应用于JBIG2的一种文档图像分割方法

JBIG2是即将实施的文档图像压缩编码标准，主要应用于传真，互联网和无线传输，其编码对象是文字与二值图像的混合文档，通过对特定内容采用特定的模式算法进行编码，图像分割是编码的第一步工作，文中在简述JBIG2标准后，通过对文字和二值图像的特征分析，提出了一种新的与轮廓无关的文档分割算法，快速准确具有一定的适应性，经过实验证明，该方法比较有效。     

蛋白质结构型预测的研究

以 nα、nβ、nβαβ、n4α、n4β等五个二级结构参数为基础 ,用离散增量研究了蛋白质的聚类和蛋白质的结构型预测 .α型 ,β型和 αβ型可以很好地分别聚在三个大支中 .蛋白质结构型预测总体预测正确率为 82 % ,用 Self-consistency和 Jake-knife这两种方法测试的结果没有明显的差别 .从结果可以看出利用蛋白质的二级结构参数能较好地体现出各种结构型蛋白质的特点 .     

一种基于主元递归分析法的多模糊逻辑系统的组合形式

根据多个模型相加可以提高整体预测精度和鲁棒性的思想，提出了一种具有递阶特点的模糊逻辑模型。该模型采用基于山峰函数的减法聚类算法，将样本数据集分成多组来进行局部模糊模型的建立和训练，大大提高了组合模糊逻辑模型的训练效率。各局部模糊系统的预测输出通过主元递归分析法（PCR）连接，解决了模型之间的严重相关性问题，增强了模型的预测能力，提高了模型的鲁棒性。仿真结果表明，组合多个模糊逻辑模型能够达到比局部模型更好的建模效果，并能有效的改善模型的预测能力和泛化能力。     

Direct multicriteria clustering algorithms

In a multicriteria clustering problem, optimization over more than one criterion is required. The problem can be treated in different ways: by reduction to a clustering problem with the single criterion obtained as a combination of the given criteria; by constrained clustering algorithms where a selected critetion is considered as the clustering criterion and all others determine the constraints; or by direct algorithms. In this paper two types of direct algorithms for solving multicriteria clustering problem are proposed: the modified relocation algorithm, and the modified agglomerative algorithm. Different elaborations of these two types of algorithms are discussed and compared. Finally, two applications of the proposed algorithms are presented. Elaborated version of the talks presented at the First Conference of the International Federation of Classification Societies, Aachen, 1987, at the International Conference on Social Science Methodology, Dubrovnik, 1988, and at the Second Conference of the International Federation of Classification Societies, Charlottesville, 1989. This work was supported in part by the Research Council of Slovenia.     

Self-Expanded Clustering Algorithm Based on Density Units with Evaluation Feedback Section

This paper presents an effective clustering mode and a novel clustering result evaluating mode. Clustering mode has two limited integral parameters. Evaluating mode evaluates clustering results and gives each a mark. The higher mark the clustering result gains, the higher quality it has. By organizing two modes in different ways, we can build two clustering algorithms： SECDU（Self-Expanded Clustering Algorithm based on Density Units） and SECDUF（Self-Expanded Clustering Algorithm Based on Density Units with Evaluation Feedback Section）. SECDU enumerates all value pairs of two parameters of clustering mode to process data set repeatedly and evaluates every clustering result by evaluating mode. Then SECDU output the clustering result that has the highest evaluating mark among all the ones. By applying ＂hill-climbing algorithm＂, SECDUF improves clustering efficiency greatly. Data sets that have different distribution features can be well adapted to both algorithms. SECDU and SECDUF can output high-quality clustering results. SECDUF tunes parameters of clustering mode automatically and no man＇s action involves through the whole process. In addition, SECDUF has a high clustering performance.     

The refinement algorithm consideration in text clustering scheme based on multilevel graph

To construct a high efficient text clustering algorithm, the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed, The model is applied to text clustering. The performance of clustering algorithm has to be improved with the refinement algorithm application, The experiment result demonstrated that the muhilevel graph text clustering algorithm is available,     

Neuromuscular synaptogenesis: clustering of acetylcholine receptors revisited

Clustering of neurotransmitter receptors in the postsynaptic membrane is critical for efficient synaptic transmission. During neuromuscular synaptogenesis, clustering of acetylcholine receptors (AChRs) is an early sign of postsynaptic differentiation. Recent studies have revealed that the earliest AChR clusters can form in the muscle independent of motorneurons. Neurally released agrin, acting through the muscle-specific kinase MuSK and rapsyn, then causes further clustering and localization of clusters underneath the nerve terminal. AChRs themselves are required for agrin-induced clustering of several postsynaptic proteins, most notably rapsyn. Once formed, AChR clusters are stabilized by several tyrosine kinases and by components of the dystrophin/utrophin glycoprotein complex, some of which also direct postnatal synaptic maturation such as formation of postjunctional folds. This review summarizes these recent results about AChR clustering, which indicate that early clustering can occur in the absence of nerves, that AChRs play an active role in the clustering process and that partly different mechanisms direct formation versus stabilization of AChR clusters. Received 10 April 2002; received after revision 4 June 2002; accepted 10 June 2002     

基于Lotus Notes的MIS系统开发的研究与实践

简要介绍公文流转型MIS系统的特点,Lotus Notes的优势,阐述《宜晶超高压管理处办公自动化系统》的设计思想,设计方案,系统实现,并对开发过程中灵活设置公文流转,自动会签功能及利用文档链接技术简化流程等关键问题的解决方法和技巧提出见解。     

计算机教学机房的建设、管理与维护

针对计算机教学机房的建设、管理与维护,介绍了一些有效可行的保证机房正常、稳定运行的“软”保护方法,不需任何投资、不存在兼容性问题,且快速、方便。     

机关科室文件资料的档案化管理初探

论述了机关科室文件资料的管理现状，说明机关科室文件资料档案化管理的必要性及科室文件资料如何进行档案化管理，提出文件资料档案管理的问题。