Search results for "Information Science"

showing 10 items of 3627 documents

Seam Puckering Objective Evaluation Method for Sewing Process

2015

The paper presents an automated method for the assessment and classification of puckering defects detected during the preproduction control stage of the sewing machine or product inspection. In this respect, we have presented the possible causes and remedies of the wrinkle nonconformities. Subjective factors related to the control environment and operators during the seams evaluation can be reduced using an automated system whose operation is based on image processing. Our implementation involves spectral image analysis using Fourier transform and an unsupervised neural network, the Kohonen Map, employed to classify material specimens, the input images, into five discrete degrees of quality…

Computational Engineering Finance and Science (cs.CE)FOS: Computer and information sciencesComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputer Science - Computational Engineering Finance and Science
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Reduced Order Models for Pricing European and American Options under Stochastic Volatility and Jump-Diffusion Models

2016

European options can be priced by solving parabolic partial(-integro) differential equations under stochastic volatility and jump-diffusion models like the Heston, Merton, and Bates models. American option prices can be obtained by solving linear complementary problems (LCPs) with the same operators. A finite difference discretization leads to a so-called full order model (FOM). Reduced order models (ROMs) are derived employing proper orthogonal decomposition (POD). The early exercise constraint of American options is enforced by a penalty on subset of grid points. The presented numerical experiments demonstrate that pricing with ROMs can be orders of magnitude faster within a given model p…

Computational Engineering Finance and Science (cs.CE)FOS: Computer and information sciencesFOS: Economics and businessQuantitative Finance - Computational FinanceEuropean optionlinear complementary problemComputational Finance (q-fin.CP)reduced order modelAmerican optionComputer Science - Computational Engineering Finance and Scienceoption pricing
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Modeling Business

2003

Business concepts are studied using a metamodel-based approach, using UML 2.0. The Notation Independent Business concepts metamodel is introduced. The approach offers a mapping between different business modeling notations which could be used for bridging BM tools and boosting the MDA approach.

Computational Engineering Finance and Science (cs.CE)FOS: Computer and information sciencesJ.1Software_SOFTWAREENGINEERINGI.6.5Computer Science - Computational Engineering Finance and ScienceI.6.5; J.1
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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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Approximation of functions over manifolds : A Moving Least-Squares approach

2021

We present an algorithm for approximating a function defined over a $d$-dimensional manifold utilizing only noisy function values at locations sampled from the manifold with noise. To produce the approximation we do not require any knowledge regarding the manifold other than its dimension $d$. We use the Manifold Moving Least-Squares approach of (Sober and Levin 2016) to reconstruct the atlas of charts and the approximation is built on-top of those charts. The resulting approximant is shown to be a function defined over a neighborhood of a manifold, approximating the originally sampled manifold. In other words, given a new point, located near the manifold, the approximation can be evaluated…

Computational Geometry (cs.CG)FOS: Computer and information sciencesComputer Science - Machine LearningClosed manifolddimension reductionMachine Learning (stat.ML)010103 numerical & computational mathematicsComplex dimensionTopology01 natural sciencesMachine Learning (cs.LG)Volume formComputer Science - GraphicsStatistics - Machine Learningmanifold learningApplied mathematics0101 mathematicsfunktiotMathematicsManifold alignmentAtlas (topology)Applied Mathematicshigh dimensional approximationManifoldGraphics (cs.GR)Statistical manifold010101 applied mathematicsregression over manifoldsComputational Mathematicsout-of-sample extensionComputer Science - Computational Geometrynumeerinen analyysimonistotapproksimointimoving least-squaresCenter manifold
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Fully Automatic Trunk Packing with Free Placements

2010

We present a new algorithm to compute the volume of a trunk according to the SAE J1100 standard. Our new algorithm uses state-of-the-art methods from computational geometry and from combinatorial optimization. It finds better solutions than previous approaches for small trunks.

