The 7th  Workshop on

Ubiquitous Computing and Intelligence Information: Challenges and Solutions

UCII-CS08

Mubarak city for Science and technology,

Egypt, July 21  2008

Organized by:

  The any place/any time/any means vision of ubiquitous computing has explosive impact on academics, industry, government and daily life. This emergence is the natural result of research and technological advances in wireless and sensor networks, embedded systems, mobile computing, distributed computing, agent technologies, autonomic computing and communication. Many novel but more specific computing mechanisms and paradigms have been recently driven from the broad view of ubiquitous computing, such as pervasive, context-aware, sentient, invisible, disappearing, everyday, wearable, proactive, autonomic, organic, sustainable, handheld, palpable, amorphous, spray, embedded computing, ambient intelligence, etc.  Following ubiquitous computers and networks, is a road towards ubiquitous intelligence, i.e., computational intelligence pervasion in both the physical world and the cyber world. Such right place/right time/right means vision of ubiquitous intelligence will greatly reform our world to create a smart world filled with a variety of embedded intelligence or smart real and virtual things ranging from software to hardware, from man-made artifacts to natural objects, from everyday appliances to sophisticated systems, from small rooms to large buildings, from enclosed sites to open spaces, from stationary places to moveable vehicles, etc. The computational intelligence will not only function as the methods or tools in systems but also result in ubiquitous existence residing in everyday objects, surrounding environments, diverse systems and even ourselves. Such future existence of ubiquitous intelligence calls for re-thinking of the conventional intelligent computing, identifying implications and important issues of the foreseen smart world, and finding corresponding solutions by joint efforts and fusions of multiple disciplines. The ubiquitous intelligence, as an emerging and very promising multidiscipline, aims at new models and technologies for graceful integrations and mutual actions of real worlds and virtual e-worlds with different scales and purposes.
 

Ubiquitous computing encompasses a wide range of research topics, including distributed computing, mobile computing, sensor networks, human-computer interaction, and artificial intelligence. For a list of research labs taking interest in developing this field, see List of ubiquitous computing research centers.

• Knowledge-Based Systems,

• Expert Systems,

• Neural Networks,

• Fuzzy Techniques and Systems,

• Genetic Algorithms and Evolutionary Computing,

• Hybrid Intelligent Systems,

• Intelligent Agents and Multi-Agent Systems,

• Knowledge Discovery and Data Mining,

• Machine Learning,

• Cognitive Modelling,

• Knowledge Representation and Management,

• Planning, Spatial & Temporal Reasoning,

• Knowledge Acquisition.Industrial Control and Monitoring,

• Fault Diagnosis,

• Robotics, Image Processing,

• Machine & Computer Vision,

• Medical & Diagnostic Systems,

• Financial & Stock Market Monitoring and Prediction,

• Speech Processing and Synthesis,

• Natural Language Processing,

• Environmental Monitoring,

• Power Electronics & Drives, High Voltage Systems,

• Engine Control and Vehicle Applications;

• Signal Processing;

• Wavelets.

• Evolvable Hardware,

• DNA Computing,

• Artificial Life,

• Bioinformatics using Intelligent & Machine Learning Techniques,

• Intelligent Tutoring Systems,

• Artificial Intelligence and the Internet,

• Information Agents on the Internet,

• E-commerce/E-business and E-learning,

• Intelligent Information Retrieval,

• Intelligent Web Mining & Applications,

• Intelligent User Interfaces,

• Virtual Reality & Multi-Media Intelligent Information Systems.

• Theoretic Foundations
• Parallel algorithms for Rough set theory
• Rough techniques in Pattern recognition
• Rough techniques to improve Artificial Neural Nets
• Uncertainty and Rough sets
• Algorithms for decision making using  rough sets
• Applications in Biomedical Domains and Business
• Methodologies for developing Decision Support Systems using  rough sets
• Algorithms for Mining gene data bases and biological data bases using  rough sets
• Solving Classification and Clustering problems using  rough sets
• Novel Algorithms using fuzzy or rough sets
• Inductive learning Methods using fuzzy or rough sets
• Lazy-learning and instance-based learning methods based on fuzzy or rough sets
• Integration of fuzzy or rough sets in Case-based reasoning
• Knowledge extraction from texts (Text Mining) using fuzzy or rough sets
• Intelligent data analysis using fuzzy or rough sets

