<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns="http://purl.org/rss/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel rdf:about="http://univ-bejaia.dz/dspace/123456789/270">
    <title>DSpace Collection:</title>
    <link>http://univ-bejaia.dz/dspace/123456789/270</link>
    <description />
    <items>
      <rdf:Seq>
        <rdf:li rdf:resource="http://univ-bejaia.dz/dspace/123456789/25965" />
        <rdf:li rdf:resource="http://univ-bejaia.dz/dspace/123456789/25964" />
        <rdf:li rdf:resource="http://univ-bejaia.dz/dspace/123456789/25963" />
        <rdf:li rdf:resource="http://univ-bejaia.dz/dspace/123456789/25962" />
      </rdf:Seq>
    </items>
    <dc:date>2026-04-08T21:05:58Z</dc:date>
  </channel>
  <item rdf:about="http://univ-bejaia.dz/dspace/123456789/25965">
    <title>Bio-inspired computation for bio-informatics problems.</title>
    <link>http://univ-bejaia.dz/dspace/123456789/25965</link>
    <description>Title: Bio-inspired computation for bio-informatics problems.
Authors: Dabba, Ali; Tari, Abdelkamel ; directeur de thèse
Abstract: The field of bioinformatics opens up great opportunities to understand biological phenomena, which has attracted&#xD;
great interest from the scientific community in recent years. Consequently, there are many problems of&#xD;
bioinformatics, including multiple sequence alignment, protein structure prediction, construction of the&#xD;
phylogenetic tree and molecular docking, etc., which need the cooperation between biologists and computer&#xD;
scientists to be solved. This work addresses two problems: multiple sequence alignment and gene selection using&#xD;
bio-inspired algorithms. Firstly, we developed a method to solve the multiple sequence alignment problem, called&#xD;
a multi-objective artificial fish swarm algorithm (MOAFS), using the behaviors of artificial fish swarm algorithms,&#xD;
Pareto optimal set, and genetic operations. Secondly, we proposed an algorithm to solve the gene selection problem&#xD;
by using mutual information, moth flame optimization algorithm, and support vector machine with leave one out&#xD;
cross-validation (SVMLOOCV). It called the Mutual Information Maximization-modified Moth Flame Algorithm&#xD;
(MIM-mMFA) that consists of two simple phases. The thesis has processed a full test of the MOAFS on the&#xD;
BaliBASE 2.0 and BaliBASE 3.0 alignment benchmark datasets as well as the MIM-mMFA test on sixteen binary&#xD;
and multi-classes cancer gene expression datasets. Finally, we have given a deep insight into the performance of&#xD;
each algorithm. In addition, our proposed algorithms achieved competitive or better results than the wellestablished&#xD;
algorithms in the literature.&#xD;
Keywords: Bio-informatics; Bio-inspired Algorithms ; Multiple Sequence Alignment ; Artificial Fish Swarm&#xD;
Algorithm ; Gene Selection Genes Expression ; Microarray ; Cancer Classification ; Moth Flame Optimization&#xD;
Algorithm.&#xD;
Résume&#xD;
Le domaine de la bio-informatique offre de grandes possibilités de comprendre les phénomènes biologiques, ce&#xD;
qui a suscité un grand intérêt de la part de la communauté scientifique ces dernières années. Par conséquent, il&#xD;
existe de nombreux problèmes de bio-informatique, y compris l’alignement de séquences multiples, la prédiction&#xD;
de la structure des protéines, la construction de l’arbre phylogénétique et l’amarrage moléculaire, etc. qui&#xD;
nécessitent la coopération entre biologistes et informaticiens pour être résolus. Ce travail aborde deux problèmes:&#xD;
l’alignement de séquences multiples et la sélection de gènes à l’aide d’algorithmes bio-inspirés. Premièrement,&#xD;
nous avons développé une méthode pour résoudre le problème de l’alignement des séquences multiples, appelée&#xD;
algorithme d’essaim de poissons artificiels multi-objectifs (MOAFS), en utilisant les comportements des&#xD;
algorithmes d’essaim de poissons artificiels, l’ensemble Pareto-optimal, et les opérations génétiques.&#xD;
Deuxièmement, nous avons proposé un algorithme pour résoudre le problème de sélection de gènes en utilisant&#xD;
l’information mutuelle, l’algorithme d’optimisation de flamme de papillon de nuit, et le Machine à vecteurs de&#xD;
support avec leave-one-out cross-validation (SVM-LOOCV). Il a appelé Mutual Information Maximizationmodified&#xD;
Moth Flame Algorithm (MIM-mMFA) qui se compose en deux phases simples. La thèse a traité un test&#xD;
complet du MOAFS sur les ensembles de données de référence d’alignement BaliBASE 2.0 et BaliBASE 3.0 ainsi&#xD;
que le test MIM-mMFA sur seize ensembles de données du cancer binaires et multi-classes. Enfin, nous avons&#xD;
donné un aperçu approfondi des performances de chaque algorithme. De plus, nos algorithmes proposés ont obtenu&#xD;
des résultats compétitifs ou meilleurs que les algorithmes bien établis dans la littérature.&#xD;
Mots-clés: Bioinformatique ; Algorithmes bio-inspirés ; Alignement de séquences multiples ; Algorithme&#xD;
d’essaim de poissons artificiels ; Sélection des gènes ; Expression des gènes ; Puces à ADN ; Classification du&#xD;
cancer; Algorithme d’optimisation de la flamme papillon.
