武林秘籍:武侠小说"情节模式"论之一

“武林秘籍”在武侠小说中频频出现,皆受瞩目,是武侠小说常见模式之一。“武林秘籍”模式导因于“武”,从“武林盟主”、“武林至尊”的区别中,可以发现在武侠小说中,武功是最关键的因素。“武林秘籍”的设计具有高超性、隐秘性、神异性、灵妙性、正宗性、道德性的特点,对小说的情节设计及推展具有枢纽作用。     

赛珍珠短篇小说写作特色分析——以作者的双重文化背景为出发点

赛珍珠作为首位获得诺贝尔文学奖的美籍女作家,虽然遭受到不少的批评,却也获得世人称赞。在她的众多短篇小说里,精湛的情节设置、巧妙的称谓、生动的词汇表述都使其小说可读性更强、文化意义更深远。通过对其短篇小说写作特色的分析读者不仅发现赛珍珠把中国真实客观地介绍给西方读者,而且体会到拥有中西双重文化背景的赛珍珠对中国人的热爱和同情。     

刘国芳小小说叙述技法摭谈

刘国芳是当代有影响的小小说代表作家之一。他较早形成了自己的创作风格。在叙述技法上 ,刘国芳的特色鲜明地体现在细节凸现、情节链重复和意象象征等几个方面     

《三国志》裴注的复调意义

陈寿《三国志》因其简略基本上只提供了历史大事的纲要,裴松之的注补引录诸书呈现出历史情景曾经的复杂与生动。以陈寿志为主,以裴松之以及二百多种著作为宾,在宾主对话中,陈寿志正史的权威性被颠覆、被解构了,而历史本真的头绪纷繁、意向杂乱以及主题阐释的多元性则被复活了。裴松之注补《三国志》主要不是历史学家的态度,而是文化学者或文学家的态度。惟其如此,裴注在文学史与史学史上具有重要地位。裴注的开放性思维对后来说话、戏曲等伎艺以及历史小说的发生发展功莫大焉。从《三国志》到《三国演义》,从"故事"转换成"情节",裴注的意义更是不容忽视。     

王安忆长篇小说《上种红菱下种藕》的叙述视角

本文用叙事学的理论,评论王安忆的小说<上种红菱下种藕>.认为这篇小说采用了照像式的叙述视角,客观真实.淡化情节,注意表现原生态的生活,并体现了现实性与诗性的结合.     

佳色功名两不朽 诗人意兴托风情——《游仙窟》的文学特质与美学价值

通过对唐传奇中的名篇《游仙窟》的分析 ,可以发现 ,唐传奇主要表现了一种普遍的“青楼意识” ,它具有独具的文化特质、美学价值。其情节进程的展开、整体的结构形式都具有独特的意义。思想的表达及写作的独特性更使其具有现代西方小说的显著特征。诗散皆备形式等更对后世文学产生了颇大的影响。     

Illustration of Sampling-Based Methods for Uncertainty and Sensitivity Analysis

A sequence of linear, monotonic, and nonmonotonic test problems is used to illustrate sampling-based uncertainty and sensitivity analysis procedures. Uncertainty results obtained with replicated random and Latin hypercube samples are compared, with the Latin hypercube samples tending to produce more stable results than the random samples. Sensitivity results obtained with the following procedures and/or measures are illustrated and compared: correlation coefficients (CCs), rank correlation coefficients (RCCs), common means (CMNs), common locations (CLs), common medians (CMDs), statistical independence (SI), standardized regression coefficients (SRCs), partial correlation coefficients (PCCs), standardized rank regression coefficients (SRRCs), partial rank correlation coefficients (PRCCs), stepwise regression analysis with raw and rank-transformed data, and examination of scatter plots. The effectiveness of a given procedure and/or measure depends on the characteristics of the individual test problems, with (1) linear measures (i.e., CCs, PCCs, SRCs) performing well on the linear test problems, (2) measures based on rank transforms (i.e., RCCs, PRCCs, SRRCs) performing well on the monotonic test problems, and (3) measures predicated on searches for nonrandom patterns (i.e., CMNs, CLs, CMDs, SI) performing well on the nonmonotonic test problems.     

Elliptical safety region plots for C pk

The process capability index C _pk is widely used when measuring the capability of a manufacturing process. A process is defined to be capable if the capability index exceeds a stated threshold value, e.g. C _pk >4/3. This inequality can be expressed graphically using a process capability plot, which is a plot in the plane defined by the process mean and the process standard deviation, showing the region for a capable process. In the process capability plot, a safety region can be plotted to obtain a simple graphical decision rule to assess process capability at a given significance level. We consider safety regions to be used for the index C _pk . Under the assumption of normality, we derive elliptical safety regions so that, using a random sample, conclusions about the process capability can be drawn at a given significance level. This simple graphical tool is helpful when trying to understand whether it is the variability, the deviation from target, or both that need to be reduced to improve the capability. Furthermore, using safety regions, several characteristics with different specification limits and different sample sizes can be monitored in the same plot. The proposed graphical decision rule is also investigated with respect to power.     

Outlier detection based on extreme value theory and applications

Whether an extreme observation is an outlier or not depends strongly on the corresponding tail behavior of the underlying distribution. We develop an automatic, data-driven method rooted in the mathematical theory of extremes to identify observations that deviate from the intermediate and central characteristics. The proposed algorithm is an extension of a method previously proposed in the literature for the specific case of heavy tailed Pareto-type distributions to all max-domains of attraction. We propose some applications such as a tail-adjusted boxplot which yields a more accurate representation of possible outliers, and the identification of outliers in a multivariate context through an analysis of associated random variables such as local outlier factors. Several examples and simulation results illustrate the finite sample behavior of the algorithm and its applications.     

Exponentiated generalized Pareto distribution: Properties and applications towards extreme value theory

The GPD is a central distribution in modelling heavy tails in many applications. Applying the GPD to actual datasets however is not trivial. In this paper we propose the Exponentiated GPD (exGPD), created via log-transform of the GPD variable, which has less sample variability. Various distributional quantities of the exGPD are derived analytically. As an application we also propose a new plot based on the exGPD as an alternative to the Hill plot to identify the tail index of heavy tailed datasets, and carry out simulation studies to compare the two.