Search results for " processing"

showing 10 items of 7549 documents

Robust constraint on Lorentz violation using Fermi-LAT gamma-ray burst data

2018

Models of quantum gravity suggest that the vacuum should be regarded as a medium with quantum structure that may have non-trivial effects on photon propagation, including the violation of Lorentz invariance. Fermi Large Area Telescope (LAT) observations of gamma-ray bursts (GRBs) are sensitive probes of Lorentz invariance, via studies of energy-dependent timing shifts in their rapidly-varying photon emissions. In this paper we analyze the Fermi-LAT measurements of high-energy gamma rays from GRBs with known redshifts, allowing for the possibility of energy-dependent variations in emission times at the sources as well as a possible non-trivial refractive index in vacuo for photons. We use st…

Astrophysics and AstronomyPhotongr-qcAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesGeneral Relativity and Quantum Cosmology (gr-qc)AstrophysicsLorentz covariance01 natural sciencesGeneral Relativity and Quantum CosmologyHigh Energy Physics - Phenomenology (hep-ph)0103 physical sciencesSensitivity (control systems)010306 general physicsParticle Physics - PhenomenologyHigh Energy Astrophysical Phenomena (astro-ph.HE)Physicsastro-ph.HE010308 nuclear & particles physicsGeneral Relativity and CosmologyGamma rayhep-phRedshiftHigh Energy Physics - PhenomenologyAstrophysics - High Energy Astrophysical PhenomenaGamma-ray burstEnergy (signal processing)Fermi Gamma-ray Space Telescope
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OBSERVATION OF THE TeV GAMMA-RAY SOURCE MGRO J1908+06 WITH ARGO-YBJ

2012

The extended gamma ray source MGRO J1908+06, discovered by the Milagro air shower detector in 2007, has been observed for about 4 years by the ARGO-YBJ experiment at TeV energies, with a statistical significance of 6.2 standard deviations. The peak of the signal is found at a position consistent with the pulsar PSR J1907+0602. Parametrizing the source shape with a two-dimensional Gauss function we estimate an extension \sigma = 0.49 \pm 0.22 degrees, consistent with a previous measurement by the Cherenkov Array H.E.S.S.. The observed energy spectrum is dN/dE = 6.1 \pm 1.4 \times 10^-13 (E/4 TeV)^{-2.54 \pm 0.36} photons cm^-2 s^-1 TeV^-1, in the energy range 1-20 TeV. The measured gamma ray…

Astrophysics::High Energy Astrophysical PhenomenaAstrophysicsgeneral – pulsars: individual (MGRO J1908+06) [gamma rays]7. Clean energy01 natural sciencesPulsar wind nebulaLuminositySettore FIS/05 - Astronomia E AstrofisicaPulsar0103 physical sciences010303 astronomy & astrophysicspulsarPhysics010308 nuclear & particles physicsgamma rays: general – pulsars: individual (MGRO J1908+06)Settore FIS/01 - Fisica SperimentaleGamma rayAstronomy and Astrophysics(MGRO J1908+06)Air showerCrab Nebula13. Climate actionSpace and Planetary Sciencegamma rayMilagroHigh Energy Physics::ExperimentAstrophysics - High Energy Astrophysical PhenomenaEnergy (signal processing)
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Filter approach to the stochastic analysis of MDOF wind-excited structures

1999

Abstract In this paper, an approach useful for stochastic analysis of the Gaussian and non-Gaussian behavior of the response of multi-degree-of-freedom (MDOF) wind-excited structures is presented. This approach is based on a particular model of the multivariate stochastic wind field based upon a particular diagonalization of the power spectral density (PSD) matrix of the fluctuating part of wind velocity. This diagonalization is performed in the space of eigenvectors and eigenvalues that are called here wind-eigenvalues and wind-eigenvectors, respectively. From the examination of these quantities it can be recognized that the wind-eigenvectors change slowly with frequency while the first wi…

