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showing 10 items of 3931 documents

Using Fourier local magnitude in adaptive smoothness constraints in motion estimation

2007

Like many problems in image analysis, motion estimation is an ill-posed one, since the available data do not always sufficiently constrain the solution. It is therefore necessary to regularize the solution by imposing a smoothness constraint. One of the main difficulties while estimating motion is to preserve the discontinuities of the motion field. In this paper, we address this problem by integrating the motion magnitude information obtained by the Fourier analysis into the smoothness constraint, resulting in an adaptive smoothness. We describe how to achieve this with two different motion estimation approaches: the Horn and Schunck method and the Markov Random Field (MRF) modeling. The t…

Mathematical optimizationRandom fieldMarkov random fieldSmoothness (probability theory)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowConstraint (information theory)symbols.namesakeMotion fieldArtificial IntelligenceFourier analysisMotion estimationSignal ProcessingsymbolsComputer Vision and Pattern RecognitionAlgorithmSoftwareComputingMethodologies_COMPUTERGRAPHICSMathematicsPattern Recognition Letters
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Smart load prediction analysis for distributed power network of Holiday Cabins in Norwegian rural area

2020

Abstract The Norwegian rural distributed power network is mainly designed for Holiday Cabins with limited electrical loading capacity. Load prediction analysis, within such type of network, is necessary for effective operation and to manage the increasing demand of new appliances (e. g. electric vehicles and heat pumps). In this paper, load prediction of a distributed power network (i.e. a typical Norwegian rural area power network of 125 cottages with 478 kW peak demand) is carried out using regression analysis techniques for establishing autocorrelations and correlations among weather parameters and occurrence time in the period of 2014–2018. In this study, the regression analysis for loa…

Mathematical optimizationRenewable Energy Sustainability and the EnvironmentComputer science020209 energyStrategy and Management05 social sciencesAutocorrelationDistributed powerRegression analysis02 engineering and technologyLoad profileIndustrial and Manufacturing EngineeringRandom forestAutoregressive modelPeak demand050501 criminology0202 electrical engineering electronic engineering information engineeringSymmetric mean absolute percentage error0505 lawGeneral Environmental ScienceJournal of Cleaner Production
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Efficient solution of the first passage problem by Path Integration for normal and Poissonian white noise

2015

Abstract In this paper the first passage problem is examined for linear and nonlinear systems driven by Poissonian and normal white noise input. The problem is handled step-by-step accounting for the Markov properties of the response process and then by Chapman–Kolmogorov equation. The final formulation consists just of a sequence of matrix–vector multiplications giving the reliability density function at any time instant. Comparison with Monte Carlo simulation reveals the excellent accuracy of the proposed method.

Mathematical optimizationSequenceMarkov chainPoisson proceMechanical EngineeringReliability (computer networking)Monte Carlo methodAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionWhite noiseWhite noiseCondensed Matter PhysicsPath IntegrationNonlinear systemNuclear Energy and EngineeringStructural reliabilityApplied mathematicsFirst passage problemRandom vibrationSettore ICAR/08 - Scienza Delle CostruzioniRandom vibrationCivil and Structural EngineeringMathematicsProbabilistic Engineering Mechanics
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On the Bias and Performance of the Edge-Set Encoding

2009

The edge-set encoding of trees directly represents trees as sets of their edges. Nonheuristic operators for edge-sets manipulate trees' edges without regard for their weights, while heuristic operators consider edges' weights when including or excluding them. In the latter case, the operators generally favor edges with lower weights, and they tend to generate trees that resemble minimum spanning trees. This bias is strong, which suggests that evolutionary algorithms (EAs) that employ heuristic operators will succeed when optimum solutions resemble minimum spanning trees (MSTs) but fail otherwise. The one-max tree problem is a scalable test problem for trees where the optimum solution can be…

Mathematical optimizationSpanning treeStochastic processEvolutionary algorithmMinimum spanning treeTree (graph theory)Evolutionary computationTheoretical Computer ScienceCombinatoricsTree structureComputational Theory and MathematicsRandom treeSoftwareMathematicsIEEE Transactions on Evolutionary Computation
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On Optimal Solutions for the Optimal Communication Spanning Tree Problem

2009

This paper presents an experimental investigation into the properties of the optimal communication spanning tree (OCST) problem. The OCST problem seeks a spanning tree that connects all the nodes and satisfies their communication requirements at a minimum total cost. The paper compares the properties of random trees to the properties of the best solutions for the OCST problem that are found using an evolutionary algorithm. The results show, on average, that the optimal solution and the minimum spanning tree (MST) share a higher number of links than the optimal solution and a random tree. Furthermore, optimal solutions for OCST problems with randomly chosen distance weights share a higher n…

Mathematical optimizationSpanning treebusiness.industryManagement Science and Operations ResearchMinimum spanning treeSearch treeComputer Science ApplicationsTree traversalRandom treeCombinatorial optimizationLocal search (optimization)businessGreedy algorithmAlgorithmMathematicsOperations Research
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Hedging of Spatial Temperature Risk with Market-Traded Futures

2011

The main objective of this work is to construct optimal temperature futures from available market-traded contracts to hedge spatial risk. Temperature dynamics are modelled by a stochastic differential equation with spatial dependence. Optimal positions in market-traded futures minimizing the variance are calculated. Examples with numerical simulations based on a fast algorithm for the generation of random fields are presented.

