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A coclustering and computational intelligence-based approach for internet-of-things services composition
No full textInternational audienceThe Internet of Things (IoT) paradigm aims at interconnecting heterogeneous devices, called smart objects and seamlessly offering a multitude of services tailored to the user requirements. With the extremely rapid growth of the number of connected objects, the IoT services composition process becomes an NP-hard challenge due to the very high increase of the number of services offering similar functionalities but that may differ in their Quality of Service (QoS) parameter values. Various approaches have been proposed in the literature to obtain compositions with suboptimal QoS in a reasonable computation time. However, when the number of services and QoS parameters increases, the performance of these approaches is limited in terms of the composition time and/or the QoS utility of the composition. To address these limitations, a coclustering-based approach for QoS-constrained services composition (CoQSC) is proposed to reduce the composition space and improve the composition time as well as the composition utility. Unlike existing services composition algorithms where the composition space is reduced only in terms of the number of candidate services, the CoQSC approach exploits a coclustering method to reduce both the number of candidate services and the number of QoS parameters to be considered in the composition process. This reduction allows the composition process to find suboptimal compositions in a reduced computation time using eight among the most representative and recent computational intelligence (CI) techniques in the literature separately. The formulation of the CoQSC approach is complemented by a complexity analysis. Simulation scenarios show that the CoQSC approach significantly improves the QoS utility of composition and substantially decreases the composition time compared to recent and representative state-of-the-art composition approaches, making it suitable for large-scale IoT service environments
Urgence: villes en surchauffe. Comment et à quel point la climatisation transforme les sociétés urbaines?
No full textArchaeological Mission of Bat / Al-Arid avec sous-titrage en français
No full textLa même vidéo existe en anglais sous-ttrée en arabe (sous-titrage Georges Mouamar)The same video is available in English with Arabic subtitles (subtitles by Georges Mouamar).OmanHydrauliqueIrrigationMétallurgie du cuivre3e millénaireAge du Bronz
Leveraging the integration of perovskite BaTiO<sub>3</sub> on ferroelectric fluorite HfO<sub>2</sub> to enhance energy storage cyclability and efficiency
No full textInternational audiencePerovskite relaxor ferroelectrics and antiferroelectrics have been the workhorse materials for energy storage applications. Recently, there has been growing interest in ferroelectric HfO2 , which is highly integrable and scalable down to the ultrathin limit. However, wake-up and fatigue phenomena in ferroelectric HfO2 are serious limitations. Interface engineering using simple AxOy binary oxides as capping layers is a promising strategy to mitigate these effects. Instead of using AxOy, we demonstrate that the integration of perovskite ferroelectric BaTiO3 as capping layer of fluorite ferroelectric Hf0.5Zr0.5O2 allows to obtain a highly cyclable and stable energy storage device of enhanced efficiency on Si(001). We study a set of samples combining epitaxial Hf0.5Zr0.5O2 with polycrystalline BaTiO3 of various thicknesses. The ferroelectricity of Hf0.5Zr0.5O2 is preserved and the efficiency is enhanced without compromising its high breakdown voltage. The device performance is optimal in terms of energy storage capacity, efficiency and breakdown field for a BaTiO3 thickness of 10 nm. We discuss the improved efficiency in terms of the role of depolarizing electric fields and the improved stability in terms of the smoother device band diagram owing to the BaTiO3 presence. These particular characteristics are attained thanks to the distinct electrical properties of BaTiO3 compared with previously investigated simpler AxOy capping layers. The investigations presented here can help to develop new strategies to enhance the energy storage efficiency in hafnia-based devices fully compatible with industrial processes
Fracture Toughness of Periodic Beam Lattices
No full textInternational audienceThe study tackles the challenge of accurately modeling fracture behavior in beam lattices, which is essential for designing robust architected materials. Our research focuses on evaluating how the lattice's microstructure and material properties affect fracture toughness. We employed finite element simulations based on the Euler-Bernoulli beam theory to investigate crack propagation, using a failure criterion that initiates beam fracture when maximum axial stress exceeds critical strength. Building on observations from these simulations, we developed a multi-phase-field fracture model with Cosserat elasticity to integrate consistent toughness characteristics into a comprehensive framework for lattice design. This model was validated through experimental tests, ensuring a close match between theoretical predictions and physical reality. Our findings reveal that the energy release rate remains relatively stable during crack propagation, underscoring its reliability as a measure of the toughness of periodic lattice structures. We discovered that toughness is predominantly influenced by beam height and material properties such as tensile strength and Young's modulus, while slenderness has minimal impact. Additionally, cracks were observed to preferentially propagate along the lattice's structural directions due to stress localization effects, highlighting the importance of the microstructure in fracture behavior. The implications of this research are significant, suggesting that improved modeling of fracture in lattice structures can enhance material design reliability and optimization. This study bridges the gap between theoretical models and real-world applications, providing valuable insights for the development of advanced materials with tailored fracture properties