Astrophysics::High Energy Astrophysical PhenomenaGaussianAerospace EngineeringGeometryOcean EngineeringCondensed Matter PhysicWind speedMatrix (mathematics)symbols.namesakePhysics::Atmospheric and Oceanic PhysicsEigenvalues and eigenvectorsMathematicsCivil and Structural EngineeringStochastic processMechanical EngineeringMathematical analysisSpectral densityStatistical and Nonlinear PhysicsFilter (signal processing)White noiseCondensed Matter PhysicsMultivariate stochastic analysis; Filter equations; Wind-excited structuresNuclear Energy and EngineeringPhysics::Space PhysicssymbolsStatistical and Nonlinear Physic
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Hidden information within series of measurements ? four examples from atmospheric science

1985

Whether in classical networks such as meteorological networks of in more recent ones of atmospheric chemistry, a wealth of data is at hand. These data have been evaluated in a manner depending on the purpose of the network. However, much more information is hidden in these time series and waits for discovery. Only the imagination of scientists is needed. Four examples are given which lead to new information about the atmospheric aerosol and the behaviour of the atmosphere. These examples are: “Atmospheric turbidity from sunshine recordings”, “Meteorological drainage area from the variance of observations”, “Location of point sources from air mass trajectories”, and “Total vertical ozone fro…

AtmosphereAtmospheric ScienceData processingAir mass (astronomy)MeteorologySeries (mathematics)Atmospheric chemistryVariance (land use)Environmental ChemistryEnvironmental scienceAtmospheric sciencesAerosolJournal of Atmospheric Chemistry
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Simulation of Future Geostationary Ocean Color Images

2012

The objective of this work is to simulate global images that would be provided by a theoretical ocean color sensor on a geostationary orbit at longitude 0, in order to assess the range of radiance value data reaching the sensor throughout the day for 20 spectral bands similar to those of the Ocean and Land Color Imager (OLCI). The secondary objective is to assess the illumination and viewing geometries that result in sunglint. For this purpose, we combined a radiative transfer model for ocean waters (Hydrolight) and a radiative transfer model for atmosphere (MODTRAN) to construct the simulated radiance images at the sea surface and at the Top-Of-Atmosphere (TOA). Bio-optical data from GlobC…

Atmospheric Science010504 meteorology & atmospheric sciencesMeteorologyMODTRANSolar zenith angleSunglint01 natural sciences010309 opticsAtmospheric radiative transfer codes13. Climate actionOcean color0103 physical sciencesGeostationary orbitRadianceEnvironmental scienceComputers in Earth Sciences[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUSZenith0105 earth and related environmental sciencesRemote sensingIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Including an environmental quality index in a demographic model

2016

This paper presents a new well-being index which allows environmental quality to be measured through CO2 emissions, renewable energies and nuclear power. Its formula derives from a geometric mean used to calculate which things in the human production system warm the planet and which do not. This index has been introduced into a gender-defined stochastic population dynamic mathematical model which measures well-being in a country. The main variables in this model are rates of death, birth, emigration and immigration, as well as three UN indices: Human Development Index, Gender Development Index and Gender Empowerment Index. This model has been extended with variables that allow an environmen…

Atmospheric Science050402 sociologyIndex (economics)Stochastic modellingWell-beingPopulationSustainable development.02 engineering and technologyManagement Monitoring Policy and Law0504 sociology0202 electrical engineering electronic engineering information engineeringEconomicsEconometricsGender Development IndexHuman Development IndexeducationEnvironmental qualityEnvironmental qualitySustainable developmentGlobal and Planetary Changeeducation.field_of_studybusiness.industry05 social sciencesEnvironmental resource managementDemographic modelSustainability020201 artificial intelligence & image processingMATEMATICA APLICADAbusinessInternational Journal of Global Warming
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2012

Abstract. A compact mobile aerosol research laboratory (MoLa) for stationary and mobile measurements of aerosol and trace gas characteristics was developed at the Max Planck Institute for Chemistry (MPIC) in Mainz, Germany. Major efforts were made to design an aerosol inlet system which is optimized and characterised for both, stationary and mobile measurements using a particle loss modelling approach. The instrumentation on board allows the determination of a multitude of physical and chemical aerosol parameters, for example particle number and mass concentration (PM1/2.5/10), particle size distributions in the diameter range 6 nm up to 32 μm, and chemical composition of the sub-micron aer…

