农残水平测试中数据多态性分析及指定值估计研究

对全国农残水平测试中毒死蜱、氯氰菊酯数据进行统计分析,在数据统计分布特征研究基础上,使用内核密度估计进行数据多态性分析,使用bootstrap模拟取样法对数据样本值重复取样,以获得稳健的水平测试样品待测物含量代表值估计、标准误差及置信区间描述,证明以bootstrap模拟取样法获取的均值与标准偏差作为有限单次样本代表值是合理、有效的,解决了四分位稳健统计方法对非正态多态分布代表值估计不稳定问题及取样理论中取样样本数限制的瓶颈,为能力验证计划指定值的获取提供了一种新方法。     

进口铁矿砷量特征的内核密度分析与Bootstrap代表值估计

对进口铁矿中的砷量进行了总体统计分析, 在数据统计分布特征研究基础上, 使用内核密度估计对进口铁矿砷量进行数据多态性分析, 使用bootstrap对原始数据样本值重复取样以获得稳健的砷量代表值估计及标准偏差, 证明以bootstrap重新取样样本分布的均值与标准偏差作为有限单次样本代表值是合理、有效的.     

取样方差估计值的精度与样本数目之间的关系

通过数学推导建立了取样方差估计值的精度与样本数目之间的定量关系。实验也证明,取样方差估计值的标准偏差与样本数目的平方根之积可近似为一常数。应用蒙特卡罗技术模拟随机取样,对该关系式进行了验证,并探讨了取样方差估计值的分布规律,表明其规律对于组分含量服从正态分布,均匀随机分布及多项分布总体是相似的。     

取样量对润滑油中微量水分检测结果的影响

研究取样量对润滑油中微量水分测定结果的影响。基于卡尔·费休滴定法,在选定的测量条件下,用发生电极为有隔膜的自动库仑水分仪对基础油、有机热载体油、压缩机油、膨胀机油等新油和发动机油、汽轮机油、涡轮机油、压缩机油、齿轮油、液压油、导热油、船用油、电器绝缘油、风动工具油、金属加工油等在用油在0.1~2.0 g内各取9组不同质量的样品进行测定,得到了润滑油中微量水分准确测定所需的取样量。实验结果表明,新油取样量大于1.0 g,在用油取样量在1.0~1.5 g范围内,可以准确测定润滑油中微量水分含量。测定结果的相对标准偏差为0.83%~3.51%(n=10),样品加标回收率为95.0%~103.0%。在选择的取样量下,该方法具有良好的精密度、准确度,可连续测定多个样品,满足测定需求。     

渐进取样法及其应用

提出了渐进取样法,通过样本数目的累积,使总方差估计值达到所需的精度。应用Ｍｏｎｔｅ Ｃａｒｌｏ模拟技术考察了满足一定取样精度的样本数目及其偏差。将该方法应用于散装生铁块中Ｓｉ、Ｍｎ、Ｃ、Ｓ、Ｐ含量分析的取样,结果令人满意。该项研究对于大宗货物的实际随机取样具有重要参考价值。     

计算机模拟取样确定标准物质的最小取样量

本文提出用计算机模拟取样对不同的取样量重复进行测试多次,统计其检测结果的标准偏差,做出标准偏差s对取样量m的拟合曲线,再计算最小取样量。设计的模式是一颗一颗地取样,这样不存在取样操作及测试过程带来的误差,操作是可行的,结果是可靠的。计算机运算速度快,参数转换方便,也可以取毫克甚至亚毫克样进行实验。只要有足够的岩矿鉴定的资料,可以模拟不同状态下的样品取样过程。     

小体积常压气体中微量水分分析方法研究

本文在卡尔·费休库仑法的基础上建立了一套独特的分析系统和相应的分析方法,用以分析常温常压下小体积气体中微量水分。通过检测高纯氮气中的微量水分考核了方法的精密度,分析数据的实验标准偏差U<10%;通过分析空气中的水分含量验证了方法的准确度,空气中水分的测量值与计算值在误差范围内一致。小体积常压气体中微量水分的卡尔.费休分析方法的建立,对分析贮存环境气体内水分变化规律及采取有效措施控制封装气体内水分含量,建立较干燥的贮存环境具有指导作用。     

