Search results for "DOMAIN"

showing 10 items of 2485 documents

Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions

2022

The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…

FOS: Computer and information sciencesComputer Science - Machine LearningEarth observationAdvanced microwave scanning radiometer-2 (AMSR-2)moderate resolution imaging spectroradiometer (MODIS)Computer scienceleaf area index (LAI)0211 other engineering and technologiesExtrapolationMachine Learning (stat.ML)02 engineering and technologycomputer.software_genreMachine Learning (cs.LG)Data-drivenConvolutionsymbols.namesakeadvanced scatterometer (ASCAT)Statistics - Machine Learningordinary differential equation (ODE)Electrical and Electronic EngineeringGaussian processsoil moisture and ocean salinity (SMOS)021101 geological & geomatics engineeringInterpretabilityForcing (recursion theory)machine learning (ML)soil moisture (SM)time series analysisgaussian process (GP)symbolsGeneral Earth and Planetary SciencesDomain knowledgeData mininggap fillingphysicscomputerfraction of absorbed photosynthetically active radiation (faPAR)IEEE Transactions on Geoscience and Remote Sensing
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Environment Sound Classification using Multiple Feature Channels and Attention based Deep Convolutional Neural Network

2020

In this paper, we propose a model for the Environment Sound Classification Task (ESC) that consists of multiple feature channels given as input to a Deep Convolutional Neural Network (CNN) with Attention mechanism. The novelty of the paper lies in using multiple feature channels consisting of Mel-Frequency Cepstral Coefficients (MFCC), Gammatone Frequency Cepstral Coefficients (GFCC), the Constant Q-transform (CQT) and Chromagram. Such multiple features have never been used before for signal or audio processing. And, we employ a deeper CNN (DCNN) compared to previous models, consisting of spatially separable convolutions working on time and feature domain separately. Alongside, we use atten…

FOS: Computer and information sciencesComputer Science - Machine LearningSound (cs.SD)Computer science020209 energyMachine Learning (stat.ML)02 engineering and technologycomputer.software_genreConvolutional neural networkComputer Science - SoundDomain (software engineering)Machine Learning (cs.LG)Statistics - Machine LearningAudio and Speech Processing (eess.AS)0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringAudio signal processingVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550business.industrySIGNAL (programming language)Pattern recognitionFeature (computer vision)Benchmark (computing)020201 artificial intelligence & image processingArtificial intelligenceMel-frequency cepstrumbusinesscomputerElectrical Engineering and Systems Science - Audio and Speech ProcessingCommunication channel
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Critical comments on EEG sensor space dynamical connectivity analysis

2019

Many different analysis techniques have been developed and applied to EEG recordings that allow one to investigate how different brain areas interact. One particular class of methods, based on the linear parametric representation of multiple interacting time series, is widely used to study causal connectivity in the brain. However, the results obtained by these methods should be interpreted with great care. The goal of this paper is to show, both theoretically and using simulations, that results obtained by applying causal connectivity measures on the sensor (scalp) time series do not allow interpretation in terms of interacting brain sources. This is because (1) the channel locations canno…

FOS: Computer and information sciencesComputer scienceSocial SciencesTransfer functionStatistics - Applications050105 experimental psychology03 medical and health sciences0302 clinical medicinegranger causalityMVARHumansApplications (stat.AP)Computer Simulation0501 psychology and cognitive sciencesRadiology Nuclear Medicine and imagingBrain connectivityEEGTime domainSpurious relationshipRepresentation (mathematics)Mixing (physics)Parametric statisticsBrain MappingRadiological and Ultrasound TechnologySeries (mathematics)05 social sciencesbrain connectivitysource modellingElectroencephalographyNeurologyFOS: Biological sciencesFrequency domainQuantitative Biology - Neurons and CognitionSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityDirected transfer functionNeurons and Cognition (q-bio.NC)Neurology (clinical)AnatomyAlgorithm030217 neurology & neurosurgery
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Free boundary methods and non-scattering phenomena

