从数据结构角度设计导游系统

从数据结构角度为旅游胜地设计导游系统。向游人提供景点的信息查询服务,根据指定的景点提供相关的景点信息。任意给定起点和终点,查询两点之间的最短路径。     

Perceived risk for influenza in veterans with spinal cord injuries and disorders.

Objective: Guided by the extended parallel process model (EPPM), the objective was to assess control processes dominant in influenza behavior decisions. Design: Cross-sectional survey. Results: Response rate was 31% (n=968). Regarding influenza risk, 59% were in danger control. Those in fear control were more likely to report influenza infection (p=.000). In the nonvaccinated, those in fear control were more likely to indicate not knowing where to get the vaccine (p=.016) and that it was unavailable (p=.027), and those in danger control believed they did not need it (p=.023). Zero critical values were more likely to indicate that no health provider recommended the shot (p=.002). Conclusions: Most perceived efficacy to be stronger than threat related to influenza; according to the EPPM, they are aware of their risk but recognize their ability to avert it. For those in danger control, messages should focus on increasing perceptions of severity and susceptibility to positively affect behavior change. For those in fear control, messages should focus on efficacy only. With a critical value of zero, no threat is induced, and a high-threat/high-efficacy approach should be taken. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Location and calculation-free node-scheduling schemes in large wireless sensor networks

In wireless sensor networks that consist of a large number of low-power, short-lived, unreliable sensors, one of the main design challenges is to obtain long system lifetime without sacrificing system original performance (sensing coverage and sensing reliability). To solve this problem, one of the potential approaches is to identify redundant nodes at the sensing interface and then assign them an off-duty operation mode that has lower energy consumption than the normal on-duty mode. In our previous work [J. Wireless Commun. Mobile Comput. 3 (2003) 271; Processing of ACM Wireless Sensor Network and Application Workshop 2002, September 2002], we proposed a node-scheduling scheme, which can provide a 100% sensing coverage preservation capability. This, however, requires each node to be aware of its own and its neighbors’ location information. Also, in that scheme, each node has to do accurate geometrical calculation to determine whether to take an off-duty status. In this paper, we propose and study several alternative node-scheduling schemes, which cannot completely preserve the original system coverage, but are nonetheless light-weighted and flexible compared with the previous one. Our simulation results compare these schemes with the previous one and demonstrate their effectiveness.     

Scheduling in or-parallel Prolog systems: Survey and open problems

Implementation of or-parallel Prolog systems offers a number of interesting scheduling problems. The main issues are the interaction between memory models and scheduling, ordering of multiple solutions, and scheduling of speculative work. The problems occur partly because of the design choices (e.g. the choice of a memory model), and partly because of the desire to maintain observational equivalence between parallel and sequential implementations of Prolog, while achieving high efficiency. In the first part of this paper a common framework for discussing scheduling in or-parallel systems is introduced, and also a collection of issues that must be addressed in such systems is presented. In the second part of the paper we survey a number of solutions to these problems comparing their efficiency whenever possible. We close the survey with a short discussion of open problems.Current association: Carlstedt Elektronik AB     

On Striping Traffic over Multiple IEEE 802.11(b) Wireless Channels

Due to interference, path loss, multipath fading, background noise, and many other factors, wireless communication normally cannot provide a wireless link with both a high data rate and a long transmission range. To address this problem, striping network traffic in parallel over multiple lower-data-rate but longer-transmission-range wireless channels may be used. In this paper, we propose a new striping method and evaluate its performances over multiple IEEE 802.11(b) channels under various conditions. Our extensive simulation results show that this method is quite effective for such an application. S.Y. Wang is an Associate Professor of the Department of Computer Science and Information Engineering at National Chiao Tung University, Taiwan. He received his Master and Ph.D. degree in computer science from Harvard University in 1997 and 1999, respectively. His research interests include wireless networks, Internet technologies, network simulations, and operating systems. He is the author of the NCTUns 2.0 network simulator and emulator, which is being widely used by network and communication researchers. More information about the tool is available at http://NSL.csie.nctu.edu.tw/nctuns.html. C.H. Hwang received his master degree in computer science from NCTU in 2002 and currently is working for a network company. C.L. Chou currently is a third-year Ph.D. student at the Department of Computer Science and Information Engineering, National Chiao TungUniversity (NCTU), Taiwan. He received his master degree in computer science from NCTU in 2002.     

可编程光学二值双轨逻辑门

基于双轨逻辑,本文提出一种可级联的并行二值逻辑门。所有十六种二值逻辑运算可以采用偏振半波相延编程来实现。也提出了用电光晶体实现实时编程的方法。本文中给出了实验结果。     

On collaborative content distribution using multi-message gossip

We study epidemic schemes in the context of collaborative data delivery. In this context, multiple chunks of data reside at different nodes, and the challenge is to simultaneously deliver all chunks to all nodes.     

On using peak amplitude and rise time for AE source characterization

Acoustic Emission (AE) signals, which are electrical version of acoustic emissions, are usually analysed using a set of signal parameters. The major objective of signal analysis is to study the characteristics of the sources of emissions. Peak amplitude(P _a ) and rise time(R _t ) are two such parameters used for source characterization. In this paper, we theoretically investigate the efficiency ofP _a andR _t to classify and characterize AE sources by modelling the input stress pulse and transducer. Analytical expressions obtained forP _a andR _t clearly indicate their use and efficiency for source characterization. It is believed that these results may be of use to investigators in areas like control systems and signal processing also