Search results for " INFORMATIQUE"

showing 10 items of 54 documents

Morphological characterisation of soil structure in tilled fields: from a diagnosis method to the modelling of structural changes over time

2004

Characterisation of soit structure within the tilled layer of cultivated fields is crucial because the importance of this soil characteristic on the biological, chemical and physical properties of the soil and its repercussions on water cycle, root growth and functioning. We present in this paper a method for field characterisation of soil structure. This method, practised since the 1970s, was designed for field diagnosis of the effects of cropping systems on soil structure. It is based on a stratification of the observation face of a pit dug perpendicular to the direction of tillage and traffic: spatial compartments are distinguished, according to the nature of the mechanical stresses they…

P33 - Chimie et physique du solhttp://aims.fao.org/aos/agrovoc/c_24242Travail du solCompactionSoil ScienceSoil scienceTrait morphologique du sol010501 environmental sciences[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study01 natural sciencesSoil surveyMouvement de l'eau dans le solhttp://aims.fao.org/aos/agrovoc/c_7209http://aims.fao.org/aos/agrovoc/c_7163http://aims.fao.org/aos/agrovoc/c_2018AGRONOMIEPropriété physicochimique du solPorosity[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil studyhttp://aims.fao.org/aos/agrovoc/c_34900ComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesEarth-Surface Processes2. Zero hungerStructure du solU10 - Informatique mathématiques et statistiqueshttp://aims.fao.org/aos/agrovoc/c_7182Soil morphologyModèle de simulation04 agricultural and veterinary sciences15. Life on landProctor compaction testMotte de terreCompactage du solSoil gradationTillagePratique culturaleSoil structureMécanique du sol040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental sciencehttp://aims.fao.org/aos/agrovoc/c_7196Agronomy and Crop Sciencehttp://aims.fao.org/aos/agrovoc/c_7771http://aims.fao.org/aos/agrovoc/c_7177http://aims.fao.org/aos/agrovoc/c_7179
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Adapter localement les prévisions climatiques saisonnières : désagrégation stochastique et interpolation spatiale.

2013

6 pages; International audience; Un panorama est fait des méthodes de descente d’échelles permettant de passer de prévisions climatiques saisonnières de large-échelle à des séries locales journalières. L’exemple des générateurs stochastiques de temps est appliqué à la prévision des récoltes de sorgho au Kenya, dans le cadre du programme ANR PICREVAT. Une méthode d’interpolation spatiale des paramètres des générateurs est testée, pour obtenir des séries journalières de précipitations en tout point du territoire. Les séries générées sont utilisées en entrée du modèle agronomique SARRA-H.

P40 - Météorologie et climatologieF01 - Culture des plantesU10 - Informatique mathématiques et statistiques[SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry[SDU.STU.GC] Sciences of the Universe [physics]/Earth Sciences/Geochemistrydésagrégationgénérateur stochastiqueprécipitationsrendementsprévision saisonnière[ SDU.STU.GC ] Sciences of the Universe [physics]/Earth Sciences/Geochemistry
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Climatic gradients along the windward slopes of Mount Kenya and their implication for crop risks. Part 2 : crop sensitivity.

2016

16 pages; International audience; Mount Kenya is an equatorial mountain whose climatic setting is fairly simple (two rainy seasons in March–May, the Long Rains, and October–December, the Short Rains) though concealing significant spatial variations related to elevation and aspect (part I, Camberlin et al., 2014). This part II is dedicated to the sensitivity of sorghum yields to climate variability in space and time, with a focus on the intra-seasonal characteristics of the rainy seasons. To that aim we use the crop model SARRA-H calibrated for the region and fed with rainfall, temperature, wind speed, humidity and solar radiation data over the period 1973–2001 at three stations located on t…

P40 - Météorologie et climatologie[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomySARRA-Hintra-seasonal componentsrainy seasonhttp://aims.fao.org/aos/agrovoc/c_9000024http://aims.fao.org/aos/agrovoc/c_10176[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/AgronomyF01 - Culture des planteshttp://aims.fao.org/aos/agrovoc/c_7244ComputingMilieux_MISCELLANEOUSPrécipitationhttp://aims.fao.org/aos/agrovoc/c_24894rainfall variabilityU10 - Informatique mathématiques et statistiquesModélisation des culturescrop modelKenyaVariation saisonnièreRendement des cultureselevation gradientshttp://aims.fao.org/aos/agrovoc/c_4086[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatologyhttp://aims.fao.org/aos/agrovoc/c_6161sorghum[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatology
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Decentralized Lightweight Group Key Management for Dynamic Access Control in IoT Environments

