锁相技术在电子束曝光机工件台稳速控制中的应用

采用锁相技术，对电子束曝光机工件台运动实现速度环的全数字控制。设计了数字差频积分回路和数字差频比例控制器，能有效消除速度的静态误差和改善系统的动态特性。     

Optimisation of fault-tolerant fabric-cutting schedules using genetic algorithms and fuzzy set theory

In apparel industry, manufacturers developed standard allowed minutes (SAMs) databases on various manufacturing operations in order to facilitate better scheduling, while effective production schedules ensure smoothness of downstream operations. As apparel manufacturing environment is fuzzy and dynamic, rigid production schedules based on SAMs become futile in the presence of any uncertainty. In this paper, a fuzzification scheme is proposed to fuzzify the static standard time so as to incorporate some uncertainties, in terms of both job-specific and human related factors, into the fabric-cutting scheduling problem. A genetic optimisation procedure is also proposed to search for fault-tolerant schedules using genetic algorithms, such that makespan and scheduling uncertainties are minimised. Two sets of real production data were collected to validate the proposed method. Experimental results indicate that the genetically optimised fault-tolerant schedules not only improve the operation performance but also minimise the scheduling risks.     

一种供应链中的知识管理绩效评价方法研究

作为知识管理的重要组成部分，知识管理绩效评价旨在帮助企业找出影响绩效提高的关键因素并及时采取有效措施，提高知识管理水平。本文从创造顾客价值、知识的获取能力、知识的共享与传播能力、知识的运用水平、知识的存量水平和知识管理平台等六个方面，分析了评价供应链的知识管理绩效应考虑的主要因素，建立了供应链的知识管理绩效评价指标体系，在此基础上，提出了运用D-S证据推理方法，对供应链知识管理绩效进行评价，并给出了证据推理的算法步骤，最后通过算例分析，说明该方法的有效性、实用性。     

基于机器视觉的离散傅里叶变换目标识别方法

提出了一种基于机器视觉与离散傅里叶变换的目标特征识别方法。利用计算机图像技术采集和处理图像信号;利用离散的傅里叶变换对图像数据提取特征,能够更好的辨别数据细节,从而可通过图像的比对来实现目标的识别。该方法在对实际的静止图像进行处理与计算后,能够很好的对图像的细节变化进行识别。     

基于SVM局部后验概率融合方法研究

研究了基于支持向量机的后验概率的应用,提出了对样本集进行分解,以产生局部后验概率,根据模式的稳健性对局部后验概率进行凸组合融合的方法.     

触摸输入技术探析

本文扼要概述触摸输入的４种技术，及其应用与性能比较。     

基于"替换法"的汉字加、解密实现技术

文章讨论的基于“替换法”的汉字信息加、解密实现技术,改变了传统的汉字加密结果,使加密后的密文仍是可以识别和再利用的汉字,发送者可以在任何可编辑汉字的通讯设备上发送和接收密文,确保中文信息传输过程中的安全性。加、解密算法实现的代码语言为VFP6.0。     

半导体元件清洗技术浅谈

随着社会的进步和科学技术的迅猛发展,对洗净技术的要求也越来越高。清洗方式多种多样,但最主要的是突出在喷射清洗和超声波清洗两大方面,应用于全国各行各业,并且也得到了明显进步。     

Support vector machine via nonlinear rescaling method

In this paper we construct the linear support vector machine (SVM) based on the nonlinear rescaling (NR) methodology (see [Polyak in Math Program 54:177–222, 1992; Polyak in Math Program Ser A 92:197–235, 2002; Polyak and Teboulle in Math Program 76:265–284, 1997] and references therein). The formulation of the linear SVM based on the NR method leads to an algorithm which reduces the number of support vectors without compromising the classification performance compared to the linear soft-margin SVM formulation. The NR algorithm computes both the primal and the dual approximation at each step. The dual variables associated with the given data-set provide important information about each data point and play the key role in selecting the set of support vectors. Experimental results on ten benchmark classification problems show that the NR formulation is feasible. The quality of discrimination, in most instances, is comparable to the linear soft-margin SVM while the number of support vectors in several instances were substantially reduced.     

台达变频器在纺织织带盘带机上的应用

盘带机是纺织织带成品分卷设备，需要使用到收放卷控制。本文基于台达变频器在盘带机上的应用案例，论述盘带机自动化系统设计调试过程以及遇到的问题分析。