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Simplified models for dark matter searches at the LHC 期刊论文  OAI收割
PHYSICS OF THE DARK UNIVERSE, 2015, 卷号: 2016-09-10, 期号: 0, 页码: 8-23
作者:  
Abdallah, J;  Araujo, H;  Arbey, A;  Ashkenazi, A;  Belyaev, A
收藏  |  浏览/下载:35/0  |  提交时间:2016/11/21
Simplified Wave Models Applicability to Shallow Mud Flows Modeled as Power-Law Fluids 期刊论文  OAI收割
Journal of Mountain Science, 2014, 卷号: 11, 期号: 6, 页码: 1454-1465
Cristiana DI CRISTO; Michele IERVOLINO; Andrea VACCA
收藏  |  浏览/下载:25/0  |  提交时间:2014/11/18
An improved algorithm to generate high quality progressive animation models (EI CONFERENCE) 会议论文  OAI收割
2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010, April 23, 2010 - April 25, 2010, Wuhan, China
作者:  
Zhao J.;  Zhang S.
收藏  |  浏览/下载:23/0  |  提交时间:2013/03/25
In computer graphics  investigation has been made in many years in progressive models generation to alleviate the workload of visualization processing. However  most of the existing algorithms only focus on static meshes  and very little works are to deal with animation models. In this paper  we propose an improved method for generating progressive multiresolution animation models. By the method we first use a normal deviation parameter to improve the famous QEM method as our basic edge contraction metric to generate a base hierarchy. The sequence of the simplified models is generated progressively from the first frame to the last one. Based on the edge contraction sequence in the previous frame  the contraction order in the current frame is adjusted according to the deformation degree. We demonstrate that our method works efficiently and can generate better approximations with well-preserved features than previous methods. 2010 IEEE.