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.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

Distributed wireless power transfer in sensor networks with multiple Mobile Chargers

We investigate the problem of efficient wireless power transfer in wireless sensor networks. In our approach, special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network information. We propose four new protocols for efficient charging, addressing key issues which we identify, most notably (i) what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.     

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%。     

Preparation and temperature-resistance characteristics of novel dense SiAlCN ceramics

The compact green bodies, prepared via a novel solid-liquid mixing method of precursors, were successfully pyrolyzed to obtain the dense bulk SiAlCN ceramics at 1000 °C. It can be seen from their SEM that they have uniform and dense microstructure, indicating that this method can be used to prepare bulk ceramics. In order to verify that they can be used as sensor heads, their temperature-resistance characteristics and repeatability were tested. The results show that the conductive mechanism belongs to Arrhenius's Tailed-State and Extended-State in the temperature range of 500–650 °C and 650–930 °C, respectively. And it shows that SiAlCN ceramics can be used as the sensor heads for high-temperature sensors.     

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).     

一种多晶硅高温压力传感器

制作压力传感器时，在二氧化硅层上淀积多晶硅膜，既可利用优良的机械特性，又可保证压敏电阻与衬底间具有良好的绝缘性，由此可大大提高器件的温度特性。介绍了一种多晶硅压力传感器的原理和设计。实验结果表明，这类传感器具有灵敏度好，精度高等特点，电路工作范围为０－２５０℃，且具有良好的温度稳定性。     

机器人手指尖六维力/力矩传感器的研制

提出一种机器人手指尖六维力／力矩传感器，并对其弹性体结构进行详细论述；分析应变量与测量量的对应关系；采用现代设计手段对弹性体进行模态分析，并介绍了传感器放大处理电路，给出实验结果。     

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。