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Inverse problem for the Helmholtz equation and singular sources in the divergence form
No full textInternational audienceWe shall discuss an inverse problem where the underlying model is related to sources generated by currents on an anisotropic layer. This problem is a generalization of another motivated by the recovering of magnetization distribution in a rock sample from outer measurements of the generated static magnetic field. The original problem can be formulated as inverse source problem for the Laplace equation [1,2] with sources being the divergence of the magnetization whereas the generalization comes from taking the Helmholtz equation. Either inverse problem is non uniquely solvable with a kernel of infinite dimension. We shall present a decomposition of the space of sources that will allow us to discuss constraints that may restore uniqueness and propose regularization schemes adapted to these assumptions. We then present some validating experiments and some related open questions
Lessons Learned From the SoBeezy Program for Older Adults During the COVID-19 Pandemic: Experimentation and Evaluation
No full textInternational audienceBackground: The SoBeezy program is an innovative intervention aimed at promoting and fostering healthy aging and aging in place by proposing to older adults concrete solutions to face daily life, tackle loneliness, promote social participation, and reduce the digital divide, thanks to a specific, easy-to-use voice assistant (the BeeVA smart display). Objective: This study aims to assess the acceptability of the SoBeezy program and its voice assistant and to identify potential areas of improvement. Methods: A 12-month experimentation of the program was deployed in real-life conditions among older adults living in the community in 4 pilot cities of France. Launched during the first lockdown of the COVID-19 crisis, this multisite study aimed to assess acceptability using questionnaires and interviews conducted at baseline and at the end of the experimentation. In addition, a series of meetings were conducted with SoBeezy staff members to obtain direct feedback from the ground. Results: In total, 109 older individuals were equipped with BeeVA to use the SoBeezy program; of these, 32 (29.4%) left the experimentation before its end and 69 (63.3%) completed the final questionnaires. In total, 335 interventions were conducted and 27 (39%) of the participants requested services, mainly for supportive calls and visits and assistance with shopping, transportation, and crafting-gardening. Of the whole sample, 52 (75%) considered BeeVA as a reassuring presence, and few persons (15/69, 22%) reported a negative opinion about the program. Among the participants, the voice assistant appeared easy to use (n=57, 82%) and useful (n=53, 77%). They also were positive about the BeeVA smart display and the SoBeezy intervention. Conclusions: This multisite study conducted in real-life conditions among more than 100 older adults living in the community provides enlightening results of the reality from the ground of digital tools designed for the aging population. The COVID-19 context appeared both as an opportunity, given the massive needs of the older adults during this crisis, and as limiting due to sanitary constraints. Nevertheless, the experimentation showed overall good acceptability of the voice assistant and a high level of satisfaction of the participants among those who really used the system and could be a way of improving the autonomy and well-being of older adults and their families. However, the findings also highlighted resistance to change and difficulties for the users to ask for help. The experimentation also emphasized levers for next deployments and future research. The next step will be the experimentation of the activity-sharing component that could not be tested due to the COVID-19 context
Stratégie de détection des Falsifications des Positions des Messages AIS Basée sur l'Application du Filtre IMM
No full textInternational audienceThe Automatic Identification System (AIS) enhances safety and control of vessel traffic by allowing vessels to exchange navigational information with each other and with terrestrial control stations. However, because AIS is not secure, the positions sent can be easily falsified. In this paper, we present a strategy that detects position falsifications applying an interactive multiple model filter. The results obtained on real and simulated AIS data show the effectiveness of this strategy for this type of application.Le système d'identification automatique (AIS) améliore la sécurité et le contrôle du trafic maritime en permettant aux navires d'échanger des informations de navigation entre eux et avec les stations de contrôle terrestre. Cependant, l'AIS n'étant pas sécurisé, les positions envoyées peuvent être facilement falsifiées. Dans cet article, nous présentons une stratégie de détection des falsifications des positions des navires qui applique un filtre à modèles multiples interactifs. Les résultats obtenus sur des données AIS réelles et simulées montrent l'efficacité de cette stratégie pour ce type d'application
