École Centrale d'Électronique

Medical IoT devices for health monitoring require constant power and connectivity, yet they face challenges in complex indoor environments like hospitals due to signal blockages and energy constraints. This paper proposes a deep learning-based approach for determining the optimal position and phase shift of a Reconfigurable Intelligent Surface (RIS) to enhance both energy harvesting and communication throughput. Simulations using OpenEMS and Octave model signal behavior in a hospital-like scenario. A regression-based neural network is trained using TensorFlow to predict the optimal RIS configuration. Results demonstrate a nonlinear, positively correlated relationship between RIS parameters and performance metrics, enabling intelligent optimization of RIS for real-time health IoT applications.

We study the quantum dynamics of cold atoms initially confined in a helical optical tube (HOT) and subsequently released into free space. This helicoidal potential, engineered via structured light fields with orbital angular momentum, imposes a twisted geometry on the atomic ensemble during confinement. We examine how this geometry shapes the initial quantum state—particularly its spatial localization and phase structure—and how these features influence the subsequent free evolution. Our analysis reveals that the overall confinement geometry supports the formation of spatially coherent, structured wavepackets, paving the way for the realization of twisted Bose–Einstein condensates and directed atom lasers. The results are of particular interest for applications in quantum technologies, such as coherent atom beam shaping, matter-wave interferometry, and guided transport of quantum matter.

Femme noire pendant la ségrégation aux États-Unis, la mathématicienne de génie Katherine Johnson fut essentielle par son travail à la réussite de la mission Apollo 11. Un rôle qui ne fut reconnu que bien des décennies après le premier pas sur la Lune.

Mental fatigue (MF) is a psychobiological state induced by prolonged exertion that has the potential to reduce performance. In military operations, MF coincides with inadequate sleep, circadian disruption and other stressors, further increasing the risk of fatigue-related errors of judgement and reduction in physical and psychological performance. Experienced leaders can detect MF, but multimodal monitoring and assessment technologies still cannot duplicate this capability. Experiments to define signals that cue this human percept could inform future technologies. Countermeasures include engagement strategies, brain endurance training to extend physical endurance, and caffeine and modafinil to temporarily sustain performance. An infrastructure for physiological monitoring and integrated analyses will advance team performance enhancement, along with the use of explainable and interpretable artificial intelligence modelling, refined through iterative experimentation. More precise definitions that distinguish MF from other types of fatigue will help advance the development of monitoring technologies and countermeasures by targeting the right physiological and behavioural metrics.