Search results for "Data analysis."

showing 10 items of 377 documents

Optimal rates of convergence for persistence diagrams in Topological Data Analysis

2013

Computational topology has recently known an important development toward data analysis, giving birth to the field of topological data analysis. Topological persistence, or persistent homology, appears as a fundamental tool in this field. In this paper, we study topological persistence in general metric spaces, with a statistical approach. We show that the use of persistent homology can be naturally considered in general statistical frameworks and persistence diagrams can be used as statistics with interesting convergence properties. Some numerical experiments are performed in various contexts to illustrate our results.

Computational Geometry (cs.CG)FOS: Computer and information sciences[ MATH.MATH-GT ] Mathematics [math]/Geometric Topology [math.GT][STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]Topological Data analysis Persistent homology minimax convergence rates geometric complexes metric spacesGeometric Topology (math.GT)Mathematics - Statistics TheoryStatistics Theory (math.ST)[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG][STAT.TH]Statistics [stat]/Statistics Theory [stat.TH][INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG][ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH][ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG]Machine Learning (cs.LG)Computer Science - LearningMathematics - Geometric Topology[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG][INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][MATH.MATH-GT]Mathematics [math]/Geometric Topology [math.GT]FOS: Mathematics[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]Computer Science - Computational Geometry[MATH.MATH-GT] Mathematics [math]/Geometric Topology [math.GT]
researchProduct

pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

2019

AbstractBackgroundPrincipal component analysis (PCA) is frequently useentirely written ind in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene expression assays. Despite the availability of many software packages developed for this purpose, an interactive and comprehensive interface for performing these operations is lacking.ResultsWe developed the pcaExplorer software package to enhance commonly performed analysis steps with an interactive and user-friendly application, which provides state saving as well as the automated creation of reproducible reports. pcaExplorer is implemented in R using the Shiny fra…

Computer scienceInterface (computing)ShinyBioconductorPrincipal component analysis610 MedizinRNA-SeqGenomicslcsh:Computer applications to medicine. Medical informaticsReproducible researchBioconductorTranscriptomeExploratory data analysisUser-friendly610 Medical sciencesGene expressionHumansRNA-SeqGenelcsh:QH301-705.5Data CurationBase Sequencebusiness.industrySequence Analysis RNARRNAReproducibility of Resultslcsh:Biology (General)Principal component analysisRNAlcsh:R858-859.7Software engineeringbusinessSoftware
researchProduct

Development of a big data bank for PV monitoring data, analysis and simulation in COST Action 'PEARL PV'

2019

COST Action entitled PEARL PV aims at analyzing data of monitored PV systems installed all over Europe to quantitatively evaluate the long-term performance and reliability of these PV systems. For this purpose, a data bank is being implemented that can contain vast amounts of data, which will enable systematic performance analyses in combination with simulations. This paper presents the development process of this data bank.

Computer scienceProcess (engineering)business.industryReliability (computer networking)Performance05 social sciencesPhotovoltaic systemBig dataData analysis050301 educationReliability7. Clean energyReliability engineeringPV systemsPEARL (programming language)Monitoring data0502 economics and businessData bankCost actionbusiness0503 educationcomputer050203 business & managementData monitoringcomputer.programming_language
researchProduct

Mass Spectrometry in Food Quality and Safety

2015

Abstract In recent years, mass spectrometry has gained a wide recognition as a selective and fast technique for the analysis and assessment of a wide range of food products. The state of the art in the determination of safety and quality of food is presented to illustrate the capability of this technique for classification and grading, defect and disease detection, distribution and visualization of chemical attributes, and evaluations of overall quality of meat, fish, fruits, vegetables, and other food products. The features of mass spectrometry for each category were summarized in the aspects of the investigated quality and safety attributes, the used systems (triple quadrupole, quadrupole…

Computer sciencebusiness.industrymedia_common.quotation_subjectMass spectrometrycomputer.software_genreFood safetyOrbitrapTriple quadrupole mass spectrometerlaw.inventionChemometricslawData analysisQuality (business)Data miningFood qualitybusinesscomputermedia_common
researchProduct

Hidden attractors on one path : Glukhovsky-Dolzhansky, Lorenz, and Rabinovich systems

2017

In this report, by the numerical continuation method we visualize and connect hidden chaotic sets in the Glukhovsky-Dolzhansky, Lorenz and Rabinovich systems using a certain path in the parameter space of a Lorenz-like system.

