Search results for "APPLICATIONS"

showing 10 items of 4965 documents

Viewpoint: Atomic-Scale Design Protocols toward Energy, Electronic, Catalysis, and Sensing Applications

2019

Nanostructured materials are essential building blocks for the fabrication of new devices for energy harvesting/storage, sensing, catalysis, magnetic, and optoelectronic applications. However, because of the increase of technological needs, it is essential to identify new functional materials and improve the properties of existing ones. The objective of this Viewpoint is to examine the state of the art of atomic-scale simulative and experimental protocols aimed to the design of novel functional nanostructured materials, and to present new perspectives in the relative fields. This is the result of the debates of Symposium I "Atomic-scale design protocols towards energy, electronic, catalysis…

010405 organic chemistrySensing applicationsChemistryNanostructured materials: Physics [G04] [Physical chemical mathematical & earth Sciences]Physik (inkl. Astronomie)010402 general chemistry01 natural sciencesAtomic units0104 chemical sciencesInorganic Chemistry: Physique [G04] [Physique chimie mathématiques & sciences de la terre]Systems engineeringMultilayers | Interfaces (materials) | Individual layermaterials theory computational DFT modellingPhysical and Theoretical ChemistryEnergy harvestingEnergy (signal processing)Inorganic Chemistry
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The MIRS computer package for modeling the rovibrational spectra of polyatomic molecules

2003

International audience; The MIRS spectroscopic software for the modeling of ro-vibrational spectra of polyatomic molecules is presented. It is designed for the global treatment of complex band systems of molecules to take full account of symmetry properties. It includes e cient algorithms based on the irreducible tensor formalism. Predictions and simultaneous data fi tting (positions and intensities) are implemented as well as advanced options related to group theory algebra. Illustrative examples on CH3D, CH4, CH3Cl and PH3 are reported and the present status of data available is given. It is written in C++ for standard PC computer operating under Windows. The full package including on-lin…

010504 meteorology & atmospheric sciences01 natural sciencesSpectral lineSoftwareComputer package0103 physical sciencesMoleculeSpectroscopy0105 earth and related environmental sciencesPhysics[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]RadiationSpectroscopic database010304 chemical physicsbusiness.industryPolyatomic ionRotational–vibrational spectroscopyMolecular spectroscopyAtmospheric applicationsAtomic and Molecular Physics and OpticsComputational physics[ PHYS.PHYS.PHYS-AO-PH ] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]Rotation vibrationCurve fittingbusinessInfraredGroup theorySoftware
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Digital thermal monitoring of the Amazon forest: an intercomparison of satellite and reanalysis products

2015

Remote sensing and climate digital products have become increasingly available in recent years. Access to these products has favored a variety of Digital Earth studies, such as the analysis of the impact of global warming over different biomes. The study of the Amazon forest response to drought has recently received particular attention from the scientific community due to the occurrence of extreme droughts and anomalous warming over the last decade. This paper focuses on the differences observed between surface thermal anomalies obtained from remote sensing moderate resolution imaging spectroradiometer (MODIS) and climatic (ERA-Interim) monthly products over the Amazon forest. With a few e…

010504 meteorology & atmospheric sciences0208 environmental biotechnologyBiome02 engineering and technology01 natural sciences020801 environmental engineeringComputer Science ApplicationsGeographyRemote sensing (archaeology)Effects of global warmingClimatologyGeneral Earth and Planetary SciencesCommon spatial patternSatellite imagerySatelliteModerate-resolution imaging spectroradiometerSoftwareDigital Earth0105 earth and related environmental sciences
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Intercomparison of Soil Moisture Retrieved from GNSS-R and from Passive L-Band Radiometry at the Valencia Anchor Station

2019

In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on the intercomparison of soil moisture monitoring from Global Navigation Satellite System Reflectometry (GNSS-R) signals and passive L-band microwave radiometer observations at the Valencia Anchor Station is introduced. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and a dual-pol down-looking antenna for receiving LHCP (left-hand circular polarization) and RHCP (right-hand circular polarization) reflected signals from the soil surface. Data were collected from the three different antennas through the two channels of Oceanpal GNSS-R receiver and, in addition, calibration …

010504 meteorology & atmospheric sciences0211 other engineering and technologies02 engineering and technologyELBARA-II radiometerlcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical Chemistrylcsh:TP1-1185L-band radiometryElectrical and Electronic EngineeringOceanpalReflectometryInstrumentationWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingValencia Anchor StationRadiometerMoistureGNSS-RMicrowave radiometerAtomic and Molecular Physics and OpticsGNSS applicationsSoil waterEnvironmental scienceRadiometrysoil moistureSensors
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Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

2020

Abstract This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological–Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key par…

010504 meteorology & atmospheric sciencesAdvanced very-high-resolution radiometerImage and Video Processing (eess.IV)0211 other engineering and technologies02 engineering and technologyVegetationElectrical Engineering and Systems Science - Image and Video Processing01 natural sciencesAtomic and Molecular Physics and OpticsComputer Science Applications13. Climate actionKrigingFOS: Electrical engineering electronic engineering information engineeringRadiative transferRange (statistics)Environmental scienceSatelliteSensitivity (control systems)Computers in Earth SciencesLeaf area indexEngineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingISPRS Journal of Photogrammetry and Remote Sensing
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A Regional Geography Approach to Understanding the Environmental Changes as a Consequence of the COVID-19 Lockdown in Highly Populated Spanish Cities

