Publications
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A Divisive Unsupervised Feature Selection Approach for Explainable Remaining Useful Life Prediction
Predicting the Remaining Useful Life (RUL) in maintenance often encounters challenges such as high dimensionality, feature redundancy, and limited explainability. This paper presents a novel approach that combines Interpretable Divisive Feature Clustering (IDFC) with Long Short-Term Memory (LSTM) networks. The IDFC algorithm leverages the strengths of variable clustering methods (VARCLUS) and the Clustering of Variables […]
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Investigating the sustainable design of a shipping container building using advanced building energy modeling and Bayesian inference
Modular buildings demonstrate environmental benefits in raw material usage but vary in energy performance by climate. Our research evaluates the energy performance of a modular educational building by calibrating a Building Energy Model (BEM) with operational data and Bayesian inference. As expected, this case study reveals that energy model calibration is not required when sufficient […]
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Structured pruning for efficient systolic array accelerated cascade Speech-to-Text Translation
We present in this paper a simple method for pruning tiles of weights in sparse matrices, that do not require fine-tuning or retraining. This method is applied here to the feed-forward layers of transformers. We assess in a first experiment the impact of such pruning on the performances of speech recognition, machine translation, and the […]
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Collaborative Semantic Mapping for Updating the Digital Twin in controlled Indoor Environment
Efficient management of indoor spaces is increasingly critical for applications such as security, evacuation planning, and roboticdeployment. Digital twin technology has emerged as a transformative solution, providing a real-time link between the physicalenvironment and its virtual counterpart to enable monitoring, simulation, analysis, and performance optimization. This paperintroduces a novel collaborative approach to semantic mapping that […]
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Towards a dynamic model of collective intelligence: Theoretical integration, nonverbal interaction and temporality
Most existing research on Collective Intelligence (CI) tends to emphasize final performance indicators or sums of individual cognitive traits, giving insufficient attention to how teams dynamically construct their collective capacity through ongoing interactions. In this paper, we propose an integrative perspective that draws on multiple existing approaches, ranging from conceptual frameworks (IMOI, TSM-CI) to measurement-oriented […]
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Augmented Perception: a real-time digital twin based approach to enhance robotic perception.
This paper introduces an Augmented Perception (AP) framework to enhance robotic perception in resilient manufacturing systems (MS) by integrating Digital Twin (DT) data directly at the sensor level in real time. Inspired by augmented reality, this approach enables robots to perceive both physical and virtual entities within a unified representation. To ensure real-time performance, we […]
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Multi-agent reinforcement learning approach for predictive maintenance of a Smart Building lighting system
This paper presents a predictive maintenance methodology for Smart Building systems using fault tree models and Weibull distributions to estimate component failure probabilities. We introduce connection events to reduce the complexity of the fault tree architecture. These new events allow us to capture system interactions and identify critical components. Reinforcement learning-based algorithms are employed to […]
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Graph-based framework for temporal human action recognition and segmentation in industrial context
Industry 5.0 places human operators at the center of industrial processes. In this context, analyzing human movements has become crucial for ensuring operator safety and improving productivity. More specifically, an accurate system for action recognition and segmentation is essential to identify and break down each action an operator performs. These systems enable a range of […]
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Maritime monitoring through LoRaWAN: Resilient decentralised mesh networks for enhanced data transmission
Resilient communication networks from ocean-deployed buoys are crucial for maritime applications. However, wireless data transmission in these environments faces significant challenges due to limited buoy battery capacity, harsh weather conditions, and potential interference from maritime vessels. LoRaWAN technology, known for its low power consumption and long-range communication capabilities, presents a promising solution. Nevertheless, the standard […]
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A game theory approach for optimizing job shop scheduling problems with transportation in common shared human–robot environments
The Job Shop Scheduling Problem with Transportation (JSSPT) is a critical challenge in modern industrial systems, particularly in environments where human operators and Autonomous Intelligent Vehicles (AIVs) interact. Traditional scheduling approaches often fail to address the dynamic and unpredictable nature of these shared human–robot environments. In response, this paper introduces a game theory-based scheduling algorithm […]
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Energy-Aware Optimization of Multi-Robot Systems with Task Allocation and Partial Recharge Scheduling
This paper presents a task allocation and scheduling model for multi-robot systems operating under energy constraints. The proposed model integrates key factors such as energy consumption, battery charging management, and task execution efficiency. To address this problem, we employ both an exact solver-based method and a bio-inspired algorithm, enabling a comparative analysis of their performance […]
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A New MILP Model for Supplier Selection: Improving Efficiency and Solution Quality under Risk
This paper contributes to the field of supplier selection under risk by proposing a Mixed Integer Linear Programming (MILP) model that integrates key decisionmaking factors such as cost and risk mitigation strategies. The proposed model offers a comprehensive approach for selecting the best supplier portfolio under uncertainty. Furthermore, the paper provides a detailed comparison of […]
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