Search results for "mobile computing"

showing 10 items of 128 documents

Une approche Web sémantique et combinatoire pour un système de recommandation sensible au contexte appliqué à l'apprentissage mobile

2014

National audience; Au vu de l'émergence rapide des nouvelles technologies mobiles et la croissance des offres et besoins d'une société en mouvement en formation, les travaux se multiplient pour identifier de nouvelles plateformes d'apprentissage pertinentes afin d'améliorer et faciliter le processus d'apprentissage à distance. La prochaine étape de l'apprentissage à distance est naturellement le port de l'e-learning (apprentissage électronique) vers les nouveaux systèmes mobiles. On parle alors de m-learning (apprentissage mobile). La recherche d'informations dans le domaine du m-learning peut être définie comme une activité dont la fi-nalité est de localiser et de délivrer des contenus d'a…

[ INFO ] Computer Science [cs]Recommandation[INFO.INFO-WB] Computer Science [cs]/Weboptimisation[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/Web[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG][INFO] Computer Science [cs][ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG][INFO.INFO-MC]Computer Science [cs]/Mobile Computing[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing[INFO]Computer Science [cs]m-learningAlgorithmes combinatoiresweb sémantiquecontexte
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Towards a methodology for semantic and context-aware mobile learning

2013

International audience; Internet and mobile devices open the way towards mobile learning (m-learning), offering new opportunities to extend learning beyond the traditional teacher-led classroom. M-learning is not only any form of teaching or studying that takes place when the user interacts with a mobile device. It is more than just using a mobile device to access resources and communicate with others. It should take account of the constant mobile situation of the learner. The challenge here is to exploit this continually changing situation with a system that can dynamically recognize and adapt educational resources and services to the "context" in which the learner operates (localization, …

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebExploitComputer science[ INFO.INFO-IU ] Computer Science [cs]/Ubiquitous Computing[ INFO.INFO-WB ] Computer Science [cs]/WebContext (language use)02 engineering and technologycontextWorld Wide Webmobile learning[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-MC]Computer Science [cs]/Mobile ComputingConstant (computer programming)semantic web[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing0202 electrical engineering electronic engineering information engineeringMobile searchSemantic Webbusiness.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing020206 networking & telecommunicationsOpen learning[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]The Internet[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businessMobile device
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eISP, une architecture de calcul programmable pour l'amélioration d'images sur téléphone portable.

2009

4 pages; Today's smart phones, with their embedded high-resolution video sensors, require computing capacities that are too high to easily meet stringent silicon area and power consumption requirements (some one and a half square millimeters and half a watt) especially when programmable components are used. To develop such capacities, integrators still rely on dedicated low resolution video processing components, whose drawback is low flexibility. With this in mind, our paper presents eISP {--} a new, fully programmable Embedded Image Signal Processor architecture, now validated in {TSMC~65nm} technology to achieve a capacity of {16.8~GOPs} at {233~MHz}, for {1.5~mm$^2$} of silicon area and…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processinglow power[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCMOS[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingeISPSIMDvideo pipeimage processing[INFO.INFO-MC]Computer Science [cs]/Mobile ComputingMulti-SIMD[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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A Context-Based Adaptation In Mobile Learning

2013

International audience; Recent developments on mobile devices and wireless technologies enable new technical capabilities for the learning domain. Nowadays, learners are able to learn anywhere and at any time. The dynamic and continually changing learning setting in learner's mobile environment gives rise to many different learning contexts. The challenge in context-aware mobile learning is to develop an approach building the best learning content according to dynamic learning situations. This paper aims to develop an adaptive system based on the semantic modeling of the learning content and the learning context. The behavioral part of this approach is made up of rules and metaheuristics to…

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC][INFO.INFO-WB] Computer Science [cs]/Web[SHS.EDU]Humanities and Social Sciences/Education[SHS.EDU] Humanities and Social Sciences/Education[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/Web[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC][ SHS.EDU ] Humanities and Social Sciences/Education[ MATH.MATH-CO ] Mathematics [math]/Combinatorics [math.CO]context[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO]mobile learning[INFO.INFO-MC]Computer Science [cs]/Mobile Computingsemantic web[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[INFO.EIAH] Computer Science [cs]/Technology for Human Learning[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO][ INFO.EIAH ] Computer Science [cs]/Technology for Human Learning[INFO.EIAH]Computer Science [cs]/Technology for Human Learning[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Adaptation
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A Mobile Computing Framework for Pervasive Adaptive Platforms

