Search results for "Computational Engineering"

showing 10 items of 60 documents

Efficient formulation of a two-noded geometrically exact curved beam element

2021

The article extends the formulation of a 2D geometrically exact beam element proposed by Jirasek et al. (2021) to curved elastic beams. This formulation is based on equilibrium equations in their integrated form, combined with the kinematic relations and sectional equations that link the internal forces to sectional deformation variables. The resulting first-order differential equations are approximated by the finite difference scheme and the boundary value problem is converted to an initial value problem using the shooting method. The article develops the theoretical framework based on the Navier-Bernoulli hypothesis, with a possible extension to shear-flexible beams. Numerical procedures …

Computational Engineering Finance and Science (cs.CE)FOS: Computer and information sciencesNumerical Analysiscurved beam geometrically exact nonlinear beam Kirchhoff beam large rotations planar frame shooting methodApplied MathematicsGeneral EngineeringComputer Science - Computational Engineering Finance and ScienceSettore ICAR/08 - Scienza Delle Costruzioni
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"Table 7" of "Search for supersymmetry with jets, missing transverse momentum and at least one hadronically decaying $\tau$ lepton in proton-proton c…

2012

The observed CLS values in the Lambda and tan(beta) plane. Note that bins with zero content in both Lambda abd Tan(Beta) have been omitted.

Condensed Matter::Quantum GasesProton-Proton ScatteringComputer Science::Computational Engineering Finance and ScienceHigh Energy Physics::PhenomenologySUSYHigh Energy Physics::ExperimentSupersymmetryJet Production
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Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance

2009

The main purpose of this paper is to present a theoretically sound portfolio performance measure that takes into account higher moments of the distribution of returns. First, we perform a study of the investor's preferences to higher moments of distribution within expected utility theory and discuss the performance measurement. To illustrate the investor's preferences to higher moments and the computation of a performance measure, we provide an approximation analysis of the optimal capital allocation problem and derive a formula for the Sharpe ratio adjusted for skewness of distribution. This performance measure justifies the notion of the Generalized Sharpe Ratio (GSR) introduced by Hodges…

Economics and EconometricsSharpe ratioNonparametric statisticsVariance (accounting)Measure (mathematics)Normal-inverse Gaussian distributionModigliani risk-adjusted performanceSkewnessComputer Science::Computational Engineering Finance and ScienceEconomicsKurtosisEconometricsPortfolioFinanceExpected utility hypothesisMathematicsParametric statisticsJournal of Banking & Finance
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Evaluation of infilled frames: an updated in-plane-stiffness macro-model considering the effects of vertical loads

2015

The influence of masonry infills on the in-plane behaviour of RC framed structures is a central topic in the seismic evaluation and retrofitting of existing buildings. Many models in the literature use an equivalent strut member in order to represent the infill but, among the parameters influencing the equivalent strut behaviour, the effect of vertical loads acting on the frames is recognized but not quantified. Nevertheless a vertical load causes a non-negligible variation in the in-plane behaviour of infilled frames by influencing the effective volume of the infill. This results in a change in the stiffness and strength of the system. This paper presents an equivalent diagonal pin-jointed…

EngineeringEquivalent diagonal pin-jointed strut modelInfilled framesDiagonalIn-plane behaviourInfilled frames In-plane behaviour Equivalent diagonal pin-jointed strutmodel Vertical load influenceVertical load influenceComputer Science::Computational Engineering Finance and SciencemedicineInfillRetrofittingGeotechnical engineeringMacroCivil and Structural Engineeringmodelbusiness.industryStiffnessStructural engineeringBuilding and ConstructionMasonryGeotechnical Engineering and Engineering GeologyEquivalent diagonal pin-jointed strutFinite element methodStiffeningSettore ICAR/09 - Tecnica Delle CostruzioniGeophysicsmedicine.symptombusinessInfilled frame
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Group Importance Sampling for particle filtering and MCMC

