Ph.D., Computer Engineering (System Modeling and Analysis), Annaba/UCL University, Algeria/Belgium
Bs.c., Computer Engineering (System Modeling and Analysis), Annaba University, Algeria
Bachelor (Engineer), Computer Engineering, Annaba University, Algeria
Multi-Agents Testing, System Modeling and Analysis, Fault Detection and Isolation, Formal Methods, Petri nets Modeling and applications, Fuzzy logic Modeling and applications, Big Data.
- Houhamdi Z., Athamena B., & Al Refae, G.A., (2020). Managing Asymmetric Information Effects in Decision-Making Productivity-Based Model. International Journal of Knowledge and Systems Science (IJKSS), Vol. 11, No. 2, pp. 86-107.
- Houhamdi Z., Athamena B., Abuzaineddin, R., & Muhairat, M. (2019). A multi-agent system for course timetable generation. TEM Journal, Vol.8, No.1, pp.211-221.
- Houhamdi Z. & Athamena B. (2019). Impacts of information quality on decision-making. Global Business and Economics Review, Vol.21, No.1, pp.26-42.
- Athamena B. & Houhamdi Z. (2018). Model for decision-making process with big data. Journal of Theoretical and Applied Information Technology, Vol.96, No.17, pp.5951-5961.
- Athamena B. & Houhamdi Z. (2017). An Exception Management Model in Multi-Agents Systems. Journal of Computer Science, Vol.13, No.5, pp.140-152.
- Mazouz A. & Athamena B. (2016). Quality Management Process Optimization. International Business Management, Vol.10, No.28, pp.6462-6469.
- Houhamdi Z. & Athamena B. (2016). Data Freshness Evaluation in Data Integration Systems. International Journal of Economics and Business Research, Vol.11, No.2, pp.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, pp.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. Springer, Electrical Engineering, Vol.97, No.2, pp.129-138.
- Houhamdi Z. & Athamena B. (2015). Ontology-based Knowledge Management. International Journal of Engineering and Technology, Vol.7, No.1, pp.51-62.
- Houhamdi Z. & Athamena B. (2015). Information Quality Framework. Global Business & Economics Anthology, Vol.I, pp.181-19.
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.
Signal Processing and Automatic Control Laboratory, Annaba University, Algeria
Energetic Systems Modeling Laboratory, Biskra University, Algeria.
Published in: International Journal of Knowledge and Systems Science
Apr 01, 2020
Making the correct decision requires the possession of sufficient information regarding each alternative possible solution. Nevertheless, the investigation of all possible solutions to select the best alternative is complex and expensive. This article addresses the Principal-Agent problem, where the key feature is asymmetric information. Asymmetric information approaches the decision investigations in a business context, where one participant possesses more or better information than the second party. The authors consider the case where the principal is more knowledgeable than the agent. The article proposes a formal model for assessing agent competence based on his productivity and the principal assessment. The model output helps the agent to make the correct decision.
Jan 30, 2020
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 agents 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 agents competence. Accordingly, the mentor matches the task complexity perfectly with the agents 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 agents competence based on his productivity and the mentors appraisal and assists the agent in making the right decision.
Published in: TEM Journal
Mar 01, 2019
In the university, course scheduling and preparation for each semester can be defined as the process of determining what courses to offer, the number of sections needed for each course, assigning of a faculty member to teach each section, and allocating a timeslot and a classroom for each section to avoid clashes. The output of this activity (which is a timetable) affects every faculty member and student in various departments. This process is essentially broken down into three main stages: determining the courses to be offered as well as their section numbers, assigning faculty members to different sections, and scheduling of the sections into timeslots and classrooms.This paper investigates each of these steps and congregates them in a scheduling and Decision Support System (DSS). The DSS is used to make easy the process of course offerings by taking into consideration the students’ suggestions because the department resources are limited. The faculty member preferences are also considered in the assignment of sections for the sake of lessening disappointments in the department. Also, the couples (faculty, section) are planned into university timeslots based on faculty member preferences. Our proposed system considers student suggestions and preferences and the time availability of a faculty member since it minimizes disappointments and avoids conflicts between faculty members and classrooms and courses.
