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Safety-impact on flight-critical systems such as flight or engine control systems is a major concern for aircraft equipment designers in civil and military fields. Current avionic equipments related to safety-critical systems are able to detect trivial faults such as loss of power, short circuits, open circuits or threshold overflow. The occurrence of these faults in actuator control loops, if detected, triggers a fail-safe mode. So, although system availability is reduced, the required safety level can still be ensured. This paper emphasizes a design methodology of nonlinear model-based FDI1 algorithms applied to a Hybrid Stepper Motor (HSM). The proposed design methodology combines a nonlinear dynamic inversion and residual generation using standard continuous Kalman Filter. The proposed fault detection method is based on residual mean-checking analysis, where the parameters are tuned with Kriging method.

Since many years, the Human-Computer Interaction community is interested in the tangible user interfaces (TUI). A part of these TUI focuses on the interaction performed with one or several objects. The domain is in extension by the development of contactless objects (using NFC, RFID technology, etc.). In the system, tangible objects could represent data, action, or complex part. Interaction on a table, which is a common furniture in the everyday life and used in multiple activities (desktop, coffee table, kitchen table, etc.), opens a new way for the research and development in HCI. This article proposes to use a framework, previously proposed in a conjunct article, to characterize applications supported by the couple . These applications aim at supporting complex business tasks; they are described from a technological point of view on the one hand, and from an applicative point of view on the other hand. These applications show the benefit brought by the couple to the interaction and they are immersed in the framework. The framework shows with these instantiations that it is generic and supports such descriptions., Depuis plusieurs années, les interfaces tangibles impliquant des interactions réalisées via un ou plusieurs objets prennent une importance grandissante en interaction homme-machine. Ce domaine est en extension grâce au développement d'objets exploitant des technologies sans contact (NFC, RFID, etc.). L'objet tangible représente un sujet ou une action ; cet objet agit sur le système, telle une action sur une interface « classique ». L'interaction sur table, c'est-à-dire sur un meuble présent dans la vie courante et utilisé à diverses fins (bureau, table à manger, table de salon, table bar, etc.), ouvre un champ nouveau de recherche et de développement. Nous proposons d'illustrer un cadre proposé dans un article conjoint, en positionnant des applications mettant en oeuvre le couple . Plusieurs applications, visant à supporter chacune une tâche métier complexe, sont décrites à la fois d'un point de vue technologique et d'un point de vue applicatif. Ces applications montrent les apports de l'association à l'interaction et sont caractérisées selon les dimensions du cadre de conception présenté dans un article conjoint, montrant ainsi la généricité et le pouvoir descriptif du cadre proposé.

Knowledge and monitoring of invasive species are fundamental measures to determine the short- and long-term effect on invaded ecosystems, in addition to developing strategies to control the problem or its specific solution. In this context, the lionfish is an invasive species that worries managers and scientists of fisheries and marine conservation, this is due to the affected area that spread starting from the east coast of the United States to the coasts of Brazil and it is recently extending to include the Mediterranean Sea. The diet of the invasive fish is small species of fish, crustaceans and invertebrates; the consequent damage is the decrease of food for species at the next level of the food chain and the lack of species to keep coral reefs healthy. In this paper, we propose a lionfish detection system that will be installed in an autonomous underwater vehicle, as part of a monitoring strategy that will allow real-time determination of the number of Lionfish, their location and without human intervention. We compared two detection systems, namely YOLOv4 and SSD-Mobilenet-v2, by training with cross-validation and evaluation with the test set we obtained the best model with 63.66% recall, 89.79% precision, and 79.15% mAP with images in the natural environment, implemented on NVIDIA's Jetson Nano embedded system.

