Publications
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A Comparative Analysis of Service Management Techniques in the Internet of Things
The Internet of Things (IoT) interconnects vast networks of heterogeneous devices across dynamic domains such as healthcare, industry, and smart cities, presenting critical challenges in real-time orchestration, resource efficiency, security, and scalability. To address these demands, diverse service management paradigms have emerged as essential frameworks. This review systematically analyzes existing IoT service management approaches, categorizing […]
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A Review of Digital Twins in Smart Environments
Transcending static digital representations, a Digital Twin (DT) functions as a dynamic, computational counterpart of a physical asset, capturing its real-time state and behavior through continuous data exchange. This mirroring capability positions DTs as a key enabler of intelligent operations in complex smart environments, from optimizing energy usage in buildings to managing urban infrastructure and […]
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A Review on Multi-Agent Deep Reinforcement Learning for IoT: Techniques and Applications
The Internet of Things (IoT) connects billions of devices across domains such as transportation, healthcare, agriculture, and energy-creating highly dynamic, distributed, and heterogeneous environments. These characteristics pose significant challenges for control, coordination, scalability, and adaptability. In response, Multi-Agent Deep Reinforcement Learning (MADRL) has emerged as a promising paradigm by combining the decision-making intelligence of reinforcement […]
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Multi-Agent System for Solving the Vehicle Routing Problem: A Hybrid Metaheuristic Approach
This paper introduces a novel Multi-Agent System (MAS) designed to solve the Vehicle Routing Problem (VRP), a well-known optimization challenge in logistics. The proposed MAS integrates seven established metaheuristics—Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Golden Ball Algorithm (GBA), Hill Climbing (HC), Tabu Search (TS), and Simulated Annealing (SA)—using a Bi-directional […]
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Des Jumeaux Numériques d’Enseignement : entre instrument et finalité de l’acte éducatif
Dans la continuité des Jumeaux Numériques (JN) industriels, la formation est devenue un champ d’application visé par le développement de Jumeaux Numériques d’Enseignement (JNE). À partir d’une étude sur l’introduction d’un JNE dans une formation d’ingénieurs, cet article se propose de comprendre dans quelle mesure le JNE peut être instrumenté comme objet pédagogique dans une […]
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Systematic review and future directions in dynamic flexible job shop scheduling: a decade of research
This paper presents a comprehensive overview of the current state-of-the-art on Dynamic Flexible Job Shop Scheduling problems (DFJSSP). It reviews a wide range of studies that address different scheduling strategies, various types of disruptive events, and multiple objectives. The numerous solution methods developed in the literature and tested on significant benchmarks are also analyzed. This […]
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Impact Detection in Fall Events: Leveraging Spatio-temporal Graph Convolutional Networks and Recurrent Neural Networks Using 3D Skeleton Data
Fall represents a significant risk of accidental death among individuals aged over 65, presenting a global health concern. A fall is defined as any event where a person loses balance and moves to an off-position, which may or may not result in an impact where the person hits the ground. While fall detection systems have […]
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Effects of Thermal Activation on Mechanical Performance and Sustainability of Slag-Based Geopolymers
Ground granulated blast furnace slag (GBFS)-based geopolymers represent a viable binder system that combines mechanical efficiency with a significantly lower carbon footprint when compared to conventional Portland cement. This work examines how thermal curing between 20 ◦C and 80 ◦C affects setting time, mechanical performance, shrinkage, and porosity of GBFS-based geopolymers. Curing at 40 ◦C […]
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Dynamic mechanical analysis of shape memory polymers: thermomechanical behavior and influence of thermal stimuli
This study explores the thermomechanical properties of polymethacrylate-based shape memory polymers (SMPs), focusing on hot water as a thermal stimulus for shape recovery. Using differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA), the research evaluates thermal transitions, viscoelastic behavior, and energy dissipation. DSC identified a glass transition temperature (Tg) of 67 °C, critical for […]
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AGCD-Net: Attention Guided Context Debiasing Network for Emotion Recognition
Context-aware emotion recognition (CAER) enhances affective computing in real-world scenarios, but traditional methods often suffer from context bias-spurious correlation between background context and emotion labels (e.g. associating “garden” with “happy”). In this paper, we propose AGCD-Net, an Attention Guided Context Debiasing model that introduces Hybrid ConvNeXt, a novel convolutional encoder that extends the ConvNeXt backbone […]
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MANAGING READINESS FOR CHANGE TO UNLOCK PROJECT PERFORMANCE -A quantitative study at the cross-section of change- and project management practices-
This study explores the influence of perceptions on individual readiness for change as an explanatory factor in the field of organizational behavior and renewed human resource practices. Hereby, this study offers a fresh perspective on the comparative significance of culture versus nationality as explanatory constructs to further explore the realm of diversity-, equity- and inclusion […]
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Smart Fleet Management for Shared Micro-mobility: Balanced demand, Redistribution and Charging via Deep Reinforcement Learning
Shared electric micro-mobility, as an emerging mode of urban transportation, has been booming worldwide in recent years. Al though it provides sustainable, eco-friendly, and cost-effective mobility, it also faces several challenges, particularly due to existing inefficient fleet management strategies. These typically rely on fixed redistribution schedules that fail to adapt to highly dynamic user demand […]