从悖论诗学的视角考察杜甫诗歌艺术的意象组合

今年是＂诗圣＂杜甫诞辰1300年,＂杜诗学＂研究领域理应努力通过当代中西学术的汇通和中西诗学理论的契合,以新的研究视角深入审视杜诗艺术的特质,不应视之为玄妙的＂奇变＂或＂天机＂。运用当前国内外文学批评界悖论诗学理论来考察,杜诗艺术在句法意象组合方面具有典型的诗学悖论特质,亦即前贤诗评家所谓的＂新变＂或＂格变＂。当代＂杜诗学＂的构建理应展开悖论诗学的新视阈,多层次地深入阐释杜诗艺术的奥秘与魅力,使之真正成为一门国际化的学问,以有利于在世界文化全球化的浪潮中增强中国传统文化软实力。     

动画片叙事节奏处理——镜头的运用研究

节奏如同我们呼吸的空气一样存在着生活与艺术当中,研究所涉及的节奏主要是动画影片叙事的节奏,阐述了通过构成镜头的画面设计、构图形式、色彩、光影等要素的运用原理、运动镜头、静止镜头的比例分配等因素对叙事节奏所产生的影响,探讨了如何基于镜头来把握叙事节奏提升作品整体魅力,让观众更好地感受视听艺术的美感,达到创作出优秀的、经久不衰的动画作品.     

Throughput and delay analysis of an opportunistic tree algorithm

Tree algorithms are a well-known class of random access algorithms with a provable maximum stable throughput under the infinite population model (as opposed to ALOHA or the binary exponential backoff algorithm). In this article, we propose a tree algorithm for opportunistic spectrum usage in cognitive radio networks. A channel in such a network is shared among so-called primary and secondary users, where the secondary users are allowed to use the channel only if there is no primary user activity. The tree algorithm designed in this article can be used by the secondary users to share the channel capacity left by the primary users.

We analyze the maximum stable throughput and mean packet delay of the secondary users by developing a tree structured Quasi-Birth Death Markov chain under the assumption that the primary user activity can be modeled by means of a finite state Markov chain and that packets lengths follow a discrete phase-type distribution.

Numerical experiments provide insight on the effect of various system parameters and indicate that the proposed algorithm is able to make good use of the bandwidth left by the primary users.     

The Media Abuse of Children. Jake's Progress from Demonic Icon to Restored Childhood Innocent

While scholarly analysis of child protection and the media has grown substantially during the 1990s (Aldridge, 1994; Franklin and Parton, 1991; Kitzinger and Skidmore, 1995), studies have ignored a crucial dimension which forms the focus for discussion here. We wish to suggest that media reporting of children and child abuse may itself constitute an abusive activity. Media presentations of children and childhood, since press coverage of the Bulger case in 1993, have assumed a distinctive and sinister guise which, we argue, fundamentally revises the previously held perception of children and childhood. We suggest that this new understanding of childhood is damaging to children and, because of the impact of such media presentations on the public mood and policy climate, harms their interests. The discussion is in three parts. First, newspaper reporting of the Bulger case is analysed to reveal how coverage challenged the idea of childhood as a period of innocence and replaced it with a perception of childhood as essentially ‘evil’. Second, the characterization of Jake, the central figure in Alan Bleasdale's recent television dramaJake's Progress, is analysed to serve as an illustrative exemplar of this new construction of childhood. Finally, we consider the possible messages conveyed by such presentations to perpetrators and victims of abuse.     

A reflected feature space for CART

We present an algorithm for learning oblique decision trees, called HHCART(G). Our decision tree combines learning concepts from two classification trees, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that uses linear structure in the training examples, captured by a modified GDT angle bisector, to define splitting directions. At each node, we reflect the training examples with respect to the modified angle bisector to align this linear structure with the coordinate axes. Searching axis parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. Our method is much simpler than HHCART because it only considers one reflected feature space for node splitting. HHCART considers multiple reflected feature spaces for node splitting making it more computationally intensive to build. Experimental results show that HHCART(G) is an effective classifier, producing compact trees with similar or better results than several other decision trees, including GDT and HHCART trees.     

Finding a Noncrossing Steiner Forest in Plane Graphs Under a 2-Face Condition

Let G = (V,E) be a plane graph with nonnegative edge weights, and let be a family of k vertex sets , called nets. Then a noncrossing Steiner forest for in G is a set of k trees in G such that each tree connects all vertices, called terminals, in net N _i, any two trees in do not cross each other, and the sum of edge weights of all trees is minimum. In this paper we give an algorithm to find a noncrossing Steiner forest in a plane graph G for the case where all terminals in nets lie on any two of the face boundaries of G. The algorithm takes time if G has n vertices and each net contains a bounded number of terminals.     

Risk of Extreme Events in Multiobjective Decision Trees Part 1. Severe Events

Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well-known method of averaging out and folding back. This first of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming the exceedance of a threshold β, where β is preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based on the insight that the conditional expected value is separable into two constituent elements of risk and can thus be optimized along with other objectives, including the unconditional expected value of the outcome, by using a multiobjective decision tree. An example of sequential decision making for improving highway capacity is given.     

Lognormal Approximations of Fault Tree Uncertainty Distributions

Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed‐form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling‐based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed‐form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks’s method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models.