Search results for "clusterin"

showing 10 items of 478 documents

A quantitative analysis of Educational Data through the Comparison between Hierarchical and Not-Hierarchical Clustering

2017

Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science Education. Moreover, in the field of Science Education, a comparison between two different Clustering methods is not discussed in the literature. Conceptions of students about modeling in physic are investigated by using an open-ended questionnaire. The questionnaire is analyzed through Clustering methods. The clustering results obtained by using the two methods are compared and show a good coherence bet…

Not-hierarchical cluster analysi3304Settore FIS/08 - Didattica E Storia Della Fisicacomputer.software_genre01 natural sciencesScience educationEducationSet (abstract data type)010104 statistics & probability0101 mathematicsCluster analysisEvaluationScience educationHierarchical cluster analysiPoint (typography)Applied Mathematics05 social sciencesModeling050301 educationCoherence (statistics)Settore MAT/04 - Matematiche Complementarivaluation hierarchical cluster analysis modeling not-hierarchical cluster analysis science educationField (geography)Hierarchical clusteringQuantitative analysis (finance)Data mining0503 educationcomputer
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Design of large scale sensors in 180 nm CMOS process modified for radiation tolerance

2019

International audience; The last couple of years have seen the development of Depleted Monolithic Active Pixel Sensors (DMAPS) fabricated with a process modification to increase the radiation tolerance. Two large scale prototypes, Monopix with a column drain synchronous readout, and MALTA with a novel asynchronous architecture, have been fully tested and characterized both in the laboratory and in test beams. This showed that certain aspects have to be improved such as charge collection after irradiation and the output data rate. Some improvements resulting from extensive TCAD simulations were verified on a small test chip, Mini-MALTA. A detailed cluster analysis, using data from laboratory…

Nuclear and High Energy PhysicsOn-chip clusteringPhysics::Instrumentation and Detectors01 natural sciencesCMOS sensors ; Tracking detectors ; Monolithic sensors ; MAPS ; On-chip clustering030218 nuclear medicine & medical imaging03 medical and health sciencesTracking detectors0302 clinical medicinesemiconductor detector: pixelRadiation toleranceCMOS sensors0103 physical sciencesMAPSElectronic engineeringIrradiation[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]numerical calculationsInstrumentationradiation: damagePhysicsPixelirradiation010308 nuclear & particles physicstracking detector: upgradecharge: yieldBandwidth (signal processing)ATLASDigital architectureChipUpgradeAsynchronous communicationMonolithic sensors
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Measurement of the mass of the W boson using direct reconstruction at √s = 183 GeV

1999

From data corresponding to an integrated luminosity of 53.5 pb(-1) taken during the 183 GeV run in 1997, DELPHI has measured the W mass from direct reconstruction of WW --> lq (q) over bar and WW --> q (q) over bar q (q) over bar events. Combining these channels, a value of m(w) = 80.238 +/- 0.154(stat) +/- 0.035(syst) +/- 0.035(fsi) +/- 0.021 (LEP) GeV/c(2) is obtained, where fsi denotes final state interaction. Combined with the W mass obtained by DELPHI from the WW production cross-section and with the direct measurement at 172 GeV this leads to a measured value of m(w) = 80.270 +/- 0.137(stat) +/- 0.031(syst) +/- 0.030(fsi) +/- 0.021(LEP)GeV/c(2), in good agreement with the Standard Mod…

Nuclear and High Energy PhysicsParticle physicsEINSTEIN CORRELATIONSCLUSTERING-ALGORITHMElectron–positron annihilationMathematicsofComputing_GENERALCOLOR DIPOLE MODEL01 natural sciencesComputer Science::Digital LibrariesPartícules (Física nuclear)LuminosityStandard ModelPHYSICSEVENTSNuclear physicsLEP20103 physical sciencesMONTE-CARLO PROGRAM[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]ANNIHILATION010306 general physicsDELPHIPhysicsAnnihilation010308 nuclear & particles physicsE(+)E(-) INTERACTIONSTheoryofComputation_GENERALLARGE ELECTRON POSITRON COLLIDERMONTE-CARLO PROGRAM; PAIR CROSS-SECTION; COLOR DIPOLE MODEL; E(+)E(-) INTERACTIONS; EINSTEIN CORRELATIONS; CLUSTERING-ALGORITHM; ANNIHILATION; PHYSICS; EVENTS; LEP2PARTICLE PHYSICS; LARGE ELECTRON POSITRON COLLIDER; DELPHIComputer Science::Mathematical SoftwarePARTICLE PHYSICSProduction (computer science)Física nuclearPAIR CROSS-SECTIONParticle Physics - ExperimentBar (unit)
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Re-Clustering tool using an Open-Reference method that improves OTU definition

2019

International audience; 1.Environmental microbial communities are now widely studied using metabarcoding approaches, thanks to the democratization of high‐throughput DNA sequencing technologies. The massive number of reads produced with these technologies requires bioinformatic solutions to be treated. A key step in the analysis is to cluster reads into Operational Taxonomic Units (or OTUs) and thus reduce the amount of data for downstream analyses. Due to the important impact of the clustering method on the quantity and quality of OTUs, finding an equilibrium between the reliability and time‐consuming nature of the chosen strategy is a real challenge. The present article proposes a new pos…

OTU definition[SDV.SA]Life Sciences [q-bio]/Agricultural sciences[SPI]Engineering Sciences [physics]post‐clusteringsoil microbial communitiesmetabarcoding approaches[SHS] Humanities and Social SciencesOTU reliability and stabilityReClustORComputingMilieux_MISCELLANEOUS[SHS]Humanities and Social Sciencesclustering
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Combined Elephant Herding Optimization Algorithm with K-means for Data Clustering

