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。     

基于案例推理的压力容器故障维修方法

针对目前压力容器故障维修依赖经验知识的程度高,智能知识库利用率低的问题,提出基于案例推理的压力容 器故障维修方法。通过定义对应故障特征关键词字典,优化案例库案例存储与索引机制,对故障案例信息进行结构化和 知识化;并采用结合最近相邻法和灰色关联度算法的案例相似度匹配方法,提高案例匹配精度。经应用实例验证,从案 例库中匹配相似案例速度快、可靠度高,可供原故障案例参考。因此,该方法在实际使用中有效降低了经验知识的依赖 程度,较好地利用智能知识库,为压力容器全生命周期的维护、修理和操作( MRO)提供便利。     

隐性知识在产品概念设计中的应用

工业设计领域中,提高产品的设计质量是利益最大化的首要途径,而产品概念设计直接决定产品设计质量,而隐 性知识为产品概念创新设计提供了新的思路,因此,提出一种关于隐性知识应用于产品概念设计中的方法。在理解隐性 知识概念的前提下,从产品出发,挖掘隐藏在产品中的隐性知识,将这些隐性知识显性化,用人们容易理解、接受的知识 进行表达,便于被重新利用。通过收集大量的产品隐性知识,建立产品隐性知识库,借助案例推理( case-based reasoning, CBR)技术,运用相似度计算法,获取知识库中与目标设计要求相似度最大的案例,将其作为目标设计或作参考,直接运 用于新产品的开发中。结果表明,该方法不仅能缩短产品设计周期,而且能大大提高产品的质量。本研究为企业迅速抢 占市场,赢得市场份额具有一定意义。     

Outlier detection in contingency tables using decomposable graphical models

For high-dimensional data, it is a tedious task to determine anomalies such as outliers. We present a novel outlier detection method for high-dimensional contingency tables. We use the class of decomposable graphical models to model the relationship among the variables of interest, which can be depicted by an undirected graph called the interaction graph. Given an interaction graph, we derive a closed-form expression of the likelihood ratio test (LRT) statistic and an exact distribution for efficient simulation of the test statistic. An observation is declared an outlier if it deviates significantly from the approximated distribution of the test statistic under the null hypothesis. We demonstrate the use of the LRT outlier detection framework on genetic data modeled by Chow–Liu trees.     

Testing the proportional odds assumption in multiply imputed ordinal longitudinal data

A popular choice when analyzing ordinal data is to consider the cumulative proportional odds model to relate the marginal probabilities of the ordinal outcome to a set of covariates. However, application of this model relies on the condition of identical cumulative odds ratios across the cut-offs of the ordinal outcome; the well-known proportional odds assumption. This paper focuses on the assessment of this assumption while accounting for repeated and missing data. In this respect, we develop a statistical method built on multiple imputation (MI) based on generalized estimating equations that allows to test the proportionality assumption under the missing at random setting. The performance of the proposed method is evaluated for two MI algorithms for incomplete longitudinal ordinal data. The impact of both MI methods is compared with respect to the type I error rate and the power for situations covering various numbers of categories of the ordinal outcome, sample sizes, rates of missingness, well-balanced and skewed data. The comparison of both MI methods with the complete-case analysis is also provided. We illustrate the use of the proposed methods on a quality of life data from a cancer clinical trial.     

Probabilities as Similarity‐Weighted Frequencies

A decision maker is asked to express her beliefs by assigning probabilities to certain possible states. We focus on the relationship between her database and her beliefs. We show that if beliefs given a union of two databases are a convex combination of beliefs given each of the databases, the belief formation process follows a simple formula: beliefs are a similarity‐weighted average of the beliefs induced by each past case.     

基于案例推理技术的企业可持续竞争能力的模型建立与应用

企业保持自身竞争能力的可持续性是企业成功的重要因素,但目前对于如何针对和结合企业自身的可持续竞争能力,以有效的制定未来的企业战略,学术界仍然研究甚少。本文的写作目的,是试图借助人工智能中的案例推理技术,建立企业的可持续竞争能力模型,为企业未来的发展方向和经营决策,提供有参考价值的指导性意见。     

An Evidential Reasoning‐Based CREAM to Human Reliability Analysis in Maritime Accident Process

This article proposes a modified cognitive reliability and error analysis method (CREAM) for estimating the human error probability in the maritime accident process on the basis of an evidential reasoning approach. This modified CREAM is developed to precisely quantify the linguistic variables of the common performance conditions and to overcome the problem of ignoring the uncertainty caused by incomplete information in the existing CREAM models. Moreover, this article views maritime accident development from the sequential perspective, where a scenario‐ and barrier‐based framework is proposed to describe the maritime accident process. This evidential reasoning‐based CREAM approach together with the proposed accident development framework are applied to human reliability analysis of a ship capsizing accident. It will facilitate subjective human reliability analysis in different engineering systems where uncertainty exists in practice.     

Management’s causal reasoning on performance and earnings management

We investigate the association between the intensity of causal reasoning on performance in a firm’s annual management commentary and its earnings management propensity. Anticipated earnings management concerns are argued to constitute a significant accountability predicament, bringing management to offer more intense causal reasoning in order to mitigate investors’ earnings management concerns. We use computer-intensive techniques to measure causal reasoning intensity as a generic disclosure quality in the management commentary of a large sample of US firms from 1999 to 2007. We find that accruals earnings management (signed discretionary accruals) is positively associated with causal reasoning intensity. The positive association holds for alternative specifications of accruals earnings management (an earnings management dummy model and an analyst expectations model) and in a change model. Our results are consistent with the assertion that firms strategically use causal reasoning on performance to establish appropriateness and cognitive legitimacy, increase perceived plausibility of reported performance and mitigate performance-related concerns of investors.     

基于人工免疫的企业流程案例库三级索引框架

根据流程案例的特点,从行业、业务和流程信息化程度3个方面构建三级索引框架,从而能够有效地对流程案例进行分类存储、快速检索与匹配。三级索引机制的核心是基于企业流程信息化程度的第三级索引构建,利用基于人工免疫的aiNet聚类方法的噪声忍耐、自组织、记忆性以及能够有效避免局部最优等方面的特点,对流程案例进行第三级分类,将人工免疫的抗体作为聚类中心,形成流程案例的第三级索引。最后利用105个样本对该三级索引机制的构建过程进行了实证。