TCP Performance in Optical Packet-switched Networks

Optical packet assembly is a key function to support inter-working between TCP/IP networks and optical packet-switched networks. It is characterized by the assembly delay and by the segment aggregation needed to form an optical packet. These counter-balancing aspects depend on several environment variables, such as the TCP parameters, the access link speed, the optical packet size whose effects are studied in this paper. Performance evaluations are obtained by extensive simulations in terms of send rate of TCP flows, fairness, efficiency, and assembly delay. Some guidelines in the design of optical packets that take into account the results presented are given.     

Spin probe study of semi‐interpenetrating polymer networks based on polyurethane and polymethacrylate functional prepolymers

The motional transition and heterogeneity of semi‐interpenetrating networks (SIPNs) based on polyurethane (PU) with carboxylic groups and methacrylic copolymer (PM) with tertiary amine groups were studied by the electron spin resonance (ESR) spin probe method. The concentration of functional groups in both prepolymers varied from 0 to 0.45 mmol g^?1. Spin‐probed SIPNs show that the temperature‐dependent spectra are sensitive to polymer interactions imposed by functional groups. These interactions determine the free volume distribution in the matrix and temperature at which motional transition takes place. The fraction of free volume increases with functional group concentration and reaches its maximum at 0.25 mmol g^?1. Further increases in the functional group concentration reduce the free volume. The results of the networks with strong interactions are discussed in terms of the interference of the plasticizing effect of the PU component and the formation of possible cluster cross‐links, which restricts segmental motions. Copyright © 2003 Society of Chemical Industry     

Current Status and Trend of Internet and E-Commerce Market in Korea

After the remarkable increase of Internet users and broadband Internet subscribers at the end of the 20th century, the size of Korean Internet and e-commerce market steadily increased but the growth rate has been either stagnant or decreased. Trends of Korean Internet and e-commerce market are summarized in this paper the trends on Internet usage are introduced. Trends of online games, blogs and wireless Internet are introduced. The trends of Korean Internet market may have implications for China and Japan.     

多传感器目标的模糊识别

根据模糊理论，采用信息融合技术和模糊识别技术，讨论了在多类传感器网内进行多目标模糊识别的一般原理和方法。     

WDM网络光层保护新算法的探讨

首先介绍了几种按照不同标准划分的WDM网络光层保护方法,然后提出了三种实现光层保护的新算法,对它们的内容和性能做了详细描述。按照提出的算法所求得的解,可以为WDM网络提供新的光层保护方式。     

Process monitoring using auto-associative,feed-forward artificial neural networks

The potential of using artificially simulated neural networks as intelligent, adaptive process-monitoring devices is discussed. The investigation is considered as a method for automatic, intelligent exception reporting for quality control applications. The technique is also compared with the conventional statistical approaches of principal component analysis and Kohonen's feature map. The applications of the technique in aerospace and manufacturing environments are presented and a possible extension of the method to incorporate a diagnostic function is discussed.Seconded from Cheltenham and Gloucester College of Higher Education as a Royal Society/SERC Research Fellow at Smith's Industries Aerospace and Defence Systems, Bishop's Cleeve, Cheltenham, UK.     

无线Ad hoc 网络及其研究难点

无线Ad hoc网络作为没有基础设施的网络，在军事和民用方面具有广阔的应用前景，是目前网络研究中的热点问题。本文对无线Ad hoc网络进行了详细的论述，指出了目前研究中存在的一些难点。     

无线局域网安全问题研究

为了提供相当于有线局域网的数据安全,IEEE802.11定义了有线等价保密(WEP)协议。然而,最近的研究发现WEP存在严重的缺陷。介绍了无线局域网存在的安全隐患,分析了WEP的结构以及WEP协议的缺陷以及可能遭受的攻击,并探讨了改进方案。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.