论洪亮吉骈文的艺术特色

洪亮吉是乾嘉时期极具声望的骈文作家。他一生学问广博，识见超卓，其骈文既继承了六朝骈文优秀的抒情风格，又自成一家，有力地证明了清代骈文卓然自立、繁荣复兴的文化地位。古朴淡雅是其骈文的总特点。以学济文，气质渊雅；用典自然，高古为尚；韵律和谐，铿锵悦耳；情感真挚，凄恻委婉是其骈文的独到之处。     

中央文献排比修辞的俄译策略研究——以十九大报告及其俄译本为例

中央文献排比修辞的频繁使用起到了增强语势、突出重点、使句式结构条理清晰的作用。本文以十九大报告及其俄译本为例,尝试基于译文与俄罗斯媒体中新闻报道的对比结果对排比修辞的俄译策略进行统计分析,提出“提取公因式,合并同类项”“舍弃复现结构,按照原文原意分别译出”“保留复现结构,遵照原文形式依次译出”“改变复现结构,转换复现词词性”以及解释性翻译等五种符合目的语表达习惯的俄译策略,以期对中央文献俄译研究以及中国对外话语体系的建设提供参考与借鉴。     

突发事件应急管理中的情景适应度研究

在突发事件的处置过程中,每个阶段对情景的确定决定了突发事件应急管理的工作方式和决策制定的指向性,从而影响整体应急管理工作的总体决策判断。本文主要针对突发事件应急情景选取问题,由粗到细的采用具有语义接近范围的情景适应度方式和情景属性云匹配方式进行情景确定问题的收敛,从而能够相对精确的确定应急处置过程中的情景,为系统决策提供支持。     

云计算在高校校园网资源管理中的应用

校园网以云计算为核心架构，可以实现基础设施与实际应用的分离，解决校园网面临的资源共享、设备更新、管理统一等问题，促进教师的教学和科研工作，丰富学生的学习和生活，并为资源的存储和安全提供的保障。     

Stochastic comparisons between extreme order statistics from scale models

Stochastic ordering relations between extreme order statistics from exponential, Weibull and gamma distributions have been studied extensively by many researchers in recent years. In this work, we obtain various ordering results for the comparisons of two extreme order statistics from scale models when one set of scale parameters majorizes the other. The new results obtained here are applied when the baseline distributions are exponentiated Weibull or generalized gamma distributions. In this way, we generalize and extend some results established recently in the literature.     

Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics

This paper concerns the geometric treatment of graphical models using Bayes linear methods. We introduce Bayes linear separation as a second order generalised conditional independence relation, and Bayes linear graphical models are constructed using this property. A system of interpretive and diagnostic shadings are given, which summarise the analysis over the associated moral graph. Principles of local computation are outlined for the graphical models, and an algorithm for implementing such computation over the junction tree is described. The approach is illustrated with two examples. The first concerns sales forecasting using a multivariate dynamic linear model. The second concerns inference for the error variance matrices of the model for sales, and illustrates the generality of our geometric approach by treating the matrices directly as random objects. The examples are implemented using a freely available set of object-oriented programming tools for Bayes linear local computation and graphical diagnostic display.     

Arranging sensations: smell and taste in augmented and virtual reality

The development of digital taste and smell underscores the importance of cultural dimensions of bodily perception in augmented reality (AR) and virtual reality (VR) devices. This can be seen in Vocktail and Season Traveller, two digital devices incorporating taste and smell. Vocktail is an AR technology that augments the experience of drinking water, or even air, through the electrical stimulation of tastebuds and the manipulation of color and smell. Season Traveller is a VR game in which the user moves through four seasonal landscapes. It uses wind, odor, and temperature in addition to the more standard audio-visual displays. The cultural dimensions of these devices can be examined using phenomenological terms. They instigate perceptual circuits, and call on and create sedimented habits. Although VR and AR are often thought of in terms of their similitude to reality, understanding Vocktail and Season Traveller this way illustrates the world-creating dimension of multisensory devices. These technologies structure and shift thresholds of taste and smell, reworking past perceptual styles and habits to develop new perceptual experiences. In so doing, Season Traveller and Vocktail throw to the fore questions about the conditions according to which people exercise their senses in digitally dominated environments.     

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

Summary.  Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox processes and geostatistical and geoadditive models. We consider approximate Bayesian inference in a popular subset of structured additive regression models, latent Gaussian models , where the latent field is Gaussian, controlled by a few hyperparameters and with non-Gaussian response variables. The posterior marginals are not available in closed form owing to the non-Gaussian response variables. For such models, Markov chain Monte Carlo methods can be implemented, but they are not without problems, in terms of both convergence and computational time. In some practical applications, the extent of these problems is such that Markov chain Monte Carlo sampling is simply not an appropriate tool for routine analysis. We show that, by using an integrated nested Laplace approximation and its simplified version, we can directly compute very accurate approximations to the posterior marginals. The main benefit of these approximations is computational: where Markov chain Monte Carlo algorithms need hours or days to run, our approximations provide more precise estimates in seconds or minutes. Another advantage with our approach is its generality, which makes it possible to perform Bayesian analysis in an automatic, streamlined way, and to compute model comparison criteria and various predictive measures so that models can be compared and the model under study can be challenged.     

基于C／S和B／S混合模式的多媒体电子阅览室管理系统设计

高职院校多媒体电子阅览室是用户获取信息和学习的重要场所,如何能进一步完善和发展它需要有效的管理系统和具有更高素质的管理队伍。从网络化、一体化、多元化的理念出发,采用三层C/S和B/S两种混合模式,在用户管理,资源管理,安全管理三个方面展开论述,为现代多媒体电子阅览室提出了方便实用、安全有效的管理系统设计方案,以供大家探讨。