Industrial Applications of Parallel Data Processing at the International Conference on Intelligent Systems Design and Applications (IAPDP@ISDA 2012)

November 27-29
Cochin, India

http://www.mirlabs.org/isda12/ss7.html
http://www.mirlabs.net/isda12


Important dates:
Paper submission due: Aug. 31, 2012
Notification of paper acceptance: Sept. 30, 2012
Final manuscript due: Oct. 15, 2012
Registration and full payment due: Oct. 15, 2012
Conference date: Nov. 27-29 2012

Processing large datasets generated by research and industry represents one of the most important challenges in data mining. The growing volumes of data represent an opportunity for the application of data processing and data mining methods. Although advanced data analysis is the main goal of data mining, even general processing of large volumes of high-dimensional data be extremely time consuming and in conclusion unusable for practical applications.
Parallel processing has been clearly identified as one of the most effective methods for fast solution of complex data-intensive problems. The emergence of inexpensive parallel computers such as commodity desktop multiprocessors, clusters of workstations or PCs, grids, and GPUs has made such parallel methods generally applicable.
Data-intensive applications such as information retrieval, data mining, and data analysis have established a new challenge for the modern generation of parallel platforms. Emerging areas such as computational biology and nanotechnology have implications for algorithms and systems development, while fast changes in architectures and programming models and applications have implications for how parallel platforms can be used to solve practical problems.
The special session seeks contributions about foundations of parallel data processing for industrial use as well as case studies, empirical, and other methodological works related to models, tools, and environments for concurrent analysis of industrial data. It will provide an opportunity to disseminate latest results in this growing field and it will aim to stimulate collaboration between industry and universities. The main topics cover the design and use of various models, algorithms, tools, libraries, and environments for the design and implementation of parallel approaches to data-intensive industrial applications.

Recommended topics include but are not limited to the following:
1. Parallel platforms for small and medium enterprises
2. Parallelism in enterprise systems
3. Parallel data processing algorithms, knowledge discovery, pattern detection and matching
4. Parallel classification and clustering of industrial and research data
5. Multicore industrial data processing on the CPUs and beyond
6. Manycore industrial data processing on the GPUs and beyond
7. Distributed data processing in industry and research
8. Parallel data processing in intranets
9. Parallel data processing in the cloud and on the Web
10. Performance analysis of parallel data processing
11. Parallel processing of streams of industrial data
12. Implementation issues of parallel data processing
13. Platforms and tools for parallel data processing
14. Applications of parallel data processing

Session Chairs
1. Václav Snášel, Department of Computer Science, VSB - Technical University of Ostrava, vaclav.snasel@vsb.cz
2. Pavel Krömer, Department of Computer Science, VSB - Technical University of Ostrava, pavel.kromer@vsb.cz
3. Petr Gajdoš, Department of Computer Science, VSB - Technical University of Ostrava,
petr.gajdos@vsb.cz

Contacts
Pavel Krömer, pavel.kromer@vsb.cz
Eliška Ochodková, eliska.ochodkova@vsb.cz

Program committee (tentative)
Vaclav Snasel, VSB-Technical University of Ostrava, Czech Republic
Milos Kudelka, VSB-Technical University of Ostrava, Czech Republic
Pavel Kromer, VSB-Technical University of Ostrava, Czech Republic
Jan Platos, VSB-Technical University of Ostrava, Czech Republic
Pavel Moravec, VSB-Technical University of Ostrava, Czech Republic
Petr Gajdos, VSB-Technical University of Ostrava, Czech Republic
Jan Martinovic, VSB-Technical University of Ostrava, Czech Republic
Dusan Husek, Institute of Computer Science, Academy of Science, Czech Republic
Petr Musilek, University of Alberta, Canada
Suhail S. Owais, AL-Balaqa University, Jordan
Eyas El-Quwashme, Jordan University of Science and Technology, Jordan
Hideyasu Sasaki, University of Hong Kong, Hong Kong
Juan D. Velasquez, University of Chile, Santiago, Chile
Michal Wozniak, Wroclaw University of Technology, Poland
Marek Penhaker, VSB-Technical University of Ostrava, Czech Republic
Standa Misak, VSB-Technical University of Ostrava, Czech Republic
Milos Besta, Google, New York
Lukas Prokop, VSB-Technical University of Ostrava, Czech Republic
Miroslav Voznak, VSB-Technical University of Ostrava, Czech Republic
Nashwa Mamdouh El-Bendary, Arab Academy for Science, Technology, and Maritime Transport, Egypt
Dr. Muhanned Al Farras, College of Computer Engineering & Sciences, Gulf University, Bahrain
Aboul Ella Hassanien, Cairo University, Egypt