Search results for "model [interaction]"

showing 10 items of 1495 documents

On the structure of certain ultradistributions

2009

Let "o" be a nonempty open subset of the k-dimensional euclidean space Rk. In this paper we show that, if S is an ultradistribution in "o", belonging to a class of Roumieu type stable under differential operators, then there is a family f , 2 Nk 0, of elements of L1 loc("o") such that S is represented in the formP 2Nk 0 D"a"f "a". Some other results on the structure of certain ultradistributions of Roumieu type are also given.

Computational MathematicsPure mathematicsClass (set theory)Algebra and Number TheoryEuclidean spaceApplied MathematicsMathematical analysisStructure (category theory)Geometry and TopologyType (model theory)Differential operatorAnalysisMathematicsRevista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas
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Multimodal data as a means to understand the learning experience

2019

Most work in the design of learning technology uses click-streams as their primary data source for modelling & predicting learning behaviour. In this paper we set out to quantify what, if any, advantages do physiological sensing techniques provide for the design of learning technologies. We conducted a lab study with 251 game sessions and 17 users focusing on skill development (i.e., user's ability to master complex tasks). We collected click-stream data, as well as eye-tracking, electroencephalography (EEG), video, and wristband data during the experiment. Our analysis shows that traditional click-stream models achieve 39% error rate in predicting learning performance (and 18% when we perf…

Computer Networks and CommunicationsComputer scienceMultimodal data05 social sciencesWord error rateFeature selection02 engineering and technologyLibrary and Information SciencesSkill developmentVariety (cybernetics)Dreyfus model of skill acquisitionLearning experienceHuman–computer interaction020204 information systems0502 economics and business0202 electrical engineering electronic engineering information engineering050211 marketingSet (psychology)Information Systems
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On the stability of spline-collocation methods of multivalue type

1987

In this paper the general classV of spline-collocation methods for first order systems of ordinary differential equations is investigated. The methods can in part be regarded as so-called multivalue methods. This type contains the generalized singly-implicit methods treated by Butcher.

Computer Networks and CommunicationsDifferential equationApplied MathematicsMathematical analysisStability (learning theory)Type (model theory)Computational MathematicsSpline collocationCollocation methodOrdinary differential equationApplied mathematicsFundamental Resolution EquationMultiValueSoftwareMathematicsBIT
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Cholesky decomposition techniques in electronic structure theory

2011

We review recently developed methods to efficiently utilize the Cholesky decomposition technique in electronic structure calculations. The review starts with a brief introduction to the basics of the Cholesky decomposition technique. Subsequently, examples of applications of the technique to ab inito procedures are presented. The technique is demonstrated to be a special type of a resolution-of-identity or density-fitting scheme. This is followed by explicit examples of the Cholesky techniques used in orbital localization, computation of the exchange contribution to the Fock matrix, in MP2, gradient calculations, and so-called method specific Cholesky decomposition. Subsequently, examples o…

Computer and Information SciencesTheoretical computer scienceBasis (linear algebra)Computer scienceCalibration (statistics)ComputationAb initioMathematicsofComputing_NUMERICALANALYSISData- och informationsvetenskapKemiType (model theory)Fock matrixChemical SciencesPruning (decision trees)AlgorithmCholesky decomposition
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A modeling study suggesting how a reduction in the context-dependent input on CA1 pyramidal neurons could generate schizophrenic behavior.

2011

The neural mechanisms underlying schizophrenic behavior are unknown and very difficult to investigate experimentally, although a few experimental and modeling studies suggested possible causes for some of the typical psychotic symptoms related to this disease. The brain region most involved in these processes seems to be the hippocampus, because of its critical role in establishing memories for objects or events in the context in which they occur. In particular, a hypofunction of the N-methyl-D-aspartate (NMDA) component of the synaptic input on the distal dendrites of CA1 pyramidal neurons has been suggested to play an important role for the emergence of schizophrenic behavior. Modeling st…

