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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.

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.

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; 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 .

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; 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

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; 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; 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.

International audience; ESTIA, école d'ingénieurs généralistes, a récemment ouvert une formation Bachelor de Technologies. Les modules d'enseignement ont été définis autour d'un Projet Fil Rouge (PFR), projet pluritechnologique trisannuel, s'inscrivant dans la mouvance actuelle de l'apprentissage par projet. Dans ce contexte, le principal défi concerne la démarche pédagogique à mettre en oeuvre pour assurer l'application de connaissances théoriques au travers du PFR. Un sujet de PFR est proposé à chaque promotion entrante. Sur trois années, les étudiants appliquent les connaissances théoriques sur les différentes étapes de conception et de réalisation d'un système pluri-technologique, de la conception préliminaire à la démonstration de fonctionnement. Cette communication détaillera le modus operandi, en s'attachant à illustrer les particularités de la démarche employée. Citons, par exemple, la démonstration finale du système par les étudiants devant un jury composé d'industriels, ou encore l'usage obligatoire des langues étrangères dans le suivi du projet en deuxième année de cycle. Cette démarche a été expérimentée par une première promotion, qui a travaillé sur la conception et la réalisation d'un système de livraison autonome du courrier. Les résultats obtenus, tant sur la réalisation que sur l'intégration des premiers diplômés Bachelor en Cycle Ingénieur sont prometteurs, et les perspectives d'évolution nombreuses.

International audience; Originally issued from cladding, the LMD-p process widens the field of possibilities in terms of manufacturing. Depending on the targeted application, the needs regarding the track geometry are different and the ability to adapt it is a key challenge. In LMD-p, the laser beam attenuation as well as the powder particles preheating are both determined by laser-powder interactions before the powder reaches the substrate. The track dimensions are directly correlated to the melt pool size: a larger pool will tend to capture more powder resulting in a higher deposition rate. The model presented here intends to determine, for a given working distance, the partition of energy, and to estimate the area of the generated melt pool and finally the dimensions of the deposited track. It is first based on a semi-analytical approach that models the powder distribution and calculates the transmitted power to both substrate and powder particles. The attenuated power density is then an input for a light Eulerian thermal simulation from which the contour of the molten zone is extracted. Several iterations are carried out to account for the energy loss caused by the heating and melting of the powder entering the pool. Lastly, the track dimensions are estimated from the stabilized melt pool configuration. Track geometries obtained with a BeAM® machine are compared to the model predictions. Such an approach opens very interesting perspectives in studying the influence of the working distance and its optimization for a given material and/or a given application.

The present work is focused on one Additive Manufacturing (AM) process – Laser powder Metal Deposition (LMD-p) – and on one metallic alloy – Ti-6Al-4V. State of the art on LMD-p on Ti-6Al-4V alloy shows that three kinds of process parameters influence mechanical properties of building parts: raw materials (powder and substrate), machine parameters (Laser Power (P), Powder Flow (F) and Building Speed (V)), and building strategies (part orientation, waiting time between layers, etc.). Thus, this paper relates to first manufacturing investigations on small sized specimens (bead, wall and block) with the aim of providing a better knowledge about the first steps of manufacturing. Particularly, this paper is dedicated to the study of machine parameters (P, F and V). First, the influence of each machine parameter on 28 beads is studied separately. The geometrical aspect (high, width, dilution) of each bead is microscopically measured. Similarly, combinations of parameters (P/F, Energy Density and Powder Density) are introduced to increase parameters degree of freedom. First results show that P, V and F have a major influence on the beads’ geometry. In addition, a window process map is plotted and allows determining functional areas of machine parameters. From this map, walls (vertical superposition of one bead) are manufactured and microscopically observed. Functional sets of parameters from walls are selected and blocks can be built.

