Search results for "physics.data-an"

showing 10 items of 69 documents

Community characterization of heterogeneous complex systems

2011

We introduce an analytical statistical method to characterize the communities detected in heterogeneous complex systems. By posing a suitable null hypothesis, our method makes use of the hypergeometric distribution to assess the probability that a given property is over-expressed in the elements of a community with respect to all the elements of the investigated set. We apply our method to two specific complex networks, namely a network of world movies and a network of physics preprints. The characterization of the elements and of the communities is done in terms of languages and countries for the movie network and of journals and subject categories for papers. We find that our method is ab…

FOS: Computer and information sciencesStatistics and Probabilityrandom graphs networks statistical inference socio-economic networksPhysics - Physics and SocietyTheoretical computer scienceProperty (programming)Complex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)socio-economic networksStatistical inferenceSocial and Information Networks (cs.SI)Random graphComputer Science - Social and Information NetworksStatistical and Nonlinear PhysicsProbability and statisticsComplex networkSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Hypergeometric distributionPhysics - Data Analysis Statistics and ProbabilitynetworkStatistics Probability and UncertaintyNull hypothesisData Analysis Statistics and Probability (physics.data-an)random graphstatistical inferenceJournal of Statistical Mechanics: Theory and Experiment
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Synergetic and redundant information flow detected by unnormalized Granger causality: application to resting state fMRI

2015

Objectives: We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. Methods: The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently we introduce a pairwise index of synergy which is zero when two in…

FOS: Computer and information sciencesgranger causality (GC)Multivariate statisticsComputer scienceRestComputer Science - Information TheoryBiomedical EngineeringsynergyFOS: Physical sciencescomputer.software_genre01 natural sciences03 medical and health sciences0302 clinical medicineGranger causality0103 physical sciencesConnectomeRedundancy (engineering)HumansBrain connectivityTime series010306 general physicsModels StatisticalHuman Connectome ProjectResting state fMRIredundancybusiness.industryInformation Theory (cs.IT)functional magnetic resonance imaging (fMRI)BrainPattern recognitionComplex networkMagnetic Resonance ImagingVariable (computer science)Physics - Data Analysis Statistics and ProbabilityQuantitative Biology - Neurons and CognitionFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPairwise comparisonNeurons and Cognition (q-bio.NC)Artificial intelligenceData miningNerve Netbusinesscomputer030217 neurology & neurosurgeryData Analysis Statistics and Probability (physics.data-an)
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Fast PET Scan Tumor Segmentation Using Superpixels, Principal Component Analysis and K-Means Clustering

2018

Positron Emission Tomography scan images are extensively used in radiotherapy planning, clinical diagnosis, assessment of growth and treatment of a tumor. These all rely on fidelity and speed of detection and delineation algorithm. Despite intensive research, segmentation remained a challenging problem due to the diverse image content, resolution, shape, and noise. This paper presents a fast positron emission tomography tumor segmentation method in which superpixels are extracted first from the input image. Principal component analysis is then applied on the superpixels and also on their average. Distance vector of each superpixel from the average is computed in principal components coordin…

FOS: Computer and information sciencespositron emission tomographyprincipal component analysisComputer scienceComputer Vision and Pattern Recognition (cs.CV)k-meansCoordinate systemComputer Science - Computer Vision and Pattern RecognitionFOS: Physical sciences02 engineering and technologyBenchmarkQuantitative Biology - Quantitative MethodsBiochemistry Genetics and Molecular Biology (miscellaneous)030218 nuclear medicine & medical imagingsuperpixels03 medical and health sciences0302 clinical medicineStructural Biology0202 electrical engineering electronic engineering information engineeringmedicineSegmentationComputer visionTissues and Organs (q-bio.TO)Cluster analysisQuantitative Methods (q-bio.QM)Pixelmedicine.diagnostic_testbusiness.industrysegmentationk-means clusteringQuantitative Biology - Tissues and OrgansPattern recognitionPhysics - Medical PhysicsPositron emission tomographyFOS: Biological sciencesPhysics - Data Analysis Statistics and ProbabilityPrincipal component analysis020201 artificial intelligence & image processingMedical Physics (physics.med-ph)Artificial intelligenceNoise (video)businessData Analysis Statistics and Probability (physics.data-an)BiotechnologyMethods and Protocols
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The limit order book on different time scales

2007

Financial markets can be described on several time scales. We use data from the limit order book of the London Stock Exchange (LSE) to compare how the fluctuation dominated microstructure crosses over to a more systematic global behavior.

