再谈口译教学和口译教学改革

口译课在我国是一门新兴的翻译课程。随着我国入世和北京申奥成功,社会用人单位对翻译尤其是口译人才的需求日益迫切。而我国目前的口译教学不容乐观。本文通过对我国口译教学现状的分析并结合针对口译教学的技巧和技能训练的说明,提出了一些口译教学的改革思路。     

分布式数据库系统的查询优化策略研究

在分析比较分布式数据库系统和集中式数据库系统查询优化目标不同特点的基础上,归纳出分布式数据库系统的查询优化目标,进而提出查询优化的策略,并在举例中重点讨论了操作执行顺序的不同对查询性能的影响。     

当前编辑工作面临的新环境及应对之策

当前,随着时代的发展,编辑工作所处的社会环境、市场环境和技术环境发生了深刻变化,从而对编辑工作带来新的挑战。针对这一时代变化,分析了编辑工作面临的新环境,并提出了应对之策,以期对提高编辑工作质量有所裨益。     

Scheduling with centralized and decentralized batching policies in concurrent open shops

This article considers batch scheduling with centralized and decentralized decisions. The context of our study is concurrent open shop scheduling where the jobs are to be processed on a set of independent dedicated machines, which process designated operations of the jobs in batches. The batching policy across the machines can be centralized or decentralized. We study such scheduling problems with the objectives of minimizing the maximum lateness, weighted number of tardy jobs, and total weighted completion time, when the job sequence is determined in advance. We present polynomial time dynamic programming algorithms for some cases of these problems and pseudo‐polynomial time algorithms for some problems that are NP‐hard in the ordinary sense. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 58: 17–27, 2011     

基于弹药目标数据库的弹药需求预计

弹药需求预计是弹药保障的前提,是科学筹划弹药保障方案的关键。首先给出了基于弹药目标数据库的弹药需求预计思路,进而在分析目标和弹药性能的基础上,分析了数据元素和数据结构,设计了弹药目标数据库,并给出了基于弹药目标数据库的配对选择及消耗量预计算法。基于弹药目标数据库的弹药需求预计方法能够最大可能避免基于经验推算法的弹药需求预计中大量依赖经验因素的缺陷,准确估计弹药需求,为弹药需求预计提供了新的思路。     

美军作战实验室建设研究

简要回顾了美军作战实验发展的历史,从军种到联合详细阐述了美军作战实验室完整的体系,并简要介绍了各作战实验室所完成的典型实验,研究了美军作战实验室主要的实验方法和技术手段,剖析了美军作战实验室的运行机制,探讨了美军作战实验室建设带给我们的启示。     

背诵对提高口译能力的正迁移及在教学中的应用

背诵是成功的语言学习者常用的策略,也是不同条件下英语教学行之有效的教学方法。文章通过跟踪调查,试验对照的形式,结合SPSS对数据加以分析,在实证研究的基础上,揭示背诵对提高大学生口译能力的正迁移作用并提出如何将背诵科学、合理地应用于口译教学,以提高教学质量。     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

Decision support model for effects estimation and proportionality assessment for targeting in cyber operations

Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical-military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical-military experts.Both the design and the results of the evaluation are revealed in this article.     

装备表面现代维修保养技术研究

结合装备表面智能维修保养技术方面的研究成果,介绍了装甲装备故障智能检测技术、自适应、自修复功能材料,装甲装备器材全自动保养设备等先进技术,侧重装备维修保养阐述了如何提高信息化程度,推进军队武器装备维修保养技术的现代化建设。