Bivariate models from univariate life distributions: A characterization cum modeling approach

Bivariate life distribution models are of importance for studying interdependent components. We present a generic approach by introducing a new concept of characterized model in stead of a characterized distribution. It strikes a balance between characterization and modeling approaches to eliminate their individual limitations and incorporate their respective strengths. The proposed model, being a characterized one, admits many important properties irrespective of the choice of marginal distributions. The retention of univariate IFR, DFR, IFRA, DFRA, NBU, and NWU class properties in the bivariate setup has been ensured along with some results on series combinations and convolution. No other models, available in the literature, can ensure simultaneous retention of these fundamental and extremely important class properties. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

A balancing problem for mixed model assembly lines with a paced moving conveyor

We state a balancing problem for mixed model assembly lines with a paced moving conveyor as: Given the daily assembling sequence of the models, the tasks of each model, the precedence relations among the tasks, and the operations parameters of the assembly line, assign the tasks of the models to the workstations so as to minimize the total overload time. Several characteristics of the problem are investigated. A line‐balancing heuristic is proposed based on a lower bound of the total overload time. A practical procedure is provided for estimating the deviation of any given line‐balance solution from the theoretical optimum. Numerical examples are given to illustrate the methodology. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Higher‐order Markov chain models for categorical data sequences*

In this paper we study higher‐order Markov chain models for analyzing categorical data sequences. We propose an efficient estimation method for the model parameters. Data sequences such as DNA and sales demand are used to illustrate the predicting power of our proposed models. In particular, we apply the developed higher‐order Markov chain model to the server logs data. The objective here is to model the users' behavior in accessing information and to predict their behavior in the future. Our tests are based on a realistic web log and our model shows an improvement in prediction. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

BIT系统的三态马尔可夫模型分析

BIT技术是改善系统测试性和诊断能力的重要途径,但是较高的虚警率一直是阻碍BIT广泛应用的一个重要原因。研究过程中将系统状态划分为正常、间歇、故障三种状态,建立了马尔可夫模型,分析、对比了三态模型与两态模型的关系。理论分析结果表明:基于三态模型的BIT,在提高故障检测率的同时,还可以较大程度地降低虚警率。     

一种用于机电产品测试性设计的传感器优选MINLP模型

在单故障假设条件下,考虑了传感器的失效概率和设备的故障率,提出一种以故障检测率和故障隔离率为约束条件的降低传感器费用和失效概率的混合整数非线性规划(MINLP)模型,从而为机电产品测试性设计中传感器选择问题提供了一种可行和有效的解决方法,并进行了案例验证,说明了该方法的有效性。     

攻防对抗仿真中高炮火力单元射击指挥模型

在分析高炮火力单元射击指挥过程的基础上,着重对高炮火力单元射击指挥仿真中的目标搜索模型与杀伤效果评估模型进行了深入探讨和构建。在实现高炮杀伤效果评估方面,运用蒙特卡罗方法构建了符合实际、满足仿真粒度要求的高炮着发射与空炸射击毁伤概率计算模型。实际应用表明:模型满足仿真可信度和实时性要求,对开展地面防空作战仿真具有一定的借鉴意义。     

多层卫星通信网络结构设计与分析

针对单层卫星网络时延高、网络阻塞概率大等问题,研究了多层卫星网络的系统结构及其特点。结合不同轨道卫星特点,引入分层卫星网络结构,采用Walker和极轨星座覆盖带设计法,设计了多层卫星网络星座。采用"弱连接"模型作为星际链路建立的基本原则,并对星座的覆盖性能和星际链路特性进行了仿真分析,结果表明,多层卫星网络在覆盖特性和星际链路性能上更具优势。     

以教师为中心教学模式在普通心理学教学中的应用初探

普通心理学是心理学专业学生的入门课程,其教学的目的是使学生通过学习获得对心理学体系的整体认识,并形成基本的学科框架,为其他专业课程的学习奠定基础。通过分析发现,普通心理学具有系统性、内容之间的关联性、对其他专业课堂的奠基性的学科特点和结构良好的知识特点;学生虽然有相关的朴素的心理学经验,但不具有科学的心理学专业知识的知识储备特点和成熟认知的思维特点。这些特征与教师中心取向的教学模式相吻合,同时学生的思维特点也为这种教学模式的开展提供了基础。     

基于ARCS动机模型的现代教育技术公共课教学策略初探

教育技术公共课是高校在校生提升信息意识和信息素养的一门必修课,但其教学效果一直不尽如人意。本文从分析当前教育技术公共课的现状入手,结合ARCS动机模型理论,提出了教育技术公共课改进的若干对策,以期提高这门课程的教学质量。     

基于相关性模型的舰船装备测试性分析与建模

为了提高舰船装备的综合诊断能力,在舰船设计、研制阶段就必须进行装备测试性设计工作。为此,根据舰船装备测试性要求,对装备进行了故障模式影响分析,确定了装备在设计和制造过程中所有可能的故障模式,以及每一故障模式的原因和影响,据此对装备功能和结构进行了划分。然后,利用相关性模型对舰船装备进行测试性分析与建模,建立了舰船装备组成单元的相关性图示模型、数学模型,并运用考虑可靠性和费用的优选方法,建立了舰船装备诊断树,得到舰船装备的测试方案。算例分析表明:该研究可有效提高舰船装备测试的效率,提升测试的经济性。