2018

Bayesian methods and their implementations by means of sophisticated Monte Carlo techniques have become very popular in signal processing over the last years. Importance Sampling (IS) is a well-known Monte Carlo technique that approximates integrals involving a posterior distribution by means of weighted samples. In this work, we study the assignation of a single weighted sample which compresses the information contained in a population of weighted samples. Part of the theory that we present as Group Importance Sampling (GIS) has been employed implicitly in different works in the literature. The provided analysis yields several theoretical and practical consequences. For instance, we discus…

FOS: Computer and information sciencesComputer Science - Machine LearningComputer sciencePosterior probabilityMonte Carlo methodMachine Learning (stat.ML)02 engineering and technologyMultiple-try MetropolisStatistics - Computation01 natural sciencesMachine Learning (cs.LG)Computational Engineering Finance and Science (cs.CE)Methodology (stat.ME)010104 statistics & probabilitysymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingStatistics - Machine LearningArtificial IntelligenceResampling0202 electrical engineering electronic engineering information engineering0101 mathematicsElectrical and Electronic EngineeringComputer Science - Computational Engineering Finance and ScienceStatistics - MethodologyComputation (stat.CO)ComputingMilieux_MISCELLANEOUSMarkov chainApplied Mathematics020206 networking & telecommunicationsMarkov chain Monte CarloStatistics::ComputationComputational Theory and MathematicsSignal ProcessingsymbolsComputer Vision and Pattern RecognitionStatistics Probability and UncertaintyParticle filter[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmImportance samplingDigital Signal Processing
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Semantics of UML 2.0 Activity Diagram for Business Modeling by Means of Virtual Machine

2005

The paper proposes a more formalized definition of UML 2.0 Activity Diagram semantics. A subset of activity diagram constructs relevant for business process modeling is considered. The semantics definition is based on the original token flow methodology, but a more constructive approach is used. The Activity Diagram Virtual machine is defined by means of a metamodel, with operations defined by a mix of pseudocode and OCL pre- and postconditions. A formal procedure is described which builds the virtual machine for any activity diagram. The relatively complicated original token movement rules in control nodes and edges are combined into paths from an action to action. A new approach is the us…

FOS: Computer and information sciencesComputer Science - Programming LanguagesSemantics (computer science)Computer scienceProgramming languageActivity diagramBusiness process modelingSecurity tokencomputer.software_genreMetamodelingComputational Engineering Finance and Science (cs.CE)Unified Modeling LanguageVirtual machineComputer Science - Computational Engineering Finance and SciencePseudocodecomputercomputer.programming_languageProgramming Languages (cs.PL)
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A Two-Stage Reconstruction of Microstructures with Arbitrarily Shaped Inclusions

2020

The main goal of our research is to develop an effective method with a wide range of applications for the statistical reconstruction of heterogeneous microstructures with compact inclusions of any shape, such as highly irregular grains. The devised approach uses multi-scale extended entropic descriptors (ED) that quantify the degree of spatial non-uniformity of configurations of finite-sized objects. This technique is an innovative development of previously elaborated entropy methods for statistical reconstruction. Here, we discuss the two-dimensional case, but this method can be generalized into three dimensions. At the first stage, the developed procedure creates a set of black synthetic …

FOS: Computer and information sciencesComputer science02 engineering and technologylcsh:Technology01 natural sciencesArticleComputational Engineering Finance and Science (cs.CE)0103 physical sciencesCluster (physics)Effective methodGeneral Materials ScienceComputer Science - Computational Engineering Finance and Sciencelcsh:Microscopy010306 general physicslcsh:QC120-168.85lcsh:QH201-278.5Pixellcsh:Tmulti-scale entropic descriptorsrandom heterogeneous materials021001 nanoscience & nanotechnologyMicrostructureStandard techniqueCement pastetwo-stage reconstructionlcsh:TA1-2040simulated annealing for clustersSimulated annealinglcsh:Descriptive and experimental mechanicslcsh:Electrical engineering. Electronics. Nuclear engineeringlcsh:Engineering (General). Civil engineering (General)0210 nano-technologylcsh:TK1-9971AlgorithmMaterials
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Compressed Particle Methods for Expensive Models With Application in Astronomy and Remote Sensing

