翻译理论新标准与语言学理论

语言学的发展一直在不断地影响着翻译理论的发展,只不过有时这种影响很间接,尼达的译学思想在中国翻译界一向占据着重要的地位,但这位大师最近宣布其观点已经发生根本变化,尼达学术观点的变化无疑会给目前译学建设带来一定的负面影响。本文着重从翻译理论的作用、翻译标准及语言学与翻译的关系三个角度对尼达翻译思想的转变加以分析;重新阐述理论在译学框架中的地位及作用,理论和实践的关系及翻译理论的意义。     

对彩电行业拓展农村市场的思考

通过对中国彩电业现状的阐述,重点分析了农村彩电市场的需求现状特点及发展趋势,从产品、价格、广告、营销渠道和经营模式方面分析了彩电企业进入农村市场的策略。     

同异反统计方法的应用及优势

介绍了一种新的统计方法———同异反统计 ,例举了这种统计方法的应用 ,并与传统数理统计方法相比较 ,肯定这种新统计方法的优越性     

杂合灰色聚类与变精度粗糙模糊集的概率决策方法及应用

在基于粗糙集理论或扩展粗糙集理论的不确定性决策中,仅由数据集无法获得决策表,同时由于决策属性呈现模糊性,以致于难以获取概率决策规则。针对这一类决策问题,基于灰色定权聚类与优势粗糙集变精度方法,本文构建了一种的杂合决策方法。该方法首先利用中心点三角白化权函数的灰色定权聚类方法将包含不同量纲指标的知识表示系统生成多属性决策表,而后运用变精度粗糙模糊集进行决策分析,生成概率决策规则,最后以区域关键技术的选择为例,表明该模型的可行性与实用性。     

Inference Based on Conditional Moment Inequalities

In this paper, we propose an instrumental variable approach to constructing confidence sets (CS's) for the true parameter in models defined by conditional moment inequalities/equalities. We show that by properly choosing instrument functions, one can transform conditional moment inequalities/equalities into unconditional ones without losing identification power. Based on the unconditional moment inequalities/equalities, we construct CS's by inverting Cramér–von Mises‐type or Kolmogorov–Smirnov‐type tests. Critical values are obtained using generalized moment selection (GMS) procedures. We show that the proposed CS's have correct uniform asymptotic coverage probabilities. New methods are required to establish these results because an infinite‐dimensional nuisance parameter affects the asymptotic distributions. We show that the tests considered are consistent against all fixed alternatives and typically have power against n^−1/2‐local alternatives to some, but not all, sequences of distributions in the null hypothesis. Monte Carlo simulations for five different models show that the methods perform well in finite samples.     

A New Multicriteria Risk Mapping Approach Based on a Multiattribute Frontier Concept

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that typically require prior knowledge of the risk components’ importance. Such information is often nonexistent for many invasive pests. This study proposes a new approach for building integrated risk maps using the principle of a multiattribute efficient frontier and analyzing the partial order of elements of a risk map as distributed in multidimensional criteria space. The integrated risks are estimated as subsequent multiattribute frontiers in dimensions of individual risk criteria. We demonstrate the approach with the example of Agrilus biguttatus Fabricius, a high‐risk pest that may threaten North American oak forests in the near future. Drawing on U.S. and Canadian data, we compare the performance of the multiattribute ranking against a multicriteria linear weighted averaging technique in the presence of uncertainties, using the concept of robustness from info‐gap decision theory. The results show major geographic hotspots where the consideration of tradeoffs between multiple risk components changes integrated risk rankings. Both methods delineate similar geographical regions of high and low risks. Overall, aggregation based on a delineation of multiattribute efficient frontiers can be a useful tool to prioritize risks for anticipated invasive pests, which usually have an extremely poor prior knowledge base.     

Assessment of supplier performance based on product-development strategy by applying multi-granularity linguistic term sets

Measuring supplier performance possesses the properties of multi-dimension and multi-scale, it increases the complexity of the aggregation and assessment process. A focal company must develop an effective procedure for overcoming the complexity of performance measurement. Furthermore, the assessment of supplier performance must conform to the product-developed strategy of the focal company. This study is a further research deeper into the concept already introduced in Chang et al. [1] [Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle. International Journal of Production Economics 2006; 100(2):348–59]; using multi-granularity linguistic variable and numerical ration scale to represent the overall supply performance. By unifying the derived information, the measurement complexity could be resolved. The fuzzy preference was constructed to adjust the consistent direction and transform information into fuzzy relationship. Finally, fuzzy linguistic quantifier guided ordered weighted aggregation (FLQG-OWA) operator with maximal entropy was computed and aggregated with all indicators to meet the current policy of the focal company.     

国家自然科学基金资助项目综合评价:基于Vague 集多准则决策

采用基于Vague 集的多准则决策方法,对国家自然科学基金11 类主要竞争性资助项目的实施情况进行综合评价和排序． 首先,通过问卷调研的方式,由国家自然科学基金项目评审专家采用“高”、“不高”和“不清楚”三类语义,对各类项目按照“评审公正性”、“管理规范性”、“科研创新性”和“社会影响力”四个准则进行评价; 然后,根据问卷统计结果,将语义评价转化为Vague 估计值,并利用一种新的评分函数计算各类项目在各准则下的得分; 最后,采用正态分布的OWA 算子集结各准则下的得分,得到所有项目的综合评价和排序． 本文的研究结果将为完善国家自然科学基金的资助结构与管理模式提供重要参考依据．     

Efficiency or Competition? A Structural Econometric Analysis of Canada's AWS Auction and the Set‐Aside Provision

In 2008, Industry Canada auctioned 105 MHz of spectrum to a group of bidders that included incumbents and potential new entrants into the Canadian mobile phone market, raising $4.25 billion. In an effort to promote new entry, 40 MHz of spectrum was set‐aside for new entrants. In order to estimate the implicit cost of the set‐aside provision, we estimate the parameters of the bidders' profit function via a maximum match estimator based on the notion of pairwise stability in matches. We find that all telecommunications firms valued both geographic complementarities across auction licenses as well as absolute spectrum. Under a reasonable alternative scenario, our results indicate that the set‐aside led to a total profit loss of approximately 10%.     

Sign Restrictions,Structural Vector Autoregressions,and Useful Prior Information

This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.