石化企业实时数据管理引擎设计与实现

实时数据管理系统是流程企业控制信息网络与管理信息网络平滑集成的基础，为两者的数据通讯提供桥梁。介绍了笔者在炼油化工C企业IMS建设中的实时数据管理引擎设计与开发，具有其先进性与实用性。     

井喷失控预警的远距离自动调焦控制研究

井喷失控是石油及天然气钻井、完井过程可能出现的灾难性事故，给人类生命财产造成严重伤害，污染环境，破坏地下资源以及在城市火灾、森林火灾、环境变化等监测工作中常需要远距离目标监测，为了获得高清晰的实时图像数据，需要实时自动调焦。通过系统分析远距离相机离焦的原因，建立了一个实时调焦数学模型，并以此为基础研制了一种新的对应距离和温度变化的离焦补偿控制系统。该系统采用微型步进电机实现智能控制，通过监测目标距离确定监测相机的初始焦距，以及环境温度变化的实时反馈实现焦距的实时控制，使相机可以在－40～125 ℃范围内获得清晰、稳定的远距离图像。该系统适用于井喷失控石油及天然气火灾、城市火灾、森林火灾、环境变化等远距离目标的实时监测。     

一种分析碳酸盐岩孔隙系统数字图像的新方法

碳酸盐岩的孔隙类型多，孔径变化范围大，孔隙系统结构复杂，研究难度大。长期以来，是利用光学显微镜法、毛细管压力分析法、岩石孔隙系统复制法和图像分析仪法等方法或其中几种方法配合来研究碳酸盐岩孔隙系统。随着计算机图像技术的迅速发展和日益完善，借助该项技术通过碳酸盐岩孔隙系统数字图像来研究碳酸盐岩孔隙系统已经成为现实。文章提出一种研究碳酸盐岩孔隙系统数字图像的新方法。通过样品光薄片的光学显微镜（OM）数字图像和环境扫描电子显微镜（ESEM）数字图像二值化识别孔隙；构造孔隙度、孔隙贡献率和孔隙形状参数的计算公式用于数字图像分析，得到孔隙大小分布和孔隙形状分布。在此基础上，总结碳酸盐岩孔隙参数对其渗透率的控制作用。与传统的孔隙系统研究方法相比，该方法与计算机图像技术紧密结合，具有定量、快速的明显优势。     

岩性指示曲线重构及其在储层预测中的应用

大牛地上古生界岩性气藏主要发育在三角洲分流河道沉积的下石盒子组、海陆交互沉积的山西组及以潮坪相沉积为主的太原组,储层是储集性能较差的致密砂岩,平均孔隙度小于10％,渗透率小于1×10-2μm2,储层单层厚度一般小于10 m,砂体横向连通性较差。由于低孔、低渗特征导致储层与围岩的波阻抗差异微弱,用地震资料进行储层预测困难。为此,针对大牛地石板太工区优质储层的岩性特征和测井响应特征进行了测井综合分析,利用对岩性粒度敏感的自然伽马曲线,以及对岩性粒度响应频率较低,且与波阻抗有较好对应关系的中子曲线重构了岩性指示曲线。岩性指示曲线不仅可以有效地识别优质砂体,划分不同岩性,为地震、测井信息结合的岩性反演建立桥梁,同时也为反演结果识别气层打下了基础。利用岩性指示曲线、波阻抗和电阻率曲线进行的地震、测井联合反演技术在石板太工区取得了较好的效果,同时,对石板太工区下石盒子组盒2段、山2段进行了储层和含气性预测,划分了有利含气区带,部署的2口开发井和1口探井有2口井见气,其中1口井获高产气流。     

Range Assignment for Biconnectivity and k-Edge Connectivity in Wireless Ad Hoc Networks

