Monographies

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    Quantum chemistry
    (University of Boumerdes : Faculty of sciences : department of chemistry, 2026) Djebra- Belmessaoud, Nadia
    Quantum chemistry provides the theoretical framework necessary to understand chemical bonding, electronic structure, and the spectroscopic properties of chemical systems. Quantum mechanics is a theory used to accurately describe the behavior of matter at the molecular, atomic, and subatomic scales. This discipline emerged in the early 20th century to address questions left unresolved by classical mechanics, such as the stability of the atom and the quantization of certain physical quantities. This handout has been prepared to support second-year undergraduate chemistry students (L2) in learning the fundamentals of quantum chemistry. This document combines theory, practical examples, and exercises to facilitate understanding and the application of the concepts covered. Students are expected to have certain mathematical foundations, such as operators and their properties, as well as some fundamental concepts, including the postulates of quantum chemistry, which are presented in the first chapter.
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    Analysis of the Reliability and Availability of the Algiers Metro Traction System Based on the Pareto and Weibull Three Parameters Methods
    (Springer, 2025) Siguerdjidjene, Hakim; Merah, Abdelkrim; Saidi, Djamel; Houari, Amin
    Rail transport by metro is a socio-economic form of transport, and the reliability of traction systems is considered to be one of the key factors required to ensure its smooth operation, safety and public comfort. In addition, it provides rapid mobility for citizens between different areas of a city and reduces the road congestion in urban areas by offering a fast, efficient transport alternative. This research is based on an in-depth analysis of the most frequent operating time data, failures and breakdowns (mechanical, electrical, etc.) of the ELDJAZAIR-Alger metro company's traction systems, with the aim of analysing the reliability and availability of these two series of traction systems, in order to minimize interruptions and maintain a high level of service to meet users' needs. Historical data was collected and thoroughly analyzed. Firstly, we visualized this data in the form of a Pareto chart known as the ‘20/80% rule’ (A, B, C) (Thomas E. Nisonger in The “80/20 Rule” and Core Journals. The Serials Librarian 55(1):62–84, in order to determine the highest priority areas. This makes it easier to process the data. Second, the reliability of vehicle traction systems is analyzed using the three-parameter Weibull probability criterion R (t, γ, η, β) (Vonta Ilia, Mangey Ram. Reliability Engineering: Theory and Applications. Publisher: CRC Press-Taylor & Francis Group ISBN: 9,780,815,355,175. (2018)), based on the calculation of the time-to-function and mean time between failures and the failure rate λ (t). The results obtained using the Pareto method show that the most critical faults are classified in zone A: where 20% corresponds to 80% of the total number of faults, representing five faults designated by codes as follows: [CLS, MON, CAJ, CAU, VAUX], which are more critical and take priority over emergency intervention by the maintenance department. The results of the analysis show that the correlatio n coefficient equals to 0.976, which indicates a very strong positive linear relationship between the percentage of variable failures and time and the reliability R (t, γ, η, β) of traction systems is almost in the approximate 50% with its parameters: γ = 0, β = 3.9776, η = 1067.62h and availability A(t) decreases over time, which requires measures to improve the latter by including new techniques for service management, control, preventive and corrective maintenance
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    Harnessing AI for control engineering
    (IGI Global, 2025) Mellal, Mohamed Arezki
    In the field of control engineering, the integration of artificial intelligence (AI) has opened new avenues for innovation and efficiency. By leveraging machine learning, neural networks, and advanced optimization algorithms, AI can enhance system performance, improve decision-making, and enable real-time adaptive control. These technologies empower engineers to design more robust, efficient, and autonomous systems that can respond to complex, dynamic environments with precision. Further research of AI and control engineering may address challenges of traditional methods and pave the way for smarter, more sustainable industrial processes. Harnessing AI for Control Engineering delves into the transformative integration of artificial intelligence (AI) within the domain of control engineering. It navigates the landscape of AI applications, from classical control methods to cutting-edge machine learning algorithms and nature-inspired optimization techniques. This book covers topics such as civil engineering, fault detection and diagnosis, and robotics, and is a useful resource for engineers, business owners, academicians, researchers, and scientists
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    محاضرات في لسانيات النص : موجهة لطلبة السنة الأولي ماستر
    (جامعة أمحمد بوقرة بومرداس : كلية الأداب و اللغات, 2025) سعدودي , سعيدة
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    A Collaborative System for Machine Learning-Based Final-Year Projects With Enhanced Dataset Accessibility
    (IGI Global, 2024) Lounas, Razika; Djerbi, Rachid; Mokrani, Hocine; Bennai, Mohamed Tahar
    This chapter explores the transformative impact of information and communication technology (ICT) on pedagogy, specifically focusing on the integration of collaboration tools in final year projects (FYPs). Final year projects (FYPs) represent the ultimate activity in the student's curriculum. They are designed to use, test, and enhance the knowledge students have gained over the years by confronting them with real-world projects. Despite existing systems for FYPs, the chapter identifies gaps, particularly in covering the entire FYP process and in addressing different collaborative aspects. With a focus on the rise of machine learning-based FYPs, this research aims to propose a comprehensive solution based on a proposed collaboration architecture in response to various needs such as communication, coordination, production, and resource sharing. The application is designed for multiple user roles, including students, advisors, and administrative staff, each allocated a personalized workspace. The novelty of the proposed system is its comprehensive coverage of all collaborative aspects mentioned throughout the FYP process, including proposal processing, project assignment, project completion, and evaluation. The research contributes to fostering innovation in machine learning projects by effectively managing and sharing datasets through collaboration tools. The results indicate good scores in improving collaborative aspects with a score of 98% for virtualization in coordination and 96% for communication. The results also showed that surveyed users are positively inclined to use the system as their final year project (FYP) management system, with an attention-to-use score of 90% of advisors and 92.8% of students.