Purpose This paper aims to perform an exhaustive revision of relevant and recent related studies, which reveals that both extraction methods are currently used to analyze credibility on Twitter. Thus, there is clear evidence of the need of having different options to extract different data for this purpose. Nevertheless, none of these studies perform a comparative evaluation of both extraction techniques. Moreover, the authors extend a previous comparison, which uses a recent developed framework that offers both alternates of data extraction and implements a previously proposed credibility model, by adding a qualitative evaluation and a Twitter-Application Programming Interface (API) performance analysis from different locations. Design/methodology/approach As one of the most popular social platforms, Twitter has been the focus of recent research aimed at analyzing the credibility of the shared information. To do so, several proposals use either Twitter API or Web scraping to extract the data to perform the analysis. Qualitative and quantitative evaluations are performed to discover the advantages and disadvantages of both extraction methods. Findings The study demonstrates the differences in terms of accuracy and efficiency of both extraction methods and gives relevance to much more problems related to this area to pursue true transparency and legitimacy of information on the Web. Originality/value Results report that some Twitter attributes cannot be retrieved by Web scraping. Both methods produce identical credibility values when a robust normalization process is applied to the text (i.e. tweet). Moreover, concerning the time performance, Web scraping is faster than Twitter API and it is more flexible in terms of obtaining data; however, Web scraping is very sensitive to website changes. Additionally, the response time of the Twitter API is proportional to the distance from the central server at San Francisco.

Products appearances are made of design choices influencing the way products are perceived. Products semantics is a methods used to understand and anticipate this phenomena. Nowadays, consumers consider sport products not only as “sport” but also as “health” products. Designers may then develop them as “sport-health” products. However, perception of “sport-health” products may vary according to the need to fit sport or health context of use. We present in this paper our experimental approach to understand the influence of sport and health contexts on “sport-health” semantics.

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Nowadays, the high competitiveness of a company depends on its ability to deal quickly and cost-effectively with the market disruptions. For this reason, companies should have an agile and flexible supply chains to solve problems related to the market fluctuation. In fact, supply chain reconfigurability is the ability to modify their capacity and functionality at the lowest cost. The objective of this article is to assess reconfigurability based on its characteristics (modularity, scalability, integrability, convertibility, diagnosability and customization) using Fuzzy logic. For this purpose, a quantitative evaluation of reconfigurability is proposed. In order to validate our assessment model, a case study is applied to evaluate the degree of reconfigurability after supply chain reconfiguration.

This research/project was undertaken with the assistance of resources and services from the FLEXTECH Chair.; International audience; The fourth industrial revolution involves more complexity. In the helicopter engine maintenance activity, which is the object of our study, decision-making can be a difficult task. Many different experts hold both partial knowledge and incomplete situation awareness due to the great diversity of everyday operational practices. In this paper, we propose a digital twin approach to collaborative decision-making based on a multi-agent system, applied to prescriptive maintenance.

Smart environments are currently overpowering traditional Human-Computer Interaction (HCI) approaches for people's everyday life applications. Proxemic interaction is an emerging area for improving HCI experiences in such environments, causing the so-called proxemic environments to emerge. Proxemic interaction describes how the five dimensions (i.e., Distance, Identity, Location, Movement, and Orientation - DILMO) can be used to define interactions among people and digital devices. Current studies in this area are focused on developing proxemic applications with specific functionalities, based on a toolkit that allows developers to obtain DILMO information from sensors. However, there exists a notable lack of general approaches able to support the whole implementation process, starting from the modelling of proxemic environments to represent general proxemics behaviours, and finalizing with the development of specific applications. In order to facilitate the integration of proxemic capabilities in HCI, we propose an approach for modelling proxemic environments based on a graphical Domain-Specific Language (DSL). The DSL allows non-specialist designers to express proxemic interactions for modelling proxemic environments and supports the development process. In order to show its suitability and functionality, we have implemented a prototype to design proxemic behaviours in different proxemic environments.

International audience; The Textile and Clothing industry is facing systemic and global challenges due both to ecological and economic crises. Today, increasing full traceability of supply chain is one of the key points to optimize production but it should also serve to inform consumers to foster sustainable purchasing decision. We argue that the total traceability of the garment supply chain must be constructed to enable a full transparency for the consumer. In this paper, we will start analysing brands' transparency communication and describe the particular complexities of the textile supply chain.

