Publications
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A global approach based on k-means clustering principle for optimal smartphones and laptops batteries waste collection in Algeria
Rapid urbanization and population growth in developing countries have posed significant challenges for solid waste management. This is clearly evident in African countries including Algeria, where environmental concerns are not effectively managed. The purpose of this article is to design a network to facilitate waste collection in Algeria. A location allocation-based clustering approach is proposed, […]
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Multi-objective resolution of hub location problem with hop-constraints
This paper investigates a flexible hub location problem within an incomplete inter-hub network, considering the multiple allocation of non-hub nodes to hubs. It assumes unlimited capacity for both hubs and links, with no direct links permitted. Although research on hub location problems with hop constraints is scarce, most studies in the literature incorporates the number […]
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Improving the Potato Supply Chain in Western Algeria: An Optimization Model
This study focuses on optimizing the potato supply chain in Algeria, particularly in the western region, where potatoes are a staple agricultural product. Despite significant production, the supply chain faces challenges such as inefficient planning, high losses, and price fluctuations, leading to food insecurity. The objective of this research is to develop a mathematical model […]
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Fault Diagnosis using Deep Neural Networks for Industrial Alarm Sequence Clustering
Significant progress has been made in the field of industrial alarm management systems (AMS) in terms of diagnostic and prognostic accuracy. However, persistent challenges, such as poorly configured alarm setups and floods, contribute to an increased number of false alarms, consequently reducing the efficiency of the monitoring system. In addition, more sophisticated models and interactive […]
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Synthetic Population Generation for Autonomous Vehicle Demand Forecasting
The growing interest in Automated Mobility on Demand (AMoD) services in passenger transportation necessitates accurate forecasting for successful deployment. However, the paucity of real-world data is a significant challenge. In this study, we present a unique technique for developing a synthetic user population tailored to AMoD car services. We identify possible passengers using selection criteria […]
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LoRaCAPS: Congestion-Aware Path Selection Protocol for Offshore LoRaWAN Networking
LoRaWAN technology plays a pivotal role in enabling data transmission from IoT devices across various industries. In the maritime sector, applications such as operational monitoring and environmental surveillance depend critically on reliable data communication. However, wireless data transmission at sea presents significant challenges, including limited device battery life, harsh weather conditions, and interference from vessels. […]
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A model-driven approach for prospective ergonomics: Application to ikigai robotics
Prospective Ergonomics requires building a vision of the future, which can be achieved empirically (e.g. analysing unmet needs) and/or creatively (e.g. creating future needs). We develop an alternative way of imagining the future, through a model-driven approach. Based on several developmental models, we provide a global picture of possible future(s) emphasising higher-ordered motivations and values […]
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Recovery and Restructuring of Fine and Coarse Soil Fractions as Earthen Construction Materials
Abstract: Excessive consumption of natural resources to meet the growing demands of building and infrastructure projects has put enormous stress on these resources. On the other hand, a significant quantity of soil is excavated for development activities across the globe and is usually treated as waste material. This study explores the potential of excavated soils […]
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Multi Objective Optimization of Human-Robot Collaboration: A Case Study in Aerospace Assembly Line
Collaborative robotics is becoming increasingly prevalent in industry 5.0, leading to a growing need to improve interactions and collaborations between humans and robots. However, the current approach to defining the sharing of responsibilities between humans and robots is empirical and uses the robot as an active fixture of parts, which is a sub-optimal method for […]
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An improved 3D skeletons UP-Fall dataset : enhancing data quality for efficient impact fall detection
Detecting impact where an individual makes contact with the ground within a fall event is crucial in fall detection systems, particularly for elderly care where prompt intervention can prevent serious injuries. The UP-Fall dataset, a key resource in fall detection research, has proven valuable but suffers from limitations in data accuracy and comprehensiveness. These limitations […]
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Improving Pain Classification using Spatio-Temporal Deep Learning Approaches with Facial Expressions
Pain management and severity detection are crucial for effective treatment, yet traditional self-reporting methods are subjective and may be unsuitable for non-verbal individuals (people with limited speaking skills). To address this limitation, we explore automated pain detection using facial expressions. Our study leverages deep learning techniques to improve pain assessment by analyzing facial images from […]
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Educational digital twins (EDT) to a sustainable future? Between promises and reality
The Sustainable Development Goals set by the United Nations in 2015 underline the urgency of sustainability in all sectors, starting with the industrial sector. The ambition of Industry 5.0 is to go beyond Industry 4.0, striving for a sustainable technological revolution centered on people (Barcellini, 2019; Julien & Martin, 2021). So-called “disruptive” industrial innovations are […]
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