Error message

  • Notice: Undefined variable: _SESSION in tracking_init() (line 27 of C:\xampp\htdocs\rsds\sites\all\modules\rsds\tracking\tracking.module).
  • Warning: file_get_contents(http://user-agent-string.info/rpc/get_data.php?key=free&format=ini&ver=y): failed to open stream: HTTP request failed! HTTP/1.1 404 Not Found in UASparser->get_contents() (line 247 of C:\xampp\htdocs\rsds\sites\all\modules\rsds\tracking\UASparser\UASparser.php).
  • Warning: file_get_contents(http://user-agent-string.info/rpc/get_data.php?key=free&format=ini): failed to open stream: HTTP request failed! HTTP/1.1 404 Not Found in UASparser->get_contents() (line 247 of C:\xampp\htdocs\rsds\sites\all\modules\rsds\tracking\UASparser\UASparser.php).

BIOGRAPHIES OF PEOPLE

Browse biographies:
A B C Ć D E F G H I J K L Ł M N O P Q R S Ś T U V W X Y Z Ź Ż
James F. Peters
University of Manitoba, Winnipeg, Canada

James F. Peters received his Ph.D. in 1991 and is a Full Professor in the Department of Electrical and Computer Engineering and Head of the Computational Intelligence Research Group at the University of Manitoba, past Chair of the IEEE Winnipeg Section and member of the IEEE Winnipeg Section. Currently he is a Member of the Advisory Board of the International Rough Sets Society, IEEE Distinguished Lecturer on Formal Methods in System Design, and Co-Editor-in-Chief of the Transactions on Rough Sets published by Springer-Verlag. He has published over 160 articles in journals, edited volumes, conferences and workshops during the past 10 years. He is the recipient of the IEEE Gold Medallion Award Medal (2000) for his work in IEEE and an IFAC Best Paper Award (1998) for a paper on rough control. His research is supported by grants from Manitoba Hydro and the Natural Sciences and Engineering Research Council (NSERC). His main research interests are in rough set theory, modeling and design of intelligent systems, and philosophy (ontology, aesthetics, language). His current research project is based on an ethological approach to evaluating biologically-inspired collective behavior in intelligent systems in the context of rough sets with particular emphasis on approximation spaces. Layered learning is being considered in the design of a swarmbot behavior testbed and vision system for colonies of line-crawling bots.