FOS: Economics and businessPhysics - Physics and SocietyQuantitative Finance - Trading and Market MicrostructureStock exchangePhysics - Data Analysis Statistics and ProbabilityFinancial marketEconomicsEconometricsFOS: Physical sciencesPhysics and Society (physics.soc-ph)Data Analysis Statistics and Probability (physics.data-an)Trading and Market Microstructure (q-fin.TR)
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Multimodal and multicriteria analysis for VLSI expertises and defects localization

2017

The purpose of this manuscript is to exhibit the research work solving the issue of data processing stem from defect localization techniques. This step being decisive in the failure analysis process, scientists have to harness data coming from light emission and laser techniques. Nevertheless, this analysis process is sequential and only depends on the expert’s decision. This factor leads to a not quantified probability of localization. Consequently to solve these issues, a multimodal and multicriteria analysis has been developped, taking advantage of the heterogeneous andcomplementary nature of light emission and laser probing techniques. This kind of process is based on advanced level too…

Failure analysisdata fusionAnalyse de défaillancescircuits intégrés[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronicsanalyse multimodale et multicritèrestraitement du signal/imagesignal/image processingVLSI[STAT] Statistics [stat]multimodal and criteria analysisdefect localizationlocalisation de défauts[PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]fusion de données[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Horizontal visibility graphs: exact results for random time series

2009

The visibility algorithm has been recently introduced as a mapping between time series and complex networks. This procedure allows us to apply methods of complex network theory for characterizing time series. In this work we present the horizontal visibility algorithm, a geometrically simpler and analytically solvable version of our former algorithm, focusing on the mapping of random series (series of independent identically distributed random variables). After presenting some properties of the algorithm, we present exact results on the topological properties of graphs associated with random series, namely, the degree distribution, the clustering coefficient, and the mean path length. We sh…

Independent and identically distributed random variablesPhysics - Physics and SocietyFOS: Physical sciencesPhysics and Society (physics.soc-ph)01 natural sciences010305 fluids & plasmas0103 physical sciencesComputer GraphicsApplied mathematicsComputer Simulation010306 general physicsRandomnessCondensed Matter - Statistical MechanicsMathematicsModels StatisticalSeries (mathematics)Statistical Mechanics (cond-mat.stat-mech)Visibility graphDegree distributionNonlinear Sciences - Chaotic DynamicsPhysics - Data Analysis Statistics and ProbabilityProbability distributionNerve NetChaotic Dynamics (nlin.CD)Random variableAlgorithmsData Analysis Statistics and Probability (physics.data-an)Coupled map lattice
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Selectivity in Probabilistic Causality: Where Psychology Runs Into Quantum Physics

2011

Given a set of several inputs into a system (e.g., independent variables characterizing stimuli) and a set of several stochastically non-independent outputs (e.g., random variables describing different aspects of responses), how can one determine, for each of the outputs, which of the inputs it is influenced by? The problem has applications ranging from modeling pairwise comparisons to reconstructing mental processing architectures to conjoint testing. A necessary and sufficient condition for a given pattern of selective influences is provided by the Joint Distribution Criterion, according to which the problem of "what influences what" is equivalent to that of the existence of a joint distr…

