Search results for "Data analysis"

showing 10 items of 383 documents

Changes in the flow and quality of water in the dam reservoir of the Mała Panew catchment (South Poland) characterized by multidimensional data analys…

2023

Multidimensional exploratory techniques, such as the Principal Component Analysis (PCA), have been used to analyze long-term changes in the fl ow regime and quality of water of the lowland dam reservoir Turawa (south-west Poland) in the catchment of the Mała Panew river (a tributary of the Odra). The paper proves that during the period of 1998–2016 the Turawa reservoir was equalizing the river’s water fl ow. Moreover, various physicochemical water quality indicators were analyzed at three measurement points (at the tributary’s mouth into the reservoir, in the reservoir itself and at the outfl ow from the reservoir). The water quality assessment was performed by analyzing physicochemical ind…

Multidimensional analysisHydrologyPrincipal Component Analysis (PCA).geographygeography.geographical_feature_categoryWater flowFlow (psychology)Drainage basinGeneral Medicinewater reservoir; river; water fl ow; water quality; multidimensional data analysisStream flowEnvironmental scienceStatistical analysisWater qualityTotal suspended solidsArchives of Environmental Protection
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Empirical Orthogonal Function and Functional Data Analysis Procedures to Impute Long Gaps in Environmental Data

2016

Air pollution data sets are usually spatio-temporal multivariate data related to time series of different pollutants recorded by a monitoring network. To improve the estimate of functional data when missing values, and mainly long gaps, are present in the original data set, some procedures are here proposed considering jointly Functional Data Analysis and Empirical Orthogonal Function approaches. In order to compare and validate the proposed procedures, a simulation plan is carried out and some performance indicators are computed. The obtained results show that one of the proposed procedures works better than the others, providing a better reconstruction especially in presence of long gaps.

Multivariate statisticsComputer scienceFunctional data analysisEmpirical orthogonal functionsMissing datacomputer.software_genreEnvironmental dataEOF FDA Missing data Environmental dataSet (abstract data type)Singular value decompositionPerformance indicatorData miningSettore SECS-S/01 - Statisticacomputer
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Neutrino interaction classification with a convolutional neural network in the DUNE far detector

2020

The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2–5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino…

Neutrino Oscillations. Neutrino detectors.Physics - Instrumentation and DetectorsPhysics::Instrumentation and Detectorsfar detector01 natural sciencesPhysics Particles & FieldsHigh Energy Physics - Experimentcharged currentHigh Energy Physics - Experiment (hep-ex)[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Particle Physics ExperimentsMuon neutrinoneutrino/e: particle identificationNeutrino detectorsDetectors and Experimental Techniquesphysics.ins-detCharged currentneutrino: interactionInformáticaPhysicsTelecomunicacionesNeutrino oscillationsPhysicsNeutrino interactions neural network DUNE Deep Underground Neutrino ExperimentInstrumentation and Detectors (physics.ins-det)Experiment (hep-ex)Neutrino detectorPhysical SciencesCP violationNeutrinoParticle Physics - ExperimentParticle physicsdata analysis method530 Physicsneural networkAstrophysics::High Energy Astrophysical PhenomenaCONSERVATIONFOS: Physical sciencesAstronomy & AstrophysicsDeep Learningneutrino: deep underground detectorneutrino physics0103 physical sciencesNeutrino Oscillations. Neutrino detectorsObject DetectionNeutrinoCP: violationDeep Underground Neutrino ExperimentHigh Energy Physics[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]Neutrinos010306 general physicsNeutrino oscillationneutrino/mu: particle identificationIOUScience & TechnologyDUNENeutrino interactions010308 nuclear & particles physicshep-exHigh Energy Physics::PhenomenologyFísicaNeutrino InteractionDetector530 PhysiksensitivityefficiencyHigh Energy Physics::ExperimentElectron neutrino
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Analysis of data fusion techniques for multi-microphone audio event detection in adverse environments

2017

Acoustic event detection (AED) is currently a very active research area with multiple applications in the development of smart acoustic spaces. In this context, the advances brought by Internet of Things (IoT) platforms where multiple distributed microphones are available have also contributed to this interest. In such scenarios, the use of data fusion techniques merging information from several sensors becomes an important aspect in the design of multi-microphone AED systems. In this paper, we present a preliminary analysis of several data-fusion techniques aimed at improving the recognition accuracy of an AED system by taking advantage of the diversity provided by multiple microphones in …

Noise measurementEvent (computing)MicrophoneComputer scienceReal-time computingFeature extractionContext (language use)02 engineering and technologycomputer.software_genreSensor fusion030507 speech-language pathology & audiology03 medical and health sciences0202 electrical engineering electronic engineering information engineeringData analysis020201 artificial intelligence & image processing0305 other medical sciencecomputerData integration2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)
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Singular hyperbolic systems

1999

We construct a class of vector fields on 3-manifolds containing the hyperbolic ones and the geometric Lorenz attractor. Conversely, we shall prove that nonhyperbolic systems in this class resemble the Lorenz attractor: they have Lorenz-like singularities accumulated by periodic orbits and they cannot be approximated by flows with nonhyperbolic critical elements.

