Search results for " nuclear"

showing 10 items of 11776 documents

Impact Evaluation of Innovative Selective Harmonic Mitigation Algorithm for Cascaded H-Bridge Inverter on IPMSM Drive Application

2021

This paper presents a detailed analysis of the use of a novel Harmonic Mitigation algorithm for Cascaded H-Bridge Multilevel Inverter in electrical drives for the transportation field. For this purpose, an enhanced mathematical model of Interior Permanent Magnet Synchronous Motor (IPMSM), that takes into account simultaneously saturation, cross-coupling, spatial harmonics, and iron loss effects, has been used. In detail, this model allows estimating accurately the efficiency and the torque ripple of the IPMSM, crucial parameters for transportation applications. Moreover, two traditional pulse width modulation strategies, Sinusoidal Phase-Shifted and Switching Frequency Optimal Phase-Shifted…

selective harmonic mitigation algorithmComputer scienceImpact evaluationHarmonic mitigationSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciCascaded H-bridge multilevel inverter (CHBMI)torque rippleH bridge inverterTK1-9971Settore ING-IND/31 - ElettrotecnicaefficiencyElectronic engineeringCascaded H-bridge multilevel inverter (CHBMI) efficiency interior permanent magnet synchronous machine (IPMSM) selective harmonic mitigation algorithm torque rippleElectrical engineering. Electronics. Nuclear engineeringinterior permanent magnet synchronous machine (IPMSM)IEEE Open Journal of Industry Applications
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Influence of a Thiolate Chemical Layer on GaAs (100) Biofunctionalization: An Original Approach Coupling Atomic Force Microscopy and Mass Spectrometr…

2013

International audience; Widely used in microelectronics and optoelectronics; Gallium Arsenide (GaAs) is a III-V crystal with several interesting properties for microsystem and biosensor applications. Among these; its piezoelectric properties and the ability to directly biofunctionalize the bare surface, offer an opportunity to combine a highly sensitive transducer with a specific bio-interface; which are the two essential parts of a biosensor. To optimize the biorecognition part; it is necessary to control protein coverage and the binding affinity of the protein layer on the GaAs surface. In this paper; we investigate the potential of a specific chemical interface composed of thiolate molec…

self-assembled thiolate monolayersMaterials scienceAnalytical chemistryproteins grafting02 engineering and technology010402 general chemistryMass spectrometrylcsh:Technology01 natural sciencesArticleGallium arsenideGaAs; self-assembled thiolate monolayers; proteins grafting; AFM; MALDI-TOF MSchemistry.chemical_compoundMonolayerMALDI-TOF MSMoleculeMicroelectronicsGeneral Materials Science[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronicslcsh:Microscopylcsh:QC120-168.85lcsh:QH201-278.5lcsh:Tbusiness.industryGaAs021001 nanoscience & nanotechnology0104 chemical sciencesMatrix-assisted laser desorption/ionizationchemistryChemical engineeringlcsh:TA1-2040Docking (molecular)lcsh:Descriptive and experimental mechanics[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronicslcsh:Electrical engineering. Electronics. Nuclear engineeringAFMlcsh:Engineering (General). Civil engineering (General)0210 nano-technologybusinesslcsh:TK1-9971BiosensorMaterials
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Automated Detection of Microaneurysms Using Scale-Adapted Blob Analysis and Semi-Supervised Learning

2014

International audience; Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are then introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier to detect true MAs. The developed system is built using only…

semi-supervised learningFundus OculiComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMicroaneurysmsblobsHealth Informatics02 engineering and technologySemi-supervised learningFundus (eye)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imagingScale spaceAutomation03 medical and health scienceschemistry.chemical_compound0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineHumansLearningComputer visionBlob analysisMicroaneurysmbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]RetinalDiabetic retinopathymedicine.diseaseAneurysmComputer Science Applicationsdiabetic retinopathyfundus imagechemistryscale-space.scale-space020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)SoftwareRetinopathy
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A Shape-based Statistical Method to Retrieve 2D TRUS-MR Slice Correspondence for Prostate Biopsy