分层性物质的组合取样误差与份样数目之间的关系及其Monte Carlo模拟

本文从理论上研究了分层性物质的组合取样误差与份样数目之间的定量关系，表明份样数目与组合取样相对标准偏差的平方之积为一常数，称为组合取样常数，它与Ｉｎｇａｍ ｅｌｌｓ 和Ｓｗ ｉｔｚｅｒ 提出的取样常数是相似的，表示６８％ 置信度下组合取样的相对标准偏差达到１％ 时的份样数目。应用Ｍｏｎｔｅ Ｃａｒｌｏ 模拟技术对该理论进行了验证，结果令人满意。     

手持式X-荧光光谱仪在云南边境口岸进口矿产品快速检测中的应用

为在云南边境口岸充分应用快速检测技术,利用手持式X-荧光光谱仪对标准样品及进口矿产品进行了定性、半定量分析,确定了矿产品中各种元素成分及其含量,与标准样品认证值以及实验室化学分析法测定结果相比较,分析了手持式X-荧光光谱仪对矿产品中元素分析的准确性。结果显示：手持式X-荧光光谱仪能够快速检测元素含量,初步识别、判断矿石品质,可有效提高工作效率,为口岸检测进口矿产品工作提供参考。     

我国进口铁矿石有害元素含量代表值估计及整体特征分析

对我国进口铁矿石中的环境有害元素As、Cr、Cd、Pb、S的含量进行了总体统计分析,选用了四分位稳健统计分析及内核密度估计分别对铁矿中的有害元素As、Cr、Cd、Pb、S的含量的代表值进行估计,探讨了两种方法在代表值估计方面的特点,并使用主成分分析、因子分析等多元统计分析方法对有害元素的含量特征进行整体分类描述,确定了含量特征整体分类的主要有害元素,全面了解进口铁矿中涉及安全、环保等有害元素的质量状况.     

生物质固体成型燃料热值和碳元素预测模型的建立

建立生物质固体成型燃料热值和碳元素预测模型。利用秸秆类生物质固体成型燃料的测试数据,以工业分析中的水分、灰分、挥发分和固定碳含量指标为4个自变量,分别以低位热值、高位热值和碳元素分析为因变量,通过多元线性回归模型(MLR)方法建立多元线性回归预测模型。内部检验和外部检验说明3组模型在应用域范围内均具有理想的预测能力,拟合效果良好,其中高位热值预测模型的R^2和R^2_(prep)分别为0.900和0.730,与已有研究相比,相对残差范围减小为–2.59%~2.26%,可为工业用途的生物质固体成型燃料的热值和碳元素分析快速做出反映。     

镍湿法冶炼中间品品质鉴定方法研究

镍湿法冶炼中间品是以含镍矿料经酸浸、碱沉等湿法冶炼工艺处理后得到的粗级产品,尤其以氢氧化镍为典型产品,该类产品粒度细,含水率高,在取制样过程中水分偏析严重。水分和镍品位是品质鉴定的关键要素,直接影响货值判定。通过对水分和镍含量的测定进行试验对比,水分测定采用两步法和一步法测定,结果上没有较大差异。对于主品位镍的分析取样,品质波动小,可以进一步扩大取样基数,减少份样数量表征货物品质,对验货同行人员具有一定的借鉴意义。     

近红外光谱法在红曲菌固态发酵过程参数检测中的应用

研究了近红外光谱技术快速检测红曲菌固态发酵过程参数水分含量和pH值的可行性。针对传统基于间隔策略波长选择方法忽略非线性因素的缺点,采用一种基于最小二乘支持向量机(Least squares support vector machines,LS-SVM)非线性模型的波长筛选算法：联合区间最小二乘支持向量机(Synergy interval least squares support vector machines,siLS-SVM),并将新算法与相关系数法、iPLS算法、siPLS算法对比。实验结果显示,联合siLS-SVM算法和LS-SVM模型取得了最好的预测效果,水分含量、pH值的预测集相关系数(Rp)分别为0.962 1、0.976 1,预测均方根误差(RMSEP)分别为0.012 9、0.145 2,表明模型具有较好的拟合度和预测性能。应用近红外光谱法进行红曲菌固态发酵过程的水分含量和pH值的快速检测可行,该方法为进一步实现其过程参数的在线检测及发酵条件优化提供了技术基础。     

