The 4th  Workshop on

  Ubiquitous Computing and Emerging Intelligent Multimedia Paradigms  

A Part of the Winter seminar series at FCI

(One day invited speakers)

Cairo, Egypt, Dec. 15,  2007

Organized by:

Egyptian Rough Sets Working Group


Faculty of Computer and Information, Cairo University



Professor Dr. Jemal Hussien Abbawajy


Deakin University

School of Engineering and Information Technology

Geelong, VIC, 3072, AUSTRALIA

Title : Secure Negotiation Framework in Inter Grid Environments


Grid computing enables the creation of Cyber-infrastructure for e-Research applications. It is recognized as one of the top five emerging technologies that will have a major impact on the quality of science and society over the next 20 years. Support for complex multi-attribute business negotiations is a critical success factor for the next generation of Grid computing. In this talk, I will discuss an approach based on mobile-agent for secure electronic negotiation in InterGrid environments.



Dr. Jemal Hussien Abbawajy is a faculty member and the deputy leader  of the IT Security stream at Deakin University, Australia.  He is currently directing the Pervasive Computing & Networks and the  Wireless Sensor Networks research groups as well as serving as the  principal supervisor of 5 PhD and co-supervisor of 3 PhD students. He  has published more than 100 articles in refereed journals and  conferences. Dr. Abawajy is on the editorial board of several  international journals and edited several special international  journals and conference proceedings. Dr. Abbawajy has given many  keynote and invited talks nad he has been a member of the organizing  committee for over 60 international conferences and workshops serving  in various capacity including best paper award chair, general  co-chair, publication chair, vice-chair and program committee. He is a  frequent reviewer for international research Journals, research grant  applications (e.g., Australian Research Council) and PhD and Masters  Degree examinations.


Dr. Mrs. P. P. Rege

Professor and Dean (Student Affairs)
Dept. of Electronics and Telecommunication
College of Engineering
(An Autonomous Institute of Govt. of Maharashtra)

Title: Recent trends in image analysis

With the advent of Internet and digital communication, the area of Digital Image Processing and analysis has emerged as a subject of interdisciplinary study and research in Physics, Chemistry, Biology, Engineering, Meteorology, Space Science and of course Computer Science. Two Dimensional and three dimensional image processing today forms a major area of research and development in the broad fields of pattern recognition, computer vision, machine learning and also artificial Intelligence. Main aim of the talk is to cover few applications of image
processing like Digital watermarking, Texture Analysis, and Document Analysis. Digital data hiding has received increasing attention from the information technology community. The talk would cover many aspects that are common to any data hiding system.  Data hiding in general, is an immature field, and that more effective solutions will be developed in the years to come.
Image segmentation finds many applications in Industry and Biomedical field. Texture Analysis is one of the methods for segmentation that enables us to classify various regions based on the texture contents of the object. There is an increasing need to digitally preserve and provide access to historical document collections residing (and possibly decaying) in libraries, museums and archives. To facilitate future automatic searching and analysis of the words and content in the documents, it is necessary to separate the useful pixels containing document content, such as handwriting, drawings, pictures and other information representing useful artifacts, from the background pixels of the paper. Document analysis is the process that performs the overall interpretation of document images. Efforts will be to represents a good description of the state of the art in these fields, and a good starting point for future research as well as for the development of practical applications."


Priti Rege received her B.E (Bachelor in Engineering) with distinction in 1983 and M.E degree with Gold medal in 1985, both from Devi Ahilya University of Indore, India. She received her doctoral degree from the Pune University, India in 2002. She is a Professor at College of Engineering, Pune. Currently, she is also working as Dean, Students affairs at the same Institute. She has authored/coauthored over 45 research publications in peer-reviewed journals and conference proceedings. She has worked on advisory committee/ program committee of various conferences and also as a reviewer for various journals.  She has also worked as chairperson at various sessions in National and International conferences. She is a Senior Member of IEEE, Life member of Institution of Electronics and Telecommunication Engineers, India, Life member and Convener of Biomedical Engineer’s Society of India. She has edited “Trends in Process Instrumentation and control”, proceedings of International Conference on Instrumentation INCON 2005. Her research interests include, Digital Watermarking, Texture Analysis, Optical character Recognition, Document enhancement and 3-D volume rendering. She has contributed in research projects funded by Government and Industries and has also received fellowship for carrying out research in the field of image processing.


