Contribution à l'intégration de C++ et de Prolog à travers la machine abstraite de Warren le système cop-compilé

Ce mémoire présente le système COP-Compilé. C'est un système permettant l'intégration de la programmation procédurale en C++ et de la programmation logique en Prolog. Le noyau de ce système est un compilateur de Prolog basé sur la machine abstraite de Warren (WAM). Cette machine qui définit une organisation de la mémoire, un ensemble de registres et un jeu d'instructions adaptés à Prolog, est actuellement la référence par excellence dans le domaine d'implantation de compilateurs Prolog. Ce projet de recherche s'insère dans le cadre d'une série de travaux qui visent à rapprocher la programmation procédurale et la programmation logique. L'objectif principal de ce projet est d'augmenter la performance d'une première version d'un compilateur réalisant l'intégration des deux styles de programmation où le code Prolog était interprété. Le système COP-Compilé a réussi à augmenter la performance du système COP original et à améliorer ses possibilités en diminuant son temps d'exécution et en étendant les programmes Prolog qu'il est capable de reconnaître

Technology on content construction of foreign language elective course for high school students

Оновлення змісту іншомовної освіти є невід'ємним елементом процесу реформування усієї національної освіти і передбачає її узгодження з вимогами сьогоднішнього дня і потреби сучасних школярів. Впровадження профільного навчання в старшій школі зумовило диференціацію змісту навчання іноземних мов відповідно до базового і профільного рівнів. Одним з важливих компонентів профільного навчання іноземної мови є елективні курси, які доповнюють і розширюють зміст профільного предмета, задовольняють різноманітні пізнавальні інтереси школярів, які виходять за рамки обраного ними профілю. На сьогоднішній день конструювання змісту елективних курсів з іноземних мов для учнів старшої школи, як і з інших предметів, здійснюється інтуїтивно, безсистемно і недостатньо результативно. Зате, знання та використання технології конструювання змісту елективних курсів допоможе зняти негативні моменти в діяльності вчителя щодо рганізації засвоєння змісту елективних курсів у профільному навчанні іноземним мовам, що забезпечить досягнення високих результатів навчальної діяльності.Обновление содержания иноязычного образования является неотъемлемым элементом процесса реформирования всего национального образования и предусматривает его согласование с требованиями сегодняшнего дня и потребности современных школьников. Внедрение профильного обучения в старшей школе обусловило дифференциацию содержания обучения иностранным языкам в соответствии с базовым и профильным уровнями. Одним из важных компонентов профильного обучения иностранному языку являются элективные курсы, которые дополняют и расширяют содержание профильного предмета, удовлетворяют разнообразные познавательные интересы школьников, которые выходят за рамки избранного ими профиля. На сегодняшний день конструирование содержания элективных курсов по иностранным языкам для учащихся старшей школы, как и по другим предметам, осуществляется интуитивно,бессистемно и недостаточно результативно. Зато, знание и использование технологии конструирования содержания элективных курсов поможет снять негативные моменты в деятельности учителя относительно организации усвоения содержания элективных курсов в профильном обучении иностранным языкам, что обеспечит достижение высоких результатов учебной деятельности.Reconstruction of foreign education content is an integral element in reformation process of national education on the whole and it foresees its coordination with current requirements and necessities of modern schoolchildren. Introduction of profile teaching at senior school caused the differentiation for content of teaching foreign languages in accordance with base and profile levels. One of the important components of profile teaching foreign language are elective courses, which complement and extend content of profile subject, satisfy various schoolchildren’s cognitive interests that exceed the limits of selected by them profile. Today constructing content of elective courses in foreign languages for the students of senior school, as well as in other subjects, is carried out intuitional, unsystematic and not enough effectively. But on the other hand, knowledge and using technology of constructing content for elective courses will help to take off negative moments in teacher’s activity concerning the organization of mastering elective courses content in profile teaching foreign languages, which will provide achievement of high results in educational activity

Stratégies pour le raisonnement sur le contexte dans les environnements d assistance pour les personnes âgées

