Publications
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Bayesian calibration of a BEM: a case study
We provide python scripts, jupyter notebooks to realize the bayesian calibration of a building energy model developped using EnergyPlus software. A dataset from an educational building located in Nanterre (France) is also provided to allow the user to reproduce the case study. For more information about the structure of the repository and please have a […]
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Multi-face emotion detection for effective Human-Robot Interaction
The integration of dialogue interfaces in mobile devices has become ubiquitous, providing a wide array of services. As technology progresses, humanoid robots designed with human-like features to interact effectively with people are gaining prominence, and the use of advanced human-robot dialogue interfaces is continually expanding. In this context, emotion recognition plays a crucial role in […]
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Optimized Scheduling for Electric Vehicle Charging: A Multi-Objective Approach to Grid Stability and User Satisfaction
The transition to electric mobility offers substantial environmental benefits but also introduces significant challenges, particularly in managing the high demand for electric vehicle (EV) charging. This demand creates the need for intelligent scheduling to optimize charging station resources and maintain grid stability. In order to address this purpose, we propose a multi-objective scheduling model designed […]
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Decoding Persuasiveness in Eloquence Competitions: An Investigation into the LLM’s Ability to Assess Public Speaking
The increasing importance of public speaking (PS) skills has fueled the development of automated assessment systems, yet the integration of large language models (LLMs) in this domain remains underexplored. This study investigates the application of LLMs for assessing PS by predicting persuasiveness. We propose a novel framework where LLMs evaluate criteria derived from educational literature […]
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PRISM: A PRIvacy Safeguard for Smart Multiservices
A privacy safeguard for smart multiservices (PRISM) is a novel privacy-aware framework designed to bridge the gap in traditional privacy protection mechanisms by tackling the intricacies of data quality and machine learning algorithms, offering adaptive and scalable solutions while ensuring the capability for real-time analysis.
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Geopolymers in nuclear waste storage and immobilization: mechanisms, applications, and challenges
According to the latest report by the International Atomic Energy Agency (IAEA), nuclear facilities generate over 30 tons of high-level radioactive waste and 300,000 tons of medium-level waste annually, highlighting the need for secure immobilization methods to safeguard environmental and public health. Cementitious materials such as ordinary Portland cement (OPC) and other materials are commonly […]
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Finite-dimensional adaptive observer design for linear parabolic systems with delayed measurements
New finite-dimensional adaptive observers are proposed for uncertain heat equation and a class of linear Kuramoto–Sivashinsky equation (KSE) with local output. The observers are based on the modal decomposition approach and use a classical persistent excitation condition to ensure practical exponential convergence of both states and parameters estimation. An important challenge of this work is […]
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A multi-agent system simulation of job shop scheduling with human consideration: A comparative analysis of AGVs and AIVs
The manufacturing landscape is undergoing a paradigm shift towards Industry 5.0, emphasizing human-centricity in a collaborative environment between humans and robots. In this context, the job shop scheduling problem (JSSP) remains a critical aspect of workshop management, optimizing task sequencing to minimize the overall completion time (makespan). Traditionally, autonomous and guided vehicles (AGVs) have been […]
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Sampled-data high gain observers for dynamic state estimation in power system
A novel dynamic state estimator is proposed for a class of synchronous generators. The proposed observer is based on high gain principle and provides an accurate estimations of all states of the systems. A sampled-data version which can works with relatively low sampling frequency is also provided. Our algorithms are vali- dated in simulations and […]
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Predictive Maintenance for Smart Buildings: Balancing QoS and Cost Efficiency
The rapid advancement of sensing technologies and connectivity has revolutionized predictive maintenance (PdM), particularly for smart buildings (SB). Despite these advancements, implementing data-driven approaches faces challenges, mainly due to scarce failure data and the SB systems complexity. In this paper, we propose a cooperative multi-agent reinforcement learning (RL) based approach to address these challenges in […]
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Biobased materials as a robust solution for building renovation
Bio-based materials like wood, straw, and hemp, offer a sustainable solution to reducing carbon footprints and confronting climate change in construction. These materials not only lower the environmental impact and emissions but also improve insulation, aligning with the circular economy and life cycle assessment goals. Their use addresses the construction sector’s high energy demand and […]
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Enhanced Calibration of a Laser Profiler Sensor for 3D Inspection and Reconstruction
In recent decades, inspection and three-dimensional reconstruction of gas and water pipes have required high-precision sensors capable of operating in confined and low-texture environments, which presents challenges to traditional sensing technologies. This paper presents the design of both hardware and software for a laser profiler sensor, introducing a novel approach to calibrating the sensor to […]
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