International audience; The present work is focused on one Additive Manufacturing (AM) process – Laser powder Metal Deposition (LMD-p) – and on one metallic alloy – Ti-6Al-4V. State of the art on LMD-p on Ti-6Al-4V alloy shows that three kinds of process parameters influence mechanical properties of building parts: raw materials (powder and substrate), machine parameters (Laser Power (P), Powder Flow (F) and Building Speed (V)), and building strategies (part orientation, waiting time between layers, etc.). Thus, this paper relates to first manufacturing investigations on small sized specimens (bead, wall and block) with the aim of providing a better knowledge about the first steps of manufacturing. Particularly, this paper is dedicated to the study of machine parameters (P, F and V).First, the influence of each machine parameter on 28 beads is studied separately. The geometrical aspect (high, width, dilution) of each bead is microscopically measured. Similarly, combinations of parameters (P/F, Energy Density and Powder Density) are introduced to increase parameters degree of freedom. First results show that P, V and F have a major influence on the beads’ geometry. In addition, a window process map is plotted and allows determining functional areas of machine parameters. From this map, walls (vertical superposition of one bead) are manufactured and microscopically observed. Functional sets of parameters from walls are selected and blocks can be built.

International audience; The sustainability of livestock systems is shaped by both local and global factors. In this context, it is useful to have digital tools that can assess animal behaviour and thus guide grazing decisions. Here, we first review available technologies and then present the CLOCheTE project This project aimed to develop a GPS-equipped accelerometer to inform decision-making during rangeland grazing operations. Surveys were conducted to identify user needs. In tandem, research was performed on experimental farms to assess the ability of digital tools to meet these needs. These two steps allowed us to draft functional and technical specifications for the tool. We believe that the success of future commercial solutions will depend on the collaborative investment in development efforts made by complementary stakeholders.; Les outils numériques centrés sur le comportement des animaux pour piloter la conduite du pâturage constituent une des réponses possibles face aux enjeux locaux et globaux qui conditionnent la durabilité des systèmes d’élevages. Après un panorama des différentes technologies et de leurs usages, nous présenterons le projet CLOChèTE. Ce dernier a été consacré au développement d’un outil combinant GPS et accéléromètre pour l’aide à la décision dans la conduite du pâturage sur parcours. En parallèle d’enquêtes visant à identifier les besoins des utilisateurs, des essais en fermes expérimentales ont été menés pour évaluer la capacité des technologies à répondre à ces besoins. Ces deux étapes ont abouti à la rédaction de cahiers des charges fonctionnel et technique de l’outil. Nous considérons que le succès des futures solutions commerciales dépendra de développements concertés entre acteurs complémentaires.

For social robots, knowledge regarding human emotional states is an essential part of adapting their behavior or associating emotions to other entities. Robots gather the information from which emotion detection is processed via different media, such as text, speech, images, or videos. The multimedia content is then properly processed to recognize emotions/sentiments, for example, by analyzing faces and postures in images/videos based on machine learning techniques or by converting speech into text to perform emotion detection with natural language processing (NLP) techniques. Keeping this information in semantic repositories offers a wide range of possibilities for implementing smart applications. We propose a framework to allow social robots to detect emotions and to store this information in a semantic repository, based on EMONTO (an EMotion ONTOlogy), and in the first figure or table caption. Please define if appropriate. an ontology to represent emotions. As a proof-of-concept, we develop a first version of this framework focused on emotion detection in text, which can be obtained directly as text or by converting speech to text. We tested the implementation with a case study of tour-guide robots for museums that rely on a speech-to-text converter based on the Google Application Programming Interface (API) and a Python library, a neural network to label the emotions in texts based on NLP transformers, and EMONTO integrated with an ontology for museums, thus, it is possible to register the emotions that artworks produce in visitors. We evaluate the classification model, obtaining equivalent results compared with a state-of-the-art transformer-based model and with a clear roadmap for improvement.

