قسم الإعلام الالي
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Item Cloud and Virtualization(University of Oum El Bouaghi, 2026) Zertal, SoumiaThis document is a course support for the subject entitled "Cloud and Virtualization ", taught in the Department of Mathematics and Computer Science at the University of Oum El Bouaghi and intended for second year Master's students in computer science, specializing in distributed architecture. The objective of this course is to provide students with: - Understanding of the principles of virtualization; - Manipulating the different concepts of virtualization through practical tools; - Discovering the concept of Cloud Computing and its applications; - Knowledge of the most well-known Cloud platforms and the ability to manipulate the services offered by at least one of these platforms. To achieve the stated objective, we made every effort to approach this work from multiple perspectives and synthesized the most relevant information using a variety of sources (books, lecture notes, articles, websites, etc.), while adhering to the official framework defined by the Ministry of Higher Education and Scientific Research. To make the course more engaging, we added practical sessions designed to facilitate the application of the theoretical concepts covered in the lectures. Nevertheless, we are aware that this document will remain partial, incomplete, and not exhaustive. For this reason, we strive to ensure continuous updates, with the aim of enriching its content. Therefore, we would be grateful if readers would point out any errors or offer suggestions in this regardItem Cours de Détection et Estimation de mouvement(Université d’Oum El Bouaghi, 2020) Ghoul, KhalidLe présent document s’agit d’un support de cours concernant la matière intitulée «Détection et estimation de mouvement», enseigné au Département de Mathématiques et d’Informatique à l’université d’Oum El Bouaghi et destiné aux étudiants de la deuxième année Master en informatique, option vision arti_cielle. Ce support de cours vise à donner aux étudiants une compréhension sur les principes de la détection et l’estimation de mouvement dans les séquences d’images, tout en montrant leurs rôles et leurs fonctionnalités dans les systèmes de vision arti_cielle. Aussi ce cours vise à former les étudiants dans les traitements des séquences d’images notamment la notion de mouvement : — Déduire les objets en mouvements, — Quanti_er les déplacements et — Déterminer l’orientation et le sens du mouvement en chaque pixel de ces objets. A_n d’atteindre l’objectif tracé, nous avons déployé tous les e_orts pour approcher ce travail dans plusieurs aspects et nous avons synthétisé les informations les plus pertinentes en nous appuyant sur des sources variées (ouvrages, notes de cours, articles, sites internet. . . ). Tout en respectant le canevas o_ciel dé_ni par le ministère de l’enseignement supérieur et de la recherche scienti_que. Néanmoins, nous avons conscience que ce document restera partiel, tronqué et non exhaustif. C’est pour cette raison que nous essayons de veiller à une actualisation permanente, dont le but est d’enrichir son contenu. Ainsi, nous serions reconnaissant aux lecteurs de nous signaler toute erreur ou de nous proposer des suggestions dans ce sens.Item Decision support systems (DSS)(University of Oum El Bouaghi, 2025) Saighi, AsmaDecision Support Systems (DSS) have become essential tools in modern organizations, helping decision-makers analyze complex problems, evaluate multiple alternatives, and improve overall efficiency. This Course Handbook provides a structured approach to understanding the key principles, methodologies, and applications of DSS. The handbook begins with an introduction to decision-making processes, highlighting the different types of decisions and the conditions under which they are made. It explores various decision theories, from normative to descriptive and prescriptive models, providing a theoretical foundation for effective decision-making. A significant focus is placed on Decision Analysis under Risk and Uncertainty, where techniques such as decision trees, expected value calculations, and utility theory are discussed. The handbook also delves into Multi-Criteria Decision-Making (MCDM) approaches, emphasizing both single-criteria and multi-criteria models, including outranking methods like ELECTRE and PROMETHEE. Furthermore, essential mathematical techniques such as normalization, weight assessment, and data transformation are introduced to help structure and quantify decision problems. Throughout the course, practical examples and real-world applications illustrate how DSS methodologies can be applied to business, engineering, healthcare, and other domains. By the end of this handbook, students will have a comprehensive understanding of DSS principles, enabling them to develop, analyze, and implement decision