An Orthogonal Expansion Algorithm of Principal Component Suitable to Deal with the Fingerprinting Data of Chinese Medicine

中药指纹图谱数据具有变量数很大而样本数较小的特点,本文中采用拉格朗日求极值的方法得到一种新的适合用于处理这类数据的主成分正交分解算法.结果表明:所得到新的算法,在处理中药指纹图谱数据时,与传统的主成分分析算法比较,节省存储单元,计算量小,计算速度快,因而计算效率高.The fingerprinting data sets of Chinese medicine are the data sets with large number of variables and few objects.A new kind of orthogonal expansion algorithm of Principal Component that is suitable to deal with this kind of data sets has been obtained by use of the Lagrange method of solving extremum problem in this paper.The results indicate that by comparing with the traditional Principal Component Analysis algorithm the new presented algorithm is memory-saving,with small amount of calculation,fast and effective when dealing with the fingerprinting data of Chinese medicine or the data with large number of variables and few objects.福建省自然科学基金(C0210006);; 福建中药GAP关键技术研究基金(2002Y024)资

有序Cram-Schmidt正交化在研究无取向硅钢质量中的应用

无取向硅钢工艺是一个多变量系统,影响产品质量的素多,本工作从生产现场收集了147组数据,应用有序Gram-Schmidt正交化等多元分析方法处理数据,找出影响质量的主要因素,根据PRESS判据排除多噪音的因素,建立预报能力较强的模型,并从分析中找出提高质量的措施

Application of pattern recognition technology in classification of Radix et Rhizoma Glycyrrhizae of different sources

目的:建立不同来源甘草药材的模式识别分类方法。方法:通过 HPLC 快速获得19个不同来源甘草药材样品的色谱指纹图谱,色谱条件固定相为 Kromasil KR100-5 C_(18)(150mm×4.6mm),流动相为乙腈-0.05%三氟乙酸溶液,梯度洗脱为乙腈20%(0min)→40%(5min)→50%(10min),流速为0.8mL·min~(-1),检测波长为254nm,从每个色谱指纹罔中提取出325个特征变量,采用聚类分析对甘草药材样品进行相似性评价,并应用 PLS 方法建立起不同植物种、不同种植方式甘草的2个分类回归模型。结果:采用分类模型对不同植物种、不同种植方式甘草进行判别,2个分类回归模型的分类准确率均为100%。结论:此方法可用于不同来源甘草药材的分类研究,本文以 HPLC 指纹图谱结合化学计量学知识,为不同中药样品的质量评价提供了一种分类方法。Objective:To establish a method for pattern recognition classification on Radix et Rhizoma Glycyrrhizae of different sources.Methods:HPLC system was applied to obtain the chromatograms of the 19 Radix et Rhizoma Glycyrrhizae samples.The Kromasil KR100-5 C_(18)(150 mm×4.6 mm)column was used.A mixture of acetonitrile 0.05% trifluoroacetic acid solution was used as the mobile phase with a flow rate of 0.8 mL·min~(-1) and the gradi- ent mode was acetonitrile 20%(0 rain)→40%(5 min)→50%(10 min).The detection wavelength was 254 nm. The 325 characteristic variables were obtained from each chromatogram.The clustering analysis was applied to eval- uate the similarity of the chromatograms.Then partial least-squares regression method was applied to build the pre- diction models of classification which were used to distinguish Radix et Rhizoma Glycyrrhizae of different species and cultivation modes.Results:The classification accuracy of the two prediction models of classification was 100% for Radix et Rhizoma Glycyrrhizae of different sources.Conclusion:This method is practicable in the pattern recog- nition classification on Radix et Rhizoma Glycyrrhizae of different sources.The developed technique could be further applied to the classification of different traditional Chinese medicine(TCM).福建省自然科学基金(C021006);; 福建 GAP 关键技术研究(2002Y024

A COMPUTER PROGRAM of DATA A CQUISITION FOR MULTICHANNEL INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION SPECTROMETER

介绍了用于多道电感耦合等离子体原子发射光谱仪数据采集程序，给出了程序的基本框架。该程序用MICrOSOfTVISuAlbASIC50编写，界面友好，操作方便，并可根据需要进行功能扩充。A computer program of data acquisition is developed for multichannel inductively couple plasma atomic emission spectrometer.The core of the program presented in this paper is written in Microsoft Visual Basic 5 0, which is easy to use and easy to extend.国家自然科学基

