一种Web目录服务系统的设计与实现

DSFW是目录服务标记语言（DSML）的微软版本。它使得应用程序可以利用XML来读取和写入活动目录（AD）或活动目录应用程序模式（ADAM），后两者均是基于轻型目录访问协议的目录。本文介绍一种基于DSFW和ADAM的Web目录服务系统模型的设计与实现。     

A new family of proximity graphs: Class cover catch digraphs

Motivated by issues in machine learning and statistical pattern classification, we investigate a class cover problem (CCP) with an associated family of directed graphs—class cover catch digraphs (CCCDs). CCCDs are a special case of catch digraphs. Solving the underlying CCP is equivalent to finding a smallest cardinality dominating set for the associated CCCD, which in turn provides regularization for statistical pattern classification. Some relevant properties of CCCDs are studied and a characterization of a family of CCCDs is given.     

On the optimal allocation of two active redundancies in a two-component series system

Components C₁ and C₂ form a series system. Suppose we can allocate the spare R₁ in parallel with C₁ and the spare R₂ in parallel with C₂, or otherwise, allocate R₁ with C₂ and R₂ with C₁. In this paper, we compare these two options using hazard rate ordering.     

空间有源消声的微机控制

本文讨论用通用微机控制空间有源消声．以修正的PID（比例、积分、微分）算法加上逻辑判断构成的控制软件，使得系统收敛迅速，跟踪速度快，消声效果令人满意，而且系统工作稳定可靠，     

自动线性跟踪Butterworth有源滤波器研究

滤波是通信、测试、数据采集和实时控制等领域至关重要的环节。通常的模拟滤波器，由于截止频率固定，在某些宽频率动态范围且有实时性要求的应用场合，往往达不到预期的滤波效果，有时甚至影响整个系统的正常运行。本文从有源滤波器的机理分析入手，提出了一种由单片机参与的滤波系统，它能自动跟踪输入信号频率，线性地选择合适的滤波器截止频率，弥补了原有滤波器的不足。     

优化设计性实验教学培养学生的科学素质

通过论证设计性实验与科学素质之间的关系，提出体现培养科学素质的问题式学习模式，并在大学物理实验教学中进行了教学改革试验。     

半导体激光器列阵有源区电场随电流变化的定点测量

采用连续波电光检测法，对ＧａＡｓ／ＧａＡｌＡｓ双异质结激光器列阵有源区进行定点测量，实验结果反映了发光区内及发光区外电场随电流变化的不同规律。文中对实验结果给出了合理解释。     

Action learning versus strategy learning

This article seeks to ascertain whether the strategy‐learning model of Hanaki, Sethi, Erev, and Peterhansl (2003) better accounts for observed behavior than do the various action‐learning models. It does so by measuring the goodness‐of‐fit of the models' predictions against published experimental results for such games as Coordination, Prisoner's Dilemma, and Chicken. The fit is measured via the mean squared deviation (MSD) between the observed behavior and the one predicted by the model. The results show that, for Chicken, the strategy‐learning model fits the observed data much better than do the action‐learning models. The best action‐learning model, on the other hand, fits the observed data well in Coordination. Overall, the strength of the strategy‐learning model is best shown in games where alternations between the two stage‐game Nash equilibria are often observed in the laboratory experiments. © 2004 Wiley Periodicals, Inc. Complexity 9: 41–50, 2004     

A hybrid active noise controller for finite ducts

A hybrid active noise controller (ANC) is proposed to solve some existing problems, which are related to the non-minimum phase (NMP) path models between uncollocated sensors and actuators in many ANC systems. For hybrid ANC schemes, the NMP path causes design difficulties to both feedforward and feedback control. These problems can be solved effectively by adding an extra actuator in the ANC system. A new design procedure is presented to take the greatest advantage of the extra actuator. Theoretical analysis and experimental results are presented to show the improved performance of the proposed ANC.     

Widrow-cellular neural network and optoelectronic implementation

A new type of optoelectronic cellular neural network has been developed by providing the capability of coefficients adjusment of cellular neural network (CNN) using Widrow based perceptron learning algorithm. The new supervised cellular neural network is called Widrow-CNN. Despite the unsupervised CNN, the proposed learning algorithm allows to use the Widrow-CNN for various image processing applications easily. Also, the capability of CNN for image processing and feature extraction has been improved using basic joint transform correlation architecture. This hardware application presents high speed processing capability compared to digital applications. The optoelectronic Widrow-CNN has been tested for classic CNN feature extraction problems. It yields the best results even in case of hard feature extraction problems such as diagonal line detection and vertical line determination.