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On the Design of a Dynamic Consensus Framework for Agreement Seeking in Maneuver Coordination
No full textInternational audienceThis paper introduces a dynamic consensus framework to improve the reliability of maneuver coordination inautonomous driving. Traditional consensus algorithms face limitations in vehicular networks, where specific vehicles mayneed to explicitly agree on maneuvers to ensure road safety.The proposed framework dynamically selects the most suitableconsensus protocol based on the roles of the vehicles involvedand the nature of the maneuver. In this scheme, full alignmentis achieved between the execution of the consensus algorithmand the standard vehicular communication service for maneuvercoordination, regarding group selection and the role of each nod
A hardware design methodology to prevent microarchitectural transition leakages
No full textInternational audienceSide-channel attacks allow information extraction from a system by analyzing indirect observations. For instance, power consumption is known to be correlated with sensitive data manipulated by digital components. Recent efforts have been put on securing the system at the software level with a formally proven method called masking. They rely on an abstract model of the target where automatic countermeasures can be efficiently applied. Recent work focused on microarchitecture, i.e. implementation details of the hardware, to deal with residual vulnerabilities which require strong knowledge of the system's hardware and have limited portability. In this paper, we present a generic methodology to harden the processor's microarchitecture to allow straightforward software defense strategy implementation (like masking) with minimal knowledge of the hardware. Based on a fine-grained vulnerability diagnosis at the microarchitecture level and a generic design hardening strategy, our proposition can be applied to produce several processors with security, performance and area tradeoffs. In addition, we provide two secured designs based on a customizable RISC-V processor and its memories, validated with real measurements on an FPGA
Simulation du LiDAR, des Véhicules Terrestres Autonomes et des Réseaux Neuronaux pour L'estimation de la Surface Foliaire dans les Vergers
No full textInternational audienceThe leaf area index (LAI) is vital for assessing plant photosynthetic activity, crucial for optimising orchard management. This study presents a method to estimate leaf area density (LAD) variations and tree LAI using LiDAR data from unmanned ground vehicles (UGVs). Combining 3D tree reconstruction with neural network-based analysis of LiDAR penetration descriptors, the approach effectively estimates canopy parameters. The method was validated through simulation using diverse 3D canopy models, achieving performance metrics: RMSE: 0.2 m²/m³, R²: 0.95 for LAD and RMSE: 0.17 m²/m², R²: 0.84 for LAI. Results confirm the potential of LiDAR-based systems for precise orchard canopy monitoring.El índice de área foliar (LAI) es fundamental para evaluar la actividad fotosintética de las plantas, un parámetro clave para la optimización de la gestión de huertos. Este estudio presenta un método para estimar las variaciones de la densidad de área foliar (LAD) y el LAI de los árboles a partir de datos LiDAR adquiridos por vehículos terrestres autónomos (UGV). Al combinar la reconstrucción 3D de los árboles con un análisis de descriptores de penetración LiDAR mediante redes neuronales, el enfoque permite una estimación eficaz de los parámetros del dosel. La metodología fue validada mediante simulaciones con diversos modelos 3D de copas, obteniendo métricas de rendimiento: RMSE: 0,2 m²/m³, R²: 0,95 para LAD y RMSE: 0,17 m²/m², R²: 0,84 para LAI. Los resultados confirman el potencial de los sistemas basados en LiDAR para el monitoreo preciso del dosel en huertos.L'indice de surface foliaire (LAI) est essentiel pour évaluer l'activité photosynthétique des plantes, un paramètre clé pour l'optimisation de la gestion des vergers. Cette étude propose une méthode d'estimation des variations de la densité de surface foliaire (LAD) et du LAI des arbres à partir de données LiDAR acquises par des véhicules terrestres autonomes (UGV). En combinant la reconstruction 3D des arbres avec une analyse des descripteurs de pénétration LiDAR par réseaux neuronaux, l'approche permet une estimation efficace des paramètres du couvert végétal. La méthode a été validée par simulation sur divers modèles 3D de canopées, obtenant des performances de RMSE : 0,2 m²/m³, R² : 0,95 pour le LAD et RMSE : 0,17 m²/m², R² : 0,84 pour le LAI. Les résultats confirment le potentiel des systèmes basés sur le LiDAR pour un suivi précis du couvert végétal des vergers
Certified bounds on optimization problems in quantum theory
