ABS塑料工件的车削加工

详细介绍了ABS塑料工件车削加工的特点，根据ABS车削加工过程中切削力小、切削温度低，热导率小、线膨胀系数大、弹性模量小的特点，需正确选择车刀的几何参数。     

适于复杂信息融合系统的近似联合概率数据关联算法

文中在B.Zhou提出的直接概率计算(DC)和近似概率计算(AC)算法基础上提出了一种新的近似多传感器多目标联合概率数据关联算法。近似概率法是以一个目标为中心的近似聚为构造互联事件的起点，并在计算中将DC和AC结合得到的一种全邻的点迹—航迹关联算法，它能有效地提高目标点迹—航迹的关联正确率，在计算时耗上较完全联合概率法快得多，能满足工程中实时性的要求。将其在杂波下目标密集、航迹复杂的数据融合系统中进行实验，对关联正确率，关联耗时等与最近邻法进行了比较，效果较好。     

Experiences with a parallel algorithm for data flow analysis

We have designed a family of parallel data flow analysis algorithms for execution on distributed-memory MIMD machines, based on general-purpose, hybrid algorithms for data flow analysis [Marlowe and Ryder 1990]. We exploit a natural partitioning of the hybrid algorithms and explore a static mapping, dynamic scheduling strategy. Alternative mapping-scheduling choices and refinements of the flow graph condensation used are discussed. Our parallel hybrid algorithm family is illustrated on Reaching Definitions, although parallel algorithms also exist for many interprocedural (e.g., Aliasing) and intraprocedural (e.g., Available Expressions) problems [Marlowe 1989]. We have implemented the parallel hybrid algorithm for Reaching Definitions on an Intel iPSC/2. Our empirical results suggest the practicality of parallel hybrid algorithms.An earlier version of this paper was presented at Supercomputing '90.The research reported here was supported, in part, by the New Jersey Commission on Science and Technology and the CAIP Center's Industrial Members, by Siemens Research Corporation and by National Science Foundation grant CCR-8920078.     

~(133)Xe吸入法测量局部脑血流及其计算机在线分析

本文介绍了用吸入~(133)Xe的清除技术测定大脑血流量的原理和方法。讨论子数据获取及其计算机在线分析。报道了一些临床测定结果。     

Delphi开发环境下的实时数据采集程序设计

本文介绍了利用Delphi开发平台开发数据采集程序的两种方法，并结合某测深仪给出了一个编程的例子.     

空调表冷器性能微机测试系统设计与软件开发

介绍了一套用于空调表冷器性能测试的试验装置及配套软件，重点叙述了系统的总体构成、程序的设计思想以及数据采样和处理等功能模块。微机测试技术以及配套软件的使用大大减少了测试人员的工作量，并在一定程度上提高了测试的精度。     

基于网络的实时数据采集系统的应用

介绍了中国石油抚顺石化分公司实时数据采集系统的系统结构、软硬件平台、系统具有的功能，以及与现场DCS连接类型的实例。该项目自2002年开始实施，目前已实现41套装置，近2万点数据的采集。该系统为公司进一步加强管理，提高工作效率，增强公司整体竞争能力，发挥了重要的作用。     

Systematic modeling and model handling for manpower planning systems

The primary purpose of this paper is to show an efficient way of handling models and model data in a decision support system, in which it is usual to consider several variants of a model. The model data primarily consist of model-defining data, but the same approach may be used for the generated results as well. By efficient handling is meant the handling by the computer as well as by the user. For the user it is particularly important that new models can be conveniently defined as variants of existing models. The approach is introduced within the context of a decision support system for manpower planning based on Markov models. In the mean time the same approach has been used for the implementation of other decision support systems and has been found to be more generally applicable.     

基于虚拟仪器技术的多线程数据采集系统

本文论述了如何利用虚拟仪器技术以及多线程技术来进行数据采集，并介绍了在工业中的实际应用。     

Mining evolving data streams for frequent patterns

A data stream is a potentially uninterrupted flow of data. Mining this flow makes it necessary to cope with uncertainty, as only a part of the stream can be stored. In this paper, we evaluate a statistical technique which biases the estimation of the support of patterns, so as to maximize either the precision or the recall, as chosen by the user, and limit the degradation of the other criterion. Theoretical results show that the technique is not far from the optimum, from the statistical standpoint. Experiments performed tend to demonstrate its potential, as it remains robust even under significant distribution drifts.