Émulation de Systèmes Cyber-Physiques sur FPGA
No full textInternational audience-Les FPGAs permettent aujourd'hui la conception de systèmes programmables complets sur puce (SoC) capables de couvrir une gamme extrêmement large d'applications, allant des systèmes embarqués classiques à la virtualisation dans le cloud. Toutefois, le potentiel des FPGAs ne s'arrête pas là. Leur flexibilité et leur parallélisme naturel invitent à explorer leur utilisation dans des domaines plus confidentiels. Dans cet article, nous nous intéressons à l'émulation de systèmes cyber-physiques complets sur FPGA. Notre cas d'étude présente l'émulation d'un système constitué d'une multitude de navires communicant selon le protocole d'identification AIS. L'étude démontre un facteur d'accélération de 75 par rapport à l'exécution purement logicielle, et permet d'esquisser un flot de conception adapté au domaine de l'émulation de tels systèmes sur FPGAs
The Effect of Agglomeration on the Electrical and Mechanical Properties of Polymer Matrix Nanocomposites Reinforced with Carbon Nanotubes
No full textInternational audienceIn this work, we investigated the effect of carbon nanotubes addition and agglomeration formation on the mechanical and electrical properties of CNT–polymer-based nanocomposites. Six specimens with carbon nanotubes (CNTs) fractions of 0%, 0.5%, 1%, 2%, 4% and 5% were manufactured and characterized by dynamic mechanical analysis (DMA) and four-probe method. The stress–strain curves and electrical conductivity properties were obtained. Scanning electron microscopy (SEM) was used to characterize both agglomeration and porosity formation. By employing micromechanics, through representative volume element (RVE), finite element analysis (FEA) and resistor network model (RNM), the Young’s modulus and electrical conductivity values were calculated. The samples’ elastic moduli showed an increment, reaching the maximum value at a CNTs fraction of 2%, thereafter an adverse effect was caused in the high CNT percentage samples. The final electrical conductivity seemed greatly altered with the addition of CNTs, reaching the percolation threshold at 2%. The unavoidable formation of CNT agglomerates appeared to influence the final physical properties. The CNT agglomerates adversely affect the mechanical performance of high-CNT-percentage samples. Conversely, an exponential increment in the electrical conductivity was presented as the agglomerates formed networks allowing the transport of electrons through the tunnelling effect. These phenomena were experimentally and numerically confirmed, showing a good correlation
An Extended Modeling Approach for Marine/Deep-Sea Observatory
No full textInternational audienceA Sensor Network (S.N.) is responsible for performing two main activities: (1) observation/measurement, which means accumulating data collected at each sensor node; (2) transferring the collected data to processing centers (e.g., Smart Sensors, Smart Fusion Servers) within the S.N. The infrastructure of Marine/Deep-sea Observatory is an Underwater Sensor Networks (UW-SN) to perform collaborative monitoring tasks over a given ocean/sea area. This observation should consider the environmental constraints since it may require specific logical and physical components. The physical ones could be specific tools, materials, and devices such as marine cables, servers, etc.). As for the logical ones, specific algorithms could validate the implementation phase early, such as validating the allowable entered bandwidth ranges of underwater acoustic channels. This paper presents our approach in extending the modeling languages to include new domain-specific concepts and constraints. Thus, we propose an extended meta-model that is used to generate a new design tool that contains the new constraints. We illustrate our proposal with an example from the Marine Observatory (MO) domain on object localization with several acoustics sensors. Additionally, we generate the corresponding simulation code for a standard network simulator using our self-developed domain-specific model compiler. Our approach helps to reduce the complexity and time of the design activity of a Marine Observatory. It provides a way to share the different viewpoints of the designers in the MO domain and obtain simulation results to estimate the network capabilities. The major improvement is to provide an early validation step via models and a simulation approach to consolidate the system design
Étude pilote d'une intervention basée sur un système tutoriel intelligent (STI) pour enseigner les mathématiques à des collégiens avec TSA et/ou DI.