International audience

International audience; The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management. The interest in solar radiation prediction is increasing nowadays so efficient prediction can greatly improve the performance of these different applications. This paper presents a novel solar radiation prediction approach which combines two models, the Auto Regressive Moving Average (ARMA) and the Nonlinear Auto Regressive with eXogenous input (NARX). This choice has been carried out in order to take the advantages of both models to produce better prediction results. The performance of the proposed hybrid model has been validated using a real database corresponding to a company located in Barcelona north. Simulation results have proven the effectiveness of this hybrid model to predict the weekly solar radiation averages. The ARMA model is suitable for small variations of solar radiation while the NARX model is appropriate for large solar radiation fluctuations.

International audience; La capacité d’innovation d’une entreprise est cruciale pour son développement et sa compétitivité. Ainsi il est essentiel de comprendre ces processus et ce qui les affectent pour améliorer l'innovation. Dans cet article nous nous concentrons sur les étapes d'idéation (générer des idées et proposer de nouveaux concepts). Nous avons développé un protocole expérimental en Réalité Virtuelle (RV), qui a prouvé être un outil utile pour la créativité. Nous avons réalisé une expérience selon deux conditions, l'une avec une induction de stress et une sans, pour évaluer l'effet du stress sur le niveau de créativité. Les niveaux de stress, de créativité et des données physiologiques ont été capturés. Nos résultats préliminaires ne montrent pas de différences significatives entre les deux groupes, cependant, comme supporté dans des études précédentes, nous avons intégré avec succès le bracelet connecté Empatica E4 dans notre contexte expérimental. Nous avons observé une hausse générale de l'activité électrodermale (EDA) chez les participants. Nous suggérons que notre expérience a permis de produire une réponse émotionnelle chez les participants, observable au travers des données physiologiques. Cette étude préliminaire nous aidera à façonner les prochaines étapes de notre recherche sur la compréhension de l'expérience créative.

International audience; Depuis quelques années, on observe une effervescence autour de l’Intelligence artificielle et de ses déclinaisons dans tous les domaines de la société. Les nouvelles puissances de calcul permettent aux algorithmes de déployer des capacités exponentielles égalant ou surpassant les logiques de compréhension humaines. Le paradoxe se profilant est d’aboutir à des systèmes ultra intelligents mais de moins en moins accessibles aux humains. Dans ces conditions, de nombreuses problématiques ressurgissent. Les questions sont nombreuses et seule une communauté scientifique éclectique peut apporter des briques de réponses pour instruire ces sujets. Nous vous invitons donc à soumettre vos contributions autour du thème suivant : « De l’Interaction Homme-Machine à la Relation Homme-Machine, comment concevoir des systèmes performants et éthiques ».

International audience; L’interprétation sismique consiste à extraire des surfacesclés de données tri-dimensionnelles de très grande taille dela croûte terrestre. L’extraction automatique de ces surfacesest complétée par une édition manuelle, étape longue,fastidieuse, répétitive, et très coûteuse en temps de calcul.Le système d’interprétation sismique Sismage-CIG™,développé par TOTAL, propose donc une architecture déportantla charge du traitement et de l’affichage sur unserveur dédié; les géologues experts travaillant sur des stationsconnectées, dotées de deux écrans 30 pouces. Cetteconfiguration, associée à la complexité de Sismage-CIG,pose un réel challenge d’ergonomie, tant pour la sélectionque pour la navigation. Dans cet article, nous exploronsla viabilité de l’oculométrie comme modalité d’interactionvenant soutenir le travail des géologues, en adressant lesverrous techniques posés par la configuration particulièrede Sismage-CIG.