Supra Topological Approach for Decision Making via Granular Computing



Dr. Tamer Medhat Mohammad Ibrahim

 (T. Medhat)




Granular computing is a valid way to describe problem spaces or solve problems. It enables us to perceive the real world under various grain sizes, obtain only those useful or interesting things at different granularities, and switch among different granularities to get various levels of knowledge. The basic ideas of granular computing have already been explored in many fields, such as soft computing, knowledge discovery, machine learning, and web intelligence. At present, there are several major research results shown as follows. The topic of fuzzy information granulation was first proposed by Professor L.A. Zadeh. Based on fuzzy set theory, he proposed a general framework of granular computing. Granules are constructed and defined based on the concept of equivalence, probability and fuzzy relationship. Relationships between granules are represented in terms of fuzzy graphs or fuzzy if-then rules. Its computation method is computing with words. Rough set theory proposed by Professor Z. Pawlak in 1982 has been applied to many fields. It is a valid mathematical method to deal with imprecise, uncertain, and vague information, As a concrete theory of granular computing,  rough set theory enables us to precisely define and analyze many notions of granular computing.  Professors Y.Y. Yao and Q. Liu study the partition model and logical reasoning based on granular computing. Construction of granules and representation of their relationships are described in terms of the decision logic language. Professor T.Y. Lin has done a lot of work in granular computing and its applications, including granular computing on binary relations in data mining and neighborhood systems. Some basic ideas of granular computing have been successfully explored in image processing and machine learning in his work.

Professors L. Zhang and B. Zhang developed the quotient space theory in 1992. It is a novel theory of granular computing. Granules are constructed and defined by collection, and relationships between granules are represented in terms of collection calculation. An important property of quotient space theory is the "false preserving" property. It means that there will be no solution in the original fine-grained space if there is no solution in a coarse-grained space. The quotient space theory has been applied in wave analyzing and bioinformation processing. Although there are differences among these theories of granular computing in their formulation, i.e., construction of granules and representation of their relationships, their core idea is the same. That is, a problem space is firstly divided into some basic granules. Then, these basic granules are further composed or decomposed into new granules at different hierarchies. The above two steps are repeated until these new granules could solve the problem more valid. Since each theory has its advantages of solving the problem in some field, it is very important to take advantages of each theory to solve the problem in a more efficient way.  We use granular computing for converting the complicated information systems into simple ones. The topological approximation space which we used in our presentation is used for decision making as reduction of superfluous attributes and determining the upper approximation and lower approximation. This space is a generalization of Pawlak's space and preferred than Yao's space by increasing the lower approximation, decreasing the upper approximation, and so decreasing the boundary region.  Also it is used for reduction in general binary relations, By making the reduction of information system values we get the minimal information table. Also, by converting any MVIS "multi-valued information system" to SVIS "single valued information system", we can deal with all programs of the equivalence relations. By calculating the degree of dependency and taking the value of error ratio, we can eliminate some of attributes with some approximation that we can't eliminate any of them using the classical rough set techniques.


Tamer Medhat received his B.Eng. "Electronic Computer and Automatic Control" in 1998 from Tanta University, Faculty of Engineering, Tanta, Egypt. M.Sc. degree "Engineering Mathematics" in 2004, and PhD degree "Engineering mathematics" in 2007, both from Tanta University, Faculty of Engineering,   Physics and Engineering Mathematics Department. Tanta, Egypt. Currently, he is a lecturer of engineering mathematics at Kafr Elsheikh University, Faculty of Engineering, Physics and Engineering Mathematics Department. He has authored/coauthored over 10 research publications in peer-reviewed reputed journals and conference proceedings. He has served as reviewer for some international journals. Dr. T. Medhat was a member of the International Rough Set Society.  Also, he was a member of the Egyptian Rough Set Group ERSG. His research interests include, rough set theory, general topology, fuzzy set theory, neural network, artificial intelligent, engineering mathematics and its applications.


