د. بلقاسم عثامنة

مدير برنامج إدارة الأعمال

مقر العين

+971 3 7024808

BusinessAdministration@aau.ac.ae

التعليم

نظم المعلومات الادارية ، جامعة عنابة، الجزائر

Master, System Modeling and Analysis, Annaba University, Algeria

Bachelor (Engineer), Computer Engineering, Annaba University, Algeria

الاهتمامات البحثية

Multi-Agents Testing, System and Software Modeling and Analysis, System and Software Verification, Validation and Testing, Fault Detection and Isolation, Formal Methods, Petri nets Modeling and applications, Fuzzy logic Modeling and applications, Ontology in Multi-Agent

منشورات مختارة

  • Houhamdi Z. & Athamena B., (2020). Identity Identification and Management in the Internet of Things. International Arab Journal of Information Technology, 17(4A), 645-654.
  • Houhamdi, Z., Athamena, B., & El Refae, G. (2020). Managing Asymmetric Information Effects in Decision-Making Productivity-Based Model. International Journal of Knowledge and Systems Science (IJKSS)11(2), 86-107.
  • Houhamdi, Z., Athamena, B., Abuzaineddin, R., & Muhairat, M. (2019). A Multi-Agent System for Course Timetable Generation. TEM Journal8(1), 211.
  • Houhamdi, Z., & Athamena, B. (2019). Impacts of information quality on decision-making. Global Business and Economics Review21(1), 26-42.
  • ATHAMENA, B., & HOUHAMDI, Z. (2018). Model for Decision-Making Process with Big Data. Journal of Theoretical & Applied Information Technology96(17).
  • Athamena B. & Houhamdi Z. (2017). An Exception Management Model in Multi-Agents Systems. Journal of Computer Science, 13(5), 140-152.
  • Mazouz A. & Athamena B. (2016). Quality Management Process Optimization. International Business Management, 10(28), 6462-6469.
  • Houhamdi, Z., & Athamena, B. (2016). Data freshness evaluation in data integration systems. International Journal of Economics and Business Research11(2), 132-144.
  • Athamena B. & Houhamdi Z. (2015). A Distributed Approach for Monitoring and Diagnosis of Multi-Agent Plan. IEEE - SAI Intelligent Systems Conference (IntelliSys), November 10-11, 2015, London, UK, 863-870.
  • Laamari, Y., Chafaa, K., & Athamena, B. (2015). Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive. Electrical Engineering97(2), 129-138.
  • Houhamdi Z. & Athamena B. (2015). Ontology-based Knowledge Management. International Journal of Engineering and Technology, 7(1), 51-62.
  • Houhamdi Z. & Athamena B. (2015). Information Quality Framework. Global Business & Economics Anthology, I, 181-19.

المواد التدريسية

Undergraduate: Database Management Systems, Project Management, Business System Analysis and Applications, Mathematics for Business, Business Data Communication, E-Commerce, Quality Management, Production and Operations Management, Introduction to Programming Languages, Introduction to Software Engineering, Human-Computer Interaction, Software Modeling and Analysis.
Graduate: System Analysis and Design, System/Software Verification, Validation and Testing, System Modeling using Fuzzy logic and neural network.

العضويات

Signal Processing and Automatic Control Laboratory, Annaba University, Algeria
Energetic Systems Modeling Laboratory, Biskra University, Algeria.

Article

Managing asymmetric information effects in decision making: Task complexity-based model

أكتوبر 01, 2020

/ Belkacem Athamena / zina houhamdi / Ghaleb El Refae

This paper proposes a formal model to manage the impact of asymmetric information in decision-making by using principal-agent problems in which an agent (who has incomplete information) must decide to perform or not perform a task on behalf of the principal. After performing a complex (simple) task, the agent underrates (overrates) his competence. As a consequence of underestimation, a competent agent may decide to stop performing the task henceforth. The agent infers his competence from his productivity on a performed task. However, the productivity depends on both the agent's competence and the task complexity. To avoid this situation, the company appoints a mentor (fully informed superior agent) who can determine the task complexity and assess the agent's competence. Accordingly, the mentor matches the task complexity perfectly with the agent's competence. In cases where the mentor and the junior have different preferences, the mentor may not confess all information to the agent. Nevertheless, the mentor desires the agent to fulfill the task. This paper proposes a solution for all of these situations by using a mathematical model. The model assesses the agent's competence based on his productivity and the mentor's appraisal and assists the agent in making the right decision.


Article

Identity Identification and Management in the Internet of Things

أغسطس 01, 2020

/ zina houhamdi / Belkacem Athamena

Henceforth, users agreed on the necessity of continuous Internet connection independently of the place, the manner, and the time. Nowadays, several elite services are accessible by people over the Internet of Things (IoT), which is a heterogeneous network defined by machine-to-machine communication. Despite the fact that the devices are used to establish the communication, the users can be considered as the actual producers of input data and consumers of the output data. Consequently, the users should be viewed as a smart object in IoT; therefore, user identification, authentication, authorization are required. However, the user identification process is too complicated because the users are worried to share their confidential and private data. on the other hand, this private data should be used by some of their devices. Accordingly, an equitable mechanism to identify users and manage their identities is necessary. In addition, the user plays an extreme important role in the establishment of rules needed for identity identification and in ensuring the continuity of receptive services.The main purpose of this paper is to develop a new framework for Identity Management System (IdMS) for IoT. The primary contributions of this paper are: the proposition of a device recognition algorithm for user identification, the proposition of a new format for the identifier, and a theoretical framework for IdMS.