东北三省外语院校英语专业复合型人才培养研究

复合型外语人才培养模式以专业为基础,使外语作为技能、工具与专业相结合,提高学生的英语应用能力和文化素养,这类复合型人才具有广泛的社会适应性,并将带来巨大的人才效应。基于对当今世界上学科融合发展趋势的认识和对就业市场调查的结果,提出东北三省英语专业复合型人才培养目标,探讨研究适应东北三省复合型英语专业人才培养的问题和复合型英语专业人才培养的定位,包括对传统领域的基础英语的语言教学和其他专业学科融合的教学之间的关系问题的研究。     

Bayesian robustness of the compound Poisson distribution under bidimensional prior: an application to the collective risk model

The distribution of the aggregate claims in one year plays an important role in Actuarial Statistics for computing, for example, insurance premiums when both the number and size of the claims must be implemented into the model. When the number of claims follows a Poisson distribution the aggregated distribution is called the compound Poisson distribution. In this article we assume that the claim size follows an exponential distribution and later we make an extensive study of this model by assuming a bidimensional prior distribution for the parameters of the Poisson and exponential distribution with marginal gamma. This study carries us to obtain expressions for net premiums, marginal and posterior distributions in terms of some well-known special functions used in statistics. Later, a Bayesian robustness study of this model is made. Bayesian robustness on bidimensional models was deeply treated in the 1990s, producing numerous results, but few applications dealing with this problem can be found in the literature.     

Tests for compound periodicities and estimating a non linear function

We propose two tests for testing compound periodicities which are the uniformly most powerful invariant decision procedures against simple periodicities. The second test can provide an excellent estimation of a compound periodic non linear function from observed data. These tests were compared with the tests proposed by Fisher and Siegel by Monte Carlo studies and we found that all the tests showed high power and high probability of a correct decision when all the amplitudes of underlying periods were the same. However, if there are at least several different periods with unequal amplitudes, then the second test proposed always showed high power and high probability of a correct decision, whereas the tests proposed by Fisher and Siegel gave 0 for the power and 0 for the probability of a correct decision, whatever the standard deviation of pseudo normal random numbers. Overall, the second test proposed is the best of all in view of the probability of a correct decision and power.     

复合期权在R＆D项目投资评价中的应用

如何评价R&D项目投资已成为目前理论界关注的一个热点。对R&D项目投资的基本评价方法———贴现现金流法 (DCF)已越来越不能适应R&D项目管理的复杂性和不确定性 ,而实物期权方法以其能够灵活评价不确定性条件下的投资项目未来的增长机会的特点 ,受到越来越多的关注。借鉴了Geske提出的复合期权模型 ,将R&D项目看作一个复合期权 ,建立了R&D项目的投资评价模型     

从吐鲁番出土文献看高昌王国

本文用吐鲁番出土的大量高昌国文献,对正史中诸《高昌传》所记“兼用胡书”、“皆为胡语”、“俗事天神,兼信佛法”等作了分析和校正。指出这些记载不符合高昌王国实际,认为无论是语言文字、生活习俗,还是文化传承及宗教信仰,高昌王国都与中原内地具有一体性,她并非化外的异域,而是华夏之邦,是历史上中国的一部分。     

日语复合动词中的甚词研究

日语复合动词里的部分后项动词以及部分前项动词在构词过程中产生了语法化变化,失去了该词汇所具有的本来意义。其语法作用相当于汉语中表示极端程度的甚词表达,主要用来表示程度或者强调等意义。但是,日语甚词表达和汉语甚词表达之间在所用词汇上没有交集。所以,不能使用汉语甚词表达去套用日语的甚词表达。     

对传统解释方法的批判与反思

本文揭示了汉代所开创的那个解释传统的完全错误的性质及其完全错误的逻辑发展 ,指出作为这个解释传统之理论基础的假借之学和考据之学本质上是一种逃亡之学 ,它不仅逃离了作为它的解释对象的先秦本文的内在思想逻辑 ,而且也逃离了先秦本文的语言文字本身 ,从而使之成为与本文完全无关的东西     

关于学生创新意识和能力培养的辩证思考

"三个代表"是一个创新的理论体系,体现出共产党人"与时俱进"的优秀品质.学习贯彻"三个代表"重在实践.作为思想政治教育工作者,要提高研究生的思想道德素质,首先要不断加强研究生的理论学习,提高研究生的理论创新水平;其次,要积极引导研究生参加社会实践活动,不断提高研究生的道德情操;再次,要加强研究生党支部建设,提高研究生整体队伍的质量.     

云南少数民族古籍修复研究

云南少数民族古籍资源丰富,各民族在历史长河中所形成的古籍具有鲜明特点,是我国古籍资源中的奇葩。由于自然和非自然的原因,许多民族古籍在流传过程中遭到损坏。因此,对这些古籍的修复是十分必要的。传统修复技术是在对汉文古籍的修复过程中总结的,但却不能完全应用于少数民族古籍的修复。     

The predictive distributions of thinning‐based count processes

This paper shows that the term structure of conditional (i.e. predictive) distributions allows for closed form expression in a large family of (possibly higher order or infinite order) thinning‐based count processes such as INAR(p), INARCH(p), NBAR(p), and INGARCH(1,1). Such predictive distributions are currently often deemed intractable by the literature and existing approximation methods are usually time consuming and induce approximation errors. In this paper, we propose a Taylor's expansion algorithm for these predictive distributions, which is both exact and fast. Through extensive simulation exercises, we demonstrate its advantages with respect to existing methods in terms of the computational gain and/or precision.