Results 101  150 of 1824  
1 2 3 4 5 6 7 8 9 10 >  
Rein Robert   2010
The present paper proposes a technical analysis method for extracting information about movement patterning in studies of motor control, based on a cluster analysis of movement kinematics. In a tutorial fashion, data from three different experiments are presented to exemplify and validate the technical method. When applied to three different ...


Foster David   2010
Ensembles of networks are used as null models in many applications. However, simple null models often show much less clustering than their realworld counterparts. In this paper, we study a "biased rewiring model" where clustering is enhanced by means of a fugacity as in the Strauss (or "triangle") model, but ...


Franz Thomas   2010
This study was concerned with the cluster analysis of saphenous vein graft data to determine a minimum number of diameters, and their values, for the constrictive smoothing of diameter irregularities of a cohort of veins. Mathematical algorithms were developed for data selection, transformation and clustering. Constrictive diameter values were identified ...


Walters Stephen J   2010
AIMS AND OBJECTIVES: The aim of this study is to describe and compare three statistical methods to allow for therapist effects in individually randomised controlled trials. BACKGROUND: In an individually randomised controlled trial where the intervention is delivered by a health professional it seems likely that the effectiveness of the ...


Iwasa Masatomo   2010
Swarm oscillator model derived by one of the authors (Tanaka), where interacting motile elements form various kinds of patterns, is investigated. We particularly focus on the cluster patterns in onedimensional space. We mathematically derive all static and stable configurations in final states for a particular but a large set of ...


Resendes Ana Paula da Costa   2010
To identify areas at risk of dengue transmission by means of cluster analysis. A cluster analysis in which the primary analysis units were the 48 districts of the municipality of Niterói, Southeastern Brazil, was conducted. The districts were grouped into six strata according to sociodemographic conditions, using the kmeans cluster ...


Gupta Gunjan   2010
A key application of clustering data obtained from sources such as microarrays, protein mass spectroscopy, and phylogenetic profiles is the detection of functionally related genes. Typically, only a small number of functionally related genes cluster into one or more groups, and the rest need to be ignored. For such situations, ...


Gianola Daniel   2010
A twostep procedure is presented for analysis of theta (FST) statistics obtained for a battery of loci, which eventually leads to a clustered structure of values. The first step uses a simple Bayesian model for drawing samples from posterior distributions of thetaparameters, but without constructing Markov chains. This step assigns ...


Wisener L V   2010
Using the spatial scan statistic with a Bernoulli model, in a comparison of the two most common canine uroliths, calcium oxalate (CaOx) and magnesium ammonium phosphate (struvite) we determined whether there was evidence of spatial and/or temporal clustering of each urolith type based on canine submissions from Ontario to the ...


Bootstrapbased methods for estimating standard errors in Cox's regression analyses of clustered ...
Xiao Yongling   2010
We propose two bootstrapbased methods to correct the standard errors (SEs) from Cox's model for withincluster correlation of rightcensored event times. The clusterbootstrap method resamples, with replacement, only the clusters, whereas the twostep bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, ...


Molitor John J Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, St Mary's Campus, Norfolk Place, London, UK.   2010
Standard regression analyses are often plagued with problems encountered when one tries to make inference going beyond main effects using data sets that contain dozens of variables that are potentially correlated. This situation arises, for example, in epidemiology where surveys or study questionnaires consisting of a large number of questions ...


Okazaki Naoaki   2010
The ultimate goal of abbreviation management is to disambiguate every occurrence of an abbreviation into its expanded form (concept or sense). To collect expanded forms for abbreviations, previous studies have recognized abbreviations and their expanded forms in parenthetical expressions of biomedical texts. However, expanded forms extracted by abbreviation recognition are ...


Bulatov Aleksandr   2010
In the present communication, we have developed a computational model related to the conception of positional coding via centersofmasses (centroids) of the objects' luminance distributions. The model predictions have been tested by the results of our psychophysical study of geometrical illusion of extent evoked by a modified Brentano figure consisting ...


Knox Craig K   2010
Atomistic molecular dynamics simulations were performed to study hydrated Nafion systems large enough (approximately 2 million atoms, approximately 30 nm box length) to directly observe several hydrophilic domains at the molecular level. These systems consisted of six of the most significant and relevant morphological models of Nafion todate: (1) the ...


Ming Wang   2011
Clustered longitudinal data are often collected as repeated measures on subjects arising in clusters. Examples include periodontal disease study, where the measurements related to the disease status of each tooth are collected over time for each patient, which can be considered as a cluster. For such applications, the number of ...


Bellec Pierre   2010
A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in restingstate functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such restingstate networks (RSNs), which was implemented with kmeans clustering. The core of the method consists ...


Pezzoli Lorenzo   2010
OBJECTIVE: Vaccination programmes targeting disease elimination aim to achieve very high coverage levels (e.g. 95%). We calculated the precision of different clustered lot quality assurance sampling (LQAS) designs in computersimulated surveys to provide local health officers in the field with preset LQAS plans to simply and rapidly assess programmes with ...


