外语阅读与思维的关系

阅读理解是一种极为复杂的心理语言学过程，是一个以理解为目的、多层次、相互作用、不断推测的过程。阅读也是一种个人现象，是使用大量的语言想象在个体的头脑世界里无声地进行的过程。     

基于证据推理和二元语文的群体语言决策方法

一、引言 在群体决策过程中,决策者根据自己的知识、经验对方案的重要性程度进行评价.由于决策问题本身的模糊性和不确定性,决策者的最好表达方式就是自然语言.关于决策者的评价信息是自然语言的群体决策研究已经有很多.     

创新人才培养绩效云集成评价模型

针对创新人才培养绩效研究局限于事后评估、系统性不强等问题,文章从系统演化的角度对创新人才培养体系进行分析,从而构建基于管理耗散的创新人才培养绩效评价指标体系.针对创新人才培养绩效评价存在自然语言环境下复杂系统决策的不确定性问题,提出了一种云集成评判模型,既解决了自然语言下的决策不确定性,又避免了人为赋权的主观干扰,还可以方便、快捷的得到确定性的评测结果.     

基于证据推理和二元语义的群体语言决策方法

一、引言在群体决策过程中,决策者根据自己的知识、经验对方案的重要性程度进行评价。由于决策问题本身的模糊性和不确定性,决策者的最好表达方式就是自然语言。关于决策者的评价信息是自然语言的群体决策研究已经有很多。在绝大多数方法中,没有考虑决策者给出的方案评价信息可     

高磊:捕捉生活的艺术

对于艺术灵感,高磊认为,在艺术创作中,灵感占少部分。他说,创作更多的是来源于艺术家对生活、文学、美学、社会等各种知识的理解,基于此,艺术家将这种个人的理解赋予在作品中。     

统计与信息论坛2007年总目次

总目次【编委之窗】中国西部地区石油天然气产业集聚水平测度的实证研究…………………………………………胡健,焦兵(1.19、封二)自然语言理解综述………………………………………………………………………………………………刘小冬(2.5、封二)从“统计生态环境建设”看提高统计数据的质量………………………………………………………………庞皓(6.5、封二)【名家走笔】抽样调查应用与理论中的若干前沿问题………………………………………………………………………………冯士雍(1.5)中国国民经济核算的新发展和SNA修订的挑战…………………     

统计随想

大学毕业后,分配到了统计局,那时候,对统计工作是没有概念的。来到统计局,纯粹的陌生反倒带来一丝灵魂的安宁,心静了,一种回归自然的静。六年来,接触了一些专业,经历了几次普查,对统计有了统计者的理解。其实,统计的根本,在世界的每个地方都一样,朴实,客观,科学,真实。我觉得对统计数据的理解,每个人都有自己的看法,只是这种看法是建立在不同的基础之上的,有些是看表面,有些是看深层。世界本身是残酷无     

通往教育现代化的阳光之路

一、建构主义学习理论 唯物主义认为,世界是客观存在的,而每个人对世界的不同理解是由个人决定的。建构主义者完全遵从唯物主义理论,认为认识过程不能凭空而来,需要找到赋予其意义的根据,这个根据就是学习者已有的经验。学习的过程就是在原有经验的基础上对新信息的改造和重视,形成被自己理解和运用的信息,然后把它变成自己的经验再去获取其它信息,这样不断反复积累的过程。任何学科的学习和理解不像在白纸上画画,它总要涉及到学习者原有的知识结构。比如我们要理解一首古诗,具体分析一首诗,需要古代汉语,古代文学史,古代历史的知识,还有一定的表达能力等等。在这些知识的基础上,重新建构对这首古诗的理解。     

一种基于不确定语言的决策方法

0引言鉴于用具体数字来描述复杂的事物比较困难,因此,决策者采用自然语言进行决策。已有许多学者对此进行了研究[1-2,7-8],主要表现在2个方面:在评价值方面,文献[1-4]都是在评价值不缺失的情况下进行属性集结,而实际情况,由于评价的数据无法得到或者决策者本身知识的有限或者决     

大体积混凝土裂缝产生原因及防裂措施综述

近年来，随着国民经济和建筑技术的发展，建筑规模不断扩大，大型现代化技术设施或构筑物不断增多，而混凝土结构以其材料廉价物美、施工方便、承载力大、可装饰强的特点，日益受到人们的欢迎，于是大体积混凝土逐渐成为构成大型设施或构筑物主体的重要组成部分。所谓大型混凝土，一般理解为尺寸较大的混凝土，美国混凝土学会给出了大体积混凝土的定义：     

Corrections on “Exact Bayesian Variable Sampling Plans for the Exponential Distribution Based on Type-I and Type-II Hybrid Censored Samples”

Some corrections are made for the article mentioned above. These errors occured due to the floating errors in the computation of the Bayes risk which involves terms of large magnitude and opposite sign as sample size increases, that resulted in loss of accuracy in fixed precision computational tool such as Fortran language. For accurate numerical calculation, we now use the symbolic math package, Maple, to implement the calculation which can supply numerical answers accurate to any required degree of precision. Based on the new tables, some comments made earlier in Sec. 4 have been changed suitably.     

