Search results for "Mathematica"

showing 10 items of 7971 documents

Electron and photon energy calibration with the ATLAS detector using 2015-2016 LHC proton-proton collision data

2019

Artículo realizado por muchos autores. Solo se referencian el que aparece en primer lugar, el nombre del grupo de colaboración y los autores que firman como pertenecientes a la UAM

Z0 --> electron positronJ/psi(3100) --> electron positronProton13000 GeV-cmsparticle identification [electron]ElectronZ0 --> electron positronelectron: transverse momentum01 natural sciencesphoton: particle identificationSubatomär fysik0302 clinical medicinescattering [p p]Nuclear Experiment proton–proton collisionsLarge Hadron ColliderCalibration and fittingphoton: transverse momentumand fitting methodsphoton: energy:Mathematics and natural scienses: 400::Physics: 430::Nuclear and elementary particle physics: 431 [VDP]calibration [energy]CERN LHC Collcalibration and fitting methodcolliding beams [p p]transverse momentum [electron]p p: scatteringCiências Naturais::Ciências Físicas610LHC ATLAS High Energy PhysicsPhoton energyFitting methodsJ/psi(3100) --> electron positronradiative decay [J/psi(3100)]Nuclear physicsMomentum03 medical and health sciencesAtlas (anatomy)High Energy Physicspair production [electron]CALORIMETERScience & Technologyradiative decay [Z0]electron: particle identification010308 nuclear & particles physicsenergy [photon]Acceleratorfysik och instrumentering jets energy: calibrationCalorimeter methodExperimental High Energy PhysicsPerformance of High Energy Physics Detectorsp p: colliding beamsacceptancetransverse momentum [photon]PhotonJ/psi(3100): radiative decayCalorimeter methods; Pattern recognition cluster finding calibration; and fitting methods; Performance of High Energy Physics Detectors; PARTON DISTRIBUTIONS; LIQUID AR; CALORIMETER; KR030218 nuclear medicine & medical imagingHigh Energy Physics - Experimentelectron: pair productionHigh Energy Physics - Experiment (hep-ex)Subatomic Physics[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Collisions Calorimeter methodsInstrumentationMathematical PhysicsBosonPhysicsPattern recognition cluster finding calibration and fitting methodsSettore FIS/01 - Fisica Sperimentalecalibration and fitting methodsATLASLIQUID ARmedicine.anatomical_structureKRCalibrationcalibration and fitting methods; Calorimeter methods; cluster finding; Pattern recognition; Performance of High Energy Physics Detectors; Instrumentation; Mathematical PhysicsParticle Physics - Experiment530 Physics:Ciências Físicas [Ciências Naturais]FOS: Physical sciencesZ0: radiative decayAccelerator Physics and Instrumentationcalibration and fitting methods; Calorimeter methods; cluster finding; Pattern recognition; Performance of High Energy Physics DetectorsPattern recognition0103 physical sciencesmedicineddc:610hep-exCluster finding:Matematikk og naturvitenskap: 400::Fysikk: 430::Kjerne- og elementærpartikkelfysikk: 431 [VDP]particle identification [photon]FísicaPARTON DISTRIBUTIONSHigh Energy Physics::Experimentexperimental results
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Exact constants in Poincaré type inequalities for functions with zero mean boundary traces

2014

In this paper, we investigate Poincare type inequalities for the functions having zero mean value on the whole boundary of a Lipschitz domain or on a measurable part of the boundary. We find exact and easily computable constants in these inequalities for some basic domains (rectangles, cubes, and right triangles) and discuss applications of the inequalities to quantitative analysis of partial differential equations. Copyright © 2014 John Wiley & Sons, Ltd.