 Abstract:    Process Control and Optimization (PC&O) both have branched-up extensively in the last few decades.     Process Control has changed from analogue to digital control accommodating, fast and continuously, digital discoveries. Examples are: Distributed Process Control (DPC), Fuzzy Control (FC), Optimal Control (OP), etc      Optimization includes numerical techniques, for given configurations, with their different search techniques for lumped systems and calculus of variation (Pontryagain Maximum Principle) for distributed systems. It also includes conceptual optimization for developing novel configurations and utilizing new discoveries especially with regard to new materials and also new renewable feedstock to achieve sustainability.     More fundamental knowledge is leading to more rigorous and reliable mathematical models for different physico-chemical processes of different degrees of sophistication. Some are lumped systems described at steady state by algebraic equations and the unsteady state dynamics by Ordinary Differential Equations (ODEs) and others are distributed systems described at steady state by ODEs (one-dimensional models) and unsteady dynamics by Partial Differential Equations (PDEs), while the rest are always described by PDEs at both steady and unsteady state conditions (two-dimensional and three-dimensional models). Both lumped and distributed systems can be homogeneous (one phase) or heterogeneous (two or more phases) adding to the complexity of the system especially when it is non-linear acquiring accurate numerical techniques for reliable solutions.   Numerical techniques and digital computers power are continuously improving and becoming more user-friendly allowing dealing with the steady and unsteady state of highly non-linear complex lumped and distributed; homogeneous and heterogeneous systems using models of different degrees of sophistication and dimensionality. In most industrial processes a system is formed of many interacting components (sub-systems) making the solutions more difficult especially when the interactions include feedbacks (recycles) leading to boundary value problems requiring some additional iterations to obtain solutions.      Stochastic Modeling and Statistical Process Control based on probabilistic variables are also quite important but are not covered in this lecture     Computer tools for steady state, dynamic simulation, optimization and on-line control have become more powerful and efficient and are improving further in a fast and continuous manner.  These advances have lead to the availability of software package for flow-sheet simulation (e.g.: Hysis, Aspen), design tools (e.g.: COMSOL Multi-physics) and dynamic simulators (e.g.: AUTODYNAMICS).      These modern aspects regarding PC&O necessitate the use of Integrated System Approach (ISA) based on System Theory (ST) as the most efficient approach to organize and transfer knowledge and finding new discoveries. In this approach systems are divided, based on thermodynamics principles, to three general categories: Isolated, Closed and Open systems with other classifications included within each category.    The above is all coupled to the need for the Cross-Disciplinary Approach (CDA) in both research and education and is linked to process economics, menu of products and the process/economic feasibility of new products/feedstock, or what may be called product design and feedstock optimal choice in an integrated contradistinction to our more classical process design using well established feedstock.    This lecture will introduce ISA and its coupling to CDA and their applications to PC&O, with all their different branches and aspects referred to above, in a systematic manner opening the door for advanced research and education with especial emphasis on scientific and technological activities related to sustainable development and optimum utilization of renewable resources.

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 Dr. . Mohamed Saleh Ibrahim,

 Vice Dean of Informatics Research Institute IRI

• • Prof. Dr. Mohy Eldin A. Abo-Elsoud, Faculty of Engineering, Mansoura University

  • Prof. Dr. Ibrahiem M. M. El Emary, Faculty of Engineering, Amman University, Jordan

  • Prof. Dr. Mohamed Nazih El-Derini,  Faculty of Engineering, Mansoura University

  • Prof. Dr. Fayez Fahmy Gomaa Areed,  Department of computers & Systems,  Faculty of Engineering, Mansoura University

  • Prof. Dr. Ismail Amr Ismail, Faculty of computers and informatics, Misr International University

  • Prof. Dr. Mohamed Rizk, Faculty of Engineering, Alex university

  • Prof. Dr. Hassan Abd El-Halim    > Electrical Engineering Department / Alex university

  • Prof. Dr. Mofreh Mohamed Salem, Former Computers & Sustems Dept - Mansoura University

  • Prof. Dr. Sabry F. Saraya,  Computers & Systems department head , Mansoura university

  • Prof. Dr. Hesham Arafat Ali, Faculty of Engineering / Mansoura University
    
     

   

We are delighted to invite you to participate in our 7th  workshop on

Ubiquitous Computing and Intelligence Information: Challenges and Solutions

UCII-CS08,  on 21 July.  2008.