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By Khaled Elleithy, Tarek Sobh, Ausif Mahmood, Magued Iskander, Mohammad A. Karim

The convention complaints of foreign convention on commercial Electronics, know-how & Automation (IETA 05), overseas convention on Telecommunications and Networking (TeNe 05) and overseas convention on Engineering schooling, educational expertise, evaluation, and E-learning (EIAE 05) comprise a suite of carefully reviewed world-class manuscripts addressing and detailing state of the art study tasks within the components of: business Electronics, know-how and Automation, Telecommunications, Networking, Engineering schooling, educational know-how and e-Learning.The 3 meetings, (IETA 05, TENE 05 and EIAE 05) have been a part of the overseas Joint convention on desktop, details, and approach Sciences, and Engineering (CISSE 2005).CISSE 2005, the World's first Engineering/Computing and platforms study E-Conference was once the 1st high-caliber examine convention on the earth to be thoroughly carried out on-line in real-time through the internet.CISSE acquired 255 examine paper submissions and the ultimate software incorporated one hundred forty approved papers, from greater than forty five international locations. the total proposal and structure of CISSE 2005 used to be very interesting and ground-breaking. The powerpoint displays, ultimate paper manuscripts and time agenda for stay displays over the net have been to be had for three weeks sooner than the beginning of the convention for all registrants, so that they may decide and select the shows they wish to wait and view questions that they could are looking to ask. The reside audio displays have been additionally recorded and are a part of the everlasting CISSE archive, inclusive of all energy aspect shows, papers and recorded presentations.All facets of the convention have been controlled online; not just the reviewing, submissions and registration approaches; but in addition the particular convention. convention contributors - authors, presenters and attendees - in basic terms wanted an online connection and sound to be had on their desktops as a way to be capable to give a contribution and perform this foreign ground-breaking convention. The online constitution of this top of the range occasion allowed educational pros and individuals to give a contribution paintings and attend world-class technical shows according to conscientiously refereed submissions, dwell, with no the necessity for making an investment major commute money or day trip of the place of work. Suffice to assert that CISSE obtained submissions from greater than 50 nations, for whose researchers, this chance awarded a way more reasonable, dynamic and well-planned occasion to wait and publish their paintings to, as opposed to a vintage, on-the-ground conference.The CISSE convention audio room supplied awesome audio even over low velocity net connections, the power to show PowerPoint shows, and cross-platform compatibility (the conferencing software program runs on home windows, Mac, and the other working approach that helps Java). additionally, the conferencing procedure allowed for an enormous variety of contributors, which in flip granted CISSE the chance to permit all members to wait all shows, instead of proscribing the variety of to be had seats for every session.The applied conferencing know-how, beginning with the submission & overview method and finishing with the web conferencing power, allowed CISSE to behavior a truly prime quality, pleasing occasion for all individuals.

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By virtue of this property, we shall call < a feature map associated with k. , kernelbased clustering, support vector machine and kernel principal component analysis. The primary disadvantage of the kernel-based method is its severe computational burden. For an image of size 512u 512 , there are in total 262144 feature vectors (262144 pixels in the feature image). If we directly use kernel-based techniques, it needs to process a matrix of size 262144u 262144 . The severe computational complexity indicates that it is unreasonable to only use the kernel-based clustering algorithm to segment the texture image.

Vol. 16, no. 2, pp. 130-149, 1994. [ 8 ] M. Unser, “Texture classification and segmentation using wavelet frames,” IEEE Trans. Image Processing, vol. 4, no. 11, pp. 1549-1560, 1995. [ 9 ] M Acharyya and M. K. Kundu, “An adaptive approach to unsupervised texture segmentation using M-band wavelet transform,” Signal Processing, vol. 81, pp. 1337-1356, 2001. [ 10 ] A. Y. Ng, M. I. Jordan and Y. Weiss, “On spectral clustering: analysis and an algorithm,” In Advances in Neural Information Processing Systems, vol.

Müller, S. Mika, G. Rätsch, K. Tsuda and B. Schölkopf, “An introduction to kernel based learning algorithm,” IEEE Trans. Neural Networks, vol. 12, no. 2, pp. 181-201, 2001. [ 12 ] Y. L. Qiao, Z. M. Lu and S. H. Sun, “Document image segmentation using Gabor wavelet and kernel-based methods,” submitted to 7th IAPR workshop on Document Analysis Systems. [ 13 ] B. S. Manjunath and W. Y. Ma, “Texture feature for browsing and retrieval of image data,” IEEE Trans. Pattern Anal. , vol. 18, no. 8, pp. 837-842, 1996.

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