With success of ICEEE 2010 in Wuhan, China, and December 4 to 5, 2010, the second International Conference of Electrical and Electronics Engineering (ICEEE 2011) will be held in Macau, China, and December 1 to 2, 2011. ICEEE is an annual conference to call together researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in Electrical and Electronics Engineering along with Computer Science and Technology, Communication Technology, Artificial Intelligence, Information Technology, etc.
This year ICEEE is sponsored by International Industrial Electronics Center, Hong Kong. And based on the deserved reputation, more than 750 papers have been submitted to ICEEE 2011, from which about 94 high quality original papers have been selected for the conference presentation and inclusion in the “Advanced Computer, Communication, and Control” book based on the referees’ comments from peer-refereed. All the papers will be published by Lecture Notes in Electrical Engineering (ISSN: 1876-1100), and will be included in Springer Link.
We expect that the Advanced Computer, Communication, and Control book will be a trigger for further related research and technology improvements in the importance subject including Signal Processing, Retrieval and Multimedia, Artificial Intelligence, Computing and Intelligent Systems, Machine Learning, Biometric and Biomedical Applications, Neural Networks, Knowledge Discovery and Data Mining, Knowledge-based Systems, Control Systems, Modeling and Simulation Techniques, Wireless Communications, Advances in Wireless Video, etc.
Table of ContentsFrom the content: A Novel Threat Prediction Framework for Network Security.- An Artiﬁcial Immune Pattern Recognition Approach for Damage Classification in Structures.- An Novel F-M Partitioning Algorithm for Parallel Logic Simulation.- The LabVIEW Based Distributed Optical Fiber Sensing System for the Concrete Bridges.- Engine Testing Fault Classification Based on the Multi-Class SVM of Auto-regression.- Dynamic Characteristic Analysis of High Precision Gear Test Box.