  DSRC: Towards Autonomous Vehicular Communications


 Dr. Y. L. Morgan

Faculty, of Engineering, Regina University, Canada

The Dedicated Short-Range Communications (DSRC) is a new wireless communication suite that is designed specifically for street and vehicular communications. DSRC is built as a tweak of the classical WiFi in order to provide solid communications at the street level for both vehicle-to-vehicle and vehicle-to-roadside. DSRC has built-in mechanisms for delivering public safety messages and facilitates safer and richer driving experience. Over and above,  DSRC helps improving infrastructure utilization and maintenance. DSRC is capable of delivering 27 Mbps data-rate over 5.9 GHz by using a two way line-of-sight short-range radio which is significantly lower cost compared to cellular, WiMax or satellite communications.  Some of the typical DSRC applications are listed below:

•       Emergency warning system for vehicles

•       Approaching emergency vehicle warning (Blue Waves)

•       Vehicle safety inspection

•       Transit or emergency vehicle signal priority

•       Probe data collection

•       Highway-rail intersection warning

•       Public transport monitor


Dr. Y. L. Morgan received his Ph.D. from Carleton University and is currently an Assistant Professor in University of Regina. Dr. Morgan is focused on research related to mobile vehicular communications and in specific the development of ITS infrastructure like DSRC and VII initiatives. Dr. Morgan has been part of the IEEE 802.11p standards group and the IEEE 1609.0/.1/.2/.3/.4/.5 groups as well. Dr. Morgan has authored and co-authored more than twenty research papers including contributions to standards like IEEE, IEEE-SA, IETF, and 3GPP. Dr. Morgan is also an active member and reviewer in the VTC and the VTS societies that are focused on vehicular transportation systems and applications. The objective of Dr. Morgan research is to develop real-time effective and secure communications between vehicles and between vehicles and roadside. This communication must be geared towards enhancing transportation safety and quality while leaving room for commercial aspects. Currently, Dr. Morgan is one of a group of researchers pioneering the ONE-ITS initiative.



Resource-Adaptive Data Stream Processing

Dr. Mohamed Medhat Gaber

CSIRO, Australia

The need for traditional data processing techniques had become increasingly important with the evolution in databases and data warehousing technologies. These

data repositories have grown in size with the wide deployment of such technologies.  Scalability had been a major research challenge in this area. Large data repositories

have been queried and analysed/mined for knowledge for business value and scientific discovery. Advances in both hardware and software technologies have led to

fast data generation. This introduces the area of data streams. Streaming data is ubiquitous and there is a real challenge to store, query, analyze and visualize such rapid large volumes of data. Resource constraints of ubiquitous environments represent the main research issue to realize such a potential field with various important applications. Examples of such applications include processing data  streams produced from sensor networks, web clickstreams, ATM transactions, stock market and many others. In this talk, we review the challenges facing data stream processing. The need for resource-awareness and adaptation is presented leading to an overview of our novel techniques in mining/querying data streams. Applications of these techniques are also presented. Finally the talk is concluded with future visions in the area of data streams and resource-constrained processing environments.