Atmospheric ScienceData processingData acquisitionMeteorologyParticle numberInstrumentationMass concentration (chemistry)Water vaporTrace gasAerosolRemote sensingAtmospheric Measurement Techniques
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Comparative study of three satellite image time-series decomposition methods for vegetation change detection

2018

International audience; Satellite image time-series (SITS) methods have contributed notably to detection of global change over the last decades, for instance by tracking vegetation changes. Compared with multi-temporal change detection methods, temporally highly resolved SITS methods provide more information in a single analysis, for instance on the type and consistency of change. In particular, SITS decomposition methods show a great potential in extracting various components from non-stationary time series, which allows for an improved interpretation of the temporal variability. Even though many case studies have applied SITS decomposition methods, a systematic comparison of common algori…

Atmospheric ScienceNon-stationary010504 meteorology & atmospheric sciencesBFASTSTL0211 other engineering and technologiesMRA-WT02 engineering and technology01 natural sciencesNormalized Difference Vegetation Indexlcsh:OceanographyDecomposition (computer science)medicineSatellite imagerylcsh:GC1-1581Computers in Earth SciencesNDVI time series021101 geological & geomatics engineering0105 earth and related environmental sciencesGeneral Environmental ScienceRemote sensingApplied Mathematicslcsh:QE1-996.5Global change15. Life on landSeasonalitymedicine.diseaselcsh:GeologyEnvironmental scienceChange detectionSatellite Image Time Seriesmedicine.symptomVegetation (pathology)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingChange detection
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Spectral Observations of Optical Emissions Associated with Terrestrial Gamma-Ray Flashes

2021

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Atmospheric SciencePhoton010504 meteorology & atmospheric sciencesOptical measurementsAtmospheric Composition and StructureAstrophysics010502 geochemistry & geophysics01 natural sciences7. Clean energyCloud OpticsCloud/Radiation InteractionResearch LetterStreamer0105 earth and related environmental sciencesPhysicsScatteringPulse (signal processing)ISSResearchGamma rayAtmosphärische SpurenstoffeLightningTGFASIMGeophysicsAmplitude13. Climate actionLeaderGeneral Earth and Planetary Sciences
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Examining the effect of adverse weather on road transportation using weather and traffic sensors.

2018

Adverse weather related to reduced visibility caused by fog and rain can seriously affect the mobility and safety of drivers. It is meaningful to develop effective intelligent transportation system (ITS) strategies to mitigate the negative effects of these different types of adverse weather related to reduced visibility by investigating the effect of rain and fog on traffic parameters. A number of previous researches focused on analyzing the effect of adverse weather related to reduced visibility by using simulated traffic and weather data. There are few researchers that addressed the impact of adverse weather instances using real-time data. Moreover, this paper conducts comprehensive inves…

Atmospheric ScienceRainIntelligenceSocial Scienceslcsh:MedicineTransportation02 engineering and technologyPreliminary analysisFogMathematical and Statistical TechniquesRisk FactorsMedicine and Health Sciences0202 electrical engineering electronic engineering information engineeringPsychologyPublic and Occupational Healthlcsh:ScienceIntelligent transportation systemMultidisciplinaryAdverse weatherStatistics05 social sciencesAccidents TrafficRegression analysisTransportation InfrastructureAutomobile drivingPhysical SciencesEngineering and Technology020201 artificial intelligence & image processingSafetyResearch ArticleAutomobile DrivingSafety ManagementMeteorologyResearch and Analysis MethodsCivil EngineeringMeteorology0502 economics and businessHumansStatistical MethodsVisibilityWeatherAnalysis of Variance050210 logistics & transportationlcsh:RTraffic SafetyCognitive PsychologyBiology and Life SciencesRoadsLogistic ModelsWeather dataEarth SciencesCognitive ScienceEnvironmental sciencelcsh:QMathematicsNeurosciencePLoS ONE
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