A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines

In this article we illustrate a methodology for building cross-language search engine. A synergistic approach between thesaurus-based approach and corpus-based approach is proposed. First, a bilingual ontology thesaurus is designed with respect to two languages: English and Spanish, where a simple bilingual listing of terms, phrases, concepts, and subconcepts is built. Second, term vector translation is used – a statistical multilingual text retrieval techniques that maps statistical information about term use between languages (Ontology co-learning). These techniques map sets of t f id f term weights from one language to another. We also applied a query translation method to retrieve multilingual documents with an expansion technique for phrasal translation. Finally, we present our findings.     

改进HSR-FCN的服装图像识别分类算法研究

目前网络上的服装图像数量增长迅猛，对于大量服装图像实现智能分类的需求日益增加。将基于区域的全卷积网络（Region-Based Fully Convolutional Networks，R-FCN）引入到服装图像识别中，针对服装图像分类中网络训练时间长、形变服装图像识别率低的问题，提出一种新颖的改进框架HSR-FCN。新框架将R-FCN中的区域建议网络和HyperNet网络相融合，改变图片特征学习方式，使得HSR-FCN可以在更短的训练时间内达到更高的准确率。在模型中引入了空间转换网络，对输入服装图像和特征图进行了空间变换及对齐，加强了对多角度服装和形变服装的特征学习。实验结果表明，改进后的HSR-FCN模型有效地加强了对形变服装图像的学习，且在训练时间更短的情况下，比原来的网络模型R-FCN平均准确率提高了大约3个百分点，达到96.69%。     

Ad Hoc与无线网络的扩展性研究

Ad Hoc作为无线网络的具有高抗毁性和灵活性的扩展网络,日益引人关注。本文首先从环绕网的理念入手,介绍Ad Hoc作为现有无线网络扩展的意义和优势,然后重点分析并提出融合策略以及需要思考的问题。     

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.     

面向应用的无线传感器网络

结合具体的应用环境分析了无线传感器网络发展到第二阶段需要考虑的重点问题；探讨了基于上述应用需求的无线传感器网络的协议栈结构和今后的研究方向。     

A call admission and rate control scheme for multimedia support over IEEE 802.11 wireless LANs

Quality of service (QoS) support for multimedia services in the IEEE 802.11 wireless LAN is an important issue for such WLANs to become a viable wireless access to the Internet. In this paper, we endeavor to propose a practical scheme to achieve this goal without changing the channel access mechanism. To this end, a novel call admission and rate control (CARC) scheme is proposed. The key idea of this scheme is to regulate the arriving traffic of the WLAN such that the network can work at an optimal point. We first show that the channel busyness ratio is a good indicator of the network status in the sense that it is easy to obtain and can accurately and timely represent channel utilization. Then we propose two algorithms based on the channel busyness ratio. The call admission control algorithm is used to regulate the admission of real-time or streaming traffic and the rate control algorithm to control the transmission rate of best effort traffic. As a result, the real-time or streaming traffic is supported with statistical QoS guarantees and the best effort traffic can fully utilize the residual channel capacity left by the real-time and streaming traffic. In addition, the rate control algorithm itself provides a solution that could be used above the media access mechanism to approach the maximal theoretical channel utilization. A comprehensive simulation study in ns-2 has verified the performance of our proposed CARC scheme, showing that the original 802.11 DCF protocol can statically support strict QoS requirements, such as those required by voice over IP or streaming video, and at the same time, achieve a high channel utilization. Hongqiang Zhai received the B.E. and M.E. degrees in electrical engineering from Tsinghua University, Beijing, China, in July 1999 and January 2002 respectively. He worked as a research intern in Bell Labs Research China from June 2001 to December 2001, and in Microsoft Research Asia from January 2002 to July 2002. Currently he is pursuing the PhD degree in the Department of Electrical and Computer Engineering, University of Florida. He is a student member of IEEE. Xiang Chen received the B.E. and M.E. degrees in electrical engineering from Shanghai Jiao Tong University, Shanghai, China, in 1997 and 2000, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Florida, Gainesville, in 2005. He is currently a Senior Research Engineer at Motorola Labs, Arlington Heights, IL. His research interests include resource management, medium access control, and quality of service (QoS) in wireless networks. He is a Member of Tau Beta Pi and a student member of IEEE. Yuguang Fang received a Ph.D degree in Systems and Control Engineering from Case Western Reserve University in January 1994, and a Ph.D degree in Electrical Engineering from Boston University in May 1997. From June 1997 to July 1998, he was a Visiting Assistant Professor in Department of Electrical Engineering at the University of Texas at Dallas. From July 1998 to May 2000, he was an Assistant Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology. In May 2000, he joined the Department of Electrical and Computer Engineering at University of Florida where he got the early promotion with tenure in August 2003 and has been an Associate Professor since then. He has published over one hundred (100) papers in refereed professional journals and conferences. He received the National Science Foundation Faculty Early Career Award in 2001 and the Office of Naval Research Young Investigator Award in 2002. He is currently serving as an Editor for many journals including IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Mobile Computing, and ACM Wireless Networks. He is also actively participating in conference organization such as the Program Vice-Chair for IEEE INFOCOM’2005, Program Co-Chair for the Global Internet and Next Generation Networks Symposium in IEEE Globecom’2004 and the Program Vice Chair for 2000 IEEE Wireless Communications and Networking Conference (WCNC’2000).     

