Search results for "gradient"

showing 10 items of 725 documents

A gradient elasticity theory for second-grade materials and higher order inertia

2012

Abstract Second-grade elastic materials featured by a free energy depending on the strain and the strain gradient, and a kinetic energy depending on the velocity and the velocity gradient, are addressed. An inertial energy balance principle and a virtual work principle for inertial actions are envisioned to enrich the set of traditional theoretical tools of thermodynamics and continuum mechanics. The state variables include the body momentum and the surface momentum, related to the velocity in a nonstandard way, as well as the concomitant mass-accelerations and inertial forces, which do intervene into the motion equations and into the force boundary conditions. The boundary traction is the …

Angular momentummedia_common.quotation_subjectTraction (engineering)Continuum thermodynamicsInertiaMaterials Science(all)Modelling and SimulationWave dispersionGeneral Materials ScienceVirtual workBoundary value problemmedia_commonMathematicsContinuum mechanicsForce densityMechanical EngineeringApplied MathematicsMathematical analysisEquations of motionCondensed Matter PhysicsDynamicsGradient elasticityClassical mechanicsHigher order inertiaMechanics of MaterialsModeling and SimulationInternational Journal of Solids and Structures
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Electromagnetic Sensitivity Analysis and Shape Optimization Using Method of Moments and Automatic Differentiation

2009

Sensitivity analysis is an important part of gradient-based optimization of electromagnetic devices. We demonstrate how sensitivity analysis can be incorporated into an existing in-house method of moments solver with a relatively small amount of labor by using a technique called automatic differentiation (AD). This approach enables us to obtain (geometrical) sensitivities of the discrete solution with accuracy up to numerical precision. We compare the assembly time and memory usage of the modified and original solvers. Moreover, we optimize the shape of a dipole antenna and the dimensions of a Yagi-Uda array using the presented AD technique, traditional response level finite difference sens…

Antenna arrayMathematical optimizationAutomatic differentiationFinite difference methodShape optimizationSensitivity (control systems)Electrical and Electronic EngineeringMethod of moments (statistics)SolverAlgorithmGradient methodMathematicsIEEE Transactions on Antennas and Propagation
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Stress concentration for closely located inclusions in nonlinear perfect conductivity problems

2019

We study the stress concentration, which is the gradient of the solution, when two smooth inclusions are closely located in a possibly anisotropic medium. The governing equation may be degenerate of $p-$Laplace type, with $1<p \leq N$. We prove optimal $L^\infty$ estimates for the blow-up of the gradient of the solution as the distance between the inclusions tends to zero.

Applied Mathematics010102 general mathematicsMathematical analysisDegenerate energy levelsZero (complex analysis)Perfect conductorAnalysiGradient blow-upType (model theory)Conductivity01 natural sciences010101 applied mathematicsNonlinear systemMathematics - Analysis of PDEsFOS: MathematicsFinsler p-Laplacian0101 mathematicsPerfect conductorAnisotropy35J25 35B44 35B50 (Primary) 35J62 78A48 58J60 (Secondary)AnalysisAnalysis of PDEs (math.AP)MathematicsStress concentration
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On a global superconvergence of the gradient of linear triangular elements

1987

Abstract We study a simple superconvergent scheme which recovers the gradient when solving a second-order elliptic problem in the plane by the usual linear elements. The recovered gradient globally approximates the true gradient even by one order of accuracy higher in the L 2 -norm than the piecewise constant gradient of the Ritz—Galerkin solution. A superconvergent approximation to the boundary flux is presented as well.

Applied MathematicsMathematical analysisOrder of accuracySuperconvergenceglobal superconvergence for the gradientComputer Science::Numerical AnalysisGlobal superconvergence for the gradientMathematics::Numerical AnalysisNonlinear conjugate gradient methodElliptic curveComputational Mathematicserror estimatesNorm (mathematics)boundary fluxPiecewisepost-processing of the Ritz—Galerkin schemeGradient descentGradient methodMathematicsJournal of Computational and Applied Mathematics
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Facilitated SLM extraction of peptides with D2EHPA as a carrier

2004

Abstract The extraction of short peptides through a supported liquid membrane containing di-2-(ethylhexyl)phosphoric acid (D2EHPA) as a carrier was investigated. The extraction was carried out from the aqueous donor phase with pH 3 to amore acidic acceptor phase. The proton gradient between the donor and the acceptor phase was the main driving force of the mass transfer in this system. The influence of various parameters such as diluent of the carrier, pH of the donor and acceptor phase, peptide structure and concentration on the extraction efficiency was presented.