No full textInternational audienceFew technology-based interventions have addressed mathematical and numeracy skills of individuals with autism spectrum disorder (ASD). However, children and adolescents with ASD may experience difficulties in mathematical learning, and even be behind their peers at school. Intelligent Tutoring System (ITS) is an innovative way for enhancing teaching programs through learning optimization algorithms coping interindividual differences in the educational curriculum progress. They have been used with success with typically-developed students for levering on the linkage learning-motivation, but remains at a theoretical stage for students with ASD and/or intellectual disability (ID). We conducted a pilot study to assess an ITS-based intervention embedded into the KidLearn application for instructing mathematical skills (i.e., adding and subtracting numbers between 0 and 100). Twenty-four secondary school students with ASD and/or intellectual disability, enrolled from special education classrooms, have been recruited: 14 students received the KidLearn intervention, while the 10 others received control intervention. Pre-post assessments showed that calculation and motivational measures were significantly improved in KidLearn condition compared to the control condition. ITS intervention appeared relevant for calculation learning in the setting of special education
RISCLESS: A Reinforcement Learning Strategy to Exploit Unused Cloud Resources
No full textOne of the main objectives of Cloud Providers (CP) is to guarantee the Service-Level Agreement (SLA) of customers while reducing operating costs. To achieve this goal, CPs have built large-scale datacenters. This leads, however, to underutilized resources and an increase in costs. A way to improve the utilization of resources is to reclaim the unused parts and resell them at a lower price. Providing SLA guarantees to customers on reclaimed resources is a challenge due to their high volatility. Some state-of-the-art solutions consider keeping a proportion of resources free to absorb sudden variation in workloads. Others consider stable resources on top of the volatile ones to fill in for the lost resources. However, these strategies either reduce the amount of reclaimable resources or operate on less volatile ones such as Amazon Spot instance. In this paper, we proposed RISCLESS, a Reinforcement Learning strategy to exploit unused Cloud resources. Our approach consists of using a small proportion of stable on-demand resources alongside the ephemeral ones in order to guarantee customers SLA and reduce the overall costs. The approach decides when and how much stable resources to allocate in order to fulfill customers' demands. RISCLESS improved the CPs' profits by an average of 15.9% compared to state-of-the-art strategies. It also reduced the SLA violation time by an average of 36.7% while increasing the amount of used ephemeral resources by 19.5% on averag
Robustness Testing of a Machine Learning-based Road Object Detection System: An Industrial Case
No full textInternational audienceWith the increasing development of critical systems based on artificial intelligence (AI), methods have been proposed and evaluated in academia to assess the reliability of these systems. In the context of computer vision, some approaches use the generation of images altered by common perturbations and realistic transformations to assess the robustness of systems. To better understand the strengths and limitations of these approaches, we report the results obtained on an industrial case of a road object detection system. By comparing these results with those of reference models, we identify areas for improvement regarding the robustness of the system and the metrics used for this evaluation
Robust MILP formulations for the two-stage weighted vertex p-center problem
No full textThe weighted vertex p-center problem (PCP) consists of locating p facilities among a set of potential sites such that the maximum weighted distance from any client to its closest open facility is minimized. This paper studies the exact resolution of the two-stage robust weighted vertex p-center problem (RPCP2). In this problem, the opening of the centers is fixed in the first stage while the client allocations are recourse decisions fixed once the uncertainty is revealed. The problem uncertainty comes from both the nodal demands and the edge lengths. It is modeled by box uncertainty sets. We introduce three different robust reformulations based on MILPs from the literature. We prove that considering a finite subset of scenarios is sufficient to obtain an optimal solution of (RPCP2). We leverage this result to introduce a column-and-constraint generation algorithm and a branch-and-cut algorithm to efficiently solve this problem optimally. We highlight how these algorithms can be adapted to solve, for the first time to optimality, the single-stage problem (RPCP1) which is obtained when no recourse is considered. We present a numerical study to compare the performance of these formulations on randomly generated instances and a case study from the literature