300km/h高速铁路PC槽型梁动力试验研究

介绍北方交通大学与比利时鲁汶大学、布鲁塞尔自由大学、比利时铁路公司合作,在巴黎至布鲁塞尔之间高速铁路线上的Antoing大桥进行的二次高速铁路桥梁动力试验。试验桥梁由跨度50m的多跨预应力混凝土简支槽型梁构成,试验中列车速度达265-310km/h。通过现场试验和实验结果分析,得到了桥梁的频率、振型、阻尼等自振特性,以及桥梁在高速列车作用下的动挠度、梁和桥墩的横向和竖向加速度、橡胶支座的相对位移、梁体的动应变等动力响应特性。试验经验和测试结果对于充实高速铁路桥梁动力分析理论、改进数值分析模型、验证计算结果、提高高速铁路桥梁的动力设计水平、保证行车安全,具有重要的意义。     

Pure Significance Tests of the Unit Root Hypothesis Against Nonlinear Alternatives

Abstract. This paper describes artificial neural network based pure significance tests for the unit root hypothesis against nonlinear alternatives. The theoretical properties of the tests are discussed and a Monte Carlo investigation of their small sample properties is undertaken.     

Evaluation of performance enhancing proxies in internet over satellite

Performance enhancing proxies (PEPs) are widely used to improve the performance of TCP over high delay‐bandwidth product links and links with high error probability. In this paper we analyse the performance of using TCP connection splitting in combination with web caching via traces obtained from a commercial satellite system. We examine the resulting performance gain under different scenarios, including the effect of caching, congestion, random loss and file sizes. We show, via analysing our measurements, that the performance gain from using splitting is highly sensitive to random losses and the number of simultaneous connections, and that such sensitivity is alleviated by caching. On the other hand, the use of a splitting proxy enhances the value of web caching in that cache hits result in much more significant performance improvement over cache misses when TCP splitting is used. We also compare the performance of using different versions of HTTP in such a system. Copyright © 2003 John Wiley & Sons, Ltd.     

网络管理中事件关联检测机制的研究

网络事件的关联检测是网络管理需要解决的一个关键问题,本文根据分布式网络管理的特点,首次明确定义了网络事件的基本关联关系,在此基础上提出了一种基于Petri Net的事件关联检测机制,实现了基于事件内容的细粒度关联检测,并且在事件检测中充分考虑了时间因素,有效地提高了事件关联检测的准确性。     

一种实现最佳用户检测的非线性优化神经网络

本文提出并讨论了实现码分多址（CDMA）系统上最佳多用户检测（MUD）的一种神经网络方法。该方法通过将最佳多用户检测视为非线性优化组合问题，利用神经网络能有效求解非线性优化问题的优势，导出了一种非线性优化神经网络来实现最佳多用户检测，理论分析和计算机模拟表明，所提出的神经网络具有可实时应用的动态性能和较传统方法优越得多的误码率性能和抗多址干扰的性能。     

具有阻力特性材料的σ_f－σ关系及一种新的阻力曲线测定方法

通过对相变增韧陶瓷及一种可切削玻璃－陶瓷动态疲劳（恒应力速率）试验中高应力速率区断裂应力下降现象的理论分析，发现这种现象与材料的阻力特性（Ｒ－ｃｕｒｖｅ）密切相关。确立的σ_ｆ－σ理论关系能够很好地描述整个应力速率区间内的动态疲劳试验结果。高应力速率区σ_ｆ－σ在双对数坐标下为负斜率直线，直线斜率为（ｍ为阻力曲线ＫＲ＝ｋ（△ａ）~ｍ的指数），断裂主要由材料阻力行为控制；低应力速率区，σ_ｆ－σ在双对数坐标下为正斜率直线，直线斜率为　（ｎ为应力腐蚀指数），断裂主要由材料应力腐蚀行为控制。建立了测定材料阻力特性的一种新方法，分别用这种方法及压痕／弯曲方法对一种可切削玻璃－陶瓷的阻力特性进行了实验测定，两种方法所得结果有很好的一致性。     

Development of a recurrent Sigma-Pi neural network rainfall forecasting system in Hong Kong

At the moment, weather forecasting is still an art — the experience and intuition of forecasters play a significant role in determining the quality of forecasting. This paper describes the development of a new approach to rainfall forecasting using neural networks. It deals with the extraction of information from radar images and an evaluation of past rain gauge records to provide shortterm rainfall forecasting. All of the meteorological data were provided by the Royal Observatory of Hong Kong (ROHK). Preprocessing procedures were essential for this neural network rainfall forecasting. The forecast of the rainfall was performed every half an hour so that a storm warning signal can be delivered to the public in advance. The network architecture is based on a recurrent Sigma-Pi network. The results are very promising, and this neural-based rainfall forecasting system is capable of providing a rain storm warning signal to the Hong Kong public one hour ahead.     

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.     

光纤通信在市内接入网的应用

先说明市内接入网的单位用户和住家用户两大类使用通信和电视、交互型和分配型业务的要求不相同，相应地对光纤传输的应用须作不同的考虑，文中认为；光纤从市内交换局直连办公大楼是合乎现实需要的，而对于居民住家，宜选用光纤连至路边或光纤与同轴结合和适当利用无源光网络等方案，俟将来时机成熟才实行光纤连至每一家，文末有概括总结，说明接入网不同于长途网，接入网的光纤系统可以使用常规单模光纤，工作于波长1．3μm，而光放大器和波分多路系统不是普遍需要，但光电子集成在光端机中是必要的。     

高氧化态（Ⅱ─Ⅳ）三核金属簇合物构型的人工神经网络判别方法

本文运用一典型的人工神经网络模型─“反向传播”模型，对高氧化态（Ⅱ─Ⅳ）三核金属簇合物的构型分布进行了分析，得到了较好的分类、预报结果为化合物结构分析提供了新的工具。