A geometric time-series model with an alternative dependent Bernoulli counting series

In this article, we first introduce an alternative way for construction of the generalized binomial thinning operator with dependent counting series. Some properties of this thinning operator are derived and discussed. Then, by using this thinning operator, we introduce an integer-valued time-series model with geometric marginals. Some conditional and unconditional properties of this model are derived and discussed. Some estimation methods are considered and for some of them, asymptotic properties of the obtained estimates are derived. Performances of the estimates are discussed through some simulations. Finally, a real data example is considered and the goodness-of-fit of this model is compared with the models based on the binomial, negative binomial, and dependent binomial thinning operators.     

Discrimination among bivariate beta-generated distributions

Some properties of the general families of bivariate distributions generated by beta dependent random variables are derived and discussed here. Some classic measures of dependence and information are derived, and their behaviours and properties are discussed as well. Finally, a discrimination procedure within this general family of bivariate distributions is proposed based on Shannon entropy. A real-life example is presented to illustrate the model as well as the inferential results developed here.     

Origins of Linguistic Zonation in the Australian Alps. Part 2 - Snell's Law

In this second paper, analysing archival SE-Australian Aboriginal word/name lists, Snell's Law is used to deduce the likely minimal sound-systems of pre Ice-Age language superfamilies - some probably dating back beyond the first occupation of Australia by humans. The deduced 'Turuwal-like' ancestral sound-system is then used as a basis for reconstructing deictic forms apparently so ancient that they seem to even unify 'PamaNyungan' and 'non-PamaNyungan' language within a single system of formal logic which, having apparently provided the semantic basis for at least 60,000 years of speech throughout the entire Australian continent, deserves to be called proto-Australian regardless of whether or not it arose in SE-Asia tens of millennia before. Whatever the exact age of this reconstructed proto-Australian, presented here for the first time, it is an order of magnitude older than any known human language and, as such, a 'Rosetta Stone' for human languages worldwide. It also provides an unprecedented window into human consciousness and perception of the world up to 75,000 years ago, which is especially significant given that humans can only have engaged in finely controlled speech and fully modern language since chance mutation of our FOXP2 gene about 120,000 years ago. These truly ancient deictic forms dating halfway back to the beginning of modern human speech, retrieved only through modern statistical analysis, provide insight into our very origins and as such are perhaps amongst the most precious cultural treasures that humanity currently possesses.1     

Markov models and Bayesian methods in image analysis

Markov random field models and Bayesian methods have provided answers to various contemporary problems in image analysis. We give a very brief introduction to the topic. In particular, we highlight the use of Bayesian methods in classifying the image into different classes. Some other current developments are also described and their relationship with other chapters in this volume is indicated. Some future directions are also outlined.     

Spatial modelling of gene frequencies in the presence of undetectable alleles

Bayesian hierarchical models are developed to estimate the frequencies of the alleles at the HLA-C locus in the presence of non-identifiable alleles and possible spatial correlations in a large but sparse, spatially defined database from Papua New Guinea. Bayesian model selection methods are applied to investigate the effects of altitude and language on the genetic diversity of HLA-C alleles. The general model includes fixed altitudinal effects, random language effects and random spatially structured location effects. Conditional autoregressive priors are used to incorporate the geographical structure of the map, and Markov chain Monte Carlo simulation methods are applied for estimation and inference. The results show that HLA-C allele frequencies are explained more by linguistic than altitudinal differences, indicating that genetic diversity at this locus in Papua New Guinea probably tracks population movements and is less influenced by natural selection than is variation at HLA-A and HLA-B.     

Approximating the distribution of a renewal process using generalized poisson distributions

The exact distribution of a renewal counting process is not easy to compute and is rarely of closed form. In this article, we approximate the distribution of a renewal process using families of generalized Poisson distributions. We first compute approximations to the first several moments of the renewal process. In some cases, a closed form approximation is obtained. It is found that each family considered has its own strengths and weaknesses. Some new families of generalized Poisson distributions are recommended. Theorems are obtained determining when these variance to mean ratios are less than (or exceed) one without having to find the mean and variance. Some numerical comparisons are also made.     

Asymptotic distribution of martingale estimators for a class of epidemic models

This article is a contribution to the asymptotic inference on the parameters of a quite general class of stochastic models for the spread of epidemics developing in closed populations. Various epidemic models are contained within our framework, for instance, a stochastic version of the Kermack and McKendrick model and the SIS epidemic model. Each model belonging to this class, which consists in a family of discrete-time stochastic process, contains certain parameters to be estimated by means of martingale estimators. Some particular cases defined by means of Markov chains are included in our setting. The main aim of this work is to prove consistency and asymptotic normality of these estimators. Some hypothesis tests based on the main results are also shown.     

A Comparative Study of Some Modified Chi-Squared Tests

Some recent results in the theory and applications of modified chi-squared goodness-of-fit tests are briefly discussed. It seems that for the first time power of modified chi-squared type tests for the logistic and three-parameter Weibull distributions based on moment type estimators is studied. Power of different modified tests against some alternatives for equiprobable fixed or random grouping intervals, and for Neyman–Pearson classes is investigated. It is shown that power of test statistic essentially depends on the quantity of Fisher's sample information this statistic uses. Some recommendations on implementing modified chi-squared type tests are given.