Publications
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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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Toward Imprecision-Aware RUL Forecasting: ANFIS-Ensemble Approach
Engine health monitoring in aeronotical domain is crucial. Aircraft engines operate under crucial conditions, and their failure can have major safety and operational consequences. The prognostic & health management (PHM) of engines plays an important role in keeping the operation of engines steady and secure. The main purpose of PHM is to predict future machinery […]
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Applying the technology acceptance model to risk communication dashboards: a case study
Purpose: This study examines how the design characteristics of risk communication dashboards influence user acceptance in Small and Medium-sized Enterprises (SMEs). As dashboards become essential for data-driven decision-making, identifying which visual and functional elements drive adoption is critical. The research focuses on features that most strongly affect perceived usefulness (PU) and perceived ease of use […]
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Enhancing decision-making in Industry 5.0 through adaptive human–machine interfaces: A systematic literature review
In the dynamic landscape of Industry 5.0, adaptive human–machine interface (HMI) plays a pivotal role in shaping decision-making processes. This study constitutes a systematic literature review focusing on adaptive HMI in Industry 5.0, exploring their applications and implications within the decision-making context. The research objectives are structured around key questions, addressing the manifestation of adaptive […]
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Safety-aware smart parking recommendations for shared micro-mobility using deep reinforcement learning
The rapid expansion of shared micro-mobility services has intensified safety concerns in dense urban environments in recent years. Traffic complexity and infrastructure limitations increase accident risks, yet safety aspects are often overlooked by operators and existing decision-support systems. Current safety-oriented approaches mainly rely on static analyzes, historical accident data, or infrastructure-based interventions, which often lack […]
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Efficient AudioVisual Fusion Architectures for Emotion Recognition
Emotion recognition plays a critical role in the development of adaptive, human-aware intelligent systems. In this work, we propose an end-to-end audiovisual emotion recognition framework that integrates speech signals and facial expressions using lightweight deep learning architectures. To develop the end-to-end architecture, we first benchmark several pretrained convolutional neural networks, employing confidence interval estimation to […]