Dr. Mohamed Medhat Gaber is a research scientist at CSIRO, Australia. He received his PhD degree in 2006 from Monash University. His PhD thesis had been nominated for Mollie Holman Award for best PhD theses. He has proposed and developed novel adaptive and lightweight data stream mining algorithms based on his novel Algorithm Output Granularity (AOG) approach to enable "on-board" processing in resource constrained devices such as handheld computers/sensors. He was awarded the competitive and prestigious IBM Doctoral Internship at the IBM T.J. Watson Research Centre in 2005. He has published more than 50 papers including 4 book chapters and 7 journal articles. Mohamed is the co-editor of the book: “Learning from Data Streams: Processing Techniques in Sensor Networks”, published by Springer in 2007. He is also the co-editor of: Proceedings of International Workshop on  Knowledge Discovery from Ubiquitous Data Streams, and Proceedings of First International Workshop on Knowledge Discovery from Sensor Data (Sensor-KDD '07). He had 5 successful Masters supervision and an Honours one at both Monash University and University of Sydney. He is currently co-supervising a PhD student at Monash University. His profile was selected for inclusion in Monash Research Graduate School Annual Report in 2004 and the university scholarship guide for students starting in 2006. Mohamed was nominated and included in Who's Who of Emerging Leaders - 2007, 1st Edition. He is a member of the International Panel of Expert Advisers for Australasian Data Mining Conferences. Mohamed was the co-chair of: International Workshop on Knowledge Discovery from Sensor Data, held in conjunction with the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2007, International Workshop on Knowledge Discovery from Ubiquitous Data Streams, held in conjunction with ECML/PKDD 2007, and IEEE International Workshop on Mining Evolving and Streaming Data, held in conjunction with ICDM'06. He served in the program committees of : ACM Symposium on Applied Computing - Data Streams Track 2008, Second International Workshop on Web Mining for Ecommerce and E-services (WMEE2008), Sixth Australasian Data Mining Conference 2007, Second International Workshop on Integrating AI and Data Mining 2007, International Workshop on Learning from Massive Data 2007, First International Workshop on Web Mining for E-commerce and E-services (WMEE2007), ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2007, ACM Symposium on Applied Computing - Data Streams Track 2007, Fifth Australasian Data Mining Conference 2006, Workshop on Integrating AI and Data Mining 2006, Fourth International Workshop on Knowledge Discovery from Data Streams 2006, Third International Workshop on Knowledge Discovery from Data Streams 2006, Fourth Australasian Data Mining Conference 2005, Second International Workshop on Knowledge Discovery from Data Streams 2005 and Third Australasian Data Mining Conference 2004. Mohamed was also invited as a journal reviewer for papers in: Data Mining and Knowledge Discovery, Springer, International Journal on Very Large Data Bases (VLDB), Journal of Information Science, Journal of New Generation Computing: Special Issue on Knowledge Discovery from Data Streams, Journal of Intelligent Data Analysis (IOS Press): Special Issue on Knowledge Discovery from Data Streams, Journal of Intelligent Information Systems: Special Issue on Mining Spatio-Temporal Data, Journal of Universal Computer Science, Special Issue on Knowledge Discovery in Data Streams, and Computational Statistics, Special Issue on Statistical Analysis of Interval Data.


Unsupervised statistical learning in causal models

of visual and audio perception


Professor Mariofanna Milanova

Computer Science Department, University of Arkansas at Little Rock


In recent years, it has become clear that many problems in perception organization are difficult to solve without introducing the contextual information. We see and hear the world in terms of meaningful causal interactions – a vase crashing to the ground, a father beckoning to his daughter – rather than raw lights and sounds. What is the role of causal inference in perception, and in bridging perception to cognition?  How can computational frameworks for causal reasoning and learning be mapped onto –and perhaps enriched by models of neural computation? To answer these questions different models of perceptual learning are developed. Barlow’s hypothesis is that the purpose of early visual processing is to transform the highly redundant sensory input into more efficient factorial code. A perceptual system should be organized to transmit maximum information. Among existing techniques for modeling multi-resolution decomposition are principal component (PCA) and independent component analysis (ICA).  We propose to improve the effectiveness of decomposition algorithms by providing   them with “classification-awareness.” Combining decomposition and classification is one of the main points of the proposed research methodology. The link between the stimulus and a given neuron action potential  source can be verified by designing a classifier that is able to “predict” under which condition a given signal has been registered, solely based on the discovered independent components. The idea is to look for basis functions whose coefficients allow for an accurate classification while preserving the reconstruction. The proposed framework was tested using neurobiological (event-related potentials ERPs) data and behavioral (eye tracking) data. We also discuss challenging direction for future research in perception.



