Search results for "recognition"

showing 10 items of 3607 documents

Preparation of potentially porous, chiral organometallic materials through spontaneous resolution of pincer palladium conformers.

2013

Understanding the mechanism by which advanced materials assemble is essential for the design of new materials with desired properties. Here, we report a method to form chiral, potentially porous materials through spontaneous resolution of conformers of a PCP pincer palladium complex ({2,6-bis[(di-t-butylphosphino)methyl]phenyl}palladium(II)halide). The crystallisation is controlled by weak hydrogen bonding giving rise to chiral qtz-nets and channel structures, as shown by 16 such crystal structures for X = Cl and Br with various solvents like pentane and bromobutane. The fourth ligand (in addition to the pincer ligand) on palladium plays a crucial role; the chloride and the bromide primaril…

crystal structuretermoanalyysichemistry.chemical_elementCrystal structurekiderakenne010402 general chemistryjauhe röntgen diffraktioCrystallography X-Ray01 natural scienceshuokoiset materiaalitpalladium kompleksiInorganic ChemistryMolecular recognitionOrganometallic CompoundsMoleculePincer ligandta116palladium pincer complexes; hexagonal channels; self-assembly; weak interactionssingle crystal X-ray diffractionpowder X-ray diffractionorganometalliMolecular Structure010405 organic chemistryChemistryStereoisomerismpalladium complexyksikide röntgen diffraktio0104 chemical sciencesPincer movementChemistryCrystallographySelf-assemblyporous materialsPorosityPalladiumMonoclinic crystal systemPalladiumDalton transactions (Cambridge, England : 2003)
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Curvelet-based method for orientation estimation of particles from optical images

2014

A method based on the curvelet transform is introduced to estimate the orientation distribution from two-dimensional images of small anisotropic particles. Orientation of fibers in paper is considered as a particular application of the method. Theoretical aspects of the suitability of this method are discussed and its efficiency is demonstrated with simulated and real images of fibrous systems. Comparison is made with two traditionally used methods of orientation analysis, and the new curvelet-based method is shown to perform better than these tradi- tional methods. peerReviewed

curveletmultiscaleComputer Science::Computer Vision and Pattern Recognitionanisotropicorientationfiber
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Enantioselective recognition of alfa-amino acids by binary complexes fluorophore/cyclodextrin

cyclodextrin chiral recognition host-guest complexesSettore CHIM/06 - Chimica Organica
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Binary complexes heptakis-(6-amino)-(6-deoxy)-beta-cyclodextrin/fluorophore: structural investigation and chiral recognition

cyclodextrin host-guest complexes chiral recognitionSettore CHIM/06 - Chimica Organica
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Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space

2019

In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results. peerReviewed

data-driven optimizationMathematical optimizationOptimization problemComputer scienceboreal forest managementComputer Science::Neural and Evolutionary Computationpäätöksenteko0211 other engineering and technologiesMathematicsofComputing_NUMERICALANALYSISdecision maker02 engineering and technologypreference informationSpace (commercial competition)Multi-objective optimizationComputingMethodologies_ARTIFICIALINTELLIGENCEData-drivenklusteritoptimointi0202 electrical engineering electronic engineering information engineeringCluster analysis021103 operations researchsurrogatesComputingMethodologies_PATTERNRECOGNITIONboreaalinen vyöhyke020201 artificial intelligence & image processingmetsänhoitoCluster basedclustering
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Predicting the availability of users' devices in Decentralized Online Social Networks

2018

The understanding of the user temporal behavior is a crucial aspect for all those systems that rely on user resources for daily operations, such as decentralized online social networks (DOSNs). Indeed, DOSNs exploit the devices of their users to take on and share the tasks needed to provide services such as storing the published data. In the last years, the increasing popularity of DOSN services has changed the way of how people interact with each other by enabling users to connect to these services at any time by using their personal devices (such as notebooks or smartphones). As a result, the availability of data in these systems is strongly affected (or reflected) by the temporal behavio…

decentralized online social networkdecentralized online social networksavailability predictionComputer Networks and CommunicationComputational Theory and Mathematicsavailabilityuser behaviorComputer Science Applications1707 Computer Vision and Pattern Recognitionpredictionavailability prediction; decentralized online social networks; user behaviorSoftwareTheoretical Computer Science
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Détection robuste de mouvement par histogrammes quasi‐continus

2012

National audience; Dans cet article, nous proposons d'utiliser la représentation de distributions de valeurs par histogrammes quasi-continus pour réaliser une détection temps réel de mouvement dans une séquence d'images. Nous comparons les résultats de cette détection à deux méthodes de référence de la littérature.

densityvision[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]motion detection[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Quasi-continuous histogram[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]image processing
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Performance of $b$-Jet Identification in the ATLAS Experiment

