Publications
-
TCAD-Based Analysis on the Impact of AlN Interlayer in Normally-off AlGaN_GaN MISHEMTs with Buried p-Region
With the growing demand for more efficient power conversion and silicon reaching its theoretical limit, wide bandgap semiconductor devices are emerging as a potential solution. For instance, Gallium Nitride (GaN)-based high-electron-mobility transistors (HEMTs) are getting more attention, and several structures for the normally off operation have been proposed. Adding an AlN interlayer in conventional AlGaN/GaN […]
-
Toward a Predictive Maintenance: Implementing an Innovative Maintenance System for Manufacturing Production Lines Based on New Technologies
The rise of “big data” has been profoundly transformed the landscape of the manufacturing sector, putting pressure on companies’ competitiveness and making the effective utilization of this vast data a critical imperative for efficient maintenance. Therefore, predictive maintenance plays an essential role in meeting these challenges, anticipating maintenance needs and enhancing equipment durability. This paper […]
-
Machine learning for density prediction and process optimization of 316L stainless steel fabricated by selective laser melting
Selective laser melting (SLM) is an additive manufacturing technique formetallic materials, currently implemented in different industrial applications. Among the various materials, 316L stainless steel (316L SS) has been widely investigated by this process. However, achieving optimal manufacturing quality is challenging due to the large number of parameters that affect the final product. Traditional methods for […]
-
Produire des connaissances transversales à partir d’une approche « micrologique » de l’activité : un défi pour l’analyse du travail en éducation-formation
La question de l’élaboration de connaissances généralisables à partir d’échelles d’analyse microscopiques et situées est à la fois récurrente et fondatrice des démarches de recherche relevant d’approches par l’analyse de l’activité dans le domaine de l’éducation-formation. Même s’il n’est pas toujours explicité et argumenté en tant que tel, ce passage d’observations locales à des interprétations […]
-
Processus de problématisation et mobilisation de la forme « problème » dans les pédagogies des écoles d’ingénieurs : une analyse de cas par les capabilités
Les méthodes de pédagogie active désignent un ensemble de démarches pédagogiques qui cherchent à mettre les apprenants en situation d’être acteurs de leurs apprentissages. Pour cela, elles s’appuient dans leurs modalités de mise en oeuvre sur l’expérience des apprenants et encouragent l’implication par l’investigation, la participation, la réflexion critique, l’appropriation par le faire et la […]
-
Optimized cooperative vehicle routing in multi-depot collection systems for circular economy: Model development and case study
Manufactured products and used raw materials should be reprocessed and reutilized to ensure sustainability in the context of the circular economy. Optimized waste collection and management play a crucial role in establishing effective circular economy practices. A collaborative waste collection system is one of the pillars for optimizing the entire waste collection process. Collaborative waste […]
-
Multisensory objects’ role on creativity
In this research, we investigated the role of multisensorial manipulation on creativity, and the influence of inspirational objects on creative outcomes. Object manipulation may support embodied cognition during a generative creative phase (emergence of motor, spatial, emotional ideas, etc.) then exploratory phase (creative fixation, development of a functional creation, etc.). Our protocol involved 136 engineering […]
-
New insights on rheology, durability and mechanical and thermal properties of polyester and steel fiber-reinforced Self-Compacting Concretes
Self-compacting concrete improves fresh-state fluidity while maintaining mechanical properties, and presents an increasing research interest in fiber incorporation. However, the effects of fibers on rheological behavior and durability remain insufficiently studied in existing literature. This study provides new insights on the effect of polyester and steel fibers on the rheological, mechanical, durability, microstructural, and thermal […]
-
A novel deep learning approach for facial emotion recognition: application to detecting emotional responses in elderly individuals with Alzheimer’s disease
Facial expressions are a critical form of nonverbal communication, conveying a wide range of emotions. Recent advancements in artificial intelligence and computer vision have led to the development of deep learning methods, particularly convolutional neural networks, which are highly effective in facial emotion recognition. This paper presents EmoNeXt, an advanced deep learning framework for FER […]
-
Fundamentals of Quantum Programming
This chapter provides an introduction to Qiskit, an open-source software frame- work for quantum computation that was developed by IBM. Its purpose is to simplify the process of quantum programming for individuals of all skill levels. This chapter explores the complexities of quantum programming by explaining the theoretical foundations and offering practical illustrations of quantum […]
-
Sécurité, complexité, imprévisibilité: apports et perspectives des travaux de Leplat
e thème de la sécurité a un statut particulier dans les travaux de Jacques Leplat puisqu’il est transversal à toute sa carrière (Leplat, 1985, 2011; Leplat & Cuny, 1974). À partir des années 80, il s’est lié à celui de complexité, devenu indispensable pour décrire le monde qui nous entoure (Leplat & De Terssac, 1990; […]
-
Split-Federated Reinforcement Learning for IoMT Data and Task Management in Edge-Fog-Cloud Infrastructure
Workload management in edge-fog-cloud infrastructure for the Internet of Medical Things (IoMT) involves significant costs and difficulties, primarily due to the challenge of managing tasks and the unpredictability of data generated by IoMT devices while processing real-time patient health states. Deep Reinforcement Learning (DRL) shows promise in efficiently addressing dynamic data placement and task offloading. […]