2020

Rapid growth of Internet of Things (IoT) devices dealing with sensitive data has led to the emergence of new access control technologies in order to maintain this data safe from unauthorized use. In particular, a dynamic IoT environment, characterized by a high signaling overhead caused by subscribers' mobility, presents a significant concern to ensure secure data distribution to legitimate subscribers. Hence, for such dynamic environments, group key management (GKM) represents the fundamental mechanism for managing the dissemination of keys for access control and secure data distribution. However, existing access control schemes based on GKM and dedicated to IoT are mainly based on ce…

PROTOCOLSCRYPTOGRAPHYComputer Networks and CommunicationsComputer scienceGROUP COMMUNICATIONKey distributionCore networkRESEAU INFORMATIQUEAccess control02 engineering and technologySCALABILITYTECHNOLOGIE SANS FIL[SPI]Engineering Sciences [physics][INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]TELECOMMUNICATIONForward secrecy0202 electrical engineering electronic engineering information engineeringRekeyingINTERNET OF THINGSElectrical and Electronic EngineeringINTERNETSECURITEDYNAMIC ENVIRONMENTSECURITYIOTTRAITEMENT DES DONNEESbusiness.industryKey distribution center020206 networking & telecommunicationsWIRELESS SENSOR NETWORKSRESEAU DE TELECOMMUNICATIONSGROUP KEY MANAGEMENTINFORMATIQUECommunication in small groupsScalabilityARCHITECTURE CLIENT-SERVEURbusinessCOMPUTER ARCHITECTUREACCESS CONTROLComputer network
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Timing and patterns of the ENSO signal in Africa over the last 30 years: insights from normalized difference vegetation index data.

2014

Abstract A more complete picture of the timing and patterns of the ENSO signal during the seasonal cycle for the whole of Africa over the three last decades is provided using the normalized difference vegetation index (NDVI). Indeed, NDVI has a higher spatial resolution and is more frequently updated than in situ climate databases, and highlights the impact of ENSO on vegetation dynamics as a combined result of ENSO on rainfall, solar radiation, and temperature. The month-by-month NDVI–Niño-3.4 correlation patterns evolve as follows. From July to September, negative correlations are observed over the Sahel, the Gulf of Guinea coast, and regions from the northern Democratic Republic of Congo…

RainfallSaisonAtmospheric ScienceEquatorhttp://aims.fao.org/aos/agrovoc/c_50098F62 - Physiologie végétale - Croissance et développementhttp://aims.fao.org/aos/agrovoc/c_6734http://aims.fao.org/aos/agrovoc/c_8516http://aims.fao.org/aos/agrovoc/c_7222http://aims.fao.org/aos/agrovoc/c_8038http://aims.fao.org/aos/agrovoc/c_6498http://aims.fao.org/aos/agrovoc/c_24199U10 - Informatique mathématiques et statistiquesIndice de surface foliairehttp://aims.fao.org/aos/agrovoc/c_165VegetationRemote sensing[ SDE.MCG ] Environmental Sciences/Global Changeshttp://aims.fao.org/aos/agrovoc/c_7657El Niño Southern OscillationGeography[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/ClimatologyClimatologyhttp://aims.fao.org/aos/agrovoc/c_6161P01 - Conservation de la nature et ressources foncières[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatologyhttp://aims.fao.org/aos/agrovoc/c_7252http://aims.fao.org/aos/agrovoc/c_7497ENSOModèle mathématiquehttp://aims.fao.org/aos/agrovoc/c_8500http://aims.fao.org/aos/agrovoc/c_1671P40 - Météorologie et climatologieTélédétectionhttp://aims.fao.org/aos/agrovoc/c_29553[SDE.MCG]Environmental Sciences/Global ChangesNormalized Difference Vegetation Indexhttp://aims.fao.org/aos/agrovoc/c_35196Interannual variabilityhttp://aims.fao.org/aos/agrovoc/c_6911Donnée climatiquePrecipitationCombined resulthttp://aims.fao.org/aos/agrovoc/c_8176http://aims.fao.org/aos/agrovoc/c_2676PrécipitationWinter rainfallIntertropical Convergence ZoneVégétation15. Life on landTempérature13. Climate actionVegetation-atmosphere interactionsAfricaClimatologiehttp://aims.fao.org/aos/agrovoc/c_4964Énergie solaire
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Adapting to Dynamic LEO-B5G Systems : Meta-Critic Learning Based Efficient Resource Scheduling

2022

Low earth orbit (LEO) satellite-assisted communications have been considered as one of key elements in beyond 5G systems to provide wide coverage and cost-efficient data services. Such dynamic space-terrestrial topologies impose exponential increase in the degrees of freedom in network management. In this paper, we address two practical issues for an over-loaded LEO-terrestrial system. The first challenge is how to efficiently schedule resources to serve the massive number of connected users, such that more data and users can be delivered/served. The second challenge is how to make the algorithmic solution more resilient in adapting to dynamic wireless environments.To address them, we first…

