基于EMD的电能质量扰动检测与分类方法

针对电能质量扰动信号的检测和分类问题,提出了一种基于EMD的电能质量扰动检测与分类方法,并对常见的几种扰动信号进行仿真。应用该方法检测扰动发生时间、持续时间以及扰动的频率与幅值。仿真结果表明,所提算法简洁有效,能够准确分析电能质量扰动信号,可以估计电压凹陷、电压凸起以及电压中断等扰动信号的变化幅度和频率。     

抑芽剂对山药保鲜效果的研究

不同浓度的抑芽剂对山药保鲜效果的试验表明:粉剂1.0 g/kg有效地抑制了山药发芽和呼吸作用,延缓了失重率和丙二醛含量的增加,抑制了PPO活性的增加并推迟了POD活性高峰期,是该研究范围的最佳山药抑芽剂浓度,其次为乳油150倍;粉剂1.5 g/kg的抑芽效果较其他浓度要差,乳油200倍的呼吸强度变化幅度最小,其值都维持在较低的水平,180 d时其呼吸强度仅为6.32 mg(/kg.h),有效地抑制了山药的呼吸作用.     

基于距离比较的等级评价模型的GUI实现与应用——以教师课堂教学质量评价为例

文章根据多元统计分析中有关分类分析(聚类分析、判别分析)中的距离比较法建立了等级评价模型,并运用MATLAB的GUI模块对应地建立了等级评价的可视化计算机操作系统。最后,在教师课堂教学质量评价标准(评价标准矩阵)和某部门的教师评价指标数据(样品矩阵)已知的假设前提下,应用该计算机GUI操作系统进行了模拟等级评价,最终评价结果与实际相符。通过模拟评价验证了该操作系统的简洁性与通用性。     

基于高阶累积量的暂态扰动Mahalanobis距离分类

为实现对脉冲暂态和振荡暂态2类暂态电能质量扰动的分类,提出一种基于高阶累积量的暂态电能质量扰动Mahalanobis距离分类法.该方法利用高阶累积量提取暂态扰动的高阶统计特征,选取其2,3,4阶累积量最大值和最小值构成扰动信号的6维特征向量,计算测试样本特征向量与标准模板之间的Mahalanobis距离,以“距离最小”作为分类判据,实现对2类暂态电能质量扰动的分类.仿真结果表明,低阶累积量不能单独用于区分不同类型暂态电能质量扰动;特征向量维数越高,对分类过程越有利.所提方法分类原理简单、准确率高,是暂态电能质量扰动的有效分类方法.     

左右手运动想象脑电模式识别研究

如何提高左右手运动想象脑电信号的分类率是脑机接口研究领域的一个热点话题。基于美国EGI64导脑电采集系统得到3名健康被试的脑电数据,首先,采用独立成分分析（Independent Component Analysis,ICA）对采集的数据进行去噪处理;然后,利用离散小波变换方法对分解C3/C4处的EEG平均功率信号,选用尺度6上逼近系数A6的重构信号作为脑电特征信号;最后,用Fisher线性判别分析法（Fisher Linear Discriminant Analysis,FLDA）、支持向量机方法 （Support Vector Machines,SVM）和极限学习机分类方法 （Extreme Learning Machine,ELM）分别对特征信号进行分类。分类结果表明：极限学习机分类方法得出的平均分类率要高于Fisher方法与SVM方法的平均分类率,可以达到92%,而且运行速度也高于另两种分类算法。     

论高校学生综合素质评价体系的重构

文章以《国家中长期教育改革和发展规划纲要（2010-2020）》提出的提高高等教育人才培养质量为出发点,在强调学生综合素质评价应取得理念创新的基础上,对当前学生评价理念上存在的问题深入剖析,并从评价目标确立、评价模式选用、评价指标建立等方面对新时期高校学生综合素质评价体系的重构进行论述,同时提出了评价实施中应注意的几个问题,试图为高校人才培养制度改革、学生综合素质评价改革等提供新的认识,对高校开展学生综合素质评价工作作出有益的探索。     

