Search results for "Cluster Analysis"

showing 10 items of 848 documents

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 reappraisal of the Pleurotus eryngii complex – New species and taxonomic combinations based on the application of a polyphasic approach, and an ide…

2014

The Pleurotus eryngii species-complex comprises choice edible mushrooms growing on roots and lower stem residues of Apiaceae (umbellifers) plants. Material deriving from extensive sampling was studied by mating compatibility, morphological and ecological criteria, and through analysis of ITS1-5.8S-ITS2 and IGS1 rRNA sequences. Results revealed that P. eryngii sensu stricto forms a diverse and widely distributed aggregate composed of varieties elaeoselini, eryngii, ferulae, thapsiae, and tingitanus. Pleurotus eryngii subsp. tuoliensis comb. nov. is a phylogenetically sister group to the former growing only on various Ferula species in Asia. The existence of Pleurotus nebrodensis outside of S…

Co-evolution of plants and fungi Fungal phylogeny Pleurotus eryngii subsp. tuoliensis comb. nov. Pleurotus ferulaginis sp. nov. Pleurotus nebrodensis subsp. fossulatus comb. nov.Molecular Sequence DataIdentification keyPleurotusDNA Ribosomal SpacerBotanyGeneticsCluster AnalysisPleurotus eryngiiDNA FungalEcology Evolution Behavior and SystematicsRecombination GeneticMicroscopyPleurotusApiaceaePhylogenetic treebiologySettore BIO/02 - Botanica SistematicaBiodiversitySequence Analysis DNAbiology.organism_classificationRNA Ribosomal 5.8SPhylogeographyInfectious DiseasesTaxonSister groupSettore BIO/03 - Botanica Ambientale E ApplicataKey (lock)ApiaceaeFungal Biology
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Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome…

2014

Background The scale and complexity of genomic data lend themselves to analysis using sophisticated mathematical techniques to yield information that can generate new hypotheses and so guide further experimental investigations. An ensemble clustering method has the ability to perform consensus clustering over the same set of genes from different microarray datasets by combining results from different clustering methods into a single consensus result. Results In this paper we have performed comprehensive analysis of forty yeast microarray datasets. One recently described Bi-CoPaM method can analyse expressions of the same set of genes from various microarray datasets while using different cl…

Co-regulation(Binarisation of consensus partition matrices) Bi-CoPaMGene Expression ProfilingStress responseGenes FungalCo-expressionGenome-wide analysisGene Expression Regulation FungalRibosome biogenesisSaccharomycetalesCluster AnalysisGene Regulatory NetworksBudding yeastRibosomesOligonucleotide Array Sequence AnalysisResearch ArticleBMC bioinformatics
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Comparative genomics and protein domain graph analyses link ubiquitination and RNA metabolism.

2006

The human gene parkin, known to cause familial Parkinson disease, as well as several other genes, likely involved in other neurodegenerative diseases or in cancer, encode proteins of the RBR family of ubiquitin ligases. Here, we describe the structural diversity of the RBR family in order to infer their functional roles. Of particular interest is a relationship detected between RBR-mediated ubiquitination and RNA metabolism: a few RBR proteins contain RNA binding domains and DEAH-box RNA helicase domains. Global protein domain graph analyses demonstrate that this connection is not RBR-specific, but instead many other proteins contain both ubiquitination and RNA-related domains. These protei…

Comparative genomicsGeneticsbiologyProtein ConformationUbiquitinUbiquitin-Protein LigasesProtein domainMolecular Sequence DataRNAGenomicsF-box proteinRNA Helicase AParkinUbiquitin ligaseProtein Structure TertiaryStructural Biologybiology.proteinAnimalsCluster AnalysisHumansRNAMolecular BiologyGeneAlgorithmsJournal of molecular biology
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On the determination of coherent solar climates over a tropical island with a complex topography

2020

Abstract Many tropical islands aim at developing a greener self-sufficient energy production systems based on renewable energy, notably solar-generated electricity. This work explores the mean diurnal and annual solar cycles over La Reunion island (southwest Indian Ocean: 21°S, 55.5°E), and their spatial behavior, using the Solar surfAce RAdiation Heliosat – East (SARAH-E) satellite-derived data at high spatial ( 0.05 ° × 0.05 ° ) and time (hourly) resolutions over period 1999–2016. Comparisons of the SARAH-E data with ground-based measurements over the period 2011–2015 show differences of ~ 15 % for diurnal-seasonal variations. The solar resource over the island displays strong spatial var…

Complex topography020209 energyLa Réunion island02 engineering and technologyAtmospheric sciencesSurface solar radiationCluster analysisSolar Resource0202 electrical engineering electronic engineering information engineeringGeneral Materials Science14. Life underwatergeographygeography.geographical_feature_categoryRenewable Energy Sustainability and the Environmentbusiness.industryComplex meteorological context021001 nanoscience & nanotechnologyRenewable energyIndian oceanTropical islandsVolcano[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology13. Climate actionPeriod (geology)Seasonal/diurnal cyclesEnvironmental scienceSpatial variability0210 nano-technologybusinessSARAH-ESolar Energy
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Continuous reformulations and heuristics for the Euclidean travelling salesperson problem

2008

We consider continuous reformulations of the Euclidean travelling salesperson problem (TSP), based on certain clustering problem formulations. These reformulations allow us to apply a generalisation with perturbations of the Weiszfeld algorithm in an attempt to find local approximate solutions to the Euclidean TSP.

