Publications
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BootBoGs-TS: Bootstrap-Based Hyperparameter Optimization for LSTM Models in Remaining Useful Life Prediction
Neural networks, particularly Long Short-Term Memory (LSTM) models, have become prominent for Remaining Useful Life (RUL) prediction due to their ability to capture temporal degradation patterns from multivariate sensor data. However, their predictive performance is highly sensitive to hyperparameter configurations, and conventional optimization methods such as Grid Search or Bayesian Optimization often become inefficient or […]
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Valuable Interactions, Valuable Recommendations: A New Approach for Integrating General User Preferences in Session-Based Recommender Systems
The advent of session-based recommender systems (SBRS) has tremendously contributed to giving recommendations to users without considering their historical data. These systems operate by recommending items based solely on the clicks (i.e., user-item interaction) within the particular session at hand, which represent short-term user preferences. Still, researchers have also attempted to integrate long-term user preferences […]
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Agir avec son corps pour qu’il “se passe quelque chose” chez autrui : mettre en mots l’activité corporelle pour mieux la définir dans le cadre de recherches avec
En appui sur des données à caractère exploratoire recueillies à l’occasion de deux dispositifs de formation réalisés auprès de professionnelles d’un LAEP et de formateurs en psychomotricité, cette contribution se propose de comprendre dans quelle mesure la mise en mots des dimensions corporelles de l’activité permet aux professionnels d’en définir les contours. Le texte présente […]
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A comprehensive framework for modeling building occupancy: technologies, methods, and research challenges
Occupancy information is a key element for improving building energy performance and occupant comfort through occupancy-centric control strategies. However, the rapid development of occupancy-related research over the past years has led to fragmented terminology and heterogeneous analytical perspectives, which complicate consistent comparison and interpretation of results. To address this issue, this paper proposes an analytical […]
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Explainable Remaining Useful Life Prediction Using Interpretable Divisive Feature Clustering
Accurate prediction of remaining useful life (RUL) is critical for effective predictive maintenance. While models like long short-term memory (LSTM) are effective, they often lack interpretability, even when using explainable artificial intelligence (XAI) methods such as shapley additive explanations (SHAP). This is particularly true when these models are trained on high-dimensional, redundant features. To tackle […]
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Sustainable reuse of excavated soils stabilized with fly ash and slag based geopolymers for backfill applications
A clayey soil excavated from the Paris region was investigated for reuse as a backfill material. It was stabilized with alkali-activated fly ash and ground-granulated blast-furnace slag with lime as a reference material. Geopolymer activation was performed using a 14 M sodium hydroxide solution combined with sodium silicate. Cylindrical specimens (33 mm diameter × 71 […]
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Perturbative analytical framework for thermal wave diffusion in non-linear building envelopes
Model Predictive Control (MPC) in building energy management requires transient thermal models balancing thermodynamic accuracy with computational efficiency. Standard spatial discretization triggers state-space inflation, paralyzing real-time solvers, while Transfer Matrix Methods (TMM) suffer from high-frequency numerical overflow and assume material homogeneity. This paper introduces a novel frequency-domain framework based on the continuous spatial Riccati equation. […]
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A new framework for measuring community diversity in temporal ecological networks
Assessing changes in community diversity is a central issue with regard to many fundamental and applied aspects in ecology, biogeography and conservation. However, some important features for the assessment of community by diversity measures still need to be considered to quantify spatio-temporal variation, notably their explicit variation through time while integrating network structure and species […]
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A novel hardware-software strategy for thermal chamber temperature control and PV energy optimization
This paper presents a hardware–software temperature regulation strategy for photovoltaic (PV) powered thermal chambers, combining Maximum Power Point Tracking (MPPT) with a high-side NMOS power disconnection mechanism. The proposed strategy disconnects the boost converter from the PV panel once the thermal setpoint is reached, allowing the PV array to operate freely and supply excess energy […]
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Community-based Vulnerability Prediction Framework for IoT Intrusion Detection using only Network Topology
Internet of Things networks in critical infrastructure face sophisticated attacks that exploit structural vulnerabilities. Existing intrusion detection methods analyze individual devices, missing patterns that emerge when functionally related devices organize into communities that communicate more frequently with each other than with the rest of the network. Current structural analysis approaches examine either individual devices or […]
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Energy-Aware Scheduling in a Flexible Flow Shop Using a Hybrid Constraint Programming Approach
This paper addresses energy-efficient production scheduling in a flexible flow shop by integrating advanced energy flexibility strategies. A smart manufacturing setting is considered, with energy supplied from multiple sources: grid electricity with time-of-use pricing, photovoltaic generation, and an energy storage system. In addition, a demand bidding mechanism allows the facility to submit curtailment capacity bids […]
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Supervised machine learning models for accurate prediction of micro pump displacement
This study presents a supervised learning framework for predicting the maximum membrane displacement of a shape memory alloy (SMA) antagonistic micro pump subjected to material and geometric uncertainties. SMA micro pumps are indeed promising candidates for precise fluid control in microfluidics, but their nonlinear and hysteretic thermomechanical behavior makes parametric analyses and uncertainty evaluation using […]