Aqueous solutionChromatographyChemistryMechanical EngineeringGeneral Chemical EngineeringInorganic chemistryExtraction (chemistry)General ChemistryD2EHPAAcceptorDiluentchemistry.chemical_compoundMembranePhase (matter)peptidesextractionGeneral Materials Sciencesupported liquid membraneElectrochemical gradientPhosphoric acidWater Science and TechnologyDesalination
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Study of uniformity of plasmas produced in a wall-stabilized arc

2003

In this contribution the plasma of an arc discharge in a mixture of helium and argon is studied. The gas mixture is introduced uniformly along the arc column between each of the stabilizing plates. From the measured lateral distribution of radiation (HeI, HI, ArI, ArII, NI, FI line intensity and width measurements), after Abel inversion, the radial temperature distributions were obtained at various positions of the arc column. Beside the expected radial temperature gradients, a distinct temperature gradient along the arc column was found.

ArgonMaterials sciencechemistry.chemical_elementPlasmaRadiationCondensed Matter PhysicsElectric arcTemperature gradientPlasma arc weldingchemistryPlasma diagnosticsAtomic physicsAstrophysics::Galaxy AstrophysicsHeliumContributions to Plasma Physics
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DeepEva: A deep neural network architecture for assessing sentence complexity in Italian and English languages

2021

Abstract Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of the text complexity evaluation, that is the study of the text-linguistic features (e.g., lexical, syntactical, morphological) to measure the grade of comprehensibility of a text. ATE can affect positively several different contexts such as Finance, Health, and Education. Moreover, it can support the research on Automatic Text Simplification (ATS), a research area that deals with the study of new methods for transforming a text by changing its lexicon and structure to meet specific reader needs. In this paper, we illustrate an ATE approach named De…

Artificial intelligenceComputer engineering. Computer hardwareText simplificationComputer scienceText simplificationcomputer.software_genreLexiconAutomatic-text-complexity-evaluationDeep-learningField (computer science)TK7885-7895Automatic text copmplexity evaluationText-complexity-assessmentText complexity assessmentStructure (mathematical logic)Settore INF/01 - InformaticaText-simplificationbusiness.industryDeep learningNatural language processingNatural-language-processingDeep learningGeneral MedicineQA75.5-76.95Artificial-intelligenceSupport vector machineElectronic computers. Computer scienceGradient boostingArtificial intelligencebusinesscomputerSentenceNatural language processingArray
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A new method for optimal synthesis of wavelet-based neural networks suitable for identification purposes

1999

Abstract This paper deals with a new method for optimal synthesis of Wavelet-Based Neural Networks (WBNN) suitable for identification purposes. The method uses a genetic algorithm (GA) combined with a steepest descent technique and least square techniques for both optimal selection of the structure of the WBNN and its training. The method is applied for designing a predictor for a chaotic temporal series

Artificial neural networkSeries (mathematics)Computer sciencebusiness.industryMathematicsofComputing_NUMERICALANALYSISChaoticPattern recognitionMachine learningcomputer.software_genreLeast squaresIdentification (information)WaveletGenetic algorithmArtificial intelligencebusinessGradient descentcomputerSelection (genetic algorithm)IFAC Proceedings Volumes
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Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators

2021

One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…

Artificial neural networks; Chaotic oscillators; Granger causality; Multivariate time series analysis; Network physiology; Penalized regression techniques; Remote synchronization; State-space models; Stochastic gradient descent L1; Vector autoregressive modelGeneral Computer ScienceDynamical systems theoryComputer science02 engineering and technologyChaotic oscillatorsPenalized regression techniquesNetwork topologySettore ING-INF/01 - ElettronicaMultivariate time series analysisVector autoregression03 medical and health sciences0302 clinical medicineScientific Computing and Simulation0202 electrical engineering electronic engineering information engineeringRepresentation (mathematics)Optimization Theory and ComputationNetwork physiologyState-space modelsArtificial neural networkArtificial neural networksData ScienceTheory and Formal MethodsQA75.5-76.95Stochastic gradient descent L1Granger causality State-space models Vector autoregressive model Artificial neural networks Stochastic gradient descent L1 Multivariate time series analysis Network physiology Remote synchronization Chaotic oscillators Penalized regression techniquesRemote synchronizationStochastic gradient descentAutoregressive modelAlgorithms and Analysis of AlgorithmsVector autoregressive modelElectronic computers. Computer scienceSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causality020201 artificial intelligence & image processingGradient descentAlgorithm030217 neurology & neurosurgeryPeerJ Computer Science
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Discontinuous Gradient Constraints and the Infinity Laplacian

2012

Motivated by tug-of-war games and asymptotic analysis of certain variational problems, we consider a gradient constraint problem involving the infinity Laplace operator. We prove that this problem always has a solution that is unique if a certain regularity condition on the constraint is satisfied. If this regularity condition fails, then solutions obtained from game theory and $L^p$-approximation need not coincide.

Asymptotic analysisGeneral Mathematicsta111010102 general mathematicsMathematical analysisinfinity Laplace operator01 natural sciences010101 applied mathematicsConstraint (information theory)Mathematics - Analysis of PDEsOperator (computer programming)Infinity LaplacianFOS: Mathematics0101 mathematicsGame theorygradient constraint problemsAnalysis of PDEs (math.AP)MathematicsInternational Mathematics Research Notices
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