support models effectively.Item Deep learning(University of Oum El Bouaghi, 2026) Zertal, SoumiaThis Deep Learning course handbook represents a comprehensive and rigorous exploration of one of artificial intelligence's most transformative disciplines, specifically designed for first-year Master's students specializing in Artificial Intelligence. The curriculum provides systematic coverage of both foundational principles and cutting-edge architectures that define contemporary deep learning practice. The course adopts a carefully structured pedagogical progression, beginning with theoretical foundations including neural network mathematics, activation functions, and backpropagation mechanisms, before advancing through specialized architectures: convolutional neural networks for visual data processing, recurrent networks (RNNs, LSTMs, GRUs) for sequential and temporal analysis, and generative models (GANs and VAEs) for data synthesis and augmentation. Each chapter integrates mathematical rigor with practical implementation, featuring real-world applications spanning computer vision, natural language processing, biomedical signal analysis, and autonomous systems. Students will develop essential competencies in designing, implementing, training, and critically evaluating deep neural networks while navigating architectural tradeoffs for domain-specific applications. The course emphasizes hands-on learning through exercises, projects, and implementation using modern frameworks, fostering both technical proficiency and conceptual intuition. Prerequisites include solid foundations in linear algebra, calculus, probability theory, and programming (preferably Python), along with basic machine learning concepts. Beyond technical mastery, the course instills critical awareness of ethical dimensions; fairness, transparency, privacy, societal impact, and environmental costs; that accompany powerful AI technologies. As future practitioners shaping artificial intelligence's trajectory, students are encouraged to approach these transformative capabilities with both excellence and responsibility, cultivating habits of continuous learning, rigorous thinking, and ethical innovation in a rapidly evolving field.Item Educational handout of tutorials and practical work in algorithms and data structures 2 (ADS2)(University of Oum El Bouaghi, 2025) Dehimi, Nour El HoudaThis document presents tutorials and practical exercises, designed to teach the subject "Algorithms and Data Structure 2," introduced in the second semester in the Department of Mathematics and Computer Science at Oum El Bouaghi University, and intended for first-year computer science students. First, the pedagogical objectives of this document are: - Manipulate sub-algorithms (subroutines): procedures & functions; - Understand recursive sub-algorithms; - Understand the declaration, syntax and semantics of pointers and linked lists; - Allow the student to acquire the fundamentals of programming. Indeed, and in order to achieve the aforementioned objectives, we have made tremendous efforts to approach this work in several aspects; where we have synthesized the most important and relevant information based on different documentary sources (books, articles, courses, websites, etc.). While respecting the official canevas determined by the Ministry of Higher Education and Scientific Research. Furthermore, this document is divided into two sections: the first presents tutorials and a set of exercises with their solutions, divided into parts, while the second section provides a set of practical exercises that enable students to acquire the basics of C programming. However, the document in question will remain partial and not exhaustive. This is why we will constantly update it to enrich its content. However, we would be grateful if readers could notify us of any errors, observations, etc., and also offer us opinions in this regard.Item Mathematical logic course and tutorial materials(University of Oum El Bouaghi, 2026) Boussaha, KarimaThis course in Mathematical Logic introduces the fundamental principles of formal reasoning and logical analysis used in mathematics and computer science. It explores the concepts of syntax and semantics, focusing on the representation and evaluation of logical statements. The course covers propositional logic, including propositions, logical connectives, truth tables, tautologies, satisfiability, normal forms (CNF and DNF), and proof systems such as resolution and refutation methods. It also introduces predicate logic as an extension of propositional logic, emphasizing predicates, quantifiers, free and bound variables, structures, interpretations, and semantic validity. Through theoretical explanations, solved exercises, and practical applications, the course aims to develop students’ ability to formalize reasoning, analyze logical structures, and apply logical methods to problem-solving