Low-pressure pyrolysis studies of a new phosphorus precursor: Tertiarybutylbis(dimethylamino)phosphine

The low pressure decomposition of tertiarybutylbis(dimethylamino) phosphine, (t-Bu)P(NMe₂)₂, (TBBDMAP), has been studied on quartz and deposited GaP and InP surfaces. This new phosphorus precursor has been found to pyrolyze on quartz surfaces at much lower temperatures than the related compounds tertiarybutylphosphine, (t-Bu)PH₂, (TBP) and tris(dimethylamino)phosphorus, P(NMe₂)₃, (TDMAP). In contrast to the results obtained for TDMAP, GaP and InP surfaces decrease the decomposition temperature of TBBDMAP only slightly. The TBBDMAP reaction products were dimethylamine, methylmethyleneimine, and isobutylene, consistent with previous pyrolysis studies of TBP and TDMAP.     

多坐标系下目标跟踪的联合滤波

针对雷达目标观测和处理在不同的坐标系下完成，本文提出了联合滤波算法来跟踪机动目标。该算法以卡尔曼滤波器为基础，直角坐标系下和极坐标系下的算法相联合，不仅克服了两种坐标系下滤波算法的不足，而且对机动目标有很好的跟踪效果。仿真实验结果表明了该算法的有效性。     

北京城市供水安全及对策研究

“十一五”期间是首都经济社会快速发展的关键时期，也是应对水资源紧缺、保障供水安全的关键时期。确保首都供水安全是北京水务工作的第一要务，北京市水务局针对城市供水存在的主要矛盾和问题，对城市供水水源、水质水量、水厂、管网、设施等情况进行了全面调查，确定了工作思路，并据此提出了保障城市供水安全的目标和措施。     

真空阴极弧离子镀类金刚石碳（DLC）膜的碳弧稳定性研究

选用氩气、氩气加氢气、氩气加乙炔等气体作为介质，石墨作为靶材进行真空阴极弧离子镀来制备类金刚石碳膜。石墨电弧有其独特的电弧特性曲线，不同气体介质对碳弧特性的影响不同，磁场的大小对电弧的稳定性有很大作用，碳弧下基片偏流随电弧电压的增加而减小，试验得到表面光滑的类金刚石碳（DLC）膜，对膜的表面进行了SEM分析。     

基于MPC850 VxWorks系统的BSP设计

首先介绍嵌入式系统VxWorks及其启动过程;分析了基于MPC 850最小系统的硬件和BSP的执行流程;重点研究了MPC850BSP的设计与应用程序加载,包括其硬件驱动程序的设计、应用程序加载、建立调试环境和target server的配置等;基于MPC850系统的Vxworks BSP调试平台的实现,对Vxworks上层应用软件和底层硬件驱动的并行开发有着很重要的意义。     

智能视频监控中运动目标检测的研究

针对某武器试验中背景复杂,现有的背景差分法在背景模型的维持和更新不能用于长期和复杂的场景,以及对近地目标提取检测困难的问题,提出一种改进的背景差分法。该算法采用结合邻域信息的背景差分法和最大方差阈值法,能够在一定程度上减小背景滞后更新引起的运动目标检测误差,且使目标边缘提取更加明确,从而提高了系统的运行速度,实现复杂背景下的运动目标检测。在Visual C＋＋6.0中用OpenCV实现了相关算法的设计,并给出了完成系统任务所需的部分关键代码,实现了运动目标和试验场景的分离与提取。仿真实验验证了该算法的有效性以及实时性。     

中职学校的计算机上机实验课

通过分析当今社会对中职学校学生的要求和目前中职学校计算机上机实验课中存在的问题,探讨了如何提高中职学校的计算机上机实验课程的教学水平。并根据当前中职学生的状况和特点,结合平时的教学经验,提出一些教学观念。     

The Bivariate Transmuted Family of Distributions: Theory and Applications

The bivariate distributions are useful in simultaneous modeling of two random variables. These distributions provide a way to model models. The bivariate families of distributions are not much widely explored and in this article a new family of bivariate distributions is proposed. The new family will extend the univariate transmuted family of distributions and will be helpful in modeling complex joint phenomenon. Statistical properties of the new family of distributions are explored which include marginal and conditional distributions, conditional moments, product and ratio moments, bivariate reliability and bivariate hazard rate functions. The maximum likelihood estimation (MLE) for parameters of the family is also carried out. The proposed bivariate family of distributions is studied for the Weibull baseline distributions giving rise to bivariate transmuted Weibull (BTW) distribution. The new bivariate transmuted Weibull distribution is explored in detail. Statistical properties of the new BTW distribution are studied which include the marginal and conditional distributions, product, ratio and conditional momenst. The hazard rate function of the BTW distribution is obtained. Parameter estimation of the BTW distribution is also done. Finally, real data application of the BTW distribution is given. It is observed that the proposed BTW distribution is a suitable fit for the data used.     

A Further Comparison of Splitting Rules for Decision-Tree Induction

One approach to learning classification rules from examples is to build decision trees. A review and comparison paper by Mingers (Mingers, 1989) looked at the first stage of tree building, which uses a splitting rule to grow trees with a greedy recursive partitioning algorithm. That paper considered a number of different measures and experimentally examined their behavior on four domains. The main conclusion was that a random splitting rule does not significantly decrease classificational accuracy. This note suggests an alternative experimental method and presents additional results on further domains. Our results indicate that random splitting leads to increased error. These results are at variance with those presented by Mingers.