Search results for " modeling"

showing 10 items of 2411 documents

Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia

2020

Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…

Support Vector MachinePhysiologyComputer scienceElectroencephalographycomputer.software_genreField (computer science)Machine Learning0302 clinical medicineLevel of consciousnessAnesthesiology030202 anesthesiologyMedicine and Health SciencesAnesthesiamedia_commonClinical NeurophysiologyAnesthesiology MonitoringBrain MappingMultidisciplinaryArtificial neural networkmedicine.diagnostic_testPharmaceuticsApplied MathematicsSimulation and ModelingQUnconsciousnessRElectroencephalographyNeuronal pathwayddc:ElectrophysiologyBioassays and Physiological AnalysisBrain ElectrophysiologyAnesthesiaPhysical SciencesEvoked Potentials AuditoryMedicinemedicine.symptomAlgorithmsAnesthetics IntravenousResearch ArticleComputer and Information SciencesConsciousnessImaging TechniquesCognitive NeuroscienceSciencemedia_common.quotation_subjectNeurophysiologyNeuroimagingAnesthesia GeneralResearch and Analysis MethodsBayesian inferenceMachine learningMachine Learning Algorithms03 medical and health sciencesConsciousness MonitorsDrug TherapyArtificial IntelligenceMonitoring IntraoperativeSupport Vector MachinesmedicineHumansMonitoring Physiologicbusiness.industryElectrophysiological TechniquesBiology and Life SciencesSupport vector machineStatistical classificationCognitive ScienceNeural Networks ComputerArtificial intelligenceClinical MedicineConsciousnessbusinesscomputerMathematics030217 neurology & neurosurgeryNeurosciencePLOS ONE
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Applications of Kernel Methods

2009

In this chapter, we give a survey of applications of the kernel methods introduced in the previous chapter. We focus on different application domains that are particularly active in both direct application of well-known kernel methods, and in new algorithmic developments suited to a particular problem. In particular, we consider the following application fields: biomedical engineering (comprising both biological signal processing and bioinformatics), communications, signal, speech and image processing.

Support vector machineKernel methodbusiness.industryComputer scienceVariable kernel density estimationPolynomial kernelRadial basis function kernelPattern recognitionArtificial intelligenceGeometric modeling kernelTree kernelbusinessKernel principal component analysis
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Comment on "surface restructuring, kinetic oscillations, and chaos in heterogeneous catalytic reactions".

1999

In a recent article Zhdanov studied the oscillating $\mathrm{NO}+{\mathrm{H}}_{2}$ reaction on the Pt(100) single-crystal surface [V. P. Zhdanov, Phys. Rev. E 59, 6292 (1999)]. We have scrutinized his model and found fundamental errors in the chemical modeling, in the modeling of the surface reconstruction and in the simulation procedure itself.

Surface (mathematics)PhysicsChemical process modelingThermodynamicsKinetic energySurface reconstructionCatalysisPhysical review. E, Statistical, nonlinear, and soft matter physics
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Exploring Innovation Adoption Behavior for Sustainable Development: The Case of Hungarian Food Sector

2020

Innovation plays a key role in the success and sustainable development of businesses. The innovation process derives from the combination of personal skills and company resources that influence food company managers in their choices on innovation (the decision-making process). This study is an attempt to try to understand which psychological constructs affect innovation decision-making in the Hungarian food sector, using the empirical data from a 2017 survey conducted in Hungary among the largest food processing companies. Planned behavior theory (TPB) was applied to the study of factors affecting innovation decision-making. Structural Equation Modeling (SEM) was used for data analysis. The…

Sustainable developmentProcess (engineering)business.industry05 social sciencesTheory of planned behaviorlcsh:Sfood innovationAffect (psychology)Innovation adoptionstructural equation modelingStructural equation modelinglcsh:AgricultureFood sectorbehavioral decision-making0502 economics and businesssustainable productionSettore AGR/01 - Economia Ed Estimo RuraleFood processing050211 marketingtheory of planned behaviorMarketingsustainable productionsbusinessAgronomy and Crop Science050203 business & managementAgronomy
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Smart Sustainable Cities of the New Millennium: Towards Design for Nature

2021

AbstractUrban environments consist of a mosaic of natural fragments, planned and unintentional habitats hosting both introduced and spontaneous species. The latter group exploits abandoned and degraded urban niches which, in the case of plants, form what is called thethird landscape. In the Anthropocene, cities, open spaces and buildings must be planned and designed considering not only human needs but also those of other living organisms. The scientific approach of habitat sharing is defined asreconciliation ecology, whilst the action of implementing the ecosystem services and functioning of such anthropogenic habitats is calledUrban Rehabilitation. However, urban development still represe…

