On the strengths of the self-updating process clustering algorithm

The self-updating process (SUP) is a clustering algorithm that stands from the viewpoint of data points and simulates the process how data points move and perform self-clustering. It is an iterative process on the sample space and allows for both time-varying and time-invariant operators. By simulations and comparisons, this paper shows that SUP is particularly competitive in clustering (i) data with noise, (ii) data with a large number of clusters, and (iii) unbalanced data. When noise is present in the data, SUP is able to isolate the noise data points while performing clustering simultaneously. The property of the local updating enables SUP to handle data with a large number of clusters and data of various structures. In this paper, we showed that the blurring mean-shift is a static SUP. Therefore, our discussions on the strengths of SUP also apply to the blurring mean-shift.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.     

Covariate Order Tests for Covariate Effect

A new approach for constructing tests for association between a random right censored life time variable and a covariate is proposed. The basic idea is to first arrange the observations in increasing order of the covariate and then base the test on a certain point process defined by the observation times. Tests constructed by this approach are robust against outliers in the covariate values or misspecification of the covariate scale since they only use the ordering of the covariate. Of particular interest is a test based on the Anderson-Darling statistic. This test has good power properties both against monotonic and nonmonotonic dependencies between the covariate and the life time variable.     

基于关联规则的中文姓名识别方法

从中文姓名识别技术是中文分词领域的重要分支的角度,分析了传统统计中文切词方法正确率低的缺失,表现为基于机器学习方法的中文姓名识别技术对词典规模和语料库容量依赖性大的缺陷,以至于不能够有效地发现未登录词,降低了中文姓名识别的正确率;以中文姓氏用字为线索,提出了一种改善的无监督的中文姓名识别方法,在统计法的基础上,利用关联规则算法挖掘出与姓氏相关的强规则进行姓名识别。实验结果表明：此方法对词典规模和语料库依赖性较小,能够自动消除歧义,有效地发现未登录词,提高了中文姓名识别的正确率。     

明代意象论研究

意象是中国古典文论所特有的一个文艺理论范畴,通常被用来评诗、论画。意象论的形成经历了漫长的发展过程,经先秦、唐宋之后,到明代才迎来了意象论的真正成熟。明代人在讨论意象时提出了明确的理论观点,认为意象要衡当、意象要含蓄、意象要虚构等。这些理论观点在清代得到了进一步的继承和发展。     

现代汉语致使构式论元实现的三种方式

现代汉语致使构式是一类比较特殊的形式一意义配对体,其多样化的句法表达形式一直是描写语言学派所探讨的重要课题之一。试用认知语言视角下的构式语法重新解读致使构式形式与语义之间的联接方式。通过对致使构式论元多寡的动态考察和分析得出结论：在句法、语义、语用的相互牵制和作用下,构式能够左右致使句的形成,对论元的实现具有强制性作用,致使构式论元实现的方式可以划分为论元一致、论元蕴涵和论元增容三种类型。     

校园文化与大学生隐性思想政治教育

校园文化是师生在特定环境中所创造的一种与社会、时代密切相关,具有校园特色的人文氛围、校园精神和生存环境,是思想政治教育的主隐性渠道。而良好的校风是校园文化中最重要的部分,它是师生员工在共同目标和共同认识的基础上,经过长期不懈的努力所形成的符合时代精神的思想、行为和作风,是学校独特的＂文化品质＂。良好的校风一旦形成,就会成为影响师生思想行为的一种客观环境,它是一种无形的教育力量,具有同化力、感染力,对学生能起到潜移默化的影响作用。     

海西战略背景下厦漳泉行业协会互动分析——基于战略协同的视角

在海峡西岸经济区建设中,素有"金三角"之称的厦漳泉有着举足轻重的地位。为促进厦漳泉三地产业密切合作,全面对接台湾新一轮产业的梯度转移,推进两岸经贸向纵深发展,加强三地的行业协会互动协作刻不容缓,并且大有作为。基于战略协同理论,分析海西战略背景下三地行业协会互动协作的可能性与必要性,并结合政府间关系理论分析现今三地行业协会互动的不足及成因,进而从营造良好的沟通环境、构建行业组织联盟、强化协会治理制度设计等方面提出促进三地行业协会有效互动的对策建议。     

高维热传导方程的高精度交替方向隐式方法

提出了数值求解二维和三维热传导方程的高精度交替方向隐式（ADI）方法，其空间为四阶精度、时间为二阶精度，并通过Neumann方法证明是无条件稳定的．该方法沿每个空间方向只涉及3个网格基架点，因此可以重复采用TDMA算法，大大节省了计算时间．数值实验验证了该方法的高阶精度，并与二阶的Peaceman—Rachford格式、Douglas格式及Crank—Nicolson格式进行了比较．     

试论汉语比喻的心理基础及文化观照

比喻是对感知过程中产生的某种联想进行描述的一种语言艺术手法,＂联想＂是比喻的心理基础。比喻的结构构成及其功能实现,都需建立在类比联想的基础之上。这种联想的产生会受到人们所生活的文化背景的影响,因此比喻也是一种文化现象。从广阔的文化背景中观察分析汉语中的比喻,能更好地了解其文化特征。