Tirant parti de notre expérience avec une approche traditionnelle des environnements d'assistance ambiante (AAL) qui repose sur l'utilisation de nombreuses technologies hétérogènes dans les déploiements, cette thèse étudie la possibilité d'une approche simplifiée et complémentaire, ou seul un sous-ensemble hardware réduit est déployé, initiant un transfert de complexité vers le côté logiciel. Axé sur les aspects de raisonnement dans les systèmes AAL, ce travail a permis à la proposition d'un moteur d'inférence sémantique adapté à l'utilisation particulière à ces systèmes, répondant ainsi à un besoin de la communauté scientifique. Prenant en compte la grossière granularité des données situationnelles disponible avec une telle approche, un ensemble de règles dédiées avec des stratégies d'inférence adaptées est proposé, implémenté et validé en utilisant ce moteur. Un mécanisme de raisonnement sémantique novateur est proposé sur la base d'une architecture de raisonnement inspiré du système cognitif. Enfin, le système de raisonnement est intégré dans un framework de provision de services sensible au contexte, se chargeant de l'intelligence vis-à-vis des données contextuelles en effectuant un traitement des événements en direct par des manipulations ontologiques complexes. L ensemble du système est validé par des déploiements in-situ dans une maison de retraite ainsi que dans des maisons privées, ce qui en soi est remarquable dans un domaine de recherche principalement cantonné aux laboratoiresLeveraging our experience with the traditional approach to ambient assisted living (AAL) which relies on a large spread of heterogeneous technologies in deployments, this thesis studies the possibility of a more stripped down and complementary approach, where only a reduced hardware subset is deployed, probing a transfer of complexity towards the software side, and enhancing the large scale deployability of the solution. Focused on the reasoning aspects in AAL systems, this work has allowed the finding of a suitable semantic inference engine for the peculiar use in these systems, responding to a need in this scientific community. Considering the coarse granularity of situational data available, dedicated rule-sets with adapted inference strategies are proposed, implemented, and validated using this engine. A novel semantic reasoning mechanism is proposed based on a cognitively inspired reasoning architecture. Finally, the whole reasoning system is integrated in a fully featured context-aware service framework, powering its context awareness by performing live event processing through complex ontological manipulation. the overall system is validated through in-situ deployments in a nursing home as well as private homes over a few months period, which itself is noticeable in a mainly laboratory-bound research domainEVRY-INT (912282302) / SudocSudocFranceF

Environnement logiciel pour l assistance à l autonomie à domicile (gestion de la dynamique et de l incertitude pour la fourniture sémantique en temps réel de services d assistance)

L hétérogénéité des environnements ainsi que la diversité des profils et des besoins des patients représentent des contraintes majeures qui remettent en question l utilisation à grande échelle des systèmes d assistance à l autonomie à domicile (AAL). En effet, afin de répondre à l évolution de l état des patients et de leurs besoins humains, les environnements AAL sont en évolution continue par l introduction ou la disparition de capteurs, de dispositifs d interaction et de services d assistance. Par conséquent, une plateforme générique et dynamique capable de s adapter à différents environnements et d intégrer de nouveaux capteurs, dispositifs d interaction et services d assistance est requise. La mise en œuvre d un tel aspect dynamique peut produire une situation d incertitude dérivée des problèmes techniques liés à la fiabilité des capteurs ou à des problèmes de réseau. Par conséquent, la notion d incertitude doit être introduite dans la représentation de contexte et la prise de décision afin de faire face à ce problème. Au cours de cette thèse, j ai développé une plateforme dynamique et extensible capable de s adapter à différents environnements et aux besoins des patients. Ceci a été réalisé sur la base de l approche Plug&Play sémantique que j ai proposé. Afin de traiter le problème d incertitude de l information lié à des problèmes techniques, j ai proposé une approche de mesure d incertitude en utilisant les caractéristiques intrinsèques des capteurs et leurs comportements fonctionnels. J ai aussi fourni un modèle de représentation sémantique et de raisonnement avec incertitude associé avec la théorie de Dempster-Shafer (DST) pour la prise de décisionThe heterogeneity of the environments as well as the diversity of patients needs and profiles are major constraints that challenge the spread of ambient assistive living (AAL) systems. AAL environments are usually evolving by the introduction or the disappearance of sensors, devices and assistive services to respond to the evolution of patients conditions and human needs. Therefore, a generic framework that is able to adapt to such dynamic environments and to integrate new sensors, devices and assistive services at runtime is required. Implementing such a dynamic aspect may produce an uncertainty derived from technical problems related to sensors reliability or network problems. Therefore, a notion of uncertain should be introduced in context representation and decision making in order to deal with this problem. During this thesis, I have developed a dynamic and extendible framework able to adapt to different environments and patients needs. This was achieved based on my proposed approach of semantic Plug&Play mechanism. In order to handle the problem of uncertain information related to technical problems, I have proposed an approach for uncertainty measurement based on intrinsic characteristics of the sensors and their functional behaviors, then I have provided a model of semantic representation and reasoning under uncertainty coupled with the Dempster-Shafer Theory of evidence (DST) for decision makingEVRY-INT (912282302) / SudocSudocFranceF

