Symposia and Study Days

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Now showing 1 - 9 of 9
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    Programme de la Journée Workshop N° 02 des doctorants ENR-ELT
    (university ghardaia, 2025-01-31) Department, of Mathematics and Computer Science
    Planning de la journée du Workshop Programme de travail de la journée du Mercredi 31 Janvier 2024
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    Open Study Day Math Day: Geometry, Fractional Equations & Algebra
    (university ghardaia, 2025-05-05) Department, of Mathematics and Computer Science; Laboratory, of Mathematics and Applied Sciences
    Open Study Day Math Day: Geometry, Fractional Equations & Algebra
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    Partial Differential Equations & Ordinary Differential Equations: Theory and Applications
    (university ghardaia, 2025-04-28) Department, of Mathematics and Computer Science; Laboratory, of Mathematics and Applied Sciences
    In our presentation, we spotlight the theory of C0 semigroups as a fundamental tool for analyzing evolution equations in Banach spaces. We begin by reviewing the general properties of C0 semigroups and their role in describing the time evolution of systems governed by linear operators. The discussion then moves to the abstract Cauchy problem, emphasizing conditions for the existence, uniqueness, and regularity of solutions using semigroup methods. We extend these ideas to nonlinear evolution equations, highlighting techniques that address the challenges posed by nonlinearity. Special attention is given to delay differential equations (DFEs), where the system’s future state depends on its history. After providing an overview of delayed systems, we discuss two major cases: abstract linear delayed equations and semi-linear delayed equations, showing how semigroup theory adapts to account for memory effectsL’objectif de cet exposé est de prouver l’existence et l’unicité d’une solution d’un problème de Goursat non linéaire dans la classe des fonctions quasi-analytiques de type Denjoy- Carleman, plus précisément dans l’ensemble des fonctions continues Denjoy-Carleman. L’idée est de transformer le problème integro-diferentiel à un problème de point fixe appliqué dans une boule fermée dans une algèbre de Banach définie par une série formelle et une suite numérique logarithméquement convexe convenablement choisieA problem of initial value problem for a nonlinear Caputo fractional differential equation on an unbounded interval is considered. Based on some fractional calculus and the Krasnoselskii’s fixed point theorem, we prove our main results (existence and asymptotic stability). Then we give an example to illustrate our study.s..It is our pleasure to cordially invite all professors and students to participate in an Open Study Day dedicated to Ordinary Differential Equations (ODE) & Partial Differential Equations (PDE).
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    phd workshop
    (university ghardaia, 2025-05-20) كلية, العلوم والتكنولوجيا
    ايام دكتوريال تخصص طاقات متجددة في الاكتروتقني لجميع الاسات\ة والباحثين المهتمين بكلية العلوم والتكنولوجياايام 21 و 22 ماي 2025
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    study day :modern application of basic physics concepts
    (university ghardaia, 2025-02-06) faculty of, science and technology
    study day of basics physics consepts :experiences qpplicqtions advanced research principles of mechanics .principles of electrycity ;principles of Quantum
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    professionnelles pour l'étudiant universitaire en spécialité hydraulique
    (University Ghardaia, 2024) Laboratoire des Matériaux, des systèmes énergétique et environnement Technologie
    Dans un monde en constante évolution, où les défis environnementaux et les besoins en infrastructures durables se font de plus en plus pressants, la spécialité hydraulique se positionne au cœur des solutions d'avenir. L'Université de Ghardaïa a l'honneur de vous convier à sa journée scientifique annuelle, intitulée "Perspectives professionnelles pour l'étudiant universitaire en spécialité hydraulique". Cette journée promet d'être un carrefour d'échanges, de découvertes et d'opportunités, ouvrant les horizons sur les vastes perspectives professionnelles dans le domaine de l'hydraulique. Notre programme est conçu pour stimuler l'esprit critique de nos étudiants, les encourager à explorer de nouvelles avenues de recherche et de développement, et à envisager leur future carrière sous un jour nouveau.
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    الاسبوع الجامعي للذكاء الاصطناعي
    (university GHardaia, 2023-04) faculty seince, and thechnology
    اسبوع الذكاء الاصطناعي بكلية العلوم تضمن الغباء الاصطناعي والذكاء الاصطناعي والعلوم الاخرى ومعرض حول اعمال وانجازات الطلبة -بوستار -حول الذكاء الاصطناعي
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    برنامج انشطة الاسبوع الجامعي للرياضيات
    (university GHardaia, 2023-03) faculty seince, and thechnology
    تضمن الاسبوع الجامعي للرياضات بجامعة غرداية كلية العلوم والتكنولوجيا برنامج ثري حول لماذا الرياضيات والهندسة التفاضلية وتطبيقاتها الرياضيات والذكاء الاصطناعي والروبوتيك والرياضيات وعالم الاقتصاد كما تضمن ورشات لتعميم الرياضيات
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    study days on deep learning and big data challanges
    (university GHardaia, 2023-04-29) Laboratory of matimatique, and applied sience
    hese study days are part of the activities of the LMSA laboratory (Laboratoire des Mathématiques et Sciences Appliquées) and within the framework of the training to strengthen the doctoral program in computer science "Artificial Intelligence and Big Data" for the year 2021/2022." Deep learning, a subfield of machine learning, uses artificial neural networks with multiple layers to learn from data. With the rise of big data comes the need for scalable and efficient deep learning algorithms that can handle massive amounts of data while still maintaining accuracy and interpretability of the outputs. In this context our study days try to highlight the challenges associated with deep learning and big data from the perspective of computer science. The program of the study days aims to be progressive, from initiation to an advanced stage of the topic being addressed. It includes an historical overview of artificial intelligence, a simple introduction to machine learning, a discussion of big data challenges, and some advanced technologies of deep learning as fine tuning LLM, generative models, deep reinforcement learning, and advanced deep learning models