Signal Processing (eess.SP)FOS: Computer and information sciencesdynamic environmentComputer Science - Machine Learningreinforcement learningmeta-critic learningComputer Science - Artificial Intelligence5G-tekniikkaresursointiMachine Learning (cs.LG): Electrical & electronics engineering [C06] [Engineering computing & technology]LEO satelliteslangaton tiedonsiirtoresources allocationalgoritmitFOS: Electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal Processing: Ingénierie électrique & électronique [C06] [Ingénierie informatique & technologie]Applied MathematicstietoliikennesatelliititComputer Science ApplicationsArtificial Intelligence (cs.AI)koneoppiminenresource schedulinglangattomat verkot
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Sensor Fusion Combining 3-D and 2-D for Depth Data Enhancement

2012

Time-of-Flight (ToF) cameras are known to be cost-efficient 3-D sensing systems capable of providing full scene depth information at a high frame rate. Among many other advantages, ToF cameras are able to provide distance information regardless of the illumination conditions and with no texture dependency, which makes them very suitable for computer vision and robotic applications where reliable distance measurements are required. However, the resolution of the given depth maps is far below the resolution given by standard 2-D video cameras which, indeed, restricts the use of ToF cameras in real applications such as those for safety and surveillance. In this thesis, we therefore investigate…

Time-of-Flight: Computer science [C05] [Engineering computing & technology]Data MatchingSpatio-temporal data enhancementDepth imagesSensor FusionComputer VisionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMultimodal SensorsAdaptive Filters: Sciences informatiques [C05] [Ingénierie informatique & technologie]
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Reconstruction et analyse sémantique de chronologies cybercriminelles

2014

International audience; La reconstruction de scénarios est l’une des étapes les plus importantes d’une investigation numérique. Elle permet aux enquêteurs d’avoir une vue des évènements survenus durant un incident. La reconstruction de scénarios est une tâche complexe requérant l’étude d’un très grand nombre d’évènements en raison de l’omniprésence des nouvelles technologies dans notre quotidien. De plus, les conclusions produites se doivent de respecter les critères fixés par la justice. Afin de répondre à ces challenges, nous proposons une nouvelle méthodologie, basée sur une ontologie intégrant les connaissances d’experts des domaines de la criminalistique et de l’ingénierie logicielle, …

[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH][ INFO.INFO-CY ] Computer Science [cs]/Computers and Society [cs.CY][INFO.INFO-CY] Computer Science [cs]/Computers and Society [cs.CY]Extraction de connaissances[INFO.INFO-WB] Computer Science [cs]/WebCriminalistique informatique[INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY][INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH][ INFO.INFO-WB ] Computer Science [cs]/Web[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]OntologieReconstruction de scénarios
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De la scène de crime aux connaissances : représentation d'évènements et peuplement d'ontologie appliqués au domaine de la criminalistique informatique

2015

International audience; Avec la démocratisation des technologies, les enquêtes de criminalistique informatique impliquent des volumes de données toujours plus grands et hétérogènes. Pour faciliter le travail des enquêteurs, nos travaux ont pour objectif de reconstruire automatiquement les évènements liés à un incident numérique, tout en respectant les exigences légales. Pour cela, il est nécessaire d'introduire un modèle de représentation de connaissances permettant de structurer les informations recueillies sur une scène de crime dans le but de faciliter l'utilisation de processus d'analyse automatisés. Ce papier propose un état de l'art des modèles de représentations d'évènements pour le …

[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH][ INFO.INFO-CY ] Computer Science [cs]/Computers and Society [cs.CY][INFO.INFO-CY] Computer Science [cs]/Computers and Society [cs.CY][INFO.INFO-WB] Computer Science [cs]/WebCriminalistique informatique[INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY][INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH][ INFO.INFO-WB ] Computer Science [cs]/Web[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]Représentation d'incidentsReconstruction de scénariosPeuplement d'ontologie
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Analyse du processus de commande et de livraison d'un système Pegakid série T

1998

Rapport de contrat Bull INRIA; Test ergonomique auprès d'utilisateurs de la livraison, du déballage et de l'installation d'un système informatique.

[SCCO.COMP] Cognitive science/Computer science[ SCCO.COMP ] Cognitive science/Computer science[SHS.INFO]Humanities and Social Sciences/Library and information sciencestest utilisateur[ SHS.INFO ] Humanities and Social Sciences/Library and information sciencesergonomie informatique[SCCO.COMP]Cognitive science/Computer scienceinstallation de système informatiqueadministration informatique[SHS.INFO] Humanities and Social Sciences/Library and information sciences
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