Search results for "Computer simulation"

showing 10 items of 1054 documents

Artificial organisms as tools for the development of psychological theory: Tolman's lesson

2007

In the 1930s and 1940s, Edward Tolman developed a psychological theory of spatial orientation in rats and humans. He expressed his theory as an automaton (the ‘‘schematic sowbug’’) or what today we would call an ‘‘artificial organism.’’ With the technology of the day, he could not implement his model. Nonetheless, he used it to develop empirical predictions which tested with animals in the laboratory. This way of proceeding was in line with scientific practice dating back to Galileo. The way psychologists use artificial organisms in their work today breaks with this tradition. Modern ‘‘artificial organisms’’ are constructed a posteriori, working from experimental or ethological observations…

Cognitive modelSettore M-PSI/01 - Psicologia GeneraleComputer scienceCognitive NeuroscienceSpatial BehaviorExperimental and Cognitive Psychologysymbols.namesakeArtificial IntelligenceOrientationArtificial organisms Cognitive modeling Schematic sowbug Tolman's theoryPsychological TheoryGalileo (satellite navigation)AnimalsLearningSchematic sowbug Cognitive modeling Artificial organisms Tolman’s theoryComputer Simulationbusiness.industrySchematicGeneral MedicineRoboticsHistory 20th CenturyModels TheoreticalTrial and errorAutomatonRatsSpace PerceptionsymbolsA priori and a posterioriRobotArtificial intelligencebusinessPsychological Theory
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FlyMove – a new way to look at development of Drosophila

2003

Development of any organism requires a complex interplay of genes to orchestrate the many movements needed to build up an embryo. Previously, work on Drosophila melanogaster has provided important insights that are often applicable in other systems. But developmental processes, which take place in space and time, are difficult to convey in textbooks. Here, we introduce FlyMove (http://flymove.uni-muenster.de), a new database combining movies, animated schemata, interactive "modules" and pictures that will greatly facilitate the understanding of Drosophila development.

Cognitive scienceanimal structuresDatabases FactualbiologyComputational BiologyGenes Insectbiology.organism_classificationBioinformaticsDrosophila melanogasterComputingMethodologies_PATTERNRECOGNITIONDevelopment (topology)Gene Expression RegulationMorphogenesisGeneticsAnimalsComputer SimulationFemaleDrosophila melanogasterDrosophilaOrganismTrends in Genetics
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Flow properties and hydrodynamic interactions of rigid spherical microswimmers.

2017

We analyze a minimal model for a rigid spherical microswimmer and explore the consequences of its extended surface on the interplay between its self-propulsion and flow properties. The model is the first order representation of microswimmers, such as bacteria and algae, with rigid bodies and flexible propelling appendages. The flow field of such a microswimmer at finite distances significantly differs from that of a point-force (Stokeslet) dipole. For a suspension of microswimmers, we derive the grand mobility matrix that connects the motion of an individual swimmer to the active and passive forces and torques acting on all the swimmers. Our investigation of the mobility tensors reveals tha…

Collective behaviorStokesian dynamicsMovementFOS: Physical sciencesCondensed Matter - Soft Condensed MatterBacterial Physiological Phenomena01 natural sciencesQuantitative Biology::OtherModels Biological010305 fluids & plasmasQuantitative Biology::Cell Behavior0103 physical sciencesComputer SimulationPhysics - Biological Physics010306 general physicsSuspension (vehicle)Plant Physiological PhenomenaPhysicsPhysics::Biological PhysicsFluid Dynamics (physics.flu-dyn)EukaryotaPhysics - Fluid DynamicsFirst orderFlow fieldDipoleClassical mechanicsBiological Physics (physics.bio-ph)HydrodynamicsSoft Condensed Matter (cond-mat.soft)Flow propertiesPhysical review. E
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Dynamics of two competing species in the presence of Lévy noise sources

2010

We consider a Lotka-Volterra system of two competing species subject to multiplicative alpha-stable Lévy noise. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence both of a periodic driving term and an additive alpha-stable Lévy noise. We study the species dynamics, which is characterized by two different regimes, exclusion of one species and coexistence of both. We find quasi-periodic oscillations and stochastic resonance phenomenon in the dynamics of the competing species, analysing the role of the Lévy noise sources.

