Extended Hazard Regression Model for Reliability and Survival Analysis

We propose an extended hazard regression model which allows the spread parameter to be dependent on covariates. This allows a broad class of models which includes the most common hazard models, such as the proportional hazards model, the accelerated failure time model and a proportional hazards/accelerated failure time hybrid model with constant spread parameter. Simulations based on sub-classes of this model suggest that maximum likelihood performs well even when only small or moderate-size data sets are available and the censoring pattern is heavy. The methodology provides a broad framework for analysis of reliability and survival data. Two numerical examples illustrate the results.     

参数绘图的数据传递方法及其程序设计研究

通过采用混合编程方法并利用接口数据，Ｃ应用程序能够直接调用已有ＦＯＲＴＲＡＮ子例程生成的样板图来实现参数绘图。文中着重论述了入口数据、文件和内存等三种参数传递方法的原理，给出了相应的程序流程。最后，分析了Ｗｉｎｄｏｗｓ环境下Ｃ应用程序调用ＦＯＲＴＲＡＮ子例程的几种方法。     

粗集神经网络系统及其应用

讨论了粗集神经网络系统及其在心电图自动识别中的应用。根据识别需要,从MIT心电图数据库获取心电图特征参数,根据粗集理论对属性进行优化,并用BP神经网络进行学习。运用这些特征参数和训练好的BP神经网络对心电图进行分类,识别准确率达到90%。     

遗传算法应用于并联管道计算中的研究

传统求解并联管路的水力计算的方法不是精度低就是限制条件多。设计了一种改进的遗传算法求解的方案，对适应度函数的选取作了详尽地分析，并提出了可增强局部搜索能力的微调变异算子。并联管路的水力计算实例证明了改进的遗传算法的有效性。     

行波管“冷参数”测试技术的研究

针对因螺旋线行波管慢波线的结构特殊,导致其管内输能机构和切断衰减器的反射系数不易测量的问题,提出了利用多点法对输能机构和切断衰减器的反射系数进行测量的方法,并讨论了测试中所用探针反射系数的测试技术。该方法具有无损伤、测试方便等优点,也可用于其他类似特殊结构反射系数的测量。     

Influence of Distributional Shape of Substance Parameters on Exposure Model Output

Uncertainty of environmental concentrations is calculated with the regional multimedia exposure model of EUSES 1.0 by considering probability input distributions for aqueous solubility, vapor pressure, and octanol-water partition coefficient, K(ow). Only reliable experimentally determined data are selected from available literature for eight reference chemicals representing a wide substance property spectrum. Monte Carlo simulations are performed with uniform, triangular, and log-normal input distributions to assess the influence of the choice of input distribution type on the predicted concentration distributions. The impact of input distribution shapes on output variance exceeds the effect on the output mean by one order of magnitude. Both are affected by influence and uncertainty (i.e., variance) of the input variable as well. Distributional shape has no influence when the sensitivity function of the respective parameter is perfectly linear. For nonlinear relationships, overlap of probability mass of input distribution with influential ranges of the parameter space is important. Differences in computed output distribution are greatest when input distributions differ in the most influential parameter range.     

Ivomec—F驱杀牦牛寄生虫后血液生理生化值的测定

Ivomec—F(含1％Ivermectin和1％Clorsulon,以下简称F药)是一种防治家畜体外寄生虫的广谱驱虫药,用该药驱杀牦牛主要寄生虫后,测定其血液生理生化值。结果,F药按1mL/50kgBW皮下注射患主要寄生虫的牦牛后,试验组牦牛RBC、WBC、Hb、BPC等生理指标与对照组相似,TTT、ZnTT、SGPT、Il、TP、A、G、SGOT、ACP、ALP、BUN、BS等生化指标与对照组比较差异不显著(P>0.05),该药对牦牛肝功、肾功、骨骼、心脏、蛋白质和糖代谢等均无任何影响,说明F药按1 mL/50kgBW的剂量驱杀寄生虫对牦牛的血液生理生化值无显著影响。     

Modifying a central composite design to model the process mean and variance when there are hard-to-change factors

Summary.  An important question within industrial statistics is how to find operating conditions that achieve some goal for the mean of a characteristic of interest while simultaneously minimizing the characteristic's process variance. Often, people refer to this kind of situation as the robust parameter design problem. The robust parameter design literature is rich with ways to create separate models for the mean and variance from this type of experiment. Many times time and/or cost constraints force certain factors of interest to be much more difficult to change than others. An appropriate approach to such an experiment restricts the randomization, which leads to a split-plot structure. The paper modifies the central composite design to allow the estimation of separate models for the characteristic's mean and variances under a split-plot structure. The paper goes on to discuss an appropriate analysis of the experimental results. It illustrates the methodology with an industrial experiment involving a chemical vapour deposition process for the manufacture of silicon wafers. The methodology was used to achieve a silicon layer thickness value of 485 Å while minimizing the process variation.     

酒精蒸馏工序重要工艺参数的控制

影响蒸馏塔运行的因素较多,各变量之间相互关联,交叉藕合,工艺参数最为复杂,要使蒸馏过程物料进出平衡,热量平衡,以及各控制点压力、温度、提取成品酒稳定,选择正确的控制方案,解决合理的变量配对至关重要。标志塔正常运行的主要工艺参数是蒸汽包压力。粗塔顶温、精塔中温、冷凝器酒气温度、塔底液位。     

由桥梁动力响应识别过桥汽车参数的灵敏度方法

为了识别通过桥梁汽车的参数，提出了在灵敏度分析的基础上由简支梁桥动力响应识别过桥汽车参数的方法。将汽车抽象为两自由度五参数模型，用有限元方法计算桥梁的动力响应。从对未知参数的猜测值开始，由测试或模拟计算的动力响应用最小二乘法和规则化技巧识别过桥汽车参数，用邻近两次识别参数的百分相对误差（RPE）控制迭代过程的终止。由数值模拟结果可知，识别得到的汽车参数是令人满意的，其中质量的识别精度最高，表明该方法识别过桥汽车参数可行。