Current status and challenges in PEMFC stacks, systems and commercialization

Polymer electrolyte membrane fuel cells(PEMFCs)operate atlowtemperatures(60~80℃),offer a fast start-up and shut downti me(few minutes),fast response to changing electric loads,andcan sustain unli mited thermal cycles·They are ideally suited fortransport…     

嵌入式操作系统Windows CE.NET中Nk.bin文件的自启动实现方法

本文介绍了嵌入式操作系统Windows CE.NET的特点及其开发流程,详细介绍了Nk.bin文件的自启动实现方法.     

一种大信噪比下的BPSK信号解调方法

提出了一种基于时间测量的BPSK信号解调方法 ,介绍了解调原理并给出了实验结果。该方法属于非相干解调方式 ,可以采用软件解调 ,需要的硬件电路很少 ,而且可以产生数据的同步时钟。该方法适合中低速大信噪比BPSK信号的解调     

基于CMPCA的化工生产过程性能监测与故障诊断

根据化工生产过程的间歇反应特点,提出了一种基于一致多方向主元分析(CMPCA)的过程性能监测与故障诊断方法.首先基于动态时间规整DTW(Dynamic Time Warping)技术对批次数据进行同步化,􀁯从而使得用于建模和诊断的数据均具一致性,保证了过程性能监测与故障诊断的.     

目前云南钢铁工业发展的对策

分析了促进我国钢铁工业持续、高速发展的因素,借鉴世界主要产钢国过去100年发展的历程,对我国今后20年钢铁需求量进行了预测,讨论了云南钢铁工业发展的有利条件和主要制约因素,提出了加快云南钢铁工业发展的对策。     

关于固定资产减值折旧核算问题及建议

随着(企业会计制度)及(企业会计准则——固定资产)的颁布实施。企业的会计信息质量得到了提高，但同时也增加了会计核算成本。本文通过举例说明固定资产减值折旧核算存在的问题，提出了对固定资产减值和折旧进行双轨核算的建议。以更简便、更合理地进行固定资产减值折旧核算。     

D-T中子穿透铁球伴生γ射线泄漏能谱实验研究

建立了系列厚度为3、6、11、16、21．8cm的铁球基准装置。用BC-501A谱仪测量了D-T中子穿透铁球伴生γ射线泄漏能谱，能量范围为0．5～5MeV。通过能谱分析，观测到铁球厚度对能谱有一定影响。利用MCNP4A程序和t-2、ENDF／B-V、ENDF／B-Ⅵ和FENDL-2等数据库对实验进行了模拟计算，并将计算结果与实验结果进行了比较。γ射线能谱实验误差为4％～6％。     

神经网络PID算法在光照度控制系统中的应用

本文提出一种基于神经网络PID的光照度控制系统．为缺乏精确数学模型及非线性的时象——高压钠灯，提供了一种有效的控制方案。仿真及实验结果表明．这种系统可获得满意的控制效果。     

Evaluation of singular integrals in the symmetric Galerkin boundary element method

The implementation of the symmetric Galerkin boundary element method (SGBEM) involves extensive work on the evaluation of various integrals, ranging from regular integrals to hypersingular integrals. In this paper, the treatments of weak singular integrals in the time domain are reviewed, and analytical evaluations for the spatial double integrals which contain weak singular terms are derived. A special scheme on the allocation of Gaussian integration points for regular double integrals in the SGBEM is developed to improve the efficiency of the Gauss–Legendre rule. The proposed approach is implemented for the two-dimensional elastodynamic problems, and two numerical examples are presented to verify the accuracy of the numerical implementation.     

NeC4.5: neural ensemble based C4.5

Decision tree is with good comprehensibility while neural network ensemble is with strong generalization ability. These merits are integrated into a novel decision tree algorithm NeC4.5. This algorithm trains a neural network ensemble at first. Then, the trained ensemble is employed to generate a new training set through replacing the desired class labels of the original training examples with those output from the trained ensemble. Some extra training examples are also generated from the trained ensemble and added to the new training set. Finally, a C4.5 decision tree is grown from the new training set. Since its learning results are decision trees, the comprehensibility of NeC4.5 is better than that of neural network ensemble. Moreover, experiments show that the generalization ability of NeC4.5 decision trees can be better than that of C4.5 decision trees.