经贸翻译常见错误剖析

经贸翻译,主要是给国际商务往来提供交流上的方便,提供足够并准确的信息。本文从“忠实、通顺”的翻译标准出发,通过具体的教学案例分析,探讨了经贸翻译中常出现的错译误译的种类,进而剖析造成此类错误的根源,指出了译者应扩大知识面和加深专业知识,翻译前多找资料多查询,翻译过程中多查词典和参考书,秉持认真严谨的态度。避免错译误译的发生。     

高职商务英语课程改革研究

本文通过分析国内、外商务英语研究,以及国内高职商务英语教学现状,初步提出高职商务英语课程改革的基本思路,确立以能力为本位的培养目标,制定课程标准,开发以英语为媒介、以商务活动为载体、以工作过程为主线、以完成工作任务为目标的项目课程,为学生提供较为真实的商务活动场景,切实培养学生应用英语进行商务活动的能力。     

一种基于元模型和多视图的企业目标建模方法

信息系统的成功研发很大程度上依赖于高质量的系统需求.企业建模可以析出目标模型,为系统需求提供依据.给出了反映企业本质属性的,具有严格语义的企业元模型.在元模型驱动下,用组织视图和业务视图对企业的组织结构和动态行为进行建模,并通过组织和业务视图建模间接地构建目标模型.这种方法使分析人员在实际建模时,能够有效地理解企业,构建目标模型.     

房地产融资租赁经营的理论分析

对房地产融资租赁经营的特性、资金筹措的方式及如何规避房地产融资租赁的风险进行了分析．     

基于规则的业务流程描述算法的研究

为了使业务逻辑具有独立性,使业务逻辑的描述更为清晰,文章提出了用产生式规则来描述软件系统的业务逻辑,实现了使用陈述性的语言来描述系统的业务逻辑.并给出了流程图到产生式规则的转换方法,根据流程图到产生式规则的转换算法,可以直接把系统分析和设计的结果转换为系统实现中的规则集合,从而实现系统的部分自动化.     

A Comparative Study of Accounting Entities Under Different Business Organizations

ln order to regu1ate the estab1ishment and operation of various types of businessenterprises, the Chinese government has issued various laws and decrees, among them areThe Law of the PeOPle'S RePublic-of China on Joint Ventures Using Chinese and ForeignInvestment, Law of the PeOPle'S RePublic Of China on Chinese--Foreign Contractual JointVentures, and The PeOPle'S RePublic Of China COmPany Law... Business enterprisesestablished in accordance with these relevant laws and decrees…     

An Efficient Algorithm for Obtaining the Optimum Solution of a Generalized Assignment Problem

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System-Organisational Aspect of a Learning Organisation in Companies

The objective of this article is to discuss the learning organisation (LO) concept in correlation with network organisation (NO), which is an indispensable element for the transition into the new era of management, i.e. knowledge networking. Business organisations (BO) rarely achieve innovativeness, and thus competitive advantage, without establishing NO/LO and knowledge management. Therefore, a suitable knowledge strategy must be developed that is related to BO's business strategy. The last two statements surface our main hypothesis, which is described in our general model on linking the elements of an LO and then tested by empirical research carried out in Slovenian BOs. Our original model of LO has proved helpful in understanding BOs as LOs in transitional economies, e.g. in Slovenia. In them an innovation-based business has not yet become the norm with BOs of all sizes, with success mainly enjoyed in larger BOs. However, NO can help the LO concept spread and support innovativeness rather quickly in all BOs.

Evaluation of Regime Switching Models for Real‐Time Business Cycle Analysis of the Euro Area

In this paper, we aim at assessing Markov switching and threshold models in their ability to identify turning points of economic cycles. By using vintage data updated on a monthly basis, we compare their ability to date ex post the occurrence of turning points, evaluate the stability over time of the signal emitted by the models and assess their ability to detect in real‐time recession signals. We show that the competitive use of these models provides a more robust analysis and detection of turning points. To perform the complete analysis, we have built a historical vintage database for the euro area going back to 1970 for two monthly macroeconomic variables of major importance for short‐term economic outlook, namely the industrial production index and the unemployment rate. Copyright © 2013 John Wiley & Sons, Ltd.     

Forecasting Core Business Transformation Risk Using the Optimal Rough Set and the Neural Network

In the process of enterprise growth, core business transformation is an eternal theme. Enterprise risk forecasting is always an important concern for stakeholders. Considering the completeness and accuracy of the information in the early‐warning index, this paper presents a new risk‐forecasting method for enterprises to use for core business transformation by using rough set theory and an artificial neural network. First, continuous attribute values are discretized using the fuzzy clustering algorithm based on the maximum discernibility value function and information entropy. Afterwards, the major attributes are reduced by the rough sets. The core business transformation risk rank judgement is extracted to define the connection between network nodes and determine the structure of the neural networks. Finally, the improved back‐propagation (BP) neural network learning and training are used to judge the risk level of the test samples. The experiments are based on 265 listed companies in China, and the results show that the proposed risk‐forecasting model based on rough sets and the neural network provides higher prediction accuracy rates than do other widely developed baselines including logistic regression, neural networks and association rules mining. Copyright © 2015 John Wiley & Sons, Ltd.