Linear programming81P05 (Primary) 91E99 (Secondary)media_common.quotation_subjectFOS: Physical sciencesMathematics - Statistics TheoryQuantum entanglementStatistics Theory (math.ST)System of linear equations01 natural sciencesQuantitative Biology - Quantitative Methods050105 experimental psychologyCausality (physics)Joint probability distributionQuantum mechanics0103 physical sciencesFOS: Mathematics0501 psychology and cognitive sciences010306 general physicsSet (psychology)ta515General PsychologyQuantitative Methods (q-bio.QM)media_commonta113ta112Quantum PhysicsVariablesta114Applied Mathematicsta11105 social sciencesFOS: Biological sciencesPhysics - Data Analysis Statistics and ProbabilityQuantum Physics (quant-ph)Random variableData Analysis Statistics and Probability (physics.data-an)
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An improved method for measuring muon energy using the truncated mean of dE/dx

2012

Nuclear instruments & methods in physics research / A 703, 190 - 198 (2013). doi:10.1016/j.nima.2012.11.081

Nuclear and High Energy PhysicsParticle physicsPhysics::Instrumentation and DetectorsFOS: Physical sciencesddc:500.2Cherenkov; dE/dx; IceCube detector; Muon energy; Neutrino energy; Truncated mean53001 natural sciencesParticle detectorParticle identificationNuclear physicsdE/dx0103 physical sciencesSpecific energyddc:530CherenkovNeutrino energyInstrumentation and Methods for Astrophysics (astro-ph.IM)010303 astronomy & astrophysicsInstrumentationCherenkov radiationHigh Energy Astrophysical Phenomena (astro-ph.HE)PhysicsMuonTruncated meanMuon energy010308 nuclear & particles physicsDE/dxPhysics - Data Analysis Statistics and ProbabilityScintillation counterHigh Energy Physics::ExperimentNeutrinoIceCube detectorAstrophysics - High Energy Astrophysical PhenomenaAstrophysics - Instrumentation and Methods for AstrophysicsData Analysis Statistics and Probability (physics.data-an)Lepton
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Identification of photon-tagged jets in the ALICE experiment

2007

30 pp.-- PACS numbers: 25.75.Nq, 24.10.Lx, 25.75.-q, 29.40.Vj.-- Published in: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. Volume 585, Issues 1-2, 21 January 2008, Pages 28-39.-- Final full-text version of the paper available at: http://dx.doi.org/10.1016/j.nima.2007.10.050.

Nuclear and High Energy PhysicsParticle physicselectromagnetic calorimetersPhotonquark-gluon plasmaElectromagnetic calorimetersPhysics::Instrumentation and DetectorsAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesQuark-Gluon plasma01 natural sciencesNuclear physicsData Analysis Statistics and Probability0103 physical sciences[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Detectors and Experimental TechniquesNuclear Experiment010306 general physicsInstrumentation25.75.Nq - 24.10.Lx - 25.75.-q - 29.40.Vjcomputer.programming_languagePhysicsSpectrometer010308 nuclear & particles physicsHigh-energy gamma rays3. Good healthIdentification (information)Electromagnetic calorimeterPhysics - Data Analysis Statistics and ProbabilityHigh Energy Physics::ExperimentAlice (programming language)computer[PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]Data Analysis Statistics and Probability (physics.data-an)
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A New Three-Dimensional Track Fit with Multiple Scattering

2017

Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution…

Nuclear and High Energy PhysicsPhysics - Instrumentation and DetectorsFOS: Physical sciencesTracking (particle physics)01 natural sciencesHigh Energy Physics - Experimentlaw.inventionMomentumHigh Energy Physics - Experiment (hep-ex)OpticsLinearizationlaw0103 physical sciences010306 general physicsColliderInstrumentationAnsatzPhysicsSpectrometer010308 nuclear & particles physicsScatteringbusiness.industryDetectorInstrumentation and Detectors (physics.ins-det)Computational Physics (physics.comp-ph)Computational physicsPhysics - Data Analysis Statistics and ProbabilitybusinessPhysics - Computational PhysicsData Analysis Statistics and Probability (physics.data-an)
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