Dr. Mariofanna Milanova is Associate Professor of Computer Science Department University of Arkansas at Little Rock, USA. She received the M. Sc. degree in Expert Systems and AI in 1991 and the Ph.D degree in Computer Science in 1995 from Technical University, Sofia, Bulgaria. She did her post-doctoral research in visual perception in University of Paderborn, Germany. She has extensive academic experience at various academic and research organizations including the Navy SPAWARS System Center, San Diego, USA, University of Louisville, USA, National Polytechnic Institute Research Center, Mexico City, Mexico, Technical University of Sofia, Bulgaria, University of Sao Paulo, Brazil, University of Porto, Portugal, Polytechnic University of Catalunya, Spain, University of Paderborn, Germany. She has been granted from German Research Foundation (Deutsche Forschungsgemeinschaft), FAPESP State of Sao Paulo Research Foundation. NSF, European Community, NATO and Department of Homeland Security.  Dr Milanova is a Senior Member of the IEEE and Computer Society, member of IAPR, member of the IEEE Women in Engineering, member of Society of Neuroscience and a member of the Cognitive Neuroscience Society. Milanova serves as book editor of two books and associate editor of several international conference proceedings including the ICMLA International Conference on Machine Learning and Application and the METMBS Mathematics and Engineering Techniques in Medicine and Biological Sciences.   Milanova chaired ICMLA’05 Conference. Milanova chaired the series of the IEEE International Conference on Information Reuse and Integration (2001, 2003-2006) and the MEMBS’ 01 and MEMBS’ 03.  Her main research interests are in the areas of artificial intelligence, biomedical signal processing and computational neuroscience, computer vision and communications, machine learning,  privacy and security based on biometric research  She has published and co-authored more than 60 publications,  over 33 journal papers,  6 book chapters, 2 patents and numerous conference papers.





Professor Hoda S. Abdel-Aty-Zohdy, Ph.D

Director of the Microelectronics System Design Lab

Department of Electrical and Computer Engineering

Oakland University



ABSTRACT:  Bio inspired systems provide novel approaches to intelligent signal processing by mimicking the intelligence of living biological systems and then implement it with controllable high speed and density, on integrated chip packages for wide scope of applications. Bio-Inspired Systems integrate the various available intelligent processing approaches such as: Neural Networks (NNs), Evolutionary Programming such as Genetic Algorithms (GAs), and Fuzzy Logic. We capitalize on the inherent advantages and limitations of each approach, with selection guidelines and criteria for specific embedded applications. Abdel-Aty-Zohdy’s lecture will elucidate observations and motivations to mimic biological systems, and will focus on applications of bio-inspired intelligence including multi-media polymorphic computational biology, and the mammalian olfactory system -- an electronic nose, based on . She will also discuss the most recent scientific discoveries gleaned from the study of spikes in the brain activity of monkeys, which have introduced the concept of plasticity in synapses. Biological memory and collaborative man–machine interfaces will be touched upon in terms of future bio-intelligence challenges. Examples of embedded bio-inspired approaches will be discussed and presented with emphasis on systems for recent bio-chemical sensing and detection (Electronic Nose), temperature prognosis, and applications towards bio computing. These include our Spiking NN system with 128 inputs and 8-outputs on an area of 0.118 square mm using the 0.16um CMOS technology.  Bio-inspired, silicon-based systems integration with organic and inorganic media via multi-phase, and multi-domain possible interface and integration promise to achieve intelligent, secure, compact, and real time applications.



Prof. Hoda Abdel-Aty-Zohdy received the B.A.Sc. degree (with First Class Honors) from Cairo University, the M.A.Sc. and the Ph.D. degrees from the University of Waterloo, all in Electrical Engineering. She is the Founder and Director of the Microelectronics System Design Laboratory, Coordinator of the Engineering Physics Program, and Professor in the department of Electrical and Systems Engineering at Oakland University. She has authored 135 refereed publications, and about 100 technical presentations.  Dr. Abdel-Aty-Zohdy has been an AFOSR/IF Visiting Faculty Research Fellow (2003 and 2002), a National Academy of Science/National Research Council Fellow (2000 and 2001), a Faculty Intern at the Chrysler Technology Center, Advanced Manufacturing Engineering, 1998 and 1997, Consultant to Fanuc-Berkeley MEMS Lab, 1996, DARPA supported Visiting Professor at The University of Michigan, Ann Arbor, Center for Integrated Sensors and Circuits, 1995; Consultant to General Motors Research Labs, ITT, and a visiting professor at the Institute for Computer Research, at the University of Waterloo. Dr. Abdel-Aty-Zohdy is elected to the Distinguished Lecture Program of the IEEE Circuits and Systems Society (2004-2005 and 2006). She served on numerous IEEE committees including: The Chairperson in 2005-06 and a member 2004 -2005 for the IEEE G. R. Kirchhoff’s Award Committee; The elected Chair for the IEEE/South East Michigan Section-Chapter-I on Circuits and Systems, Signal Processing, Information Theory, and Control since 2000; The Chair of future symposia committee, general cochair, track chair, session organizer, and speaker for the IEEE Midwest Symposium on Circuits and Systems since; The Organizer and General Chair of the Educational program for the IEEE Custom Integrated Circuits Conference (CICC88). She served as the General Chair for the first Collaborative Technologies Workshop in 1999, at Oakland University.  She presented the Oakland University President’s Colloquium, April 1st, 2005, Keynote, and plenary lectures at: the International Conference on Telecommunications (ICT05) South Africa, 2005; IEEE NEWCAS 2004, in Montreal Canada; IEEE MWSCAS 2003, Cairo, Egypt; IEEE ECCTD 2003 in Krakow, Poland; and the ICCC 2001, in Hamammat, Tunisia.


