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。     

一种用MATLAB实现的基于小波变换的图象水印技术

论文给出了一种在小波变换域中对静态图像加水印的方案。方案利用了小波分析的优良性质,对小波变换后的载体图像系数块,按水印图像小波变换后的系数块大小进行分块,将分得的系数子块按不同层次不同方向重复嵌入相应的水印系数块。通过与原始载体图像进行比较实现水印的提取。最后与嵌入的水印进行相关性检测来检测提取出的水印是否有效。实验结果表明这个方案取得了良好的效果。     

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．     

一般化的灰SOM模型及其性能评估

自组织特征映射是Kohonen提出的一种人工神经网络模型，它能把高维的信息数据以有序方式映射到低维空间上，形成一种拓扑意义上的有序图，但其权值的调整仅考虑了学习率及输入模式与获胜神经元及其邻域，却忽略了输入模式分量与全体参与竞争的神经元权值向量间的某种相关关系。Hu等人利用灰关系系数(GRC)的描述方法显式地刻画这种关系。尽管如此，但GRC仍忽略了输入模式与所有参与竞争的神经元权值间的整体描述关系。该文通过在GRC中引入该整体关系，提出了一个一般化的灰关系模型G^2SOM，并将GSOM作为其特例，进而侧重就三种特殊的函数关系进行了性能评估，最后，通过实验验证了G^2SOM的有效性与可行性。     

地形图点状虚线的自动矢量化研究与实现

虚线的矢量化一直是地形图自动识别的难点之一。文章通过人眼对虚线视觉感知特性的分析，提出了基于点与点之间相互作用的视觉组织模型。根据感知的类似性对地图图像进行形态滤波，然后运用有界深度优先搜索法生成初始种子段，提出可变形模型迭代算法实现对虚线的自动跟踪矢量化。从理论分析及实验结果得出，本算法是行之有效的，具有稳定性好、易于实现的特点。     

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.     

Geometrical study of the three-dimensional temperature–composition diagrams. An important aid to understand the behavior of the liquid–vapour equilibrium in ternary systems

In this work the usefulness of qualitatively studying and drawing three-dimensional temperature–composition diagrams for ternary systems is pointed out to understand and interpret the particular behavior of the liquid–vapour equilibrium of non-ideal ternary systems. Several examples have been used in order to highlight the interest and the possibilities of this tool, which should be an interesting support not only for lecturers, but also for researchers interested in experimental equilibrium data determination.     

A weighted full-reference image quality assessment based on visual saliency

In full reference image quality assessment (IQA), the images without distortion are usually employed as reference, while the structures in both reference images and distorted images are ignored and all pixels are equally treated. In addition, the role of human visual system (HVS) is not taken account into subjective IQA metric. In this paper, a weighted full-reference image quality metric is proposed, where a weight imposed on each pixel indicates its importance in IQA. Furthermore, the weights can be estimated via visual saliency computation, which can approximate the subjective IQA via exploiting the HVS. In the experiments, the proposed metric is compared with several objective IQA metrics on LIVE release 2 and TID 2008 database. The results demonstrate that SROCC and PLCC of the proposed metric are 0.9647 and 0.9721, respectively,which are higher than other methods and it only takes 427.5 s, which is lower than that of most other methods.