The complexity of multi-domain access control policy integration makes it difficult to understand and manage the policy conflict information. The policy information visualization technology can express the logical rel...The complexity of multi-domain access control policy integration makes it difficult to understand and manage the policy conflict information. The policy information visualization technology can express the logical relation of the complex information intuitively which can effectively improve the management ability of the multi-domain policy integration. Based on the role-based access control model, this paper proposed two policy analyzing methods on the separated domain statistical information of multi-domain policy integration conflicts and the policy element levels of inter-domain and element mapping of cross-domain respectively. In addition, the corresponding visualization tool is developed. We use the tree-maps algorithm to statistically analyze quantity and type of the policy integration conflicts. On that basis, the semantic substrates algorithm is applied to concretely analyze the policy element levels of inter-domain and role and permission mapping of cross-domain. Experimental result shows tree-maps and semantic substrates can effectively analyze the conflicts of multi-domain policy integration and have a good application value.展开更多
Diffusion-weighted magnetic resonance imaging（d MRI） is widely used to study white and gray matter（GM） micro-organization and structural connectivity in the brain. Super-resolution track-density imaging（TDI） is ...Diffusion-weighted magnetic resonance imaging（d MRI） is widely used to study white and gray matter（GM） micro-organization and structural connectivity in the brain. Super-resolution track-density imaging（TDI） is an image reconstruction method for d MRI data, which is capable of providing spatial resolution beyond the acquired data, as well as novel and meaningful anatomical contrast that cannot be obtained with conventional reconstruction methods. TDI has been used to reveal anatomical features in human and animal brains. In this study, we used short track TDI（st TDI）, a variation of TDI with enhanced contrast for GM structures, to reconstruct directionencoded color maps of fixed tree shrew brain. The results were compared with those obtained with the traditional diffusion tensor imaging（DTI） method. We demonstrated that fine microstructures in the tree shrew brain, such as Baillarger bands in the primary visual cortex and the longitudinal component of the mossy fibers within the hippocampal CA3 subfield, were observable with st TDI,but not with DTI reconstructions from the same d MRI data.The possible mechanisms underlying the enhanced GM contrast are discussed.展开更多
Graphical representation of hierarchical clustering results is of final importance in hierarchical cluster analysis of data. Unfortunately, almost all mathematical or statistical software may have a weak capability of...Graphical representation of hierarchical clustering results is of final importance in hierarchical cluster analysis of data. Unfortunately, almost all mathematical or statistical software may have a weak capability of showcasing such clustering results. Particularly, most of clustering results or trees drawn cannot be represented in a dendrogram with a resizable, rescalable and free-style fashion. With the “dynamic” drawing instead of “static” one, this research works around these weak functionalities that restrict visualization of clustering results in an arbitrary manner. It introduces an algorithmic solution to these functionalities, which adopts seamless pixel rearrangements to be able to resize and rescale dendrograms or tree diagrams. The results showed that the algorithm developed makes clustering outcome representation a really free visualization of hierarchical clustering and bioinformatics analysis. Especially, it possesses features of selectively visualizing and/or saving results in a specific size, scale and style (different views).展开更多
In this paper, a method to initiate, develop and visualize an abstract syntax tree (AST) in C++ source code is presented. The approach is in chronological order starting with collection of program codes as a string an...In this paper, a method to initiate, develop and visualize an abstract syntax tree (AST) in C++ source code is presented. The approach is in chronological order starting with collection of program codes as a string and split into individual characters using regular expression. This will be followed by separating the token grammar using best first search (BFS) algorithm to determine node having lowest value, lastly followed by graph presentation of intermediate representation achieved with the help of graph visualization software (GraphViz) while former is implemented using python programming language version 3. The efficacy of our approach is used in analyzing C++ code and yielded a satisfactory result.展开更多
针对多视觉任务中传输成本高、解码端计算压力大的问题,提出一种自适应可伸缩视频编码(adaptive scalable video coding,ASVC)传输框架,将视频分为语义层和背景层,分别传输语义和背景信息。此外,提出一种自适应压缩算法,构建了C4.5决策...针对多视觉任务中传输成本高、解码端计算压力大的问题,提出一种自适应可伸缩视频编码(adaptive scalable video coding,ASVC)传输框架,将视频分为语义层和背景层,分别传输语义和背景信息。此外,提出一种自适应压缩算法,构建了C4.5决策树模型分析网络环境对视频进行压缩的决策判定,并对帧序列进行光流分析,在保留变化显著的帧基础上引入插值机制保持图像的平滑性。仿真结果表明,ASVC方法在不同码率环境下表现更高的识别精准率,视频质量和传输效率的显著提升。展开更多
文摘The complexity of multi-domain access control policy integration makes it difficult to understand and manage the policy conflict information. The policy information visualization technology can express the logical relation of the complex information intuitively which can effectively improve the management ability of the multi-domain policy integration. Based on the role-based access control model, this paper proposed two policy analyzing methods on the separated domain statistical information of multi-domain policy integration conflicts and the policy element levels of inter-domain and element mapping of cross-domain respectively. In addition, the corresponding visualization tool is developed. We use the tree-maps algorithm to statistically analyze quantity and type of the policy integration conflicts. On that basis, the semantic substrates algorithm is applied to concretely analyze the policy element levels of inter-domain and role and permission mapping of cross-domain. Experimental result shows tree-maps and semantic substrates can effectively analyze the conflicts of multi-domain policy integration and have a good application value.