Zero meanPartial differential equationeigenvalue problemsGeneral MathematicsMathematical analysista111General EngineeringBoundary (topology)Value (computer science)Type (model theory)Physics::History of PhysicsPoincare type inequalitiessymbols.namesakeLipschitz domainerror estimatesPoincaré conjecturesymbolsfunctional inequalitiesMathematicsMathematical Methods in the Applied Sciences
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Correction parameters in X-ray fluorescence analysis applying the limit dilution method (LDM)

1992

This paper is a study of the interelemental effect and its correction based on the mathematical model used to develop LDM in XRF analysis. A “compensation coefficient” is defined which is obtained from the quotient of the mass absorption coefficients of the problem and the standard (μs*/μp*). This coefficient compensates the effects produced by interactions between the analyt and the interferences and therefore acts as a correction factor for the interelemental effect within this theoretical model. The model itself establishes a simple relation of the “compensation coefficient” and the Y/H correction parameters for the unknown and the standard. An algorithm is proposed for calculating the “…

ZirconiumMass absorptionChemistryMathematical analysisAnalytical chemistrychemistry.chemical_elementX-ray fluorescenceBiochemistryAnalytical ChemistryCompensation (engineering)DilutionFluorescence intensityLimit (mathematics)QuotientFresenius' Journal of Analytical Chemistry
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Relating RSS News/Items

2009

Merging related RSS news (coming from one or different sources) is beneficial for end-users with different backgrounds (journalists, economists, etc.), particularly those accessing similar information. In this paper, we provide a practical approach to both: measure the relatedness, and identify relationships between RSS elements. Our approach is based on the concepts of semantic neighborhood and vector space model, and considers the content and structure of RSS news items. © 2009 Springer Berlin Heidelberg.

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer scienceRSS[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologySimilarityTheoretical Computer ScienceWorld Wide Web[SCCO.COMP] Cognitive science/Computer science020204 information systemsSimilarity (psychology)0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Neighbourhood (mathematics)[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]Structure (mathematical logic)[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Measure (data warehouse)[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Information retrievalRelationship[INFO.INFO-WB]Computer Science [cs]/WebComputer Science (all)[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]computer.file_format[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]RSS Relatedne[ SCCO.COMP ] Cognitive science/Computer scienceVector space model020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]InformationSystems_MISCELLANEOUSNeighbourhoodcomputer
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Detecting Inference Channels in Private Multimedia Data via Social Networks

2009

International audience; Indirect access to protected information has been one of the key challenges facing the international community for the last decade. Providing techniques to control direct access to sensitive information remain insufficient against inference channels established when legitimate data reveal classified facts hidden from unauthorized users. Several techniques have been proposed in the literature to meet indirect access prevention. However, those addressing the inference problem when involving multimedia objects (images, audio, video, etc.) remain few and hold several drawbacks. In essence, the complex structure of multimedia objects makes the fact of detecting indirect a…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer sciencemedia_common.quotation_subject[ INFO.INFO-WB ] Computer Science [cs]/WebInference[SCCO.COMP]Cognitive science/Computer scienceAccess control02 engineering and technologycomputer.software_genre01 natural sciences010104 statistics & probability[SCCO.COMP] Cognitive science/Computer science020204 information systems0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]0101 mathematicsSet (psychology)Function (engineering)media_common[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]Structure (mathematical logic)[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Social networkMultimediabusiness.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]Information sensitivity[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer scienceKey (cryptography)[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businesscomputer
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Model Free Control for muscular force by Functional Electrical Stimulation using pulse width modulation

2016

International audience; Functional Electrical Stimulation (FES) is a useful technique for restoring functions for patients with neurological disorders. Muscle activities can be artificially driven through delivery of electrical pulses to skeletal muscles. Typically, muscles are activated by using constant stimulation train with a fixed parameters (amplitude, frequency and pulse width). In addition, the FES systems do not adapt the parameters stimulation to obtain a desired force response during the rehabilitation session. The purpose of this study is to investigate a real-time FES system for adapting automatically the stimulation parameters (stimulation pulse width) to track a desired force…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation0209 industrial biotechnologyPredictsMaterials scienceMathematical-ModelsStimulation02 engineering and technology03 medical and health sciences020901 industrial engineering & automation0302 clinical medicineMuscle-forceFunctional electrical stimulationMuscular force[ SDV.IB ] Life Sciences [q-bio]/BioengineeringFatigueMuscle forceFunctional Electrical Stimulationpulse width modulationbusiness.industryElectrical engineeringFrequencyModel free[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationFesAmplitudeSpinal-Cord InjuriesMuscle[SDV.IB]Life Sciences [q-bio]/Bioengineeringmodel free controlbusiness030217 neurology & neurosurgeryPulse-width modulationBiomedical engineering2016 4th International Conference on Control Engineering & Information Technology (CEIT)
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Needle-shape quality control by shadowgraphic image processing

