• • Part of the book series (LNCS, volume 5227) Abstract Extracting useful information from a very large amount of biomedical texts is an important and difficult activity in biomedicine field. Data to be examined are generally unstructured and the available computational resources do not still provide adequate mechanisms for retrieving and analyse very large amount of contents. In this paper we present a rule-based system for Text Mining process applied in biomedical textual documents.

This application requires a strongly use of the computational resource to perform intensive operations. We propose a grid computing approach to improve application performance. Cite this paper as: Castellano M. (2008) Biomedical Text Mining Using a Grid Computing Approach. In: Huang DS., Wunsch D.C., Levine D.S., Jo KH. Crystal Eye Installer Unrecognized Cameras. (eds) Advanced Intelligent Computing Theories and Applications.

Full-text (PDF) In this paper a parallel implementation of an encoder and of a decoder for cyclic codes to increase the bit rate is proposed. The structures a. Dipartimento di Elettrotecnica ed Elettronica. Politecnico di Bari. Orabona, 4 - 70125. If the first n bits of the code word are the. Message bits and the last r bits. Istituto Professionale di Stato per l?industria e l'Artigianato 'G. Vallauri' - Carpi (MO). [6] R.Mottola and G.L.Sicuranza, “Finite word length effects in a multimicroprocessor-oriented implementation of two-dimensional digital filters”, Alta Frequenza, vol. 10, Oc- tober 1979. [7] G.L.Sicuranza, “Signal processing activities at the Istituto di Elettrotecnica ed Elettronica of the University of Trieste”, Signal.

With Aspects of Artificial Intelligence. Lecture Notes in Computer Science, vol 5227. Springer, Berlin, Heidelberg • DOI • Publisher Name Springer, Berlin, Heidelberg • Print ISBN 978-3-540-85983-3 • Online ISBN 978-3-540-85984-0 • eBook Packages • •.