Stetoscope: underStand TargEting and manipulaTiOnS via COllaborative Private data collEction
No full textInternational audienceContent personalization is ubiquitous on the web and mobile applications. However, the mechanisms that practically control this personalization by the different parties in the targeted advertising ecosystem remain unclear, raising serious questions about possible user manipulations to encourage them to take certain actions (e.g., consent to cookies, purchase a product). Due to its user-centric nature, it is technically difficult to collect this personalization in order to analyze it on a large scale. In this paper, we present Stetoscope (underSTand targETing and manipulatiOnS via COllaborative Private data collEction), a participative mobile application to analyze content personalization. Instead of relying on bots for data collection (which are subject to detection by platforms and may induce bias in the content), Stetoscope engages individuals by providing them with data collection campaigns linked to legitimate questions posed by citizens (e.g., is there price discrimination on this platform? Is this incentive message trustworthy?). A data collection campaign guides the user to specific web pages or mobile applications where a screenshot is triggered by the participant to collect the targeted information. These screenshots are then analyzed on a backend server to draw conclusions. This participatory application allows users to be involved in issues related to different forms of personalization on mobile, such as the analysis of dark patterns, price or search discrimination, the exchange of personal information with third parties, trust in incentive messages, or information bubbles for instance. To assess the prospects and limitations of the Stetoscope, we conducted preliminary data collection campaigns on e-commerce, bus and hotel booking, and recruitment platforms. Our preliminary results show evidence of search discrimination on most platforms, evidence of price discrimination on AliExpress, and evidence of fake discounts during Black Friday on Temu and on many e-commerce platforms before and after Christmas
Regularizing the inverse problem of ultrasound beamforming with non-local structure tensor total variation
No full textInternational audienc
On the partial Grundy coloring of graphs
No full textInternational audienceIn a proper vertex coloring of a graph, a Grundy vertex is a vertex colored with color c and adjacent to any color 1 to c-1. A partial Grundy coloring of a graph is a proper coloring of its vertices where any color admits at least one Grundy vertex. The partial Grundy number of a graph is the maximum number of colors used in a partial Grundy coloring of this graph. In this article we consider this parameter for some classes of graphs, in particular -free graphs, regular graphs, Cartesian and direct products of graphs
Stratégies de Stabilisation pour les EDP linéarisées par des méthodes d'optimisation
No full textWe adapt an optimization technique, originally developed for quadratic matrix model updating problems, to construct optimal stabilizers for linearized partial differential equations (PDEs). The proposed approach is flexible, allowing the optimization of mass, damping, and stiffness operators either individually or simultaneously. It is also straightforward to implement within standard numerical frameworks. We analyze the numerical and practical properties of the method, highlighting its robustness even with loworder discretizations and its capacity to produce interpretable stabilization operators. The effectiveness and versatility of the approach are demonstrated through numerical experiments on several representative linearized PDEs, including the Klein-Gordon, Boussinesq, Benjamin-Bona-Mahony, and Korteweg-de Vries equations. Our results indicate that the method provides a unified, efficient, and modular tool for PDE stabilization.Nous adaptons une technique d'optimisation, initialement développée pour les problèmes de mise à jour de modèles matriciels quadratiques, afin de construire des stabilisateurs optimaux pour les équations aux dérivées partielles (EDP) linéarisées. L'approche proposée est flexible, elle permet l'optimisation des opérateurs de masse, d'amortissement et de rigidité individuellement ou simultanément. Elle est également facile à implémenter dans les environnements numériques standards. Nous analysons les propriétés numériques et pratiques de la méthode, en soulignant sa robustesse même avec des discrétisations d'ordre faible et sa capacité à produire des opérateurs de stabilisation interprétables. L'efficacité et la polyvalence de l'approche sont démontrées par des expériences numériques sur plusieurs EDP linéarisées représentatives, notamment les équations de Klein-Gordon, de Boussinesq, de Benjamin-Bona-Mahony et de Korteweg-de Vries. Nos résultats indiquent que la méthode constitue un outil unifié, efficace et modulaire pour la stabilisation des EDP
« Inventaire utopiste. Des pratiques d’inventaire aux imaginaires technologiques »
No full textInternational audienceCet article présente le projet Inventaire utopiste de Marie Lukasiewicz, qui explore le geste d’inventorier à travers une approche transdisciplinaire mêlant photographie, enregistrements sonores et technologies numériques (spectrogrammes, outils de restauration sonore, impression 3D). En détournant les codes de l’esthétique scientifique, le projet questionne les logiques de classification, de hiérarchisation et de mise en ordre du réel, tout en mettant en lumière les dimensions esthétiques, affectives et politiques de l’inventaire dans un contexte de crise écologique. À mi-chemin entre restitution d’entretien, lecture photographiques et réflexions épistémologiques, l’article interroge les régimes de temporalité et les imaginaires spéculatifs que mobilise le geste d’inventaire au sein des disciplines artistiques et scientifiques