(One day invited speakers)

Cairo, Egypt, Dec. 18,  2007




Knowledge Maps = Stable Pattern Languages


Professor Mohamed E. Fayad, PhD,



Pattern languages form the strong groundwork for any discipline understanding. Its uses have spilled over to the software engineering field, to precisely describe past experiences and better understand software architectures conceptualization and realization, along with, how their building blocks are insightfully woven seamlessly to satisfy a determined purpose resolution. Current representations of pattern languages [5, 6, 7] strives hard in providing the sufficient means or guidelines to build software architecture out of patterns; bringing as a consequent problems, such as poor traceability [3], lack of stability, poor adaptability, out of context understanding realization, are more prominent within the pattern language implementation.  To overcome these problems in traditional pattern languages, we have provided both a set of quality factors to evaluate pattern language definition, accuracy, and application; and also a newly enhanced Pattern Language representation, driven by Software Stability Concepts [8, 9, 10], called Knowledge Map, which provides many significant benefits to the software architecture’s development practices.



Resource Management in Heterogeneous Wireless Networks –

 Challenges and Opportunities


Professor Hossam Hassanein

Telecommunications Research Lab

Queen’s University


Abstract: This talk describes our efforts in addressing the challenges to Resource Management (RM) in Heterogeneous Wireless Networks (HWNs). Our understanding is that establishing a comprehensive RM framework for such networks requires the consideration of elements in two dimensions – the access level and the end-to-end level. It is also crucial to accommodate the unique characteristics of HWNs.  In the talk we, will detail our efforts in three main directions. The first comprises establishing a framework overlooking the interactions of network levels (network, path, link and access) in end-to-end service delivery. We describe practical mechanisms for multi-metric routing, in addition to inter-level mapping of end-to-end QoS requirements. We also describe generalized access scheduling techniques with economic considerations. The second direction entails the introduction of novel and non-traditional RM mechanisms that exploit characteristics specific to HWNs. We show how technologies within a HWN can be enhanced through joint functionalities. The third direction shows how vertical handoffs, despite their challenges, can be used to the benefit of the service provider; and how the use of wireless multihop communication can be utilized in a structurally-hybrid environment to maintain a robust network operation.



Hossam Hassanein is a leading researcher in the School of Computing at Queen's University in the areas of broadband, wireless and variable topology networks architecture, protocols, control and performance evaluation. Before joining Queen's University in 1999, he worked at the department of Mathematics and Computer Science at Kuwait University (1993-1999) and the department of Electrical and Computer Engineering at the University of Waterloo (1991-1993). Dr. Hassanein obtained his Ph.D. in Computing Science from the University of Alberta in 1990. He is the founder and director of the Telecommunication Research (TR) Lab in the School of Computing at Queen’s. Dr. Hassanein has more than 300 publications in reputable journals, conferences and workshops in the areas of computer networks and performance evaluation. Dr. Hassanein has organized and served on the program committee of a number international conferences and workshops. He is a senior member of the IEEE and serves as the Secretary of the IEEE Communication Society Technical Committee on Ad hoc and Sensor Networks (TC AHSN). Dr. Hassanein is the recipient of Communications and Information Technology Ontario (CITO) Champions of Innovation Research award in 2003.




We are delighted to invite you to participate in our 4th  workshop on  Emerging Intelligent Systems Paradigms (EISP), on 15 Dec.  2007.




