基于Internet的远程教育系统模型研究

随着计算机网络技术的发展，远程教学系统的结构发生了重大的变化，逐步由原来的客户机／服务器(C／S)结构转变为基于Internet的浏览器／服务器(B／S)结构。本文提出了基于CORBA技术的B／S结构系统模型。分析了其运行过程，并与传统的结构进行了比较，指明了其优越性。在本文的结尾。指出了使用这种技术的一个具体例子。     

汽车计算平台工程国外相关标准概述

结合我国汽车计算平台工程,分析了国外相关的标准现状和基本框架,并为今后工作的开展提出了建议.     

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.     

一种新的TDRSS扩频调制方式的研究

本文讨论跟踪及数字中继卫星系统（TDRSS）一种新通信体制，即并行MSK扩频系统，发射端采用长短码正交扩频的平衡调制，接收端采用一种简单解扩方式简化了并行MSK信号的解调，同时用短码全“1”引导长码同步的方法大大减小了长码的捕获时间，实验结果证明了良好的伪码同步性能。     

Global and uniform convergence of subspace correction methods for some convex optimization problems

This paper gives some global and uniform convergence estimates for a class of subspace correction (based on space decomposition) iterative methods applied to some unconstrained convex optimization problems. Some multigrid and domain decomposition methods are also discussed as special examples for solving some nonlinear elliptic boundary value problems.

     

高可用度的冗余UPS

简述通信行业标准《通信局(站)电源系统总技术要求》(YD/T1051)对UPS可用度的要求,介绍适用于电信系统的高可用度冗余UPS。     

Large scale petroleum reservoir simulation and parallel preconditioning algorithms research

Solving large scale linear systems efficiently plays an important role in a petroleum reservoir simulator, and the key part is how to choose an effective parallel preconditioner. Properly choosing a good preconditioner has been beyond the pure algebraic field. An integrated preconditioner should include such components as physical background, characteristics of PDE mathematical model, nonlinear solving method, linear     

A modular integer GCD algorithm

This paper describes the first algorithm to compute the greatest common divisor (GCD) of two n-bit integers using a modular representation for intermediate values U, V and also for the result. It is based on a reduction step, similar to one used in the accelerated algorithm [T. Jebelean, A generalization of the binary GCD algorithm, in: ISSAC '93: International Symposium on Symbolic and Algebraic Computation, Kiev, Ukraine, 1993, pp. 111–116; K. Weber, The accelerated integer GCD algorithm, ACM Trans. Math. Softw. 21 (1995) 111–122] when U and V are close to the same size, that replaces U by (U−bV)/p, where p is one of the prime moduli and b is the unique integer in the interval (−p/2,p/2) such that . When the algorithm is executed on a bit common CRCW PRAM with O(nlognlogloglogn) processors, it takes O(n) time in the worst case. A heuristic model of the average case yields O(n/logn) time on the same number of processors.     

A numerical experimental study of inverse preconditioning for the parallel iterative solution to 3D finite element flow equations

Integration of the subsurface flow equation by finite elements (FE) in space and finite differences (FD) in time requires the repeated solution to sparse symmetric positive definite systems of linear equations. Iterative techniques based on preconditioned conjugate gradients (PCG) are one of the most attractive tool to solve the problem on sequential computers. A present challenge is to make PCG attractive in a parallel computing environment as well. To this aim a key factor is the development of an efficient parallel preconditioner. FSAI (factorized sparse approximate inverse) and enlarged FSAI relying on the approximate inverse of the coefficient matrix appears to be a most promising parallel preconditioner. In the present paper PCG using FSAI, diagonal and pARMS (parallel algebraic recursive multilevel solvers) preconditioners is implemented on the IBM SP4/512 and CLX/768 supercomputers with up to 32 processors to solve underground flow problems of a large size. The results show that FSAI may allow for a parallel relative efficiency larger than 50% on the largest problems with p=32 processors. Moreover, FSAI turns out to be significantly less expensive and more robust than pARMS. Finally, it is shown that for p in the upper range may be much improved if PCG–FSAI is implemented on CLX.     

一种带时间窗和车辆数目限制的车辆路线问题及其算法

本文提出了带时间窗和车辆数目限制的车辆路线问题的数学模型,针对该问题的特征构造了一种路线生成算法和禁忌搜索算法,并对Solomon提出的C1、R1、RC1类数据集给出了数值运算的结果,实验结果表明算法是有效的.