in computer science and mathematics.Item Mobile applications(University of Oum El Bouaghi, 2026) Zaidi, SofianeWith the rapid evolution of mobile technologies, smartphones and portable devices have become an integral part of everyday life. At the core of these devices lies the mobile operating system, which plays a fundamental role in ensuring their functionality, usability, and performance. A mobile operating system not only manages hardware resources and wireless communication but also provides a platform for running applications and delivering services to users. Over the years, mobile operating systems have evolved significantly, transitioning from early systems designed for Personal Digital Assistants (PDAs) to sophisticated platforms capable of supporting complex applications while efficiently managing limited resources such as battery life and processing power. This evolution has led to the emergence of a wide range of operating systems, which can be broadly classified into proprietary and open-source systems, each with its own advantages and ecosystem. Today, the mobile operating system market is largely dominated by a few key players, shaping the direction of mobile computing and application development. Understanding these systems is essential for grasping how modern mobile applications are designed, deployed, and optimized.Item Mobile applications(University of Oum El Bouaghi, 2026) Silem, AbdelheqThis document serves as a comprehensive synthesis of the Mobile Application Development course delivered at the University of Oum El Bouaghi. The field of mobile development is at once fascinating, fast-paced, and technically demanding. Building modern mobile applications is often considered one of the most dynamic challenges in computer science, as it requires a developer to master a diverse ecosystem ranging from fundamental software engineering principles to the specific constraints of handheld hardware. To navigate this complexity, the student must be equipped with a varied toolkit. This includes foundational knowledge (application lifecycles, resource management, and asynchronous programming) as well as practical technical skills (UI/UX design, database persistence, and hardware integration like sensors and GPS). In alignment with academic standards, this course is structured to address the multi-layered nature of mobile systems. The first part focuses on the Frontend and User Interface (UI), covering layout design, activity lifecycles, and event handling. The second part explores Data Management and Integration, including local persistence (SQLite/Room), background services, and network communication with remote APIs. The documentation surrounding mobile development is vast and constantly evolving. Nevertheless, this manuscript draws from several foundational references, including the official Android Documentation, the architectural guidelines from Google, and seminal works on mobile software engineering. I have also integrated insights from industry-standard practices and modern pedagogical frameworks. While every effort has been made to ensure the accuracy and pedagogical clarity of this work, perfection remains a human ideal and this report is no exception. Given the rapid shifts in mobile technology and the inherent pressure of academic preparation, some errors may persist. Therefore, I kindly invite all readers to signal any errors whether they be typographical, methodological, or technical to help improve future editions of this course.Item Operating Systems 2(University of Oum El Bouaghi, 2026) Benaboud, RohallahThis course is an advanced study of operating system principles, intended for students who have a foundational understanding of the subject. It addresses the critical and complex challenges related to the management of concurrent processes and the resources they share. The main objective is to produce course support that is both rigorous and clear, ensuring a deep and unambiguous understanding of the concepts covered. The goal is to facilitate mastery of the principles of concurrency and to gather the necessary knowledge for designing and implementing robust, efficient, and correct multi-process and multi-threaded software. It should be noted that certain prerequisites are necessary to fully grasp the concepts presented. A foundational understanding of operating systems (process and memory management basics), as well as computer architecture, is assumed. Furthermore, strong programming skills, particularly in the C language, are required to understand and implement the practical examples. This course is organized into four main chapters: First, Chapter 1 provides a review of fundamental operating system concepts. It re-establishes the role and architecture of an OS and provides a detailed examination of the two core units of execution: processes and threads. This chapter covers their structure, lifecycle, and