高校公共体育课程体系优化的研究——以浙江工业大学体育课程改革为例

文章通过资料、访谈、问卷调查和统计分析方法对浙江工业大学公共体育课程体系的操作现状进行调查与分析,针对调查中发现的问题,从优化课程资源、构建课内外一体化的课程模式、优化课程评价体系以及加强以长跑为特色的校园体育文化建设角度提出了课程体系的优化策略,以期为高校体育课程改革的理论研究和实践操作提供一定的参考。     

WATER QUALITY ASSESSMENT AND APPORTIONMENT OF POLLUTION SOURCES OF TIGRIS RIVER (TURKEY) USING MULTIVARIATE STATISTICAL TECHNIQUES—A CASE STUDY

The Tigris is one of the most important transboundary rivers in western Asia and originates in the Toros mountains of the Eastern Anatolia region of Turkey. Multivariate statistical techniques, such as cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA), were applied for the evaluation of temporal/spatial variations and the interpretation of a water quality data set for the Tigris River, which was obtained during 1 year of monitoring. This study presents the usefulness of multivariate statistical techniques for the evaluation and interpretation of complex water quality data sets and apportionment of pollution sources/factors to obtain better information about water quality and the design of a monitoring network for the effective management of water resources. Hierarchical CA grouped 12 months into two periods (the first and second periods) and classified seven monitoring sites into three groups, that is, less polluted sites, medium polluted sites and highly polluted sites, based on similarities in the water quality characteristics. PCA/FA identified five factors in the data structure, which explained 77.5% of the total variance of the data set. This allowed us to group the selected parameters according to common features and to evaluate the influence of each group on the overall variation in water quality. Varifactors obtained from the factor analysis indicated that the parameters responsible for water quality variation were mainly related to soluble salts (natural), organic pollution and nutrients (anthropogenic). Copyright © 2011 John Wiley & Sons, Ltd.     

Development of a fish‐based index of biotic integrity (FIBI) for monitoring riverine ecosystems in the Lake Victoria drainage Basin,Kenya

The long term monitoring of aquatic ecosystems based on chemical analysis is expensive resulting in a lack of time series data for management purposes thus necessitating the need for new cost effective methodologies. This study developed a fish‐based index of biotic integrity (FIBI) for monitoring environmental conditions in riverine ecosystems within the Lake Victoria Basin, Kenya. The fish fauna in the basin is poorly studied, less diverse and ecologically specialized than the temperate fauna that provided the origins of the Index of Biotic Integrity. Fish samples were collected by electrofishing from 24 sites during baseflow periods in February, March and July 2004. Validation data were collected from 7 sites with varying levels of degradation. Fish samples were identified, counted and grouped into different trophic groups, relative tolerance to pollution, habitat guild and whether exotic or native to riverine environment. Thirty‐three candidate metrics were evaluated for responsiveness to habitat quality and twelve were selected for inclusion in the final index. The index classified 6 of the 7 validation sites according to their levels of degradation. As a bioassessment tool, the index was useful in laying the basis for long‐term monitoring of rivers in the Lake Victoria drainage basin. Copyright © 2010 John Wiley & Sons, Ltd.     

ENVIRONMENTAL DETERMINANTS OF WATER QUALITY IN BOREAL RIVERS BASED ON PARTITIONING METHODS

Quantitative studies of the relationships between river water quality and environmental variables are needed to improve understanding of the impacts of natural and human factors on aquatic environments. However, multicollinearity between environmental variables can hinder the identification of key factors when water quality–environment relationship is studied using traditional regression methods. This study utilized two alternative statistical methods, variation and hierarchical partitioning, to address these difficulties in studies of river water quality. Using these methods, we explored the effects of catchment physiography, climate and land use variables on total phosphorus and nitrogen, pH, water colour and dissolved oxygen during the years 1995–2005 in 32 boreal rivers in Finland. Catchment physiography and land use explained most of the variation in water quality, especially in phosphorus, nitrogen and water colour data. The strong correlations (r_s > 0.8) between agricultural land use and phosphorus and nitrogen concentrations indicate that water quality is highly affected by agriculture in boreal regions. By determining the environmental drivers of different water quality variables, we can estimate the water quality of different catchments in response to environmental changes and identify areas that are sensitive to global changes. Our study shows that novel statistical methods integrated with geographic information system data and techniques provide deeper insights into water quality–environment relationships than traditional regression, and these should be considered when developing, for example, conservation planning for rivers. Copyright © 2011 John Wiley & Sons, Ltd.