Publications
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Optimizing Supplier Selection Under Risk: A Multi-Method Approach
This paper presents an innovative approach to optimize supplier selection while minimizing transportation costs in supply chain management. The methodology integrates Mixed Integer Linear Programming (MILP), Genetic Algorithm (GA), and a stochastic programming approach (MILP combined with Monte Carlo simulation, called MCLP) to address the complexities of supplier selection. The MILP model is designed to […]
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Artificial Intelligence Non-invasive Methods for Neonatal Jaundice Detection: A Review
Neonatal jaundice is a common and potentially fatal health condition in neonates, especially in low and middle income countries, where it contributes considerably to neonatal morbidity and death. Traditional diagnostic approaches, such as Total Serum Bilirubin (TSB) testing, are invasive and could lead to discomfort, infection risk, and diagnostic delays. As a result, there is […]
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Authoring framework for industrial XR digital twin and autonomous agent : a proof of concept
Extended Reality-Interfaced Digital Twins (XR-DTs) can be used in a wide range of industrial applications, including visualization, monitoring, training, simulation and industrial systems design. However, interacting with and controlling autonomous agents, whether virtual or real, through XR-DTs can be challenging. NEURONES aims to address this issue by providing immersive ways to create complex scenarios with […]
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Warming the Ice: The Role of Social Touch and Physical Warmth on First Impressions in Virtual Reality
First impressions are critical in shaping social interactions, with perceptions of interpersonal warmth playing a central role in foster- ing positive judgments. Social touch, such as handshake, conveys both interpersonal and physical warmth, potentially influencing im- pressions and social proximity. Using VR and haptic technologies, we explore how handshake temperature (warm or cold) affects first […]
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A hybrid approach using ant colony optimisation for integrated scheduling of production and transportation tasks within flexible manufacturing systems
This paper studies the integrated scheduling problem in flexible manufacturing systems (FMS), where flexible machines and Automated Guided Vehicles (AGV) shared by production jobs are scheduled simultaneously in an integrated manner. Routing flexibility, a crucial advantage of FMS, enabling a job to be handled via alternative machine combinations, is involved. To address this problem, we […]
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Experimental and modeling study on earthen sediment-based bricks with and without flax fibers: a finite element analysis
This paper investigates the improvement of earthen sediment-based bricks through the use of natural flax fibers to enhance their mechanical properties. The experimental tests were designed to develop numerical modeling based on material guidelines that have been partially followed. To facilitate the precise placement of flax fibers within the earthen sediment, periodically distributed holes have […]
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Multi-Objective Approach for Efficient Grid Resources Allocation in Electric Vehicle Charging Schedules
Our study introduces a novel multi-objective optimization model for electric vehicle (EV) charging scheduling, balancing two critical objectives: maximizing the energy delivered to clients while minimizing peak energy consumption. This is achieved under real-world constraints, including limited charging infrastructure, varying charging power levels, client availability, and the sequential nature of vehicle charging. The proposed approach […]
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Preference-Based Multi-Objective Optimization for Student Transportation: A Machine Learning Approach
This paper presents a novel framework for optimizing student transportation through the integration of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with Multi-Layer Perceptron (MLP) neural networks. Our approach integrates preference learning with multi-objective optimization to develop personalized mobility solutions that reconcile individual preferences with institutional sustainability goals. Utilizing comprehensive data from over 1,000 students […]
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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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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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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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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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