Publications
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An Overview of Artificial Intelligence Driven Li-Ion Battery State Estimation
The omnipresence of batteries in nowadays appliances such as portable devices, electrical vehicles, hybrid microgrids, etc. gives them a special priority in energy storage. In addition, the high cost of battery manufacturing makes the maintenance and the monitoring of their states critical. The state estimation is a complicated process that may include many parameters to […]
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Photogrammetry and deep learning for energy production prediction and building-integrated photovoltaics decarbonization
Building-Integrated photovoltaics (BIPV) have emerged as a promising sustainable energy solution, relying on accurate energy production predictions and effective decarbonization strategies for efficient deployment. This paper presents a novel approach that combines photogrammetry and deep learning techniques to address the problem of BIPV decarbonization. The method is called BIM-AITIZATION referring to the integration of BIM […]
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Development and Evolution of Hybrid Microgrids in the context of Contemporary Applications
This chapter provides a valuable insight to the development and evolution of hybrid microgrids, their applications, energy demand analysis, energy sources, mathematical modeling, objective parameters, and case studies. It begins with the definition of hybrid microgrids and highlights their importance in various sectors. Onward, it discusses the key microgrid applications. The analysis of energy demand […]
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Raw dataset of compression tests on a vegetable oil-based polyurethane foam exposed to different ageing conditions
The current dataset brings raw compression test information of a vegetable-based polyurethane foam (PUF) exposed to different temperatures over different periods of time. Such experimental dataset can provide researchers with important information in the application of numerical and data-driven simulations. Also, it saves money and time once the experimental part is already available. At total, […]
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Choix de fournisseurs sous une demande dynamique et des délais de livraison stochastiques
Ce travail traite du choix optimal des fournisseurs dans un contexte de demande dynamique et de délais de livraison stochastiques. L’étude propose plusieurs modèles linéaires stochastiques pour optimiser la répartition des commandes entre différents fournisseurs, en tenant compte des coûts d’achat, des pénalités de retard et des coûts de stockage. L’objectif est de minimiser le […]
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Evolutionary-Based Ant System Algorithm to Solve the Dynamic Electric Vehicle Routing Problem
This article addresses the Dynamic Electric Vehicle Routing Problem with TimeWindows (DEVRPTW) using a hybrid approach blending genetic and Ant Colony Optimization (ACO) algorithms. It employs an Ant System algorithm (AS) with an integrated memory system that undergoes mutations for solution diversification. Testing on Schneider instances under static and dynamic conditions, with run time of […]
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Elevating Manufacturing Excellence: A Data-Driven Approach to Optimize Overall Equipment Effectiveness (OEE) for a Single Machine
In the intensely competitive landscape of global manufacturing, achieving operational excellence is paramount for survival and success. Central to this endeavor is the optimization of Overall Equipment Effectiveness (OEE), a key metric that directly influences resource efficiency and product quality. Manufacturing companies face numerous challenges, including maintenance inefficiencies, unplanned downtimes, and product quality variations, which […]
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A Comparative Study of Blockchain Development Platforms
Blockchain technology is nowadays applied to several domains, essentially finance, healthcare, supply chain, and digital identity management. For enterprises to adopt a blockchain solution, many existing platforms facilitate the development process rather than implementing the system from scratch. Each platform has its own characteristics, capabilities, and limitations. Thus, several factors should be considered, including the […]
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Improving Semantic Mapping with Prior Object Dimensions Extracted from 3D Models
Semantic mapping is a critical challenge that must be addressed to ensure the safe navigation of mobile robots. Equipping robots with semantic information enhances their interactions with humans, as well as their navigation and task planning capabilities. Semantic maps go beyond occupancy information, providing supplementary details about mapped elements that empower robots to gain a […]
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Benchmarking OpenStack for edge computing applications
In this paper, we focus on the identification and evaluation of performance factors of OpenStack-based edge computing platforms. Such infrastructure relies on the deployment of additional computing resources close to the data source, to alleviate low throughput, latencies and network congestion. While cloud data centres offer numerous compute-intensive processing units, the edge layer leverages heterogeneous, […]
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Integration of Pricing and Production Scheduling Decisions: A Mathematical Model
In today’s competitive manufacturing landscape, achieving operational efficiency and optimizing revenue generation are key objectives for make-to-order manufacturers. This paper presents a novel approach for integrating production scheduling and pricing decisions in a make-to-order manufacturing environment. We propose a comprehensive mathematical model that addresses the complex interplay between production scheduling and pricing strategies. By jointly […]
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EEG-based Emotion Recognition Using Modified Covariance and Ensemble Classifiers
The Electroencephalography (EEG)-based precise emotion identification is one of the most challenging tasks in pattern recognition. In this paper, an innovative EEG signal processing method is devised for an automated emotion identification. The Symlets-4 filters based « Multi Scale Principal Component Analysis » (MSPCA) is used to denoise and reduce the raw signal’s dimension. Onward, the « Modified […]
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