Published in: Global Business and Economics Review
Jan 01, 2019
Prior investigations have pointed out that an understanding of the impacts of information quality is essential to the organisation's success. Nevertheless, few investigations have analysed the impacts of information quality in a business context. This paper analyses the impacts of information quality on the decision-making process in a systematic way. To reach this goal, we suggest a pragmatic approach that allows estimation of information quality categories and dimensions. The results of the proposed approach indicate that intrinsic and contextual categories of information quality affect decision quality in a positive manner. On the other hand, decision quality is not necessarily influenced by representational category of the information quality. Additionally, the findings suggest that, contrary to consistency, increased information completeness and accuracy significantly improves the quality of the decision. Consequently, not all of the categories of information quality have the same effectiveness for the amelioration of decision quality.
Published in: Journal of Computer Science
Mar 01, 2017
Multi-Agents Systems (MAS) are modern approaches that need an additional investigation to improve their reliability and adaptability levels. Exception management is one way to reach this goal and this paper is dedicated to this specific subject. The purpose of this document is to examine the exception concept in MAS domain and to suggest a model adjusted to MAS challenges such as heterogeneity, openness and particularly agents' autonomy. Previous attempts in the agent's society have concluded set of findings that demonstrated the necessity of exception handling in MAS at the system level. The handling includes management and the needed processes related to management. The attainment up to now can be applied only to special MAS type. Usually, agents are non-autonomous and the system-level strategies need an impeccable cooperation between agents in the exception handling process. In our proposed model, the agent's ability to approach exceptions by itself is considered as a prerequisite to assure agent autonomy. Then, exception handling depends on agent-level processes to deal with the limitations of contemporary attainments and thus, they are complementary. Agent preserves the ability to independently decide when to activate exception handling and when to receive system-level help or believe in its skills.
Published in: International Journal of Economics and Business Research
Apr 01, 2016
The availability of data in different datasources increases highly the demand on accessing this data in a uniform and generalised way, especially in decision making applications which require an exhaustive investigation and examination of the data. The data quality represents an essential characteristic requested by the users, particularity with the arrival of the data integration systems (DIS) which integrate data from multiple datasources and present them to the users as single database. This paper discusses the data quality evaluation in DIS systems. Precisely, it addresses the issues of the quality evaluation of the data delivered to the end users as results to their queries and the verification of the achievement of users' quality expectations. Besides, it analyses how to improve the DIS systems by using quality scales and to enforce data quality. We propose to study one quality attribute, to analyse its effect in a DIS system, and to suggest methods for its assessment. Between the quality attributes that have been defined, this paper investigates the more significant one which is data freshness.
Published in: Global Business & Economics Anthology
Sep 01, 2015
This paper discusses a general, meaningful and repeated problem in information systems practice: under investment in the client information quality. Many organizations need precise financial models so as to initiate investments in their information systems and associated processes. Nevertheless, there are no broadly recognized strategies to accurately combining the expenses and profits of potential quality enhancement to client information. This can result in inadequate quality client information which influences the organizational goals. Further, the absence of such a strategy impedes the ability for Information System (IS) developers to discuss the investing case in betterments since the organizational resources access is dependent on such a case being made. To address this problem, we propose and assess a structure for generating financial models of the expenses and profits of client information quality. These models can be exploited to select and prioritize from various candidate interventions across multiple client processes and information resources, and to set up a business case for the society to make the investment. As the work tried to provide and evaluate an artifact instead of answer a question, design science was identified as the most suitable research approach. With design science, utility of a conceived artifact is precisely established as the goal rather than the theory truth. So instead of following a process of expressing and answering a sequence of research questions, design science develops by constructing and evaluating an artifact. In this case, the framework is built as an abstract artifact, incorporating models, measures and a method.
Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive
Published in: Electrical Engineering
Jun 01, 2015
A novel method based on a combination of the extended Kalman filter with particle swarm optimization (PSO) to estimate the speed and rotor flux of an induction motor drive is presented. The proposed method will be performed in two steps. As a first step, the covariance matrices of state noise and measurement noise will be optimized in an off-line manner by the PSO algorithm. As a second step, the optimal values of the above covariance matrices are injected in our speed–rotor flux estimation loop (on-line). Computer simulations of the speed and rotor flux estimation have been performed to investigate the effectiveness of the proposed method. Simulations and comparison with genetic algorithms show that the results are very encouraging and achieve good performances.
Published in: Modern Applied Science
Mar 01, 2012
In Multi-Agent System (MAS), developers concentrate on creating design models and evolving them, from higher level models to lower level models, in several steps. Considerable part of MAS implementations is automatically produced from the design models. If a design model contains faults, they are passed to the generated implementations. Practical model validation techniques are required to discover and delete faults in abstract design models. In this paper, we introduce a formal approach for MAS design testing. It specifies a testing process that complements Multi-agent Systems Engineering (MaSE) methodology and strengthens the mutual relationship between UML and MAS. Besides, it defines a structured and comprehensive testing process for engineering software agents at the design level by providing a systematic way of converting the MAS design models to UML design diagram. Then a Petri Net (PN) diagram is generated from the UML models to simulate the behavior of the MAS system. Finally, because Petri Nets (PNs) are formal models, their analysis techniques can be applied to automatic MAS behavioral testing.
