Search results for " Computer science"

showing 10 items of 3983 documents

Impact de l'épandage des boues sur le phosphore dissous et particulaire des écoulements de surface

2003

Abstract The aim of this study was to assess the effect of land application of sewage sludge on phosphorus (P) losses during intense rainfall. Three rainfall simulations (40 mm h−1 of 30 min duration) were conducted on a field amended with sewage sludge. The overland flow water (OFW) was monitored and sampled every minute. The suspended solid, the dissolved and total phosphorus (respectively SS, TP and DP) concentrations were analysed. The forms of particulate bound P (PP) were investigated. Several results stem from this experiment: (a) sludge application induced a large increase in the DP content of the OFW; the concentrations obtained (0.15–0.57 mg l−1) were shown to result from desorpti…

[SDE] Environmental SciencesAMENDEMENT DE SOLEPANDAGE DES EAUX USEES[SDV]Life Sciences [q-bio]chemistry.chemical_elementParticulate phosphorusSoil surface[INFO] Computer Science [cs]010501 environmental sciences01 natural sciencesSUSPENSIONDesorption[INFO]Computer Science [cs]0105 earth and related environmental sciencesWater Science and TechnologyHydrologySuspended solidsPhosphorusTRANSFERT04 agricultural and veterinary sciencesParticulates6. Clean water[SDV] Life Sciences [q-bio]chemistryEnvironmental chemistryEUTROPHICATION[SDE]Environmental Sciences040103 agronomy & agriculture0401 agriculture forestry and fisheriesSurface runoffSludge
researchProduct

Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering

2015

20 pages; International audience; Data warehouses (DW) and OLAP systems are business intelligence technologies allowing the on-line analysis of huge volume of data according to users' needs. The success of DW projects essentially depends on the design phase where functional requirements meet data sources (mixed design methodology) (Phipps and Davis, 2002). However, when dealing with complex applications existing design methodologies seem inefficient since decision-makers define functional requirements that cannot be deduced from data sources (data driven approach) and/or they have not sufficient application domain knowledge (user driven approach) (Sautot et al., 2014b). Therefore, in this p…

[SDE] Environmental SciencesMultidimensional designData Warehouse[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingOLAPbusiness.industryComputer scienceOnline analytical processingCLUSTERING HIERARCHIQUEVolume (computing)Functional requirementcomputer.software_genreData warehouseData-driven[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingApplication domain[SDE]Environmental SciencesBusiness intelligenceData MiningData mining[SDE.BE]Environmental Sciences/Biodiversity and EcologybusinessDesign methodscomputerProceedings of the 17th International Conference on Enterprise Information Systems
researchProduct

Une méthodologie et un outil pour le prototypage rapide des entrepôts de données en utilisant le data mining : application à la biodiversité des oise…

2014

International audience; Data Warehouses (DWs) are large repositories of data aimed at supporting the decision-making process by enabling flexible and interactive analyses via OLAP systems. Rapid prototyping of DWs is necessary when OLAP applications are complex. Some work about the integration of Data Mining and OLAP systems has been done to enhance OLAP operators with mined indicators, and/or to define the DW schema. However, to best of our knowledge, prototyping methods for DWs do not support this kind of integration. Then, in this paper we present a new prototyping methodology for DWs, extending [3], where DM methods are used to define the DW schema. We validate our approach on a real da…

[SDE] Environmental Sciences[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]OLAP[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Rapid prototypingInformationSystems_DATABASEMANAGEMENTOLAMiningData Warehouse design
researchProduct

Capteurs et images aériennes pour l’évaluation du peuplement de mauvaises herbes

2013

AIRINOV is specialized in use of UAV for precision agriculture. Thanks to a high spatial resolution up to 1.5 cm/pixel in RGB images, discrimination between vegetation (crop row, weed) and soil can be done. Variability can be detected in weed density inside the whole field. The detection of weeds in the inter-row of hoed row crops was tested on RGB images. The methodology developed is based on Hough transform, and is composed of three main steps: image segmentation, soil/vegetation discrimination and crop rows localization. First results are promising but need complementary measures for validation.

