讨论并比较了Internet数据库访问的两层和三层两种模式，描述了实现Internet数据库的CGI，API，JDBC三种方式。通过理论分析和数据测试，说明了在对Internet数据库访问性能上，JDBC方式优于CGI方式，API方式优于JDBC方式。

The existence, uniqueness, globally exponential stability and speed of exponential con-vergence for a class of cellular neural networks are investigated. The existence of a unique equilibrium is proved under very concise conditions, and theorems for estimating the global convergence speed approaching the equilibrium and criteria for its globally exponential stability are derived, Considering synapse time delay, by constructing appropriate Lyapunov functional, the existence of a unique equilib-rium and its global stability for the delayed network are also proved. The results, which do not require the cloning template to be symmetric, are easy to use in network design.

在总结传统软件开发方法经验的基础上，严格遵守软件开发方法原则，从UML建模思想出发，对传统UML三层抽象建模结构进行了分析，并引入“抽象”和“分解”作为UML建模的核心思想；提出了UML分层抽象建模机制的构想，将计算机系统开发过程概括为对功能信元、结构信元、关联信元、实现信元和集成信元的提取过程，并以此作为UML建模的指导，有效了利用UML完整语义定义，克服了传统面向对象开发方法的缺陷，实现了建模过程从需求到分析的过渡以及功能和实现事实上的分离。

In this paper, a system architecture of data mining in network based on the technology of Mobile Agent and RDF is presented. This system architecture provides a standard and uniform structured data-platform for the con-crete data-mining application. Mobile Agent implements the concrete data mining application. The relative technolo-gies of this system architecture are introduced first, then two species of logic architecture of the network based appli-cation system are explained. And an accomplished prototyping of network-based data mining system architecture is proposed. The combination of the up-to-date XML/RDF and Mobile Agent technologies provides a new method for data mining in network.

In the Mobile Decision Support System(MDSS), the key problems of the decision-making technology based on multiple analytical sources are how to articulateand represent the user's global decision-making requests, and then decompose and map them to local analyzing requests on each DSS analytical source, as well as how to integrate the heterogeneous analyzing results. This article develops an object-subject model (OSM) which is based on decision-making subjects. By means of subjects and their operations, the OSM model unifies the decision-making capabilities supplied by varied DSS analytical sources so as to facilitate the formulation of the user's global requests and the inte-gration of heterogeneous analyzing results. Then the article describes the OSM-based algorithms of the formulation and decomposition of the user's global decision-making requests, the dispatching of analysis agents and the integration of the analyzing results.

提出了一种基于Web数据库系统设计、实现和性能调优的新方法，该方法包括由RDBMS配置优化、应用模式设计优化和编程优化。通过内存、分段、磁盘参数和时间相关参数的优化可以设置一个好的RDBMS运行环境。在编程时，通过减少与后台连接和断开操作、建立和使用索引、多用存储过程和优化SQL语句可以优化系统性能。在应用设计时，通过优化应用逻辑和降低规范化可以大大地改善系统性能。

本文通过对现有网络中服务类别的分析、归纳，针对现有的分层网络体系结构存在的层间功能重叠和复杂的分层处理过程所带来的网络服务效率低下的问题，提出了一种基于服务元的网络体系结构。服务元只提供服务，不接受服务，所以避免了层间交互和服务传递的开销。服务元不仅能为本节点应用提供服务，而且不同节点的服务元可以合作向某一节点或整个网络提供服务。本文给出了微通信元系统构架，它是一种易于从TCP/IP过渡的服务元网络体系结构的构架。作为微通信元的服务元被组织成微通信系统，大量的微通信系统被组织成网络系统。微通信元系统构架具有简洁、可扩展和容易实现的特点。

A new event-handling paradigm and its application model are proposed. The working mechanism and principle of event listener model is given in detail. Finally, the launching event mechanisms, the choosing event handling models and the dispatching mechanism are illustrated.

文中提出了基于Multi-MobileAgent技术的个性化数据挖掘模型，介绍了该模型各个组成部分的功能，以及多个Agent之间如何相互协作完成个性化的数据挖掘，并给出了相关的算法。

rincipal component analysis(PCA) by neural network is an adaptive statistical signal processing method which has many applications Since many PCA neural networks do not converge globally, it is nature to study the global convergence of PCA learning algorithm. In this paper, the previous works on the globally convergent PCA neural networks are presented first. Then based on the mismatch of previous PCA neural networks, we propose and analyze a PCA learning algorithm. This algorithm is convergent globally. And a rigorous mathematical proof is given. Simulation results show the efiiciency and effectiveness ofthis algorithm.