DSR的一种自适应路由自动缩短机制

动态源路由协议是无线自组织网络众多路由协议中被广泛关注的一种按需路由协议，目前，关于该协议的优化措施有很多。本文先分析了动态源路由协议的一种优化机制——路由自动缩短，该机制能动态缩短处于工作状态路由的跳数，但不保证缩短路由的质量，在此基础上，提出一种自适应路由自动缩短机制，新机制既可缩短路由．又能保证缩短路由质量．理论分析及仿真结果表明，自适应路由缩短机制的各项性能优于原路由缩短机制。     

用于机器人轨迹定位纠正系统的回声状态神经网络研究

循环神经网络(RecurrentNeuralNetworks)是人工神经网络(ArtificialNeuralNetworks)中重要的分支,与前馈神经网络(ForwardNeuralNetworks)相比具有更好的时间序列学习能力。但长期以来其学习法一直不能脱离前馈神经网络而自成一体,回声状态神经网络(EchoStateNetworks(ESN))是打破这一局面的全新学习方法。其独特的结构,良好的短期记忆能力,方便的学习方法,不俗的非线性特性是以前循环神经网络所不可比的。本文在介绍了回声状态神经网络之后将其用于四轮机器人的位置测量系统中,有良好的表现。     

A Monte Carlo simulation study of the mechanical and conformational properties of networks of helical polymers. I. General concepts

We study the mechanical and conformational properties of networks of helical polymers with a combination of Monte Carlo simulations based on the Wang-Landau algorithm and the three-chain model. We find that the stress-strain behavior of these networks has novel features not observed in typical networks made of synthetic polymers. In particular, we find that as these networks are stretched they first strengthen, then soften and finally strengthen again. This non-monotonic behavior of the stress correlates with the one of the helical content and is rationalized by the elongation-induced formation and melting of the helical structure of the polymer. We complement these results with a study of other conformational properties of the polymer strands that clarify the molecular mechanisms behind the mechanical behavior of these networks. Finally, we present a qualitative comparison of some of our results with the theoretical ones recently reported by Kutter and Terentjev.     

On parity problems and the functional-link artificial neural network

This paper contains the proof of a theorem on the capability of functional-link artificial neural networks both to represent and to learn the n-dimensional parity problem. The result is obtained by an embedding of the problem into a space of dimension 2ⁿ — 1. It is shown that the Volterra expansion of the data in n-dimensions provides the necessary transformation. By computing the parity function, it is shown that a suitable set of neural network weights can be deduced. Finally, it is demonstrated that 2ⁿ — 1 is the minimum embedding dimension for the problem.The contribution of A Zuderell of the University of Innsbruck is acknowledged.