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International audience; Les systèmes d’eye-tracking permettent d’étudier les comportements visuels. Pour que les données de ces systèmes soient précises, la calibration est primordiale. Une bonne calibration se traduit par des valeurs de précision et de justesse faibles. Dans cette étude exploratoire, pour évaluer l’effet de la distance, de la luminosité et de l’angle de calibration sur la précision et la justesse de lunettes d’eye-tracking, des mesures ont été effectuées en champ visuel proche, intermédiaire et éloigné sur un écran de calibrage. Neuf combinaisons de calibration ont été testées selon un plan en carré latin. La distance, la luminosité et l’angle de calibration n’ont pas d’effet significatif sur la précision et la justesse des lunettes. A l’inverse, la précision et la justesse des lunettes sont meilleures en champ éloigné, qu’en champ proche et intermédiaire. Ces résultats montrent que les lunettes d’eye-tracking sont davantage adaptées à des études de terrain.

International audience; The textile industry is facing ecological and economic crises. Since the rise of fast fashion, the textile industry is one of the major and ever-increasing contributors to pollution and waste. Fashion brands are now producing twice the amount of clothing today compared with before the year 2000 (Ellen MacArthur Foundation, 2017). In the meantime, more consumers become aware of both social and ecological risks in the textile industry and do not want to encourage such practices. In 2018, 44clothing and for 40people (18-25 years old) (Ditty, n.d.). This phenomenon reveals a growing consumer awareness and a growing distrust of the industry's companies. A survey conducted in April 2020 across 2035 British and German consumers reveals that 64spend less on fashion during the crisis, and half of them expect that trend to continue after the crisis passes. As well, consumers are open to purchasing more durable fashion items, as well as repairing and keeping them longer. This survey reveals a shift in purchasing behavior, customers want to make informed purchases (Granskog et al., n.d.). The globalized and fragmented textile supply chain requires different laws and regulations (Fletcher and Grose, 2012) to improve its transparency. The paper is structured as follow: The first part presents the current situation regarding the transparency of information communicated by brands in store and online, and in the second part, we will describe what information could be shared with informed consumers, after an experiment with a product from a French luxury brand. The first part is the result of a study both in store and online about legal requirements and recommendations about traceability information related to products and environmental displays. We compare these requirements with actual data gathered in store and in online-shop. From our initial observations: The consumer survey by Fashion Revolution in 2018 and 2020 suggests that fashion labels should be transparent with the disclosure of information to consumers: Manufacturer's address, the origin of fabric, and raw material(Fashion Revolution, 2018) (Fashion Revolution, 2020). In the second part of the article, we focus on the importance of traceability for gathering the information necessary for a full transparency. We leverage how information technology could be used to gather, collect, sort, and select information to render to the consumer.

International audience

International audience; Electric grid, as we nowadays know it, is undergoing a significant transformation. What we are now witnessing is an undoubted change of trend towards a decentralized and decarbonized electric grid, where the electric generation based on local resources will take on special relevance. In this context, the encouragement of collective selfconsumption becomes one of the key issues when it comes to taking steps forward to this end. One of the aspects that will contribute to this aim is the development of a consumptionforecasting tool. Hence, a load-forecasting model based on NARX Neural Network is proposed in the following paper. The prediction of the next day (24h) load profile of an individual building is carried out aiming an optimal management of the flexible loads so to achieve the maximum self-consumption. To ensure a consistent behavior of the NARX Neural Network model, identification and removing of outliers, together with data normalization and fixing common time interval has been carried out. The first results of the research are promising, being obtained a 17,6% MAPE in NARX and 25,19% with LSTM model, both evaluated during a regular week on winter in adverse conditions .

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International audience

Aiming to take full advantage of Electric Vehicles' (EVs) batteries despite unpredictability in their arrival and departure time, in this paper, a two-level hierarchical model predictive controller coupled with an innovative charging-discharging scheduler for EVs in building microgrids is proposed. Besides providing a complete framework for its design, this paper also analyses different scenarios of EVs' batteries exploitation that would be beneficial for both building microgrids and EVs' owners. The simulation results conducted in MATLAB Simulink demonstrated that the proposed hierarchical controller could assure that most EVs are completely charged before their departure time while enabling building microgrids to increase their annual photovoltaic self-consumption rate by about 3 percent point compared to the uncontrolled strategy.

