Publications
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A Novel Approach for Optimal Power Smoothing in Floating Offshore Wind Turbine Conversion Chains
The study proposes using battery storage systems to smooth floating offshore wind turbine (FWOT) power. However, FOWT, battery, and grid interact complexly; therefore, power flow should be optimized. This research provides a power management method that manages power flow between the FOWT and battery to smooth power grid injection.
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An innovative Machine Learning model for predicting compressive strength of biobased concretes
Biobased concretes, which incorporate renewable and environmentally friendly components such as plant-based aggregates, offer a promising alternative to conventional materials. However, their widespread adoption is hindered by several challenges such as variability in raw materials, complex interactions between components, the lack of standardized methodologies, and requirement of advanced technics for characterizing and optimizing their mechanical […]
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Lightweight Deep Learning for Photovoltaic Energy Prediction: Optimizing Decarbonization in Winter Houses
This paper proposes an innovative hybrid multivariate deep learning approach to predict photovoltaic (PV) energy production in winter houses, with a focus on lightweight models with low environmental impact. A methodology is developed to assess the carbon footprint of these models, considering training energy consumption, operational CO2 emissions, and energy savings from PV production optimization. […]
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Deterministic Scheduling of Periodic Messages for Low Latency in Cloud RAN
Cloud-RAN (C-RAN) is a cellular network architecture where pro- cessing units, previously attached to antennas, are centralized in data centers. The main challenge in meeting protocol time con- straints is minimizing the latency of periodic messages exchanged between antennas and processing units. We demonstrate that sta- tistical multiplexing introduces significant logical latency due to buffering […]
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Minimizing the total completion time for a class of semi-online single machine scheduling problems
Semi-online single machine scheduling problems with information on jobs’ processing times and the objective to minimize the total completion time are considered. In these problems, a set of jobs arriving over time are to be scheduled on a single machine and their characteristics become known only upon arrival. Some of the studied problems are shown […]
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Exploring Emotion Expression Recognition in Older Adults Interacting with a Virtual Coach
The EMPATHIC project aimed to design an emotionally expressive virtual coach capable of engaging healthy seniors to improve well-being and promote independent aging. In particular, the system’s human sensing capabilities allow for the perception of emotional states to provide a personalized experience. This paper outlines the development of the emotion expression recognition module of the […]
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Calibration améliorée d’un capteur profileur laser pour l’inspection et la reconstruction 3D
Au cours des dernières décennies, l’inspection et la reconstruction tridimensionnelle des canalisations de gaz et d’eau ont nécessité l’utilisation de capteurs de haute précision capables de fonctionner dans des environnements confinés et à faible texture, posant ainsi des défis aux technologies de détection conventionnelles. Cet article présente la conception, tant matérielle que logicielle, d’un capteur […]
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Occupant behavior and impact of the HVAC system on occupant comfort in two-person offices in a mediterranean climate in the south of France
The Mediterranean climate of the south of France is characterized by a long and hot summer season. Under these conditions, it is important to understand the impact of the HVAC system on the comfort of office occupants as well as their adaptive behaviors to create a comfortable indoor thermal environment. The objective of this study […]
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Une approche divisive et interprétable de réduction de dimension pour la prédiction de la RUL
En maintenance, la prédiction de la durée de vie utile restante (RUL) est entravée par la grande dimensionnalité et le manque d’explicabilité. Cette étude propose une approche combinant une méthode innovante de réduction de dimension interprétable, l’IDFC (Interpretable Divisive Feature Clustering), et un modèle LSTM (Long Short-Term Memory) à une couche. L’IDFC s’inspire des algorithmes […]
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Double-Layer Soft Data Fusion for Indoor Robot WiFi-Visual Localization
This paper presents a novel WiFi-Visual data fusion method for indoor robot (TIAGO++) localization. Long-term follow-up experiments show that this method can use 10 WiFi samples and 4 low-resolution images ($58 times 58$ in pixels) to localize an indoor robot with an average error distance of about 1.32 meters 3 months (or 1.7 meters 7 […]
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Building Fast Dynamic 3D Maps for Trajectory Planning of Autonomous Ground Vehicles Using Non-Repetitive Scanning LiDAR Sensor
Building fast and reliable maps of the environment is a fondamental task for autonomous navigation. However, this process offers several challenges such as accurate registration of 3D point clouds. Recently, non-repetitive scanning LiDAR sensors have emerged as a promising alternative for 3D data acquisition, leveraging some of these challenges. In this paper, we present a […]
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Chemical servoing with hexapod robot for gas source localization and YOLO‑based visual defect detection
Robotic systems have the ability to perform industrial inspection tasks through the integration of visual and chemical servoing functions. A commonly used system is the image-based servoing system. This study presents an innovative approach that merges chemical servoing with visual defect detection in industrial settings using a hexapod robot. The main goal is to develop […]
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