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To compress multiview video and depth information, we synthesize a virtual image for the current view using color and depth data of neighboring views. In this article, we then use a view interpolation prediction scheme at the virtual image to improve the inter-view prediction. We also propose a solution for overlapping regions and empty holes that are generated during the intermediate view synthesis process due to occlusion and disocclusion situations. Experimental results show that the proposed methods achieve approximately 0.65 dB of Peak Signal-to-Noise Ratio (PSNR) gain on average for multiview depth data and 0.17 dB of PSNR gain for multiview video coding, compared with the reference software, Joint Multiview Video Model 1.0. We also show that our method is even more powerful for smaller search ranges. Furthermore, we examine the effects of inter-view prediction on hierarchical Bpictures. V

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The recent diversification in terms of the scope and techniques used for simulations has highlighted the importance of analyzing state of the art trends and applying these for educational and study purposes. While qualitative methods such as literature research or experts' assessments have previously been used, such methods are in fact likely to reflect the subjective viewpoint of experts, and to involve too much time and money for the results obtained. For the purpose of an objective analysis, a quantitative analysis that included the examination of topics found in domestic academic journal articles was conducted in the present study. In this regard, simulation was found to be most actively used domestically in the electrical and electronic fields. In addition, simulation was also found to be employed for the purpose of education and entertainment in the social sciences. The results of this study are expected to help to facilitate the prediction of the direction of the development of not only the Korea Society for Simulation, but also domestic simulation studies. This study also raises the possibility of applying text mining to trend analysis, and proves that it can be a useful method for deriving future key topics and helping experts' decisions regarding quantitative data.