2012

International audience; This paper presents a method based on shape-context and statistical measures to match interventional 2D Trans Rectal Ultrasound (TRUS) slice during prostate biopsy to a 2D Magnetic Resonance (MR) slice of a pre-acquired prostate volume. Accurate biopsy tissue sampling requires translation of the MR slice information on the TRUS guided biopsy slice. However, this translation or fusion requires the knowledge of the spatial position of the TRUS slice and this is only possible with the use of an electro-magnetic (EM) tracker attached to the TRUS probe. Since, the use of EM tracker is not common in clinical practice and 3D TRUS is not used during biopsy, we propose to per…

shape-contextProstate biopsyComputer science[INFO.INFO-IM] Computer Science [cs]/Medical Imaging030230 surgeryTranslation (geometry)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]urologic and male genital diseasesRectal ultrasound030218 nuclear medicine & medical imagingProstate biopsy03 medical and health sciences0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]ProstateBiopsymedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingComputer visionnormalized mutual information.normalized mutual informationmedicine.diagnostic_test[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Magnetic resonance imagingTissue samplingmedicine.anatomical_structure2D TRUS/3D MR correspondenceArtificial intelligenceUltrasonographybusiness
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Charged jet cross sections and properties in proton-proton collisions at $\sqrt{s}=7$ TeV

2015

The differential charged jet cross sections, jet fragmentation distributions, and jet shapes are measured in minimum bias proton-proton collisions at centre-of-mass energy $\sqrt{s}=7$ TeV using the ALICE detector at the LHC. Jets are reconstructed from charged particle momenta in the mid-rapidity region using the sequential recombination $k_{\rm T}$ and anti-$k_{\rm T}$ as well as the SISCone jet finding algorithms with several resolution parameters in the range $R=0.2$ to $0.6$. Differential jet production cross sections measured with the three jet finders are in agreement in the transverse momentum ($p_{\rm T}$) interval $20<p_{\rm T}^{\rm jet,ch}<100$ GeV/$c$. They are also consistent w…

shapes:Kjerne- og elementærpartikkelfysikk: 431 [VDP]parton distributionsMonte Carlo methodP(P)OVER-BAR COLLISIONSALICE Charged jet proton-proton 7 TeVATLAS DETECTOR01 natural sciencesSpectral lineHigh Energy Physics - Experimentdifferential charged jet cross sectionENERGYHigh Energy Physics - Experiment (hep-ex)ALICEFragmentation (mass spectrometry)Nuclear and High Energy Physics differential charged jet cross sectionfragmentation[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Nuclear Experiment (nucl-ex)ROOT-S(NN)=2.76 TEVNuclear ExperimentNuclear Experimentroot-s(nn)=2.76 tevatlas detectorPhysicsLarge Hadron Collidercross sectionPhysicsDetectorCharged particle3. Good health:Mathematics and natural scienses: 400::Physics: 430::Nuclear and elementary particle physics: 431 [VDP]charged jetsPRIRODNE ZNANOSTI. Fizika.:Nuclear and elementary particle physics: 431 [VDP]SHAPESTransverse momentumHADRON-COLLISIONSFRAGMENTATIONpp collisionsenergyParticle physicsNuclear and High Energy PhysicsAstrophysics::High Energy Astrophysical PhenomenaCharged jetVDP::Matematikk og naturvitenskap: 400::Fysikk: 430::Kjerne- og elementærpartikkelfysikk: 431FOS: Physical sciences[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]114 Physical sciencestransverse-momentumNuclear physicsMinimum bias(P)OVER-BAR-P COLLISIONS P(P)OVER-BAR COLLISIONS PP COLLISIONS PARTON DISTRIBUTIONS TRANSVERSE-MOMENTUM SHAPES ALGORITHM ENERGY0103 physical sciences7 TeVNuclear Physics - Experimentproton-protonALGORITHM010306 general physics(p)over-bar-p collisionsPP COLLISIONSta114(P)OVER-BAR-P COLLISIONSVDP::Mathematics and natural scienses: 400::Physics: 430::Nuclear and elementary particle physics: 431010308 nuclear & particles physics:Matematikk og naturvitenskap: 400::Fysikk: 430::Kjerne- og elementærpartikkelfysikk: 431 [VDP]TRANSVERSE-MOMENTUMNATURAL SCIENCES. Physics.(p)over-bar-p collisions ; parton distributions ; transverse-momentum ; root-s(nn)=2.76 tev ; hadron-collisions ; atlas detector ; pp collisions ; fragmentation ; shapes ; energy ; charged jet ; cross section ; proton-proton ; 7 TeVhadron-collisionsPARTON DISTRIBUTIONSALICE; Charged jet; proton-proton; 7 TeVproton-proton collisionsHigh Energy Physics::Experimentcharged jet
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Deep-learning based reconstruction of the shower maximum X max using the water-Cherenkov detectors of the Pierre Auger Observatory

