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.     

等离子体刻蚀工艺控制模型分析

讨论了主因素分析法以及神经网络法在等离子体刻蚀工艺中的应用.结果表明主元素分析法可以实现对数据的压缩,而神经网络算法则显示出比传统的统计过程控制算法更好的准确性.     

径向基函数神经网络的再学习算法及其应用

为了应用径向基函数神经网络逐步地识别待研究系统,文章针对径向基函数神经网络的再学习算法开展了深入的研究.应用严格的数学推理方法,将径向基函数神经网络的再学习问题转化为矩阵求逆的附加运算.详细给出了径向基函数神经网络再学习算法中增加新训练样本和增加新基函数的数学公式,同时对如何获取新的训练样本进行了研究.     

一种智能型的PCB产业需求预测方法

目前需求预测在整个印制电路板产业的生产活动控制中正扮演着越来越重要的角色。分析了影响印制电路板需求的因素和现有的预测方法,提出了一种适用于PCB产业需求预测的有效方法——遗传/BP—神经网络。实验表明该方法能够进一步改善印制电路板预测的准确度和减少生产成本的消耗。     

一种新的主动网络安全体系的设计

尽管主动网络原型系统中设计了一些安全措施，但是它们都不具通用性且主要集中在security方面，这在主动网络必须和传统网络相兼容的情况下，阻碍了主动网络的发展。本文在定义消极型错误和积极型错误的基础上，设计了主动网络资源控制核。然后提出了集security和safety保障为一体的基于资源控制核的一种通用的主动网络安全体系，探讨了该体系应具有的特点、设计目标和可行性，并设计了主动节点的安全机制。     

Performance of PKI-based security mechanisms in mobile ad hoc networks

Security for ad hoc network environments has received a lot of attention as of today. Previous work has mainly been focussing on secure routing, fairness issues, and malicious node detection. However, the issue of introducing and conserving trust relationships has received considerably less attention. In this article, we present a scalable method for the use of public key certificates and their revocation in mobile ad hoc networks (MANETs). With the LKN-ad hoc security framework (LKN-ASF) a certificate management protocol has been introduced, bringing PKI technology to MANETs. In addition a performance analysis of two different revocation approaches for MANETs will be presented.     

用于磁场测量的高精度500A/30V零压开关直流稳流电源

研制了一种带有无源辅助网络的全桥移相脉宽调制零压开关(FB PSPWMZVS)高精度磁铁稳流电源,并在电磁铁磁场测量中得到应用,其电流稳定度在8h内优于±1×10-4。     

可信计算与可信网络

论文对主流的可信计算技术——TCPA和NGSCB进行了分析,并对可信计算平台(TCP)进行了研究,对基于可信计算的可信网络的三个基本属性进行了分析和研究,最后介绍了可信网络的发展现状。     

人工智能的原理及应用

介绍了人工智能的发展，并对改进的神经网络专家系统的优越性做了介绍，指出了神经网络专家系统广阔的应用前景及实现。     

卷积码的线性系统

介绍了卷积码的线性离散时不变系统模型。从建立卷积码的状态变量方程出发,研究了卷积码的代数结构,并详细论述了基于状态变量方程描述的迭代译码算法。