A Study of Risk Relevance Reasoning Based on a Context Ontology of Railway Accidents

With the application of risk management and accident response in the railway domain, risk detection and prevention have become key research topics. Many dangers and associated risk sources must be considered in collaborative scenarios of heavy-haul railways. In these scenarios, (1) various risk sources are involved in different data sources, and context affects their occurrence, (2) the relationships between contexts and risk sources in the accident cause mechanism need to be explicitly defined, and (3) risk knowledge reasoning needs to integrate knowledge from multiple data sources to achieve comprehensive results. To express the association rules among core concepts, this article constructs two ontologies: The accident-risk ontology and the context ontology. Concept analysis is based on railway domain knowledge and accident analysis reports. To sustainably integrate knowledge, an integrated evolutionary model called scenario-risk-accident chain ontology (SRAC) is constructed by introducing new data sources. The SRAC is integrated through expert rules between the two ontologies, and its evolution process involves new knowledge through a new risk source database. After three versions of the upgrade process, potential risk sources can be mined and evaluated in specific contexts. To evaluate the risk source level, a long short-term memory (LSTM) neural network model is used to capture context and risk text features. A model comparison for different neural network structures is performed to find the optimal evaluation results. Finally, new concepts, such as risk source level, and new instances are updated in the context-aware risk knowledge reasoning framework.     

网络技术对人类沟通方式的影响

网络技术的兴起对人类沟通方式产生了深刻影响,它所引发的信息媒体革命改变着我们的生活世界.作为一种新的传播媒介,网络技术的特质使沟通空间、沟通背景、沟通距离、沟通对象等发生了变化,同时也引发了若干社会问题,必须引起有关方面的充分注意.     

意象理论在汉英量词研究中的认知解读

汉英量词数量众多、用法灵活,体现出量词与名词搭配时所形成的纵聚合关系和横组合关系。文章通过汉英对比的研究方法,应用Langacker意象理论中的视角、认知域和突显等理论对汉英量词的纵聚合关系和横组合关系进行认知解读,发现其共性在于汉英民族使用量词时经常存在对相关事物对象进行突显,选择不同的认知域和进行视角转换所致。     

从认知的角度探讨名词的翻译

从认知语言学的基本概念入手，通过对物质名词和概念名词的探讨，利用例证阐述了在名词翻译过程中如何运用认知语言学的知识来帮助译者更好地理解其意义。     

Symbolic cumulant calculations for frequency domain time series

With time series data, there is often the issue of finding accurate approximations for the variance of such quantities as the sample autocovariance function or spectral estimate. Smith and Field (J. Time. Ser. Anal 14: 381–395, 1993) proposed a variance estimate motivated by resampling in the frequency domain. In this paper we present some results on the cumulants of this and other frequency domain estimates obtained via symbolic computation. The statistics of interest are linear combinations of products of discrete Fourier transforms. We describe an operator which calculates the joint cumulants of such statistics, and use the operator to deepen our understanding of the behaviour of the resampling based variance estimate. The operator acts as a filter for a general purpose operator described in Andrews and Stafford (J.R. Statist. Soc. B55, 613–627).     

Genetic Algorithm in the Wavelet Domain for Large p Small n Regression

Many areas of statistical modeling are plagued by the “curse of dimensionality,” in which there are more variables than observations. This is especially true when developing functional regression models where the independent dataset is some type of spectral decomposition, such as data from near-infrared spectroscopy. While we could develop a very complex model by simply taking enough samples (such that n > p), this could prove impossible or prohibitively expensive. In addition, a regression model developed like this could turn out to be highly inefficient, as spectral data usually exhibit high multicollinearity. In this article, we propose a two-part algorithm for selecting an effective and efficient functional regression model. Our algorithm begins by evaluating a subset of discrete wavelet transformations, allowing for variation in both wavelet and filter number. Next, we perform an intermediate processing step to remove variables with low correlation to the response data. Finally, we use the genetic algorithm to perform a stochastic search through the subset regression model space, driven by an information-theoretic objective function. We allow our algorithm to develop the regression model for each response variable independently, so as to optimally model each variable. We demonstrate our method on the familiar biscuit dough dataset, which has been used in a similar context by several researchers. Our results demonstrate both the flexibility and the power of our algorithm. For each response variable, a different subset model is selected, and different wavelet transformations are used. The models developed by our algorithm show an improvement, as measured by lower mean error, over results in the published literature.     

情绪隐喻的取象与文化认知

在文化语言学和认知语言学的框架下,情绪隐喻生成于身体本能反应、空间概念映射、物性特征迁移、社会文化四条途径.身体本能禀赋先天遗传特征.是情绪隐喻的第一来源.空间概念投射于情绪域源于人类的空间思维定势.物性迁移隐喻取象自事物与心灵之间相似性的隐性概念结构.另外,不同的文化形态衍生不同的情绪概念.     

领域知识促进创造性问题解决——专家与新手的比较

研究采用错误记忆范式和远距离联想范式，探讨了领域知识对创造性问题解决的影响。结果发现，专家比新手产生更多的错误记忆，具有更好地解决创造性问题的能力。这一结果表明，专家在领域内比新手具有更广泛的概念扩散激活，能更好地解决创造性问题，说明领域知识在创造性思维过程中所发挥的独特作用。     

巴泽尔的产权理论评介

巴泽尔的产权理论观点新颖、方法独特，丰富了已有的产权理论和新制度经济学。他在产权界定方式、界定费用的影响、个人在产权界定中的作用以及产权合理配置原则等多方面提出了与众不同的见解。从辩证逻辑的角度揭示了产权界定的相对性和渐进性。指出由于存在交易费用，产权实际上常常不可能界定清晰，未加界定的财产价值就被留在公共领域；产权边界是个人努力、他人争夺和政府维护的函数，个人在产权界定中比政府有优势。他还从共同财产问题和延留义务的角度揭示了企业的性质。     

Small domain estimation by empirical bayes and kalman filtering procedures - a case study

An application of empirical Bayes and Kalman filtering tecniques is reported, using live data from Indian Statistical Institute (ISI), Calcutta . to illustrate how initial small domain estimators may be vastly improved upon. A stratified two stage sampling procedure is adopted, allowing selection of first stage units with unequal probabilities but of second stage units with equal probabilities. Standard design-based estimators for domain totals are initialized based on domain specific survey data alone. Strength is then borrowed across domains and from past surveys. The resulting gains in efficacy are numlerically demonstrated, through replicated sampling from official records.