Computational Geometry (cs.CG)FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSComputer Science - Data Structures and AlgorithmsComputer Science - Computational GeometryData Structures and Algorithms (cs.DS)Computer Science - Discrete Mathematics
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Topology-based goodness-of-fit tests for sliced spatial data

2023

In materials science and many other application domains, 3D information can often only be extrapolated by taking 2D slices. In topological data analysis, persistence vineyards have emerged as a powerful tool to take into account topological features stretching over several slices. In the present paper, we illustrate how persistence vineyards can be used to design rigorous statistical hypothesis tests for 3D microstructure models based on data from 2D slices. More precisely, by establishing the asymptotic normality of suitable longitudinal and cross-sectional summary statistics, we devise goodness-of-fit tests that become asymptotically exact in large sampling windows. We illustrate the test…

Computational Geometry (cs.CG)FOS: Computer and information sciencesStatistics and ProbabilityGoodness-of-fit testsApplied MathematicsTopological data analysisPersistence diagramMathematics - Statistics TheoryStatistics Theory (math.ST)VineyardsMaterials scienceComputational MathematicsComputational Theory and Mathematics60F05Topological data analysis Persistence diagram Materials science Vineyards Goodness-of-fit tests Asymptotic normalityFOS: MathematicsAlgebraic Topology (math.AT)Computer Science - Computational GeometryAsymptotic normalityMathematics - Algebraic TopologyComputational Statistics & Data Analysis
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On the reducibility of geometric constraint graphs

2018

Geometric modeling by constraints, whose applications are of interest to communities from various fields such as mechanical engineering, computer aided design, symbolic computation or molecular chemistry, is now integrated into standard modeling tools. In this discipline, a geometric form is specified by the relations that the components of this form must verify instead of explicitly specifying these components. The purpose of the resolution is to deduce the form satisfying all these constraints. Various methods have been proposed to solve this problem. We will focus on the so-called graph-based or graph-based methods with application to the two-dimensional space.

Computational Geometry (cs.CG)FOS: Computer and information sciences[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]Computer Science - Computational Geometry[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]
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Optimal rates of convergence for persistence diagrams in Topological Data Analysis

2013

Computational topology has recently known an important development toward data analysis, giving birth to the field of topological data analysis. Topological persistence, or persistent homology, appears as a fundamental tool in this field. In this paper, we study topological persistence in general metric spaces, with a statistical approach. We show that the use of persistent homology can be naturally considered in general statistical frameworks and persistence diagrams can be used as statistics with interesting convergence properties. Some numerical experiments are performed in various contexts to illustrate our results.

Computational Geometry (cs.CG)FOS: Computer and information sciences[ MATH.MATH-GT ] Mathematics [math]/Geometric Topology [math.GT][STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]Topological Data analysis Persistent homology minimax convergence rates geometric complexes metric spacesGeometric Topology (math.GT)Mathematics - Statistics TheoryStatistics Theory (math.ST)[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG][STAT.TH]Statistics [stat]/Statistics Theory [stat.TH][INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG][ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH][ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG]Machine Learning (cs.LG)Computer Science - LearningMathematics - Geometric Topology[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG][INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][MATH.MATH-GT]Mathematics [math]/Geometric Topology [math.GT]FOS: Mathematics[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]Computer Science - Computational Geometry[MATH.MATH-GT] Mathematics [math]/Geometric Topology [math.GT]
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Computation of the topological type of a real Riemann surface

2012

We present an algorithm for the computation of the topological type of a real compact Riemann surface associated to an algebraic curve, i.e., its genus and the properties of the set of fixed points of the anti-holomorphic involution $\tau$, namely, the number of its connected components, and whether this set divides the surface into one or two connected components. This is achieved by transforming an arbitrary canonical homology basis to a homology basis where the $\mathcal{A}$-cycles are invariant under the anti-holomorphic involution $\tau$.

Computational Geometry (cs.CG)FOS: Computer and information sciencesreal Riemann surface[MATH.MATH-AG] Mathematics [math]/Algebraic Geometry [math.AG]homology basis[ MATH.MATH-AG ] Mathematics [math]/Algebraic Geometry [math.AG]Mathematics - Algebraic Geometryreal algebraic curveholomorphic differentialsFOS: MathematicsComputer Science - Computational Geometryreal ovals[MATH.MATH-AG]Mathematics [math]/Algebraic Geometry [math.AG]Algebraic Geometry (math.AG)
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