纤维素酶分子的计算机辅助序列分析

利用生物大分子数据库（EMBL、SWALL和PDB）及软件技术（DNASIS和AntheProt）对嗜热子囊菌（Thermoascus aurantiacus)的产生的一种纤维素酶分子进行了序列分析及结构预测；通过多种来源的纤维素酶的比较研究，分析了其催化区、活性位点及局部保守序列。     

一种基于区域分割的多级环境建模方法

针对现有移动机器人路径规划中各种环境建模方法存在使用范围有限、复杂问题处理能力不足和运行效率低、缺乏灵活性等问题，结合二维半描述和知识利用原理，提出了一种可以比较圆满地解决诸如建筑物内不同楼层连接、室内室外环境交替出现等实用结构性空间问题的基于区域分割的多级环境建模方法。     

镧系钙钛矿型氧化物（LaBO3）的催化氧化性能及其净化效果的研究

本文在气相色谱仪联用微反应器装置上,研究了LaBO_3型催化剂中的B位元素对催化氧化活性的影响规律,并进行了程序升温脱附实验。另外,还对LaBO_3型载体催化剂进行了活性筛选,并在柴油机台架上与贵金属Pt/Al_2O_3进行了有害气体净化效果的对比实验。实验结果表明,LaBO_3氧化物中LaMnO_3对CO、CH_4的催化氧化活性最高,且CO、CH_4活性中心并不一致。LaMnO_3/γ-Al_2O_3浸渍微量助化剂后,能使CO在130℃完全氧化,CH_4的氧化温度在300～500℃范围内,LaMnO_3载体催化剂对柴油机有害排放物的净化率很低,浸渍微量助化剂后,净化率提高一倍以上,特别是LaMnO_3/堇青石蜂窝陶瓷,浸渍后的净化效果同贵金属Pt/Al_2O_3接近。     

An analysis of contemporary printed wiring board manufacturing environment in the USA

This article presents a comparative analysis of contemporary printed wiring assembly (PWA) batch manufacturing systems employing surface mount technology (SMT), This analysis is accomplished by reviewing a typical case study of PWA manufacturing system in the USA. A previously developed model is then applied to the system to predict the cost and performance in the production of typical PWA designs. Various modifications to the system are then proposed and evaluated. From the case study, conclusions concerning optimum manufacturing system configuration for this industry can be drawn and are presented.     

现场总线技术在发电系统数据采集中的应用

介绍了现场总线网络在干熄焦汽轮机发电生产过程中所起的作用，并重点介绍了系统所完成的数据采集，监视和管理等功能。     

Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence

Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.     

炼油厂区内新建项目改扩建施工现场灭火器配置的分析

在对石油化工改扩建工程施工现场火灾危险因素识别评估的基础上，判定现场火灾危险等级、火灾类别，对灭火级别和保护距离进行验算，提出施工现场灭火器选型和配置方案。     

Humans: the missing link in manufacturing simulation?

Computer based discrete event simulation (DES) is one of the most commonly used aids for the design of automotive manufacturing systems. However, DES tools represent machines in extensive detail, while only representing workers as simple resources. This presents a problem when modelling systems with a highly manual work content, such as an assembly line. This paper describes research at Cranfield University, in collaboration with the Ford Motor Company, founded on the assumption that human variation is the cause of a large percentage of the disparity between simulation predictions and real world performance. The research aims to improve the accuracy and reliability of simulation prediction by including models of human factors.     

Analysis of the MSS51 region on chromosome XII of Saccharomyces cerevisiae.

We have localized gene MSS51 on chromosome XII of Saccharomyces cerevisiae between the RDN1 and CDC42 loci. 'Head to head' with MSS51 is another gene, QRI5, the function of which is unknown. However, the proximity of these genes, the structure of the intergenic region and the presence of an ABF1 binding site right in the middle of this region suggest that the MSS51 and QRI5 expressions are submitted to a common regulatory process.     

Transformations in machining. Part 1. enhancement of wavelet transformation neural network (WT-NN) combination with a preprocessor

Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was used to classify the experimental cutting force data of milling operations previously. Preprocessing (PreP) of the approximation coefficients of the WT is proposed just before the classification by using the Adaptive Resonance Theory (ART2) type NNs. Genetic Algorithm (GA) was used to estimate the weights of each coefficient of the PreP. The WT-PreP-NN (ART2) combination worked at lower vigilances by creating only a few meaningful categories without any errors. The WT-NN (ART2) combination could obtain the same error rate only if very high vigilances are used and many categories are allowed.