Description: Option : Cloud Computing</description>
    <dc:date>2021-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://univ-bejaia.dz/dspace/123456789/25964">
    <title>Mécanismes de formation de coalitions multi-agents avec externalités.</title>
    <link>http://univ-bejaia.dz/dspace/123456789/25964</link>
    <description>Title: Mécanismes de formation de coalitions multi-agents avec externalités.
Authors: Sklab, Youcef; Tari, Abdelkamel ; directeur de thèse
Abstract: Formation de coalitions : Externalités dynamiques : Dépendances entre tâches*
Description: Option : Cloud Computing</description>
    <dc:date>2021-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://univ-bejaia.dz/dspace/123456789/25963">
    <title>Option : Réseaux et Systèmes distribués</title>
    <link>http://univ-bejaia.dz/dspace/123456789/25963</link>
    <description>Title: Option : Réseaux et Systèmes distribués
Authors: Djamila, Zamouche; Aissani, Soufiane ; directeur de thèse
Abstract: Over the last decades, advancements in computing, electronics, and mechanical systems&#xD;
have been resulting in the development of transportation all over the world, which has&#xD;
been providing a lot of benefts for many aspects of human life. Intelligent Transportation Systems (ITSs) are advanced applications that aim to make the transportation&#xD;
infrastructures safer, more convenient, and smarter by using information that is shared&#xD;
among vehicles such as crash warning, sudden-brake warning, lane-change warning,&#xD;
and so on. Thus, such systems provide a wide variety of services including, but not&#xD;
limited to, trafc control, trafc management, passenger and road safety, and remote&#xD;
region connectivity. However, several challenges hampering the proper operation of&#xD;
these systems, such as extreme disturbances and they rely on several kinds of devices&#xD;
that can cause malfunctions. Moreover, vehicular communications are expected to&#xD;
be subject to severe breaches that a?ect the reliability of the exchanged information.&#xD;
Seeking to improve the safety and protect human life, in this thesis, we address these&#xD;
problems by providing improvements to the existing STIs. In particular, we have proposed an enhanced train-centric communication-based train control system for railway&#xD;
transportation that allows improving the quality and enhancing reliability of the train&#xD;
control. Moreover, we have proposed our second contribution that manifests itself in&#xD;
the proposition of a discordant safety messages detection strategy in connected vehicles&#xD;
environment that provides the vehicles with the ability to quickly and preemptively&#xD;
identify discordant messages and hence dealing against potential disturbances, while&#xD;
ensuring a trade-o? between the efciency and safety. The proposed mechanisms are&#xD;
evaluated through simulations in terms of important metrics. The obtained results&#xD;
highlight the promising performances of our proposals.
Description: Option : Data Science</description>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://univ-bejaia.dz/dspace/123456789/25962">
    <title>Time synchronization in wireless senor and actuator networks.</title>
    <link>http://univ-bejaia.dz/dspace/123456789/25962</link>
    <description>Title: Time synchronization in wireless senor and actuator networks.
Authors: Boukhechem, Nadhir; Badache, Nadjib ; directeur de thèse
Abstract: The purpose of time synchronization is to allow the different nodes' clocks in a network to get relatively&#xD;
close values at any moment. Currently, time synchronization is a fundamental problem in wireless sensor&#xD;
and actuator networks (WSANs). Indeed, many WSANs applications, including node localization, sleep&#xD;
schedule, and data aggregation, require accurate time synchronization to function properly. In this thesis, we&#xD;
propose two cluster-based time synchronization protocols for WSANs, namely Sensor and Actuator&#xD;
Networks Synchronization Protocol (SANSync), and Optimized Sensor and Actuator Networks&#xD;
Synchronization Protocol (OSANSync). These protocols, contrary to existing protocols, fully exploit the&#xD;
available resources of the actuators, particularly their large transmission range, to improve time&#xD;
synchronization accuracy. We also propose a heuristic-based method to select the ROOT node through&#xD;
which all the other nodes in the network are synchronized. The proposed method is fully distributed and can&#xD;
be easily integrated into time synchronization protocols to improve their performance.
Description: Option : Réseaux et Systèmes distribués</description>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
  </item>
</rdf:RDF>

