Scale Up from Small Oven-Drying Tests of Mineral Concentrate to Pilot-Scale Drying with a Heated Pad

While Fickian diffusion models are commonly used in other applications, there are few reports of them being applied to the batch drying of a mineral concentrate. Diffusion coefficients estimated from small-scale oven-drying tests were used to predict the drying behavior of a concentrate sample 1 m × 1 m in area and 50 cm deep, with a heated bottom pad. These pilot-scale tests included both daily turning of the sample and turning every three days. The excellent quantitative agreement between the predicted and observed pilot-scale behavior gives a high level of confidence in the model predictions and suggests that a Fickian diffusion model is adequate to predict the behavior of mineral concentrates at the low moisture contents used here.     

校园网宿舍网络管理模式的探讨

讨论了高校学生宿舍区网络的特点，结合天津商学院校园网的实践，讨论了校园网宿舍网络管理的模式。     

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。     

USERS' TWO-DIMENSIONAL INTEREST AND ITS STORAGE METHOD

The users' interest can be mined from the web cache and can be used widely. The interest can be specialized by the two-tuple (term, weight) in the simple interest model, in which the association relations are not mined, and then the interest cannot be associated in expressing the users' interest. Based on analyzing the WWW cache model, this letter brings forward a two-dimensional interest model and gives the interrelated methods on how to store the two-dimensional interest model effectively.     

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。     

给水管网计算中的数据转换方法

在给水管网计算中,通过建立环-管段矩阵、环-节点矩阵以及输入节点流量、节点坐标等少量数据,通过计算和数据转换,便可求得经济管径、管段设计流量、节点水压值、水厂供水量、管网造价、年费用折算值等。采用该方法进行管网计算,可以减少40%～70%的计算时间。     

USERS’ TWO-DIMENSIONAL INTEREST AND ITS STORAGE METHOD

The users‘ interest can be mined from the web cache and can be used widely.The interest can be specialized by the two-tuple(term,weight) in the simple interest model,in which the association relations are not mined.and then interest cannot be associated in expressing the users‘interest.Based on analyzing the WWW cache model,this letter brings forward a twodimensional interest model and gives the interrelated methods on how to store the two-dimensional interest model effectively.     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.