基金supported by grants from the National Basic Research Development Program of China (2011CB707800)the National Natural Science Foundation of China (21790390, 21790392, and 61371014)
文摘Diffusion-weighted magnetic resonance imaging（d MRI） is widely used to study white and gray matter（GM） micro-organization and structural connectivity in the brain. Super-resolution track-density imaging（TDI） is an image reconstruction method for d MRI data, which is capable of providing spatial resolution beyond the acquired data, as well as novel and meaningful anatomical contrast that cannot be obtained with conventional reconstruction methods. TDI has been used to reveal anatomical features in human and animal brains. In this study, we used short track TDI（st TDI）, a variation of TDI with enhanced contrast for GM structures, to reconstruct directionencoded color maps of fixed tree shrew brain. The results were compared with those obtained with the traditional diffusion tensor imaging（DTI） method. We demonstrated that fine microstructures in the tree shrew brain, such as Baillarger bands in the primary visual cortex and the longitudinal component of the mossy fibers within the hippocampal CA3 subfield, were observable with st TDI,but not with DTI reconstructions from the same d MRI data.The possible mechanisms underlying the enhanced GM contrast are discussed.
文摘Graphical representation of hierarchical clustering results is of final importance in hierarchical cluster analysis of data. Unfortunately, almost all mathematical or statistical software may have a weak capability of showcasing such clustering results. Particularly, most of clustering results or trees drawn cannot be represented in a dendrogram with a resizable, rescalable and free-style fashion. With the “dynamic” drawing instead of “static” one, this research works around these weak functionalities that restrict visualization of clustering results in an arbitrary manner. It introduces an algorithmic solution to these functionalities, which adopts seamless pixel rearrangements to be able to resize and rescale dendrograms or tree diagrams. The results showed that the algorithm developed makes clustering outcome representation a really free visualization of hierarchical clustering and bioinformatics analysis. Especially, it possesses features of selectively visualizing and/or saving results in a specific size, scale and style (different views).
文摘In this paper, a method to initiate, develop and visualize an abstract syntax tree (AST) in C++ source code is presented. The approach is in chronological order starting with collection of program codes as a string and split into individual characters using regular expression. This will be followed by separating the token grammar using best first search (BFS) algorithm to determine node having lowest value, lastly followed by graph presentation of intermediate representation achieved with the help of graph visualization software (GraphViz) while former is implemented using python programming language version 3. The efficacy of our approach is used in analyzing C++ code and yielded a satisfactory result.
文摘针对多视觉任务中传输成本高、解码端计算压力大的问题,提出一种自适应可伸缩视频编码(adaptive scalable video coding,ASVC)传输框架,将视频分为语义层和背景层,分别传输语义和背景信息。此外,提出一种自适应压缩算法,构建了C4.5决策树模型分析网络环境对视频进行压缩的决策判定,并对帧序列进行光流分析,在保留变化显著的帧基础上引入插值机制保持图像的平滑性。仿真结果表明,ASVC方法在不同码率环境下表现更高的识别精准率,视频质量和传输效率的显著提升。
