Search results for " dimensionality"

showing 10 items of 129 documents

Ligand effects on the dimensionality of oxamato-bridged mixed-metal open-framework magnets

2012

Increasing dimensionality [from 2D (1) to 3D (2)] and T(C) [from 10 (1) to 20 K (2)] in two new oxamato-bridged heterobimetallic Mn(II)(2)Cu(II)(3) open-frameworks result from the steric hindrance provided by the different alkyl substituents of the N-phenyloxamate bridging ligands.

Steric effectschemistry.chemical_classificationBridging (networking)Mixed metalChemistryLigandStereochemistryMetals and AlloysGeneral ChemistryOpen frameworkCatalysisSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsCrystallographyMagnetMaterials ChemistryCeramics and CompositesAlkylCurse of dimensionalityChemical Communications
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A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms

2014

The file attached to this record is the author's final peer reviewed version. The publisher's final version can be found by following the DOI link. The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the most successful operators. In this paper we extend the idea of the ensemble to multiple local search logics. In a memetic fashion, the search structure of an ensemble framework cooperatively/competitively optimizes the problem jointly with a pool of diverse local search algorithms. In this way, the algorithm progressively adapts…

Structure (mathematical logic)Theoretical computer sciencebusiness.industryComputer scienceMeta-heuristicsComputational intelligenceAdaptive algorithmsDifferential evolutionLocal search (optimization)OptimisationDifferential evolutionAdaptation (computer science)businessGlobal optimizationAlgorithmMetaheuristicEnsembleMemetic ComputingCurse of dimensionality
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Enhanced superconductivity in atomically thin TaS2

2016

The ability to exfoliate layered materials down to the single layer limit has presented the opportunity to understand how a gradual reduction in dimensionality affects the properties of bulk materials. Here we use this top–down approach to address the problem of superconductivity in the two-dimensional limit. The transport properties of electronic devices based on 2H tantalum disulfide flakes of different thicknesses are presented. We observe that superconductivity persists down to the thinnest layer investigated (3.5 nm), and interestingly, we find a pronounced enhancement in the critical temperature from 0.5 to 2.2 K as the layers are thinned down. In addition, we propose a tight-binding …

SuperconductivityWork (thermodynamics)Materials scienceScienceTantalumFOS: Physical sciencesGeneral Physics and Astronomychemistry.chemical_element02 engineering and technology01 natural sciencesArticleGeneral Biochemistry Genetics and Molecular BiologySuperconductivity (cond-mat.supr-con)Mesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciences010306 general physicsSuperconductivitatSuperconductivityCoupling constantMultidisciplinaryCondensed Matter - Mesoscale and Nanoscale PhysicsAtomically thinCondensed matter physicsCondensed Matter - SuperconductivityQDisulfide bondFísicaGeneral ChemistryCiència dels materials021001 nanoscience & nanotechnologychemistry0210 nano-technologyLayer (electronics)Single layerCurse of dimensionality
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The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.

2019

Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …

Theoretical computer scienceHierarchical learning automataHierarchy (mathematics)DiscretizationLearning automataComputer Networks and CommunicationsComputer scienceLarge action numbersPursuit learning automata02 engineering and technologyVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Probability vectorLearning automataComputer Science ApplicationsAutomatonOperator (computer programming)Artificial Intelligence0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Estimator-based learning automata020201 artificial intelligence & image processingVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550SoftwareCurse of dimensionalityIEEE transactions on neural networks and learning systems
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The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions

2018

Part 10: Learning - Intelligence; International audience; Although the field of Learning Automata (LA) has made significant progress in the last four decades, the LA-based methods to tackle problems involving environments with a large number of actions are, in reality, relatively unresolved. The extension of the traditional LA (fixed structure, variable structure, discretized, and pursuit) to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and consequently, most components of the vector will, after a relatively short time, have values that are smal…

Theoretical computer scienceHierarchical learning automataHierarchy (mathematics)Learning automataComputer sciencePursuit learning automataPursuit LALearning Automata02 engineering and technologyEstimator-based LAProbability vectorField (computer science)020202 computer hardware & architectureLA with large number of actionsVariable (computer science)Operator (computer programming)Learning Automata (LA)Action (philosophy)0202 electrical engineering electronic engineering information engineeringEstimator-based learning automata[INFO]Computer Science [cs]020201 artificial intelligence & image processingHierarchical LACurse of dimensionality
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2004

This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1) feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE), and (2) AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to …

