Search results for " learning"

showing 10 items of 5299 documents

Integrating Environmental Temperature Conditions into the SIR Model for Vector-Borne Diseases

2020

International audience; Nowadays, Complex networks are used to model and analyze various problems of real-life e.g. information diffusion in social networks, epidemic spreading in human population etc. Various epidemic spreading models are proposed for analyzing and understanding the spreading of infectious diseases in human contact networks. In classical epidemiological models, a susceptible person becomes infected after getting in contact with an infected person among the human population only. However, in vector-borne diseases, a human can be infected also by a living organism called a vector. The vector population that also help in spreading diseases is very sensitive to environmental f…

Computer sciencePopulationEpidemic dynamicsEpidemic SpreadingComplex NetworkContact networkMachine learningcomputer.software_genre01 natural sciences010305 fluids & plasmasEnvironmental temperature0103 physical sciences[INFO]Computer Science [cs]010306 general physicseducationeducation.field_of_studybusiness.industryTemperatureComplex network3. Good healthHomogeneousDy- namics on NetworkVector (epidemiology)Artificial intelligenceSIR modelEpidemic modelbusinesscomputer
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CovSel

2018

Ensemble methods combine the predictions of a set of models to reach a better prediction quality compared to a single model's prediction. The ensemble process consists of three steps: 1) the generation phase where the models are created, 2) the selection phase where a set of possible ensembles is composed and one is selected by a selection method, 3) the fusion phase where the individual models' predictions of the selected ensemble are combined to an ensemble's estimate. This paper proposes CovSel, a selection approach for regression problems that ranks ensembles based on the coverage of adequately estimated training points and selects the ensemble with the highest coverage to be used in th…

Computer scienceProcess (computing)Phase (waves)Genetic programming02 engineering and technology01 natural sciencesEnsemble learningSet (abstract data type)010104 statistics & probability0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPoint (geometry)0101 mathematicsSymbolic regressionAlgorithmSelection (genetic algorithm)Proceedings of the Genetic and Evolutionary Computation Conference
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Emulation of 2D Hydrodynamic Flood Simulations at Catchment Scale Using ANN and SVR

2021

Two-dimensional (2D) hydrodynamic models are one of the most widely used tools for flood modeling practices and risk estimation. The 2D models provide accurate results

Computer scienceProcess (engineering)Geography Planning and DevelopmentAquatic ScienceMachine learningcomputer.software_genreBiochemistrysupport vector regressionTD201-500Uncertainty analysisWater Science and TechnologyEmulationArtificial neural networkFlood mythWater supply for domestic and industrial purposesbusiness.industryDimensionality reductionHydraulic engineeringSupport vector machineemulatorsVDP::Teknologi: 500Sample size determinationerror structureArtificial intelligencetraining set sizebusinessTC1-978computerartificial neural networkWater
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On-line Coordination in Complex Goal-directed Movements: a Matter of Interactions between Several Loops.

2012

International audience; Motor flexibility is the ability to rapidly modify behavior when unexpected perturbations occur. In goal directed movements, this process may be involved during the motor execution itself, by using on-line motor corrections, or off-line, on a trial-by-trial basis. A consensus has emerged to describe and unify these two dependant processes within the framework of the internal models theory in which the cerebellum is involved in error processing. However, this general framework may be incomplete to describe on-line motor corrections when complex motor coordination is involved in the task. In particular, interaction torques existing between different effectors limit the…

Computer scienceProcess (engineering)Movement050105 experimental psychology[SPI.AUTO]Engineering Sciences [physics]/Automatic03 medical and health sciences0302 clinical medicineControl theory[ SPI.AUTO ] Engineering Sciences [physics]/AutomaticNeural PathwaysReaction TimeAnimalsHumans0501 psychology and cognitive sciencesCerebral CortexFlexibility (engineering)Communicationbusiness.industryGeneral Neuroscience[SCCO.NEUR]Cognitive science/Neuroscience05 social sciences[SCCO.NEUR] Cognitive science/NeuroscienceMotor controlEfference copy16. Peace & justiceMotor coordinationDegrees of freedom problem[SPI.AUTO] Engineering Sciences [physics]/Automatic[ SCCO.NEUR ] Cognitive science/NeuroscienceNerve NetMotor learningbusinessGoalsMotor goalPsychomotor Performance030217 neurology & neurosurgery
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Computational Offloading in Mobile Edge with Comprehensive and Energy Efficient Cost Function: A Deep Learning Approach

