By Jiangang Cai, Shutian Deng, Hua Shan, Li Jiang, Chaoqun Liu (auth.), Wu Zhang, Weiqin Tong, Zhangxin Chen, Roland Glowinski (eds.)
A huge foreign convention on excessive functionality Computing and its - plications was once held in Shanghai, China, August 8–10, 2004. It served as a discussion board to offer present paintings by way of researchers and software program builders from all over the world in addition to to focus on actions within the excessive functionality computing zone. It aimed to assemble examine scientists, program - oneers,andsoftwaredeveloperstodiscussproblemsandsolutionsandtoid- tify new matters during this region. The convention fascinated about the layout and research of excessive functionality computing algorithms, instruments, and structures and their s- enti?c, engineering, clinical, and commercial purposes. It drew approximately a hundred and fifty individuals from Canada, China, Germany, India, Iran, Japan, Mexico, S- gapore, South Korea, the uk, and the USA of the United States. greater than a hundred and seventy papers have been obtained on quite a few matters in sleek excessive functionality computing and its purposes, reminiscent of numerical and software program set of rules layout and research, grid computing develop, adaptive and par- lel set of rules improvement, dispensing debugging instruments, computational grid and community surroundings layout, computing device simulation and visualization, and computational language learn and their functions to technological know-how, engineering, and drugs. This booklet comprises 90 papers which are consultant in those matters. It serves as a great learn reference for graduate s- dents, scientists, and engineers who paintings with excessive functionality computing for difficulties coming up in technological know-how, engineering, and medication. This convention should not have been attainable with no the aid of a few businesses and businesses and the help of many people.
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Additional resources for Current Trends in High Performance Computing and Its Applications: Proceedings of the International Conference on High Performance Computing and Applications, August 8–10, 2004, Shanghai, P.R. China
These are not possible for Ching’s model. From the tested results, the best model for the “Sample” sequence is our new model with order 4 and the best model for the “DNA” sequence is our new model with order 3. ||∞ minimization. 8 1 Fig. 1. 5 1 Fig. 2. 5 1 Fig. 3. 2 Fig. 4. “DNA”, order n = 4 5 Concluding Remarks In this paper, we proposed and developed a higher-order Markov chain model for categorical data sequences. The number of model parameters increases linearly with respect to the number of lags.
3043). 4 Some Numerical Examples In this section, we present two methods for comparing the performance of the new method and the model by Ching et al. based on two sets of data: the data set in Section 3 and the DNA data sequences in . We ﬁrst propose the prediction method as follows. Given the state vectors Xi , i = t − n, t − n + 1, · · · , t − 1, the state probability distribution at time t can be estimated as follows: n ˆt = X ˆ i Xt−i . λi Q i=1 In many applications, one would like to make use of the higher-order Markov models for the purpose of prediction.
4 Jiangang Cai et al. However, most numerical studies to date are still focused on low Reynolds number or laminar ﬂows around a circular cylinder or sphere, which is important to oil industry but still pretty far away from the real applications in Naval Hydrodynamics. In real Naval Hydrodynamics, the Reynolds number is high and inﬂow is most likely turbulent. Therefore, the numerical simulation of wakes behind juncture of the control surface and sub oﬀ body with high Reynolds number turbulent ﬂow is required to gain more understanding of the complex ﬂow.