No full textInternational audienceSemidefinite relaxations of polynomial optimization have become a central tool for addressing the non-convex optimization problems over non-commutative operators that are ubiquitous in quantum information theory and, more in general, quantum physics. Yet, as these global relaxation methods rely on floating-point methods, the bounds issued by the semidefinite solver can - and often do - exceed the global optimum, undermining their certifiability. To counter this issue, we introduce a rigorous framework for extracting exact rational bounds on non-commutative optimization problems from numerical data, and apply it to several paradigmatic problems in quantum information theory. An extension to sparsity and symmetry-adapted semidefinite relaxations is also provided and compared to the general dense scheme. Our results establish rational post-processing as a practical route to reliable certification, pushing semidefinite optimization toward a certifiable standard for quantum information science
Conception et réalisation d’une cellule photovoltaïque pour l’intégration dans un système hybride photovoltaïque-thermoélectrique
No full textNational audienceThe concept of photovoltaic–thermoelectric hybridization (PVTEG) emerged in the 2010s. Originally, these systems were designed to support photovoltaic (PV) cells in configurations with variable illumination, such as embedded photovoltaics. For over 15 years, the idea of a hybrid PV system capable of supplying sufficient power to operate IoT devices without batteries has generated significant interest. However, the appeal of PV-TEG hybrid systems has diminished with the continuous improvement of PV technologies: the efficiency losses due to cell heating are no longer compensated by the relatively low efficiency of current thermoelectric modules. Therefore, to maintain high conversion efficiency, it becomes essential to minimize the thermal resistance between the PV cell and the thermoelectric generator.In this work, we present the development of a fabrication process for a GaAs-based photovoltaic cell, known for its reduced sensitivity to temperature, and its transfer onto a copper substrate, whose high thermal conductivity promotes efficient heat extraction. This thesis focuses on implementing an Au/Au thermocompression bonding process, coupled with the selective removal of the GaAs growth substrate. This process required fine optimization of bonding parameters to mitigate mechanical stress resulting from the thermal expansion mismatch between GaAs and Cu, while ensuring a stable and conductive interface.In parallel, a probe-based and illuminated characterization platform was designed to evaluate the performance of the transferred cells. Finally, a multiphysics model, initially developed in Sébastien Hanauer's thesis, was adapted to simulate the thermal and electrical behavior of the hybrid PV-TEG system. This model enables prediction of the system’s electrical and thermal properties, paving the way for optimized PVTEG device design.This work lays the groundwork for the development of high-efficiency photovoltaic cells mounted on metallic heat spreaders from the perspective of functional PV-TEG hybridization and highlights the importance of a combined process characterization and modeling approach to addressing the challenges of thermal integration.Le concept d'hybridation photovoltaïque-thermoélectrique (PVTEG) est apparu dans les années 2010. Originellement, ces systèmes étaient conçus pour soutenir une cellule photovoltaïque dans des configurations avec une illumination variable, comme du photovoltaïque embarqué. L'idée d'un système hybride photovoltaïque qui fournirait assez de puissance pour alimenter des systèmes IoT sans batterie intéresse depuis plus de 15 ans. Or, ces hybridations PV-TEG perdent de leur intérêt avec l’amélioration des technologies photovoltaïques : la perte de rendement causée par l’échauffement de la cellule n’est pas compensée par la faible efficacité des modules thermoélectriques actuels. Ainsi, pour préserver les performances de conversion, il devient crucial de réduire au maximum la résistance thermique entre la cellule et le générateur thermoélectrique.Nous présentons ici le développement d’un procédé de fabrication d’une cellule photovoltaïque en GaAs, notoirement moins sensible à la température, et son transfert sur un substrat de cuivre, dont la conductivité thermique élevée favorise l’extraction de chaleur. Le cœur de cette thèse repose sur la mise en œuvre d’un collage par thermocompression Au/Au, couplé à un processus d’enlèvement sélectif du substrat de croissance GaAs. Ce procédé a nécessité l’optimisation fine des paramètres de collage afin de limiter les contraintes mécaniques induites par la différence de coefficients de dilatation entre le GaAs et le Cu, tout en assurant une interface conductrice et mécaniquement stable.Parallèlement, un banc de caractérisation sous pointes et sous illumination a été conçue afin d’évaluer les performances des cellules transférées. Enfin, un modèle multiphysique développé dans le cadre de la thèse de Sébastien Hanauer a été adapté pour simuler le comportement thermique et électrique de l’ensemble du système hybride PV-TEG. Ce modèle permet de prédire les propriétés électriques et thermique du système ainsi de tracer la voie vers une meilleure optimisation de ces système PVTEG.Ce travail ouvre la voie au développement de cellules photovoltaïques à haut rendement montées sur dissipateurs thermiques métalliques, dans une optique d’hybridation fonctionnelle PV-TEG, et souligne l’importance d’une approche couplée procédé, caractérisation et modélisation pour relever les défis de l’intégration thermique
MICROWAVE DIELECTRIC SPECTROSCOPY FOR BIOLOGICAL CHARACTERIZATION AND HEALTHCARE APPLICATIONS: EXPLORING THE 3D BIOLOGICAL SCALE
