Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

基于遗传算法的装备采购决策优化研究

在装备采购中，由于需求单位地域分布和担负的任务各不相同，对装备的品种、数量、时限要求也就不一样，如何使装备采购科学化、合理化，是一个涉及多变量、多目标的复杂系统问题。在综合考虑装备采购各项因素的基础上，构建多约束条件下的多目标模糊指派模型，提出了基于遗传算法的解决方案，最后通过案例进行仿真实验，验证该算法的可行性和有效性，解决了采用传统优化方法难以解决的装备采购优化决策问题。     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

城市道路交通问题与对策探讨

从中国大城市交通堵塞现象着手,研究了机动车辆的增加与道路通行能力的关系,以及机动车迅速增长所带来的环境污染问题,分析了问题产生的原固及其危害程度,探讨改善城市交通的途径和解决的方案,提出适当限制个人轿车,积极发展轨道交通,规划建设中心网络城市的现点。     

基于TMS320C40的FFT算法改进及应用

讨论了充分利用C4 0的硬件并行结构进行实数FFT的并行算法 ,并在地震勘探信号处理中得以应用     

中国与中亚国家交通运输合作探析

中国新疆与周边国家已开通国际公路客货运输线路101条，铁路运输合作中亚欧第二大陆桥中亚段的运行状况整体良好。与中亚国家交通运输合作的障碍性因素主要表现为：技术性障碍突出，交通运输通而不畅，有效运力不足，运输成本上扬。具备有利的自然条件和发展潜力，建立欧亚陆桥运输走廊的愿景与可能趋向统一，经济全球化和区域经济一体化发展的促进，及良好的政治外交关系的保障，有利于双方共建欧亚大陆无障碍运输畅通走廊愿景的实现。     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

传统科技视野下的恐怖主义及其应对

科学技术的发展及其被恶意运用,使当代的恐怖主义活动变得更加复杂多样和令人恐慌.掌握和使用高科技的超级恐怖主义组织的确存在,但对于一般恐怖分子而言,高科技的运用还不大现实.多数情况下,都是传统通用科技引导着普通的恐怖主义活动.恐怖活动与传统通用科技相伴发展的历史事实,表明传统通用科技对恐怖主义与反击恐怖主义双重力量扩张所起的作用,具体体现在武器技术、交通运输和通信技术的应用等方面.科学技术既是恐怖主义盛行的因素,也是恐怖主义的克星,运用高科技手段反击恐怖主义也是我们的必然选择.     

基于RSA的电子商务信息加密技术研究

21世纪是网络信息时代,电子商务的迅猛发展和普及打破了人们传统的经营和消费理念,网上消费已成为一种新的消费形式,但随之而来的便是电子商务赖以生存和发展的安全问题。文章主要通过对电子商务安全隐患的分析,论证了数据加密技术在电子商务安全中的作用,重点探讨了RSA公钥加密算法,并通过实例对其加密原理、计算复杂性等安全性问题作了详尽的分析和阐述。