2021

The atmospheric depth of the air shower maximum $X_{\mathrm{max}}$ is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of $X_{\mathrm{max}}$ are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of $X_{\mathrm{max}}$ from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of $X_{\mathrm{max}}$. The reconstruction relies on the signals induced by shower particles in the groun…

showers: energylongitudinal [showers]interaction: modelPhysics::Instrumentation and DetectorsAstronomyCalibration and fitting methods; Cluster finding; Data analysis; Large detector systems for particle and astroparticle physics; Particle identification methods; Pattern recognition01 natural sciencesHigh Energy Physics - ExperimentAugerHigh Energy Physics - Experiment (hep-ex)Particle identification methodscluster findingsurface [detector]ObservatoryLarge detector systemsInstrumentationMathematical PhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)astro-ph.HEPhysicsPattern recognition cluster finding calibration and fitting methodsPhysicsSettore FIS/01 - Fisica Sperimentalemodel [interaction]DetectorAstrophysics::Instrumentation and Methods for AstrophysicsData analysicalibration and fitting methodsenergy [showers]AugerobservatoryPattern recognition cluster finding calibration and fitting methodastroparticle physicsAstrophysics - Instrumentation and Methods for AstrophysicsAstrophysics - High Energy Astrophysical Phenomenaatmosphere [showers]airneural networkAstrophysics::High Energy Astrophysical PhenomenaUHE [cosmic radiation]Data analysisFOS: Physical sciences610Cosmic raydetector: fluorescencePattern recognition0103 physical sciencesddc:530High Energy Physicsddc:610[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]cosmic radiation: UHEstructureparticle physicsnetwork: performance010306 general physicsInstrumentation and Methods for Astrophysics (astro-ph.IM)Ciencias ExactasCherenkov radiationfluorescence [detector]Pierre Auger ObservatoryCalibration and fitting methodsmass spectrum [nucleus]showers: atmospheredetector: surfacehep-ex010308 nuclear & particles physicsLarge detector systems for particle and astroparticle physicsCluster findingFísicaresolutioncalibrationComputational physicsperformance [network]Cherenkov counterAir showerLarge detector systems for particle and astroparticle physicExperimental High Energy PhysicsHigh Energy Physics::Experimentnucleus: mass spectrumshowers: longitudinalRAIOS CÓSMICOSEnergy (signal processing)astro-ph.IM
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Charge Transport Mechanisms in Heavy-Ion Driven Leakage Current in Silicon Carbide Schottky Power Diodes

2016

Under heavy-ion exposure at sufficiently high reverse bias voltages silicon carbide (SiC) Schottky diodes are observed to exhibit gradual increases in leakage current with increasing ion fluence. Heavy-ion exposure alters the overall reverse current-voltage characteristics of these diodes, leaving the forward characteristics practically unchanged. This paper discusses the charge transport mechanisms in the heavy-ion damaged SiC Schottky diodes. A macro model, describing the reverse current-voltage characteristics in the degraded SiC Schottky diodes is proposed. peerReviewed

silicon carbide (SiC)Materials scienceAnnealing (metallurgy)Schottky barrierSchottky diodesMetal–semiconductor junction01 natural sciencesTemperature measurementpower semiconductor deviceschemistry.chemical_compoundstomatognathic system0103 physical sciencesSilicon carbidecurrent-voltage characteristicsElectrical and Electronic EngineeringSafety Risk Reliability and QualityDiode010302 applied physicsta114ta213010308 nuclear & particles physicsbusiness.industrySchottky diodemodelingElectronic Optical and Magnetic MaterialschemistryOptoelectronicsbusinession radiation effectsVoltageIEEE Transactions on Device and Materials Reliability
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A Multi-Projector Calibration Method for Virtual Reality Simulators with Analytically Defined Screens