2021

In mobile edge computing (MEC), partial computational offloading can be intelligently investigated to reduce the energy consumption and service delay of user equipment (UE) by dividing a single task into different components. Some of the components execute locally on the UE while the remaining are offloaded to a mobile edge server (MES). In this paper, we investigate the partial offloading technique in MEC using a supervised deep learning approach. The proposed technique, comprehensive and energy efficient deep learning-based offloading technique (CEDOT), intelligently selects the partial offloading policy and also the size of each component of a task to reduce the service delay and energy …

Computer scienceReal-time computingTP1-118502 engineering and technologyBiochemistryVDP::Teknologi: 500::Elektrotekniske fag: 540ArticleAnalytical Chemistry0202 electrical engineering electronic engineering information engineeringcomputational offloadingElectrical and Electronic EngineeringInstrumentationenergy efficiencyMobile edge computingArtificial neural networkbusiness.industryChemical technologyDeep learningdeep learning020206 networking & telecommunicationsEnergy consumptionAtomic and Molecular Physics and OpticsTask (computing)cost functionUser equipment020201 artificial intelligence & image processingmobile edge computingArtificial intelligenceEnhanced Data Rates for GSM Evolutionremote executionbusinessEfficient energy useSensors
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Semiautomatic Behavioral Change-Point Detection: A Case Study Analyzing Children Interactions With a Social Agent

2021

The study of human behaviors in cognitive sciences provides clues to understand and describe people’s personal and interpersonal functioning. In particular, the temporal analysis of behavioral dynamics can be a powerful tool to reveal events, correlations and causalities but also to discover abnormal behaviors. However, the annotation of these dynamics can be expensive in terms of temporal and human resources. To tackle this challenge, this paper proposes a methodology to semi-automatically annotate behavioral data. Behavioral dynamics can be expressed as sequences of simple dynamical processes: transitions between such processes are generally known as change-points. This paper describes th…

Computer scienceSemi-automated annotationInterpersonal communicationHuman BehaviorMachine learningcomputer.software_genreHuman behaviorTask (project management)[SCCO]Cognitive scienceAnnotationArtificial IntelligenceChange-pointPsychologyTrainingComputingMilieux_MISCELLANEOUSPsychiatrySettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryManualComputational modelingSocial agentsDynamics (music)Task analysisToolTask analysiArtificial intelligencebusinesscomputerSoftwareChange detectionIEEE Transactions on Cognitive and Developmental Systems
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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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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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Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text

2016

International audience; Depression is a major cause of disability world-wide. The present paper reports on the results of our participation to the depression sub-challenge of the sixth Audio/Visual Emotion Challenge (AVEC 2016), which was designed to compare feature modalities ( audio, visual, interview transcript-based) in gender-based and gender-independent modes using a variety of classification algorithms. In our approach, both high and low level features were assessed in each modality. Audio features were extracted from the low-level descriptors provided by the challenge organizers. Several visual features were extracted and assessed including dynamic characteristics of facial elements…

Computer scienceSpeech recognitionPosterior probabilitymultimodal fusionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI]Engineering Sciences [physics]AVEC 2016Histogram0202 electrical engineering electronic engineering information engineeringFeature (machine learning)[ SPI ] Engineering Sciences [physics]Affective computingaffective computing[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]speech processing[SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph]Modality (human–computer interaction)[ SPI.ACOU ] Engineering Sciences [physics]/Acoustics [physics.class-ph]pattern recognition020206 networking & telecommunicationsSpeech processingimage processingStatistical classificationdepression assessment13. Climate actionPattern recognition (psychology)020201 artificial intelligence & image processing
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Mediated learning materials: visibility checks in telepresence robot mediated classroom interaction

2021

Videoconferencing is increasingly used in education as a way to support distance learning. This article contributes to the emerging interactional literature on video-mediated educational interaction by exploring how a telepresence robot is used to facilitate remote participation in university-level foreign language teaching. A telepresence robot differs from commonly used videoconferencing set-ups in that it allows mobility and remote camera control. A remote student can thus move a classroom-based robot from a distance in order to shift attention between people, objects and environmental structures during classroom activities. Using multimodal conversation analysis, we focus on how partici…

Computer scienceTeaching methodDistance educationComputer-Assisted Instructionluokkatyöskentelycomputer.software_genreEducationMultimodalityVideoconferencingHuman–computer interactionetäosallistuminenvideoneuvottelutlearning materialsmultimodalitymultimodaalisuusoppimateriaali060201 languages & linguisticsTeleroboticskieltenopetus4. Education05 social sciencesVisibility (geometry)Educational technology050301 educationvideo-mediated interaction06 humanities and the artstelepresence robotcomputer-assisted language learning0602 languages and literaturerobotitclassroom interaction516 Educational sciences0503 educationcomputer
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