Training setCorrelation coefficientMean squared errorComputer sciencebusiness.industryApplied MathematicsFeature selectionMutual informationMachine learningcomputer.software_genreBiochemistryComputer Science ApplicationsSupport vector machineStructural BiologyFeature (machine learning)Artificial intelligencebusinessMolecular BiologycomputerEnergy (signal processing)Curse of dimensionalityBMC Bioinformatics
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Saliency in spectral images

2011

International audience; Even though the study of saliency for color images has been thoroughly investigated in the past, very little attention has been given to datasets that cannot be displayed on traditional computer screens such as spectral images. Nevertheless, more than a means to predict human gaze, the study of saliency primarily allows for measuring infor- mative content. Thus, we propose a novel approach for the computation of saliency maps for spectral images. Based on the Itti model, it in- volves the extraction of both spatial and spectral features, suitable for high dimensionality images. As an application, we present a comparison framework to evaluate how dimensionality reduct…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputation0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingImage (mathematics)[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingInformative content0202 electrical engineering electronic engineering information engineeringVisual attentionComputer visionRelevance (information retrieval)spectral images[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing021101 geological & geomatics engineeringSaliencybusiness.industryDimensionality reductionPattern recognitionKadir–Brady saliency detector020201 artificial intelligence & image processingArtificial intelligenceHigh dimensionalitybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Measuring vine leaf roughness by image processing

2013

International audience; In precision spraying, spray application efficiency depends on the pesticide application method, the phytosanitary product as well as the leaf surface properties. For environmental and economic reasons, the global trend is to reduce the pesticide application rate of the few approved active substances. Under these constraints, one of the challenges is to improve the efficiency of pesticide application. Different parameters can influence on pesticide application as nozzle types, liquid viscosity and leaf surface. Specific models have been developed showing that the predominant factor for the leaf is the leaf roughness, because it is related on adhesion mechanisms of li…

[SDV] Life Sciences [q-bio][SDE] Environmental SciencesGeneralized Fourier Descriptor[SDV]Life Sciences [q-bio][SDE]Environmental SciencesNeural Network[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologyleaf surface roughnessnonlinear reduction dimensionality methodstexture
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A multiple-response chi-square framework for the analysis of Free-Comment and Check-All-That-Apply data

2021

International audience; Free-Comment (FC) and Check-All-That-Apply (CATA) provide a contingency table containing citation counts of descriptors by products. The analyses performed on this table are most often related to the chi-square statistic. However, such practices are not well suited because they consider experimental units as being the citations (one descriptor for one product by one subject) while the evaluations (vector of citations for one product by one subject) should be considered instead. This results in incorrect expected frequencies under the null hypothesis of independence between products and descriptors and thus in an incorrect chi-square statistic. Thus, analyses related …

[SPI] Engineering Sciences [physics]030309 nutrition & dieteticsComputer sciencedimensionality testmultiple-response correspondence analysiscomputer.software_genremultiple-response dimensionality test of dependenceCorrespondence analysis[SHS]Humanities and Social Sciencescorrespondence analysis[SPI]Engineering Sciences [physics]multiple-response hypergeometric test03 medical and health sciences0404 agricultural biotechnologyChi-square testComputingMilieux_MISCELLANEOUSStatisticIndependence (probability theory)Contingency table0303 health sciencesNutrition and Dieteticscontingency tableMultiple-Response Correspondence Analysis (MR-CA)chi-square statistic04 agricultural and veterinary sciences040401 food scienceHypergeometric distribution[STAT]Statistics [stat][SDV.AEN] Life Sciences [q-bio]/Food and NutritionProduct (mathematics)[SHS] Humanities and Social SciencesData miningNull hypothesis[SDV.AEN]Life Sciences [q-bio]/Food and Nutritioncomputeranalysis of multiple-response dataFood ScienceFood Quality and Preference
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Visible-NIR reflectance spectroscopy and manifold learning methods applied to the detection of fungal infections on citrus fruit

2015

Abstract The development of systems for automatically detecting decay in citrus fruit during quality control is still a challenge for the citrus industry. The feasibility of reflectance spectroscopy in the visible and near infrared (NIR) regions was evaluated for the automatic detection of the early symptoms of decay caused by Penicillium digitatum fungus in citrus fruit. Reflectance spectra of sound and decaying surface parts of mandarins cv. ‘Clemenvilla’ were acquired in two different spectral regions, from 650 nm to 1050 nm (visible–NIR) and from 1000 nm to 1700 nm (NIR), pointing to significant differences in spectra between sound and decaying skin for both spectral ranges. Three diffe…

business.industryChemistryDimensionality reductionFeature vectorNear-infrared spectroscopyNonlinear dimensionality reductionLinear discriminant analysisSammon mappingOpticsPrincipal component analysisbusinessSpectroscopyBiological systemFood Science
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