Publications Internationales

Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/13

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Author: search.filters.author.Mezghiche, Mohamed

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Now showing 1 - 10 of 24
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    A Formalized procedure for database horizontal fragmentation in isabelle/HOL Proof Assistant
    (Springer, 2018) Cheikh, Salmi; Chaabani, Mohamed; Mezghiche, Mohamed
    We propose a logical procedure for the horizontal fragmentation problem based on predicate abstraction over the entire domain of database relations. The set of minterm predicates is constructed using rewriting rules similar to the well-known semantic tableau algorithm. The procedure start from an initial set of simple predicates, build the set of minterm predicates until rules are no longer required. To ensure this proposition, we give a formal proof of its correctness namely, it’s soundness, completeness and termination with Isabelle proof assistant. The main contribution of this work are: refining the minterm approach by adding a semantic layer to predicates, minimizing the set of minterm predicates by automatically eliminating contradictory ones, detecting and handling subsumptions between them. This leads to the best construction time of the final partitioning schema. Finally, a source code of the procedure is generated automatically by the Isabelle proof assistant.
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    Multi-agent medical image segmentation : a survey
    (Elsevier, 2023) Bennai, Mohamed Tahar; Guessoum, Zahia; Mazouzi, Smaine; Cormier, Stéphane; Mezghiche, Mohamed
    During the last decades, the healthcare area has increasingly relied on medical imaging for the diagnosis of a growing number of pathologies. The different types of medical images are mostly manually processed by human radiologists for diseases detection and monitoring. However, such a procedure is time-consuming and relies on expert judgment. The latter can be influenced by a variety of factors. One of the most complicated image processing tasks is image segmentation. Medical image segmentation consists of dividing the input image into a set of regions of interest, corresponding to body tissues and organs. Recently, artificial intelligence (AI) techniques brought researchers attention with their promising results for the image segmentation automation. Among AI-based techniques are those that use the Multi-Agent System (MAS) paradigm. This paper presents a comparative study of the multi-agent approaches dedicated to the segmentation of medical images, recently published in the literature
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    Towards compositional verification of synchronous reactive systems
    (2021) Chabane, Sarah; Ameur-Boulifa, Rabéa; Mezghiche, Mohamed
    We present work towards a compositional design approach that will lead designers to develop safe reactive systems. To this end, we extend the theory of I/O-automata that is widely used for modelling reactive systems with composition operator required for dealing with a specific assembly of such systems: systems that consist of a chain of components arranged so that the output of each component is the input of the next, and behave like pipelines. We show that the proposed composition operator ensures semantics preserving of reactive components models. The paper presents a general result on correct-by-construction approach for reactive systems design
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    A practical approach for verification of graph transformation with description logic
    (2020) Chaabani, Mohamed; Mezghiche, Mohamed
    Graphs and visual models play a central role in the modeling and meta-modeling of software systems, these models are specified using a modeling formalism, in a high-level abstraction independent of the platform, in which the focus is on the concepts rather than the implementation. This allows keeping the model, transporting it, and then transforming it into code. Several graph transformation tools have been developed to ensure efficient transformations. This transformation requires a process of verification and validation to guarantee the correction of this transformation process, of which there are different ways to checking that a software system achieves its goal. In computer science, formal methods are techniques that allow rigorous reasoning, using semantic and formal methods, to prove their validity with respect to a certain set of properties. In this sense, description logics are promising candidates for encoding graph structures and reasoning about graph transformations, they are privileged target to operationalize graph transformation tools because they have the mechanisms of reasoning or inference
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    Exploiting links to improve search in XML documents
    (Digital Information Research Foundation, 2018) Berchiche-Fellag, Samia; Mezghiche, Mohamed
    This paper describes an approach that ex-ploits links in XML retrieval. The proposed approach con-sists of reranking the set of documents returned for agiven query by considering three sources of evidencenamely, the relevance scores w.r.t query of a documentneighbours, the text of the anchor links, and the docu-ment title tag. Our approach is evaluated on INEX 2006collection. The results showed significant improvementsof the retrieval performances
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    Formal methods in dynamic software updating : a survey
    (Inderscience, 2019) Lounas, Razika; Mezghiche, Mohamed; Lanet, Jean Louis