International audience

Current development of renewable energy systems (RES) is characterised by an increasing participation of citizens in the upstream decision-making process. These citizens can be future users of the RES but also members of a Renewable Energy Community that develop RES. They can be at the same time Renewable Energy producer, investor and consumer. Moreover, several type of businesses and terms are used to cope with social innovations within the energy sector: local renewable projects, sustainable energy communities or community of renewable energy production. So, actors' engagement opens new solutions for designers who are induced to share alternatives before making decisions. They usually impose constraints since the early phases of the design process. This approach implies for designers to consider new criteria related to citizens motivations and barriers. This paper presents a study to define the main factors that drive people to contribute in social innovation schemes for clean-energy transition. After a state of the art, a survey about 6 main factors and 18 criteria is presented. The analysis based on the responses from 34 participants (i.e. experts) reveals 2 most important factors of motivation and 2 principal barrier sources.

Industrial digital transformation is bringing a need for new tools and concepts. However, designing such complex tools and concept requires methods to be correctly implemented. These methods are studied as part of system engineering to satisfy various identified goals, and more specifically human-system integration, which is the topic of this paper. This article introduces the method used to define key elements of human perception of reality called reality anchors to design scenarios to be tested in a digital twin prototype. This method goes from regulation study to user cognitive function analysis on the specific case of digital twin designing in oil-and-gas industry. This method highlighted the differences between theoretical process and the followed process as well as tools and competencies used to identify reality anchors. This knowledge will then be used to implement a new process to be implemented with a digital twin and scenarios to test the prototype using realistic simulation.

International audience; Electricity-distribution network operators face several operational constraints in the provision of safe and reliable power given that investments for network area reinforcement must be commensurate with improvements in network reliability. This paper provides an integrated approach for assessing the impact of different operational constraints on distribution-network reliability by incorporating component lifetime models, time-varying component failure rates, as well as the monetary cost of customer interruptions in an all-inclusive probabilistic methodology that applies a time-sequential Monte Carlo simulation. A test distribution network based on the Roy Billinton test system was modelled to investigate the system performance when overloading limits are exceeded as well as when preventive maintenance is performed. Standard reliability indices measuring the frequency and duration of interruptions and the energy not supplied were complemented with a novel monetary reliability index. The comprehensive assessment includes not only average indices but also their probability distributions to adequately describe the risk of customer interruptions. Results demonstrate the effectiveness of this holistic approach, as the impacts of operational decisions are assessed from both reliability and monetary perspectives. This informs network planning decisions through optimum investments and consideration of customer outage costs.

International audience; The aim of the work presented in this paper is the energy management in residential microgrids. The study focuses on Multi Agent System approach based on sensors and actuators network. The system operation requires a large amount of data both for its architectural description and for its real time control. Dealing with this heterogeneous data needs the development of a relational database model.

International audience; Human emotion recognition from visual expressions is an important research area in computer vision and machine learning owing to its significant scientific and commercial potential. Since visual expressions can be captured from different modalities (e.g., face expressions, body posture, hands pose), multi-modal methods are becoming popular for analyzing human reactions. In contexts in which human emotion detection is performed to associate emotions to certain events or objects to support decision making or for further analysis, it is useful to keep this information in semantic repositories, which offers a wide range of possibilities for implementing smart applications. We propose a multi-modal method for human emotion recognition and an ontology-based approach to store the classification results in EMONTO, an extensible ontology to model emotions. The multi-modal method analyzes facial expressions, body gestures, and features from the body and the environment to determine an emotional state; this processes each modality with a specialized deep learning model and applying a fusion method. Our fusion method, called EmbraceNet+, consists of a branched architecture that integrates the EmbraceNet fusion method with other ones. We experimentally evaluate our multi-modal method on an adaptation of the EMOTIC dataset. Results show that our method outperforms the single-modal methods.

