Publications
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Improving predictive maintenance: Evaluating the impact of preprocessing andmodel complexity on the effectiveness of eXplainable Artificial Intelligence methods
Due to their performance in this field, Long-Short-Term Memory Neural Network (LSTM) approaches are often used to predict the remaining useful life (RUL). However, their complexity limits the interpretability of their results. So, eXplainable Artificial Intelligence (XAI) methods are used to understand the relationship between the input data and the predicted RUL. Modeling involves making […]
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A Continual Learning Approach for Failure Prediction under Non-Stationary Conditions: Application to Condition Monitoring Data Streams
Accurate forecasting of Remaining Useful Life (RUL) is crucial for predictive maintenance (PdM), permitting prompt actions that decrease downtime and maintenance expenses. Yet, conventional RUL estimation techniques often struggle to adjust to changing operational conditions and data drift, restricting their use in dynamic industrial settings. This research presents a continual learning framework designed for these […]
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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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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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The hidden face of the Proteus effect: Deindividuation, embodiment and identification
The Proteus effect describes how users of virtual environments adjust their attitudes to match stereotypes associated with their avatar’s appearance. While numerous studies have demonstrated this phenomenon’s reliability, its underlying processes remain poorly understood. This work investigates deindividuation’s hypothesized but unproven role within the Proteus effect. Deindividuated individuals tend to follow situational norms rather than […]
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IdeAM: A serious game to foster creativity in Additive Manufacturing
This study investigates the potential of serious games (SG) to enhance creativity in additive manufacturing (AM). While AM offers unique opportunities to explore complex designs, traditional manufacturing methods often limit designers’ creativity due to cognitive biases formed by years of using conventional processes. This research aims to introduce IdeAM, a SG designed to foster creativity […]
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Exploring Behavioral Dynamics to Enhance Collective Intelligence in Virtual Environments
Collective intelligence (CI) is a predictive measure of a group’sability to perform a wide variety of tasks. It is an essential conceptfor understanding team dynamics and enhancing team performance.While extensively studied in traditional environments such as faceto-face settings or online interactions, CI remains underexplored inimmersive Virtual Reality (VR). This thesis has three goals: (1) toanalyze […]
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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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Floating Offshore Wind Turbine Optimized Control for Power Regulation With Experimental Validation
This article proposes a new strategy for blade pitch control to regulate power production while alleviating the negative effects of the structural motions of floating offshore wind turbines (FOWTs). FOWTs frequently experience significant fluctuations in rotor speed when wind speed is above its rated value in the presence of significant wave heights. This condition reduces […]
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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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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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