[SDE] Environmental Sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingTransformée de Hough[SDV]Life Sciences [q-bio][ SDV.SA.STA ] Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agriculturedrone[SDV] Life Sciences [q-bio]images RGB THR[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[SDV.SA.STA]Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agriculture[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologyadventices
researchProduct

Mesure de netteté basée sur les descripteurs généralisés de Fourier appliquée à la reconstruction 3D par Shape from Focus

2013

National audience; L'étape principale de la méthode de reconstruction 3D " Shape from Focus " est l'utilisation d'un opérateur de mesure de netteté de chaque pixel de la séquence d'image. Le choix de l'opérateur de mesure de netteté est une étape cruciale pour une reconstruction 3D de qualité. La précision de la mesure de netteté dépend de la taille du voisinage autour du pixel choisi et de la présence ou non de bruit additif dans la séquence d'images. Dans cet article, nous présentons deux nouveaux opérateurs de mesure de netteté basés sur les Descripteurs Généralisés de Fourier. Une nouvelle étude comparative des différents opérateurs est présentée. Cette comparaison est basée sur un plan…

[SDE] Environmental Sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SDV]Life Sciences [q-bio][ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing??[SDV] Life Sciences [q-bio]Mesure de netteté[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingDescripteurs généralisés de Fourier[SDE]Environmental SciencesShape from Focus[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
researchProduct

Influence de l'apport d'amendements organiques sur les émissions de N2O et de N2 par les sols, au cours de la dénitrification, révélée par le traçage…

2006

International audience

[SDE] Environmental Sciences[ SDE ] Environmental Sciences[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[SDE]Environmental Sciences[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputingMilieux_MISCELLANEOUS
researchProduct

Neutral modelling of agricultural landscapes by tessellation methods: the GenExP-LandSiTes software - Application to the simulation of gene flow

2010

International audience; We present a three steps approach that aimed at simulating neutral agricultural landscape models: (1) we characterized the geometry of three real field patterns; (2) we generated simulated field patterns with two tessellation methods attempting to control the value of some of the observed characteristics and, (3) we evaluated the simulated field patterns. The first two steps were integrated to the GenExP-LandSiTes software that thus simulates two-dimensional agricultural landscapes. It is written in Java, and it is freely accessible through a Gnu Public Licence. For the third step, we considered that good simulated field patterns should capture characteristics of rea…

[SDE] Environmental Sciences[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][SDV.SA]Life Sciences [q-bio]/Agricultural sciences[SDV.SA] Life Sciences [q-bio]/Agricultural sciencesTESSELATIONFLUX DE GENE[SDV]Life Sciences [q-bio][MATH] Mathematics [math][INFO] Computer Science [cs]NEUTRAL LANDSCAPE MODEL[SHS]Humanities and Social Sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SDV] Life Sciences [q-bio][SDE]Environmental SciencesGENE FLOW[INFO]Computer Science [cs][SHS] Humanities and Social Sciences[MATH]Mathematics [math][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI][ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences
researchProduct

Constitution de corpus thématique : Pour un meilleur suivi du territoire de la Métropole de Montpellier Méditerranée

2021

International audience

[SDE] Environmental Sciences[SDE]Environmental Sciences[INFO]Computer Science [cs][INFO] Computer Science [cs]ComputingMilieux_MISCELLANEOUS
researchProduct

Rapport Partenariat, Transfert, Innovation (PTI)

2015

[SDE] Environmental Sciences[SDV.GEN]Life Sciences [q-bio]/Genetics[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering[SDV]Life Sciences [q-bio][SDV.GEN] Life Sciences [q-bio]/Genetics[SDV.GEN.GA] Life Sciences [q-bio]/Genetics/Animal genetics[INFO] Computer Science [cs][SDV.IDA] Life Sciences [q-bio]/Food engineering[SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio][SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics[SDE]Environmental Sciences[SDV.IDA]Life Sciences [q-bio]/Food engineering[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs][SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering[SHS] Humanities and Social Sciences
researchProduct

Options for reducing greenhouse gas emissions from the agricultural sector: abatement potential and cost of technical measures

2015

National audience

[SDE] Environmental Sciences[SDV.GEN]Life Sciences [q-bio]/Genetics[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering[SDV]Life Sciences [q-bio][SDV.GEN] Life Sciences [q-bio]/Genetics[SDV.GEN.GA] Life Sciences [q-bio]/Genetics/Animal genetics[SDV.IDA] Life Sciences [q-bio]/Food engineering[INFO] Computer Science [cs][SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio][SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics[SDV.IDA]Life Sciences [q-bio]/Food engineering[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering[INFO]Computer Science [cs][SHS] Humanities and Social SciencesComputingMilieux_MISCELLANEOUS
researchProduct