International audience; The paper has a focus on energy consumption habits, trends and intervention strategies in residential buildings, mainly through the serious game approach with a combination of direct consumer feedback through smart metering. More than 150 homes in France and Spain have been involved in the research experiment and the consumption habits of approximately 50 homes were deeply analyzed. The applied methods, processes, results and findings of the monitoring data analysis are presented in the paper with two aims. First, consumption profiles and trends were determined for apartment homes with regard to heating, domestic hot water and electric consumption. Second, the impact of a serious game experiment was assessed comparing energy consumption, indoor air temperature and users' habits (based on questionnaires) before and after launching the experiment.

International audience; Design space exploration (DSE) describes the systematic activity of discovery and evaluation of the elements in a design space in order to identify optimal solutions by reducing the design space to an area of performance. Designers sample thousands of design points iteratively, explore the design space, gain knowledge about the problem and make design decision. The literature tells us that DSE results in a decision of quality called informed decision, which is supported by information visualization. The representation of design points is seen as primordial to gain an understanding of the problem and make an informed decision. In our work, we have sought to identify what type of graph is best suited to the discovery phase, and enables designers to make an informed decision. We designed a web platform with four design problems, and carried out an experiment with 42 participants. We found a graph that was better suited to making a decision of quality and to gaining greater understanding: the scatter plot matrix.

International audience; There exists a variety of network simulators, used to imitate the protocols, nodes, and connections in data networks. They differ in their design, goals, and characteristics. Thus, comparing simulators requires a clear and standardized methodology. In this paper, based on a set of measurable and comparable criteria, we propose an approach to evaluate them. We validate the suggested approach with two network simulators, namely Packet Tracer and GNS3. In that regard, a test scenario is put forward on the two simulators, both in Linux and Windows environments, and their performance is monitored based on the suggested approach. This paper does not propose a method for selecting the best simulator, but it rather supplies the researchers with an evaluation tool, that can be used to describe, compare, and select the most suitable network simulators for a given scenario.

International audience; The Semantic Web and the Linked Open Data (LOD) initiatives promote the integration and combination of RDF data on the Web. In some cases, data need to be analyzed and protected before publication in order to avoid the disclosure of sensitive information. However, existing RDF techniques do not ensure that sensitive information cannot be discovered since all RDF resources are linked in the Semantic Web and the combination of different datasets could produce or disclose unexpected sensitive information. In this context, we propose a framework, called RiAiR, which reduces the complexity of the RDF structure in order to decrease the interaction of the expert user for the classification of RDF data into identifiers, quasi-identifiers, etc. An intersection process suggests disclosure sources that can compromise the data. Moreover, by a generalization method, we decrease the connections among resources to comply with the main objectives of integration and combination of the Semantic Web. Results show a viability and high performance for a scenario where heterogeneous and linked datasets are present.

While the 7 million-head French sheep industry is contracting, the average herd size is rising, providing challenging issues to maintain and improve its productivity. Precision Livestock Farming has allowed the sheeps and herds to be equipped with sensors and has a result the amount of data to be processed by farmers has surged. We argue that in order for the farmers to take appropriate actions there is a need for the development of a decision support system that take into account not only real-time data but also expert knowledge. In this work, we first highlight the specific challenges presented by the field of precision sheep farming to the development of a Cyber-Physical and Human System. We then introduce a methodology to implement a decision support in this context.

