Academic advising is limited in its ability to assist students in identifying academic pathways. Selecting a major and a university is a challenging process rife with anxiety. Students at high school are not sure how to match their interests with their working future or major. Therefore, high school students need guidance and support. Moreover, students need to filter, prioritize and efficiently get appropriate information from the web in order to solve the problem of information overload. This paper represents an approach for developing ontology-based recommender system improved with machine learning techniques to orient students in higher education. The proposed recommender system is an assessment tool for students' vocational strengths and weaknesses, interests and capabilities. The main objective of our ontology-based recommender system is to identify the student requirements, interests, preferences and capabilities to recommend the appropriate major and university for each one.

This paper presents SpCLUST, a new C++ package that takes a list of sequences as input, aligns them with MUSCLE, computes their similarity matrix in parallel and then performs the clustering. SpCLUST extends a previously released software by integrating additional scoring matrices which enables it to cover the clustering of amino-acid sequences. The similarity matrix is now computed in parallel according to the master/slave distributed architecture, using MPI. Performance analysis, realized on two real datasets of 100 nucleotide sequences and 1049 amino-acids ones, show that the resulting library substantially outperforms the original Python package. The proposed package was also intensively evaluated on simulated and real genomic and protein data sets. The clustering results were compared to the most known traditional tools, such as UCLUST, CD-HIT and DNACLUST. The comparison showed that SpCLUST outperforms the other tools when clustering divergent sequences, and contrary to the others, it does not require any user intervention or prior knowledge about the input sequences.

No abstract

Network security policy enforcement consists in configuring heterogeneous security mechanisms (IPsec gateways, ACLs on routers, stateful firewalls, proxies, etc) that are available in a given network environment. The complexity of this task resides in the number, the nature, and the interdependence of the mechanisms to consider. Although several researchers have proposed different analysis tools, achieving this task requires experienced and proficient security administrators who can handle all these parameters today. We propose in the article a mathematical data flow oriented modelling approach in order to detect inconsistencies between security mechanisms. Our model is independent from specific security mechanisms to admit of their diversity, and also future security mechanisms not yet available. In addition, it allows fine-grained inconsistency analysis.Résumé-La mise en oeuvre de politique de sécurité réseau consiste en la configuration de mécanismes de sécurité hétérogènes (passerelles IPsec, liste de contrôle d'accès sur les routeurs, pare-feu à états, proxy, etc) disponibles dans un environnement réseau donné. La complexité de cette tâche réside dans le nombre, la nature, l'interdépendance des mécanismes à considérer. Si différents travaux de recherche ont tenté de fournir des outils d'analyse, la réalisation de cette tâche repose aujourd'hui encore sur l'expérience et la connaissance des administrateurs sécurité qui doivent maîtriser tous ces paramètres. Nous proposons dans cet article une approche de modélisation mathématique orientée flux de données dont l'objectif est de détecter les problèmes de consistance entre mécanismes de sécurité. Ce modèle est indépendant des mécanismes de sécurité pour prendre en compte leur diversité ainsi que l'évolution future, mais il permet aussi une analyse fine des problèmes de consistance.

Abstract-Business Artifacts, as an alternative approach to Business Process Modeling, combines both process and data aspects of a Business into the same model. Many works in the literature have focused on defining Artifactcentric processes and graphical modeling notations. But, to the best of our knowledge, no prior work has directly tackled the problem of generating Database Schemas from Business Artifact Models. In this paper, we propose an algorithm that generates Database Schemas from Business Artifact Models (BAMs). The proposed algorithm not only takes into consideration the different data attribute types of Artifacts' Information Models, but also supports different Artifacts relationships. We also validate our work with a prototype implementation of a Business Artifact Models Modeler and a Database Schema Generator.

Academic advising is inhibited at most of the high schools to help students identify appropriate academic pathways. The choice of a career domain is significantly influenced by the complexity of life and the volatility of the labor market. Thus, high school students feel confused during the shift period from high school to university, especially with the enormous amounts of data available on the Web. In this paper, an extensive comparative study is conducted to investigate five approaches of recommender systems for university study field and career domain guidance. A novel ontology is constructed to include all the needed information for this purpose. The developed approaches considered user-based and item-based collaborative filtering, demographic-based recommendation, knowledge base supported by case-based reasoning, ontology, as well as different hybridizations of them. A case study on Lebanese high school students is analyzed to evaluate the effectiveness and efficiency of the implemented approaches. The experimental results indicate that the knowledge-based hybrid recommender system, combined with the user-based collaborative filtering and braced with case-based reasoning as well as ontology, generated 98% of similar cases, 95% of them are personalized based on the interests of the high school students. The average usefulness feedback and satisfaction level of the students concerning this proposed hybrid approach reached 95% and 92.5% respectively, which could be a solution to similar problems, regardless of the application domain. Besides, the constructed ontology could be reused in other systems in the educational domain.

No abstract

No abstract