Search results for " Parallel"

showing 10 items of 224 documents

Toward fast and accurate emergency cases detection in BSNs

2020

International audience; In body sensor networks (BSNs), medical sensors capture physiological data from the human body and send them to the coordinator who act as a gateway to health care. The main aim of BSNs is to save peoples' lives. Therefore, fast and correct detection of emergencies while maintaining low-energy consumption of sensors is essential requirement of BSNs. In this study, the authors propose a new adaptive data sampling approach, where the sampling ratio is adapted based on the sensed data variation. The idea is to use the modified version of the cumulative sum (CUSUM) algorithm (modified CUSUM) that they previously proposed for wireless sensor networks to monitor the data v…

Data variabilityProperty (programming)Computer science010401 analytical chemistryReal-time computing020206 networking & telecommunicationsCUSUM02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]01 natural sciences[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationIndustrial and Manufacturing Engineering0104 chemical sciences[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Data samplingSampling (signal processing)[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Default gateway0202 electrical engineering electronic engineering information engineering[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Wireless sensor network
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Etude numérique d'équations aux dérivées partielles non linéaires et dispersives

2011

Numerical analysis becomes a powerful resource in the study of partial differential equations (PDEs), allowing to illustrate existing theorems and find conjectures. By using sophisticated methods, questions which seem inaccessible before, like rapid oscillations or blow-up of solutions can be addressed in an approached way. Rapid oscillations in solutions are observed in dispersive PDEs without dissipation where solutions of the corresponding PDEs without dispersion present shocks. To solve numerically these oscillations, the use of efficient methods without using artificial numerical dissipation is necessary, in particular in the study of PDEs in some dimensions, done in this work. As stud…

Davey-Stewartson systems[ MATH.MATH-GM ] Mathematics [math]/General Mathematics [math.GM]equations dispersivesdispersive shocksexponential time-differencing[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM][MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph]spectral methodschocs dispersifsnumerical methodsdispersive equationsNo english keywordssplit stepschemas de decomposition d'operateursmethodes spectrales[MATH.MATH-MP] Mathematics [math]/Mathematical Physics [math-ph]Kadomtsev-Petviashvili equationintegrating factor methodparallel computing[ MATH.MATH-MP ] Mathematics [math]/Mathematical Physics [math-ph]Pas de mot clé en français[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]methodes numeriquesblow upequation de Kadomtsev-PetviashviliIntegrateurs exponentielssystemes de Davey-Stewartsoncalcul parallele
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Portable Video Supercomputing

2004

As inexpensive imaging chips and wireless telecommunications are incorporated into an increasing array, of portable products, the need for high efficiency, high throughput embedded processing will become an important challenge in computer architecture. Videocentric applications, such wireless videoconferencing, real-time video enhancement and analysis, and new, immersive modes of distance education, will exceed the computational capabilities of current microprocessor and digital signal processor (DSP) architectures. A new class of embedded computers, portable video supercomputers, will combine supercomputer performance with the energy efficiency required for deployment in portable systems. …

Digital signal processorComputer scienceData parallelismVideo processingSupercomputerTheoretical Computer ScienceMicroarchitectureMPEG encodinglaw.inventionMicroprocessorComputational Theory and MathematicsComputer architectureHardware and ArchitecturelawSIMDSoftware
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"Table 19" of "Measurement of event shape and inclusive distributions at s**(1/2) = 130-GeV and 136-GeV."

1997

2-jet rate for the Durham Algorithm.

Dijet Production133.0Astrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringIntegrated Cross SectionExclusiveHigh Energy Physics::ExperimentJet ProductionE+ E- --> 2JETCross SectionSIGComputer Science::Distributed Parallel and Cluster Computing
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"Table 27" of "Tuning and test of fragmentation models based on identified particles and precision event shape data."

1996

Differential 2-jet rate for the Durham Algorithm. Corrected to final state particles. YCUT is the jet finding cutt-off parameter.

Dijet ProductionDN/DSIGAstrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringExclusiveHigh Energy Physics::Experiment91.2Single Differential DistributionJet ProductionE+ E- --> 2JETComputer Science::Distributed Parallel and Cluster Computing
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Online Scheduling of Task Graphs on Heterogeneous Platforms

2020

Modern computing platforms commonly include accelerators. We target the problem of scheduling applications modeled as task graphs on hybrid platforms made of two types of resources, such as CPUs and GPUs. We consider that task graphs are uncovered dynamically, and that the scheduler has information only on the available tasks, i.e., tasks whose predecessors have all been completed. Each task can be processed by either a CPU or a GPU, and the corresponding processing times are known. Our study extends a previous $4\sqrt{m/k}$ 4 m / k -competitive online algorithm by Amaris et al. [1] , where $m$ m is the number of CPUs and $k$ k the number of GPUs ( $m\geq k$ m ≥ k ). We prove that no online…

Discrete mathematics[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]020203 distributed computingScheduleCompetitive analysisComputer scienceHeuristicSchedulingOnline algorithmsProcessor schedulingSymmetric multiprocessor system02 engineering and technologyUpper and lower boundsGraphScheduling (computing)Computational Theory and MathematicsHardware and ArchitectureSignal Processing0202 electrical engineering electronic engineering information engineeringTask analysisTask graphsHeterogeneous computingOnline algorithm[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]
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Performance analysis of optical imaging systems based on the fractional fourier transform

1998

Some image quality parameters, such as the Strehl ratio and the optical transfer function, are analysed in the generalized phase-space, or x-p domain, of the fractional Fourier transform associated with a modified one-dimensional pupil function. Some experimental results together with computer simulations are performed which illustrate the tolerance to defocus of different apertures.

Discrete-time Fourier transformStrehl ratioIngenieríaDiscrete Fourier transformsymbols.namesakePupil functionOpticsOptical transfer functionPupil functionComputer Science::Distributed Parallel and Cluster ComputingCiencias ExactasPhysicsbusiness.industryPhysicsAstrophysics::Instrumentation and Methods for AstrophysicsShort-time Fourier transformStrehl ratioOpticsDiscrete Fourier transformFourier analysisAtomic and Molecular Physics and OpticsFractional Fourier transformFractional Fourier transformOptical transfer functionFourier analysisShort-time Fourier transformsymbolsbusinessDiscrete-time Fourier transformJournal of Modern Optics
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"Table 14" of "Studies of quantum chromodynamics with the ALEPH detector"

1997

Measure n-jet rates using the Durham cluster algorithm as a function of thejet-resolution parameter YCUT.

E+ E- --> 3JET XE+ E- --> HADRONSE+ E- --> Z0Integrated Cross Section91.2Jet ProductionCross SectionSIGInclusiveE+ E- ScatteringExclusiveHigh Energy Physics::ExperimentR measurementComputer Science::Distributed Parallel and Cluster Computing
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"Table 21" of "Measurement of event shape and inclusive distributions at s**(1/2) = 130-GeV and 136-GeV."

1997

4-jet rate for the Durham Algorithm.

E+ E- --> 4JET133.0Astrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringIntegrated Cross SectionExclusiveHigh Energy Physics::ExperimentJet ProductionCross SectionSIGComputer Science::Distributed Parallel and Cluster Computing
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"Table 31" of "Tuning and test of fragmentation models based on identified particles and precision event shape data."

1996

Differential 4-jet rate for the Durham Algorithm. Corrected to final state particles. YCUT is the jet finding cutt-off parameter.

E+ E- --> 4JETDN/DSIGAstrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringExclusiveHigh Energy Physics::Experiment91.2Single Differential DistributionJet ProductionComputer Science::Distributed Parallel and Cluster Computing
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