Portail HAL UHA (Université de Haute-Alsace)
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L’incommunication : un impensé de la cohabitation culturelle ?
No full textNational audienceOur research, based on an ethnographic approach carried out within an NGO defending people in migrant situations, explores cultural cohabitation, a concept that remains underexplored in Information and Communication Sciences (ICS). Our aim is to integrate the notion of incommunication as a key analytical object for understanding intercultural interactions. In this perspective, we enrich the definition of cultural cohabitation by conceptualising it as a process of incommunication, in which individuals from different cultural backgrounds meet and interact, while recognising and respecting their different ways of being sensitive to the world.Notre recherche, fondée sur une approche ethnographique menée au sein d’une ONG de défense des droits des personnes en situation de migration, explore la cohabitation culturelle, un concept qui reste peu étudié en sciences de l’information et de la communication (SIC). Notre propos vise à intégrer la notion d’incommunication en tant qu’objet essentiel s’agissant de la compréhension des interactions interculturelles. Ainsi, nous enrichissons la définition de la cohabitation culturelle en l’envisageant comme un processus d’incommunication, dans lequel des personnes de cultures différentes se rencontrent et interagissent, tout en reconnaissant et en respectant leur manière d’être sensibles au monde différemment
NIR photothermal activation in epoxy/anhydride systems for advanced polymerization
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Compte rendu : Christine Bénévent, Miroirs d’encre. Reflets d’une lecture
No full textNational audienceBased on the autobiography of her habilitation to supervise research, Christine Bénévent's book offers a reflection on the book at the crossroads of history and literature. The author examines the continuities and ruptures between the book as artefact and the book as text, while at the same time highlighting the epistemological divergences in research in the human sciences that result from focusing on one of these two aspects. Drawing on personal reading experience and social and professional biases, the essay explores the multiple dimensions of the book, its powers and its limits.Issu de l’autobiographie de son habilitation à diriger des recherches, l’ouvrage de Christine Bénévent propose une réflexion sur le livre, au croisement de l’histoire et de la littérature. L’autrice interroge les continuités et les ruptures entre le livre comme artefact et le livre comme texte, tout en soulignant les divergences épistémologiques de la recherche en sciences humaines induites par la focalisation sur l’un de ces deux aspects. À partir d’une expérience de lecture personnelle et de biais d’ordre sociaux et professionnels, l’essai rend compte des dimensions multiples du livre, de ses pouvoirs et de ses limites
Comment préserver nos démocraties entre réseaux sociaux, intelligence artificielle et ingérences étrangèresdans le processus électoral ? À propos de l’annulation du scrutin présidentiel en Roumanie
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Critical Effects of Polarity and Doping on the UV Photocatalysis of ZnO Nanowires
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Multi-objective electric vehicle charging scheduling under stochastic duration uncertainty
No full textInternational audienceThe ongoing electrification of the transport sector, driven by the numerous advantages of electric vehicles (EVs), introduces new challenges related to charging logistics, particularly due to long charging durations and uncertain conditions, posing significant negative impacts on grid stability and user satisfaction. While existing literature on EV charging scheduling often assumes deterministic charging durations, real-world conditions introduce randomness due to uncontrollable factors such as battery state-of-charge (SoC), fluctuating grid demand, and ambient temperature. In this paper, we address the Electric Vehicle Charging Scheduling Problem (EVCSP) under uncertain charging durations. First, we introduce a novel, flexible multi-objective scheduling model operating on a continuous time horizon, considering stochastic charging durations and incorporating controlled preemptions during charging, where the non-preemptive mode is a particular case. Then, we prove that finding a feasible assignment of EVs to chargers is strongly NP-hard under this uncertainty, even assuming identical chargers. Our model accounts for realistic constraints, including heterogeneous charger power levels and vehicle-charger compatibility, aiming