Disorder effects on the strain response of model polymer networks

Molecular dynamics simulations are used to investigate polymer networks made by either end-linking or randomly crosslinking a melt of linear precursor chains. The resulting network structures are very different, since end-linking leads to nearly ideal monodisperse networks, while random crosslinking leads to polydisperse networks, characterized by an exponential strand length distribution. Networks with average strand length 20 and 100 were generated. These networks were used to study the effects of disorder in the network connectivity on observables averaged either over the entire network or selected sub-structures. Heterogeneities in the randomly crosslinked networks cause significant differences in the localization of monomers, however, neither the localization of crosslinks nor the microscopic strain response are significantly affected. Compared to end-linked networks, randomly crosslinked networks have a slightly increased tube diameter, and as a result a slightly decreased shear modulus, but otherwise identical stress-strain behavior. For the investigated systems, we conclude that the microscopic strain response, tube diameter, and stress-strain relation are all insensitive to the heterogeneities due to the linking process by which the network were made.     

3COM交换机技术及应用

本文介绍了3COM Superstack ⅡSwitch 3300 的主要特性及其在局域网中的实际应用，评述了冗余网络的构造等问题。     

色彩心理效应模型在人性化Web导购系统中的搭建与应用

人性化、个性化系统是现代Web商务系统的一个发展趋势,也是人工心理的一个研究方向。本文以服装选购系统为例,对人类情感的重要影响因素之一——色彩心理效应进行了进一步的深入研究。文中首次使用人工神经网络对色彩带来的膨胀紧缩感的心理效应进行数学建模,并且在服装导购系统中进行应用算法的设计和实施,从而实现了一种心理效应由感性描述到理性模型的转化,同时也使人性化、个性化智能系统的理念得到进一步完善。实验结果表明此数学模型能够较好的模拟色彩给人带来的膨胀紧缩感,在系统中的应用效果也收到了用户的好评。     

基于遗传算法的BP网络在导弹武器系统元器件贮存可靠性预测中的应用

针对目前BP神经网络在应用中,网络结构难以确定以及网络极易陷入局部解问题,用遗传算法优化神经网络的连接权和网络结构,并在遗传进化过程中引入交叉概率和变异概率与个体的适度值相联系,改进了操作算子,而且在交叉操作后又引入模拟退火机制,提高遗传算法的局部搜索能力.建立了基于改进遗传算法的BP网络贮存可靠性预测模型,并以某型导弹武器系统的元器件进行实例分析,计算结果表明,该方法预测的准确性高,且预测结果稳定.     

A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

Neural network systems to reproduce crash behavior of structural components

The use of neural networks as global approximation tool in crashworthiness problems is here investigated. Neural networks are not only asked to return some meaningful indices of the structural behavior but also to reproduce load-time curves during crash phenomena. To contain the number of examples required for the training process, parallel subsystems of small neural networks are designed. Design points for the training process are obtained by explicit finite element analyses performed by PAMCRASH. The settlement of the points in the design domain is defined using a maximum distance concept. The procedure is applied to different typical absorption structures made of aluminum alloy: riveted tubes, honeycomb structures, longitudinal keel beam and intersection elements of helicopter subfloors.     

An immune oriented multi-agent system for biological image processing

In this article, we present a parallel image processing system based on the concept of reactive agents. Our system lies in the oRis language, which allows to describe finely and simply the agents’ behaviors to detect image features. We also present a method of segmentation using a multi-agent system, and two biological applications made with oRis. The stopping of this multi-agent system is implemented through a technique issued from immunology: the apoptosis.     

遗传算法在CDMA网络基站分布规划中的应用

CDMA网络的基站分布规划属于多目标组合优化问题，为此在遗传算法的基础上提出了一种基于成本控制的CDMA网络基站分布规划算法。该算法综合考虑了在CDAM网络规划实际工程中的多种规划目标和要求，能够找到符合CDMA网络建设需要的基站分布方案。     

关于本地传输网网络优化的探讨

根据长期工作经验,对现有网络存在的问题进行分析,提出对本地传输网网络优化的有关建议。