Search results for "data set"

showing 10 items of 154 documents

Measurement of integrated luminosity and center-of-mass energy of data taken by BESIII at

2017

Chinese physics / C 41(11), 113001 (2017). doi:10.1088/1674-1137/41/11/113001

Nuclear and High Energy PhysicsPhysics::Instrumentation and DetectorsAstrophysics::High Energy Astrophysical Phenomena01 natural sciences530law.inventionNuclear physicslaw0103 physical sciencesddc:530Nuclear Experiment010306 general physicsColliderInstrumentationAstrophysics::Galaxy AstrophysicsBhabha scatteringPhysicsLuminosity (scattering theory)010308 nuclear & particles physicsDetectorAstronomy and AstrophysicsCollisionData setHigh Energy Physics::ExperimentCenter of massAstrophysics::Earth and Planetary AstrophysicsEnergy (signal processing)
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Artificial neural networks for neutron/ γ discrimination in the neutron detectors of NEDA

2020

Three different Artificial Neural Network architectures have been applied to perform neutron/? discrimination in NEDA based on waveform and time-of-flight information. Using the coincident ?-rays from AGATA, we have been able to measure and compare on real data the performances of the Artificial Neural Networks as classifiers. While the general performances are quite similar for the data set we used, differences, in particular related to the computing times, have been highlighted. One of the Artificial Neural Network architecture has also been found more robust to time misalignment of the waveforms. Such a feature is of great interest for online processing of waveforms. Narodowe Centrum Nau…

Nuclear and High Energy Physics[formula omitted]-ray spectroscopyNeutron detectorComputer Science::Neural and Evolutionary Computationγ -ray spectroscopy[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]01 natural sciences030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineCoincident0103 physical sciencesMachine learningNeutron detectionWaveformNeutron[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]InstrumentationComputingMilieux_MISCELLANEOUSPhysicsArtificial neural networkArtificial neural networksPulse-shape discriminationn- γ discrimination010308 nuclear & particles physicsbusiness.industryPattern recognitionData setn-[formula omitted] discriminationFeature (computer vision)n-? discriminationAGATAArtificial intelligencey-ray spectroscopybusiness
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Data Blinding for the nEDM Experiment at PSI

2020

Psychological bias towards, or away from, prior measurements or theory predictions is an intrinsic threat to any data analysis. While various methods can be used to try to avoid such a bias, e.g. actively avoiding looking at the result, only data blinding is a traceable and trustworthy method that can circumvent the bias and convince a public audience that there is not even an accidental psychological bias. Data blinding is nowadays a standard practice in particle physics, but it is particularly difficult for experiments searching for the neutron electric dipole moment (nEDM), as several cross measurements, in particular of the magnetic field, create a self-consistent network into which it …

Nuclear and High Energy Physicsdata analysis methodPhysics - Instrumentation and DetectorsOffset (computer science)BlindingNeutron electric dipole momentOther Fields of PhysicsFOS: Physical sciencesSeparate analysis[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]nucl-ex01 natural sciencesHigh Energy Physics - Experimentphysics.data-anHigh Energy Physics - Experiment (hep-ex)0103 physical sciences[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Nuclear Physics - Experiment[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]Nuclear Experiment (nucl-ex)Detectors and Experimental Techniques010306 general physicsNuclear Experimentphysics.ins-detPhysicsn: electric moment010308 nuclear & particles physicshep-exProbability and statisticsInstrumentation and Detectors (physics.ins-det)Data setSpecial Article - New Tools and TechniquesTrustworthinessPhysics - Data Analysis Statistics and ProbabilityAlgorithmData Analysis Statistics and Probability (physics.data-an)Particle Physics - Experiment[PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]
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Automated Detection of Optic Disc Location in Retinal Images

2008

This contribution presents an automated method to locate the optic disc in color fundus images. The method uses texture descriptors and a regression based method in order to determine the best circle that fits the optic disc. The best circle is chosen from a set of circles determined with an innovative method, not using the Hough transform as past approaches. An evaluation of the proposed method has been done using a database of 40 images. On this data set, our method achieved 95% success rate for the localization of the optic disc and 70% success rate for the identification of the optic disc contour (as a circle).

