Search results for " Soft"

showing 10 items of 1710 documents

A Review on Applications of Big Data for Disaster Management

2017

International audience; The term " disaster management " comprises both natural and man-made disasters. Highly pervaded with various types of sensors, our environment generates large amounts of data. Thus, big data applications in the field of disaster management should adopt a modular view, going from a component to nation scale. Current research trends mainly aim at integrating component, building, neighborhood and city levels, neglecting the region level for managing disasters. Current research on big data mainly address smart buildings and smart grids, notably in the following areas: energy waste management, prediction and planning of power generation needs, improved comfort, usability …

[ INFO ] Computer Science [cs]Computer scienceBig data02 engineering and technology[INFO] Computer Science [cs]7. Clean energydisasters12. Responsible consumptionbig data020204 information systemsComponent (UML)11. Sustainability0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Building automationEmergency managementbusiness.industry020207 software engineeringUsabilityEnergy consumptionDisaster managementsensor dataSystematic reviewSmart gridRisk analysis (engineering)13. Climate actionbusiness
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Fuzzy formalizations of cognitive distance

1992

Spatial training process allows more and more precise informations to be collected and memorized. The aim of this article is to describe a three steps training process based on three fuzzy formalizations of cognitive distance associated to three different types of informations : (1) expression of a linguistic relative distance based on fuzzy relation of closeness or/and remoteness, (2) expression of a linguistic absolute distance expressed by primary linguistic terms like short or long and (3) expression of a fuzzy metric absolute distance. A fourth part is devoted to expression of precise correspondance rule between linguistic and metric opinions described below.

[ INFO ] Computer Science [cs]ProgrammingPsychologyComputer software[INFO] Computer Science [cs]InformatiqueComputer science
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Management and interaction with multimodal information content

2010

[Chbeir, Richard] Univ Bourgogne, CNRS, LE2I, Dept Comp Sci, F-21000 Dijon, France. [Coninx, Karin] Univ Hasselt, Expertise Ctr Digital Media EDM, BE-3590 Diepenbeek, Belgium. [Ferri, Fernando; Grifoni, Patrizia] CNR, Inst Res Populat & Social Policies, Rome, Italy.

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Operations research[INFO.INFO-WB] Computer Science [cs]/WebComputer Networks and CommunicationsComputer science[ INFO.INFO-WB ] Computer Science [cs]/WebLibrary science[SCCO.COMP]Cognitive science/Computer science02 engineering and technologyDigital media[SCCO.COMP] Cognitive science/Computer science0202 electrical engineering electronic engineering information engineeringMedia Technology[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]ComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]business.industry05 social sciences[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]020207 software engineering[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Hardware and Architecture[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]0509 other social sciences050904 information & library sciencesbusinessSoftware
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Towards A Twitter Observatory: A Multi-Paradigm Framework For Collecting, Storing And Analysing Tweets

2016

International audience; In this article we show how a multi-paradigm framework can fulfil the requirements of tweets analysis and reduce the waiting time for researchers that use computational resources and storage systems to support large-scale data analysis. The originality of our approach is to combine concerns about data harvesting, data storage, data analysis and data visualisation into a framework that supports inductive reasoning in multidisciplinary scientific research. Our main contribution is a polyglot storage system with a generic data model to support logical data independence and a set of tools that can provide a suitable solution for mixing different types of algorithms in or…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][ INFO ] Computer Science [cs]Computer scienceknowledge discovery02 engineering and technology[INFO] Computer Science [cs][INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]Data modelingmassive datasetsopen source softwareData visualization[ INFO.INFO-IT ] Computer Science [cs]/Information Theory [cs.IT]polyglot storage020204 information systems0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Twitter analysis . SystemsComputingMilieux_MISCELLANEOUS[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]business.industryPolyglotInductive reasoningData science[SPI.TRON] Engineering Sciences [physics]/ElectronicsData independence[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsData model[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT]Data architecturebusinessSoftware architecture
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Integrating user preference to similarity queries over medical images datasets

2010

International audience; Large amounts of images from medical exams are being stored in databases, so developing retrieval techniques is an important research problem. Retrieval based on the image visual content is usually better than using textual descriptions, as they seldom gives every nuances that the user may be interested in. Content-based image retrieval employs the similarity among images for retrieval. However, similarity is evaluated using numeric methods, and they often orders the images by similarity in a way rather distinct from the user's intention. In this paper, we propose a technique to allow expressing the user's preference over attributes associated to the images, so simil…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer scienceComputed tomography02 engineering and technologyContent-based image retrievalSemanticsImage (mathematics)Similarity (network science)[SCCO.COMP] Cognitive science/Computer science020204 information systems0202 electrical engineering electronic engineering information engineeringmedicine[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Image retrieval[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Information retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]medicine.diagnostic_test[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]020207 software engineeringPreferenceImportant research[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]
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Guest Editors' Introduction: Multimedia Metadata and Semantic Management

2009

This special issue assesses the current status and technologies and describes major challenges and proper solutions for effective multimedia production and management related to evolving Semantic Web strategies. The included articles, which cover different facets of the semantic management of multimedia and multimedia metadata from retrieval and processing to consumption and presentation, represent a step forward in research targeted at improving aspects of the semantic metadata life cycle.

