Publications
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Prospective ergonomics in the anthropocene era: Reconsidering human needs
This position paper discusses the roles of Prospective Ergonomics to face the challenges of Anthropocene. In particular, we question the nature of human needs to distinguish between fundamental needs essential to human development and artificial needs partly responsible for overconsumption and detrimental effects on Earth system. An overview of theories of human needs across Psychology, […]
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Net-zero futures cities and transportation systems: estimation and analyzing of vehicle’s carbon dioxide production by knowledge transferring
The limited energy resources, critical climate change conditions, and globalwarming, coupled with today’s enormous industrial development, necessitate innovative approaches to control the situation. The automotive industry and its pollution emissions remain among the top environmental concerns. In this article, we present a progressive plan that leverages deep neural networks and inductive transfer learning methods to […]
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Generating Realistic Cyber Security Datasets for IoT networks with Diverse Complex Network Properties
In the cybersecurity community, finding suitable datasets for evaluating Intrusion Detection Systems (IDS) is a challenge, particularly due to limited diversity in complex network properties. This paper proposes a dualpurpose approach that generates diverse datasets while producing efficient, compact versions that maintain detection accuracy. Our approach employs three techniques – community mixing modification, centralitybased modification, […]
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Graph-based Learning for Multimodal Route Recommendation
Transportation recommendations are a vital feature of map services in navigation applications. Earlier transportation recommendation systems have struggled to deliver a satisfactory user experience because they focus exclusively on single-mode routes, such as cycling, taxis, or buses. In this paper, we represent the transportation network as a complex network (or graph). Modeling transportation as a […]
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Adaptive Compression of Supervised and Self-Supervised Models for Green Speech Recognition
Computational power is crucial for the development and deployment of artificial intelligence capabilities, as the large size of deep learning models often requires significant resources. Compression methods aim to reduce model size making artificial intelligence more sustainable and accessible. Compression techniques are often applied uniformly across model layers, without considering their individual characteristics. In this […]
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Enhancing IoT Network Intrusion Detection with a new GraphSAGE embedding algorithm using Centrality measures
The rapid expansion of the Internet of Things (IoT) has led to many opportunities in addition to introducing complex security challenges, necessitating more powerful Network Intrusion Detection Systems (NIDS). This study addresses this challenge by enhancing Graph Neural Networks (GNNs) with centrality measures to improve intrusion detection performance in IoT environments. We propose the so-called […]
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Ingénierie pédagogique et technologies émergentes : défis et leviers d’action identifiés dans la conception de Jumeaux d’Enseignement Numériques Immersifs et Interactifs
Les jumeaux numériques d’enseignement (JNE) sont des environnements virtuels pour l’apprentissage humain (EVAH) qui ouvrent des perspectives en matière de conception pédagogique pour se rapprocher des réalités professionnelles des ingénieurs. Le jumeau numérique est la réplique numérique d’un objet ou d’un système industriel ou physique existant, qui peut être doté d’outils d’exploitation pour comprendre, analyser […]
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Hygroscopic stresses development in epoxy-metal bonded assemblies under hydrothermal conditions
Epoxy-metal bonded assemblies are widely used in various industrial applications due to their mechanical efficiency and stress distribution capabilities. However, the durability of these assemblies in humid environments remains the subject of extensive research. This study focuses on the development of a numerical hygroelastic model to investigate hygroscopic stresses in a single-lap epoxy-metal bonded assembly […]
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Enhancing Fuzzy Forests with Consensus Clustering for Unbiased and Robust Feature Selection
This study presents the Fuzzy Forests algorithm, which uses consensus clustering to improve feature selection in high-dimension data and address multicollinearity issues. While Fuzzy Forests mitigates feature selection biases, its effectiveness relies on the clustering method used. Our proposed consensus clustering framework enhances robustness and reduces variability in results, demonstrating better feature independence through extensive […]
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Multimodal Route Planning Integrating Soft Mobility: A Real-World Case Study for Student Mobility
Soft and active mobility (SAM) integration into multimodal route planning is a critical innovation for advanc ing sustainable transportation. This study explores the inclusion of shared (SSAM) and personal (PSAM) soft and active mobility modes within public transport systems. Leveraging a time-expanded model, the proposed approach optimizes route planning by introducing reliability as a novel […]
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Data generation and deep neural network predictions for aged mechanical properties
The aim of this work is the data generation of aged mechanical properties following the Arrhenius equation and large deformation theory for a transversely isotropic bio-based polyurethane foam, and the application of this dataset in the training process of different deep neural network architectures to evaluate their capacity to predict the full stress–strain behavior of […]
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NETLOGOPY: UNLOCKING ADVANCED SIMULATION AND INTEGRATION FOR NETLOGO USING PYTHON
NetLogo is widely recognized as one of the most popular software tools for agent-based simulation. However, it has notable limitations, particularly the lack of advanced libraries in specialized areas such as optimization, artificial intelligence (AI), and mechanical or electrical modeling. On the other hand, Python is a feature-rich programming language that is increasingly used in […]
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