对我国体育院校田径教材的科学化研究

介绍我国体育院校田径教材的历史沿革,对16种田径教材进行科学化研究,分析教材的系统性和层次性,使田径教学、训练和研究更加科学化.为我国体育院校田径教材向着系统化、科学化方向发展提供理论参考.     

任务型教学法在民族高校大学英语教学中的重要作用

民族高校的地缘和生源特点等诸多因素,决定了教师在开展大学英语教学过程中必须采用适合自身特点的教学模式和教学策略。任务型教学法从学生的基本心理需求出发,强调用语言做事,注重学生交际能力的培养,符合大学英语现行的培养目标。从分析任务型教学法的特点以及任务型教学实践入手,阐述了任务型教学法在民族高校大学英语教学中的重要作用。     

推广到多维系统的钱德拉塞卡方法

将钱德拉塞卡等提出的构造拉格朗日函数方法从一维系统推广到多维系统,并讨论其中存在的问题.举例说明所得结果的应用.     

高校青年教师胜任力提高路径实现中的障碍分析及解决措施探析

在工作实践中学习是高校青年教师胜任力提高的主要途径。目前高校青年教师有效的学习途径因各种原因难以顺利实现。在调查的基础上，笔者对有效的学习途径难以实现的原因进行了分析，提出解决这些问题的措施，主要包括高校建立和完善相关制度，采取必要的组织干预措施，督促青年教师围绕学校发展目标落实胜任力提高的规划。     

论口译教材编撰的困境与突破

口译是一门年轻的学科。口译教材是培养口译人才的关键着手点。我国目前的口译教材数量剧增,但是并没有质的提升。本文就口译教材编撰问题所面临的困境,根据哲学主义体验观和链接主义学习观,提出了突破困境的方法,即口译教材的音质化。     

基于区间证据推理的不确定性航线配船方法

为弥补不确定性航线配船模拟算法的不足,提出一种基于区间证据推理的航线配船解析算法.该方法以证据推理理论为基础,以船舶公司期望效用最大化为目标,考虑航线特征及船舶属性等因素,构建出一个多航线、多船型的航线配船模型.与目前的模拟算法相比,该方法具有稳定性好、准确性高、可以处理模糊数据等优点.最后,通过算例验证了模型的可行性和方法的有效性.     

The Role of Survey Data in Nowcasting Euro Area GDP Growth

This paper evaluates the impact of new releases of financial, real activity and survey data on nowcasting euro area gross domestic product (GDP). We show that all three data categories positively impact on the accuracy of GDP nowcasts, whereby the effect is largest in the case of real activity data. When treating variables as if they were all published at the same time and without any time lag, financial series lose all their significance, while survey data remain an important ingredient for the nowcasting exercise. The subsequent analysis shows that the sectoral coverage of survey data, which is broader than that of timely available real activity data, as well as their information content stemming from questions focusing on agents' expectations, are the main sources of the ‘genuine’ predictive power of survey data. When the forecast period is restricted to the 2008–09 financial crisis, the main change is an enhanced forecasting role for financial data. Copyright © 2015 John Wiley & Sons, Ltd.     

Underdetermined DOA estimation and blind separation of non-disjoint sources in time-frequency domain based on sparse representation method

This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time-frequency （TF） disjoint to a certain extent. In particular, the number of sources presented at any TF neighborhood is strictly less than that of sensors. We can identify the real number of active sources and achieve separation in any TF neighborhood by the sparse representation method. Compared with the subspace-based algorithm under the same sparseness assumption, which suffers from the extra noise effect since it can-not estimate the true number of active sources, the proposed algorithm can estimate the number of active sources and their cor-responding TF values in any TF neighborhood simultaneously. An-other contribution of this paper is a new estimation procedure for the DOA of sources in the underdetermined case, which combines the TF sparseness of sources and the clustering technique. Sim-ulation results demonstrate the validity and high performance of the proposed algorithm in both blind source separation （BSS） and DOA estimation.     

大学生参与高校图书馆管理活动的心理轨迹分析

以大学生参与图书馆行为的需求价值为出发点,阐述了问题分析的基本框架,提出了大学生参与图书馆行为的需求价值实现路径。