Lecturers & Sessions*
Plenary Lectures
- Prof. Marco Dorigo (Curriculum Vitae. PLENARY LECTURE: ’Swarm Optimization’)
- Prof. Ronald R. Yager (Curriculum Vitae, PLENARY LECTURE: ‘Prioritized Aggregation Operators and their Application’)
- Prof. Nikola Kasabov (Curriculum Vitae. PLENARY LECTURE: ‘Spiking Neuro-Genetic Networks for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition’)
- Arthur Kordon, Ph.D. (Curriculum Vitae. PLENARY LECTURE: ‘Applying Intelligent Systems in Industry: A Realistic Overview’)
- Alexander Gegov (Curriculum Vitae. PLENARY LECTURE: ‘Advances in Fuzzy Systems and Networks’)
- Prof. Janusz Kacprzyk DSc (Curriculum Vitae. PLENARY LECTURE: ‘Bipolarity in preferences and intentions for more human consistent decision analysis and database querying’)
Intelligent Computing: A Basis for Intelligent Systems
September 6 at 14:00-14:40. Keynote Speaker: Michael Flynn – Stanford University http://arith.stanford.edu/~flynn/.
Space Elevator Challenges: DataMining and SuperComputing
September 6 at 14:50-16:20. Tutorial 1 (90 min)
by: Hiro Fujii, Tokyo, Japan,
Oskar Mencer, London, UK,
Dragan Bojic and Veljko Milutinovic, Belgrade, Serbia,
Goran Rakocevic, Berkeley, USA,
Miroslav Bojovic, Zabljak, Montenegro
Sasa Stojanovic, Foca, Bosnia
Abstract:
First, this tutorial presents the state of the art in the Space Elevator technology, with special emphasis on the efforts taken by the Fujii Labs of Tokyo, Japan. Second, the supercomputing problems of interest for space research are presented and it is shown how they can be treated with dataflow supercomputers, of which the Maxeler of London, UK, demonstrates the best speed/watt (its architecture and programming challenges are presented). Third, a case study related to datamining of space information on a Maxeler machine is presented. Forth, examples are given that show how young researchers from three different Balkan countries have mastered the art of programming of a modern dataflow supercomputer.
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Datamining in Wireless Sensor Networks
September 6 at 16:35-18:05. Tutorial 2 (90 min)
by: Zoran Babovic,
Milica Knezevic,
Nemanja Kojic,
Dragan Milicev,
Goran Dimic,
Milica Pejanovic,
Veljko Milutinovic,
Nenad Mitic,
Zoran Ognjanovic,
Bozidar Radenkovic,
Goran Rakocevic,
Stasa Vujicic Stankovic,
Zoran Ognjanovic,
Vladimir Filipovic,
Zhilbert Tafa,
Marija Milanovic,
Ivan Vukasinovic, Serbia
Abstract:
First, an introduction to datamining is given, with special emphasis on algorithms of interest for WSNs (wireless sensor networks). Second, a classification of existing research to DM-WSN (datamining in WSNs) is presented. Third, each example is described with an algorithm and the infrastructure needed to run the algorithm. Third, pros and cons of the presented approaches are discussed and novel ideas for future R+D are presented. Fourth, basics of the agent technology in WSNs are prsented. Fifth, it is explained how the agent technology can help improve the efficiency and effectiveness of DM-WSN. Sixth, examples are presented and a conclusion is generated.
* the program will be ready by summer 2012