2011

International audience; We propose a needle-shape quality-control method. To this end, we have devised a new acquisition system that combines a camera and a backlight. Needle measurements are carried out at a micrometric scale using shadowgraphic image processing. Our method not only distinguishes good needles from bad ones, but also allows classifying flawed needles into various categories of defects. This classification is important because some categories of defects can affect the entire production, whereas others do not. The results of our needle-shape quality-control method are validated using real samples directly off the manufacturing line. Needles are correctly classified at >97%, a…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceImage qualityImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyBacklightMathematical morphology[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingneedle020204 information systems[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionquality controlImage sensorRadon transformbusiness.industryGeneral EngineeringImage segmentationAtomic and Molecular Physics and Opticsimage processingmetrology[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingShape analysis (digital geometry)Optical Engineering
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Reaction-Diffusion Network For Geometric Multiscale High Speed Image Processing

2010

International audience; In the framework of heavy mid-level processing for high speed imaging, a nonlinear bi-dimensional network is proposed, allowing the implementation of active curve algorithms. Usually this efficient type of algorithm is prohibitive for real-time image processing due to its calculus charge and the inadequate structure for the use of serial or parallel architectures. Another kind of implementation philosophy is proposed here, by considering the active curve generated by a propagation phenomenon inspired from biological modeling. A programmable nonlinear reaction-diffusion system is proposed under front control and technological constraints. Geometric multiscale processin…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceNonlinear signal processingImage processing02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingType (model theory)Multiscale geometryComputational scienceImage analysisNonlinear signal processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingReaction–diffusion systemDigital image processing0202 electrical engineering electronic engineering information engineeringComputer visionStructure (mathematical logic)Biological modelingbusiness.industry020208 electrical & electronic engineeringNonlinear systemSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Kolmogorov Superposition Theorem and Wavelet Decomposition for Image Compression

2009

International audience; Kolmogorov Superposition Theorem stands that any multivariate function can be decomposed into two types of monovariate functions that are called inner and external functions: each inner function is associated to one dimension and linearly combined to construct a hash-function that associates every point of a multidimensional space to a value of the real interval $[0,1]$. These intermediate values are then associated by external functions to the corresponding value of the multidimensional function. Thanks to the decomposition into monovariate functions, our goal is to apply this decomposition to images and obtain image compression. We propose a new algorithm to decomp…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing010102 general mathematicsMathematical analysisWavelet transform02 engineering and technologyFunction (mathematics)[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingSuperposition theorem01 natural sciencesWavelet packet decompositionWavelet[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Dimension (vector space)[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPoint (geometry)0101 mathematics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingImage compressionMathematics
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Noise removal using a nonlinear two-dimensional diffusion network

1998

Un reseau electrique non lineaire bidimensionnel, constitue de N×N cellules identiques, et modelisant l’equation de Nagumo discrete est presente. A l’aide d’une nouvelle description de la fonction non lineaire, on peut predire analytiquement l’evolution temporelle de la partie coherente du signal, ainsi que celle des perturbations de petites amplitudes qui lui sont superposees. Enfin, des applications a l’amelioration du rapport signal sur bruit, ou au traitement d’images sont suggerees.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingNoise reductionDiffusion networkImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciences010305 fluids & plasmassymbols.namesakeSignal-to-noise ratio[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][NLIN.NLIN-PS] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]0103 physical sciencesElectronic engineering[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]Electrical and Electronic Engineering010306 general physics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematicsSignal processingMathematical analysisWhite noiseNonlinear systemGaussian noisesymbols[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAnnales Des Télécommunications
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