汇文Libsys5.5和ILASⅡ馆藏统计功能对比分析--以河北工程大学图书馆实践为例

介绍了ILASⅡ和汇文Libsys5.5的馆藏统计功能设置,阐述了汇文Libsys5.5和ILASⅡ馆藏统计功能的应用,提出了ILASⅡ向汇文Libsys5.5转换时应注意的问题。     

高校图书馆大规模馆藏精准迁移模式探讨--以华北电力大学图书馆为例

书库藏书迁移的运作主要在于精心准备和周密筹划。详细介绍了华北电力大学图书馆利用汇文文献信息服务系统的强大分析功能并结合Excel软件的使用技巧,实现大规模馆藏迁移精准排架工作的经验。     

杨氏模量实验的优化研究

针对传统杨氏模量测量存在的一些问题进行深入分析,进而对传统杨氏模量测量仪进行改进,最后提出了减少实验误差、简化数据处理的建议.     

2009年亚锦赛决赛中国女排失利的因素分析

通过查阅国内期刊库和及观看比赛回放等途径,从非技术因素和技术因素方面对2009年亚州女子排球锦标赛中国女排和泰国女排比赛失利进行分析.结果表明：中国女排失利的原因主要有心理状态不佳、伤病因素、教练因素及发球拦网一传等技术环节的失误.通过进行全方位的分析为中国女排再创辉煌提供理论上的参考.     

关于“对Thomas＆Wollan定理的R．Diestel证明方法”的一个注记

指出了Diestel关于图论的研究生教材中Thomas＆Wollan定理的一个弱形式证明中存在的一个错误（第76页式（3））,并提供了一种改正方式。     

基于非负矩阵分解技术探寻早期阿尔茨海默症基因表达调控网络

本文利用非负矩阵分解(NMF)技术,依据加强算法的稀疏性对患早期阿尔茨海默 症(Alzheimer’s Disease,AD)样本的基因表达数据进行了分析,提取了对疾病早期诊断具有重 要意义的显著基因,样本分类实验结果证明了算法的有效性。在此基础上,结合与炎症反应 有重要关系的 NF-κB 等基因初步建立了与早期 AD 密切相关的基因表达调控网络结构图, 为 AD 致病机理的探询、早期诊断与治疗等提供了有益的途径和方法。     

基于素质教育的中学地理教学改革与方法创新

结合中学地理教学目标、教材特点和当代中学生学习环境的变化,提出了基于素质教育的中学地理教师应具备的素质和技能:教师是复合型研究性人才;具有终身学习理念;具有科学方法论做指导;具有跨学科知识结构体系.根据目前中学地理教学的现状和问题,提出了基于素质教育的中学地理教学改革和方法创新的途径:自觉运用哲学理论和逻辑方法;软化学...     

8周健身运动处方教学对保健班学生身体成分的影响

为了解健身运动处方对保健班学生身体成分的影响,对齐齐哈尔大学23名保健班学生进行8周健身运动处方教学,并对所有学生在8周教学前后的体脂百分比、BMI和身体形态等指标进行测试.结果表明,保健班学生实验后的体脂百分比出现一定程度的下降,符合健康标准的人数逐步增多,胸围和呼吸差发生了一定的变化(P<0.05),腰围在低于风险...     

Correcting the January optimism effect

Each month, various professional forecasters give forecasts for next year's real gross domestic product (GDP) growth and unemployment. January is a special month, when the forecast horizon moves to the following calendar year. Instead of deleting the January data when analyzing forecast updates, I propose a periodic version of a test regression for weak-form efficiency. An application of this periodic model for many forecasts across a range of countries shows that in January GDP forecast updates are positive, whereas the forecast updates for unemployment are negative. I document that this January optimism about the new calendar year is detrimental to forecast accuracy. To empirically analyze Okun's law, I also propose a periodic test regression, and its application provides more support for this law.     

Intermittent demand forecasting in the Enterprise: Empirical verification

Forecasting methods are often valued by means of simulation studies. For intermittent demand items there are often very few non–zero observations, so it is hard to check any assumptions, because statistical information is often too weak to determine, for example, distribution of a variable. Therefore, it seems important to verify the forecasting methods on the basis of real data. The main aim of the article is an empirical verification of several forecasting methods applicable in case of intermittent demand. Some items are sold only in specific subperiods (in given month in each year, for example), but most forecasting methods (such as Croston's method) give non–zero forecasts for all periods. For example, summer work clothes should have non–zero forecasts only for summer months and many methods will usually provide non–zero forecasts for all months under consideration. This was the motivation for proposing and testing a new forecasting technique which can be applicable to seasonal items. In the article six methods were applied to construct separate forecasting systems: Croston's, SBA (Syntetos–Boylan Approximation), TSB (Teunter, Syntetos, Babai), MA (Moving Average), SES (Simple Exponential Smoothing) and SESAP (Simple Exponential Smoothing for Analogous subPeriods). The latter method (SESAP) is an author's proposal dedicated for companies facing the problem of seasonal items. By analogous subperiods the same subperiods in each year are understood, for example, the same months in each year. A data set from the real company was used to apply all the above forecasting procedures. That data set contained monthly time series for about nine thousand products. The forecasts accuracy was tested by means of both parametric and non–parametric measures. The scaled mean and the scaled root mean squared error were used to check biasedness and efficiency. Also, the mean absolute scaled error and the shares of best forecasts were estimated. The general conclusion is that in the analyzed company a forecasting system should be based on two forecasting methods: TSB and SESAP, but the latter method should be applied only to seasonal items (products sold only in specific subperiods). It also turned out that Croston's and SBA methods work worse than much simpler methods, such as SES or MA. The presented analysis might be helpful for enterprises facing the problem of forecasting intermittent items (and seasonal intermittent items as well).