The Geometry of M/D/1 Queues and Large Deviation

Since an M/D/1 queue is represented by a Markov chain, we can consider the set of all the M/D/1 queues as a subset of Markov chains. A geometric structure is induced from the geometric structure of the set of Markov chains, which forms an exponential family. In this paper, we show that in the large deviation of the tail probability of the queue length of an M/D/1, the rate function and a twisted Markov chain, etc., are represented in terms of the geometry. Moreover, in the importance sampling (IS) simulation for the M/D/1 queue, we elucidate the geometric relation between the underlying distribution and a simulation distribution, and evaluate the variance of an IS estimate by geometric quantities.     

抓好用邓小平理论武装人这个根本

本文通过对学校用邓小平理论武装人“五抓”工程(抓骨干、抓课堂主渠道、抓活动、抓实践、抓舆论)的具体论述,阐明了大学生学习邓小平理论的有效途径和新方法。     

A methodology of determining aggregated importance of engineering characteristics in QFD

Quality function deployment (QFD) is a planning and problem-solving tool that is gaining acceptance for translating customer requirements (CRs) into engineering characteristics (ECs) of a product. Deriving the importance of ECs is a crucial step of applying QFD. However, the inherent fuzziness in QFD presents a special challenge to effectively evaluate the importance of ECs and correlation among them. Furthermore, degree of impact of an engineering characteristic (EC) on the other ECs also reflects the importance of the ECs. In previous studies, those impacts were neglected or simply represented using a linear combination in determining the importance of ECs. To address this issue, in this paper, a new methodology of determining aggregated importance of ECs is presented which involves the consideration of conventional meaning of importance of ECs as well as the impacts of an EC on other ECs. In the proposed methodology, fuzzy relation measures between CRs and ECs as well as fuzzy correlation measures among ECs are determined based on fuzzy expert systems approach. These two types of measures are then used to determine the aggregated importance of ECs. An example of design of a digital camera is used to illustrate the proposed methodology.     

Situational influences on ethical decision-making in an IT context

Processes of ethical decision-making are thought to depend on the issue faced when making the decision. We examined the processes by examining student's reactions to five scenarios involving IT use. Data were collected using a questionnaire following a group discussion. The results showed that ethical decision-making processes did indeed vary by scenario, suggesting that a single-issue approach is inadequate for studying ethical decision-making. Perceived importance of the ethical issue was a factor in the scenarios, but it did not have an all-inclusive influence on the decision-making of the participants. The results were considered in the context of theories and Mason's ethical issues of the information age. We offer advice to managers on how to limit unethical behavior.     

视觉注意引导和区域竞争控制的医学图像分割

模糊连接度已经成为医学图像分割的实用方法，但其困难在于需要设定多种子点，自动给定的手段不是很有效.为此将种子点等价于视觉特征显著点，提出了在视觉注意模型引导下种子点给定的新方法.通过研究显著点定位与图像特征概率密度估计之间的关系，引入新的视觉特征估计地图，构造了注意计算模型，采用无阈值方法定位各类物体的视觉显著点并用于引导区域增长方式的图像分割.新的注意计算模型的定量描述能力较以往的模型有很大提高，适用于处理模糊图像.新方法能够完全自动定位种子点，有效分割图像，准确率高.引入多种子点之间的竞争策略加快了图像分割中的区域增长处理过程.     

基于重要抽样的联锁软件安全性评估

根据计算机联锁软件失效危险严重性等级的不同,科学地建立了安全性评估指标,介绍了重要抽样的基本原理,以及利用层次分析法确定抽样概率。重点研究了基于重要抽样方法在计算机联锁软件测试和评估中的具体应用。实验证明,该方法在不影响评估结果的准确性情况下,解决了传统联锁软件测试效率低的问题。     

基于综合重要度的电网关键线路辨识方法

更加精准快速识别出电网关键线路，对提高电网运行的稳定程度以及预防电网连锁故障具有重要意义。文章首先基于复杂网络理论提出改进潮流介数指标，从结构角度判别系统受到功率扰动后线路的脆弱程度；然后基于熵理论，提出计及线路负载率的加权潮流转移熵指标，克服原有指标中只考虑转移潮流分布均匀性的不足；最后建立包括以上2种指标的综合重要度评估指标，更加全面地衡量线路在电力系统中的重要程度。通过对IEEE 39节点系统进行仿真，得出了不同攻击方式下系统的改进网络传输效率变化曲线图，证明了综合重要度指标的有效性，对预防电力系统连锁故障具有重要意义。     

基于事故树分析的水泵断轴事故的危险评价

基于事故致因理论建立水泵断轴事故模型,将水泵断轴事故危险源分为工作应力超负荷、工作强度超负荷、泵轴维护正确三类,提出基于事故树分析法的水泵断轴危险性专项评价方法。通过对最小割集和最小径集的分析可知,对水泵断轴影响最大的是作用时间过长、次数过多、承受应力过大、对中不符合要求、装配过紧或过松、形位公差过大。对水泵断轴事故的预防提出建议,对水泵运行时间进行合理分配,正确合理地装配水泵并且时刻关注水泵的运行状态。     

Point estimate-based importance analysis for structural models with correlated variables

Importance analysis is conducted to find the contributions of the inputs to the output uncertainty. In this work, a point estimate-based importance analysis algorithm is established for models involving correlated input variables, and the variance contribution by an individual correlated input variable is decomposed into correlated contribution and uncorrelated contribution. In the established algorithm, the correlated variables are orthogonalised to generate corresponding independent variables, and the performance function is reconstructed in the independence space. Then, the point estimate is employed to compute the variance-based importance measures in the independence space, by which the variance contribution of the original correlated variables, including the correlated part and uncorrelated part, can be obtained. Different point estimate methods can be employed in the proposed algorithm; thus, the algorithm is adaptable and improvable. The proposed algorithm avoids the sampling procedure, which usually consumes a heavy computational cost. Discussion of numerical and engineering examples in this work has demonstrated that the proposed algorithm provides an effective tool to deal with uncertainty analysis involving correlated inputs.     

Learning effective state-feedback controllers through efficient multilevel importance samplers

Monte Carlo sampling can be used to estimate the solution of path integral control problems, which are a restricted class of nonlinear control problems with arbitrary dynamics and state cost, but with a linear dependence of the control on the dynamics and quadratic control cost. Although importance sampling is used to improve numerical computations, the effective sample size may still be low or many samples could be required. In this work, we propose a method to learn effective state-feedback controllers for nonlinear stochastic control problems based on multilevel importance samplers. In particular, we focus on the question of how to compute effective importance samplers considering a multigrid scenario. We test our algorithm in finite horizon control problems based on Lorenz-96 model with chaotic and non-chaotic behaviour, showing, in all cases, that our multigrid implementation reduces the computational time and improves the effective sample size.