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China-Ireland International Conference on Information and Communications Technologies (CIICT 2008)

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  • Location: Beijing, China
  • Conference date: 26-28 Sept. 2008
  • ISBN: 978 0 86341 921 8
  • Conference number: CP544
  • The following topics were dealt with: software engineering; natural language processing; signal processing; artificial intelligence; modelling and scientific computing; security and encryption; communication and networks; wireless and sensor network; mobile communication and network/Internet/IP network; telecommunication service and network; circuits, optics and optoelectronics; Web intelligence and engineering applications; multimedia applications; and virtual reality.

1 - 20 of 174 items found

  • A AST and context based duplicated code detecting method
  • Study on information classification of tourism emergency events
  • Performance evaluation of a parallel C/A code acquisition scheme based on maximum likelihood criterion
  • A modulized algorithm for computing 4M- point DFT
  • A new method for four dimensional parameters estimation of near field sources
  • An efficient joint algorithm based on one training sequence for OFDM system
  • Orthogonal frequency division multiplexing (OFDM)
  • Gait recognition based on combined invariant moment
  • The solve of the high profit development of the tourism destination
  • Weighted multi-criteria workflow task assignment
  • Analysis of China's economic growth
  • Forecasting heartbeat delay for failure detector over Internet using neural network
  • Building a heterogeneous software architecture for the WBC service layer
  • A new frame rate up conversion scheme based on mixed genetic algorithm and particle filter approach
  • Using DNA computing to solve minimum spanning tree problem
  • Research on knowledge expressing method based on multi-agent
  • On coordinating strategy for one-to-many negotiation
  • Study on Web data extraction
  • Design of vertical search engine model based on the analysis of page links and correlation
  • Using clustering to enhance text classification
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