International audience; Les systèmes de stockage sont des éléments clefs pour permettre la conception de micro-réseaux dédiés aux bâtiments. Cependant, les imprécisions des modèles mathématiques des batteries, dû aux effets de la température et de leur vieillissement peuvent réduire les performances d’un système micro-réseaux. Cet article présente un contrôleur par modèle prédictif doté d'un algorithme d'identification en temps réel des modèles des batteries pour mieux estimer leur état de charge afin d’exploiter au maximum les batteries sans les endommager. Les résultats démontrent que l'algorithme proposé associé au nouveau modèle pour l’estimation de l’état de charge des batteries est capable d’améliorer jusqu’à trois fois la précision des modèles de l’estimation de l’état de charge des batteries Li-ion, et d’augmenter jusqu’à 3% l’indice d’autoconsommation annuel d’un micro-réseau dédié aux bâtiments.

International audience

National audience; Wireless Sensor Network (WSN) applications in the industrial sector are in permanent evolution due the emergence of the Industry 4.0 concept. Considering this context, Wireless Image Sensor Networks (WISN) appeared as a solution to supervise production processes. In this specific type of WSN, the size of the data to process and to transmit constitutes an important constraint that could cause network congestion and impact node lifetime. Thus, the goal of this paper is to study and evaluate a typical image compression algorithm as a solution to optimize the energy consumption and communication traffic in a WISN, dedicated to control a chemical industrial process.

International audience; The aim of the work presented in this paper is the energy management in residential microgrids. The study focuses on Multi Agent System approach based on sensors and actuators network. The system operation requires a large amount of data both for its architectural description and for its real time control. Dealing with this, the fundamental step in the energy management is the organization of data in order to construct the suitable relational database model. The second step is to analyze the system architecture and identify the agents to use for the system. When data are structured and Multi Agent System is modelled, the energy management algorithms are developed and validated taking into account the data availability and the agents properties.

International audience; Although linear electromagnetic energy harvester (LEH) is a promising technique for converting energy in a vehicle suspension, due to the large displacements, one of the main drawbacks of the solutions inside the vehicle is still their size and complexity. To address this issue, this paper focuses on the design and fabrication of a fully embedded LEH without any modification of the suspension initial structure. After a determination of the electrical, mechanical and electromechanical parameters using a Finite Element analysis, the dynamic efficiency is highlighted with a global Bond Graph model. This formalism is well adapted to simulate energy transfers inside multiphysic systems and to reduce the computational time, whereas the finite element model is not exploitable for a complete suspension simulation. In order to validate the Bond Graph simulation results, an embedded prototype has been built and tested in a laboratory environment. The embedded LEH system delivers around 10 W for a solicitation of linear velocity of 1 m/s which is sufficient to power a classical electronic circuit which is in good correlation with the measured ones and significant power has been obtained.

International audience; During the last decade, the smart grid (SG) concept has started to become a reality, mainly thanks to the technical progress achieved in telecommunications, informatics and power electronics, among other domains, leading to an evolution of the traditional electrical grid into an intelligent one. Nowadays, the SG can be seen as a system of smart systems that include cyber and physical parts from different technologies that interact with each other. In this context, intelligent buildings (IBs) constitute a paradigm in which such smart systems are able to guarantee the comfort of residents while ensuring an appropriate tradeoff of energy production and consumption by means of an energy management system (EMS). These interconnected EMSs remain the objective of potential cyber-attacks, which is a major concern. Therefore, this paper conducts a survey, from a multidisciplinary point of view, of some of the main security and privacy issues related to IBs as part of the SG, including an overview of EMS, smart meters, and the main communication networks employed to connect IBs to the overall SG. Future research directions towards a security enhancement from both technical and human perspectives are also provided.

International audience; Whether it is for evolution, competitiveness or problem solving, innovation is necessary to a company’s survival. Thus, it is essential to understand these processes and what affects them in order to improve innovation. In this paper we focus on the ideation steps (generating ideas and proposing new concepts). We developed an experimental protocol in Virtual Reality, as it has been demonstrated to be a useful medium for creativity. We conducted the experiment following two conditions, one with an induction of stress and one without, to evaluate the effect of stress on the level of creativity. The levels of stress, creativity and physiological signals have been monitored. Our early results did not show significant differences between the two groups, however, as supported by previous studies, we have successfully used the Empatica E4 physiological wearable in our experimental context and observed a general rise in electrodermal activity (EDA) among our participants. We suggest that our experiment was able to elicit an emotional response in our participants that is observable in the physiological data. This preliminary study will help us shape the next steps of our research on the understanding of the creativity experience depending on different parameters.

