多波长直线回归法测定氯地滴眼液中的氯霉素和地塞米松磷酸钠

研究建立测定氯地滴眼液中氯霉素和地塞米松磷酸钠含量的多波长直线回归法。在238.0 nm-290.0 nm波长区间,选择42个波长点作测定;采用计算机多波长直线回归程序作计算;不经分离,直接测定氯地滴眼液中氯霉素和地塞米松磷酸钠的含量。二者的平均回收率和相对标准偏差,分别为99.5%,1.1%和100.7%,1.3%。该方法简单、快速、准确、适用于氯地滴眼液的质量控制。     

计算机程序-多波长直线回归法测定牙周康胶囊中的甲硝唑和芬布芬

研究建立计算机程序一多波长直线回归法,以测定药品牙周康胶囊中甲硝唑和芬布芬的含量.在277.0 nm～318.0 nm波长范围内,选择42个波长点进行测定;采用计算机多波长直线回归程序计算;不经分离,直接测定牙周康胶囊中甲硝唑和芬布芬的含量.两者的平均回收率和相对标准偏差,分别为98.3%,0.75%和98.9%,1.0%.本方法简单、快速、准确、适用于控制牙周康胶囊的质量.     

Determination of the first order reaction rate constant by weighted linear regression

A calculator program K1 is described for computing the first order rate constant by least squares using weighted linear regression. As a result, calculation times are shorter than with iterative methods without compromising on the quality of the result. The presented coding is for the Hewleytt-Packard 41C, but the general algorithms and design features are adaptable for other calculators of comparable or greater program and memory capacity (e.g.TI-59).     

近红外光谱法测定黄芩提取物中黄芩苷含量

应用近红外光谱技术探讨了黄芩提取物中黄芩苷含量的快速检测新方法.共收集12个不同厂家的100批黄芩提取物样品,利用Nicolet 6700型傅立叶变换近红外光谱仪采集样品近红外漫反射光谱,通过HPLC法测定黄芩苷含量值,结合偏最小二乘法(PLS)建立黄芩苷含量的近红外定量校正模型,并通过筛选合适的光谱预处理方法、建模区间和主成分数获得最优模型.所建最优校正模型的相关系数(R2)、校正均方差(RMSEC)和内部交叉验证均方差(RMSECV)分别为0.995、0.440和2.259;经外部验证,模型的预测相关系数(r2)、预测均方差(RMSEP)和平均回收率分别为0.988、0.486和100.190%.结果表明,该方法可用于不同厂家黄芩提取物中黄芩苷含量的直接测定,操作简便,无污染,结果准确可靠,可实现大批量样品的快速分析.     

Input selection and shrinkage in multiresponse linear regression

The regression problem of modeling several response variables using the same set of input variables is considered. The model is linearly parameterized and the parameters are estimated by minimizing the error sum of squares subject to a sparsity constraint. The constraint has the effect of eliminating useless inputs and constraining the parameters of the remaining inputs in the model. Two algorithms for solving the resulting convex cone programming problem are proposed. The first algorithm gives a pointwise solution, while the second one computes the entire path of solutions as a function of the constraint parameter. Based on experiments with real data sets, the proposed method has a similar performance to existing methods. In simulation experiments, the proposed method is competitive both in terms of prediction accuracy and correctness of input selection. The advantages become more apparent when many correlated inputs are available for model construction.     

双波长比值光谱法测定氯地滴眼液中二组分的含量

建立氯地滴眼液中,氯霉素和地塞米松磷酸钠的双波长比值光谱测定法。用Excel绘制氯霉素和地塞米松磷酸钠的比值光谱,选择比值光谱的峰点(或谷点)和交点作为测定波长对,能有效地消除共存组分的干扰,以实现对被测组分的准确测定。在选定的实验条件下,氯霉素和地塞米松磷酸钠在5.0 mg/L～50.0 mg/L范围内,其线性关系良好,平均回收率分别为100.3%、101.5%,相对标准偏差(RSD)分别为0.71%、0.59%。该方法简便、快速、重现性好,可用于氯地滴眼液的质量控制。     

Prediction of feed abrasive value by artificial neural networks and multiple linear regression

In order to evaluate rapid testing methods based on the relationship between feed abrasive value (FAV) and physicochemical properties (particle size, bulk density, dry matter (DM), soluble dry matter, water-holding capacity (WHC), ash, crud protein, neutral detergent fiber (NDF), physically effective NDF and non-fibrous carbohydrates (NFC)), 100 empirical dataset were used. Relationships were investigated using multiple linear regression (MLR) and artificial neural networks (ANNs). The mean relative error was significantly (P?<?0.01) lower for ANN than MLR model. Globally, the non-linear ANN model approach is shown to provide a better prediction of FAV than linear multiple regression.     

Estimation of algebraic solution by limiting the solution set of an interval linear system

In this paper, we introduce a new method for estimating the algebraic solution of an interval linear system (ILS) whose coefficient matrix is real-valued and right-hand side vector is interval-valued. In the proposed method, we first apply the interval Gaussian elimination procedure to obtain the solution set of an interval linear system and then by limiting the solution set of related ILS by the limiting factors, we get an algebraic solution of ILS. In addition, we prove that the obtained solution by our method satisfies the related interval linear system. Finally, based on our method, an algorithm is proposed and numerically demonstrated.     

Combination of linear regression classification and collaborative representation classification

Classification using the l ₂-norm-based representation is usually computationally efficient and is able to obtain high accuracy in the recognition of faces. Among l ₂-norm-based representation methods, linear regression classification (LRC) and collaborative representation classification (CRC) have been widely used. LRC and CRC produce residuals in very different ways, but they both use residuals to perform classification. Therefore, by combining the residuals of these two methods, better performance for face recognition can be achieved. In this paper, a simple weighted sum based fusion scheme is proposed to integrate LRC and CRC for more accurate recognition of faces. The rationale of the proposed method is analyzed. Face recognition experiments illustrate that the proposed method outperforms LRC and CRC.     

Parallel solution of linear systems by quadrant interlocking factorisation methods

This paper presents a parallel algorithm for the solution of linear systems and determinant evaluation suitable for use on the proposed parallel computers of the future. The new method can be considered as extending the novel matrix factorisation strategies introduced by Evans and Hatzopoulos [1] and Evans and Hadjidimos [2] in which quadrant interlocking factors are considered instead of the more usual LU factors of triangular decomposition.