    Dymanic software updating DSU consists in updating running programs on-the-fly without any downtime that leads to systems unavailability. The use of DSU in critical applications raises several issues related to update correctness. Indeed, an erroneous dynamic update may introduce safety vulnerabilities and security breaches. In this perspective, the use of formal methods has gained a large interest since they respond to the high need of rigor required by such applications. Several frameworks were developed to first express update correctness which is based on several criteria. Then, the proposed formalisms are used to specify DSU systems, express correctness criteria and establish them. In this paper, we present a review of researches on the application of formal methods to DSU systems. We give a classification of systems according to the paradigms of programming languages and then we explain the correctness criteria and categorise the articles regarding the approaches of formalisation to establish the correctness. This information is useful to help ongoing researches in having an overview on the application of formal methods in DSU
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    A new AOMDV lifetime prolonging routing algorithm for Ad-Hoc networks
    (IGI Global, 2019) Baddari, Ibtihel; Riahla, Mohamed Amine; Mezghiche, Mohamed
    Network lifetime is a key design metric in MANETs, it is considered as one of the most important parametersalgorithmstobeusedinadhocnetworks.Eachnetworknodeworkscompletely independently and acts as a router for relaying communications. If some nodes die prematurely because of battery depletion, the network lifetime will be adversely affected, and the network will get disconnected. This article presents AOMDV-LP, a new AOMDV lifetime-prolonging routing algorithm for MANETs. This new algorithm helps to maximize the network lifetime by managing nodesenergy,linkcostandcontrollingthenetworkscongestion.Simulationsquantifytheperformance gains of the authors algorithm
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    Hiding a fault enabled virus through code construction
    (2020) Hamadouche, Samiya; Lanet, Jean-Louis; Mezghiche, Mohamed
    Smart cards are very secure devices designed to execute applica-tions and store confidential data. Therefore, they become the target of manyhardware and software attacks that aim to bypass their embedded securitymechanisms in order to gain access to the sensitive stored data. Recently, anew kind of attacks called combined attacks has appeared. They aim to induceperturbations in the application’s execution environment. Thus, correct andlegitimate application can be dynamically modified to become a hostile one af-ter being loaded in the card using a fault injection. In this paper, we treat theproblem from another angle: how to design an innocent looking code in sucha way that it becomes intentionally hostile after being activated by a fault in-jection? We present an original approach of backward code construction basedon constraints satisfaction and a tree traversal algorithm. After that, we pro-pose a way to optimize the search process by introducing heuristics for a fasterconvergence towards more realistic solutions.We implement this approach inaTrace Generatortool; thereafter evaluate its capacity to generate the re-quired solutions while giving a proof-of-concept of the code desynchronizationtechnique
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    A cooperative approach based on local detection of similarities and discontinuities for brain MR images segmentation
    (2020) Bennai, Mohamed Tahar; Smaine, Mazouzi; Guessoum, Zahia; Mezghiche, Mohamed; Cormier, Stephane
    This paper introduces a new cooperative multi-agent approach for segmenting brain Magnetic Resonance Images (MRIs). MRIs are manually processed by human radiology experts for the identification of many diseases and the monitoring of their evolution. However, such a task is time-consuming and depends on expert decision, which can be affected by many factors. Therefore, various types of research were and are still conducted to automate MRI processing, mainly MRI segmentation. The approach presented in this paper, without any parametrization or prior knowledge, uses a set of situated agents, locally interacting to segment images according to two main phases: the detection of discontinuities and the detection of similarities. An implementation of this approach was tested on phantom brain MR images to assess the results and prove its efficiency. Experimental results ensure a minimum of 89% Dice coefficient with increasing values of the noise and the intensity non-uniformity
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    A stochastic multi-agent approach for medical-image segmentation: Application to tumor segmentation in brain MR images
    (ELSEVIER, 2020) Bennai, Mohamed Tahar; Guessoum, Zahia; Mazouzi, Smaine; Cormier, Stéphane; Mezghiche, Mohamed
    According to functional or anatomical modalities, medical imaging provides a visual representation of complex structures or activities in the human body. One of the most common processing methods applied to those images is segmentation, in which an image is divided into a set of regions of interest. Human anatomical complexity and medical image acquisition artifacts make segmentation of medical images very complex. Thus, several solutions have been proposed to automate image segmentation. However, most existing solutions use prior knowledge and/or require strong interaction with the user. In this paper, we propose a multi-agent approach for the segmentation of 3D medical images. This approach is based on a set of autonomous, interactive agents that use a modified region growing algorithm and cooperate to segment a 3D image. The first organization of agents allows region seed placement and region growing. In a second organization, agent interaction and collaboration allow segmentation refinement by merging the over-segmented regions. Experiments are conducted on magnetic resonance images of healthy and pathological brains. The obtained results are promising and demonstrate the efficiency of our method.