilamellar vesicles of controlled compositional heterogeneity and will ease the development of eukaryotic cell mimics that resemble their natural templates as well as the fabrication of novel multi-agent drug delivery systems for combination therapies and complex artificial microreactors.

  2. Anisotropic and Hierarchical Porosity in Multifunctional Ceramics

    Science.gov (United States)

    Lichtner, Aaron Zev

    The performance of multifunctional porous ceramics is often hindered by the seemingly contradictory effects of porosity on both mechanical and non-structural properties and yet a sufficient body of knowledge linking microstructure to these properties does not exist. Using a combination of tailored anisotropic and hierarchical materials, these disparate effects may be reconciled. In this project, a systematic investigation of the processing, characterization and properties of anisotropic and isotropic hierarchically porous ceramics was conducted. The system chosen was a composite ceramic intended as the cathode for a solid oxide fuel cell (SOFC). Comprehensive processing investigations led to the development of approaches to make hierarchical, anisotropic porous microstructures using directional freeze-casting of well dispersed slurries. The effect of all the important processing parameters was investigated. This resulted in an ability to tailor and control the important microstructural features including the scale of the microstructure, the macropore size and total porosity. Comparable isotropic porous ceramics were also processed using fugitive pore formers. A suite of characterization techniques including x-ray tomography and 3-D sectional scanning electron micrographs (FIB-SEM) was used to characterize and quantify the green and partially sintered microstructures. The effect of sintering temperature on the microstructure was quantified and discrete element simulations (DEM) were used to explain the experimental observations. Finally, the comprehensive mechanical properties, at room temperature, were investigated, experimentally and using DEM, for the different microstructures.

  3. Wear of control rod cluster assemblies and of instrumentation thimbles: first results obtained with the vibrateau wear simulator

    International Nuclear Information System (INIS)

    Zbinden, M.; Hersant, D.

    1993-07-01

    Several REP components are affected by a particular sort of damage called impact/sliding wear. This kind of wear, originating from flow induced vibrations, affects loosely supported tubular structures. The main involved components are: - the RCCAs claddings and the guides tubes, - the instrumentation thimbles, - the fuel rods claddings, - the SG tubes. The R and D Division is concerned with studies aiming to understand and to master the phenomena leading to this wear. The MTC Branch is charged of the study of the wear itself. Tests are carried out on wear rigs to understand and to model wear mechanisms. The following work is related to the two first wear tests campaigns on the VIBRATEAU wear simulator: - a reproducibility test series in order to assess the spreading of the experimental results, - a comparative test series on surface treatments used to improve the components war resistance. (authors). 7 figs., 2 tabs., 4 refs

  4. Facile synthesis and photocatalytic activity of zinc oxide hierarchical microcrystals

    KAUST Repository

    Xu, Xinjiang

    2013-04-04

    ZnO microcrystals with hierarchical structure have been synthesized by a simple solvothermal approach. The microcrystals were studied by means of X-ray diffraction, transmission electron microscopy, and scanning electron microscopy. Research on the formation mechanism of the hierarchical microstructure shows that the coordination solvent and precursor concentration have considerable influence on the size and morphology of the microstructures. A possible formation mechanism of the hierarchical structure was suggested. Furthermore, the catalytic activity of the ZnO microcrystals was studied by treating low concentration Rhodamine B (RhB) solution under UV light, and research results show the hierarchical microstructures of ZnO display high catalytic activity in photocatalysis, the catalysis process follows first-order reaction kinetics, and the apparent rate constant k = 0.03195 min-1.

  5. Conceptual hierarchical modeling to describe wetland plant community organization

    Science.gov (United States)

    Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.

    2010-01-01

    Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.

  6. Cluster management.

    Science.gov (United States)

    Katz, R

    1992-11-01

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

  7. The effect of a brief social intervention on the examination results of UK medical students: a cluster randomised controlled trial

    Directory of Open Access Journals (Sweden)

    Dacre Jane

    2009-06-01

    Full Text Available Abstract Background Ethnic minority (EM medical students and doctors underperform academically, but little evidence exists on how to ameliorate the problem. Psychologists Cohen et al. recently demonstrated that a written self-affirmation intervention substantially improved EM adolescents' school grades several months later. Cohen et al.'s methods were replicated in the different setting of UK undergraduate medical education. Methods All 348 Year 3 white (W and EM students at one UK medical school were randomly allocated to an intervention condition (writing about one's own values or a control condition (writing about another's values, via their tutor group. Students and assessors were blind to the existence of the study. Group comparisons on post-intervention written and OSCE (clinical assessment scores adjusted for baseline written assessment scores were made using two-way analysis of covariance. All assessment scores were transformed to z-scores (mean = 0 standard deviation = 1 for ease of comparison. Comparisons between types of words used in essays were calculated using t-tests. The study was covered by University Ethics Committee guidelines. Results Groups were statistically identical at baseline on demographic and psychological factors, and analysis was by intention to treat [intervention group EM n = 95, W n = 79; control group EM n = 77; W n = 84]. As predicted, there was a significant ethnicity by intervention interaction [F(4,334 = 5.74; p = 0.017] on the written assessment. Unexpectedly, this was due to decreased scores in the W intervention group [mean difference = 0.283; (95% CI = 0.093 to 0.474] not improved