Search results for "Clusterin"

showing 10 items of 478 documents

Bayesian versus data driven model selection for microarray data

2014

Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is a particular instance of the model selection problem, i.e., the identification of the correct number of clusters in a dataset. In what follows, for ease of reference, we refer to that instance still as model selection. It is an important part of any statistical analysis. The techniques used for solving it are mainly either Bayesian or data-driven, and are both based on internal knowledge. That is, they use information obtained by processing the input data. A…

Clustering Model selection Bayesian information criterion Akaike information criterion Minimum message length BioinformaticsSettore INF/01 - InformaticaComputer sciencebusiness.industryModel selectionBayesian probabilitycomputer.software_genreMachine learningComputer Science ApplicationsData-drivenDetermining the number of clusters in a data setIdentification (information)Bayesian information criterionData miningArtificial intelligenceAkaike information criterionCluster analysisbusinesscomputer
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Project Management Information Systems (PMISs): A Statistical-Based Analysis for the Evaluation of Software Packages Features

2021

Project Managers (PMs) working in competitive markets are finding Project Management Information Systems (PMISs) useful for planning, organizing and controlling projects of varying complexity. A wide variety of PMIS software is available, suitable for projects differing in scope and user needs. This paper identifies the most useful features found in PMISs. An extensive literature review and analysis of commercial software is made to identify the main features of PMISs. Afterwards, the list is reduced by a panel of project management experts, and a statistical analysis is performed on data acquired by means of two different surveys. The relative importance of listed features is properly comp…

Clustering; Conjoint analysis; Design of Experiment (DoE); Project Management Information System (PMIS); Ranking method; Surveyranking methodTechnologyComputer scienceQH301-705.5QC1-999SoftwareSettore ING-IND/17 - Impianti Industriali MeccaniciGeneral Materials SciencesurveyProject managementBiology (General)Cluster analysisInstrumentationQD1-999Fluid Flow and Transfer ProcessesCommercial softwareScope (project management)business.industryProcess Chemistry and TechnologyTPhysicsGeneral EngineeringProject Management Information System (PMIS); survey; Design of Experiment (DoE); conjoint analysis; ranking method; clusteringClustering Conjoint analysis Design of Experiment (DoE) Project Management Information System (PMIS) Ranking method SurveyProject Management Information System (PMIS)Engineering (General). Civil engineering (General)Data scienceDesign of Experiment (DoE)Computer Science ApplicationsConjoint analysisVariety (cybernetics)ChemistryRespondentconjoint analysisTA1-2040businessclusteringApplied Sciences; Volume 11; Issue 23; Pages: 11233
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A Greedy Algorithm for Hierarchical Complete Linkage Clustering

2014

We are interested in the greedy method to compute an hierarchical complete linkage clustering. There are two known methods for this problem, one having a running time of \({\mathcal O}(n^3)\) with a space requirement of \({\mathcal O}(n)\) and one having a running time of \({\mathcal O}(n^2 \log n)\) with a space requirement of Θ(n 2), where n is the number of points to be clustered. Both methods are not capable to handle large point sets. In this paper, we give an algorithm with a space requirement of \({\mathcal O}(n)\) which is able to cluster one million points in a day on current commodity hardware.

CombinatoricsCURE data clustering algorithmSUBCLUNearest-neighbor chain algorithmCorrelation clusteringSingle-linkage clusteringHierarchical clustering of networksGreedy algorithmComplete-linkage clusteringMathematics
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Balanced Words Having Simple Burrows-Wheeler Transform

2009

The investigation of the "clustering effect" of the Burrows-Wheeler transform (BWT) leads to study the words having simple BWT , i.e. words w over an ordered alphabet $A=\{a_1,a_2,\ldots,a_k\}$, with $a_1 < a_2 < \ldots <a_k$, such that $bwt(w)$ is of the form $a_k^{n_k} a_{k-1}^{n_{k-1}} \cdots a_1^{n_1}$, for some non-negative integers $n_1, n_2, \ldots, n_k$. We remark that, in the case of binary alphabets, there is an equivalence between words having simple BWT, the family of (circular) balanced words and the conjugates of standard words. In the case of alphabets of size greater than two, there is no more equivalence between these notions. As a main result of this paper we prove that, u…

CombinatoricsConjugacy classClustering effectBurrows–Wheeler transformSettore INF/01 - InformaticaBurrows Wheeler Transform Combinatorics on Words Balanced sequences epistandard rich words words having simple BWTBinary numberBurrows-Wheeler TransformAlphabetBinary alphabetBurrows-Wheeler Transform; Clustering effectMathematics
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Internacionalización de empresas a través de clústeres: análisis bibliométrico de palabras clave de 152 publicaciones destacadas en el período 2009-2…

2022

[EN] While countless studies on the role of clusters in regional economic developments and business performance have been done, some disadvantages and limitations also have been identified. Limitations such as small local markets, limited resources, isolation, and over-independence which lead companies to a lock-in state regarding knowledge and innovation can be solved by means of internationalization or foreign market expansion. Therefore, the internationalization of clusters still needs more attention. Furthermore, by conducting a bibliometric study based on the keywords from previous research, this investigation intends to identify the principal and most influential items, their relation…