A life cycle assessment (LCA) was conducted on an innovative concrete 3D printing system, offering the following main advantages: (1) additive and subtractive capabilities, allowing for the automated post-processing of printed parts, including operations such as surface polishing, grooving and drilling and (2) the use of a cable robot, which is less expensive, lighter, more transportable, more energy-efficient and more easily reconfigurable than alternatives such as gantry-type systems. The production of a 4-m height structural pillar was assessed, comparing it to production with traditional methods, namely, using a mould. The study included the entire supply chain of the 3D printing equipment, operation and end-of-life, based on real data from the design and operation of a demonstration plant installed in Spain. Data for traditional construction was based on literature and expert judgement. The 3D production process included printing the pillar perimeter in four pieces with 3D printing concrete, transporting to the construction site and reinforcing and casting with conventional concrete. Traditional production involved reinforcing and casting with the mould on-site. The results show that when only one pillar needs to be produced, 3D printing has a lower environmental impact in all the environmental indicators assessed when compared to using a mould that is discarded after a single use. As an example, GHG emissions are lower by 38%. It was also found that the contribution of 3D printing to the environmental impact of producing a pillar is almost negligible, representing less than 1% of the pillar’s total GHG emissions. However, when the same pillar needs to be produced in higher numbers, the results show that 3D printing and conventional production have a similar environmental impact, given that the mould used in conventional production can be reused, becoming a comparatively efficient option.

International audience; When responding to calls for tenders, companies must elaborate on relevant bids relative to the needs and expectations of customers (for example, in terms of price and delay). We built and deployed a knowledge-based system (KBS) to aid companies when developing bids. Based on a pre-defined generic bid model, a methodology to support companies when deploying the KBS is proposed in this paper. To capture, formalize, and reuse knowledge relevant to bids, a combination of several approaches, such as taxonomy, constraint satisfaction problem, and case-based reasoning, is proposed. The methodology is composed of five steps: Initialization, Specialization, Implementation, Exploitation, and Maintenance. A case study from a company building electrical parts of harbor lifting devices illustrates our proposal and allows validating the proposed methodology.

International audience; In recent years, advanced manufacturing processes have been developed to increase the speed of production in order to reduce production costs. At the scale of thermoplastic composites, the translation is the combination of advanced manufacturing processes. The focus in this study is more specifically on the coupling of automated lay-up (AFP) and stamp forming processes. To date, a consolidation process, such as press-consolidation of thermoplastic composites, obtained blanks. Several trials have begun using an automated fiber placement consolidation to reduce manufacturing time and use unidirectional material. However, the combination of AFP and stamp forming is useful if it optimizes this process without the blank's full consolidation, which by resulting reduces the manufacturing time. This study estimates blank characteristics through thermal history imposed by a more rapid manufacturing process. A set of blanks with varying process parameters is produced to investigate the influence at the microscopic scale. The interface behaviour is observed with optical microscope and image processing. A statistical study applied to the process is carried out in order to relate the material observations to the input parameters. The results of this study are used for the study of the next process of the combination: the stamp forming.