International audience; Depuis quelques années, l’introduction des nouvelles technologies, en particulier des systèmes cyber-physiques (CPS), dans la production industrielle est au cœur de nombreuses perspectives de recherche et de croissance économiques dans le monde. Ces évolutions sont souvent nommées Usines Intelligentes ou, Usines du Futur, et sont caractérisées entre autres, par l’interopérabilité entre ses sous-systèmes endogènes, l’aide dans la prise de décision, l’interaction entre l’humain et la machine, etc. Dans ce contexte de mutation industrielle, la modélisation paraît complexe et cruciale pour l’implémentation des CPS. Cet article, en s’appuyant sur des travaux de recherches antérieures menés dans le domaine de la modélisation des systèmes complexes, vise à contribuer en proposant un modèle générique des CPS. Ce modèle générique caractérise les principales composantes d’un CPS, et nous présentons un exemple d’instanciation de ce modèle dans le contexte de la production chimique. L’originalité réside dans l’intégration de l’humain comme élément au centre des préoccupations pour la modélisation de CPS, ce qui, à notre connaissance, a rarement été fait dans la littérature. Ainsi, ce modèle générique constitue un guide pour la modélisation de système de production à base de CPS avec notamment la prise en compte de l’humain dans la boucle et le pilotage du système par l’aide à la décision.

International audience; Model order reduction (MOR) has demonstrated its robustness and wide applicability in simulating large-scale mathematical models in the engineering research domain. In this paper, MOR techniques are applied to quantify relevant reliability metrics of power distribution systems and the impact associated with the integration of different smart grid technologies. To the best of the authors' knowledge, this is the first application of MOR techniques of balanced truncation to derive reliability models of electricity networks, which exhibit a reduced number of equivalent components and thus simplify the complexity for network analysis. The extensive case studies presented, based on both radial and meshed systems, demonstrate that the proposed technique allows for a faster reliability assessment through Monte Carlo simulation while preserving high accuracy. The proposed methodology can also be applied to systems endowed with photovoltaic and energy storage technologies, emphasising that this approach represents a promising starting point for reliability analysis of more complex systems, which are normally characterised by a large penetration of these distributed energy resources.

International audience; L’enseignement des statistiques fait partie du socle de connaissances nécessaires dans le cadre d’une formation d’ingénieurs généralistes. Cependant, les résultats des étudiants dans cette discipline n’étaient pas à la hauteur des objectifs pédagogiques fixés. Une refonte des modalités d’enseignement a été menée en s’appuyant sur trois constats : les apprenants (1) ne percevaient pas l’intérêt de la discipline pour leur futur métier, (2) souhaitaient être plus actifs dans leur phase d’apprentissage et (3) appréciaient l’usage des outils numériques comme supports à leur formation.Un travail, mené par l’équipe pédagogique, a défini l’adaptation de l’enseignement proposé en intégrant plus de pédagogie active et plus d’outils numériques. Cette communication présentera la démarche pédagogique innovante issue de ce travail. Cette démarche s’appuie sur un cas d’étude nécessitant une implication forte des apprenants pour servir de base à un apprentissage par problème et est soutenue par des « briques » numériques (contenant chacune un apport théorique, des exercices et une évaluation) permettant à l’apprenant d’avancer à son rythme suivant un escalier pédagogique pour atteindre les objectifs pédagogiques. Les premiers résultats sont très prometteurs tant du point de vue des évaluations (amélioration significative des notes) que de la satisfaction des étudiants comme des enseignants.