Commercemapeo bibliométricoF06UNESCO::CIENCIAS ECONÓMICASSciMATR01HF1-6182internacionalizaciónanálisis de palabras clavebibliometric mappingSJRkeyword analysisinternationalizationclustering
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V11. Functional hierarchy within an overall network for visual motion processing and ocular-motor control at rest

2015

Introduction Visual motion processing on one hand and ocular motor functions on the other are rarely studied together in vivo in humans. The interrelation of these functional networks is rather unclear, even though their functional dependence seems obvious. In several fMRI studies the essential nodes of both networks could be localized using voluntary optokinetic ('look') nystagmus (OKN) in the horizontal plane incorporating visual motion tracking (Dieterich et al., 2009). Here, functional connectivity (FC) between these nodes representing both networks was studies using resting-state FC. Methods Resting-state fMRI data of 200 healthy adults (age 44.1±17.9; 79 male) were included in the cro…

Communicationbusiness.industrySuperior colliculusPattern recognitionNystagmusOptokinetic reflexHorizontal planecomputer.software_genreSensory SystemsHierarchical clusteringWhite mattermedicine.anatomical_structureNeurologyVoxelPhysiology (medical)medicineNeurology (clinical)Artificial intelligencemedicine.symptomPsychologybusinesscomputerPartial correlationClinical Neurophysiology
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Algorithms for Graph and Network Analysis: Clustering and Search of Motifs in Graphs

2019

In this article we deal with problems that involve the analysis of topology in graphs modeling biological networks. In particular, we consider two important problems: (i) Network clustering, aiming at finding compact subgraphs inside the input graph in order to isolate molecular complexes, and (ii) searching for motifs, i.e., sub-structures repeated in the input network and presenting high significance (e.g., in terms of their frequency). We provide a compact overview of the main techniques proposed in the literature to solve these problems.

Community detection Network clustering Network motifs Network topology
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Compaction of Open-Graded HMAs Evaluated by a Fuzzy Clustering Technique

2015

The aim of this paper is the proposal of an expeditious procedure to be used during the execution of an asphalt layer for improving the compaction task. This procedure, based on a fuzzy clustering technique, starts from the knowledge of some information recorded by ordinary measuring instruments and provides an aid to the decision-maker on the number of roller passes needed to achieve a specific density at a certain temperature. This result can be deduced with great rapidity during the paving operations on site without waiting for the time spent in the core extraction and in the subsequent laboratory analysis. In this way it is possible to identify more precisely which aspects of the execut…

Compaction Density Fuzzy C-means Hot mix asphaltFuzzy clusteringComputer scienceCompactionCompactionDensitycomputer.software_genreHot mix asphaltSpecific densityTask (project management)Asphalt pavementMeasuring instrumentSettore ICAR/04 - Strade Ferrovie Ed AeroportiData miningLayer (object-oriented design)Fuzzy C-meanscomputer
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Complex Networked Systems: Convergence Analysis, Dynamic Behaviour, and Security.

Complex networked systems are a modern reference framework through which very dierent systems from far disciplines, such as biology, computer science, physics, social science, and engineering, can be described. They arise in the great majority of modern technological applications. Examples of real complex networked systems include embedded systems, biological networks, large-scale systems such as power generation grids, transportation networks, water distribution systems, and social network. In the recent years, scientists and engineers have developed a variety of techniques, approaches, and models to better understand and predict the behaviour of these systems, even though several research…

Complex Network Data clustering Hegselmann-Krause model Consensus Security Attacks Line Network k-means Opinion Dynamics.Settore ING-INF/04 - Automatica
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Cluster-based RF fingerprint positioning using LTE and WLAN signal strengths

2017

Wireless Local Area Network (WLAN) positioning has become a popular localization system due to its low-cost installation and widespread availability of WLAN access points. Traditional grid-based radio frequency (RF) fingerprinting (GRFF) suffers from two drawbacks. First it requires costly and non-efficient data collection and updating procedure; secondly the method goes through time-consuming data pre-processing before it outputs user position. This paper proposes Cluster-based RF Fingerprinting (CRFF) to overcome these limitations by using modified Minimization of Drive Tests data which can be autonomously collected by cellular operators from their subscribers. The effect of environmental…

Computer Networks and CommunicationsComputer scienceReal-time computingK-means clustering02 engineering and technologySignallaw.inventionK-nearest neighbors0203 mechanical engineeringlaw0202 electrical engineering electronic engineering information engineeringfuzzy C-means clusteringWi-FiElectrical and Electronic EngineeringData collectionbusiness.industryFingerprint (computing)k-means clusteringRF fingerprint positioning020206 networking & telecommunications020302 automobile design & engineeringGridHardware and ArchitectureEmbedded systemMinificationRadio frequencybusinesshierarchical clustering
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