Classification Model of HCC Patients and Healthy People Established from Mass Spectrometry Data

通过对质谱数据处理和分析,建立肝细胞癌(HCC)病人与健康人的分类模型,可以用来判别样本是否来源于肝癌病人。运用表面加强激光解析电离-飞行时间质谱(SELDI-TOF-MS)获取肝癌病人和健康人血清蛋白指纹图谱数据,并运用偏最小二乘(PLS)变量筛选法建立分类模型,最终得到分类模型的交叉检验相关系数达0.96以上,判别准确率大大提高。同时对模型进行分析,找出对肝癌病人和健康人的差异有重要影响的因素或变量。这些变量为30个质荷比区间内特定蛋白的峰强度值,反映这些质荷比区间内蛋白量的增加或减少与肝癌的形成有密切关系,可作为重要的生物标志物进一步加以研究。并且采用所得模型的拟合值等一些信息做分类图,能较好地表达回归模型的分类效果。Classification models of hepatocellular carcinoma(HCC) patients and healthy people were built from mass spectrometry data,which could be used for the detection of HCC.Surface-enhanced laser desorption and ionization time-of-flight mass spectrometry(SELDI-TOF-MS) technique was applied to get the data of serum protein from HCC patients and healthy people.Then PLS variable selection method was used to deal with the data and to establish the classification model.The cross validation relativity coefficients of the model cames to over 0.96.Furthermore the important factors or variables that discriminated HCC patients and healthy people were found by analyzing the model.The 30 variables were several peak intensities of protein from some m/z sections,which could express the up-regulation or down-regulation of protein in the sections.As potential biomarkers,the proteins may be closely related to the formation of HCC,which can be deeply studied.The classification figures constructed by the fitting value of the model in the article are clear and intuitive,and can express the discrimination effect of the model well.福建省自然科学基金(批准号:2007J0290)资

正交递归选择法及其在转炉炉龄研究中的应用

本文提出了一种新的变量筛选法—正交递归选择法,该法可以得到预报能力较强的模型,即PRESS(预报残差平方和)值较低的模型。转炉炉龄问题作为研究实例,并与逐步回归正向选择法及偏最小二乘回归法进行了比较

聚二甲基硅烷质量的评估方法

聚碳硅烷(PCS)是生产碳化硅陶瓷和碳化硅纤维的先驱体,由聚二甲基硅烷(PDMS)经高温热解重组获得。文中采用在线热裂解-气相色谱-质谱对PDMS热裂解碎片进行分离和结构分析。通过将不同的PDMS谱图与标准样品谱图进行对比,定量确定不同PDMS的相似度,然后根据PCS的纺丝性能评价PDMS的质量,从而建立PDMS热裂解-气相色谱-质谱图与PDMS质量等级之间的相关性,以及建立以Pearson相关系数为定量指标、评估PDMS质量等级的方法

Classification Study by Pattern Recognition on the Relationship Between the Trace Elements in Human Hair and Sex

通过对人发样品中22种元素含量的数据进行变量扩维及压缩筛选处理，选出了影响性别判断较显著的变量，用PlS法处理这些变量组成的数据，得到男性与女性分类清晰的二维判别图及预报模型，并根据所建立的预报模型及人发微量元素的含量判别人的性别，准确率为81%.The data of 22 trace elements concentrations in human hair samples were obtained by ICP AES and GFAAS.The variables which have significant influence on discriminating the sex are selected through the treatment of the concentration data by the variable dimension expansion and the variable selection methods.The discrimination plane figure with the good classification is obtained through the treatment of the data with selected variables by PLS method.The prediction models are built and used to distinguish the human sex according to the element concentrations data in human hair.The accuracy of the prediction is 81%.国家教育委员会留学回国人员科研启动费;福建省自然科学基

最优判别平面法改进及其在癌症诊断中的应用

采用了一种最优判别平面法的改进方法,在该法中用判别矢量P_1和P_2的共轭约条件代替原来P_1和P_2的正交约条件,从而使投影矢量t_1与t_2正交,住模式判别分析中可得到更好的分类效果,用该方法对癌证论断问题进行了分析、结果表明有较好的分类效果

Software development of multielement transient signal acquisition and processing with multi-channel ICP-AES

A software for multi-channel ICP-AES multi-element transient signal acquisition and processing were developed in this paper. It has been successfully applied to signal acquisition and processing in many transient introduction techniques on-line hyphenated with multi-channel ICP-AES