Search results for "Simulation."

showing 10 items of 4779 documents

Shooting methods for 1D steady-state free boundary problems

1993

AbstractIn this note, we present two numerical methods based on shooting methods to solve steady-state diffusion-absorption models.

Computational MathematicsSteady state (electronics)Shooting methodComputational Theory and MathematicsQuantitative Biology::Tissues and OrgansModeling and SimulationNumerical analysisModelling and SimulationMathematical analysisBoundary (topology)GeometryMathematicsComputers & Mathematics with Applications
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Structure‐Activity Relationships of Benzamides and Isoindolines Designed as SARS‐CoV Protease Inhibitors Effective against SARS‐CoV‐2

2020

Abstract Inhibition of coronavirus (CoV)‐encoded papain‐like cysteine proteases (PLpro) represents an attractive strategy to treat infections by these important human pathogens. Herein we report on structure‐activity relationships (SAR) of the noncovalent active‐site directed inhibitor (R)‐5‐amino‐2‐methyl‐N‐(1‐(naphthalen‐1‐yl)ethyl) benzamide (2 b), which is known to bind into the S3 and S4 pockets of the SARS‐CoV PLpro. Moreover, we report the discovery of isoindolines as a new class of potent PLpro inhibitors. The studies also provide a deeper understanding of the binding modes of this inhibitor class. Importantly, the inhibitors were also confirmed to inhibit SARS‐CoV‐2 replication in …

Computational chemistryProteases2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)medicine.medical_treatmentSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)virusesStructure-activity relationshipsCysteine Proteinase InhibitorsIsoindolesCrystallography X-RayVirus Replicationmedicine.disease_causeAntiviral Agents01 natural sciencesBiochemistryDrug designStructure-Activity Relationshipchemistry.chemical_compoundCatalytic DomainChlorocebus aethiopsDrug DiscoverymedicineAnimalsddc:610General Pharmacology Toxicology and PharmaceuticsBenzamideVero CellsCoronavirus 3C ProteasesCoronavirusPharmacologyProteaseMolecular StructureFull PaperSARS-CoV-2010405 organic chemistryOrganic ChemistryFull PapersProtease inhibitors0104 chemical sciencesMolecular Docking Simulation010404 medicinal & biomolecular chemistrychemistryBiochemistryBenzamidesddc:540Molecular MedicineProtein BindingCysteine
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Comparison of implementations of the lattice-Boltzmann method

2008

AbstractSimplicity of coding is usually an appealing feature of the lattice-Boltzmann method (LBM). Conventional implementations of LBM are often based on the two-lattice or the two-step algorithm, which however suffer from high memory consumption and poor computational performance, respectively. The aim of this work was to identify implementations of LBM that would achieve high computational performance with low memory consumption. Effects of memory addressing schemes were investigated in particular. Data layouts for velocity distribution values were also considered, and they were found to be related to computational performance. A novel bundle data layout was therefore introduced. Address…

Computational fluid mechanicsMemory addressing schemesComputer scienceLattice Boltzmann methodsParallel computingSupercomputerAddressing modeHigh memoryMemory addressComputational MathematicsComputational Theory and MathematicsModeling and SimulationBundleModelling and SimulationLattice-Boltzmann methodImplementationHigh-performance computingCoding (social sciences)Computers & Mathematics with Applications
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Stochastic analysis of dynamical systems with delayed control forces

2006

Abstract Reduction of structural vibration in actively controlled dynamical system is usually performed by means of convenient control forces dependent of the dynamic response. In this paper the existent studies will be extended to dynamical systems subjected to non-normal delta-correlated random process with delayed control forces. Taylor series expansion of the control forces has been introduced and the statistics of the dynamical response have been obtained by means of the extended Ito differential rule. Numerical application provided shows the capabilities of the proposed method to analyze stochastic dynamic systems with delayed actions under delta-correlated process contrasting statist…

Computational methods in classical mechanicNumerical AnalysisDynamical systems theoryStochastic processApplied MathematicsStochastic analysis methodsProcess (computing)General linear dynamical systemDynamical systemLinear dynamical systemsymbols.namesakeControl theoryModeling and SimulationTaylor seriessymbolsNonlinear dynamics and nonlinear dynamical systemDifferential (infinitesimal)Reduction (mathematics)MathematicsCommunications in Nonlinear Science and Numerical Simulation
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Serious Games for Health and Safety Training

2011

EUROSTAT figures show that 5720 people die in the European Union every year as a consequence of work-related accidents. Training in Health and Safety is indeed a key aspect to reduce this figure, and serious games constitute an effective method to provide this training. However, the development of this type of computer applications is a complex issue, requiring cross discipline knowledge on different areas, including instructional design, psychology, sociology, law, and computer graphics. Beyond the challenges already present in the development of non-educational computer games, serious games for health and safety are instructional tools. Therefore, they require an instructional design to c…

Computer ApplicationsInstructional designmedia_common.quotation_subjectContext (language use)Occupational safety and healthEntertainmentRisk analysis (engineering)media_common.cataloged_instanceEuropean unionPsychologyGames for HealthSimulationSeriousnessmedia_common
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Modeling and Performance Analysis of Channel Assembling in Multichannel Cognitive Radio Networks With Spectrum Adaptation