Computer scienceCognitive Neurosciencemedia_common.quotation_subjectSchizophrenia Realistic model CA1 Hippocampus Object recognition Synaptic integrationCentral nervous systemModels NeurologicalCa1 neuronHippocampusHippocampal formationSynapse03 medical and health sciences0302 clinical medicineArtificial IntelligencePerceptionmedicineAnimalsHumansInvariant (mathematics)CA1 Region Hippocampal030304 developmental biologymedia_common0303 health sciencesRecallArtificial neural networkPyramidal NeuronSynaptic integrationPyramidal CellsCognitive neuroscience of visual object recognitionDendritesmedicine.diseasemedicine.anatomical_structurenervous systemSchizophreniaSynapsesSchizophreniaNMDA receptorNeuronNerve NetNeuroscience030217 neurology & neurosurgeryNeural networks : the official journal of the International Neural Network Society
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Boolean Networks: A Primer

2021

Abstract Autism Spectrum Disorders (ASDs) stand out as a relevant example where omics-data approaches have been extensively and successfully employed. For instance, an outstanding outcome of the Autism Genome Project relies in the identification of biomarkers and the mapping of biological processes potentially implicated in ASDs’ pathogenesis. Several of these mapped processes are related to molecular and cellular events (e.g., synaptogenesis and synapse function, axon growth and guidance, etc.) that are required for the development of a correct neuronal connectivity. Interestingly, these data are consistent with results of brain imaging studies of some patients. Despite these remarkable pr…

Computer scienceIn silicoAttractor Autism spectrum disorders (ASDs) Axon guidance Basin of attraction Boolean network BoolNet Computational model Copy number variants (CNVs) Growth cone In silico mutagenesis Mutations Neurodevelopmental disorders Systems biologyGenome projectComputational biologyGene mutationmedicine.diseasePhenotypeEndophenotypemental disordersmedicineAutismIdentification (biology)Function (biology)
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Transformations that preserve learnability

1996

We consider transformations (performed by general recursive operators) mapping recursive functions into recursive functions. These transformations can be considered as mapping sets of recursive functions into sets of recursive functions. A transformation is said to be preserving the identification type I, if the transformation always maps I-identifiable sets into I-identifiable sets.

Computer scienceLearnabilityType (model theory)Inductive reasoningAlgebraTuring machinesymbols.namesakeIdentification (information)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESTransformation (function)TheoryofComputation_LOGICSANDMEANINGSOFPROGRAMSRecursive functionssymbolsInitial segment
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FMI4j: A Software Package for working with Functional Mock-up Units on the Java Virtual Machine

2018

This paper introduces FMI4j, a software package for working with Functional Mock-up Units (FMUs) on the Java Virtual Machine (JVM). FMI4j is written in Kotlin, which is 100% interoperable with Java, and consists of programming APIs for parsing the meta-data associated with an FMU, as well as running them. FMI4j is compatible with FMI version 2.0 for Model Exchange (ME) and Co-Simulation (CS). Currently, FMI4j is the only software library targeting the JVM supporting ME 2.0. In addition to provide bare-bones access to such FMUs, it provides the means for solving them using a range of bundled fixedand variable-step solvers. A command line tool named FMU2Jar is also provided, which is capable …

Computer scienceMockupOperating systemCo-simulationSoftware packageJava virtual machinecomputer.software_genrecomputerModel exchange
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Statistical geometric affinity in human brain electric activity

2007

10 pages, 9 figures.-- PACS nrs.: 87.19.La; 05.45.Tp.-- ISI Article Identifier: 000246890100105

Computer scienceModels NeurologicalNeurophysiologyElectroencephalographyInterpretation (model theory)[PACS] Time series analysis (nonlinear dynamical systems)LacunaritymedicineHumansComputer SimulationDiagnosis Computer-AssistedWakefulnessRepresentation (mathematics)ScalingEvoked PotentialsModels Statisticalmedicine.diagnostic_testbusiness.industry[PACS] Neuroscience (higher organisms)BrainPattern recognitionElectroencephalographyNeurophysiologyAmplitudeStatistical analysisData Interpretation StatisticalBioelectric phenomenaLacunarityAffine transformationArtificial intelligenceSleep StagesbusinessSleep
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Theoretical Foundations of the Monte Carlo Method and Its Applications in Statistical Physics

2002

In this chapter we first introduce the basic concepts of Monte Carlo sampling, give some details on how Monte Carlo programs need to be organized, and then proceed to the interpretation and analysis of Monte Carlo results.

Computer scienceMonte Carlo methodThermodynamic limitPeriodic boundary conditionsMonte Carlo method in statistical physicsIsing modelStatistical physicsImportance samplingMonte Carlo molecular modelingInterpretation (model theory)
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