Publications
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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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Optimizing Resource Allocation in the Flexible Job Shop Problem: Assessing the Impact of Rest Breaks on Task Strenuousness Reduction
The integration of collaborative robots (cobots) in production workshops aims to enhance productivity while minimizing physical strain for human operators. However, physical strain is often treated merely as a constraint rather than as an objective to address. To effectively model the production process and incorporate human factors, it is crucial to employ an appropriate index […]
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Potatoes Supply Chain Challenges and Opportunities in Algeria : A literature Review
The Agri-Food Supply Chain (AFSC) has become a focal point of attention in recent times due to the intersection of technology and integrated Supply Chain (SC) performance. Current research endeavors aim to minimize waste, maximize yield, and enhance planning while ensuring chain traceability and maintaining product price equilibrium. This paper offers a comprehensive summary of […]
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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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SPDGAN: A Generative Adversarial Network based on SPD Manifold Learning for Automatic Image Colorization
This paper addresses the automatic colorization problem, which converts a gray-scale image to a colorized one. Recent deep-learning approaches can colorize automatically grayscale images. However, when it comes to different scenes which contain distinct color styles, it is difficult to accurately capture the color characteristics. In this work, we propose a fully automatic colorization approach […]
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Contribution to Maintenance 4.0 by Monitoring and Prognosis of Industrial Installations by Digital Twin: Case Study on Wastewater Filtration Pilot
The digital solutions have taken an advance during the digital transition in the industrial development, the use of new technologies has allowed to better understand the behavior of the different parts of an industrial installation and to verify the interactions between the adjustment parameters and the optimal functioning of the production units and their impact […]
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Investigation of Input Feature Combinations Considering Occupant Behavior for Modelling Indoor Air Temperature in a Classroom
This study investigated the performance of artificial neural networks and random forests with various combinations of input variables in modelling indoor air temperature in a classroom. The data collection methodology was designed to investigate key input parameters, including indoor air data, classroom occupancy, and occupant behavior factors such as windows, doors, blind operation, and occupant […]
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D-STGCNT: A Dense Spatio-Temporal Graph Conv-GRU Network based on Transformer for Assessment of Patient Physical Rehabilitation
This paper tackles the challenge of automatically assessing physical rehabilitation exercises for patients who perform the exercises without clinician supervision. The objective is to provide a quality score to ensure correct performance and achieve desired results. To achieve this goal, a new graph-based model, the Dense Spatio-Temporal Graph Conv-GRU Network with Transformer, is introduced. This […]
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Fault Prediction in a Smart Building Lighting System
With the advances in many areas such as sensing technologies, new connectivity options and improved IoT architectures, predictive maintenance is considered as a promising solution for the maintenance of Smart Buildings (SBs). However, because of the lack of failure data for these systems, the approaches in the literature, which are mostly data-based approaches, are not […]
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Guaranteeing information integrity and access control in smart cities through blockchain
The distributed devices in a smart city are characterized by different degrees of sensitivity. Some of them can be accessed by everyone whereas others are limited to a specific class of users (subjects). Therefore, we created an access control system named (Subject-Object-Task System) supported by blockchains that sort processes applied by subjects on smart devices. […]
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