The few key technologies interact in an interesting and yet useful way, bringing along the multimedia revolution. This revolution is transforming the way people live, work, and interact with each other, and is impacting the way businesses, government services, education, entertainment, and health care are operating. Intelligent Multimedia Computing is an interdisciplinary field combining the arts, sciences, artificial intelligence, computer science, mathematics, and the humanities. The field presented is deeply rooted in AI, mathematical logic and models, modern communications, computer, and human sciences. Academic digital media studies are at times a partnership among Arts and Sciences, Computer Science, and Mathematics. The new fields encompass the Intelligent and cognitive aspects of media arts and sciences, exploring the technical, cognitive, and aesthetic bases to human multimedia intelligence and its computation, the applications to business intelligence, model discovery, data mines and intelligent data bases, and IT.  Recommended topics include but are not limited to the following:


  • Creative Multimedia Techniques

  • AI and Intelligent Multimedia

  • Multimedia/Web Graphic  User Interface

  • Basic Intelligent Multimedia Techniques

  • Agent Computing and Intelligent Multimedia

  • The Mathematical Foundations

  • Intelligent Visual DB and DM

  • Internet Multimedia and Wireless Multimedia

  • watermark technologies

  • animation and computer graphics
  • audio and video compression
  • Image Processing and application

  • Audio processing and Application

  • 3D audio and video
  • image, video, audio content analysis and indexing/retrieval
  • multi-paradigmatic information retrieval
  • multimedia stream synchronization
  • game technology
  • Multimedia & Security
  • multimedia authoring tools and intelligent tutoring
  • Applications ( E-commerce systems and recommendation systems, multimedia digital libraries and mail systems, multimedia search engines, games, computer-supported cooperative work, cultural heritage multimedia applications, distance learning applications, virtual reality systems, tele-conferencing, tele-medicine, etc......


Workshop General Chair

Professor  Aly Fahmy,

Faculty of Computers and Information
Cairo University,
5 Ahmed Zoweil St., Dokki
Giza, Egypt
Tel: (+202) 3350107  - : (+2012) 3420162
Fax: (+202) 3350109
Personal e-mail:

Workshop Coordinators and Co-Chair

Professor  Reem Bahgat,

Vice Dean of Research and Higher Studies, 

 Faculty of Computers and Information, Cairo University


Dr.  Aboul Ella Hassanien,  ERS coordinator




Workshop Place



Faculty of Computers and Information, Cairo University,
5 Ahmed Zoweil St., Dokki, Giza, Egypt





For further Information, please contact:


Dr. Aboul Ella Hassanien


ERS coordinator


Workshop Program


Workshop Program


Dec. 15 2007




Session I: Data computing and Image analysis

Session Chair: Professor Hoda Owns and Dr Neamat El Gayar



Recent trends in image analysis,  

Professor Dr. Mrs. P. P. Rege, India


Secure Negotiation Framework in Inter Grid Environments

Professor Dr. Jemal Hussien Abbawajy, AUSTRALIA


Resource-Adaptive Data Stream Processing,

Dr. Mohamed Medhat Gaber,  CSIRO, Australia

12:15-12:30 Coffee break

Session II:  Communication and Intelligent multimedia systems


Session Chair:  Professor  Aly Fahamy and Dr. Galal



Bio-Inspired Intelligent Integrated systems

Professor Hoda S. Abdel-Aty-Zohdy,  Oakland University


Unsupervised statistical learning in causal models of visual and audio perception

Professor Mariofanna Milanova, University of Arkansas


DSRC: Towards Autonomous Vehicular Communications


Dr. Y. L. Morgan Canada


Supra Topological Approach for Decision Making via Granular Computing

Dr. Tamer Medhat Mohammad Ibrahim, Egypt

Lunch time and closing


Workshop Program

18 Dec. 2007




Session Chair: Professor Aly Fahmay and Professor Reem



 Knowledge Maps = Stable Pattern Languages

Professor Mohamed E. Fayad,


Resource Management in Heterogeneous Wireless Networks –Challenges and Opportunities

Professor Hossam Hassanein



Service-Oriented Sensor-Actuator Networks


Professor Mohamed Eltoweissy, Virginia Tech

12:15-12:30  coffee break




ISCAPABO2007 proceeding

1      2      3     4    5    6    7