Depending on whether bidirectional links or unidirectional links are used for communications, the network topology under a given range assignment is either an undirected graph referred to as the bidirectional topology, or a directed graph referred to as the unidirectional topology. The Min-Power Bidirectional (resp., Unidirectional) k-Node Connectivity problem seeks a range assignment of minimum total power subject to the constraint that the produced bidirectional (resp. unidirectional) topology is k-vertex connected. Similarly, the Min-Power Bidirectional (resp., Unidirectional) k-Edge Connectivity problem seeks a range assignment of minimum total power subject to the constraint the produced bidirectional (resp., unidirectional) topology is k-edge connected. The Min-Power Bidirectional Biconnectivity problem and the Min-Power Bidirectional Edge-Biconnectivity problem have been studied by Lloyd et al. [23]. They show that range assignment based the approximation algorithm of Khuller and Raghavachari [18], which we refer to as Algorithm KR, has an approximation ratio of at most 2(2 – 2/n)(2 + 1/n) for Min-Power Bidirectional Biconnectivity, and range assignment based on the approximation algorithm of Khuller and Vishkin [19], which we refer to as Algorithm KV, has an approximation ratio of at most 8(1 – 1/n) for Min-Power Bidirectional Edge-Biconnectivity. In this paper, we first establish the NP-hardness of Min-Power Bidirectional (Edge-) Biconnectivity. Then we show that Algorithm KR has an approximation ratio of at most 4 for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity, and Algorithm KV has an approximation ratio of at most 2k for both Min-Power Bidirectional k-Edge Connectivity and Min-Power Unidirectional k-Edge Connectivity. We also propose a new simple constant-approximation algorithm for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity. This new algorithm applies only to Euclidean instances, but is best suited for distributed implementation. A preliminary version of this work appeared in the proceedings of the 2nd International Conference on AD-HOC Network and Wireless (Adhoc-Now 2003). Research performed in part while visiting the Max-Plank-Institut fur Informatik. Gruia Calinescu is an Assistant Professor of Computer Science at the Illinois Institute of Technology since 2000. He held postdoc or visiting researcher positions at DIMACS, University of Waterloo, and Max-Plank Institut fur Informatik. Gruia has a Diploma from University of Bucharest and a Ph.D. from Georgia Insitute of Technology. His research interests are in the area of algorithms. Peng-Jun Wan has joined the Computer Science Department at Illinois Institute of Technology in 1997 and has been an Associate Professor since 2004. He received his Ph.D. in Computer Science from University of Minnesota in 1997, M.S. in Operations Research and Control Theory from Chinese Academy of Science in 1993, and B.S. in Applied Mathematics from Tsinghua University in 1990. His research interests include optical networks and wireless networks.     

农村饮水解困工程持续利用的探讨

分析了尧都区农村饮水工程存在的问题，阐述了农村饮水解困工程持续利用的管理措施，提出建立新的农村供水市场理念。     

某雷达数据处理有关问题分析

对某雷达数据处理应用中存在的一些特殊问题进行讨论分析,并就具体问题提出了解决的方法.     

Efficient multicast search under delay and bandwidth constraints

The issue of a multicast search for a group of users is discussed in this study. Given the condition that the search is over only after all the users in the group are found, this problem is called the Conference Call Search (CCS) problem. The goal is to design efficient CCS strategies under delay and bandwidth constraints. While the problem of tracking a single user has been addressed by many studies, to the best of our knowledge, this study is one of the first attempts to reduce the search cost for multiple users. Moreover, as oppose to the single user tracking, for which one can always reduce the expected search delay by increasing the expected search cost, for a multicast search the dependency between the delay and the search cost is more complicated, as demonstrated in this study. We identify the key factors affecting the search efficiency, and the dependency between them and the search delay. Our analysis shows that under tight bandwidth constraints, the CCS problem is NP-hard. We therefore propose a search method that is not optimal, but has a low computational complexity. In addition, the proposed strategy yields a low search delay as well as a low search cost. The performance of the proposed search strategy is superior to the implementation of an optimal single user search on a group of users. Amotz Bar-Noy received the B.Sc. degree in 1981 in Mathematics and Computer Science and the Ph.D. degree in 1987 in Computer Science, both from the Hebrew University, Israel. From October 1987 to September 1989 he was a post-doc fellow in Stanford University, California. From October 1989 to August 1996 he was a Research Staff Member with IBM T. J. Watson Research Center, New York. From February 1995 to September 2001 he was an associate Professor with the Electrical Engineering-Systems department of Tel Aviv University, Israel. From September 1999 to December 2001 he was with AT research labs in New Jersey. Since February 2002 he is a Professor with the Computer and Information Science Department of Brooklyn College - CUNY, Brooklyn New York. Zohar Naor received the Ph.D. degree in Computer Science from Tel Aviv University, Tel Aviv, Israel, in 2000. Since 2003 he is with the University of Haifa, Israel. His areas of interests include wireless networks, resource management of computer networks, mobility, search strategies, and multiple access protocols.     

分类挖掘技术在高校人事管理中的应用

探讨分类挖掘技术在高校实际工作中的应用方式与应用领域。以高校人事管理为模型，应用数据挖掘中决策树算法，对高校人力资源数据源中的信息进行分析，发现其中有价值的数据模式，寻找其中存在的关系和规则，对高校人才规划提供比较客观的决策支持。     

软件集成测试技术研究

首先分析了集成测试的原理和特点，并指出了集成测试的重要性。然后结合传统软件与面向对象软件开发的方法和技术，详细介绍了传统软件的集成测试方法和策略，并深入分析了面向对象软件集成测试的原理和方法。