汉语比喻与汉文化

文化与语言具有双向互动性,文化影响着不同民族的语言哲学观,制约着该语言社团全体成员运用语言对客观世界的认知与摹写。汉语修辞是汉文化的重要组成部分,汉文化基因对句法单位的象似组合,汉语比喻辞格的生成都具有某种编程式的钳控。汉语比喻的构建、喻体取舍、喻点的多"边"二"柄",无不潜存着丰富的汉文化信息。     

IPPS Sampling Plans Excluding Adjacent Units

The concept of inclusion probability proportional to size sampling plans excluding adjacent units separated by at most a distance of m (≥ 1) units {IPPSEA plans} is introduced. IPPSEA plans ensure that the first-order inclusion probabilities of units are proportional to size measures of the units, while the second-order inclusion probabilities are zero for pairs of adjacent units separated by a distance of m units or less. IPPSEA plans have been obtained by making use of binary, proper, and unequireplicated block designs and linear programing approach. The performance of IPPSEA plans using Horvitz–Thompson estimator of population total has been compared with existing sampling plans such as simple random sampling without replacement (SRSWOR), balanced sampling plans excluding adjacent units {BSA (m) plans}, probability proportional to size with replacement, Hartley and Rao's plan (1962 Hartley , H. O. , Rao , J. N. K. ( 1962 ). Sampling with unequal probabilities and without replacement . Ann. Math. Statist. 33 : 350 – 374 .[Crossref] , [Google Scholar]), Rao et al.'s strategy (1962 Rao , J. N. K. , Hartley , H. O. , Cochran , W. G. ( 1962 ). On a simple procedure of unequal probability sampling without replacement . J. Roy. Statist. Soc. B 24 : 482 – 491 . [Google Scholar]), and Sampford's IPPS plan (1967 Sampford , M. R. ( 1967 ). On sampling without replacement with unequal probabilities of selection . Biometrika 54 ( 3 ): 499 – 513 .[Crossref], [PubMed] , [Google Scholar]) using a real life population. Unbiased estimation of Horvitz–Thompson estimator of population total is not possible in these types of plans because some of the second-order inclusion probabilities are zero. To resolve this problem, one approximate variance estimation technique has been suggested.     

An integrated dominance analysis and dynamic programing approach for measuring predictor importance for customer satisfaction

Abstract

Dominance analysis is a procedure for measuring the importance of predictors in multiple regression analysis. We show that dominance analysis can be enhanced using a dynamic programing approach for the rank-ordering of predictors. Using customer satisfaction data from a call center operation, we demonstrate how the integration of dominance analysis with dynamic programing can provide a better understanding of predictor importance. As a cautionary note, we recommend careful reflection on the relationship between predictor importance and variable subset selection. We observed that slight changes in the selected predictor subset can have an impact on the importance rankings produced by a dominance analysis.     

对多目标线性规划的λ－算法的修正

本文指出运用多目标线性规划λ－算法在某些情况下会得出错误的结果，分析了发生错误的原因，并给出修正的λ－算法．     

Dynamic stochastic dominance in bandit decision problems

The aim of this paper is to study the monotonicity properties with respect to the probability distribution of the state processes, of optimal decisions in bandit decision problems. Orderings of dynamic discrete projects are provided by extending the notion of stochastic dominance to stochastic processes.     

C语言的公理语义(1)──控制结构

由于篇幅的缘故，本义从公理语义的角度主要讨论了C语言的流程控制结构的语义，而关于该语言的函数和对象的公理语义将在后续的各文章中陆续给出。     

视觉电生理诊断系统微机软件的设计

视觉电生理诊断系统是眼科诊断重要的医疗设备，整个系统由微型计算机及外部设备组成．本文在分析了系统运行要求及特点的基础上，介绍了该系统中计算机软件的设计思路，并给出采用面向对象编程方法的实现方案．     

基于最小最大后悔值的应急救灾网络构建鲁棒优化模型与算法

应急救灾过程分为两个阶段：第一阶段启动应急救灾网络构建,在灾区附近设立临时应急配送中心,并由应急资源供应方向其紧急调配应急资源;第二阶段将应急资源从临时应急配送中心向灾区受灾点进行调度,以保证救灾过程顺利进行。本文研究第一阶段应急救灾网络的构建问题,考虑到突发灾害初期灾情相关参数概率分布情况难以获取,建立了基于情景的最小最大后悔值准则的应急救灾网络构建鲁棒优化模型。求解模型时,利用有限情景集表示第二阶段的不确定性数据,并将模型化为与其等价的混合整数规划模型,利用情景松弛的迭代算法进行求解。数值试验中给出相应的绝对鲁棒模型与本文偏差鲁棒模型作了比较,结果表明基于最小最大后悔值准则的应急救灾网络优化模型具有良好的鲁棒性,而且算法也是有效的。     

COVID-19疫情下一种新的地铁平峰运营策略

地铁在城市交通中发挥着重要作用。然而，在新冠肺炎(COVID-19)疫情下，地铁的运营出现了包括消毒、限流及出行独立等多重约束。错峰出行成为了众多城市地铁运营过程中的必然选择。如何既满足居民的基本出行需求，为顺利实现复工复学提供交通支持，又能有效降低乘客感染病毒的风险与追踪密切接触者的成本成为了城市地铁运营的新目标。本文通过对北京地铁运营现状及居民的出行规律分析发现，在新型冠状病毒疫情下，地铁运营过程中存在出行需求与地铁运力不匹配，复工复产与疫情防控，乘客交叉出行数量过多等难题，并针对以上难题提出了分时段复工出行与周末可复工在内的复杂指派模型。这一指派模型不仅实现了城市关键地铁站点平峰人流量、降低疫情传播风险及追踪难度的目标，同时通过模型目标函数与约束条件的灵活修改可实现更为复杂的乘坐地铁复工复产目标。本文所提出的模型在复杂周期性平峰问题中具有较强的推广应用价值。