现代意义下作战模型的研究

本文阐述了现代战争的特点，构造了现代意义下的作战模型，通过求解与分析，指明信息在现代战争中的重要作用和对未来战争的指导意义。     

基于可拓论的工业水分过程系统综合建模

介绍了工业水分过程系统建模的研究方法。该文采用数学机理模型、经验模型、神经网络模型在物元模型的基础上综合方法，建立了大时延、大流量、大范围非线性时变的烟丝水分过程的模型。该模型以数学机理模型的解作为初始点，经验模型作为全局调节器，菱形思维神经网络模型作为局部调节器，从而使该模型更接近于实际工业过程。此方法物理机理明晰、能获得工业过程的全局优化结果、能解决系统中一些结构不良问题等。仿真结果表明：较之三种模型的有效性，对于解决复杂工业过程控制系统问题，可知工程方法是一条可探索途径。     

对三个民族尝味能力测定结果的统计分析

利用离散多元分析方法对三个民族尝味能力的测定结果进行了统计分析,结果表明:三个民族间的PTC尝味阈值差异高度显著,味盲率间差异高度显著;男女尝味阈值差异高度显著,男女味盲率差异高度显著.     

基于随机Petri网的客户/服务器模型及其分析

提出了一种基于随机Petri网的客户 服务器模型 ,模拟了客户 服务器系统的基本工作原理 ,在此基础上 ,利用随机Petri网的时间特性对该模型进行了定量分析 .     

含有纯滞后对象的控制方法

评述纯滞后对象控制的两种典型方法─—大林算法和纯滞后补偿法的原理、优缺点、设计要求及存在问题，并讨论了两者的联系。     

激光开槽、埋槽电极硅太阳电池

报道一种新颖的激光开槽、埋槽电极硅太阳电池的结构、工艺流程及其研制结果。在ＡＭ１．５，２５℃，１００ｍＷ／ｃｍ２的条件下，以面积为４５ｃｍ３的３６片硅片研制的硅太阳电池的输出参数的平均值为ＪＳＣ＝３６．１ｍＡ／ｃｍ２，Ｖ∞＝６３３ｍＶ，Ｆ．Ｆ．＝０．７９８，η＝１８．２３％，最后分析了种高性能硅太阳电池的设计特点。     

Isolation and purification of BVⅠ-2H from bee venom and analysis of its biological action

The medical use of bee venom for rheumatoid arthritis ( RA ) has a very long tradition. In this study, isolation and purification of polypeptides from bee venom were carried out on sephadex chromatography, heparin sepharose CL-6B chromatography and HPLC. Several fractions were extracted, and their effects on activation of splenocyte and THP-1 cell were studied. The inhibitory fraction was selected for further studies. Finally, BVⅠ-2H that the HPLC elution profiles was a single peak was isolated by C8 column. ESI- MS detection results showed that BVⅠ-2H was a fraction of bee venom, and the molecular weight of the major component was 644.8. BVⅠ-2H could inhibit ConA-induced splenocyte proliferation, IL-1 production and interfere with splenocyte cycle in mice. Moreover, BVⅠ-2H could inhibit PMA-induced TNFα production in THP-1 cells, which was due to its inhibitory effects on TNFα mRNA expression and protein phosphorylation of IκBα. Our studies indicated that BVⅠ-2H was one of the anti-inflammatory components of bee venom.     

一种基于模糊神经网络的自适应模糊辨识方法

基于改进的T-S模型，提出一种自适应模糊神经网络模型(AFNN)。首先，基于模糊竞争学习算法确定系统的模糊空间和模糊规则数，并得出每个样本对每条规则的适用程度。其次，利用卡尔曼滤波算法在线辨识AFNN的后件参数。AFNN具有结构简洁，逼近能力强，能够显著提高辨识精度，并且辨识的模糊模型简单有效。最后，将该AFNN用于非线性系统的模糊辨识，仿真结果验证了该方法的有效性。     

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.     

工矿企业能量平衡通用模式的研究

提出了适用于工矿企业能量平衡的一种通用模式，将与ＧＢ３４８４－８３《企业能量平衡通则》再增加“一表两图”──“企业能量平衡表”、“企业能源网络图”和“企业能流图”的效果相一致，能更加科学、合理地反映企业能量平衡的结果。