2012

[EN] To accommodate spectrum access in multichannel cognitive radio networks (CRNs), the channel-assembling technique, which combines several channels together as one channel, has been proposed in many medium access control (MAC) protocols. However, analytical models for CRNs enabled with this technique have not been thoroughly investigated. In this paper, two representative channel-assembling strategies that consider spectrum adaptation and heterogeneous traffic are proposed, and the performance of these strategies is evaluated based on the proposed continuous-time Markov chain (CTMC) models. Moreover, approximations of these models in the quasistationary regime are analyzed, and closed-fo…

Computer Networks and CommunicationsComputer scienceAerospace EngineeringMarkov process02 engineering and technologyContinuous-time Markov chain (CTMC) modelsChannel assemblingsymbols.namesake0203 mechanical engineering0202 electrical engineering electronic engineering information engineeringCognitive radio networks (CRNs)Electrical and Electronic EngineeringAdaptation (computer science)SimulationMarkov chainPerformance analysisSpectrum (functional analysis)020206 networking & telecommunications020302 automobile design & engineeringINGENIERIA TELEMATICACognitive radioAutomotive EngineeringsymbolsSpectrum adaptationAlgorithmCommunication channelIEEE Transactions on Vehicular Technology
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BELM: Bayesian Extreme Learning Machine

2011

The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This brief proposes a bayesian approach to ELM, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap…

Computer Networks and CommunicationsComputer scienceComputer Science::Neural and Evolutionary ComputationBayesian probabilityOverfittingMachine learningcomputer.software_genrePattern Recognition AutomatedReduction (complexity)Artificial IntelligenceComputer SimulationRadial basis functionExtreme learning machineArtificial neural networkbusiness.industryEstimation theoryBayes TheoremGeneral MedicineComputer Science ApplicationsMultilayer perceptronNeural Networks ComputerArtificial intelligencebusinesscomputerAlgorithmsSoftwareIEEE Transactions on Neural Networks
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A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning

2016

Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…

Computer Networks and CommunicationsComputer scienceDecision MakingModels NeurologicalAction PotentialsContext (language use)Insect mushroom bodies bio-inspired control spiking neurons02 engineering and technologyVariation (game tree)Motor Activitybio-inspired control03 medical and health sciences0302 clinical medicineRewardSubsequence0202 electrical engineering electronic engineering information engineeringAnimalsLearningComputer SimulationMushroom BodiesTRACE (psycholinguistics)NeuronsSequencebio-inspired control; Insect mushroom bodies; learning; neural model; resonant neurons; spiking neurons; Action Potentials; Animals; Computer Simulation; Decision Making; Drosophila melanogaster; Learning; Motor Activity; Mushroom Bodies; Neurons; Perception; Reward; Robotics; Models Neurological; Neural Networks Computerspiking neuronsbusiness.industryRoboticsGeneral MedicineInsect mushroom bodiesComplex dynamicsDrosophila melanogasterMushroom bodiesPerception020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligenceSequence learningbusiness030217 neurology & neurosurgery
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Classes of sum-of-cisoids processes and their statistics for the modeling and simulation of mobile fading channels

2013

Published version of an article in the journal: EURASIP Journal on Wireless Communications and Networking. Also available from the publisher at: http://dx.doi.org/10.1186/1687-1499-2013-125 Open access In this paper, we present a fundamental study on the stationarity and ergodicity of eight classes of sum-of-cisoids (SOC) processes for the modeling and simulation of frequency-nonselective mobile Rayleigh fading channels. The purpose of this study is to determine which classes of SOC models enable the design of channel simulators that accurately reproduce the channel’s statistical properties without demanding information on the time origin or the time-consuming computation of an ensemble ave…

Computer Networks and CommunicationsComputer scienceStochastic processAutocorrelationEnsemble averageErgodicityVDP::Technology: 500::Information and communication technology: 550Computer Science ApplicationsModeling and simulationVDP::Mathematics and natural science: 400::Information and communication science: 420Signal ProcessingStatisticsErgodic theoryFadingCommunication channelRayleigh fadingEURASIP Journal on Wireless Communications and Networking
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Perceptual adaptive insensitivity for support vector machine image coding.

2005

Support vector machine (SVM) learning has been recently proposed for image compression in the frequency domain using a constant epsilon-insensitivity zone by Robinson and Kecman. However, according to the statistical properties of natural images and the properties of human perception, a constant insensitivity makes sense in the spatial domain but it is certainly not a good option in a frequency domain. In fact, in their approach, they made a fixed low-pass assumption as the number of discrete cosine transform (DCT) coefficients to be used in the training was limited. This paper extends the work of Robinson and Kecman by proposing the use of adaptive insensitivity SVMs [2] for image coding u…

Computer Networks and CommunicationsImage processingPattern Recognition AutomatedArtificial IntelligenceDistortionImage Interpretation Computer-AssistedDiscrete cosine transformComputer SimulationMathematicsModels StatisticalArtificial neural networkbusiness.industryPattern recognitionSignal Processing Computer-AssistedGeneral MedicineData CompressionComputer Science ApplicationsSupport vector machineFrequency domainVisual PerceptionA priori and a posterioriArtificial intelligencebusinessSoftwareAlgorithmsImage compressionIEEE transactions on neural networks
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