Category of Study: Multimedia & Semantic Video, Semantic Web, Mobile  Learning, Distributed Computing

Email:  rbenlamri@lakeheadu.ca

Fax: (807) 766-7243

Personal Homepage

General Information:
Rachid Benlamri is an Associate Professor in the Department of Software Engineering at Lakehead University. He graduated in 1985 with a B.Eng. in Computer Engineering from the University of Constantine - Algeria. He was then awarded a Master of Science and a PhD in Computer Science from the University of Manchester - UK in 1987 and 1990 respectively. His research interests are in the areas of Multimedia & Semantic Video, Semantic Web, Mobile Learning, and Distributed Computing.

Research Areas:
My research interests are in the field of Semantic Web, Mobile Learning, Multimedia & Semantic Video, and Distibuted Computing. I am currently working on the following projects:

Semantic Video Analysis for Human Motion Understanding
Semantic video analysis for human motion capture and understanding continues to be an increasingly active research area in computer vision. Significant progress has been made in areas such as automatic initialization, tracking, pose estimation, automatic understanding of human actions and behavior. This project investigates novel methods for inferring the pose and motion of a highly articulated and self-occluding non-rigid 3D object from video. From an application perspective such approaches can be applied to surveillance, control, and analysis.

Ontology Based Framework for Context-Aware Mobile Learning (NSERC Funded Project)
The semantic web has the potential to revolutionize the ways learning resources available on the web are discovered, adapted, and delivered according to context. In this project we are developing a proactive context aware mobile learning system on the semantic web. This is based on a global ontology model for user context and domain applications to enable reasoning with the various contextual elements. The aim is to dynamically build context-aware personalized learning services. The contextual information used in the personalization process encompasses all elements that characterize the interactions between the learner, the system, and the surrounding environment. These include learner, device, environment, and activity contexts.

Time Dependent Knowledge Management for Corporate Learning
Time-dependent personalized instruction is important for corporate learning providers in order to make it possible for organizations to transform learning into a strategic lever. The ability to grasp the exact knowledge required to accomplish a specific task, in a limited allotted time, is a key factor for organizations to remain economically competitive in the new knowledge society. However, time-constrained learning is not easy to achieve especially if the learning material is not structured in a way that satisfies the requirements of learners with multi-level cognitive skills. This challenging aspect is dealt with in this project by proposing ontological structures which model learning domains in such a way that ontology-reasoning mechanisms are capable of mapping concepts to learning resources at different granularity levels, hence customizing the material in a cost-efficient and timely manner. The framework being developed produces knowledge that meets the immediate needs of learners using a judicious application of real-time software development principles.

Current Students:
Ph.D.

• Abdunaser Diaf : Semantic Video Analysis for Human Motion Understanding

MASc.

• Xiaoyun Zhang: Semantic Web Technologies for Personalized Mobile Learning
• Luke Docksteader: Context Sensing and Management for e-learning
• Kristopher Scott: Context-Awareness in Ubiquitous Computing
• Aminul Islam: Web-Services for Mobile Learning

Courses Taught:
I taught many courses in the area of Computer Science, Computer Engineering, Software Engineering, and Information Technology. In the past few years, I taught the following courses.

Undergraduate Courses:
Computer Logic Circuits
Data Management and Information Systems
Software Design and Testing
Performance Analysis of Software
Data Structures and Algorithms
Programming Paradigms
Introduction to Software Engineering
Advanced Software Engineering

Graduate Courses:
Semantic Web and Ubiquitous Computing
Web Engineering
Image Processing
Computer Network Infrastructures
Information Systems and Organizational Strategy

Recent Publications (Journal Papers and Book Chapters)
R. Benlamri, Y. Atif, and J. Berri, “An Ontology-based Approach for Context-aware Mobile Learning”, Advances in Ubiquitous Computing: Future Paradigms and Directions, IGI Global Ed., pp.23-44, 2008.

R. Benlamri, H. Barada, and A. Al-Raqabani, “Analysis of Coordinated Load Sharing For Large Distributed Systems, Vol.30, No.2, Acta Press Ed., 2008.

M Sabah, A. Orabi, J. Fiaidhi, M. Orabi and R. Benlamri, “Developing a Web 2.0 Telemedical Education System: The AJAX-Cocoon Portal”, (in Press) Int. Journal of Electronic Healthcare, 2008.

E. Basaeed, J. Berri, J. Zemerly, R. Benlamri, “ Web-based Context-Aware m-Learning Architecture”, Int. Journal of Interactive Mobile Technologies, Vol.1, No.1, pp.5-10, 2007.

E. Basaeed, J. Berri, J. Zemerly, R. Benlamri. “Learner-Centric Context-Aware Mobile Learning”, IEEE Multidisciplinary Engineering Education Magazine, 2(2), pp.30-33, June 2007.

R. Benlamri, J. Berri and Y. Atif, “A Framework for Ontology-aware Instructional Design and Planning”, Journal of E-Learning and Knowledge Society, 2(1), 83-96, 2006.

R. Benlamri and Y. Al-Marzooqi, “Free-form object segmentation and representation from registered range and color images”, Image and Vision Computing, 22(9), 703-717, 2004.

Y. Attif, R. Benlamri and J. Berri, “Dynamic Learning Modeler”, IEEE/IFETS Journal of Educational Technology and Society, Special issue on Electronic Content for Education, 6(4), 60-72, 2003.

Y. Attif, R. Benlamri and J. Berri, “Learning Objects Based Framework for Self-Adaptive Learning”, Journal of Education and Information Technologies, 8(4), 345-368, 2003.

R. Benlamri, " Parallelizing Infinite Impulse Response Filters", in Advances in Information Science and Soft Computing, WSEAS Press, 248-253, 2002.

R. Benlamri, "Range Image Segmentation of Scenes with Occluded-Curved Objects", Pattern Recognition Letters, 21(2), 1050-1061, 2000.

R. Benlamri, M. Batouche, S. Rami and C. Bouanaka, "An Automated System for Interpretation and Analysis of Epileptiform Activity in the EEG", Computers in Biology and Medicine, Vol. 27, No.2, pp.129-139, 1997.

M. Batouche, R. Benlamri and M.K. Kholladi, "A Computer Vision System for Diagnosing Scoliosis Using Moiré Images", Computers in Biology and Medicine, Vol. 26, No.4, pp.339-353, 1996.