2017

The geometric calibration of projectors is a demanding task, particularly for the industry of virtual reality simulators. Different methods have been developed during the last decades to retrieve the intrinsic and extrinsic parameters of projectors, most of them being based on planar homographies and some requiring an extended calibration process. The aim of our research work is to design a fast and user-friendly method to provide multi-projector calibration on analytically defined screens, where a sample is shown for a virtual reality Formula 1 simulator that has a cylindrical screen. The proposed method results from the combination of surveying, photogrammetry and image processing approac…

simulatorComputer scienceCalibration (statistics)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyVirtual realitylcsh:Computer applications to medicine. Medical informatics01 natural scienceslcsh:QA75.5-76.95010309 opticsSimulació per ordinadorComputer graphics (images)0103 physical sciences0202 electrical engineering electronic engineering information engineeringimage processing; projector calibration; virtual reality; simulator; surveyingRadiology Nuclear Medicine and imagingPoint (geometry)lcsh:PhotographysurveyingElectrical and Electronic EngineeringRealitat virtualProcess (computing)020207 software engineeringlcsh:TR1-1050Computer Graphics and Computer-Aided DesignSample (graphics)projector calibrationimage processingTask (computing)Photogrammetryvirtual realitylcsh:R858-859.7lcsh:Electronic computers. Computer scienceComputer Vision and Pattern RecognitionImatges ProcessamentJournal of Imaging
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MELCOR per lo Studio Integrale di Sequenze Incidentali su Reattori PWR da 900 MWe e valutazioni preliminari d'impatto a breve e medio raggio

2014

Il presente documento è stato preparato nel corso della seconda annualità dell'AdP ENEA-MSE nell'ambito dell'obiettivo B-Task B_1 (Sviluppo di una Metodologia per Valutazioni di Sicurezza in Condizioni Incidentali o di Pre-Emergenza) della Linea Progettuale 1 (Sviluppo competenze scientifiche nel campo della sicurezza nucleare). Esso riporta i principali risultati della simulazione MELCOR di un transitorio del tipo “short term Station Blackout (SBO)” con possibile rottura dei tubi a U del GV (Steam Generator Tube Rupture - SGTR) indotta da stress termici e un lavoro preliminare di raccolta di informazioni sulle potenzialità presentate da alcune piattaforma di simulazione ad oggi utilizzate …

simulazione MELCOR calpuff calmet frames MM5Settore ING-IND/19 - Impianti Nucleari
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One-loop corrections to light cone wave functions: the dipole picture DIS cross section

2018

We develop methods needed to perform loop calculations in light cone perturbation theory using a helicity basis, refining the method introduced in our earlier work. In particular this includes implementing a consistent way to contract the four-dimensional tensor structures from the helicity vectors with d-dimensional tensors arising from loop integrals, in a way that can be fully automatized. We demonstrate this explicitly by calculating the one-loop correction to the virtual photon to quark-antiquark dipole light cone wave function. This allows us to calculate the deep inelastic scattering cross section in the dipole formalism to next-to-leading order accuracy. Our results, obtained using …

small-xNuclear TheoryGeneral Physics and AstronomyVirtual particleFOS: Physical scienceshiukkasfysiikka01 natural sciences114 Physical sciencesNuclear Theory (nucl-th)Dimensional regularizationHigh Energy Physics - Phenomenology (hep-ph)Light cone0103 physical sciencesTensorHelicity basis010306 general physicskvanttifysiikkaPhysicsDISta114010308 nuclear & particles physicsHelicityLoop integralQCDEVOLUTIONlight-cone perturbation theoryDipoleHigh Energy Physics - PhenomenologyQuantum electrodynamicsREGULARIZATIONcolor glass condensate
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