模糊C-球壳聚类算法及其在血液细胞图像中的应用

文章从经典的模糊C均值算法开始通过改变其中相似性的度量形式，介绍了一种模糊C球壳聚类（FCSS）算法。在将该算法应用于细胞显微图像半径统计时，采用基于形态学的图像预处理措施，可以获得FCSS算法中有关原型模式的知识，加快收敛速度并避免随机初始化造成的局部极小问题。     

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本文应用灰色关联分析方法,对70种不同类型和组成的钻井液,进行了两参数流变模式优选及评价。与现行方法比较的结果表明此方法与现行结果的吻合度高,并有新颖、数据要求量少、结论易于比较等优点。     

应用灰色动态模型对事故进行预测分析

利用灰色动态模型的主要方法和观点,分析企、事业发生的工伤事故(损失工作日),建立灰色数据预测模型GM(1,1)的基本模型和微分方程式,并根据累加生成数列结果,预测事物进一步发生、发展的规律,从而预测其在今后一段时间内的变化。最后对统计实例进行计算和相关关联度分析,精度达88％,拟合程度较好。此方法对企、事业单位的安全生产有一定的指导意义。     

A Unified View on Clustering Binary Data

Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This paper studies the problem of clustering binary data. Binary data have been occupying a special place in the domain of data analysis. A unified view of binary data clustering is presented by examining the connections among various clustering criteria. Experimental studies are conducted to empirically verify the relationships.     

触觉传感器及其图象识别

本文讨论了两种触觉传感器,系统地阐述了这两种触觉传感器的数据采集系统和图象二值化的有关算法。     

利用U矩阵对SOM网络的处理

自组织神经网络的最大优点是能够保持原始数据的拓扑结构。但是当数据量很大的时候，自组织神经网络的神经元的数据也随之增大。因此为了更好地对数据进行分析，需要将自组织神经网络中相似的神经元进行分组，也就是聚类。在对SOM网络进行再次分析之前，为了减少“噪音”数据和孤立点对聚类结构的影响，用U矩阵的变型方法对自组织神经网络分析的结果进行预处理。     

用有限带宽反射波波形分析法进行储层横向预测

以正演地震模拟为基础的有限带宽反射波渡形分析法是一种新的储层横向预测方法。首先利用波形分解确定地震反射层的地质属性,找出能反映岩性变化的反射波波形特征参数;然后,采用多元数据聚类分析和灰色系统理论完成储层横向的预测。文中以预测江苏 J 凹陷 F 构造上阜二段生物灰岩分布及厚度横向变化为例,简述了反射波波形分析的全过程。预测结果已为钻探证实。     

一种基于Web文本聚类的用户兴趣发现模型的研究

研究了一种基于Web文本聚类的用户兴趣发现方法．他通过Web文档信息获取，文本的形式表示，以及Web文本聚类方法最终提取用户兴趣知识，并给出了一个设计模型。     

缓解开封市水资源短缺的技术及工程措施研究

需水量的科学预测是制定水资源开发利用规划的基础和前提,对于实现区域水利工程规划、水资源合理配置和社会经济和谐发展具有重要意义。预测了开封市规划水平年的需水量,分析了开封市水资源可利用量,提出了缓解开封市水资源供需紧张的技术措施、工程措施和管理措施,对社会经济的可持续发展起到了重要的作用。     

Studies of substrate specificities of lipases from different sources

Although lipases are widely applied in a wide variety of reactions, available information on the factors that are responsible for the substrate specificities of lipases from different sources is scarce. In this paper, nine lipase‐producing microorganism strains were isolated from oil‐containing samples. The properties of these enzymes, including pH optima, temperature optima, thermal stability, and pH stability, vary significantly with the different sources from which these lipases were isolated. The substrate specificities of the nine lipases, including fatty acid and positional specificities, were also studied. The fatty acid specificities of the nine lipases were observably different toward 15 substrates with different carbon chain lengths, different saturation degrees and different side chains. The lipases from S₃ Penicillium citrinum (PCL), MJ₁ Aspergillus niger (ANL), MJ₂ Aspergillus oryzae (AOL), YM Bacillus coughing (BCL), S₉ Geotrichum candidum (GCL), and S₁₁ Candida lypolytica (CLL) showed the strongest specificities to short‐chain esters, and the other lipases showed strong selectivity for medium‐ or long‐chain and branched esters. The positional specificities were examined by analyzing the hydrolytic products of triolein catalyzed by the nine lipases, using TLC. The lipases can be mainly classified into two groups by their specificities for the ester bond at position 2 of triglycerides; one group can selectively hydrolyze the ester bond at position 2 of the triglycerides, the other group cannot. All these nine lipases were divided into four groups by hierarchical clustering analysis on the basis of the results of fatty acid and positional specificities.