International audience

Wireless Sensor Network (WSN) is a set of battery-powered nodes that include sensors coupled with processing units and wireless transceivers. Nowadays, WSN is a major topic in the research and development domain. Indeed, it constitutes an interesting solution to give an answer to different situations related to social, societal and economic issues such as the need to manage the Smart Grids or to supervise patient’s health in the context of the aging population. This kind of network has the capacity to be simply deployed in harsh environments, such as forests, volcanoes and buildings, to achieve various goals, like tracking targets, animals or human beings for example, or monitoring physical phenomena, such as patient physiological signals or ambient temperature in a building.However, the deployment of WSNs can be critical because of the difficult conditions imposed by the application environment, for example, the high temperatures in the case of volcano activity supervision, or the impossibility of reaching the nodes after deployment, when the WSN must be used to structural health monitoring of a highway or a building. Therefore, researchers and developers need tools to test and evaluate, in the design process of a WSN, node and network performances before deploying it in real surroundings.In this context, simulation can provide a solution that can save time, cost, and effort before deploying a WSN application in its real environment. This explains that simulation tools are widely used in WSN designing stages and for research works evaluation related to this kind of network. Nevertheless, designing a WSN, dedicated to a specific application, needs to address its multilevel structure: topology, nodes and circuits. Thus, to handle the main challenges of WSN design such as energy issues, WSN modelling is considered a complex task because the adopted modelling approach has to take into account the WSN multilevel structure in order to provide exploitable results from different points of view at the same time.In this thesis, we define, propose and implement a cross-level energy-aware model for WSN that allows considering different levels of abstraction at the same time: circuits, nodes and topology. This energy-oriented model is able to trace the energy consumption from multiple points of view: a specific circuit's activity, circuit or node activities, as well as the impact on the WSN lifetime. The proposed model is implemented in a dedicated WSN simulator, which is used, defining different scenarios, to compare obtained results with a well-known simulator and physical WSN nodes with the aim to validate the relevance of our approach., Un Réseau de Capteurs Sans Fil (RCSF) est composé d’un ensemble de noeuds alimentés par batterie, associant des capteurs à une unité de traitement et à un émetteur-récepteur sans fil. De nos jours, les RCSF font l’objet de nombreux travaux de recherche et développement. En effet, ces réseaux constituent une solution intéressante afin d’apporter une réponse à différents enjeux sociaux, sociétaux et économiques tels que le déploiement des Smart Grids ou la supervision à distance de la santé de personnes dans un contexte de vieillissement de la population. Ces RCSF ont la capacité d'être déployé dans des environnements contraints, tels que les forêts, les volcans et les bâtiments, pour atteindre divers objectifs : la localisation d’objets et d’individus mais aussi la surveillance de phénomènes physiques, comme les signaux physiologiques de patients ou la température ambiante d’un bâtiment.Cependant, le déploiement de ces RCSF est souvent rendu critique en raison des contraintes imposées par l'environnement d’application, par exemple, les températures pouvant être subies lors de la supervision d’un volcan, ou la difficulté d’accès aux noeuds lorsque ceux-ci sont utilisés pour la surveillance de l'état structurel d'une autoroute ou d'un bâtiment. Par conséquent, les chercheurs et développeurs de ce type de réseau ont besoin d'outils pour tester et évaluer, dans le cadre du processus de conception d'un RCSF, les performances des noeuds et du réseau avant de le déployer dans un environnement réel.Dans ce contexte, les outils de simulation peuvent apporter une solution permettant un gain de temps, une limitation des coûts et des efforts avant le déploiement d’un tel réseau dans son environnement d’utilisation. Ces outils sont donc aujourd’hui largement répandus et utilisés pour évaluer les performances d’un RCSF mais aussi les propositions issues de travaux de recherche relatifs à ce type de réseau. Néanmoins, la conception d'un RCSF, dédié à une application, doit tenir compte de sa structure multi-niveau : topologie, noeuds et circuits. Ainsi, pour aborder les principaux défis liés au RCSF, tels que la problématique d’autonomie énergétique des noeuds, la modélisation de ces réseaux est considérée comme une tâche complexe car l'approche de modélisation utilisée doit considérer sa structure multi-niveau afin de fournir des résultats exploitables provenant simultanément de niveaux d’abstraction différents.Dans cette thèse, nous définissons, proposons et implémentons un modèle trans-niveaux orienté énergie dédié au RCSF permettant de considérer simultanément différents niveaux d'abstraction : topologie, noeuds et circuits. Ce modèle est capable de tracer la consommation énergétique à partir de différents points de vue : l'activité spécifique d'un circuit, les activités d'un circuit ou d'un noeud, ainsi que son impact sur la durée de vie du RCSF. Notre modèle est ensuite implémenté dans un simulateur de RCSF dédié afin, en considérant différents scénarios, de comparer les résultats obtenus avec un simulateur existant et des noeuds réels dans le but de valider la pertinence de notre approche.

6 pages; International audience; In the last decade, HCI research has proposed promising technologies for shape-changing interfaces. The usefulness and the user experience of shape-change are, however, still to be explored and understood. This paper extends the understanding of the potential utility and usability of axisymmetric shape-change. First, we present 16 potential use cases for a cylindrical shape-changing display. Second, we present a two-month comparative field study in the workplace. Six participants had to shift energy consumption by using energy storage. To do so, they were notified about local energy forecasts. Compared with flat-screen animations, early results show that cylindrical shape-change animations keep a better attractiveness over time.

