Publications
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Integrating BIM with Lean Principles for Enhanced Decision-making: Optimizing Insulation Material Selection in Sustainable Construction Project
This study addresses the construction sector’s growing need for improved decisionmaking and reduced carbon emissions by integrating Lean principles into Building Information Modeling (BIM). A decision-support tool was developed using Python and RStudio to enhance stakeholder efficiency, reduce errors, and streamline communication. The tool combines Set-Based Design, Choosing By Advantages, and Big Room methods with […]
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Extensive development of a Bayesian calibration approach for building energy models using an innovative case study: a shipping container building.
The building sector is responsible for almost a third of global energy consumption and a quarter of CO2 emissions. Innovative architectural designs that promote the reusability of raw materials, such as shipping container architecture, can help to reduce construction’s environmental impact. By creating physical models to analyze energy consumption, we can develop practical tools to […]
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Electrochemical and thermodynamic modeling of PEM electrolyzer performance: A comparative study with and without diffusion overpotential
In this paper, a mathematical model is developed, combining thermodynamic and electrochemical models. It was used to study the effect of operating parameters, such as membrane thickness and operating temperature on the performance of PEM electrolzer cell. The effect of ion diffusion through the membrane on the cell potential was also studied. In addition, an […]
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Predicting wind turbines faults using Multi-Objective Genetic Programming
Wind turbines are a key component of renewable energy, converting wind into electricity with minimal environmental impact. Ensuring their continuous operation is crucial for maximizing energy production and reducing costly downtimes. To extend their operational lifespan, proactive maintenance strategies that predict and address potential faults are essential. While Machine Learning (ML) and Deep Learning (DL) […]
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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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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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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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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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