Optic Disc Image Analysis DetectionSettore INF/01 - InformaticaPixelComputer sciencebusiness.industryImage processingFundus (eye)Object detectionHough transformlaw.inventionData setmedicine.anatomical_structureImage texturelawComputer Science::Computer Vision and Pattern RecognitionmedicineComputer visionArtificial intelligencebusinessOptic disc2008 21st IEEE International Symposium on Computer-Based Medical Systems
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Temperature Distribution of a Non-flaring Active Region from Simultaneous Hinode XRT and EIS Observations

2011

We analyze coordinated Hinode XRT and EIS observations of a non-flaring active region to investigate the thermal properties of coronal plasma taking advantage of the complementary diagnostics provided by the two instruments. In particular we want to explore the presence of hot plasma in non-flaring regions. Independent temperature analyses from the XRT multi-filter dataset, and the EIS spectra, including the instrument entire wavelength range, provide a cross-check of the different temperature diagnostics techniques applicable to broad-band and spectral data respectively, and insights into cross-calibration of the two instruments. The emission measure distribution, EM(T), we derive from the…

PhysicsImaging spectrometerGamma rayFOS: Physical sciencesAstronomy and AstrophysicsPlasmaAstrophysicsabundances Sun: activity Sun: corona Sun: UV radiation Sun: X-rays gamma rays techniques: spectroscopic [Sun]Sun: abundances Sun: activity Sun: corona Sun: UV radiation Sun: X-rays gamma rays techniques: spectroscopicSpectral linelaw.inventionTelescopeData setSettore FIS/05 - Astronomia E AstrofisicaAstrophysics - Solar and Stellar AstrophysicsSpace and Planetary SciencelawExtreme ultravioletThermalSolar and Stellar Astrophysics (astro-ph.SR)
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Search for the rare decayBs0→μ+μ−

2013

Contains fulltext : 111249pub.pdf (Publisher’s version ) (Open Access) Contains fulltext : 111249.pdf (Author’s version preprint ) (Open Access)

PhysicsNuclear and High Energy PhysicsParticle physics010308 nuclear & particles physicsTevatronD0 experiment01 natural scienceslaw.inventionData setNuclear physicslawExperimental High Energy Physics0103 physical sciencesComputingMethodologies_DOCUMENTANDTEXTPROCESSINGPhysics::Accelerator PhysicsHigh Energy Physics::ExperimentFermilab010306 general physicsColliderPhysical Review D
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Measurement of the branching fraction for ψ(3770) → γχc0

2016

Kolcu, Onur Buğra (Arel Author) --- Makale 70 yazarlıdır.

PhysicsNuclear and High Energy PhysicsParticle physicsBESIII детектор010308 nuclear & particles physicsBranching fractionElectron–positron annihilationMonte Carlo methodDetectorCollision01 natural scienceslcsh:QC1-999NOData setNuclear physicsBEPCII коллайдер0103 physical sciences010306 general physicslcsh:Physics
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Analysis of the atmospheric neutrino data in terms of 3-neutrino oscillations

2000

A global analysis of atmospheric and reactor neutrino data is presented in terms of three-neutrino oscillations. We consider in our analysis both contained events and upward-going neutrino-induced muon events, including the previous data samples of Frejus, IMB, Nusex, and Kamioka experiments as well as the full 71 kton-yr (1144 days) Super-Kamiokande data set, the recent 5.1 kton-yr contained events of Soudan-2 and the results on upgoing muons from the MACRO detector. After presenting the results for the analysis of atmospheric data alone, we add to our data sample the reactor bound of the CHOOZ experiment, showing and important complementarity between the atmospheric and reactor limits whi…

PhysicsNuclear and High Energy PhysicsParticle physicsMuonDetectorFOS: Physical sciencesCHOOZAtomic and Molecular Physics and OpticsData setHigh Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)High Energy Physics::ExperimentReactor neutrinoAtmospheric neutrinoNeutrino oscillationParticle Physics - Phenomenology
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Commissioning and performance of the Belle II pixel detector

2021

Belle-II DEPFET and PXD Collaboration: et al.

PhysicsNuclear and High Energy PhysicsPixel010308 nuclear & particles physicsPhysics beyond the Standard Model01 natural sciencesNoise (electronics)law.inventionData setNuclear physicsPower consumptionlaw0103 physical sciencesField-effect transistorColliderInstrumentationPixel detector
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Partition function based analysis of cosmic microwave background maps

1999

We present an alternative method to analyse cosmic microwave background (CMB) maps. We base our analysis on the study of the partition function. This function is used to examine the CMB maps, making use of the different information embedded at different scales and moments. Using the partition function in a likelihood analysis in two dimensions (Qrms-PS, n), we find the best-fitting model to the best data available at present (the COBE–DMR 4 years data set). By means of this analysis we find a maximum in the likelihood function for n=1.8-0.65+0.35 and Qrms-PS = 10-2.5+3μ K (95 per cent confidence level) in agreement with the results of other similar analyses [Smoot et al. (1 yr), Bennet et a…

PhysicsPartition function (quantum field theory)Cosmic microwave backgroundFísicaAstronomy and AstrophysicsMultifractal systemFunction (mathematics)Measure (mathematics)Cosmic microwave backgroundData setTheoretical physicsDistribution (mathematics)Methods: data analysisSpace and Planetary ScienceStatistical physicsdata analysis [Methods]Likelihood functionMonthly Notices of the Royal Astronomical Society
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