Search results for " Prediction"

showing 10 items of 366 documents

MAGEMin 1.0.0

2022

MAGEMin is a Gibbs energy minimization solver package, which computes the thermodynamically most stable assemblage for a given bulk rock composition and pressure/temperature condition. It also returns parameters such as melt fraction or density, which can be combined with geodynamic/petrological tools to simulate, for example, the evolving chemistry of a crystallising melt. MAGEMin is written as a parallel C library and uses a combination of linear programming, extended Partitioning Gibbs free Energy and gradient-based local minimization to compute the most stable mineral assemblage. In this, it differs from exisisting approaches which makes it particularly suitable to utilize modern multic…

Geodyanmics couplingGibbs energy minimizerIgneous stable phase prediction
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MAGEMin 1.0.0

2022

MAGEMin is a Gibbs energy minimization solver package, which computes the thermodynamically most stable assemblage for a given bulk rock composition and pressure/temperature condition. It also returns parameters such as melt fraction or density, which can be combined with geodynamic/petrological tools to simulate, for example, the evolving chemistry of a crystallising melt. MAGEMin is written as a parallel C library and uses a combination of linear programming, extended Partitioning Gibbs free Energy and gradient-based local minimization to compute the most stable mineral assemblage. In this, it differs from exisisting approaches which makes it particularly suitable to utilize modern multic…

Geodyanmics couplingGibbs energy minimizerPhysics::GeophysicsIgneous stable phase prediction
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A novel hardware accelerator for the HEVC intra prediction

2015

International audience; A novel hardware accelerator for the High Efficiency Video Coding (HEVC) intra prediction is presented in this paper in order to reduce the computation complexity within this standard and to accelerate the concerned calculations. We propose a new pipelined structure that we called Processing Element (PE) to execute all angular modes, and we repeat it in five paths that our architecture composed of. We present also another structure to carry out the Planar mode. This architecture supports all intra prediction modes for all prediction unit sizes. The synthesis results show that our design can run at 213 MHz for Xilinx Virtex 6 and is capable to process real time 120 10…

HEVC0209 industrial biotechnologyAdderVirtexComputer scienceProcessing element020208 electrical & electronic engineering1080pFPGAs02 engineering and technologyParallel computingIntra prediction[SPI]Engineering Sciences [physics]020901 industrial engineering & automationPlanar0202 electrical engineering electronic engineering information engineering[ SPI ] Engineering Sciences [physics]Hardware accelerationField-programmable gate arrayCoding (social sciences)
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Fully pipelined real time hardware solution for High Efficiency Video Coding (HEVC) intra prediction

2016

International audience; A fully pipelined hardware accelerator for the High Efficiency Video Coding (HEVC) intra prediction is presented in this paper in order to reduce the computation complexity coming with this module and to accelerate the concerned calculations. Two reconfigurable structures are developed in this paper, the first one concerns angular modes and is identified as Processing Element for Angular (PEA) modes, the other is made in order to handle with the Planar mode and is identified as Processing Element for the Planar (PEP) mode. Each structure is repeated in five paths, that our architecture composed of, working in parallel way. This architecture supports all intra predict…

HEVC[ INFO ] Computer Science [cs]Image compressionComputer scienceReal-time processing1080pFPGAs02 engineering and technologyIntra prediction0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Field-programmable gate arrayVirtexbusiness.industryReconfigurable computing020206 networking & telecommunicationsFrame rateReconfigurable computingHardware and ArchitectureHardware acceleration020201 artificial intelligence & image processingbusinessSoftwareComputer hardwareImage compressionCoding (social sciences)
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A HARDWARE SOLUTION FOR HEVC INTRA PREDICTION LOSSLESS CODING

2015

International audience; The lossless coding mode of the High Efficiency Video Coding (HEVC) main profile that bypasses transform, quantization, and in-loop filters is described. Compared to the HEVC non-lossless coding mode, the HEVC lossless coding mode provides perfect fidelity and an average bit-rate reduction of 3.2%–13.2%. It also significantly outperforms the existing lossless compression solutions, such as JPEG2000 and JPEG-LS for images as well as WinRAR for data archiving. A fully parallel-based solution is presented in this paper in order to reduce processing time and computation complexity resulting from intra prediction. Two higher performance structures are designed to perform …

HEVC[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-IM ] Computer Science [cs]/Medical Imaginglossless coding[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing[INFO.INFO-IM] Computer Science [cs]/Medical Imaging[INFO.INFO-IM]Computer Science [cs]/Medical Imagingparallel computing 1intra predictionFPGA
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Atmospheric and astrophysical neutrinos above 1 TeV interacting in IceCube

2015

The IceCube Neutrino Observatory was designed primarily to search for high-energy (TeV--PeV) neutrinos produced in distant astrophysical objects. A search for $\gtrsim 100$~TeV neutrinos interacting inside the instrumented volume has recently provided evidence for an isotropic flux of such neutrinos. At lower energies, IceCube collects large numbers of neutrinos from the weak decays of mesons in cosmic-ray air showers. Here we present the results of a search for neutrino interactions inside IceCube's instrumented volume between 1~TeV and 1~PeV in 641 days of data taken from 2010--2012, lowering the energy threshold for neutrinos from the southern sky below 10 TeV for the first time, far bel…