International audience; Due to decarbonisation and decentralisation of energy sectors, the rise of distributed generation (DG) will modify generation and demand patterns at grid supply points (GSPs), where the interface between distribution and transmission systems takes place. With the increasing penetration of such devices, methodologies able to evaluate its contribution to both local distribution network and transmission system become crucial. This paper proposes an analytical method to evaluate the DG locational incremental contribution (LIC) to the interface with the transmission grid. Accordingly, the original model of the UK engineering recommendation P2 is enhanced by studying the impacts from high-voltage distribution networks (i.e. ≤ 132 kV) under normal and contingent conditions. This approach enables a more accurate network security assessment, especially when considering contingencies such as distribution system faults. To illustrate the proposed method, the original P2 model is compared against different enhanced approaches on three basic distribution networks, followed by a case study and a sensitivity analysis on a revised IEEE 14-bus GSP system. The proposed LIC method produces results that assess a wider range of conditions including DG penetration, concentration, and system reliability. Furthermore, it provides an increased DG visibility for transmission planning and operation.

Social media and other platforms on Internet are commonly used to communicate and generate information. In many cases, this information is not validated, which makes it difficult to use and analyze. Although there exist studies focused on information validation, most of them are limited to specific scenarios. Thus, a more general and flexible architecture is needed, that can be adapted to user/developer requirements and be independent of the social media platform. We propose a framework to automatically and in real-time perform credibility analysis of posts on social media, based on three levels of credibility: Text, User, and Social. The general architecture of our framework is composed of a front-end, a light client proposed as a web plug-in for any browser; a back-end that implements the logic of the credibility model; and a third-party services module. We develop a first version of the proposed system, called T-CREo (Twitter CREdibility analysis framework) and evaluate its performance and scalability. In summary, the main contributions of this work are: the general framework design; a credibility model adaptable to various social networks, integrated into the framework; and T-CREo as a proof of concept that demonstrates the framework applicability and allows evaluating its performance for unstructured information sources; results show that T-CREo qualifies as a highly scalable real-time service. The future work includes the improvement of T-CREo implementation, to provide a robust architecture for the development of third-party applications, as well as the extension of the credibility model for considering bots detection, semantic analysis and multimedia analysis. This research was supported by the FONDO NACIONAL DE DESARROLLO CIENTIFICO, TECNOLOGICO Y DE INNOVACION TECNOLOGICA ~ FONDECYT as an executing entity of CONSEJO NACIONAL DE CIENCIA, TECNOLOGIA E INNOVACION TECNOLOGICA - CONCYTEC under grant agreement No. 01-2019-FONDECYT-BM-INC.INV in the project RUTAS: Robots for Urban Tourism centers, Autonomous and Semantic-based.

In this paper a hierarchical energy management strategy design methodology for total cost of ownership management at fleet level is proposed. The decisions are taken from the fleet level point of view, to optimize the whole fleet based on the hierarchical decision maker and management, composed of three levels. The outer part is the offline route-to-bus data exploitation and decision maker, aiming to establish the dynamic programming optimization design. The next level is the offline optimization bus-to-route. Based on the previous decision, the neuro-fuzzy learns from the global optimal solutions. Finally, the trained fuzzy-logic strategy is used to manage the online operation. This fleet is re-organized and the online operation energy management strategy is updated throughout the bus lifetime. These decisions are made based on the evaluated battery lifetime of the fleet, with the aim to meet the planned total cost of ownership requirements. The total cost of ownership for the bus-to-route energy management strategy, has been improved a 7.65 % at fleet level against a charge-sustaining charge-depleting strategy. In the route-to-bus fleet re-organization and update, up to 5.51 % total cost of ownership improvement at fleet level has been obtained against not applying the fleet management.

Twitter is one of the most popular information source available on the Web. Thus, there exist many studies focused on analyzing the credibility of the shared information. Most proposals use either Twitter API or web scraping to extract the data to perform such analysis. Both extraction techniques have advantages and disadvantages. In this work, we present a study to evaluate their performance and behavior. The motivation for this research comes from the necessity to know ways to extract online information in order to analyze in real-time the credibility of the content posted on the Web. To do so, we develop a framework which offers both alternatives of data extraction and implements a previously proposed credibility model. Our framework is implemented as a Google Chrome extension able to analyze tweets in real-time. Results report that 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.