Computer sciencechaosChaoticFOS: Physical sciencesPhysics::Data Analysis; Statistics and ProbabilityParameter space01 natural sciences010305 fluids & plasmasRabinovich systemLorenz system0103 physical sciencesAttractorGlukhovsky–Dolzhansky systemApplied mathematics010301 acousticsEngineering (miscellaneous)kaaosteoriaApplied Mathematicsta111Lorenz-like systemNonlinear Sciences - Chaotic DynamicsNonlinear Sciences::Chaotic DynamicsNumerical continuationModeling and SimulationPath (graph theory)numeerinen analyysiChaotic Dynamics (nlin.CD)hidden attractorInternational Journal of Bifurcation and Chaos
researchProduct

Deep-Learning-Enabled Fast Optical Identification and Characterization of Two-Dimensional Materials

2019

Advanced microscopy and/or spectroscopy tools play indispensable role in nanoscience and nanotechnology research, as it provides rich information about the growth mechanism, chemical compositions, crystallography, and other important physical and chemical properties. However, the interpretation of imaging data heavily relies on the "intuition" of experienced researchers. As a result, many of the deep graphical features obtained through these tools are often unused because of difficulties in processing the data and finding the correlations. Such challenges can be well addressed by deep learning. In this work, we use the optical characterization of two-dimensional (2D) materials as a case stu…

Condensed Matter - Materials SciencePhysics - Data Analysis Statistics and ProbabilityMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesApplied Physics (physics.app-ph)Physics - Applied PhysicsData Analysis Statistics and Probability (physics.data-an)
researchProduct

"Table 2" of "Measurement of the shape of the boson transverse momentum distribution in p anti-p ---> Z / gamma* ---> e+ e- + X events produced…

2008

Correlation matrix for all rapidity Z bosons for the 12 bins used for PT < 30.

Condensed Matter::Quantum GasesInclusiveZ ProductionElectron productionPBAR P --> E+ E- XCORRHigh Energy Physics::PhenomenologyPBAR P --> GAMMA* XAstrophysics::Cosmology and Extragalactic AstrophysicsPhysics::Data Analysis; Statistics and ProbabilityPBAR P --> Z0 X
researchProduct

An Overview of Collapsibility

2004

Collapsing over variables is a necessary procedure in much empirical research. Consequences are yet not always properly evaluated. In this paper, different definitions of collapsibility (simple, strict, strong, etc.) and corresponding necessary and sufficient conditions are reviewed and evaluated. We point out the relevance and limitations of the main contributions within a unifying interpretative framework. We deem such work to be useful since the debate on the topic has often developed in terms that are neither focused nor clear.

Contingency tableCategorical data analysisEmpirical researchPoint (typography)Work (electrical)Computer scienceRelevance (information retrieval)Mathematical economicsSimple (philosophy)
researchProduct

Role of conditional probability in multiscale stationary markovian processes.

2010

The aim of the paper is to understand how the inclusion of more and more time-scales into a stochastic stationary Markovian process affects its conditional probability. To this end, we consider two Gaussian processes: (i) a short-range correlated process with an infinite set of time-scales bounded from below, and (ii) a power-law correlated process with an infinite and unbounded set of time-scales. For these processes we investigate the equal position conditional probability P(x,t|x,0) and the mean First Passage Time T(L). The function P(x,t|x,0) can be considered as a proxy of the persistence, i.e. the fact that when a process reaches a position x then it spends some time around that posit…

Continuous-time stochastic processPure mathematicsStationary processStationary distributionStatistical Mechanics (cond-mat.stat-mech)Stochastic processStochastic ProcesseFokker-Plank EquationFOS: Physical sciencesOrnstein–Uhlenbeck processConditional probability distributionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)CombinatoricsStable processPhysics - Data Analysis Statistics and ProbabilityMarkovian processeFirst-hitting-time modelCondensed Matter - Statistical MechanicsData Analysis Statistics and Probability (physics.data-an)MathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
researchProduct

A PCA-based clustering algorithm for the identification of stratiform and convective precipitation at the event scale: an application to the sub-hour…

2021

AbstractUnderstanding the structure of precipitation and its separation into stratiform and convective components is still today one of the important and interesting challenges for the scientific community. Despite this interest and the advances made in this field, the classification of rainfall into convective and stratiform components is still today not trivial. This study applies a novel criterion based on a clustering approach to analyze a high temporal resolution precipitation dataset collected for the period 2002–2018 over the Sicily (Italy). Starting from the rainfall events obtained from this dataset, the developed methodology makes it possible to classify the rainfall events into f…

ConvectionEnvironmental Engineering010504 meteorology & atmospheric sciencesFunctional data analysis01 natural sciencesExtreme rainfall Convective and stratiform precipitation Functional data analysis PCA-based clustering analysis010104 statistics & probabilityIdentification (information)HyetographClimatologyTemporal resolutionEnvironmental ChemistryPrecipitation0101 mathematicsSafety Risk Reliability and QualityCluster analysisGeology0105 earth and related environmental sciencesGeneral Environmental ScienceWater Science and TechnologyConvective precipitation
researchProduct