The effect of various potato cultivars at different times during growth on starch content determined by DSC

Differential scanning calorimetry (DSC) was used to determine the starch content of potato dry matter isolated from various cultivars at different times during growth. When potato dry matter was heated in the presence of excess water, a symmetrical endothermic peak resulted, which was similar to the gelatinization peak of pure starch. From the enthalpy value of potato dry matter and pure potato starch at a moisture content of 70%, the starch content in the potato dry matter can be determined. Starch content increased as growth progressed to a maximum and then decreased. The effect of moisture content and sample mass on gelatinization of dry matter and starch was also investigated. Compared to other starch analysis technique, DSC is a simple and more rapid method.     

A bootstrap estimation scheme for chemical compositional data with nondetects

The bootstrap method is commonly used to estimate the distribution of estimators and their associated uncertainty when explicit analytic expressions are not available or are difficult to obtain. It has been widely applied in environmental and geochemical studies, where the data generated often represent parts of whole, typically chemical concentrations. This kind of constrained data is generically called compositional data, and they require specialised statistical methods to properly account for their particular covariance structure. On the other hand, it is not unusual in practice that those data contain labels denoting nondetects, that is, concentrations falling below detection limits. Nondetects impede the implementation of the bootstrap and represent an additional source of uncertainty that must be taken into account. In this work, a bootstrap scheme is devised that handles nondetects by adding an imputation step within the resampling process and conveniently propagates their associated uncertainly. In doing so, it considers the constrained relationships between chemical concentrations originated from their compositional nature. Bootstrap estimates using a range of imputation methods, including new stochastic proposals, are compared across scenarios of increasing difficulty. They are formulated to meet compositional principles following the log‐ratio approach, and an adjustment is introduced in the multivariate case to deal with nonclosed samples. Results suggest that nondetect bootstrap based on model‐based imputation is generally preferable. A robust approach based on isometric log‐ratio transformations appears to be particularly suited in this context. Computer routines in the R statistical programming language are provided. Copyright © 2014 John Wiley & Sons, Ltd.     

粮食水分的测量和电子水分仪测量不确定度的评定

介绍粮食中水分的两种测量方法：烘干称重法和电测法。同一台水分仪测量不同品种的粮食可能有不同的不确定度,一台水分仪要存入多条工作曲线用以测量不同品种粮食的含水量。介绍了电子水分仪测量不确定度的评定方法。     

Determination of 5-hydroxymethylfurfural after Winkler and by the HPLC method for authentication of honey

The quality and authenticity of commercially available honey from Slovak market and the development of HPLC method for determination of hydroxymethylfurfural (HMF) content of honey with fine separation efficiency, sensitivity, applicability, and recovery was evaluated. Physicochemical parameters (moisture, total acidity, content of proline, saccharides, and value of electrical conductivity) have been determined.     

On estimating model complexity and prediction errors in multivariate calibration: generalized resampling by random sample weighting (RSW)

The present paper focuses on determining the number of PLS components by using resampling methods such as cross validation (CV), Monte Carlo cross validation (MCCV), bootstrapping (BS), etc. To resample the training data, random non‐negative weights are assigned to the original training samples and a sample‐weighted PLS model is developed without increasing the computational burden much. Random weighting is a generalization of the traditional resampling methods and is expected to have a lower risk of getting an insufficient training set. For prediction, only the training samples with random weights less than a threshold value are selected to ensure that the prediction samples have less influence on training. For complicated data, because the optimal number of PLS components is often not unique or readily distinguished and there might exist an optimal region of model complexity, the distribution of prediction errors can be more useful than a single value of root mean squared error of prediction (RMSEP). Therefore, the distribution of prediction errors are estimated by repeated random sample weighting and used to determine model complexity. RSW is compared with its traditional counterparts like CV, MCCV, BS and a recently proposed randomization test method to demonstrate its usefulness. Copyright © 2010 John Wiley & Sons, Ltd.