Competitive BehaviorComplex systemsBistabilityStochastic resonancePopulation DynamicsComplex systemModels BiologicalStochastic differential equationControl theoryQuantitative Biology::Populations and EvolutionAnimalsHumansComputer SimulationStatistical physicsEcosystemMathematicsPopulation dynamics and ecological pattern formationModels StatisticalStochastic processDynamics (mechanics)Multiplicative functionStochastic analysis methods (Fokker-Planck Langevin etc.)Adaptation PhysiologicalRandom walks and Lévy flightQuasiperiodic functionPredatory Behavior
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The effect of geometrical parameters on the discharge capacity of meandering compound channels

2008

A number of methods and formulae has been proposed in the literature to estimate the discharge capacity of compound channels. When the main channel has a meandering pattern, a reduction in the conveyance capacity for a given stage is observed, which is due to the energy dissipations caused by the development of strong secondary currents and to the decrease of the main channel bed slope with respect to the valley bed slope. The discharges in meandering compound channels are usually assessed applying, with some adjustments, the same methods used in the straight compound channels. Specifically, the sinuosity of the main channel is frequently introduced to account for its meandering pattern, al…

Compound channels Meanders Sinuosity Stage—discharge curves Numerical simulationHydrologyMean curvatureComputer simulationTurbulenceGeometrySinuosityRadiusDissipationSettore ICAR/01 - IdraulicaReynolds-averaged Navier–Stokes equationsGeologyComputer Science::Information TheoryWater Science and TechnologyCommunication channelAdvances in Water Resources
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The Economic Impact of Restricted Water Supply: a Computable General Equilibrium Analysis

2007

Water problems are typically studied at the level of the river catchment. About 70% of all water is used for agriculture, and agricultural products are traded internationally. A full understanding of water use is impossible without understanding the international market for food and related products, such as textiles. The water embedded in commodities is called virtual water. Based on a general equilibrium model, we offer a method for investigating the role of water resources and water scarcity in the context of international trade. We run five alternative scenarios, analyzing the effects of water scarcity due to reduced availability of groundwater. This can be a consequence of physical con…

Computable general equilibriumEnvironmental EngineeringWater scarcityNatural resource economicsWater supplyInternational trade and waterSustainable water supply/dk/atira/pure/sustainabledevelopmentgoals/clean_water_and_sanitationWater scarcityFLOWSWater SupplyIRRIGATIONEconomicsComputer Simulationjel:Q25Waste Management and Disposaljel:Q28Water Science and TechnologyCivil and Structural EngineeringComputable General Equilibrium Sustainable Water Supply Virtual Water Water Scarcitybusiness.industryEcological ModelingVirtual waterEnvironmental engineeringAgricultureComputable general equilibriumPollutionTRADEjel:D58Water resourcesModels EconomicPlus:VIRTUAL WATERVirtual waterDESALINATIONAllocative efficiencybusinessSDG 6 - Clean Water and SanitationWater use
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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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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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Upport vector machines for nonlinear kernel ARMA system identification.

2006

Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…

Computer Science::Machine LearningStatistics::TheoryComputer Networks and CommunicationsBiomedical signal processingInformation Storage and RetrievalMachine learningcomputer.software_genrePattern Recognition AutomatedStatistics::Machine LearningArtificial IntelligenceApplied mathematicsStatistics::MethodologyAutoregressive–moving-average modelComputer SimulationMathematicsTelecomunicacionesHardware_MEMORYSTRUCTURESSupport vector machinesModels StatisticalNonlinear system identificationbusiness.industryAutocorrelationSystem identificationSignal Processing Computer-AssistedGeneral MedicineComputer Science ApplicationsSupport vector machineNonlinear systemKernelAutoregressive modelNonlinear DynamicsARMA modelling3325 Tecnología de las TelecomunicacionesArtificial intelligenceNeural Networks ComputerbusinesscomputerSoftwareAlgorithmsReproducing kernel Hilbert spaceIEEE transactions on neural networks
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