高职院校混合式教学改革的实践及思考--以浙江省级精品在线开放课程《国际金融实务》为例

随着"互联网+"教育对教学的广泛影响,开发建设数字化教学资源、实施线上线下相结合的混合式教学已成为高职院校课程建设、教学改革的发展方向。浙江省级精品在线开放课程《国际金融实务》混合式教学改革的实践表明,混合式教学模式能够实现激发学生学习兴趣、拓展课堂教学时间和空间、提升课堂教学互动、促进学生个性化自主学习、带动欠发达地区高职院校教学水平提升等效果。着眼未来发展,混合式教学改革还需从完善线上线下整体教学设计、完善教师建设应用在线课程的激励机制、完善在线课程建设应用的考核机制、教育行政主管部门加强顶层设计避免多平台重复建设等方面进一步推进,优化混合式教学改革的应用效果。     

本科教学中逻辑性课程《纳米材料》的主线设计探索

《纳米材料》课程主要讲解纳米材料的结构与性能之间关系的概念与理论,这种定位决定了纳米材料课应采用逻辑教学法.在这种方法下需找到课程逻辑起点,然后沿着起点设计出一条课程主线,建立课程理论体系,从而合理承接培养方案中的课程群.在《纳米材料》中,纳米结构就是逻辑起点,主线就是"结构与性能"的关系.故该门课程应按"结构和性能"这条主线展开.对现行纳米材料课程内容进行分析,大部分内容均可用主线串联起来.该方法为类似的逻辑性课程教学方法改革以及在课程章节内容之间建立逻辑关联提供借鉴.     

Predictive ability and economic gains from volatility forecast combinations

The availability of numerous modeling approaches for volatility forecasting leads to model uncertainty for both researchers and practitioners. A large number of studies provide evidence in favor of combination methods for forecasting a variety of financial variables, but most of them are implemented on returns forecasting and evaluate their performance based solely on statistical evaluation criteria. In this paper, we combine various volatility forecasts based on different combination schemes and evaluate their performance in forecasting the volatility of the S&P 500 index. We use an exhaustive variety of combination methods to forecast volatility, ranging from simple techniques to time-varying techniques based on the past performance of the single models and regression techniques. We then evaluate the forecasting performance of single and combination volatility forecasts based on both statistical and economic loss functions. The empirical analysis in this paper yields an important conclusion. Although combination forecasts based on more complex methods perform better than the simple combinations and single models, there is no dominant combination technique that outperforms the rest in both statistical and economic terms.     

Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts

By linking measures of forecast accuracy as well as testing procedures with regard to forecast rationality this paper investigates aggregated survey forecasts with forecast horizons of 3, 12, and 24 months for the exchange rates of the Chinese yuan, the Hong Kong dollar, the Japanese yen, and the Singapore dollar vis-à-vis the US dollar and, hence, for four different currency regimes. The rationality of the exchange rate predictions is initially assessed utilizing tests for unbiasedness and efficiency which indicate that the investigated forecasts are irrational in the sense that the predictions are biased. As one major contribution of this paper, it is subsequently shown that these results are not consistent with an alternative, less restrictive, measure of rationality. Investigating the order of integration of the time series as well as cointegrating relationships, this empirical evidence supports the conclusion that the majority of forecasts are in fact rational. Regarding forerunning properties of the predictions, the results are rather mediocre, with shorter term forecasts for the tightly managed USD/CNY FX regime being one exception. As one additional important and novel evaluation result, it can be concluded, that the currency regime matters for the quality of exchange rate forecasts.     

Combining multivariate volatility forecasts using weighted losses

The ability to improve out-of-sample forecasting performance by combining forecasts is well established in the literature. This paper advances this literature in the area of multivariate volatility forecasts by developing two combination weighting schemes that exploit volatility persistence to emphasise certain losses within the combination estimation period. A comprehensive empirical analysis of the out-of-sample forecast performance across varying dimensions, loss functions, sub-samples and forecast horizons show that new approaches significantly outperform their counterparts in terms of statistical accuracy. Within the financial applications considered, significant benefits from combination forecasts relative to the individual candidate models are observed. Although the more sophisticated combination approaches consistently rank higher relative to the equally weighted approach, their performance is statistically indistinguishable given the relatively low power of these loss functions. Finally, within the applications, further analysis highlights how combination forecasts dramatically reduce the variability in the parameter of interest, namely the portfolio weight or beta.     

基于广义梯形模糊数相似度的交叉效率集结

在不确定环境下,针对模糊数据的多样性和复杂性,本文结合广义梯形模糊数相似度理论将广义梯形模糊数的交叉效率矩阵转换为交叉互评相似度矩阵,并根据模糊信息检索系统中的布尔模型,以能最大程度还原信息本身为准则,构建满足"正相容性"的有序几何平均集结函数对交叉互评相似度矩阵进行集结,从而得到关于每个决策单元的同行评价综合相似度.根据决策单元的同行评价综合相似度,建立反映决策者偏好的模糊一致性偏好矩阵,并对决策单元进行集结权重的分配,根据分配结果计算决策单元的全局交叉效率值.本文的集结方法可以解决不确定环境下,交叉效率矩阵数据多样性的问题,有较高的适用性;并且其集结结果具有较高的一致性和稳定性.最后本文以梯形模糊数的交叉效率矩阵为算例,来说明该方法的合理性和适用性.     

科技成果社会影响力评估的国际经验及启示

 对英国的卓越研究框架（REF）、荷兰的标准评估协议（SEP）和美国的STAR METRICS这3个典型的科技成果社会影响力评估方案进行比较，识别了其评估对象、评估程序和评估目标方面的差异，重点围绕这3个方案的评估内容指标和评估方法进行了深入分析。结合国际经验，认为中国应当将科技成果社会影响力评估置于公立科研机构绩效评价的核心地位；需要在贯彻国家战略导向和体现评估对象、评估目标和区域差异的基础上开发符合中国国情的科技成果社会影响力评估内容和指标体系；要构建大数据评估并使用数据驱动方法进行科技成果的社会影响力评估。     

建构主义学习理论在Java语言教学中的应用

建构主义强调以学习为中心,学习者是学习的主体。建构主义不仅形成了全新的学习理论,也正在形成全新的教学理论。建构主义的四要素包括情境、协作、会话和意义建构。Java语言是一门面向对象程序设计语言。通过介绍建构主义学习理论在Java语言教学中的应用,说明了在教学情境的创设方面的具体方法和技巧。     

智能控制系统智能水平评价的软件系统

在“一种智能控制系统智能水平的评价方法”提出方法的基础上,提出一种新的评价算法,并设计开发出智能控制系统智能水平评价的软件系统。给出了系统的功能模块设计、数据库设计等,最后列举了两个模拟评价的例子。     

慢跑鞋的足底压强分析与功能评价

采用德国Novel公司的Pedar鞋垫式(in-sole)足底压力测量系统,对6款适合于健身长跑和中长跑运动员训练或公路比赛所穿的慢跑鞋和1款体操鞋(模拟赤足状态)进行3个速度下的足底压强测量.通过步态周期(TGC)、最大地面反作用力(Fmax)、最大足底压强(pmax)、力量-时间积分值(∫Fdt)以及压强-时间积分值(∫pdt)等参数的分析,对各款运动鞋的功能特性进行了初步评价,建立了初步的评价标准.