集群计算机上基于BSP模型的并行算法及其程序设计

文章分析了BSP模型和集群计算机的特点，给出了在集群计算机根据BSP模型设计并行算法及其软件的原则，举例说明了利用BSP模型代价公式定性分析并行算法性能的方法，并利用实验结果验证了得出的结论。结果表明模型的成功地抽象出了集群计算中影响算法性能的诸种因素，并通过代价公式反映出来，利用代价公式可以基本准确地估计并行算法代价，这对集群计算机上的并行算法及其软件及设计和优化具有重要的指导意义。     

Object-oriented DBMS requirements

The requirements on an object-oriented DBMS for management of information in a large, complex enterprise are presented. These requirements aid in the achievement of an environment characterized by data sharing, open architectures, application and data portability, and assurance of data integrity. They were defined from the point of view of a user of the DBMS; therefore they describe the expected functionality of the DBMS and do not specify the method of implementation to achieve this functionality. They encompass requirements on the data model, query and data manipulation languages, the system architecure, interfaces to the system, change management, and transaction management.     

基于EAI的多层分布式应用与实现

针对目前大型企业各类应用迅速增加但应用之间缺乏有效通信的问题,采用企业应 用集成(EAI)技术,提出了4层分布式应用体系结构,实现流程自动化和松耦合的应用集成.文中首先从EAI技术和常见解决方案出发,详细阐述了表示层、企业门户、EAI总线层和数据源层的功能及软件结构,并结合电信业务运营支撑系统的实际需求,给出了J2EE平台下的应用实例开发.利用组件和容器的技术构建企业门户,通过工作流和企业Java组件(EJB)技术实现EAI总线,借助资源适配器完成应用之间的互连互通.该系统现已投入实际运行,取得了良好的应用效果.     

电容传感器在使用中存在的几个问题及处理方法

随着电容测量技术的迅速发展，电容传感器在非电量测量和自动检测中得到广泛应用，但它在使用过程中也存在一些问题，针对在使用电容传感器过程中存在的几个问题，从电容传感器的原理和工作过程两个方面进行了讨论，并提出行之有效的处理方法。     

A new distributed approximation algorithm for constructing minimum connected dominating set in wireless ad hoc networks

In recent years, constructing a virtual backbone by nodes in a connected dominating set (CDS) has been proposed to improve the performance of ad hoc wireless networks. In general, a dominating set satisfies that every vertex in the graph is either in the set or adjacent to a vertex in the set. A CDS is a dominating set that also induces a connected sub‐graph. However, finding the minimum connected dominating set (MCDS) is a well‐known NP‐hard problem in graph theory. Approximation algorithms for MCDS have been proposed in the literature. Most of these algorithms suffer from a poor approximation ratio, and from high time complexity and message complexity. In this paper, we present a new distributed approximation algorithm that constructs a MCDS for wireless ad hoc networks based on a maximal independent set (MIS). Our algorithm, which is fully localized, has a constant approximation ratio, and O(n) time and O(n) message complexity. In this algorithm, each node only requires the knowledge of its one‐hop neighbours and there is only one shortest path connecting two dominators that are at most three hops away. We not only give theoretical performance analysis for our algorithm, but also conduct extensive simulation to compare our algorithm with other algorithms in the literature. Simulation results and theoretical analysis show that our algorithm has better efficiency and performance than others. Copyright © 2005 John Wiley & Sons, Ltd.     

一种考虑分布电容的模糊故障测距算法

提出了一种考虑分布电容的故障测距新算法。该算法基于微分方程描述的线路数学模型，利用单端信息对高压输电线路进行故障测距，保留了解微分方程算法的简单可靠、现实可行、不必考虑衰减直流分量和谐波及电网频率波动影响的特点，同时考虑过渡电阻和分布电容的影响，克服了传统解微分方程法中在经高阻接地故障时测距误差过大和忽略分布电容引起的故障定位不准确的缺点。为了检验算法的精度，进行了大量的动模实验。结果表明，算法原理正确并具有较高的测距精度。     

Optimal and self‐tuning fusion Kalman filters for discrete‐time stochastic singular systems

Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

DCOP FOR SMART HOMES: A CASE STUDY

The aim of this article is to bring forth the issue of integrating the services provided by intelligent artifacts in Ambient Intelligence applications. Specifically, we propose a Distributed Constraint Optimization procedure for achieving a functional integration of intelligent artifacts in a smart home. To this end, we employ Adopt-N , a state-of-the-art algorithm for solving Distributed Constraint Optimization Problems (DCOP). This article attempts to state the smart home coordination problem in general terms, and provides the details of a DCOP-based approach by describing a case study taken from the RoboCare project. More specifically, we show how (1) DCOP is a convenient metaphor for casting smart home coordination problems, and (2) the specific features which distinguish Adopt-N from other algorithms for DCOP represent a strong asset in the smart home domain.     

Spin Dependent Hopping in Ti Doped La0.67 Ca0.33 MnO3

A systematic investigation of the magnetic and transport properties of Ti doped La0.67Ca0.33MnO3 was reported. The Ti substitution for Mn ions results in a reduction in ferromagnetism and conductivity. The metal-insulator transition temperature is close to Curie temperature which decreases from 274 to 82 K as x increases from 0 to 0.17. The most important effect of Ti doping is to introduce spin clusters in the samples due to the distortion of local lattice and the inhomogeneous magnetic structure induced primarily by the random distribution of Mn ions. A maximum magnetoresistance ratio as large as 90% in 1 T at 122 K was obtained for the sample with x =0. 055, which is four times larger than that obtained for LCMO sample at 272 K. There is a remarkable field-history dependent MR in the cooling process for the doped samples while such phenomenon disappears in the warming run. The resistivity follows well the variable range hopping behavior in paramagnetic state. Both the size effect and spin dependent hopping of carriers between the spin clusters should be considered in this system.     

A heuristic algorithm for distributed control in manufacturing systems

Distributed Problem Solving Networks (DPSN) provide a means for interconnecting intelligent problem solver nodes that can solve only a part of a problem depending on their ability in the problem domain. The decomposition of a problem into subproblems, and the selection of nodes to solve them can be regarded as the generation of an AND/OR tree, and the solution of the problem as a search for a solution tree. Introducing measurements for the cost of a solution tree, we present an algorithm to find one having minimal cost under certain conditions. A Flexible Manufacturing System consisting of a network of flexible workcells is used as an example.