Nonlinear Sciences::Chaotic DynamicsMathematics::Dynamical SystemsApplied MathematicsGeneral MathematicsMathematical analysisPhysics::Data Analysis; Statistics and ProbabilityHyperbolic systemsMathematicsProceedings of the American Mathematical Society
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FINITE ELEMENT APPROXIMATION OF NONLOCAL HEAT RADIATION PROBLEMS

1998

This paper focuses on finite element error analysis for problems involving both conductive and radiative heat transfers. The radiative heat exchange is modeled with a nonlinear and nonlocal term that also makes the problem non-monotone. The continuous problem has a maximum principle which suggests the use of inverse monotone discretizations. We also estimate the error due to the approximation of the boundary by showing continuous dependence on the geometric data for the continuous problem. The final result of this paper is a rigorous justification and error analysis for methods that use the so-called view factors for numerical modeling of the heat radiation.

Nonlinear systemMonotone polygonMaximum principleThermal radiationApplied MathematicsModeling and SimulationMathematical analysisInverseBoundary (topology)Finite element methodMathematicsGeometric data analysisMathematical Models and Methods in Applied Sciences
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Combining Inter-Subject Modeling with a Subject-Based Data Transformation to Improve Affect Recognition from EEG Signals

2019

Existing correlations between features extracted from Electroencephalography (EEG) signals and emotional aspects have motivated the development of a diversity of EEG-based affect detection methods. Both intra-subject and inter-subject approaches have been used in this context. Intra-subject approaches generally suffer from the small sample problem, and require the collection of exhaustive data for each new user before the detection system is usable. On the contrary, inter-subject models do not account for the personality and physiological influence of how the individual is feeling and expressing emotions. In this paper, we analyze both modeling approaches, using three public repositories. T…

Normalization (statistics)Data AnalysisSupport Vector MachineDatabases FactualComputer sciencemedia_common.quotation_subjectEmotionsData transformation (statistics)Context (language use)02 engineering and technologyvalence detectionElectroencephalographyAffect (psychology)Machine learningcomputer.software_genrelcsh:Chemical technologyBiochemistryModels BiologicalArticleAnalytical Chemistrydata transformation0202 electrical engineering electronic engineering information engineeringmedicinePersonalityHumanslcsh:TP1-1185EEGElectrical and Electronic EngineeringInstrumentationarousal detectionmedia_commonmedicine.diagnostic_testbusiness.industry020206 networking & telecommunicationsSubject (documents)ElectroencephalographySignal Processing Computer-AssistedAtomic and Molecular Physics and Opticsnormalization020201 artificial intelligence & image processingArtificial intelligencebusinessArousalcomputerSensors
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Global analysis of fragmentation functions for eta mesons

2011

Fragmentation functions for eta mesons are extracted at next-to-leading order accuracy of QCD in a global analysis of data taken in electron-positron annihilation and proton-proton scattering experiments. The obtained parametrization is in good agreement with all data sets analyzed and can be utilized, for instance, in future studies of double-spin asymmetries for single-inclusive eta production. The Lagrange multiplier technique is used to estimate the uncertainties of the fragmentation functions and to assess the role of the different data sets in constraining them.

Nuclear and High Energy PhysicsParticle physicsMesonCiencias FísicasElectron–positron annihilationHadronFOS: Physical sciencesElementary particle//purl.org/becyt/ford/1 [https]symbols.namesakeHigh Energy Physics - Phenomenology (hep-ph)Fragmentation FunctionsNuclear ExperimentQuantum chromodynamicsPhysicsAnnihilation//purl.org/becyt/ford/1.3 [https]QcdEtaAstronomíaHigh Energy Physics - PhenomenologyLagrange multiplierData analysissymbolsHigh Energy Physics::ExperimentCIENCIAS NATURALES Y EXACTASHadronization
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Hadronic Shower Development in Iron-Scintillator Tile Calorimetry

2000

The lateral and longitudinal profiles of hadronic showers detected by a prototype of the ATLAS Iron-Scintillator Tile Hadron Calorimeter have been investigated. This calorimeter uses a unique longitudinal configuration of scintillator tiles. Using a fine-grained pion beam scan at 100 GeV, a detailed picture of transverse shower behavior is obtained. The underlying radial energy densities for four depth segments and for the entire calorimeter have been reconstructed. A three-dimensional hadronic shower parametrization has been developed. The results presented here are useful for understanding the performance of iron-scintillator calorimeters, for developing fast simulations of hadronic showe…

Nuclear and High Energy PhysicsParticle physicsPhysics::Instrumentation and DetectorsAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesCalorimetryScintillatorCalorimetry01 natural sciencesParticle detectorPartícules (Física nuclear)High Energy Physics - ExperimentNuclear physicsHigh Energy Physics - Experiment (hep-ex)0103 physical sciencesComputer data analysis[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]Detectors and Experimental Techniques010306 general physicsNuclear ExperimentInstrumentationPhysics010308 nuclear & particles physicsPROFILESCalorimeterTransverse planevisual_artScintillation countervisual_art.visual_art_mediumMeasuring instrumentFísica nuclearHigh Energy Physics::ExperimentTile
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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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