No full textInternational audienceNon-invasive techniques for characterizing biological materials are essential for advancing biomedical research. Among these, microwave dielectric spectroscopy (MDS) has emerged as a powerful method for non-invasive, non-destructive, cost-effective and label-free analysis. By measuring the interaction of microwave frequencies with biological structures, MDS provides insights into hydration, cellular density, and metabolic activity without damaging the sample. While MDS has been successfully applied to 2D biological systems, its adaptation for assessment of 3D samples remains largely unexplored. A few years ago, our team initiated efforts to bridge this gap, and this paper presents our progress while exploring the application of MDS to 3D biological objects, including cancerous hepatic spheroids
A Green Transportation Problem for E-commerce Deliveries
No full textInternational audienceTo get involved in the fight against climate change, e-commerce actors should reduce the environmental impact of their activities. For retailers, a key challenge to is identify the stock sources for fulfilling online orders. In this paper, our goal is to orchestrate orders while minimizing the associated environmental impact. We propose a model of Green Transportation Problem for E-commerce Deliveries (GTP-ED) which can be seen as a general case of Fixed Charge Transportation Problem. We detail how we obtain the environmental objective function and how we generate instances based on real world and realistic data, and that good quality solutions can be obtained quickly. Then, we show the relevance of our environmental objective function by comparing the results with an orchestration based on minimizing the distance traveled by the parcels, which leads to a 30% increase of environmental cost. Finally, we compare the GTP-ED with an economic approach and outline a significant tension between our environmental and economic objectives in that context
Ordonnancement en shifts avec préemption et contraintes de charges maximales de travail
No full textNational audienceWith the constant evolution of industry, supervisors are facing increasingly complex planningsystems. In this context, decision-support tools (DSTs) can help alleviate the cognitive loadexperienced by decision-makers. It is crucial that planning DSTs incorporate a flexible and responsive approach that is adapted to these constraints while ensuring consistent and realistic decision-making in a dynamic environment. We are therefore proposing a new approach to model maximum workload constraints in shift-based scheduling
A MEMS Electromagnetic Vibration Energy Harvester with Monolithically Integrated NdFeB Micromagnets
No full textInternational audienceThe monolithic integration of high‐performance magnets into microfabricated devices remains a technological challenge despite the great interest for telecommunications, automotive, biomedical or space applications. Here the integration of 50 µm thick sputtered arrays of NdFeB micromagnets into a functional micro‐electro mechanical system (MEMS) in‐plane electromagnetic vibration energy harvester is reported. A combination of analytical modeling and numerical simulations guided the design of the magnet arrays along with ad‐hoc planar coils, to produce a high transduction factor. The resulting energy harvesters deliver a voltage of 2.5 mV, a power of 6 nW under an acceleration of 0.8 g and a normalized power density of 3 × 10 −4 kg s m −3 (20 mW m −3 ) for a device volume of roughly 300 mm 3 , which is comparable to state‐of‐the‐art MEMS electromagnetic vibration harvesters. This study serves as a show‐case for the possibility of integrating high‐performance micromagnets into functional devices using microfabrication processes
Influence of high frequency power cycles on SiC power module lifetime under automotive mission profile
No full textInternational audienceSiC MOSFETs have higher thermal impedance compared to their Silicon counterparts for same rated power. For that reason, when used in AC/DC or DC/AC applications, they suffer from temperature variation as high as 40K at frequencies close to 50Hz. This temperature variation, also called Power Cycling, may reduce lifetime of power modules using SiC transistors, which was not the case for Silicon based power modules. These high frequency power cycles are indeed poorly modelled and rarely considered in lifetime estimation model of SiC power modules. This paper presents the procedure to take into account these high frequency power cycles when estimating SiC power module lifetime using automotive mission profiles. The mission profile is used to create representative current waveforms flowing through the power module for the entire mission. Thus, instantaneous SiC die temperature (averaged in each switching period) is calculated, based on precise instantaneous loss estimation coupled with accurate thermal impedance model. The result is a junction temperature profile which contains power cycles at the same frequency of the sinusoidal current flowing through the SiC die. The influence of such "high frequency" power cycles in the total lifetime of a SiC power module is then demonstrated using lifetime models found in literature