By Mohammad Taheri, Elham Chitsaz, Seraj D. Katebi, Mansoor Z. Jahromi (auth.), Hamid Sarbazi-Azad, Behrooz Parhami, Seyed-Ghassem Miremadi, Shaahin Hessabi (eds.)

ISBN-10: 3540899847

ISBN-13: 9783540899846

ISBN-10: 3540899855

ISBN-13: 9783540899853

This publication constitutes the revised chosen papers of the thirteenth overseas CSI computing device convention, CSICC 2008 hung on Kish Island, Iran, in March 2008. The eighty four commonplace papers offered including sixty eight poster displays have been conscientiously reviewed and chosen from a complete of 426 submissions.

The papers are prepared in topical sections on learning/soft computing, set of rules idea, SoC and NoC, wireless/sensor networks, video processing and similar themes, processor structure, AI/robotics/control, clinical snapshot processing, p2p/cluster/grid platforms, cellular advert hoc networks, internet, sign processing/speech processing, misc, safeguard, picture processing functions in addition to VLSI.

**Read or Download Advances in Computer Science and Engineering: 13th International CSI Computer Conference, CSICC 2008 Kish Island, Iran, March 9-11, 2008 Revised Selected Papers PDF**

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**Extra resources for Advances in Computer Science and Engineering: 13th International CSI Computer Conference, CSICC 2008 Kish Island, Iran, March 9-11, 2008 Revised Selected Papers**

**Example text**

Simply, these methods try to extract a set of attributes. As alluded to it before, according to distribution hypothesis, the more the common attributes of two concepts, the similarity of the concepts and therefore the probability of existence of a ‘is-a’ relation between them increases. According to diversity of attributes, different similarity measures could be used. For example [3] uses co-occurrence of two words in a window using point wise mutual exclusion(PMI) to compute the similarity value of two words.

C ( U ij = 1 / ∑ Dist ( x j , ω i ) / Dist ( x j , ω L ) L =1 ) 1 m −1 m >1 ; (2) Then a1, a2, a3, which are multipliers of dissimilarity metric, are updated according to the following formula. a i1 ( t + 1) = a i1 ( t ) + η × a i1 ( t )U ij (t ) ( ) (3) × MLSd − dist M ( x j , ω imass ) / Sd In which; ( ) MLSd = dist L ( x j , ω ilinear ) + dist S ( x j , ω ishell ) / 2 * Sd = dist M ( x j , ω imass ) + dist L * ( x j , ω ilinear ) + dist S ( x j , ω ishell ) η = 1 N (4) (5) (6) The formula (3) is the updating rule for ai1 weight and the ones for ai2 and ai3 can be achieved easily substituting the numerator terms.

These numbers are used as indices for feasible Multiplicative Squares. It means that the numbers n to 1 are placed in the square respectively, according to indices generated by the ants. Once the tours are completed ants deposit pheromones on the edges, using (5). , , , , (5) Where FS is sum of the product of rows, columns, diagonals, and broken diagonals is in(or Function Score) of the square, constructed by ant . Note that the ratio verse to one suggested in (3) because of the maximization case.

### Advances in Computer Science and Engineering: 13th International CSI Computer Conference, CSICC 2008 Kish Island, Iran, March 9-11, 2008 Revised Selected Papers by Mohammad Taheri, Elham Chitsaz, Seraj D. Katebi, Mansoor Z. Jahromi (auth.), Hamid Sarbazi-Azad, Behrooz Parhami, Seyed-Ghassem Miremadi, Shaahin Hessabi (eds.)

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