Read e-book online Advances in Information Technology: 6th International PDF

By Komate Amphawan, Philippe Lenca (auth.), Borworn Papasratorn, Nipon Charoenkitkarn, Vajirasak Vanijja, Vithida Chongsuphajaisiddhi (eds.)

ISBN-10: 331903782X

ISBN-13: 9783319037820

ISBN-10: 3319037838

ISBN-13: 9783319037837

This ebook constitutes the lawsuits of the sixth foreign convention on Advances in details know-how, IAIT 2013, held in Bangkok, Thailand, in December 2013. The 23 revised papers awarded during this quantity have been conscientiously reviewed and chosen from a variety of submissions. They care for all parts concerning utilized info technology.

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Read Online or Download Advances in Information Technology: 6th International Conference, IAIT 2013, Bangkok, Thailand, December 12-13, 2013. Proceedings PDF

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Additional info for Advances in Information Technology: 6th International Conference, IAIT 2013, Bangkok, Thailand, December 12-13, 2013. Proceedings

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1, i-Cloud algorithm is totally O(NlogN) + O(logN) equal to O(NlogN). In other words, i-Cloud strategy can be implemented. 5 Performance Evaluation We have evaluated the i-Cloud modules (Fig. 1) as a whole by HTTP trace-driven simulations based on four preprocessed traces 15-day and 31-day BO trace and 15-day and 30-day NY traces. (2) excluding ci , which can be ignored here since we used uniform cost model (meaning that cost-saving ratio is absolutely equal to byte-hit ratio). Four configurations of window sizes have been used for comparisons as follows.

Extract the values from the coefficients. Save them to as image coefficients. Then perform the inverse lifting wavelet transforms to obtain the secret image. Start Video Transform frame video using Lifting multi-level wavelet secret image Steganography Video Extract coefficients from frames Index Decrypt indices Transforms image using inversed wavelet transform Secret image End Fig. 4. A block diagram of the proposed doffing model 4 Results In this section, the experiments are carried out to show the efficiency of the proposed scheme.

3)) and was generated every time capacity miss occurs during the i-Cloud simulation of a certain trace, cache size and respective optimal window size. The result of each simulation is a number of input patterns, which were contained inside a training data set. We prepared four different training data sets shown in Table 3. All patterns within the same training data set were associated with a single target window An Intelligent Cloud Cache Replacement Scheme 29 Table 3. , an optimal window size in Table 2) because i-Cloud was found to give a successful performance results when using a fixed window size per trace as substantiated by [6], [7] and [8].

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Advances in Information Technology: 6th International Conference, IAIT 2013, Bangkok, Thailand, December 12-13, 2013. Proceedings by Komate Amphawan, Philippe Lenca (auth.), Borworn Papasratorn, Nipon Charoenkitkarn, Vajirasak Vanijja, Vithida Chongsuphajaisiddhi (eds.)


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