Published in: Computer and Information Science
Jan 01, 2012
In recent years, Agent-Oriented Software Engineering (AOSE) methodologies are proposed to develop complex distributed systems based upon the agent paradigm. The implementation for such systems has usually the form of Multi-Agent Systems (MAS). Testing of MAS is a challenging task because these systems are often programmed to be autonomous and deliberative, and they operate in an open world, which requires context awareness. In this paper, we introduce a novel approach for goal-oriented software acceptance testing. It specifies a testing process that complements the goal oriented methodology Tropos and strengthens the mutual relationship between goal analysis and testing. Furthermore, it defines a structured and comprehensive acceptance testing process for engineering software agents by providing a systematic way of deriving test cases from goal analysis.
Published in: Journal of Computer Science
May 01, 2011
Problem statement: In recent years, Agent-Oriented Software Engineering (AOSE) methodologies are proposed to develop complex distributed systems based upon the agent paradigm. The implementation for such systems has usually the form of Multi-Agent Systems (MAS). Testing of MAS is a challenging task because these systems are often programmed to be autonomous and deliberative and they operate in an open world, which requires context awareness. Approach: We introduce a novel approach for goal-oriented software integration testing. It specifies an integration testing process that complements the goal oriented methodology Tropos and strengthens the mutual relationship between goal analysis and testing. Results: The derived test suites from the system goals can be used to observe emergent properties resulting from agent interactions and make sure that a group of agents and contextual resources work correctly together. Conclusion: This approach defines a structured and comprehensive integration test suite derivation process for engineering software agents by providing a systematic way of deriving test cases from goal analysis.
Apr 01, 2011
In recent years, Agent-Oriented Software Engineering (AOSE) methodologies are proposed to develop complex distributed systems based upon the agent paradigm. The implementation for such systems has usually the form of Multi-Agent Systems (MAS). MAS’testing is a challenging task because these systems are often programmed to be autonomous and deliberative, and they operate in an open world, which requires context awareness. In this paper, we introduce a novel approach for goal-oriented software system testing. It specifies a testing process that complements the goal oriented methodology Tropos and reinforces the mutual relationship between goal analysis and testing. Furthermore, it defines a structured and comprehensive system test suite derivation process for engineering software agents by providing a systematic way of deriving test cases from goal analysis.
Published in: Journal of Theoretical & Applied Information Technology
Feb 15, 2011
Abstract The Graphical User Interfaces (GUIs) of software products are extensively used by researchers and practitioners in Software Engineering field. For Example, they are used for testing, measuring usability, and many other purposes. This paper describes a new reverse engineering approach to transform the GUI into class diagram. However, the correctness of such transformation process is essential for the corrected execution of the overall software. To assure this correctness, the interpreted Petri nets models will be implemented on the proposed transformation processes (ie capturing, normalization, and translation processes).
Fault detection and isolation in dynamic systems using statistical local approach and hybrid least squares algorithm
Published in: American Journal of Applied Sciences
Dec 01, 2007
A fault detection and isolation (FDI) scheme for dynamic system proposed. This study deals with the design of discrete-time linear system using delta operator approach and the hybrid least squares (HLS) algorithm. A third residual generation based on statistical local approach and the derivative of the normalized residual on a small temporal window investigated. This new technique meets the desired FDI performance specifications by increasing the faults magnitude and decreasing the noise effects. Some simulation results were provided to evaluate the design.
Published in: Informatica
Feb 11, 2002
Fault diagnosis has become an issue of primary importance in modern process automation as it provides the prerequisites for the task of fault detection. The ability to detect the faults is essential to improve reliability and security of a complex control system. When a physical parameter change due to failure has occurred in a system, the failure effect will hardly be visible in the output performance. Since the failure, effect is reflected as a change in the predictor model. In this paper we describe a completed feasibility study demonstrating the merit of employing hybrid parameter-estimation and fuzzy logic for fault diagnosis. In this scheme, the residual generation is obtained from input-output data process, and identification technique based on ARX model, and the residual evaluation is based on fuzzy logic adaptive threshold method. The proposed fault detection and isolation tool has been tested on a magnetic levitation vehicle system.