Search results for "modeling"

showing 10 items of 4489 documents

Internet of Things with Deep Learning-Based Face Recognition Approach for Authentication in Control Medical Systems

2022

Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant role in many applications, including medical and healthcare systems. It can help users in this field get an advantage in terms of enhanced touchless authentication, especially in spreading infectious diseases like coronavirus disease 2019 (COVID-19). Even though there is a number of available security systems, they suffer from one or more of issues, such as identity fraud, loss of keys and passwords, or spreading diseases through touch authentication tools. To overcome these issues, IoT-based intelligent control medical authentication systems using DL models are proposed to enhance the security f…

Support Vector MachineGeneral Immunology and MicrobiologyArticle SubjectDatabases FactualSARS-CoV-2Applied MathematicsAutomated Facial RecognitionInternet of ThingsCOVID-19General MedicineEquipment DesignVDP::Teknologi: 500::Industri- og produktdesign: 640General Biochemistry Genetics and Molecular BiologyPattern Recognition AutomatedDeep LearningVDP::Teknologi: 500::Bioteknologi: 590VDP::Teknologi: 500::Medisinsk teknologi: 620Modeling and SimulationHumansComputer SimulationAlgorithmsComputer Security
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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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An empirical model for free surface energy of strained solids at different temperature regimes.

2006

Abstract We have developed an empirical formulation, based on the elastic theory, to calculate the variation of the surface free energy when a crystal is strained in the elastic regime. The model permits to obtain the variation of the surface energy at different strains and temperatures when are known the thermal dependence on the bulk and surface elastic constants. Molecular dynamics (MD) simulations were performed using the three low index surfaces of Al, to validate the accuracy of the model. The comparison between the empirical model and the MD simulations shows a good agreement for temperatures ranging between 0 and 900 K, and for deformation between −2% and 2%.

Surface (mathematics)ChemistryGeneral Physics and AstronomyThermodynamicsmodelingSurfaces and InterfacesGeneral ChemistryMolecular dynamicsCondensed Matter PhysicsSurface energySurfaces Coatings and FilmsStrain energyCrystalMolecular dynamicsPACS: 68.35.Md; 31.15.Qgsurface energyFree surface[ CHIM.MATE ] Chemical Sciences/Material chemistryThermalStatistical physicsDeformation (engineering)
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Curvilinear constraints for free form deformations on subdivision surfaces

2010

This paper presents a method to deform a subdivision surface with curvilinear constraints. It combines an intuitive free form deformation with a Loop subdivision algorithm. The main advantage of this method of deformation is that it uses only vertices of an object and satisfies the geometrical constraints provided by the user. It permits us to control the final shape of the deformed object, defining the range (i.e. the impact) of the deformation before applying it. The deformation takes into account the Loop properties to follow the subdivision scheme, allowing the user to fix some curvilinear constraints at the subdivision level he works on and to render the final object at the level he wa…

Surface (mathematics)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020101 civil engineering02 engineering and technologyDeformation (meteorology)Topology[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]0201 civil engineeringModelling and Simulation0202 electrical engineering electronic engineering information engineeringSubdivision surfaceComputingMilieux_MISCELLANEOUSComputingMethodologies_COMPUTERGRAPHICSMathematicsSubdivisionCurvilinear coordinatesbusiness.industry020207 software engineering[ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR]Object (computer science)[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]Computer Science ApplicationsRange (mathematics)Modeling and Simulation[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]Free-form deformationbusinessMathematical and Computer Modelling
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On harmonic and biharmonic Bézier surfaces

2004

We present a new method of surface generation from prescribed boundaries based on the elliptic partial differential operators. In particular, we focus on the study of the so-called harmonic and biharmonic Bezier surfaces. The main result we report here is that any biharmonic Bezier surface is fully determined by the boundary control points. We compare the new method, by way of practical examples, with some related methods such as surfaces generation using discretisation masks and functional minimisations.

