An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

Evidential inference for diffusion-type processes

This article analyses diffusion-type processes from a new point-of-view. Consider two statistical hypotheses on a diffusion process. We do not use a classical test to reject or accept one hypothesis using the Neyman–Pearson procedure and do not involve Bayesian approach. As an alternative, we propose using a likelihood paradigm to characterizing the statistical evidence in support of these hypotheses. The method is based on evidential inference introduced and described by Royall [Royall R. Statistical evidence: a likelihood paradigm. London: Chapman and Hall; 1997]. In this paper, we extend the theory of Royall to the case when data are observations from a diffusion-type process instead of iid observations. The empirical distribution of likelihood ratio is used to formulate the probability of strong, misleading and weak evidences. Since the strength of evidence can be affected by the sampling characteristics, we present a simulation study that demonstrates these effects. Also we try to control misleading evidence and reduce them by adjusting these characteristics. As an illustration, we apply the method to the Microsoft stock prices.     

Moral conformity in online interactions: rational justifications increase influence of peer opinions on moral judgments

Over the last decade, social media has increasingly been used as a platform for political and moral discourse. We investigate whether conformity, specifically concerning moral attitudes, occurs in these virtual environments apart from face-to-face interactions. Participants took an online survey and saw either statistical information about the frequency of certain responses, as one might see on social media (Study 1), or arguments that defend the responses in either a rational or emotional way (Study 2). Our results show that social information shaped moral judgments, even in an impersonal digital setting. Furthermore, rational arguments were more effective at eliciting conformity than emotional arguments. We discuss the implications of these results for theories of moral judgment that prioritize emotional responses.     

学前儿童基于重量和声音进行因果推理的发展研究

儿童的推理能力历来都是考察儿童认知发展的重点。本研究探讨了在多种属性刺激下3~5岁儿童基于重量和声音进行 因果推理的表现。结果发现：4岁和5岁儿童选择正确目标物的准确率显著高于3岁儿童；和同时使用声音与重量判断目标物相 比，儿童在单独使用重量或声音的情况下更容易区分目标物。总之，儿童因果推理能力发展的关键期在4岁并且当任务难度较高 的情况下其因果机制极易受到干扰。     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.     

Predictors of Antisocial and Prosocial Behavior in an Adolescent Sports Context

This study examined antisocial and prosocial behavior of N = 439 adolescent athletes between 14 and 17 years of age (67 teams). Multi‐level analyses showed that team membership explained 20 and 13 percent of the variance in antisocial and prosocial behavior in the sports context, respectively. The team effects suggest that aggregating antisocial or prosocial adolescents within teams may partially explain differences in antisocial and prosocial behavior among athletes in the sports context. A trend was found toward a relation between higher levels of moral reasoning within teams, and less antisocial behavior in the sports context. Favorable moral atmosphere was positively associated with more prosocial behavior in the sports context. Finally, supportive coach–athlete relationships were associated with both less antisocial and more prosocial behavior in the sports context.     

关于留数定理的一个推广

研究了留数定理的有关问题,通过举例论证和归纳推理等证明方法,得到了单个留数定理的一个推广结论,最后将此结论应用于一些积分问题中.     

浅析法律论证

"法律论证"是通过提出某些论据或理由来证明法律决定正确性的活动,从而实现法律理性的目标。所以,首先必须了解法律论证的历史发展和研究现状,才能明确法律论证的外延范围,不然很容易引起混乱。接着分析传统法律推理的局限性,说明当今法律推理已经不再是形式逻辑在司法中的简单运用。最后提出法律论证理论,并对于认识论带来的"明希豪森困境",提出自己的解决方法。     

基于CBR技术的员工流失风险识别方法

员工流失风险识别是企业发现并准确识别各种员工流失风险因素的过程，是企业制定相应的员工流失风险管理措施的基础。基于员工流失风险识别的特征，讨论一种基于实例的推理技术在员工流失风险识别过程中的具体应用，重点研究风险识别实例的知识表示、组织管理及检索与匹配方法，为企业有效实施员工流失风险管理提供解决方案。