Automatic heart rate detection from FBG sensors using sensor fusion and enhanced empirical mode decomposition

International audienceCardiovascular diseases are the world's top leading causes of death. Real time monitoring of patients who have cardiovascular abnormalities can provide comprehensive and preventative health care. We investigate the role of the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and sensor fusion for automatic heart rate detection from a mat with embedded Fiber Bragg Grating (FBG) sensor arrays. The fusion process is performed in the time domain by averaging the readings of the sensors for each sensor array. Subsequently, the CEEMDAN is applied to obtain the interbeat intervals. Experiments are performed with 10 human subjects (males and females) lying on two different positions on a bed for a period of 20 minutes. The overall system performance is assessed against the reference ECG signals. The average and standard deviation of the mean relative absolute error are 0.049, 0.019 and 0.047, 0.038 for fused and best sensors respectively. Sensor fusion together with CEEMDAN proved to be robust against motion artifacts caused by body movements

Ametsa : un système de contrôle de l'environnement domestique générique fondé sur UPnP

International audienceLe développement de services de l'habitat est devenu un enjeu majeur dans le monde de l'informatique communicante. De nombreux acteurs proposent des systèmes de découverte et d'utilisation de services (SDUS) qui supposent l'existence d?équipements interprétant les protocoles d'Internet standards et ouverts, ce qui les rend indépendants des constructeurs d'équipements. Néanmoins, le manque d'appareils domestiques capables d'interpréter ces protocoles a freiné le développement d'applications de contrôle de l'habitat et restreint l'utilisation pratique de ces systèmes aux environnements informatiques. Le projet " Maison Intelligente " s'intéresse au développement de services génériques pour le contrôle de l'habitat en utilisant des SDUS afin de garantir l'indépendance vis-à-vis des constructeurs d'équipements. Le premier outil que nous avons développé, le service Ametsa, repose sur le SDUS UpnP pour permettre la découverte d'équipements de la maison et l?envoi de commandes dédiées. Des expérimentations ont été menées sur une plate-forme matérielle constituée d'équipements X2D, protocole domotique propriétaire. La conversion des ordres lancées par Ametsa en ordres X2D est .

IoT in medical diagnosis: detecting excretory functional disorders for Older adults via bathroom activity change using unobtrusive IoT technology

The Internet of Things (IoT) and Artificial Intelligence (AI) are promising technologies that can help make the health system more efficient, which concurrently can be particularly useful to help maintain a high quality of life for older adults, especially in light of healthcare staff shortage. Many health issues are challenging to manage both by healthcare staff and policymakers. They have a negative impact on older adults and their families and are an economic burden to societies around the world. This situation is particularly critical for older adults, a population highly vulnerable to diseases that needs more consideration and care. It is, therefore, crucial to improve diagnostic and management as well as proposed prevention strategies to enhance the health and quality of life of older adults. In this study, we focus on detecting symptoms in early stages of diseases to prevent the deterioration of older adults' health and avoid complications. We focus on digestive and urinary system disorders [mainly the Urinary Tract Infection (UTI) and the Irritable Bowel Syndrome (IBS)] that are known to affect older adult populations and that are detrimental to their health and quality of life. Our proposed approach relies on unobtrusive IoT and change point detections algorithms to help follow older adults' health status daily. The approach monitors long-term behavior changes and detects possible changes in older adults' behavior suggesting early onsets or symptoms of IBS and UTI. We validated our approach with medical staff reports and IoT data collected in the residence of 16 different older adults during periods ranging from several months to a few years. Results are showing that our proposed approach can detect changes associated to symptoms of UTI and IBS, which were confirmed with observations and testimonies from the medical staff

GATEKEEPER’s Strategy for the Multinational Large-Scale Piloting of an eHealth Platform: Tutorial on How to Identify Relevant Settings and Use Cases

Background: The World Health Organization’s strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. Objective: We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. Methods: The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. Results: Seven European countries were selected, covering Europe’s geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence–based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. Conclusions: This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space

GATEKEEPER’s Strategy for the Multinational Large-Scale Piloting of an eHealth Platform: Tutorial on How to Identify Relevant Settings and Use Cases

Background: The World Health Organization’s strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. Objective: We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. Methods: The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. Results: Seven European countries were selected, covering Europe’s geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence–based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. Conclusions: This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space