STUDY ON RESIDUES OF ~（14）C－FENITROTHION IN MODEL RICE－FISH ECOSYSTEM AND FIELD RICE－FISH ECOSYSTEM

ＳＴＵＤＹＯＮＲＥＳＩＤＵＥＳＯＦ~（１４）Ｃ－ＦＥＮＩＴＲＯＴＨＩＯＮＩＮＭＯＤＥＬＲＩＣＥ－ＦＩＳＨＥＣＯＳＹＳＴＥＭＡＮＤＦＩＥＬＤＲＩＣＥ－ＦＩＳＨＥＣＯＳＹＳＴＥＭＺｈａｎｇＺｈｏｎｇｌｉａｎｇ（张仲良）；ＷａｎｇＨｕａｘｉｎ（王化新）；Ｇ?..     

Measurement selection for parametric IC fault diagnosis

This article presents experimental results which show feedforward neural networks are well-suited for analog IC fault diagnosis. Boundary band data (BBD) measurement selection is used to reduce the computational overhead of the FFN training phase. We compare the diagnostic accuracy between traditional statistical classifiers and feedforward neural networks trained with various measurement selection criteria. The feedforward networks consistently perform as well as or better than the other classifiers in term of accuracy. Training using BBD consistently reduces the FFN training efforts without degrading the performance. Experimental results suggest that feedforward networks provide a cost efficient method for IC fault diagnosis in a large scale production testing environment.This work is supported by NSF-IUC CDADIC, Project 90-1.     

加氢装置高压进料泵的特点及选用

结合API610及工程设计的实际 ,讨论了高压进料泵的特点及选用     

中国新移动运营商3G发展策略

通过对3G的市场分析、技术分析、制式选择关键因素分析和经济分析,得出了中国新移动运营商3G的发展策略。无论从基于频率资源与制式关系的考虑,基于选择3G主流制式的考虑,还是从基于利用非对称频段资源、采用TD-SCDMA混合组网的考虑,对新的运营商来说,采用WCDMA来建设移动通信系统都是必要和有利的选择。     

基于供应链管理的供应商选择问题初探

首先讨论了供应链环境下选择供应商的意义，然后建立了供应商选择的评价指标体系，重点讨论了应用TOPSIS 方法对供应商选择的模型及算法，最后用一个简单的案例进行了说明。     

一种结合知识挖掘的进化规划算法

进化规划是一种进化计算方法。进化规划主要使用随机化技术来实现优化过程。与其它进化算法相比,进化规划只有变异操作,而没有交叉操作,因此变异操作的有效性对进化规划算法的成功至关重要。在传统进化规划算法中,进化规划的变异操作具有完全的随机性,这虽然有利于避免局部极值,但却导致较大的计算量。在本文算法中,将知识挖掘技术引入进化规划之中。知识挖掘技术主要用于发现规则,然后利用发现的规则指导变异操作过程,提高变异操作的效率。最终加快了进化规划算法的速度,而计算效果没有明显下降。通过知识挖掘技术的引入,进化规划算法有了初步的智能特性。将本文所介绍的新算法应用于视频编码的运动估计实验中,结果表明新算法有良好的计算速度和计算精确性。     

DCS的评价与选择

本文综述了ＤＣＳ（集散控制系统）三代产品的总体水平评价，介绍了ＤＣＳ的总体性能、评价指标和它的选择准则。     

AutoCAD图形的打印输出技巧

针对AutoCAD使用者出图时所遇到的问题,提供了两种不同的解决方法.     

Interactive key frame selection model

Video summarization can provide a fine representation of the content of video stream and reduce a large amount of data involved in video indexing, browsing, and retrieval. Moreover, Key frame selection is an important step in the research of content-based video analysis and retrieval. Although there exist a variety of methods for key frame selection, they are heuristic and closed systems, which cannot dynamically generate video summary with user’s preference. In this paper, an M-estimator and epipolar line distance constraint camera motion estimation algorithm is introduced as camera parameters is an important motion feature for key frame selection, and Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is applied to optimize estimated parameters. Moreover, since Interactive Computing is a novel-computing model that represents the transition of algorithm to interaction, an interactive model of key frame selection (IKFS) is presented as a result of improving the model of key frame selection (KFS). The model of KFS and IKFS are proved to satisfy the criterion of induction and coinduction, respectively. Experimental results show that the processing scheme generates flexible and desirable summarizations whose distortion rate is lower than current method. Above all, IKFS is an extension to KFS.