2018

Clustering is an important task in machine learning and data mining. Due to various applications that use clustering, numerous clustering methods were proposed. One well-known, simple, and widely used clustering algorithm is k-means. The main problem of this algorithm is its tendency of getting trapped into local minimum because it does not have any kind of global search. Clustering is a hard optimization problem, and swarm intelligence stochastic optimization algorithms are proved to be successful for such tasks. In this paper, we propose recent swarm intelligence elephant herding optimization algorithm for data clustering. Local search of the elephant herding optimization algorithm was im…

Optimization problemComputer sciencebusiness.industryk-means clustering020206 networking & telecommunications02 engineering and technologycomputer.software_genreSwarm intelligence0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingStochastic optimizationLocal search (optimization)Data miningHerdingbusinessCluster analysiscomputerMetaheuristic
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Clustering local tourism systems by threshold acceptance

2015

Despite the importance of tourism as a leading industry in the development of a country’s economy, there is a lack of criteria and methodologies for the detection, promotion and governance of local tourism systems. We propose a quantitative approach for the detection of local tourism systems that are optimal with respect to geographical, economic, and demographical criteria. To this end, we formulate the issue as an optimization problem, and we solve it by means of Threshold Acceptance, a meta-heuristic algorithm which does not require us to predefine the number of clusters and also does not require all geographic areas to belong to a cluster.

Optimization problemSettore INF/01 - InformaticaComputer scienceCorporate governancemedia_common.quotation_subjectRural tourismEnvironmental economicsPromotion (rank)Clustering Threshold Accepting Tourist Local SystemsSettore MAT/09 - Ricerca OperativaCluster analysisTourismmedia_commonTourist flow
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A hybrid algorithm for planning public charging stations

2014

International audience; Green mobility solutions are receiving currently an enormous attention. Indeed, during last years, electric vehicles, being part of the field of the smart-grid, entered the automobile market of the whole world. This technology requires an effective deployment of charging stations of electric refill since the main problem in this system remains over the duration of refill of the batteries. In this work, we propose an optimized algorithm to locate electric charging stations. The main task of the algorithm is to find the best site of charging stations locations so as to minimize loss on the way to the charging station, as well as minimize investment cost, we take into a…

OptimizationClustering algorithmsComputer science[SPI] Engineering Sciences [physics]Real-time computinggenetic optimizationSmart-Gridk-means clustringGenetic algorithmsHybrid algorithmCharging stationCharging stations[SPI]Engineering Sciences [physics]Smart gridMathematical modelWork (electrical)Software deploymentHardware_GENERALGenetic algorithmGeneticsDuration (project management)InvestmentCluster analysisSimulationelectric vehicles
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Multi-party metering: An architecture for privacy-preserving profiling schemes

2013

Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing …

OptimizationInformation privacyEngineeringtatistical analysiSmart meterDistributed computingpattern clusteringC.2 COMPUTER-COMMUNICATION NETWORKSSmart gridelectricity supply industryComputer securitycomputer.software_genreCOMPUTER-COMMUNICATION NETWORKSElectricityClustering algorithmProfiling (information science)Metering modemart meterIndexeArchitectureCluster analysisgas industrydata privacybusiness.industrySettore ING-INF/03 - TelecomunicazioniComplexity theoryreal gas consumption dataVectorsA sharehigh-frequency metering datamultiparty meteringInformation sensitivityynthetic electricity consumption dataCryptographyprivacy-preserving profiling schemeprivacy-preserving analysibusinesscomputeruser profiling clustering mechanismMulti-Party Metering
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Correlation, hierarchies, and networks in financial markets

2010

We discuss some methods to quantitatively investigate the properties of correlation matrices. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Specifically, we discuss how to define and obtain hierarchical trees, correlation based trees and networks from a correlation matrix. The hierarchical clustering and other procedures performed on the correlation matrix to detect statistically reliable aspects of the correlation matrix are seen as filtering procedures of the correlation matrix. We also discuss a method to associate a hierarchically nested factor model to a hierarchical tre…

Organizational Behavior and Human Resource ManagementEconomics and EconometricsPhysics - Physics and SocietyCorrelation based networkKullback–Leibler divergenceStability (learning theory)FOS: Physical sciencesKullback–Leibler distancePhysics and Society (physics.soc-ph)computer.software_genreHierarchical clusteringFOS: Economics and businessCorrelationMultivariate analysis Hierarchical clustering Correlation based networks Bootstrap validation Factor models Kullback–Leibler distancePortfolio Management (q-fin.PM)Bootstrap validationQuantitative Finance - Portfolio ManagementMathematicsFactor analysisStatistical Finance (q-fin.ST)Covariance matrixMultivariate analysiQuantitative Finance - Statistical FinanceHierarchical clusteringFactor modelTree (data structure)Physics - Data Analysis Statistics and ProbabilityData miningPortfolio optimizationcomputerData Analysis Statistics and Probability (physics.data-an)
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Analyzing and organizing the sonic space of vocal imitations

2015

The sonic space that can be spanned with the voice is vast and complex and, therefore, it is difficult to organize and explore. In order to devise tools that facilitate sound design by vocal sketching we attempt at organizing a database of short excerpts of vocal imitations. By clustering the sound samples on a space whose dimensionality has been reduced to the two principal components, it is experimentally checked how meaningful the resulting clusters are for humans. Eventually, a representative of each cluster, chosen to be close to its centroid, may serve as a landmark in the exploration of the sound space, and vocal imitations may serve as proxies for synthetic sounds.

PCALandmarkSettore INF/01 - InformaticaComputer scienceSound designSpeech recognitionCentroidSpace (commercial competition)ClusteringLandmarkPrincipal component analysisVocal imitationsCluster analysisCurse of dimensionality
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