Assessment of Catastrophic Risk Using Bayesian Network Constructed from Domain Knowledge and Spatial Data

Prediction of natural disasters and their consequences is difficult due to the uncertainties and complexity of multiple related factors. This article explores the use of domain knowledge and spatial data to construct a Bayesian network (BN) that facilitates the integration of multiple factors and quantification of uncertainties within a consistent system for assessment of catastrophic risk. A BN is chosen due to its advantages such as merging multiple source data and domain knowledge in a consistent system, learning from the data set, inference with missing data, and support of decision making. A key advantage of our methodology is the combination of domain knowledge and learning from the data to construct a robust network. To improve the assessment, we employ spatial data analysis and data mining to extend the training data set, select risk factors, and fine‐tune the network. Another major advantage of our methodology is the integration of an optimal discretizer, informative feature selector, learners, search strategies for local topologies, and Bayesian model averaging. These techniques all contribute to a robust prediction of risk probability of natural disasters. In the flood disaster's study, our methodology achieved a better probability of detection of high risk, a better precision, and a better ROC area compared with other methods, using both cross‐validation and prediction of catastrophic risk based on historic data. Our results suggest that BN is a good alternative for risk assessment and as a decision tool in the management of catastrophic risk.     

Statistical techniques in stereology

Stereology typically concerns estimation of properties of a geometric structure from plane section information. This paperprovides a brief review of some statistical aspects of this rapidly developing field, with some reference to applications in the earth sciences. After an introductory discussion of the scope of stereology, section 2 briefly mentions results applicable when no assumptions can be made about the stochastic nature of the sampled matrix, statistical considerations then arising solelyfrom the ‘randomness’ of the plane section. The next two sections postulate embedded particles of specific shapes, the particular case of spheres being discussed in some detail.

References are made to results for ‘thin slices’ and other prob-ing mechanisms. Randomly located convex particles, of otherwise arbitrary shape, are discussed in section 5 and the review concludes with a specific application of stereological ideas to some data on neolithic mining.     

三螺旋混成组织视阈下的科学知识生产

多价知识观的提出改变了传统的强调科学知识生产过程特定要素或某个片段的视阈,内在地要求以集成性的观点来审视科学组织。在分析知识多价性与科学知识生产场域集成性关系的基础上,阐释了大学—产业—政府三螺旋混成组织是一种科学知识生产的集成性组织。它捕捉了科学知识生产过程中包含学术、市场和政策的多元重叠关系,使科学知识生产所需的资源、组织结构及运作过程都具有集成性特征。     

提高我国信息咨询业服务水平的对策研究

在全球信息咨询业迅猛发展的大背景下，通过对目前我国信息咨询业管理中存在问题的分析，探索提高我国信息咨询业服务水平的策略。     

从汉语传统中两种“文学”观念看第三次“重写文学史”的趋势

文学史的重写以一定的文学观念为基础,同时又要以古代中国的文献材料为研究对象。在方法上,必然要以观念来指导对材料的选择与解释。而通过考察汉语言传统中＂文学＂概念的流变发现,文学观念有一个由古代的经验总结模式向现代功能性移植模式的突变过程。如何弥合当代文学观念与传统文学实存之间的巨大差异,成为当下＂重写文学史＂要解决的首要问题。     

知识经济时代的新产业革命

在概括知识经济时代特征的基础上 ,重点分析了由知识经济引发的产业结构演变和发展的新趋向 ,指出知识的产业化和产业的知识化将是知识经济时代产业结构演变的主要特征。认为今后经济增长的主要推动力将来源于知识产业这一“主发动机” ,而经知识化改造的第一、二产业则将作为承重的“底盘”     

语文知识：是什么？怎么办？

在新课程改革和知识观变革的大背景下，再来讨论语文知识教学问题具有一定的理论和现实针对性。建构一个应用性的语文知识系统，这个系统既要关注到学生的语识学习，又要关注到学生的语感培养。在语文教学实践中，要立足于语文知识的建构性、默会性、情境性与整体性等特点进行语文知识教学。     

新理念与图书馆知识服务创新

基于愿景、执着、准确和务实理念,结合社会信息化的发展,提出图书馆知识服务应有明确愿景,应执着于追求公民普遍平等获取知识的自由,应明确图书馆在社会信息化中的角色定位,以使图书馆的信息资源配置符合社会发展需求。     

Emotion Knowledge, Social Competence, and Behavior Problems in Childhood and Adolescence: A Meta-analytic Review

The present meta-analytic review examined the magnitude of the relation between discrete emotion knowledge and three of its most commonly studied correlates in childhood and adolescence: social competence, internalizing problems, and externalizing problems. Emotion knowledge demonstrated small to medium-sized relations with each correlate. Moderators of effect size were also examined and included multiple sample and methodological characteristics. Using random effects models, significant moderators of effect size for relations between emotion knowledge and externalizing problems included sample recruitment, sample age, and the source of externalizing problems ratings. Moderators of effect size were not found for emotion knowledge and social competence, and the effect sizes across samples for emotion knowledge and internalizing problems were homogeneous. Results highlight the relatively consistent yet modest relations between emotion knowledge and its correlates. Implications for applied research and new directions for research on emotion knowledge using innovative methods are discussed.     

语用前提与大学英语阅读教学

本文把语用前提理论应用到大学英语阅读教学中,提出要加强学生在单词、词组、句子、语法等语言内知识的学习;要让学生学会利用已学的知识和上下文所提供的信息进行积极有效的推理;要向学生提供相关的外国文化背景知识,以扩充学生的知识范围。