to minimize the conditional expected values of grid overload and total tardiness, while also minimizing the undelivered energy to users. Given the problem’s computational complexity, we adapt four evolutionary algorithms (EAs), namely, extensions of the Non-Dominated Sorting Genetic Algorithm (NSGA), namely NSGA-II and NSGA-III, alongside other state-of-the-art multi-objective metaheuristics, including the Multi-Objective Cuckoo Search (MOCS) algorithm, and the Multi-Objective Grey Wolf Optimizer (MOGWO) by defining problem-specific operators to explore the search space and efficiently approximate the optimal Pareto front. Assuming lognormally distributed charging durations, we conducted a comparative experimental analysis on real-world data to evaluate the four methods and revealed that MOCS algorithm outperforms the other competitors
FedWKD: Federated Learning Weighted Aggregation with Knowledge Distillation for IoT Forecasting
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Enhancing Time Series Classification with Diversity-Driven Neural Network Ensembles
No full textInternational audienceEnsemble methods have played a crucial role in achieving state-of-the-art (SOTA) performance across various machine learning tasks by leveraging the diversity of features learned by individual models. In Time Series Classification (TSC), ensembles have proven highly effective whether based on neural networks (NNs) or traditional methods like HIVE-COTE. However most existing NN-based ensemble methods for TSC train multiple models with identical architectures and configurations. These ensembles aggregate predictions without explicitly promoting diversity which often leads to redundant feature representations and limits the benefits of ensembling. In this work, we introduce a diversity-driven ensemble learning framework that explicitly encourages feature diversity among neural network ensemble members. Our approach employs a decorrelated learning strategy using a feature orthogonality loss applied directly to the learned feature representations. This ensures that each model in the ensemble captures complementary rather than redundant information. We evaluate our framework on 128 datasets from the UCR archive and show that it achieves SOTA performance with fewer models. This makes our method both efficient and scalable compared to conventional NN-based ensemble approaches
Bimetallic Pd- and Co-Containing Mesoporous Carbons as Efficient Reusable Nanocatalysts for Hydrogenations of Nitroarenes and Enones Under Mild and Green Conditions
No full textInternational audienceEasy and rapid preparations of magnetic Co-and Pd-containing mesoporous carbons (IM1, IM2 and DM) from green phenolic resins, amphiphilic templates and metallic salts via two synthetic routes are reported. Catalysts IM1 and IM2 are prepared via an indirect method involving two steps, i.e., the preparation of Co-containing mesoporous carbons with different Co contents (2.5 and 12.5%) and the further introduction of Pd (2.3%) via impregnation using a solution of a Pd salt and a process of thermal reduction. The mesoporous carbon obtained contains two distinct crystalline metallic phases, i.e., Co particles of 5.0 nm (IM1) and Pd nanoparticles of ~1.3 nm (IM1), while the increase in Co content triggers higher Co particle sizes of 23 nm and Pd particle sizes of 1.3 and 6.8 nm (IM2). Differently, the catalyst DM is prepared via direct synthesis, in one step, including all precursors and both metal salts. This results in Pd 50 -Co 50 nanoalloys of 6.5 nm uniformly dispersed in the carbon matrix. The reactivity and reusability of catalysts IM1, IM2 and DM were then ascertained in organic synthesis for hydrogenations of nitroarenes and enones. It turned out that no reactions were observed in the presence of the catalyst DM due to the presence of Co in Pd 50 -Co 50 , which deactivates the catalytic activity of Pd. Gratifyingly, catalysts IM1 and IM2 were very efficient for mild hydrogenations of both nitroarenes and enones using only 5 mequiv. of supported Pd in EtOH at room temperature. The smaller Pd particle sizes (1.3 nm) and the high surface-to-volume area are probably responsible for the high reactivity observed. Catalysts IM1 and IM2 can be recovered by application of an external magnetic field. However, a more efficient magnetic recovery of catalyst IM2 compared to IM1 was observed due to its higher Co content. Catalyst IM2 can be successfully reused at least seven times without a loss of efficiency. Finally, almost-Pd-free products can be obtained directly after reaction without any purification step, since the Pd leaching is very low (<0.1% of the initial amount), thus decreasing waste and increasing the reaction's efficiency