2021

In many inference problems, the evaluation of complex and costly models is often required. In this context, Bayesian methods have become very popular in several fields over the last years, in order to obtain parameter inversion, model selection or uncertainty quantification. Bayesian inference requires the approximation of complicated integrals involving (often costly) posterior distributions. Generally, this approximation is obtained by means of Monte Carlo (MC) methods. In order to reduce the computational cost of the corresponding technique, surrogate models (also called emulators) are often employed. Another alternative approach is the so-called Approximate Bayesian Computation (ABC) sc…

FOS: Computer and information sciencesComputer scienceAstronomyModel selectionBayesian inferenceMonte Carlo methodBayesian probabilityAerospace EngineeringAstronomyInferenceMachine Learning (stat.ML)Context (language use)Bayesian inferenceStatistics - ComputationComputational Engineering Finance and Science (cs.CE)remote sensingimportance samplingStatistics - Machine Learningnumerical inversionparticle filteringElectrical and Electronic EngineeringUncertainty quantificationApproximate Bayesian computationComputer Science - Computational Engineering Finance and ScienceComputation (stat.CO)IEEE Transactions on Aerospace and Electronic Systems
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Diffusion map for clustering fMRI spatial maps extracted by Indipendent Component Analysis

2013

Functional magnetic resonance imaging (fMRI) produces data about activity inside the brain, from which spatial maps can be extracted by independent component analysis (ICA). In datasets, there are n spatial maps that contain p voxels. The number of voxels is very high compared to the number of analyzed spatial maps. Clustering of the spatial maps is usually based on correlation matrices. This usually works well, although such a similarity matrix inherently can explain only a certain amount of the total variance contained in the high-dimensional data where n is relatively small but p is large. For high-dimensional space, it is reasonable to perform dimensionality reduction before clustering.…

FOS: Computer and information sciencesDiffusion (acoustics)Computer sciencediffusion mapMachine Learning (stat.ML)02 engineering and technologycomputer.software_genreMachine Learning (cs.LG)Computational Engineering Finance and Science (cs.CE)Correlation03 medical and health sciencesTotal variation0302 clinical medicineStatistics - Machine LearningVoxel0202 electrical engineering electronic engineering information engineeringComputer Science - Computational Engineering Finance and ScienceCluster analysisdimensionality reductionta113spatial mapsbusiness.industryDimensionality reductionfunctional magnetic resonance imaging (fMRI)Pattern recognitionIndependent component analysisSpectral clusteringComputer Science - Learningindependent component analysista6131020201 artificial intelligence & image processingArtificial intelligenceDYNAMICAL-SYSTEMSbusinesscomputer030217 neurology & neurosurgeryclustering
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Reliability analysis of processes with moving cracked material

2015

Abstract The reliability of processes with moving elastic and isotropic material containing initial cracks is considered in terms of fracture. The material is modelled as a moving plate which is simply supported from two of its sides and subjected to homogeneous tension acting in the travelling direction. For tension, two models are studied: (i) tension is constant with respect to time, and (ii) tension varies temporally according to an Ornstein–Uhlenbeck process. Cracks of random length are assumed to occur in the material according to a stochastic counting process. For a general counting process, a representation of the nonfracture probability of the system is obtained that exploits condi…

FOS: Computer and information sciencesStochastic modellingBoundary (topology)02 engineering and technologyComputational Engineering Finance and Science (cs.CE)0203 mechanical engineeringfirst passage timeComputer Science - Computational Engineering Finance and Sciencestochastic modelMathematics040101 forestryta214Counting processTension (physics)Applied Mathematicsta111Mathematical analysisIsotropyOrnstein–Uhlenbeck process04 agricultural and veterinary sciencesmoving material020303 mechanical engineering & transportsfractureModeling and Simulation0401 agriculture forestry and fisheriesOrnstein-Uhlenbeck processFirst-hitting-time modelConstant (mathematics)Applied Mathematical Modelling
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