2021

Spain has been highly impacted by the COVID-19 pandemic, which is reflected at different scales. From an economic point of view, lockdowns and the reduction of activities have damaged the country (e.g., complete lockdown from March 13 to June 21, 2020). However, it is not clear if the associated environmental impacts could be observed in 2020. Currently, studies on the effects of the lockdown (e.g., decrease in economic activities, transport and social communication) on specific parameters related to climate change, such as air temperature or air pollution, due to a drastic decrease in human activities are rare. They are focused on specific cities and short periods of time. Therefore, the m…

010504 meteorology & atmospheric sciencesAir pollutionClimate change010501 environmental sciencesmedicine.disease_cause01 natural scienceslcsh:Technologylcsh:ChemistryEnvironmental protectionUrban climatemedicineGeneral Materials ScienceInstrumentationAir quality indexlcsh:QH301-705.5climate variations0105 earth and related environmental sciencesFluid Flow and Transfer ProcessesPollutantlcsh:TProcess Chemistry and TechnologyGeneral EngineeringCOVID-19data miningRegional geographylcsh:QC1-999Computer Science ApplicationsGeographylcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Scale (social sciences)epidemiologyregional geographylcsh:Engineering (General). Civil engineering (General)Tourismlcsh:PhysicsApplied Sciences
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Statistical retrieval of atmospheric profiles with deep convolutional neural networks

2019

Abstract Infrared atmospheric sounders, such as IASI, provide an unprecedented source of information for atmosphere monitoring and weather forecasting. Sensors provide rich spectral information that allows retrieval of temperature and moisture profiles. From a statistical point of view, the challenge is immense: on the one hand, “underdetermination” is common place as regression needs to work on high dimensional input and output spaces; on the other hand, redundancy is present in all dimensions (spatial, spectral and temporal). On top of this, several noise sources are encountered in the data. In this paper, we present for the first time the use of convolutional neural networks for the retr…

010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesWeather forecasting02 engineering and technologycomputer.software_genreAtmospheric measurements01 natural sciencesConvolutional neural networkLinear regressionRedundancy (engineering)Information retrievalInfrared measurementsComputers in Earth SciencesEngineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesArtificial neural networkbusiness.industryDeep learningDimensionality reductionPattern recognitionAtomic and Molecular Physics and OpticsComputer Science Applications13. Climate actionNoise (video)Artificial intelligencebusinesscomputerNeural networksISPRS Journal of Photogrammetry and Remote Sensing
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Automotive Radar in a UAV to Assess Earth Surface Processes and Land Responses

2020

The use of unmanned aerial vehicles (UAVs) in earth science research has drastically increased during the last decade. The reason being innumerable advantages to detecting and monitoring various environmental processes before and after certain events such as rain, wind, flood, etc. or to assess the current status of specific landforms such as gullies, rills, or ravines. The UAV equipped sensors are a key part to success. Besides commonly used sensors such as cameras, radar sensors are another possibility. They are less known for this application, but already well established in research. A vast number of research projects use professional radars, but they are expensive and difficult to hand…

010504 meteorology & atmospheric sciencesComputer scienceUAVReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION0211 other engineering and technologiesComputerApplications_COMPUTERSINOTHERSYSTEMS77 GHz02 engineering and technologylcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical Chemistrylaw.inventionARS-408lawlcsh:TP1-1185ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSElectrical and Electronic EngineeringRadarInstrumentationARS-404021101 geological & geomatics engineering0105 earth and related environmental sciencesRadarAtomic and Molecular Physics and OpticsEarth surfaceAutomotive radarKey (cryptography)Sensors
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Estimating Missing Information by Cluster Analysis and Normalized Convolution

2018

International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.

010504 meteorology & atmospheric sciencesComputer sciencemedia_common.quotation_subjectReal-time computingEnergy Engineering and Power Technology02 engineering and technologyIterative reconstructionsmart city dealsCluster (spacecraft)01 natural sciencesIndustrial and Manufacturing Engineeringnormalized convolutionstandard clustering technique[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ConvolutionArtificial IntelligenceSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringLimit (mathematics)SimplicityCluster analysisInstrumentationad-hoc sensors0105 earth and related environmental sciencesmedia_commonSettore INF/01 - InformaticaRenewable Energy Sustainability and the EnvironmentComputer Science Applications1707 Computer Vision and Pattern Recognitionenvironmental informationmissing informationComputer Networks and CommunicationKernel (image processing)020201 artificial intelligence & image processingcluster analysis2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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Transferring deep learning models for cloud detection between Landsat-8 and Proba-V

2020

Abstract Accurate cloud detection algorithms are mandatory to analyze the large streams of data coming from the different optical Earth observation satellites. Deep learning (DL) based cloud detection schemes provide very accurate cloud detection models. However, training these models for a given sensor requires large datasets of manually labeled samples, which are very costly or even impossible to create when the satellite has not been launched yet. In this work, we present an approach that exploits manually labeled datasets from one satellite to train deep learning models for cloud detection that can be applied (or transferred) to other satellites. We take into account the physical proper…

010504 meteorology & atmospheric sciencesExploitComputer sciencebusiness.industryDeep learning0211 other engineering and technologiesCloud detectionCloud computing02 engineering and technologyEarth observation satellitecomputer.software_genre01 natural sciencesConvolutional neural networkAtomic and Molecular Physics and OpticsComputer Science ApplicationsSatelliteData miningArtificial intelligenceComputers in Earth SciencesbusinessTransfer of learningEngineering (miscellaneous)computer021101 geological & geomatics engineering0105 earth and related environmental sciencesISPRS Journal of Photogrammetry and Remote Sensing
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