Computational MathematicsMathematical optimizationControl and OptimizationControl and Systems EngineeringProblem FormulationsEuclidean geometryApplied mathematicsComputer Science::Data Structures and AlgorithmsHeuristicsCluster analysisMathematicsESAIM: Control, Optimisation and Calculus of Variations
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Domain-Knowledge Optimized Simulated Annealing for Network-on-Chip Application Mapping

2013

Network-on-Chip architectures are scalable on-chip interconnection networks. They replace the inefficient shared buses and are suitable for multicore and manycore systems. This paper presents an Optimized Simulated Annealing (OSA) algorithm for the Network-on-Chip application mapping problem. With OSA, the cores are implicitly and dynamically clustered using knowledge about communication demands. We show that OSA is a more feasible Simulated Annealing approach to NoC application mapping by comparing it with a general Simulated Annealing algorithm and a Branch and Bound algorithm, too. Using real applications we show that OSA is significantly faster than a general Simulated Annealing, withou…

Computer Science::Hardware ArchitectureInterconnectionMulti-core processorNetwork on a chipBranch and boundComputer scienceScalabilitySimulated annealingComputer Science::Networking and Internet ArchitectureParallel computingAdaptive simulated annealingCluster analysis
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Combining Supervised and Unsupervised Learning to Discover Emotional Classes

2017

Most previous work in emotion recognition has fixed the available classes in advance, and attempted to classify samples into one of these classes using a supervised learning approach. In this paper, we present preliminary work on combining supervised and unsupervised learning to discover potential latent classes which were not initially considered. To illustrate the potential of this hybrid approach, we have used a Self-Organizing Map (SOM) to organize a large number of Electroencephalogram (EEG) signals from subjects watching videos, according to their internal structure. Results suggest that a more useful labelling scheme could be produced by analysing the resulting topology in relation t…

Computer science050109 social psychologyuser modelling02 engineering and technologyMachine learningcomputer.software_genrePersonalization0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesEmotion recognitionEEGValence (psychology)Affective computingaffective computingclass discoverybusiness.industry05 social sciencesSupervised learningPattern recognitionHybrid approachComputingMethodologies_PATTERNRECOGNITIONUnsupervised learning020201 artificial intelligence & image processingArtificial intelligencebusinesscomputercluster analysis
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Combining conjunctive rule extraction with diffusion maps for network intrusion detection

2013

Network security and intrusion detection are important in the modern world where communication happens via information networks. Traditional signature-based intrusion detection methods cannot find previously unknown attacks. On the other hand, algorithms used for anomaly detection often have black box qualities that are difficult to understand for people who are not algorithm experts. Rule extraction methods create interpretable rule sets that act as classifiers. They have mostly been combined with already labeled data sets. This paper aims to combine unsupervised anomaly detection with rule extraction techniques to create an online anomaly detection framework. Unsupervised anomaly detectio…

Computer scienceAnomaly-based intrusion detection systemNetwork securityintrusion detectiontunkeutumisen havaitseminenFeature extractionDiffusion mapdiffusion mapIntrusion detection systemMachine learningcomputer.software_genrepoikkeavuuden havaitseminenBlack boxtiedon louhintan-grammiCluster analysista113Training setrule extractionbusiness.industryn-gramanomaly detectiondiffuusiokarttakoneoppiminensääntöjen erottaminenAnomaly detectionArtificial intelligenceData miningtiedonlouhintabusinesscomputer2013 IEEE Symposium on Computers and Communications (ISCC)
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Automated prostate gland segmentation based on an unsupervised fuzzy C-means clustering technique using multispectral T1w and T2w MR imaging

2017

Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection and delineation of prostate gland on multispectral MRI data is currently a time-expensive and operator-dependent procedure. Efficient computer-assisted segmentation approaches are not yet able to address these issues, but rather have the potential to do so. In this paper, a novel automatic prostate MR image segmentation method based on the Fuzzy C-Means (FCM) clustering algorithm, which enables multispectral T1-weighted (T1w) and T2-weighted (T…

Computer scienceAutomated segmentation; Fuzzy C-Means clustering; Multispectral MR imaging; Prostate cancer; Prostate gland; Unsupervised machine learningMultispectral image02 engineering and technologyautomated segmentation; multispectral MR imaging; prostate gland; prostate cancer; unsupervised Machine Learning; Fuzzy C-Means clustering030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicineProstate0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentationautomated segmentationunsupervised Machine LearningCluster analysisSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimedicine.diagnostic_testbusiness.industryINF/01 - INFORMATICAMagnetic resonance imagingmedicine.diseaseprostate cancerFuzzy C-Means clusteringmultispectral MR imagingmedicine.anatomical_structureUnsupervised learning020201 artificial intelligence & image processingArtificial intelligencebusinessprostate glandInformation SystemsMultispectral segmentation
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