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologySemanticsWorld Wide Web[SCCO.COMP] Cognitive science/Computer scienceSemantic computing0202 electrical engineering electronic engineering information engineeringMedia Technology[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Semantic Web StackSemantic WebImage retrieval[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]business.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]020207 software engineeringComputer Science ApplicationsMetadataSemantic grid[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Hardware and Architecture[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Signal Processing020201 artificial intelligence & image processingThe Internet[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businessSoftware
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Automatic Temporal Formatting of Multimedia Presentations Using Dynamic Petri Nets.

2009

An efficient authoring tool would provide support for automatic temporal formatting and modeling of multimedia presentations. Automatic temporal formatting is a process of converting the given presentation specifications into a required temporal format. This paper presents an algorithm that can convert a temporal layout into a dynamic petri net (DPN )w hich can represent iterative and interactive presentation components effectively. The prototype of the authoring tool extracts the temporal layout from any given SMIL file representation and uses the proposed algorithm to automatically convert it into a DPN. The DPN generated automatically at compile-time helps the run-time components in effe…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer sciencemedia_common.quotation_subject[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologycomputer.software_genreDisk formattingPresentation[SCCO.COMP] Cognitive science/Computer scienceFormal specificationSynchronization (computer science)0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Representation (mathematics)ComputingMilieux_MISCELLANEOUSmedia_common[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]MultimediaProgramming language[INFO.INFO-WB]Computer Science [cs]/WebProcess (computing)[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]020207 software engineeringPetri net[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computer
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Reasoning with Vague Spatial Information from Upper Mesopotamia (2000BC)

2015

International audience; Concepts such as near, far, south of, etc., are by its own nature vague. However, they are quite common in human language. In the case of historical records, these concepts are often the only source of information regarding the position of ancient places whose exact location has been lost. In our research, we use digitized written records from Upper Mesopotamia (2000BC) from the HIGEOMES project. Our goal is to provide better understanding of the location of places, based on the analysis of spatial statements. In our approach, we analyse cardinal statements between places with known location. Using this information we construct a probabilistic function representing t…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]media_common.quotation_subjectReasonning02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Description logic0202 electrical engineering electronic engineering information engineeringMesopotamia ;[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Function (engineering)Spatial analysisGeneral Environmental ScienceMathematicsmedia_commondescription logicsInformation retrievalPoint (typography)Ontologybusiness.industryProbabilistic logic[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]020207 software engineeringVaguenessspatial uncertainty[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Upper MesopotamiaOntologyGeneral Earth and Planetary Sciences[ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO]020201 artificial intelligence & image processingArtificial intelligencebusinessConstruct (philosophy)Procedia Environmental Sciences
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Extensions of the witness method to characterize under-, over- and well-constrained geometric constraint systems

2011

International audience; This paper describes new ways to tackle several important problems encountered in geometric constraint solving, in the context of CAD, and which are linked to the handling of under- and over-constrained systems. It presents a powerful decomposition algorithm of such systems. Our methods are based on the witness principle whose theoretical background is recalled in a first step. A method to generate a witness is then explained. We show that having a witness can be used to incrementally detect over-constrainedness and thus to compute a well-constrained boundary system. An algorithm is introduced to check if anchoring a given subset of the coordinates brings the number …

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationBoundary (topology)Witness configuration020207 software engineeringContext (language use)CAD02 engineering and technologyW-decompositionComputer Graphics and Computer-Aided DesignWitness[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationIndustrial and Manufacturing EngineeringComputer Science ApplicationsConstraint (information theory)symbols.namesakeTransformation groupJacobian matrix and determinant0202 electrical engineering electronic engineering information engineeringsymbolsGeometric constraints solving020201 artificial intelligence & image processingFinite setAlgorithmAlgorithmsMathematics
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Extending SPARQL with Temporal Logic

2009

The data integration and sharing activities carried on in the framework of the Semantic Web lead to large knowledge bases that must be queried, analyzed, and exploited efficiently. Many of the knowledge representation languages of the Semantic Web, starting with RDF, are based on directed, labeled graphs, which can be also manipulated using graph algorithms and tools coming from other domains. In this paper, we propose an analysis approach of RDF graphs by reusing the verification technology developed for concurrent systems. To this purpose, we define a translation from the SPARQL query language into XTL, a general-purpose graph manipulation language implemented in the CADP verification too…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/WebInformationSystems_DATABASEMANAGEMENTlabeled transition system[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]ACM : H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.3: Languages/H.2.3.3: Query languagesSPARQL[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationmodel checkingRDFACM: D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.4: Model checking[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]temporal logicACM : D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.4: Model checking[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO]ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.3: Languages/H.2.3.3: Query languages[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulationverification
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