近代城市空间改造的时空进程

近代城市人口的增长、城市职能的变化、市政机构的出现带来了城市空间的转变。２０世纪初，中国开始了大范围的城市基础设施改造与新建。其中最有代表性的是拆城、填濠、修筑环城马路的工程，此后全国大部分的城市改造都遵循了相似的模式。本文通过对近１２００座治所城市城墙变动信息的研究发现，２０世纪大规模的城市空间改造最初主要从东南沿海省份开始，３０年代末至４０年代的战争打破了这一过程，但随着新中国成立后城市建设的恢复，空间改造的进程继续向西部省份推进，总体上呈现由东向西，由中心向边缘发展的特点。     

Bayesian Classifiers Applied to the Tennessee Eastman Process

Fault diagnosis includes the main task of classification. Bayesian networks (BNs) present several advantages in the classification task, and previous works have suggested their use as classifiers. Because a classifier is often only one part of a larger decision process, this article proposes, for industrial process diagnosis, the use of a Bayesian method called dynamic Markov blanket classifier that has as its main goal the induction of accurate Bayesian classifiers having dependable probability estimates and revealing actual relationships among the most relevant variables. In addition, a new method, named variable ordering multiple offspring sampling capable of inducing a BN to be used as a classifier, is presented. The performance of these methods is assessed on the data of a benchmark problem known as the Tennessee Eastman process. The obtained results are compared with naive Bayes and tree augmented network classifiers, and confirm that both proposed algorithms can provide good classification accuracies as well as knowledge about relevant variables.     

基于层次分析法的多媒体教学评价研究综述

从基于层次分析法的多媒体教学评价角度,对教学条件、教学课件、课堂教学效果及实验教学等领域的多媒体教学评价进行了综述研究,就目前这些研究方向存在的问题及其发展趋势进行了点评概括.     

中国商品流通现代化的模糊综合评价研究

完善了商品流通现代化指标体系,并运用模糊综合法将商品流通现代化指标转换成了指数。研究发现商品流通现代化水平与其区域位置、总体经济实力密切相关,且受到产业结构的影响。同时,通过基于指数的聚类分析得到如下结论:"率先发展型区域"要抓住历史机遇,培养创新型人才,保持领先地位;"积极追赶型区域"要发挥地理优势,打破省之间、行业和部门之间、所有制之间的界限,积极参与各种区域经济合作;"流通欠发达型区域"要进一步推进和实施西部大开发战略,推进物流现代化。     

论消费在国际传媒生产总过程中的地位

在国际传媒生产贸易中，传媒产品消费的本质就是价值认可式的精神性消费，在自愿获得消费物的消费中，得到精神与心灵上的满足，实现对一国传媒产品的最优化接受。由此本质出发，总结了消费的六种类型，在分析梳理其逻辑关系的基础上，论证了消费在国际传媒生产总过程中的主导地位。     

广告语篇连贯形成的动态模式分析

指出作为一种特殊的交际形式,广告语篇具有隐含性特点,因此,其连贯也呈现出鲜明的特征,即其连贯是隐性的;广告语篇连贯的形成过程是一个语言使用者不断建立心理空间的动态过程。     

程序正义理念下的死刑复核问题探析

受我国传统刑事诉讼价值取向的影响,现行死刑复核程序在实践运行中一直存在着很多问题,大大影响到死刑复核程序功能的实现。死刑核准权统一收归最高人民法院行使,既让我们在死刑复核问题上看到了希望,又给我们提出了新的研究课题。虽然近期最高人民法院及相关部门颁布了一系列指导死刑复核程序运作的相关规定,但从实际操作效果来看,仍有一些问题需要进一步明确。     

中华人民共和国民族互动过程述论

中华人民共和国成立之后,在中国共产党的领导下,在人民当家作主的新平台上,经过新一轮的民族互动,在马克思主义民族理论的基础上,中国各民族实现了现代意义的民族团结。     

Semiparametric regression methods for temporal processes subject to multiple sources of censoring

Process regression methodology is underdeveloped relative to the frequency with which pertinent data arise. In this article, the response-190 is a binary indicator process representing the joint event of being alive and remaining in a specific state. The process is indexed by time (e.g., time since diagnosis) and observed continuously. Data of this sort occur frequently in the study of chronic disease. A general area of application involves a recurrent event with non-negligible duration (e.g., hospitalization and associated length of hospital stay) and subject to a terminating event (e.g., death). We propose a semiparametric multiplicative model for the process version of the probability of being alive and in the (transient) state of interest. Under the proposed methods, the regression parameter is estimated through a procedure that does not require estimating the baseline probability. Unlike the majority of process regression methods, the proposed methods accommodate multiple sources of censoring. In particular, we derive a computationally convenient variant of inverse probability of censoring weighting based on the additive hazards model. We show that the regression parameter estimator is asymptotically normal, and that the baseline probability function estimator converges to a Gaussian process. Simulations demonstrate that our estimators have good finite sample performance. We apply our method to national end-stage liver disease data. The Canadian Journal of Statistics 48: 222–237; 2020 © 2019 Statistical Society of Canada     

Risk aggregation with dependence and overdispersion based on the compound Poisson INAR(1) process

Abstract

This paper considers an extension of the classical discrete time risk model for which the claim numbers are assumed to be temporal dependence and overdispersion. The risk model proposed is based on the first-order integer-valued autoregressive (INAR(1)) process with discrete compound Poisson distributed innovations. The explicit expression for the moment generating function of the discounted aggregate claim amount is derived. Some numerical examples are provided to illustrate the impacts of dependence and overdispersion on related quantities such as the stop-loss premium, the value at risk and the tail value at risk.