Sustainable developmentSettore BIO/07 - EcologiaSettore ICAR/15 - Architettura Del Paesaggiobusiness.industryGeodesignReconciliation ecologyGeneral Engineering711: Raumplanung (Städtebau)BiodiversityUrban ecology Biodiversity Holistic design Design with Nature Nature-based solution GeoBIM DeMoFundamental human needsEcosystem servicesGeodesignGeographyUrban ecologyUrban ecologyBuilding information modelingUrban planningSettore BIO/03 - Botanica Ambientale E ApplicataHolistic designbusinessGeoBIMEnvironmental planningDeMoDesign with nature
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A Hidden Markov Model for Automatic Generation of ER Diagrams from OWL Ontology

2014

Connecting ontological representations and data models is a crucial need in enterprise knowledge management, above all in the case of federated enterprises where corporate ontologies are used to share information coming from different databases. OWL to ERD transformations are a challenging research field in this scenario, due to the loss of expressiveness arising when OWL axioms have to be represented using ERD notation. In this paper we propose an innovative technique for estimating the most likely composition of ERD constructs that correspond to a given sequence of OWL axioms. We model such a process using a Hidden Markov Model (HMM) where the OWL inputs are the observable states, while E…

Syntax (programming languages)Computer sciencebusiness.industrycomputer.internet_protocolWeb Ontology Languagecomputer.software_genreNotationOWL-SData modelingSet (abstract data type)Entity–relationship modelArtificial intelligenceHidden Markov modelbusinesscomputerNatural language processingcomputer.programming_language2014 IEEE International Conference on Semantic Computing
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Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part I : remote sensing model intercomparison

2011

A number of energy balance models of variable complexity that use remotely sensed boundary conditions for producing spatially distributed maps of surface fluxes have been proposed. Validation typically involves comparing model output to flux tower observations at a handful of sites, and hence there is no way of evaluating the reliability of model output for the remaining pixels comprising a scene. To assess the uncertainty in flux estimation over a remote sensing scene requires one to conduct pixel-by-pixel comparisons of the output. The objective of this paper is to assess whether the simplifications made in a simple model lead to erroneous predictions or deviations from a more complex mod…

Synthetic aperture radarAtmospheric SciencePixelMeteorologyPlanetary boundary layerMETIS-303907Energy balanceAtmospheric modelData modelingremote sensingHeat fluxenergy balance modelRadiative transferEnvironmental scienceComputers in Earth SciencesAgrisarRemote sensingIEEE Journal of selected topics in applied earth observations and remote sensing
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A practical methodology to perform global sensitivity analysis for 2D hydrodynamic computationally intensive simulations

2021

Sensitivity analysis is a commonly used technique in hydrological modeling for different purposes, including identifying the influential parameters and ranking them. This paper proposes a simplified sensitivity analysis approach by applying the Taguchi design and the ANOVA technique to 2D hydrodynamic flood simulations, which are computationally intensive. This approach offers an effective and practical way to rank the influencing parameters, quantify the contribution of each parameter to the variability of the outputs, and investigate the possible interaction between the input parameters. A number of 2D flood simulations have been carried out using the proposed combinations by Taguchi (L27…

TC401-506Physical geographyComputer sciencetaguchi designcomputer.software_genreGB3-5030River lake and water-supply engineering (General)VDP::Teknologi: 500Global sensitivity analysisglobal sensitivity analysisData mininganovacomputer2d hydrodynamic flood modelingWater Science and TechnologyHydrology Research
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Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset

2021

[EN] In patients with atrial fibrillation, intracardiac electrogram signal amplitude is known to decrease with increased structural tissue remodeling, referred to as fibrosis. In addition to the isolation of the pulmonary veins, fibrotic sites are considered a suitable target for catheter ablation. However, it remains an open challenge to find fibrotic areas and to differentiate their density and transmurality. This study aims to identify the volume fraction and transmurality of fibrosis in the atrial substrate. Simulated cardiac electrograms, combined with a generalized model of clinical noise, reproduce clinically measured signals. Our hybrid dataset approach combines in silico and clinic…

TECNOLOGIA ELECTRONICABidomainMachine learningDensityCardiac modelingddc:620Atrial fibrillationFibrosisEngineering & allied operationsTransmurality
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TRACX2: a RAAM -like autoencoder modeling graded chunking in infant visual -sequence learning

2017

International audience; Even newborn infants are able to extract structure from a stream of sensory inputs and yet, how this is achieved remains largely a mystery. We present a connectionist autoencoder model, TRACX2, that learns to extract sequence structure by gradually constructing chunks, storing these chunks in a distributed manner across its synaptic weights, and recognizing these chunks when they re-occur in the input stream. Chunks are graded rather than all-or-none in nature and during learning their component parts become ever more tightly bound together. TRACX2 successfully models data from four experiments from the infant visual statistical-learning literature, including tasks i…

TRACX2[SCCO.PSYC] Cognitive science/Psychology[SCCO.PSYC]Cognitive science/Psychologyautoencoder modelingvisual -sequence learning[ SCCO.PSYC ] Cognitive science/Psychology
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