2016

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT an…

detector-systems performancePerformance of High Energy Physics Detectorsecondary [vertex]Elementary particle01 natural sciencesPARTONlaw.inventionSubatomär fysikCHANNELcluster findingscattering [p p]impact parameterGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)протон-протонные столкновенияQBLarge detector-systems performanceHigh energy physics detectorLarge Hadron ColliderLarge detector systems for particle and astroparticle physics; Large detector-systems performance; Pattern recognition cluster finding calibration and fitting methods; Performance of High Energy Physics Detectors; Instrumentation; Mathematical Physicstrack data analysisQUARK PAIR PRODUCTIONbottom [jet]CERN LHC CollPattern recognition cluster finding calibration and fitting method7000 GeV-cmscolliding beams [p p]performanceHADRONIC COLLISIONSCiências Naturais::Ciências FísicasLarge detectorFitting methodHigh energy physicATLAS LHC High Energy Physics510 MathematicsmuonDISTRIBUTIONSUncertainty analysis Astroparticle physicHigh Energy Physics010306 general physicsSystematic uncertainties AlgorithmsAstroparticle physicsCalibration and fitting methodsScience & Technology010308 nuclear & particles physicsLarge detector systems for particle and astroparticle physicsParticle acceleratorRangingPerformance of High Energy PhysicsCOLLIDERScorrelationExperimental High Energy PhysicsPerformance of High Energy Physics DetectorshadronATLAS детекторБольшой адронный коллайдерcharm [jet]Elementary particleHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)lawSubatomic Physics[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Detectors and Experimental TechniquesInstrumentationUncertainty analysisMathematical PhysicsPhysicsPattern recognition cluster finding calibration and fitting methods4. EducationATLAS experimentSettore FIS/01 - Fisica SperimentaleDetectorsflavor [jet]calibration and fitting methodsATLASLarge Hadron ColliderLarge detector systems for particle and astroparticle physics; Large; detector-systems performance; Pattern recognition cluster finding; calibration and fitting methods; Performance of High Energy Physics; Detectors; PRODUCTION CROSS-SECTION; QUARK PAIR PRODUCTION; ROOT-S=7 TEV; PARTON; DISTRIBUTIONS; HADRONIC COLLISIONS; MATRIX-ELEMENTS; LHC; COLLIDERS; DETECTOR; CHANNEL8. Economic growthCalibrationparticle identification [bottom]LHCImpact parameterParticle Physics - ExperimentParticle physicsdata analysis method530 Physics:Ciências Físicas [Ciências Naturais]FOS: Physical sciences530MATRIX-ELEMENTSparticle identification [charm]on-line [trigger]Pattern recognition0103 physical sciencesComplementary methodddc:610DETECTORROOT-S=7 TEVCluster findingFísicaLarge detector systems for particle and astroparticle physics; Large detector-systems performance; Pattern recognition cluster finding calibration and fitting methods; Performance of High Energy Physics DetectorsPattern recognition systemcalibrationtracksPRODUCTION CROSS-SECTIONefficiencyHadronLarge detector systems for particle and astroparticle physicLargeHigh Energy Physics::ExperimentStatistical correlationstatisticalexperimental results
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Linear Feature Extraction for Ranking

2018

We address the feature extraction problem for document ranking in information retrieval. We then propose LifeRank, a Linear feature extraction algorithm for Ranking. In LifeRank, we regard each document collection for ranking as a matrix, referred to as the original matrix. We try to optimize a transformation matrix, so that a new matrix (dataset) can be generated as the product of the original matrix and a transformation matrix. The transformation matrix projects high-dimensional document vectors into lower dimensions. Theoretically, there could be very large transformation matrices, each leading to a new generated matrix. In LifeRank, we produce a transformation matrix so that the generat…

dimension reductionComputer scienceFeature extractionMathematicsofComputing_NUMERICALANALYSISFeature selectiontiedonhakujärjestelmät02 engineering and technologyLibrary and Information SciencesRanking (information retrieval)Matrix (mathematics)Transformation matrix020204 information systemsalgoritmit0202 electrical engineering electronic engineering information engineeringtiedonhakulearning to rankbusiness.industryfeature extractionPattern recognitionkoneoppiminenPattern recognition (psychology)Benchmark (computing)020201 artificial intelligence & image processingLearning to rankArtificial intelligencebusinessInformation Systems
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Human Activity Signatures Captured under Different Directions Using SISO and MIMO Radar Systems

2022

In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2×2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Anc…

direction-independent human activity recognition; fall detection; distributed MIMO; FMCW radar; micro-Doppler signatures; aspect angle; multistatic radar systems; passive step counter; DTW; velocity estimationFluid Flow and Transfer ProcessesProcess Chemistry and TechnologyGeneral EngineeringVDP::Medisinske Fag: 700General Materials ScienceVDP::Matematikk og Naturvitenskap: 400InstrumentationComputer Science::Information TheoryComputer Science ApplicationsApplied Sciences
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