Novel Fiberoptic Sensing Array an Fundamental Experiments

A suitable fiberoptic sensing array embedded in the smart structure to monitor quasi-distrbuted froces on the structrue in presented in this paper.Artificial neural networks are used in processing of fiberoptic sensing array signals.Fundamental experiments have been done and the results are also given.     

The Tenet experience and the design of protocols for integrated-services internetworks

The research done by the Tenet Group in multimedia networking has reached a point where it may be useful to reflect on the significance of its results for the current debate on how integrated-services internetworks should be designed. Such reflections constitute the main subject of this paper. The principles of the work and the conclusions reached so far by the Tenet researchers are discussed in the light of the conflict between the two major technologies being proposed to build future information infrastructures: namely, the Internet and the ATM technologies. The Tenet approach suggests one feasible way for resolving the conflict to the advantage of all the users of those infrastructures. This paper discusses various fundamental aspects of integrated-services network design: the choice of the service model, the type of charging policy to be adopted, and the selection of a suitable architecture.     

Negative effects of sufficiently small initial weights on back-propagation neural networks

In the training of feedforward neural networks,it is usually suggested that the initial weights should be small in magnitude in order to prevent premature saturation.The aim of this paper is to point out the other side of the story:In some cases,the gradient of the error functions is zero not only for infinitely large weights but also for zero weights.Slow convergence in the beginning of the training procedure is often the result of sufficiently small initial weights.Therefore,we suggest that,in these cases,the initial values of the weights should be neither too large,nor too small.For instance,a typical range of choices of the initial weights might be something like(0.4,0.1) ∪(0.1,0.4),rather than(0.1,0.1) as suggested by the usual strategy.Our theory that medium size weights should be used has also been extended to a few commonly used transfer functions and error functions.Numerical experiments are carried out to support our theoretical findings.     

无线传感器网络（WSN）在花卉大棚环境监测中的应用研究

针对传统花卉大棚环境参数监测系统的某些缺点,本文对基于Zigbee技术的无线传感器网络在花卉大棚中的应用可行性进行分析和研究,并建立了花卉大棚无线环境监测系统,使得该监测系统的各节点位置、监测范围、节点扩展性、节点间距离都得以改善和提高。     

基于OPNET的高速列车控制网络负载平衡研究

随着工业以太网应用于高速列车并成为其控制网络,将可能出现带宽、吞吐量等一系列技术问题。采用基于流水线R—R的负载平衡调度算法,通过OPNET软件建模并调用该算法进行仿真。仿真结果表明,该算法在列车控制网络中的应用是可行的,能较好地解决列车控制网络的负载平衡问题。     

基于MSP430的低功耗近距无线图像传输系统设计与实现

近距无线图像传输系统主要用于无线传感器网络中的图像采集、传输、处理和显示,本文设计并实现了一种具有较强实用性的近距无线图像传输系统。采用OV7670图像传感器作为图像数据采集器,高速低功耗的nRF24L01射频模块作为无线收发器,采用MSP430F14916位超低功耗单片机作为微处理器,所构成的系统具有功耗低、图像传输速度快等优点。作者详细阐述了该系统的硬件结构和软件设计。     

基于减聚类优化算法的无线传感网络分簇路由协议研究

无线传感网络是当前无线网络研究的热点领域,分簇路由协议作为降低网络能耗、提高网络生存时间的核心技术而备受关注。在深入分析已有算法存在诸多不足的基础上,本文提出了一种基于减聚类优化的分簇路由算法。本文首先建立一阶能耗模型,确定网络最优簇首数量;然后建立减聚类优化数学模型,确定可供选择的分簇方案;最后以最小化最大簇内距离方差作为评价指标,确定最优的分簇结果。仿真结果表明:相比经典的LEACH分簇路由协议,该算法划分的网络能够有效地降低网络能耗、提高网络生存时间,弥补已有算法的不足之处。     

车辆TPMS轮速传感器误差消除方法研究

轮胎压力监测系统能够实时地自动监测行驶中汽车的轮胎气压,对于提高行车安全具有重要的意义。基于轮胎压力监测系统硬件平台,阐述了轮速信号的获取,研究了异点剔除方法,提出了基于弹性BP神经网络分析轮速传感器误差的方法,实现了对轮速信号的修正。仿真和实验结果表明,该轮速传感器误差消除方法的精度可达2×10-4rad,能够显著降低传感器误差,提高轮速信号的获取精度。     

医院局域网丢包实例解析

医院局域网的日常运维管理,经常会遇到的一种故障现象就是丢包,当网络出现传输延迟、无法连接服务器数据库等异常现象以后,如何能快速找到故障原因并排除故障．这是对网络管理人员的一大挑战,网管人员应当具备处理这种网络丢包故障的能力。列举工作中遇到的几种丢包案例,总结出故障解决的经验与心得,希望能够提高大家的分析能力和解决此类网络故障的能力。     

利用AJAX优化网络课程的开发

随着web技术的不断进步,网络课程的开发亟需紧跟时代步伐,不断更新自身的技术服务,以更快、更好、更合理的方式呈现在学习者面前,从而提高学习者的学习效率。AJAX是Web2．0的技术代表．将其引入到网络课程的开发中来将从根本上改变传统网络课程的开发模式,给人耳目一新的感觉,为此分析如何利用AJAX优化网络课程的开发。