2021

We study a question arising in inverse scattering theory: given a penetrable obstacle, does there exist an incident wave that does not scatter? We show that every penetrable obstacle with real-analytic boundary admits such an incident wave. At zero frequency, we use quadrature domains to show that there are also obstacles with inward cusps having this property. In the converse direction, under a nonvanishing condition for the incident wave, we show that there is a dichotomy for boundary points of any penetrable obstacle having this property: either the boundary is regular, or the complement of the obstacle has to be very thin near the point. These facts are proved by invoking results from t…

FOS: Physical sciencesBoundary (topology)01 natural sciencesinversio-ongelmatTheoretical Computer ScienceMathematics - Analysis of PDEsMathematics (miscellaneous)ConverseFOS: MathematicsPoint (geometry)0101 mathematicsMathematical PhysicsComplement (set theory)MathematicsosittaisdifferentiaaliyhtälötQuadrature domainsScatteringApplied MathematicsResearch010102 general mathematicsMathematical analysisMathematical Physics (math-ph)010101 applied mathematicsComputational MathematicsObstacleInverse scattering problemAnalysis of PDEs (math.AP)Research in the Mathematical Sciences
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Observation of Geometric Parametric Instability Induced by the Periodic Spatial Self-Imaging of Multimode Waves

2016

Spatio-temporal mode coupling in highly multimode physical systems permits new routes for exploring complex instabilities and forming coherent wave structures. We present here the first experimental demonstration of multiple geometric parametric instability sidebands, generated in the frequency domain through resonant space-time coupling, owing to the natural periodic spatial self-imaging of a multimode quasi-continuous-wave beam in a standard graded-index multimode fiber. The input beam was launched in the fiber by means of an amplified microchip laser emitting sub-nanosecond pulses at 1064 nm. The experimentally observed frequency spacing among sidebands agrees well with analytical predic…

FOS: Physical sciencesGeneral Physics and AstronomyPhysics::Optics01 natural scienceslaw.invention010309 opticsOpticslaw0103 physical sciencesDispersion (optics)010306 general physicsComputingMilieux_MISCELLANEOUSCouplingPhysics[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics][ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics]Multi-mode optical fiberSidebandbusiness.industryLaserFrequency domain analysis; infrared devices; infrared lasersWavelengthFrequency domainMode coupling[ SPI.OPTI ] Engineering Sciences [physics]/Optics / PhotonicbusinessOptics (physics.optics)Physics - Optics
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Remote heart rate variability for emotional state monitoring

2018

International audience; Several researches have been conducted to recognize emotions using various modalities such as facial expressions , gestures, speech or physiological signals. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system. It has been shown for example that there is an undeniable relationship between emotional state and Heart Rate Variability (HRV). In this paper, we present a methodology to monitor emotional state from physiological signals acquired remotely. The method is based on a remote photoplethysmography (rPPG) algorithm that estimates remote Heart Rate Variability (rHRV) using a …

Facial expressionModalities[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceSpeech recognition020208 electrical & electronic engineering0206 medical engineering[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020601 biomedical engineeringSignal[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingFeature (computer vision)Frequency domainPhotoplethysmogram0202 electrical engineering electronic engineering information engineeringHeart rate variabilityGesture
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Coarse scales are sufficient for efficient categorization of emotional facial expressions: Evidence from neural computation

2010

The human perceptual system performs rapid processing within the early visual system: low spatial frequency information is processed rapidly through magnocellular layers, whereas the parvocellular layers process all the spatial frequencies more slowly. The purpose of the present paper is to test the usefulness of low spatial frequency (LSF) information compared to high spatial frequency (HSF) and broad spatial frequency (BSF) visual stimuli in a classification task of emotional facial expressions (EFE) by artificial neural networks. The connectionist modeling results show that an LSF information provided by the frequency domain is sufficient for a distributed neural network to correctly cla…

Facial expressionVisual perceptionArtificial neural networkComputer sciencebusiness.industryCognitive NeurosciencePattern recognitionCognitive neuroscienceComputer Science ApplicationsPerceptual systemModels of neural computationConnectionismArtificial IntelligenceParvocellular cellFrequency domainComputer visionArtificial intelligencebusinessNeurocomputing
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p53 triggers apoptosis in oncogene-expressing fibroblasts by the induction of Noxa and mitochondrial Bax translocation.