Spatiotemporal epidemiology of Campylobacter jejuni enteritis, in an area of Northwest England, ...
Gabriel E   2010
A total of 969 isolates of Campylobacter jejuni originating in the Preston, Lancashire postcode district over a 3year period were characterized using multilocus sequence typing. Recently developed statistical methods and a genetic model were used to investigate temporal, spatial, spatiotemporal and genetic variation in human C. jejuni infections. The analysis ...


Hossain Md Monir   2010
This paper extends the spatial locallikelihood model and the spatial mixture model to the spacetime (ST) domain. For comparison, a standard random effect spacetime (SREST) model is examined to allow evaluation of each model's ability in relation to cluster detection. To pursue this evaluation, we use the ST counterparts of ...


Fuchs Susanne   2010
Most theories of prosodic structure postulate at least two phrasal categories above the word level, a minor and a major one. One correlate of phrasal boundary marking is lengthening on the right edge of a phrase. To gain a theory neutral understanding of the nature of prosodic boundaries, a Gaussian ...


Navlakha Saket   2010
Hierarchical clustering is a popular method for grouping together similar elements based on a distance measure between them. In many cases, annotations for some elements are known beforehand, which can aid the clustering process. We present a novel approach for decomposing a hierarchical clustering into the clusters that optimally match ...


Ioup Juliette W   2010
Several clustering methods are available to group like objects into classes. The K means approach is well established. Both standard and homegrown algorithms have been tested in the following applications. One neural network technique is selforganizing map clustering [T. Kohonen, SelfOrganizing Maps, 2nd ed. Springer, New York (1997)]. Although it ...


Abraham Douglas A   2010
False alarms in active sonar systems are often represented statistically as having a probability density function (PDF) with tails heavier than the traditionally assumed Rayleigh PDF. Distributions such as the Weibull, K, and PoissonRayleigh have been used to represent such nonRayleigh clutter and to derive the associated probabilities of false ...


Kim TaeJoon   2010
We present a novel compressed bounding volume hierarchy (BVH) representation, randomaccessible compressed bounding volume hierarchies (RACBVHs), for various applications requiring random access on BVHs of massive models. Our RACBVH representation is compact and transparently supports random access on the compressed BVHs without decompressing the whole BVH. To support random access ...


Köhn HansFriedrich HF Department of Psychological Sciences, University of Missouri, Columbia, MO 652112500, USA.   2010
The pmedian clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around exemplars, that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, stateoftheart implementations of pmedian clustering are virtually unavailable in ...


Bruzual A Gustavo   2010
In this paper, I review to what extent we can understand the photometric properties of star clusters, and of lowmass, unresolved galaxies, in terms of populationsynthesis models designed to describe 'simple stellar populations' (SSPs), i.e. groups of stars born at the same time, in the same volume of space and ...


Keller Bettina   2010
The identification of metastable states of a molecule plays an important role in the interpretation of molecular simulation data because the freeenergy surface, the relative populations in this landscape, and ultimately also the dynamics of the molecule under study can be described in terms of these states. We compare the ...


Stoner J A JA Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA.   2010
Multilevel nested, correlated data often arise in biomedical research. Examples include teeth nested within quadrants in a mouth or students nested within classrooms in schools. In some settings, cluster sizes may be large relative to the number of independent clusters and the degree of correlation may vary across clusters. When ...


Jonsson Malin K B   2010
To improve proarrhythmic predictability of preclinical models, we assessed whether human ventricularlike embryonic stem cellderived cardiomyocytes (hESCCMs) can be selected following a standardized protocol. Also, we quantified their arrhythmogenic response and compared this to a contemporary used rabbit Purkinje fiber (PF) model. Multiple transmembrane action potentials (AP) were recorded from ...


Han XiaoJing   2010
Based on the fact that the kinetic energy of one atom in small cluster still obeys the Boltzmann distribution, a statistical model is developed to predict the time consumed by a small cluster transforming from one isomer to another and is tested by vast molecular dynamics simulations of C(12) isomers ...


Kaupuzs J   2010
A parallel [open multiprocessing (OpenMP)] implementation of the Wolff singlecluster algorithm has been developed and tested for the threedimensional (3D) Ising model. The developed procedure is generalizable to other lattice spin models and its effectiveness depends on the specific application at hand. The applicability of the developed methodology is discussed ...


Seiler Michael   2010
We have created a standalone software tool, ConsensusCluster, for the analysis of highdimensional single nucleotide polymorphism (SNP) and gene expression microarray data. Our software implements the consensus clustering algorithm and principal component analysis to stratify the data into a given number of robust clusters. The robustness is achieved by combining ...


Alzate Carlos   2010
A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primaldual leastsquares support vector machine (LSSVM) formulations. The formulation allows the extension to outofsample points. In this way, the proposed clustering model can be trained, validated, and ...


Dean Nema   2010
We propose a method for selecting variables in latent class analysis, which is the most common modelbased clustering method for discrete data. The method assesses a variable's usefulness for clustering by comparing two models, given the clustering variables already selected. In one model the variable contributes information about cluster allocation ...


