Publications
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Machine Learning Assistive State of Charge Estimation of Li-Ion Battery
For an effective and economical deployment of battery-powered electric vehicles, mobile phones, laptops, and medical gadgets, the State of Charge (SoC) of the batteries must be properly assessed. It permits a safe operation, have a longer usable battery life, and prevent malfunctions. In this context, the battery management systems provide diverse SoC estimation solutions. However, […]
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Hybradization of Emperical Mode Decomposition and Machine Learning for Categorization of Cardiac Diseases
The arrhythmia is one of the cardiovascular diseases which has several types. In literature, researchers have presented a broad study on the strategies utilized for Electrocardiogram (ECG) signal investigation. Automated arrhythmia detection by analyzing the ECG data is reported using a number of intriguing techniques and discoveries. In order to effectively categorize arrhythmia, a novel […]
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Artificial Intelligence Assistive Fire Detection and Seeing the Invisible Through Smoke using Hyperspectral and Multi-spectral Images
Abstract— The global warming has serious impact on our climate. Due to this, the frequency and the intensity of forest fires is increasing. It has shown serious challenges such as the protection of resources, human and wild life, health, and property. This study focuses on developing an artificial intelligence assistive innovative solution for active fire […]
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Particle filter meets hybrid octrees: an octree-based ground vehicle localization approach without learning
This paper proposes an accurate lidar-based outdoor localization method that requires few computational resources, is robust in challenging environments (urban, off-road, seasonal variations) and whose performances are equivalent for two different sensor technologies: scanning LiDAR and flash LiDAR. The method is based on the matching between a pre-built 3D map and the LiDAR measurements. Our […]
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Improving Causality in Interpretable Video Retrieval
This paper focuses on the causal relation between the detection scores of concept (or tag) classifiers and the ranking decisions based on these scores, paving the way for these tags to be used in the visual explanations. We first define a measure for quantifying a causality on a set of tags, typically those involved in […]
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Errare humanum est, perseverare autem diabolicum: A Follow-Up Study on the Human-Likeness of an AI Othello Player
Othello, also known as Reversi, is a popular 2-players board game. Olivaw is an intelligent agent playing Othello. Compared to the most famous ones (such as Saio), it exploits limited resources by autonomously learning how to improve its gameplay by playing against itself. In previous occasions, Othello players reported the impression of a sort of […]
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NSGA-II for solving a multi-objective, sustainable and flexible job shop scheduling problem
Recently, sustainable scheduling has emerged to make the trade-off between economic, environmental and social factors. While classical scheduling research focuses on economic and environmental indicators such as makespan and energy consumption, modern human-centred manufacturing systems consider additional important factors such as workers’ well-being and ergonomic risks. This study proposes a multi-objective mathematical model that jointly […]
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Distributed dynamics scheduling based reinforcement learning: importance and challenges
When it comes to scheduling choices inside complex industrial systems, the dynamic job shop scheduling problem (DJSSP) poses substantial difficulties. Deep learning, artificial intelligence (AI), and reinforcement learning approaches have all shown promising solutions in recent years to enhance the effectiveness and performance of DJSSP systems. This study provides a detailed analysis of the DJSSP […]
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Machine Learning for Predicting Personality Traits from Eye Tracking
Recently, personality prediction holds significant importance in human centered systems, particularly in decision support systems, the smart industry, and the development of human machine interfaces. Eyes can reveal deep insights into a person’s personality, so people’s visual behavior could better reflect their personality. In this research, we demonstrate that machine learning techniques can predict individual […]
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Comparative Study of Waste Management Systems in Algeria and Other Countries : a literature review
Waste management holds significant importance for developing countries due to its impact on the environment, health, and economy. Insufficient waste management practices can result in pollution, disease outbreaks, greenhouse gas emissions, and social conflicts. Consequently, developing countries must make strategic decisions to enhance their waste management systems and practices. This article aims to examine waste […]
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lectric Vehicle Route Simulation: A Preliminary Approach
This article presents a NetLogo-based multi-agent simulator developed to optimize route and task planning using electric vehicles for travel between branches of Société Générale. The simulator takes into account constraints linked to the limited autonomy of electric vehicle batteries in the dense urban context of branches. We carried out simulation tests to evaluate the simulator’s […]
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Hub location problems: Classification and bibliometric analysis of relevant works
This paper presents a detailed study of the wellknown hub location problem (HLP). Its primary objective is to introduce novice readers to the complexity of this field. We focus on a review of pioneering work in HLP and have classified it according to several criteria. To do this, several classes have been identified, in particular: […]
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