Surface (mathematics)DiscretizationMathematical analysisAerospace EngineeringBoundary (topology)Harmonic (mathematics)Bézier curveBiharmonic Bézier surfaceTopologyComputer Graphics and Computer-Aided DesignPDE surfaceModeling and SimulationAutomotive EngineeringBiharmonic equationMathematicsComputer Aided Geometric Design
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Hybrid approach to surface roughness evaluation in multistage machining processes

2003

Abstract An assessment of surface quality in turned, ground and honed specimens is made by means of a computer-based processing of digitised surface profiles. Three different methods of surface finish characterisation, i.e. statistical, fractal and neural network-based approaches are examined and compared. Correlations between some representative roughness parameters and the fractal dimension (D) values estimated were found. Consequently, they can be converted to their corresponding roughness parameters, i.e. Ra, Rz and RΔa. Finally, a set of parameters including the minimum surface finish data for machining of external cylindrical surfaces when using complex technological process, is propo…

Surface (mathematics)EngineeringArtificial neural networkbusiness.industryMetals and AlloysProcess (computing)Mechanical engineeringSurface finishFractal dimensionIndustrial and Manufacturing EngineeringComputer Science ApplicationsFractalMachiningModeling and SimulationCeramics and CompositesElectronic engineeringSurface roughnessbusinessJournal of Materials Processing Technology
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Adsorption of organic compounds at the surface of Enceladus' ice grains. A grand canonical Monte Carlo simulation study

2021

International audience; In this paper, we characterise the adsorption of ethylene, propanol and hexanal molecules on crystalline ice by grand canonical Monte Carlo simulations performed at 236 K, a temperature which is typical of some Enceladus’ environments. We show that at low coverage of the ice surface, the adsorption of propanol and hexanal is driven by the interaction of these molecules with the ice phase and, as a consequence, the adsorbed molecules lie more or less parallel to the ice surface. On the other hand, upon saturation, the adsorbate–adsorbate interactions become more and more important and the molecules tend to become tilted with respect to the surface, the aliphatic chain…

Surface (mathematics)EthyleneMaterials scienceGeneral Chemical EngineeringiceThermodynamics02 engineering and technology01 natural sciencesHexanalPropanolCondensed Matter::Materials Sciencechemistry.chemical_compoundEnceladusAdsorptiontrace gases0103 physical sciencesPhysics::Atomic and Molecular ClustersMoleculeGeneral Materials SciencePhysics::Chemical PhysicsEnceladus[PHYS]Physics [physics]010304 chemical physicsGeneral Chemistry021001 nanoscience & nanotechnologyCondensed Matter PhysicssimulationTrace gasCondensed Matter::Soft Condensed Matterchemistry13. Climate actionadsorption[SDU]Sciences of the Universe [physics]Modeling and SimulationAstrophysics::Earth and Planetary Astrophysics0210 nano-technology[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]Information Systems
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A general 4th-order PDE method to generate Bézier surfaces from the boundary

2006

In this paper we present a method for generating Bezier surfaces from the boundary information based on a general 4th-order PDE. This is a generalisation of our previous work on harmonic and biharmonic Bezier surfaces whereby we studied the Bezier solutions for Laplace and the standard biharmonic equation, respectively. Here we study the Bezier solutions of the Euler-Lagrange equation associated with the most general quadratic functional. We show that there is a large class of fourth-order operators for which Bezier solutions exist and hence we show that such operators can be utilised to generate Bezier surfaces from the boundary information. As part of this work we present a general method…

Surface (mathematics)Partial differential equationAerospace EngineeringBoundary (topology)Harmonic (mathematics)Bézier curveTopologyComputer Graphics and Computer-Aided DesignEuler–Lagrange equationPDE surfaceComputer Science::GraphicsModeling and SimulationAutomotive EngineeringBiharmonic equationApplied mathematicsMathematicsComputer Aided Geometric Design
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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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