基于Z曲线的SARS冠状病毒特征的研究

刺突（Spike）蛋白是SARS（Severe Acute Respiratory Syndmme）冠状病毒表面最重要的膜蛋白，它通过与被感染细胞的受体结合来作为感染的媒介。受此启发，该文利用Z曲线方法，对S蛋白及SARS受体序列进行探究，捕捉到一种SARS病毒的可视化特征。大量序列比对的结果证明该特征是SARS病毒所特有的。将这种特征图谱应用到SARS病毒的检测中，可以提供一种非标准的、简单、直观的检验方法，能够诊断一些利用标准方法难以判断的SARS病例。由此可见，Z曲线作为一种基因序列的几何学研究途径是一种有效的研究方法。     

Promoting Software Reuse Using Self Organizing Maps

Reusability of software, regardless of its utilizing technique, is widely believed to be a promising means for improving software productivity and reliability. However it is not practiced adequately due to the lack of techniques that facilitate the locating of reusable components that are functionally close. In this paper we apply Kohonen's Self-Organizing Maps to develop an approach for promoting Software Reuse. We look at the details of how Self-Organization can arrange and regularize data from the original pattern space into a topology preserving map. We describe a practical implementation of the SOM methodology for Software Reuse using a database of UNIX commands. And finally we briefly present our proposed Software Reuse Methodology.     

C上全纯自映射的完全不变域

设ｆ（ｚ）是Ｃ上全纯自映射，０和是它的本性奇点，其中本文讨论ｆ（ｚ）的完全不变域的性质，证明了如果Ｄ是ｆ（ｚ）的完全不变域，那么Ｄ一定是二连通的且Ｄ包含了的奇异值集；此外，如果ｆ（ｚ）是有限型的，则Ｄ＝Ｆ（ｆ）．由此结论可以推出ｆ（ｚ）最多只有一个完全不变域在Ｆ（ｆ）中     

边际函数的绝对连续性

本文给出边际函数的绝对连续性性质．     

Evaluation of Linguistic Features for Word Sense Disambiguation with Self-Organized Document Maps

Word sense disambiguation automatically determines the appropriate senses of a word in context. We have previously shown that self-organized document maps have properties similar to a large-scale semantic structure that is useful for word sense disambiguation. This work evaluates the impact of different linguistic features on self-organized document maps for word sense disambiguation. The features evaluated are various qualitative features, e.g. part-of-speech and syntactic labels, and quantitative features, e.g. cut-off levels for word frequency. It is shown that linguistic features help make contextual information explicit. If the training corpus is large even contextually weak features, such as base forms, will act in concert to produce sense distinctions in a statistically significant way. However, the most important features are syntactic dependency relations and base forms annotated with part of speech or syntactic labels. We achieve 62.9% ± 0.73% correct results on the fine grained lexical task of the English SENSEVAL-2 data. On the 96.7% of the test cases which need no back-off to the most frequent sense we achieve 65.7% correct results.     

Building ontology based knowledge maps to assist business process re-engineering

Business Process Re-engineering (BPR) is being used to improve the efficiency of the organizational processes, however, a number of obstacles have prevented its full potential from being realised. One of these obstacles is caused by an emphasis on the business process itself at the exclusion of considering other important knowledge of the organization. Another is due to the lack of tools for identifying the cause of the inefficiencies and inconsistencies in BPR. In this paper we propose a methodology for BPR that overcomes these two obstacles through the use of a formal organizational ontology and knowledge structure and source maps. These knowledge maps are represented formally to facilitate an inferencing mechanism which helps to automatically identify the causes of the inefficiencies and inconsistencies. We demonstrate the applicability of this methodology through the use of a case study of a university domain.     

基于可编程图形硬件的实时阴影算法及实现

阴影在增强三维场景真实感方面起着非常重要的作用。随着计算机图形硬件的发展,利用可编程图形硬件加速并提高渲染效果已经成为主要发展趋势。基于当前可编程图形硬件技术,针对目前shadow maps算法存在的问题,提出了一种根据场景特征程序自动生成合适偏移量的实时的阴影生成算法,该算法很好的改善了阴影渲染效果,防止了走样。最后给出了算法基于GLSL着色语言的实现代码。     

Learning multiple experiences useful visual features for active maps localization in crowded environments

Crowded urban environments are composed of different types of dynamic and static elements. Learning and classification of features is a major task in solving the localization problem in such environments. This work presents a gradual learning methodology to learn the useful features using multiple experiences. The usefulness of an observed element is evaluated by a scoring mechanism which uses two scores – reliability and distinctiveness. The visual features thus learned are used to partition the visual map into smaller regions. The robot is efficiently localized in such a partitioned environment using two-level localization. The concept of active map (AM) is proposed here, which is a map that represents one partition of the environment in which there is a high probability of the robot existing. High-level localization is used to track the mode of the AMs using discrete Bayes filter. Low-level localization uses a bag-of-words model to retrieve images and accurately localize the robot. The pose of the robot is the one retrieved from the AM that has maximum a posteriori. Experiments have been conducted on a unique highly crowded data-set collected from Indian roads. The results support the proposed method due to speed and localization accuracy.     

Generalization of the Lambertian model and implications for machine vision

Lambert's model for diffuse reflection is extensively used in computational vision. It is used explicitly by methods such as shape from shading and photometric stereo, and implicitly by methods such as binocular stereo and motion detection. For several real-world objects, the Lambertian model can prove to be a very inaccurate approximation to the diffuse component. While the brightness of a Lambertian surface is independent of viewing direction, the brightness of a rough diffuse surface increases as the viewer approaches the source direction. A comprehensive model is developed that predicts reflectance from rough diffuse surfaces. The model accounts for complex geometric and radiometric phenomena such as masking, shadowing, and interreflections between points on the surface. Experiments have been conducted on real samples, such as, plaster, clay, sand, and cloth. All these surfaces demonstrate significant deviation from Lambertian behavior. The reflectance measurements obtained are in strong agreement with the reflectance predicted by the proposed model. The paper is concluded with a discussion on the implications of these results for machine vision.     

基于混沌消息扩展的Hash函数

构造了一种基于混沌消息扩展的Hash函数,方案中将消息权重矩阵融入时空混沌系统,加强了每个消息块中各字符之间及各消息块之间的联系,构建了统计特性良好的扩展消息,采用4轮64步迭代得到160 bit的消息摘要。和SHA-1算法相比在不明显影响运算效率的前提下安全性得到了提高。