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    Challenges and Opportunities in Green Hydrogen Production Materials for Biological Hydrogen Production
    (Springer, 2024) Akroum-Amrouche, Dahbia; Akroum, Hamza; Lounici, Hakim
    Biohydrogen is regarded as an attractive renewable source of clean energy and an environmentally friendly alternative to conventional fossil fuels. BioH2 can be produced via different biological pathways like direct and indirect biophotolysis, photo-fermentation, dark-fermentation, and bio-electrolysis using microbial electrolysis cells (MEC). The MEC is a bioelectrochemical approach that can be used to treat wastewater and produce biohydrogen, simultaneously. The MEC performance is highly affected by several factors such as microbial communities, cathode and anode catalysts’ activities, electrode materials and structures, current output, reactor design, associated anode and biocathode, catalysts, and substrate type, and concentration used. This chapter provides an overview of the recent developments in biological and non-biological materials involved in microbial electrolysis cells for biohydrogen production. The microbial species and enzymes, bio-inspired catalysts, advances in materials, and integration systems applied in these bioprocesses to improve catalytic performance, achieve lower configuration cost, and provide stable and efficient biohydrogen production are presented.
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    Binary whale optimization algorithm for topology planning in wireless mesh networks
    (Elsevier, 2023) Taleb, Sylia Mekhmoukh; Meraihi, Yassine; Mirjalili, Seyedali; Yahia, Selma; Ramdane-Cherif, Amar
    The objective of this research is to tackle the topology planning issue in Wireless Mesh Networks (WMNs) through the implementation of a Binary Whale Optimization Algorithm (BWOA). S-shaped and V-shaped families of transfer functions are employed to obtain a binary versions of WOA. BWOA is designed to reduce the number of mesh routers needed to meet the full coverage and full connectivity requirements. The performance of BWOA is evaluated using three metrics, namely the minimum, maximum, and average number of mesh routers, while taking into account variations in the number of mesh clients. According to the findings of the simulations carried out in Matlab®, BWOA algorithms utilizing V-shaped transfer functions outperform S-shaped transfer functions-based BWOA algorithms in terms of required number of mesh routers.
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    An enhanced whale optimization algorithm with opposition-based learning for LEDs placement in indoor VLC systems
    (Elsevier, 2023) Benayad, Abdelbaki; Boustil, Amel; Meraihi, Yassine; Mirjalili, Seyedali; Yahia, Selma; Taleb, Sylia Mekhmoukh
    Visible Light Communication (VLC) is a new technology that has attracted lately much interest from researchers and academics. It allows communication between users using photo-detectors (PDs) as receivers and light emitting diodes (LEDs) as transmitters. The deployment of LEDs in indoor VLC Systems is an important issue that affects the coverage of the network. In this article, we propose an improved version of Whale Optimization Algorithm, named EWOA, to resolve the LEDs placement problem in indoor visible light communication (VLC) systems. The EWOA is based on the integration of chaotic map concept and Opposition based learning method (OBL) into the standard WOA to improve its optimization performance. By taking into account the user throughput and coverage metrics while employing several produced instances and evaluating results against some meta-heuristics, the usefulness of EWOA was confirmed. The meta-heuristics that we used in the comparison are WOA, (MRFO) Manta Ray Foraging Optimizer, (CHIO) Herd immunity coronavirus optimizer, (MPA) Marine Predator Algorithm, (BA) Bat Algorithm, and (PSO) Particle Swarm Optimizer. The results showed that EWOA is more effective in finding optimal LEDs positions.
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    A hybrid whale optimization algorithm with tabu search algorithm for resource allocation in indoor VLC systems
    (Elsevier, 2023) Yahia, Selma; Meraihi, Yassine; Mirjalili, Seyedali; Taleb, Sylia Mekhmoukh; Refas, Souad; Ramdane-Cherif, Amar; Eldeeb, Hossien B.
    This paper proposes a novel hybrid approach (WOATS) based on the hybridization of Whale Optimization Algorithm (WOA) with Tabu search Algorithm (TS) for solving the resource allocation problem for indoor multi-user downlink VLC systems. The efficiency of the proposed WOATS is validated in several scenarios under different settings, considering the throughput and fairness parameters. The results demonstrated that WOATS provides competitive performance in optimizing resource allocation in indoor VLC systems compared to WOA, TS, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Arithmetic Optimization Algorithm (AOA), Moth Flame Optimization (MFO), Grey Wolf Optimizer (GWO), and Sine Cosine Algorithm (SCA).
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    Detection system parameters' effects on amplitude and spectral features of SFAP generated from a cylindrical multilayer volume conductor
    (Nova Science Publishers, Inc, 2023) Messaoudi, Noureddine; Belkacem, Samia
    The electromyographic (EMG) signal represents the electrical variations of muscles activities. It can be detected on the skin surface above the aimed muscle. The assessment of the effects of anatomical, physiological and detection system parameters on the shape of the detected surface EMG signal is more evident by using the signal generated by a single fibre action potential (SFAP). Amplitude and spectral characteristics of the detected signal are good estimators of the effects of the anatomical, physiological and detection system parameters on the shape of generated signal. In this work, we interpret the effects of the detection system parameters (the fibres inclination angle and the inter-electrode distance) on the average rectified value (ARV) and on the median frequency (MDF) of the surface SFAP signal generated in a multilayer cylindrical volume conductor contains the limb muscle. The potential is detected on the skin surface with a detection system which is constituted by eight 1D and 2D spatial filters and a grid of nine point electrodes. We show that the increase of the fibres inclination angle decreases the ARV and the MDF of the simulated signal and that the increase of the inter-electrode distance increases them.