虚拟企业图纸数据传输

图纸数据是企业间合作需交换的一种重要的信息。本文分析了虚拟企业环境下企业之间交换图纸数据的要求，提出了一种具体的解决方案，并给出实例。     

压电类智能层合结构的力学和计算模型综述

综述了压电类智能层合结构的力学和计算模型。基于大量国内外有关压电类智能层合结构的文献 ,根据各自采用的运动学假设、场变量的近似、压电层的表达法以及曲率和温度的影响 ,对压电层合结构的力学和计算模型进行了分类 ,阐述了各种理论的特点及一般形式。     

Optimal Solutions for the Temporal Precedence Problem

Abstract. In this paper we refer to the Temporal Precedence Problem on Pure Pointer Machines . This problem asks for the design of a data structure, maintaining a set of stored elements and supporting the following two operations: insert and precedes . The operation insert (a) introduces a new element a in the structure, while the operation precedes (a,b) returns true iff element a was inserted before element b temporally. In [11] a solution was provided to the problem with worst-case time complexity O (log log n ) per operation and O(n log log n) space, where n is the number of elements inserted. It was also demonstrated that the precedes operation has a lower bound of Ω (log log n ) for the Pure Pointer Machine model of computation. In this paper we present two simple solutions with linear space and worst-case constant insertion time. In addition, we describe two algorithms that can handle the precedes (a,b) operation in O (log log d ) time, where d is the temporal distance between the elements a and b .     

测井数据实时采集与接口设计

介绍了一种采用改进型的ＣＬＳ３７００数控测井系统对微电阻率扫描仪数据采集与控制接口的设计及实现方法。基于ＣＬＳ３７００数控测井仪和ＦＭＳ仪采用８９Ｃ５１单片机设计出通信接口，解决了微电阻率方法。基于ＣＬＳ３７００数控测井仪和ＦＭＳ仪采用８９Ｃ５１单片机设备出通信接口电路，解决了微电阻主扫描仪现现场实时处理中的瓶颈问题。     

变井储系数的确定方法及其在反褶积分析中的应用

中针对变井储试井分析问题，给出了确定变井储系数及计算续流量的方法，并用反褶积分析积分析方法解释了未出现径向流的早期测压数据，给出了解决早期试井资料分析问题的有效方法。     

广播电视中心发展新趋势——多媒体化初探

本文讨论了多媒体技术所需的软硬件基础和网络传输技术，及其在数字化广播电视中心节目制作中的应用，展望了无磁带广播电视中心有美好前景，在此基础上提出了完整的广播电视中心多媒体系统结构图。     

湿敏半导体材料电导率计算方法的研究

结合修正了的耗尽层理论和多孔湿敏半导体的特点，本文提出了一个简单的物理模型作为ｎ型湿敏半导体特征的一级近似。描述了多孔湿敏半导体的导电机理，并给出了湿度与宏观电导率的关系。     

峒室爆破CAD设计方法研究

本文对峒室爆破断面布药计算机辅助设计参数驱动方法进行了探讨围绕断面布药主要参数的变化，提出一种基于参数驱动的计算机辅助设计方法，利用ｗｉｎｄｏｗｓ操作系统下的动态数据交换特性，对断面布药进行布药参数优化，实现了交互调整布药，形成一套断面布的计算机软件，为工程爆破设计实现计算机提供了一种可行的方法。     

A Search for Hidden Relationships: Data Mining with Genetic Algorithms

This paper presents an algorithm that permits the search for dependencies among sets of data (univariate or multivariate time-series, or cross-sectional observations). The procedure is modeled after genetic theories and Darwinian concepts, such as natural selection and survival of the fittest. It permits the discovery of equations of the data-generating process in symbolic form. The genetic algorithm that is described here uses parts of equations as building blocks to breed ever better formulas. Apart from furnishing a deeper understanding of the dynamics of a process, the method also permits global predictions and forecasts. The algorithm is successfully tested with artificial and with economic time-series and also with cross-sectional data on the performance and salaries of NBA players during the 94–95 season.