Ross Michelle E ME Department of Biostatistics, University of Washington, Seattle, WA,   2010
Incidence of myelodysplastic syndromes (MDS) has been described in the United States since its inclusion in the Surveillance, Epidemiology, and End Results program in 2001, and the SeattlePuget Sound region of Washington State has among the highest rates of the registries. In this investigation, we described smallscale incidence patterns of ...


Chen DuanRung   2010
Obesity, one of the most significant health problems now facing developed countries, has been increasing steadily in Taiwan. This study addresses how neighborhood factors affect individual obesity by simultaneously examining individuallevel socioeconomic status and neighborhoodlevel characteristics using a multilevel approach combined with a spatial analysis. The data are from Taiwan's ...


Holliday T W   2010
The proximal femur has long been used to distinguish fossil hominin taxa. Specifically, the genus Homo is said to be characterized by larger femoral heads, shorter femoral necks, and more lateral flare of the greater trochanter than are members of the genera Australopithecus or Paranthropus. Here, a digitizing arm was ...


Shatsky Maxim M Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.   2010
Biological macromolecules can adopt multiple conformational and compositional states due to structural flexibility and alternative subunit assemblies. This structural heterogeneity poses a major challenge in the study of macromolecular structure using singleparticle electron microscopy. We propose a fully automated, unsupervised method for the threedimensional reconstruction of multiple structural models from ...


The relationship between leadership, teamworking, structure, burnout and attitude to patients on ...
Bowers Len   2011
Conflict (aggression, substance use, absconding, etc.) and containment (coerced medication, manual restraint, etc.) threaten the safety of patients and staff on psychiatric wards. Previous work has suggested that staff variables may be significant in explaining differences between wards in their rates of these behaviours, and that structure (ward organisation, rules ...


Chen ShyiMing   2010
In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzytrend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical ...


Wang Fei   2010
Maximum margin clustering (MMC) is a newly proposed clustering method which has shown promising performance in recent studies. It extends the computational techniques of support vector machine (SVM) to the unsupervised scenario. Traditionally, MMC is formulated as a nonconvex integer programming problem which makes it difficult to solve. Several methods ...


K?hn Andreas   2010
In explicitly correlated coupledcluster singles and doubles [CCSD(F12)] calculations, the basis set incompleteness error in the double excitations is reduced to such an extent that the error in the HartreeFock energy and the error in the single excitations become important. Using arguments from perturbation theory to systematically truncate the coupledcluster ...


Unsupervised white matter fiber clustering and tract probability map generation: applications of ...
Wassermann D D INRIA Sophia AntipolisMediterranée, Odyssée Project Team, 2004 Route des Lucioles, Sophia Antipolis, 06902, France.   2010
With the increasing importance of fiber tracking in diffusion tensor images for clinical needs, there has been a growing demand for an objective mathematical framework to perform quantitative analysis of white matter fiber bundles incorporating their underlying physical significance. This article presents such a novel mathematical framework that facilitates mathematical ...


Layton Anita T   2010
A new, regionbased mathematical model of the urine concentrating mechanism of the rat renal inner medulla (IM) was used to investigate the significance of transport and structural properties revealed in recent studies that employed immunohistochemical methods combined with threedimensional computerized reconstruction. The model simulates preferential interactions among tubules and vessels ...


Oyana Tonny J   2010
The central purpose of this study is to further evaluate the quality of the performance of a new algorithm. The study provides additional evidence on this algorithm that was designed to increase the overall efficiency of the original kmeans clustering techniquethe Fast, Efficient, and Scalable kmeans algorithm (FESkmeans). The FESkmeans ...


Martins David   2010
Background. Renal disease is commonly described as a complication of metabolic syndrome (MetS) but some recent studies suggest that Chronic Kidney disease (CKD) may actually antecede MetS. Few studies have explored the predictive utility of coclustering CKD with MetS for cardiovascular disease (CVD) mortality. Methods. Data from a nationally representative ...


Zheng Fengbin   2010
A subset selected by a supervised feature selection method may not be a good one for unsupervised learning and vice versa. We propose a novel Feature Selection algorithm through Feature Clustering, FSFC. FSFC does not need the class label information in the data set and is suitable for both supervised ...


Gangnon Ronald E   2010
The spatial scan statistic is a widely applied tool for cluster detection. The spatial scan statistic evaluates the significance of a series of potential circular clusters using Monte Carlo simulation to account for the multiplicity of comparisons. In most settings, the extent of the multiplicity problem varies across the study ...


Nugent Rebecca   2010
In molecular biology, we are often interested in determining the group structure in, e.g., a population of cells or microarray gene expression data. Clustering methods identify groups of similar observations, but the results can depend on the chosen method's assumptions and starting parameter values. In this chapter, we give a ...


Guo Ying   2010
Brain imaging data have shown great promise as a useful predictor for psychiatric conditions, cognitive functions and many other neuralrelated outcomes. Development of prediction models based on imaging data is challenging due to the high dimensionality of the data, noisy measurements, complex correlation structures among voxels, small sample sizes, and ...


1 2 3 4 5 6 7 8 9 10 > 