HIGH-ENERGY NEUTRINOSNuclear and High Energy PhysicsParticle physicsAMANDAMesonSolar neutrinoAstrophysics::High Energy Astrophysical PhenomenaINDUCED CASCADESFOS: Physical sciencesCosmic rayAstrophysicsFLUX PREDICTIONS01 natural sciencesIceCube Neutrino ObservatoryIceCubeObservatorySEARCH0103 physical sciencesddc:530Blazar010303 astronomy & astrophysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)Physics010308 nuclear & particles physicsHigh Energy Physics::PhenomenologyAstrophysics::Instrumentation and Methods for AstrophysicsASTRONOMYPERFORMANCEBLAZARSPROMPT LEPTONSGAMMA-RAYPhysics and AstronomyHigh Energy Physics::ExperimentNeutrino astronomyNeutrinoAstrophysics - High Energy Astrophysical PhenomenaphysicsPhysical Review D
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Discussion of “Soil Water Retention Characteristics of Vertisols and Pedotransfer Functions Based on Nearest Neighbor and Neural Networks Approaches …

2013

HYDRAULIC PROPERTIESArtificial neural networkPREDICTIONSWRCSoil scienceSoil Water Retention Curve Soil Shrinkage Characteristic CurveVertisolHYDRAULIC PROPERTIES; SHRINKAGE; PREDICTION; SWRC; ANNAgricultural and Biological Sciences (miscellaneous)k-nearest neighbors algorithmPedotransfer functionSoil waterSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSHRINKAGEANNWater Science and TechnologyCivil and Structural EngineeringMathematics
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A machine learning approach to determine airport asphalt concrete layer moduli using heavy weight deflectometer data

2021

An integrated approach based on machine learning and data augmentation techniques has been developed in order to predict the stiffness modulus of the asphalt concrete layer of an airport runway, from data acquired with a heavy weight deflectometer (HWD). The predictive model relies on a shallow neural network (SNN) trained with the results of a backcalculation, by means of a data augmentation method and can produce estimations of the stiffness modulus even at runway points not yet sampled. The Bayesian regularization algorithm was used for training of the feedforward backpropagation SNN, and a k-fold cross-validation procedure was implemented for a fair performance evaluation. The testing p…

Heavy weight deflectometerComputer scienceMaintenanceRunwayGeography Planning and DevelopmentTJ807-830Management Monitoring Policy and LawStiffness modulusTD194-195Machine learningcomputer.software_genreRenewable energy sourcesMachine learningPerformance predictionGE1-350Layer (object-oriented design)Environmental effects of industries and plantsArtificial neural networkRenewable Energy Sustainability and the Environmentbusiness.industryFeed forwardPavement managementBuilding and ConstructionBackpropagationEnvironmental sciencesAsphalt concreteShallow neural networkHeavy weight deflectometer; Machine learning; Maintenance; Runway; Shallow neural network; Stiffness modulusRunwayArtificial intelligencebusinesscomputer
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Determination of the Chiral Couplings L10 and C87 from Semileptonic τ Decays

2008

Using recent precise hadronic tau-decay data on the V-A spectral function, and general properties of QCD such as analyticity, the operator product expansion and chiral perturbation theory, we get accurate values for the QCD chiral order parameters L_10^r(M_rho) and C_87^r(M_rho). These two low-energy constants appear at order p^4 and p^6, respectively, in the chiral perturbation theory expansion of the V-A correlator. At order p^4 we obtain L_10^r(M_rho) = -(5.22\pm 0.06)10^{-3}. Including in the analysis the two-loop (order p^6) contributions, we get L_10^r(M_rho) = -(4.06\pm 0.39)10^{-3} and C_87^r(M_rho) = (4.89\pm 0.19)10^{-3}GeV^{-2}. In the SU(2) chiral effective theory, the correspon…

High Energy Physics - Lattice (hep-lat)Spectral functionsFOS: Physical sciencesFísicaPerturbation theoryLow-energy constantsHigh Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)High Energy Physics - LatticeStrange quark massQCD predictionsHigh Energy Physics::ExperimentUs-vertical-barHadronic width
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Measurement of Event Shape and Inclusive Distributions at $\sqrt{s} =$ 130 and 136 GeV

1997

Inclusive charged particle and event shape distributions are measured using 321 hadronic events collected with the DELPHI experiment at LEP at effective centre of mass energies of 130 to 136 GeV. These distributions are presented and compared to data at lower energies, in particular to the precise Z data. Fragmentation models describe the observed changes of the distributions well. The energy dependence of the means of the event shape variables can also be described using second order QCD plus power terms. A method independent of fragmentation model corrections is used to determine $\alpha_s$ from the energy dependence of the mean thrust and heavy jet mass. It is measured to be: % %\alpha_s…

High energyParticle physicsZ(0) RESONANCEPhysics and Astronomy (miscellaneous)Electron–positron annihilationHADRONIC Z-DECAYS; E+E-ANNIHILATION; ALPHA-S; POWER CORRECTIONS; Z(0) RESONANCE; MONTE-CARLO; QCD MODELS; ENERGY; FRAGMENTATION; PREDICTIONSHadronPREDICTIONSThrust01 natural sciences7. Clean energyPartícules (Física nuclear)Nuclear physicsENERGYFragmentation (mass spectrometry)POWER CORRECTIONSMONTE-CARLO0103 physical sciences[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]ALPHA-S010306 general physicsDetectors de radiacióDELPHIPhysicsQuantum chromodynamics010308 nuclear & particles physicsHigh Energy Physics::PhenomenologyE+E-ANNIHILATIONLARGE ELECTRON POSITRON COLLIDERCharged particleHADRONIC Z-DECAYSLarge Electron–Positron ColliderPARTICLE PHYSICS; LARGE ELECTRON POSITRON COLLIDER; DELPHIQCD MODELSPARTICLE PHYSICSHigh Energy Physics::ExperimentFRAGMENTATIONParticle Physics - Experiment
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