Boulbaba Ben Ammar

Boulbaba Ben Ammar
University of Sfax | US · Department of Computer Science and Communication

Doctor of Philosophy
Assistant Professor

About

16
Publications
3,777
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51
Citations

Publications

Publications (16)
Article
Full-text available
Nowadays, the appearance of common symptoms, such as cough, fever, and loss of smell and taste, is the starting point of a battle against the coronavirus. The first standard method of COVID-19 infection assertion has become the RT-PCR test, which is however an uncomfortable solution for both patients and medical staff due to its high cost, timeline...
Article
Fraud can take on various forms, including financial fraud, identity theft, and insurance fraud, among others. With the growing use of technology, fraudulent activities have become more sophisticated, making it difficult for organizations to detect and prevent them. One major challenge in the insurance industry is vehicle insurance fraud, which lea...
Conference Paper
Full-text available
Financial businesses have a significant challenge with credit card fraud. Approximately more than one million individuals from different countries are losing money yearly due to credit card fraud. Due to privacy concerns, there is an absence of research studies that can be conducted on the analysis of real credit card data. In this study, various d...
Article
Full-text available
Fraud can take on various forms, including financial fraud, identity theft, and insurance fraud, among others. With the growing use of technology, fraudulent activities have become more sophisticated, making it difficult for organizations to detect and prevent them. One major challenge in the insurance industry is vehicle insurance fraud, which lea...
Article
Full-text available
In the context of machine learning, an imbalanced classification problem states to a dataset in which the classes are not evenly distributed. This problem commonly occurs when attempting to classify data in which the distribution of labels or classes is not uniform. Using resampling methods to accumulate samples or entries from the minority class o...
Article
In the context of machine learning, an imbalanced classification problem states to a dataset in which the classes are not evenly distributed. This problem commonly occurs when attempting to classify data in which the distribution of labels or classes is not uniform. Using resampling methods to accumulate samples or entries from the minority class o...
Chapter
The fast spread of Covid-19 or the novel Coronavirus in the world has influenced it and caused a huge number of deaths. This remains a disastrous warning to general wellbeing and will be set apart as probably the most dangerous pandemic in world history and one of the important health challenges that the world has ever faced. The public health poli...
Article
Full-text available
Refactoring is an important software development process involving the restructuring of a model to improve its internal qualities without changing its external behavior. In this paper, we propose a new approach of model refactoring based on the combined use of UML, B and CSP. UML models are described by class diagrams, OCL constraints, and state ma...
Article
Full-text available
This paper gives the definition of Transparent Neural Network "TNN" for the simulation of the globallocal vision and its application to the segmentation of administrative document image. We have developed and have adapted a recognition method which models the contextual effects reported from studies in experimental psychology. Then, we evaluated an...
Article
Full-text available
This paper gives the definition of Transparent Neural Network “TNN” for the simulation of the global-local vision and its application to the segmentation of administrative document image. We have developed and have adapted a recognition method which models the contextual effects reported from studies in experimental psychology. Then, we evaluated a...
Article
Full-text available
Specifying complex systems is a difficult task which cannot be done in one step. In the framework of formal methods, the refinement is a key feature to incrementally develop more and more detailed models, preserving correctness in each step. The refactoring activity consists in restructuring a model in order to improve its quality, preserving the c...
Article
In an incremental specification development process, operations are used to model dynamic aspects and can be refined gradually. We propose four kinds of operation refinement in order to control modifications when developing and refactoring UML specifications. Each refinement is described with its properties and illustrated by an example, showing wh...
Article
La specification de systemes complexes est une tâche difficile qui ne peut etre accomplie en une seule etape. Dans les methodes formelles, le concept de raffinement a donne lieu a de nombreux travaux dans lesquels la preuve de la correction entre les differents etats de specifications joue un role important. Nous proposons d'utiliser le raffinement...
Article
Full-text available
L'activité de refactoring consiste à restructurer un modèle en vue d'améliorer certains facteurs de qualité, tout en préservant la cohérence de ce modèle. Dans cet article, nous proposons un schéma de refactoring de diagrammes de classes basé sur la notion de délégation. L'idée consiste à redistribuer le contenu d'une classe d'un diagramme de class...
Article
Full-text available
Le concept de raffinement est un élément clé dans les approches formelles pour le développement de logiciels et a donné lieu à de nombreux travaux dans lesquels la preuve de la correction entre les différents états de spécifications joue un rôle important. Nous proposons un cadre formel de définition des patrons de raffinement de diagrammes de clas...
Article
Full-text available
Specifying complex systems is a difficult task which cannot be done in one step. Step-by-step development processes have been studied using formal methods, based on refinement mechanisms. The refinement is a key feature for incrementally developing more and more detailed models, preserving correctness in each step. Our purpose is to instantiate thi...

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