2012

International audience; Ubiquitous computing is now the new computing trend, such systems that interact with their environment require self-adaptability. Bioinspiration is a natural candidate to provide the capability to handle complex and changing scenarios. This paper presents a programming framework dedicated to pervasive platforms programming. This bioinspired and agentoriented framework has been developed within the frame of the PERPLEXUS European project that is intended to provide support for bioinspiration-driven system adaptability. This framework enables the platform to adapt itself to application requirements at high-level while using hardware acceleration at node level. The resu…

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR]Context-aware pervasive systemsUbiquitous computingArticle SubjectComputer Networks and CommunicationsComputer scienceDistributed computingmedia_common.quotation_subjectMobile computing02 engineering and technologycomputer.software_genreAdaptabilitylcsh:QA75.5-76.950202 electrical engineering electronic engineering information engineeringAdaptation (computer science)media_commonbusiness.industryFrame (networking)General Engineering020206 networking & telecommunicationsSoftware frameworkEmbedded systemHardware accelerationRobot020201 artificial intelligence & image processinglcsh:Electronic computers. Computer sciencebusinesscomputer
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Recommandation de parcours de formation dans un contexte mobile

2013

National audience; Les récentes avancées dans les technologies de l'information et de la communication ont vu naître de nouvelles formes d'enseignement. L'apprentissage à distance classique s'enrichit et se transforme pour donner jour à un apprentissage plus flexible, accessible sur de multiples supports, à toute heure et en tout lieu : l'apprentissage mobile. Nos travaux portent sur la conception d'un système de recommandation basé sur le contenu, modélisé en utilisant les technologies du web sémantique. La recommandation prendra en compte l'objectif de formation, mais également les supports disponibles pour dispenser cette formation, les préférences personnelles de l'apprenant, ou encore …

[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-MC]Computer Science [cs]/Mobile Computing[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computingplus court chemin multi-modal[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-IU ] Computer Science [cs]/Ubiquitous Computing[INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]m-learningrecommandationmétaheuristiques
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Context-aware semantic Web service discovery protocol

2009

The Web of today represents a broad space where users research, discover and share information. In this context, the process of Web service discovery plays a significant role. Indeed, such process allows linking the information published by service providers and the requests of users, looking for information. Generally, such process involves text or keyword-based techniques. Still, this kind of discovery fails in retrieving only relevant information. Our approach is to design a more " intelligent " system that allows using a knowledge base during the service discovery process, as it is done in the Semantic Web vision. This thesis presents a framework for semantic Web service discovery using…

[INFO.INFO-WB] Computer Science [cs]/Webdécouverte de servicesservice discoveryRDFservices Web sémantiques[INFO.INFO-MC] Computer Science [cs]/Mobile ComputingAndroiddécouverte de services Web sémantiquessemantic Web serviceWeb sémantique[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]semantic Web service discoverySemantic WebOWL
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Virtualization of Remote Devices and Services in Residential Networks

2009

Lately solutions for remote access for residential services have been proposed. However, these solutions require modifications to the service controllers. In addition, remote access adds complexity to the client application. We propose here a solution for decoupling remote access from the client itself with an entity that creates virtual instances of remote services in a local network. Thereby, clients will be able to discover the virtual instance and use it. Moreover, client applications do not need to distinguish between local and remote services hence reducing complexity.

business.industryComputer scienceMobile computingLocal area networkVirtual realityVirtualizationcomputer.software_genreComputer securityServerUniversal Plug and PlayHome computingbusinesscomputerComputer network2009 Third International Conference on Next Generation Mobile Applications, Services and Technologies
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Security in mobile agent systems

2007

business.industryComputer scienceNetwork Access ControlMobile computingbusinessMobile agent systemsComputer network
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SCARKER: A sensor capture resistance and key refreshing scheme for mobile WSNs

2011

How to discover a captured node and to resist node capture attack is a challenging task in Wireless Sensor Networks (WSNs). In this paper, we propose a node capture resistance and key refreshing scheme for mobile WSNs which is based on the Chinese remainder theorem. The scheme is able of providing forward secrecy, backward secrecy and collusion resistance for diminishing the effects of capture attacks. By implementing our scheme on a Sun SPOT based sensor network testbed, we demonstrate that the time for updating a new group key varies from 56 ms to 546 ms and the energy consumption is limited to 16.5–225 mJ, depending on the length of secret keys and the number of sensors in a group.

business.industryComputer scienceNode (networking)TestbedMobile computingEnergy consumptionSun SPOTKey distribution in wireless sensor networksForward secrecyMobile telephonybusinessWireless sensor networkComputer networkGroup key2011 IEEE 36th Conference on Local Computer Networks
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