By Chuan-Yu Chang, Shu-Han Chang, Shao-Jer Chen (auth.), Jeng-Shyang Pan, Shyi-Ming Chen, Ngoc Thanh Nguyen (eds.)
This quantity composes the complaints of the second one foreign convention on Computational Collective Intelligence––Technologies and purposes (ICCCI 2010), which was once hosted by way of nationwide Kaohsiung collage of technologies and Wroclaw collage of expertise, and used to be held in Kaohsiung urban on November 10-12, 2010. ICCCI 2010 was once technically co-sponsored by way of Shenzhen Graduate institution of Harbin Institute of know-how, the Tainan bankruptcy of the IEEE sign Processing Society, the Taiwan organization for net Intelligence Consortium and the Taiwanese organization for shopper Electronics. It aimed to assemble researchers, engineers and po- cymakers to debate the similar thoughts, to interchange learn principles, and to make buddies. ICCCI 2010 concerned with the next issues: • Agent concept and alertness • Cognitive Modeling of Agent structures • Computational Collective Intelligence • machine imaginative and prescient • Computational Intelligence • Hybrid platforms • clever picture Processing • info Hiding • desktop studying • Social Networks • net Intelligence and interplay round 500 papers have been submitted to ICCCI 2010 and every paper was once reviewed by way of a minimum of referees. The referees have been from universities and commercial companies. a hundred and fifty five papers have been permitted for the ultimate technical application. 4 plenary talks have been kindly provided by means of: Gary G. Yen (Oklahoma kingdom collage, USA), on “Population regulate in Evolutionary Multi-objective Optimization Algorithm,” Chin-Chen Chang (Feng Chia college, Taiwan), on “Applying De-clustering thought to details Hiding,” Qinyu Zhang (Harbin Institute of know-how, China), on “Cognitive Radio Networks and Its Applications,” and Lakhmi C.
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Additional resources for Computational Collective Intelligence. Technologies and Applications: Second International Conference, ICCCI 2010, Kaohsiung, Taiwan, November 10-12, 2010. Proceedings, Part III
Initially, a population of particles is randomly created and then optimum is searched by increasing generations. -C. -S. -F. Jhan the discoveries and previous experience of other particles during the exploration. Therefore, a new population is created based on a preceding one and the particles are updated by the following equations: vi,j (t + 1) = wvi,j (t) + c1 r1 (pi,j − xi,j (t)) +c2 r2 (pg,j − xi,j (t)), j = 1, 2, . . , N, xi,j (t + 1) = xi,j (t) + vi,j (t + 1), j = 1, 2, . . , N, (4) (5) where w is called the inertia factor, for which value is typically setup to vary linearly from 1 to 0 during the iterated processing.
As predicted by the GPM algorithm, the CC gain location of the new image is now aligned with the unit gain point, as shown in Fig. 18. An accurate CC measure for up to 30% channel gain adjustment is thus demonstrated. It is observed that the base area of the spike in Fig. 18 becomes larger, as compared to that of Fig. 12. This change reflects the amount of distortion due to the application of von Kries coefficient law. For channel gain adjustment such as less than 30-40%, the chromatic adaptation and CC gain prediction using the GPM method generally works well.
A CC process is essentially adjusting the RGB channel gain to compensate for the external cast. The key is to utilize this effect in a systematic fashion. Utilizing these features and the RGB channel-gain scanning, a basic structure of an effective cast evaluation method is thus created. Addition features of this algorithm include RGB-HSV color space transformation and graphical schemes to illustrate and analyze the gain-response relation. The offset gain required for CC can be easily visualized using the GPM diagrams.
Computational Collective Intelligence. Technologies and Applications: Second International Conference, ICCCI 2010, Kaohsiung, Taiwan, November 10-12, 2010. Proceedings, Part III by Chuan-Yu Chang, Shu-Han Chang, Shao-Jer Chen (auth.), Jeng-Shyang Pan, Shyi-Ming Chen, Ngoc Thanh Nguyen (eds.)