Mathematical optimizationStochastic differential equationWork (thermodynamics)Random fieldApplied MathematicsStochastic simulationEconometricsVariance (accounting)Spatial dependenceHedge (finance)Futures contractFinanceMathematicsApplied Mathematical Finance
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Incremental bipartite drawing problem

2001

Abstract Layout strategies that strive to preserve perspective from earlier drawings are called incremental. In this paper we study the incremental arc crossing minimization problem for bipartite graphs. We develop a greedy randomized adaptive search procedure (GRASP) for this problem. We have also developed a branch-and-bound algorithm in order to compute the relative gap to the optimal solution of the GRASP approach. Computational experiments are performed with 450 graph instances to first study the effect of changes in grasp search parameters and then to test the efficiency of the proposed procedure. Scope and purpose Many information systems require graphs to be drawn so that these syst…

Mathematical optimizationTheoretical computer scienceGeneral Computer ScienceManagement Science and Operations ResearchModular decompositionGraph drawingModeling and SimulationIndependent setClique-widthBipartite graphForce-directed graph drawingGraph productGreedy randomized adaptive search procedureMathematicsofComputing_DISCRETEMATHEMATICSMathematicsComputers & Operations Research
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A Highly Flexible Trajectory Model Based on the Primitives of Brownian Fields—Part II: Analysis of the Statistical Properties

2016

In the first part of our paper, we have proposed a highly flexible trajectory model based on the primitives of Brownian fields (BFs). In this second part, we study the statistical properties of that trajectory model in depth. These properties include the autocorrelation function (ACF), mean, and the variance of the path along each axis. We also derive the distribution of the angle-of-motion (AOM) process, the incremental traveling length process, and the overall traveling length. It is shown that the path process is in general non-stationary. We show that the AOM and the incremental traveling length processes can be modeled by the phase and the envelope of a complex Gaussian process with no…

Mathematical optimizationUniform distribution (continuous)Applied MathematicsGaussianAutocorrelationMathematical analysis020206 networking & telecommunications020302 automobile design & engineering02 engineering and technologyComputer Science ApplicationsComplex normal distributionsymbols.namesake0203 mechanical engineeringLog-normal distribution0202 electrical engineering electronic engineering information engineeringsymbolsTrajectoryElectrical and Electronic EngineeringGaussian processRandom variableMathematicsIEEE Transactions on Wireless Communications
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Randomized heuristics for the Capacitated Clustering Problem

2017

In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between randomization and greediness on the performance of these multi-start heuristic search methods when solving this NP-hard problem. The former is a memory-less approach that constructs independent solutions, while the latter is a memory-based method that constructs linked solutions, obtained by partially rebuilding previous ones. Both are based on the combination of greediness and randomization in the constructive process, and coupled with a subsequent l…

MatheuristicMathematical optimizationInformation Systems and Management0211 other engineering and technologies02 engineering and technologyCapacitated ClusteringTheoretical Computer ScienceArtificial Intelligence0202 electrical engineering electronic engineering information engineeringLocal search (optimization)Cluster analysisGreedy randomized adaptive search procedureMathematicsGrasp021103 operations researchbusiness.industryHeuristicGRASPGraph partitioningGraph partitionComputer Science ApplicationsControl and Systems EngineeringSimulated annealing020201 artificial intelligence & image processingHeuristicsbusinessSoftware
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Survival Rate and Prosthetic and Sinus Complications of Zygomatic Dental Implants for the Rehabilitation of the Atrophic Edentulous Maxilla: A System…

2021

Simple Summary Zygomatic dental implants have been proposed as an alternative to atrophic total edentulous maxillae rehabilitation with the necessity of bone grafting procedures. However, surgical, prosthetic, and maxillary sinus complications have been associated with this surgical procedure. Therefore, it is necessary to produce a systematic review and meta-analysis that provides evidence associated with the prognosis when using zygomatic dental implants as an alternative to atrophic total edentulous maxillae rehabilitation. Abstract The aim of this systematic review and meta-analysis was to analyze and compare the survival rate and prosthetic and sinus complications of zygomatic dental i…

Maxillary sinusQH301-705.5sinusitisDentistryReviewBiologysurvivalGeneral Biochemistry Genetics and Molecular Biologylaw.invention03 medical and health sciences0302 clinical medicineRandomized controlled triallawprosthetic rehabilitationmedicineBiology (General)SinusitisSurvival rateGeneral Immunology and Microbiologybusiness.industryImplant failureRetrospective cohort study030206 dentistrymedicine.diseasestomatognathic diseasesmedicine.anatomical_structureSystematic reviewimplant failure030220 oncology & carcinogenesisMeta-analysiszygomatic implantsmaxillary sinusGeneral Agricultural and Biological SciencesbusinessBiology
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