2003

The mechanism of p53-dependent apoptosis is still only partly defined. Using early-passage embryonic fibroblasts (MEF) from wild-type (wt), p53(-/-) and bax(-/-) mice, we observe a p53-dependent translocation of Bax to the mitochondria and a release of mitochondrial Cytochrome c during stress-induced apoptosis. These events proceed independent of zVAD-inhibitable caspase activation, are not prevented by dominant negative FADD (DN-FADD), but are negatively regulated by Mdm-2. Bcl-x(L) expression prevents the release of mitochondrial Cytochrome c and apoptosis, but not Bax translocation. At a single-cell level, enforced expression of p53 is sufficient to induce Bax translocation and Cytochrom…

Fas-Associated Death Domain ProteinDown-RegulationChromosomal translocationApoptosisCytochrome c GroupMitochondrionMiceBcl-2-associated X proteinFetusDownregulation and upregulationProto-Oncogene ProteinsAnimalsFADDEnzyme InhibitorsMolecular BiologyCells CulturedAdaptor Proteins Signal Transducingbcl-2-Associated X ProteinMice KnockoutbiologyOncogeneChemistryCytochrome cCell BiologyFibroblastsMolecular biologyCell biologyMitochondriaProtein TransportGene Expression RegulationProto-Oncogene Proteins c-bcl-2ApoptosisCaspasesbiology.proteinTumor Suppressor Protein p53Carrier ProteinsCell death and differentiation
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Toward Optimal LSTM Neural Networks for Detecting Algorithmically Generated Domain Names

2021

Malware detection is a problem that has become particularly challenging over the last decade. A common strategy for detecting malware is to scan network traffic for malicious connections between infected devices and their command and control (C&C) servers. However, malware developers are aware of this detection method and begin to incorporate new strategies to go unnoticed. In particular, they generate domain names instead of using static Internet Protocol addresses or regular domain names pointing to their C&C servers. By using a domain generation algorithm, the effectiveness of the blacklisting of domains is reduced, as the large number of domain names that must be blocked g…

Feature engineeringGeneral Computer ScienceArtificial neural networkComputer sciencebusiness.industrymalwareDeep learningGeneral EngineeringDeep learningdomain generation algorithmscomputer.software_genreBlacklistDomain (software engineering)TK1-9971ServerMalwareGeneral Materials ScienceNetwork performanceArtificial intelligenceData miningElectrical engineering. Electronics. Nuclear engineeringbusinessLSTMcomputerIEEE Access
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The domain structure in PLZT (6-8)/65/35 and spontaneous ferroelectric-relaxor phase transition

1995

Abstract In order to test the hypothesis proposed in Reference 10 about a spontaneous relaxor-ferroelectric phase transition in PLZT (6-7)/65/35 the hysteresis loops and domain structure measurements were carried out. The results confirm this hypothesis. The appearance of the ferroelectric long range order in PLZT with decreasing concentration of La ions is explained by a larger coupling between the feroelectrically active BO6 octahedrons due to smaller concentration of defects and higher dielectric constant.

Ferroelectric relaxorPhase transitionMaterials scienceCondensed matter physicsbusiness.industryDielectricCondensed Matter PhysicsFerroelectricityElectronic Optical and Magnetic MaterialsIonCoupling (electronics)HysteresisOpticsDomain (ring theory)businessFerroelectrics
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