基于CSCW的数据库集成管理系统的设计与实现

分析了CSCW应用系统对数据库系统的要求,简介了CSCW与数据库集成系统的构成和开发环境。同时给出了基于CSCW的数据库集成系统的实现,即如何有效地进行用户数据、群组数据、数据库权限和实时数据等管理功能。为创建计算机支持的群体协同工作环境,快速构造CSCW应用系统,提供了可靠的保证。     

基于组件技术的网上购物系统

为了提高软件的可重用性、软件开发的效率、软件系统的可靠性和灵活性,软件开发技术在传统的结构化程序设计和面向对象的程序设计方法的基础上,发展到了基于组件的开发阶段。文中介绍了系统采用的关键技术———组件技术及基于组件的软件开发过程,然后应用组件技术设计了网上购物系统。实践证明基于组件技术的软件设计方法可以缩短软件开发周期,降低开发费用,增强软件的复用能力。基于组件技术设计的网上购物系统具有很好的可靠性、可维护性以及安全性。     

软件复用机会的识别

软件危机的出现制约了软件规模的进一步发展。软件复用技术成为解决软件危机的一个途径,构件复用是软件复用的一个重要的组成部分。对软件开发者来说,如何着手进行复用,是一个急需解决的问题。文中通过对可复用构件理论的研究,结合在软件开发中的实践经验,总结了识别软件可复用机会的方法和策略,提出了多领域再分析法。给出了该方法的实施步骤、相应技术及策略,建立了相应模型。     

决策树方法在软构件查询中的应用研究

在基于可复用构件库的软件开发中,如何从构件库中查询满足条件的构件是构件库系统的研究重点之一。数据挖掘技术为解决上述问题提供了一条可行的途径,文中对如何利用决策树的分类发现方法进行可复用构件的查询作一探讨。通过对数据挖掘技术的应用,为复用者理解和选取构件提供了一定程度的辅助决策支持,为复用的成功提供了技术保障。     

Genetic algorithms combined with discriminant analysis for key variable identification

Many trouble-shooting problems in process industries are related to key variable identification for classifications. The contribution charts, based on principal component analysis (PCA), can be applied for this purpose. Genetic algorithms (GAs) have been proposed recently for many applications including variable selection for multivariate calibration, molecular modeling, regression analysis, model identification, curve fitting, and classification. In this paper, GAs are incorporated with Fisher discriminant analysis (FDA) for key variable identification. GAs are used as an optimization tool to determine variables that maximize the FDA classification success rate for two given data sets. GA/FDA is a proposed solution for the variable selection problem in discriminant analysis. The Tennessee Eastman process (TEP) simulator was used to generate the data sets to evaluate the correctness of the key variable selection using GA/FDA, and the T² and Q statistic contribution charts. GA/FDA correctly identifies the key variables for the TEP case studies that were tested. For one case study where the correlation changes in two data sets, the contribution charts incorrectly suggest that the operating conditions are similar. On the other hand, GA/FDA not only determines that the operating conditions are different, but also identifies the key variables for the change. For another case study where many key variables are responsible for the changes in the two data sets, the contribution charts only identifies a fraction of the key variables, while GA/FDA correctly identifies all of the key variables. GA/FDA is a promising technique for key variable identification, as is evidenced in successful applications at The Dow Chemical Company.     

From Cards to Code: How Extreme Programming Re-Embodies Programming as a Collective Practice

This paper discusses Extreme Programming (XP), a relatively new and increasingly popular ‘user-centred’ software design approach. Extreme Programming proposes that collaborative software development should be centred on the practices of programming. That proposal contrasts strongly with more heavily instrumented, formalised and centrally managed software engineering methodologies. The paper maps the interactions of an Extreme Programming team involved in building a commercial organisational knowledge management system. Using ethnographic techniques, it analyses how this particular style of software development developed in a given locality, and how it uniquely hybridised documents, conversations, software tools and office layout in that locality. It examines some of the many artifices, devices, techniques and talk that come together as a complicated contemporary software system is produced. It argues that XP's emphasis on programming as the core activity and governing metaphor can only be understood in relation to competing overtly formal software engineering approaches and the organisational framing of software development. XP, it suggests, gains traction by re-embodying the habits of programming as a collective practice. This revised version was published online in August 2006 with corrections to the Cover Date.     

Redundant Sensor Calibration Monitoring Using Independent Component Analysis and Principal Component Analysis

This paper presents a comparison of methods for industrial on-line sensor calibration monitoring for redundant sensors. Principal component analysis (PCA) and independent component analysis (ICA) techniques are developed and compared using both simulated data and data sets from an operating nuclear power plant. The performance is dependent on the types of noise sources; however, under most conditions ICA outperforms PCA, based on the bias and variance of their respective parameter estimates. A case study is included to demonstrate the usefulness of both techniques for the early detection of sensor drift.     

应用质量管理实现500kV线路带电作业的实践

本介绍合肥供电公司如何应用质量管理理论和方法开展质量管理(QC)小组活动，实现500kV线路带电更换四联串耐张绝缘子的创新与实践过程。本成果是全国电力行业QC成果第10名，并获得全国优秀QC成果奖。     

改进BP神经网络在负荷动静比例确定中的应用

指出了电力系统负荷动、静组成比例在实际电力系统分析、计算中的重要性，并应用一种改进的BP算法——Levenberg-Marquardt反向传播算法来对神经网络进行训练，进而利用人工神经网络(ANN)来确定电力系统综合负荷动、静组成比例为β=F[Y(t)，Y(t-1)，…，Y(t-n)，U(t)，U(t-1)，…，U(t-n)]。其中，β为动态负荷在综合负荷中所占的比例，Y=[P，Q]^T。，U=[V，f]^T。该算法改进了BP神经网络学习速度慢的缺点。应用该方法对仿真数据、动模实验数据和现场实测数据进行了测算，得出了其相应的动、静组成比例。测算结果验证了在确定负荷动、静比例时可以忽略频率的变化，证明了BP神经网络用于确定负荷动、静组成比例的有效性。     

实时网损电量的计算及分摊

该文阐述了电源在支路中引起的全电能损耗分量的概念及其叠加原理，及节点阻抗矩阵为基础的算法，推导了全电能损耗分量的精确计算公式。全电能损耗分量既包含了各电源单独作用时的电能损耗，又包含了电源间交叉作用项的电能损耗，仅与本身的电流分量共轭值有关，从而避免了网损分摊中对交叉项的粗略处理。实时网损电量计算的重要步骤是对全损耗功率分量分时段积分求和，采样间隔长短可调节以满足要求的精确度。在此基础上提出了按电源在支路中引起的全电能损耗分量公平分摊网损的新方法，分摊原则是谁引起的损耗由谁承担，该方法克服了网损分摊中人工指定分配因子及按功率比例分摊网损的不足。