Search results for "STATISTICS"

showing 10 items of 7671 documents

A Survey of the Reliability Methods Approach in Some Codes for Structural Design

1992

Structural codes are documents which are subject to periodic revision and amendment. The main reason of this is due to developments from theoretical and experimental research. The rules and codes for the design of civil engineering structures which are prepared or which are under preparation by different regional and international organizations are under review. Similarities and differences in the approaches to the reliability — oriented concept of calculated safety verifications on the design stages prescribed in the codes (available to author) are presented in this paper.

Computer scienceReliability methodsSubject (documents)Reliability (statistics)Experimental researchReliability engineering
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Modeling Snow Dynamics Using a Bayesian Network

2015

In this paper we propose a novel snow accumulation and melt model, formulated as a Dynamic Bayesian Network DBN. We encode uncertainty explicitly and train the DBN using Monte Carlo analysis, carried out with a deterministic hydrology model under a wide range of plausible parameter configurations. The trained DBN was tested against field observations of snow water equivalents SWE. The results indicate that our DBN can be used to reason about uncertainty, without doing resampling from the deterministic model. In all brevity, the DBN's ability to reproduce the mean of the observations was similar to what could be obtained with the deterministic hydrology model, but with a more realistic repre…

Computer scienceResamplingMonte Carlo methodRange (statistics)Bayesian networkComputer Science::Artificial IntelligenceSnowRepresentation (mathematics)AlgorithmField (computer science)Dynamic Bayesian networkSimulation
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Efficient anomaly detection on sampled data streams with contaminated phase I data

2020

International audience; Control chart algorithms aim to monitor a process over time. This process consists of two phases. Phase I, also called the learning phase, estimates the normal process parameters, then in Phase II, anomalies are detected. However, the learning phase itself can contain contaminated data such as outliers. If left undetected, they can jeopardize the accuracy of the whole chart by affecting the computed parameters, which leads to faulty classifications and defective data analysis results. This problem becomes more severe when the analysis is done on a sample of the data rather than the whole data. To avoid such a situation, Phase I quality must be guaranteed. The purpose…

Computer scienceSample (material)0211 other engineering and technologies02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]01 natural sciences[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing010104 statistics & probabilitysymbols.namesake[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]ChartControl chartEWMA chart0101 mathematics021103 operations researchData stream miningbusiness.industryPattern recognition[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]OutliersymbolsAnomaly detection[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Artificial intelligence[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessGibbs sampling
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Statistical Methods for the Geographical Analysis of Rare Diseases

2010

In this chapter we provide a summary of different methods for the detection of disease clusters. First of all, we give a summary of methods for computing estimates of the relative risk. These estimates provide smoothed values of the relative risks that can account for its spatial variation. Some methods for assessing spatial autocorrelation and general clustering are also discussed to test for significant spatial variation of the risk. In order to find the actual location of the clusters, scan methods are introduced. The spatial scan statistic is discussed as well as its extension by means of Generalised Linear Models that allows for the inclusion of covariates and cluster effects. In this …

Computer scienceScan statisticStatisticsCovariateLinear modelZero-inflated modelSpatial variabilityContext (language use)Cluster analysisSpatial analysis
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Comparative assessment of spatial perception in augmented reality depending on the consistency of depth cues

2021

Discrepancies between depth cues (accommodation and vergence) is one of the major issues caused in a stereoscopic augmented reality at close viewing distances. It adversely affects not only user comfort but also spatial judgements. Images with consonant cues at different distances have become available due to the implementation of multifocal architecture in the head-mounted displays, although its effect on spatial perception has remained unknown. In this psychophysical study, we investigated the effects of consonant and conflicting depth cues on perceptual distance matching in the stereoscopic environment of augmented reality using a head-mounted display that was driven in two modes: multif…

Computer scienceScienceQGeneral Engineeringvisual perceptiondistance matchingSpatial perceptiondepth cuesaugmented realityhead-mounted displayConsistency (statistics)multiple planes.Augmented realityDepth perceptionCognitive psychologyProceedings of the Estonian Academy of Sciences
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Different mechanisms underlie implicit visual statistical learning in honey bees and humans

2020

International audience; The ability of developing complex internal representations of the environment is considered a crucial antecedent to the emergence of humans’ higher cognitive functions. Yet it is an open question whether there is any fundamental difference in how humans and other good visual learner species naturally encode aspects of novel visual scenes. Using the same modified visual statistical learning paradigm and multielement stimuli, we investigated how human adults and honey bees ( Apis mellifera ) encode spontaneously, without dedicated training, various statistical properties of novel visual scenes. We found that, similarly to humans, honey bees automatically develop a comp…