Until now, construction is an area where most activities are artisanal. Concrete is linked to the masonry trade where few machines are used. Moreover, this material is mainly used for building construction, but it can be used for other applications like urban furniture for example where a mold is necessary to pour and maintain the concrete until it is dry. This method can be expensive for unique part because of the implementation time. Moreover, the part geometry is limited by the mold shape. For a few years, the additive manufacturing is used with the concrete material, mainly to build house walls but without finishing step to have smooth or assembling surfaces. So, it is composed by the layers of concrete and it is difficult to assembly two parts for example because of the shape but also dimensional accuracy. For these reasons, in the frame of the HINDCON project, a low-cost subtractive task has been introduced, to perform post-printing machining with respect of geometrical constraints.

International audience; We present two design solutions and an experimental platform that highlight the benefits of tangible interfaces in guiding visitors in museums while ensuring a better distribution of their attention between the exhibition and the guidance. We explore the use of the interactionattention continuum of Bakker et al. to design interfaces that allow the visitor to regulate his attention at different times of the visit. The Visiting Stick draws on the walking habits and the Marauder's Brochure extends the use of a recurring museum object, the visit brochure, by augmenting it with a dynamic display and various tactile and kinesthetic modalities. We have thus designed and built a physical experimental platform using several sensory channels: visual, audio and haptic (using heat, vibration and change of shape) to guide visitors. This platform will allow us in future work to compare the different modalities and their combination for guiding in the museum.

International audience; As stated in the literature, Low Power Listening (LPL) duty cycle is one of the most common energy conservation solution for WSN. By using channel check mechanism, the purpose of LPL solutions is to reduce the energy consumption of the listening phase. In this paper, we propose to study the performances and limitations of this kind of solutions. Therefore, we deploy a ContikiMAC LPL on both real and simulated WSN platform to demonstrate the impact of LPL on the energy consumptions of the node radio and microcontroller but also on the application Quality of Service. Based on the obtained results, shortcomings of LPL solutions are highlighted and potential improvements are discussed such as the use of multi-parameter dynamic duty cycle.

This paper develops a novel two-stage coordinated volt-pressure optimization (VPO) for integrated energy systems (IES) networked with energy hubs considering renewable energy sources. The promising power-to-gas (P2G) facilities are used for improving the interdependency of the IES. The proposed VPO contains the traditional volt-VAR optimization functionality to mitigate the voltage deviation while ensuring a satisfying gas quality due to the hydrogen mixture. In addition to the conventional voltage regulating devices, i.e., on-load tap changers and capacitor banks, P2G converter and gas storage are used to address the voltage fluctuation problem caused by renewable penetration. Moreover, an effective two-stage distributionally robust optimization (DRO) based on Wasserstein metric is utilized to capture the renewable uncertainty with tractable robust counterpart reformulations. The Wasserstein-metric based ambiguity set enables to provide additional flexibility hedging against renewable uncertainty. Extensive case studies are conducted in a modified IEEE 33-bus system connected with a 20-node gas system. The proposed VPO provides a voltage-regulated economic operation scheme with gas quality ensured that contributes to high-quality but low-cost multi-energy supply to customers. British Council (Grant Number: 515761951); National Natural Science Foundation of China (Grant Number: 72042018 and 71621002).

International audience; Solar radiation prediction has a great importance for many applications such as PV power forecasting and solar water heaters. The need of solar radiation prediction increase over time and certainly the accurate prediction can greatly improve the performance of these applications. In this paper a prediction of solar radiation for a winter day using ARMA model is performed. The performance of this model to predict the solar radiation has been validated for a real database. Simulations results show that the effectiveness of ARMA model is proven to predict especially the small variation of solar radiation.

The widespread diffusion of smart and mobile devices continuously connected to the Internet has facilitated the users’ contact and interaction with other people, devices, and with their physical surroundings. Proxemic interaction, derived from proxemics theory, focuses on how Human-Computer Interaction (HCI) works with smart devices, using the five proxemic dimensions: Distance, Identity, Location, Movement, and orientation (DILMO). The current tools for developing proxemic applications require fixed devices that make it difficult to build proxemic mobile apps. In this work, we propose a framework to manage all components in a proxemic environment (i.e., interaction objects and DILMO dimensions that govern the HCI). We demonstrate and evaluate the effectiveness and suitability of our framework, through the development of two proxemic mobile applications, as proof-of-concept.