management, providing the essential foundation for the rest of the course. Chapter 2 describes the techniques for Process Synchronization. This chapter addresses the core challenge of concurrency: the race condition. It introduces the critical-section problem and details the various solutions, from early software algorithms (like Peterson's) to hardware support (atomic instructions) and powerful OS-level primitives like semaphores and monitors. The following chapter, Chapter 3, deals with Interprocess Communication (IPC). Once processes are synchronized, they often need to cooperate. This chapter covers the primary mechanisms that allow processes to exchange information, including shared memory, asynchronous notifications via signals, and data streaming using both unnamed and named pipes. Chapter 4 is entirely dedicated to the problem of Deadlocks. It begins by characterizing the four necessary conditions for a deadlock to occur. It then details the primary strategies for managing them: Deadlock Prevention, by structurally negating one of the conditions; Deadlock Avoidance, using the Banker's Algorithm to maintain a safe state; and finally, Deadlock Detection and Recovery.Item Outils d’Intelligence Artificielle(Université d’Oum El Bouaghi, 2023) Guerram, TaharLes premiers programmes intelligents commercialisés s‘appellent les systèmes experts qui permettent d‘automatiser le processus cognitif chez les experts humains. Bien que ces systèmes aient connu un succès extravagant depuis leur apparition au début des années soixante-dix jusqu‘à la fin des années quatre- vingt, leurs limites, se résument en la difficulté de modéliser parfois les aspects intuitifs du raisonnement humain, en plus de la difficulté de prendre en charge aussi d‘autres tâches complexes telles la vision artificielle et la traduction automatique des textes. Ces difficultés, ont poussé, plus tard, les développeurs et les chercheurs en systèmes experts à développer des systèmes experts hybrides utilisant des techniques un peu plus avancées de l‘Intelligence Artificielle, telle la théorie de l‘incertitude et la logique floue. Dans le même ordre d‘idée et pour pallier à la complexité de certains problèmes (tels les problèmes à explosion combinatoire comme le fameux problème du voyageur de commerce ou bien un problème de planification de tâches), des systèmes d‘Intelligence Artificielle inspirés de la nature et de la biologie ont été développés. Ces derniers copient la façon dont les systèmes biologiques et naturels se comportent pour résoudre les problèmes auxquels ils doivent faire face quotidiennement, par exemple les algorithmes génétiques en intelligence artificielle sont inspirés du principe de la sélection naturelle qui stipule, que les individus d‘une population qui s‘adaptent le mieux à leur environnement, ont de fortes chances de survivre et de se reproduire pour donner naissance à d‘autres populations. Aussi, les algorithmes de colonies de fourmis en intelligence artificielle, est un modèle artificiel qui s‘inspire du comportement d‘une colonie de fourmis lors de la recherche collective d‘une source de nourriture. Les individus appartenant à la population d‘un système naturel ou biologique communiquent d‘une manière directe ou indirecte ( par exemple, les fourmis communiquent indirectement par dépôt d‘une matière chimique dans l‘environnement appelée phéromone et ressentie par les autres fourmis. Par contre dans un réseaux de neurones, les cellules neuronales communiquent directement par envoi de signaux) dans le but de de trouver une solution à un problème auquel la population est confrontée. Par exemple, résoudre un problème d‘approvisionnement en alimentation ou résoudre un problème de sécurité de la population contre des ennemis, des intrus, ou des sources virales. La résolution de tels problèmes se fait d‘une manière collective par la coopération des individus de la population et dont la finalité est de mettre le système en entier dans un état de confort ou un état désiré dit objectif de la population.. Inspirés notamment par ces concepts de comportements collectifs intelligents émanant de systèmes naturels et biologiques, les chercheurs en intelligence artificielle ont réussi par la suite à mettre en oeuvre une nouvelle approche pour l‘intelligence artificielle distribuée connue sous le nom de « systèmes multi agents ». Selon cette nouvelle approche, un système multi agents est composé d‘un ensemble d‘agents autonomes qui coopèrent et interagissent pour atteindre un but global du système. Ce document est le fruit de l‘enseignement durant plusieurs années de la matière Intelligence Artificielle au profit des étudiants de troisième année palier licence et des étudiants du palier Master. L‘objectif escompté est de mettre à la disposition de ces étudiants une référence bibliographique leur serviront en tant que support de cours unifié de la matière Intelligence Artificielle.