Computer scienceSensory systemEnvironmentENCODEunsupervised learning03 medical and health sciences[SCCO]Cognitive science0302 clinical medicineCognitionMemoryAnimalsHumansLearninginternal representation030304 developmental biologyhuman visual cognition0303 health sciencesMultidisciplinaryRepresentation (systemics)Contrast (statistics)Cognition[SCCO] Cognitive scienceBeesBiological Sciencesinsect cognitionAntecedent (behavioral psychology)Unsupervised learningApis melliferaVisual learning030217 neurology & neurosurgeryCognitive psychology
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Daily streamlow prediction with uncertainty in ephemeral catchments using the GLUE methodology

2009

Abstract The Generalised Likelihood Uncertainty Estimation (GLUE) approach is presented here as a tool for estimating the predictive uncertainty of a rainfall–runoff model. The GLUE methodology allows to recognise the possible equifinality of different parameter sets and assesses the likelihood of a parameters set being acceptable simulator when model predictions are compared to observed field data. The results of the GLUE methodology depend greatly on the choice of the likelihood measure and on the choice of the threshold which determines if a parameters set is behavioural or not. Moreover the sampling size has a strong influence on the uncertainty assessment of the response of a rainfall–…

Computer scienceSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaEquifinalityVariance (accounting)Measure (mathematics)GeophysicsGeochemistry and PetrologySample size determinationStatisticsEconometricsSample varianceSensitivity analysisGLUEPredictive uncertainty Rainfall-Runoff model Generalized Likelehood Uncertainty Estimation Ephemeral catchmentsUncertainty analysis
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Atrial activity extraction for atrial fibrillation analysis using blind source separation.

2004

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA …

Computer scienceSpeech recognitionHeart VentriclesBiomedical EngineeringSignalBlind signal separationSensitivity and SpecificityElectrocardiographyRobustness (computer science)Heart Conduction SystemAtrial FibrillationmedicineHumansDiagnosis Computer-AssistedHeart AtriaPrincipal Component Analysismedicine.diagnostic_testBody Surface Potential MappingContrast (statistics)Reproducibility of ResultsAtrial fibrillationmedicine.diseaseIndependent component analysisKurtosisElectrocardiographyAlgorithmsIEEE transactions on bio-medical engineering
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A Musical Pattern Discovery System Founded on a Modeling of Listening Strategies

2004

Music is a domain of expression that conveys a paramount degree of complexity. The musical surface, composed of a multitude of notes, results from the elaboration of numerous structures of different types and sizes. The composer constructs this structural complexity in a more or less explicit way. The listener, faced by such a complex phenomenon, is able to reconstruct only a limited part of it, mostly in a non-explicit way. One particular aim of music analysis is to objectify such complexity, thus offering to the listener a tool for enriching the appreciation of music (Lartillot and SaintJames, 2004). The trouble is, traditional musical analysis, although offering a valuable understanding …

Computer scienceSpeech recognitionMusical050105 experimental psychology060404 music[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[STAT.ML]Statistics [stat]/Machine Learning [stat.ML][INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]Media Technology0501 psychology and cognitive sciencesSet (psychology)Musical formCognitive scienceStructure (mathematical logic)[INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL][SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts05 social sciences06 humanities and the artsData structureComputer Science ApplicationsExpression (architecture)Music theory[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]NA0604 artsMusicMusical analysis
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An Information-Theoretic Framework to Measure the Dynamic Interaction between Neural Spike Trains

2021

Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumptions that may lead to wrong inferences if not met. This work presents a framework, grounded in the field of information dynamics, for the model-free, continuous-time estimation of both undirected (symmetric) and directed (causal) interactions between pairs of spike trains. The framework decomposes the overall information exchanged dynami…

Computer scienceSpike trainEntropyModels NeurologicalBiomedical EngineeringAction Potentials01 natural sciencesAtmospheric measurementsPoint process010305 fluids & plasmask-nearest neighbors algorithm0103 physical sciencesEntropy (information theory)Computer Simulation010306 general physicsBiomedical measurementmutual informationpoint processesParametric statisticsNeuronsneural synchronyQuantitative Biology::Neurons and CognitionParticle measurementstransfer entropyMutual informationTime measurementSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)FOS: Biological sciencesQuantitative Biology - Neurons and CognitionSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaNeurons and Cognition (q-bio.NC)Transfer entropySpike (software development)information dynamicsAlgorithmEstimationIEEE Transactions on Biomedical Engineering
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