In the past few years, genome-wide association study （GWAS） has made great successes in identifying genetic susceptibility loci underlying many complex diseases and traits. The findings provide important genetic ins...In the past few years, genome-wide association study （GWAS） has made great successes in identifying genetic susceptibility loci underlying many complex diseases and traits. The findings provide important genetic insights into understanding pathogenesis of diseases. In this paper, we present an overview of widely used approaches and strategies for analysis of GWAS, offered a general consideration to deal with GWAS data. The issues regarding data quality control, population structure, association analysis, multiple comparison and visual presentation of GWAS results are discussed; other advanced topics including the issue of missing heritability, meta-analysis, setbased association analysis, copy number variation analysis and GWAS cohort analysis are also briefly introduced.展开更多
Multivariate statistical process monitoring and control (MSPM& C) methods for chemical process monitoring with statistical projection techniques such as principal component analysis (PCA) and partial least squares...Multivariate statistical process monitoring and control (MSPM& C) methods for chemical process monitoring with statistical projection techniques such as principal component analysis (PCA) and partial least squares (PLS) are surveyed in this paper,The four-step procedure of performing MSPM &C for chemical process ,modeling of processes ,detecting abnormal events or faults,identifying the variable(s) responible for the faults and diagnosing the source cause for the abnormal behavior,is analyzed,Several main research directions of MSPM&C reported in the literature are discussed,such as multi-way principal component analysis (MPCA) for batch process ,statistical monitoring and control for nonlinear process,dynamic PCA and dynamic PLS,and on -line quality control by infer-ential models,Industrial applications of MSPM&C to several typical chemical processes ,such as chemical reactor,distillation column,polymeriztion process ,petroleum refinery units,are summarized,Finally,some concluding remarks and future considerations are made.展开更多
In the present article we study the production of grape molasses. Data drawn from a specified biolaboratory, are properly analyzed in order to detect factors that affect significantly the Brix value and the volatile a...In the present article we study the production of grape molasses. Data drawn from a specified biolaboratory, are properly analyzed in order to detect factors that affect significantly the Brix value and the volatile acidity of the final product. The ground that is used for planting and a variety of grapes have been taken into account. Off-line statistical quality control techniques have been employed and the outcomes are displayed and discussed in detail.展开更多
A variety of factors affect air quality, making it a difficult issue. The level of clean air in a certain area is referred to as air quality. It is challenging for conventional approaches to correctly discover aberran...A variety of factors affect air quality, making it a difficult issue. The level of clean air in a certain area is referred to as air quality. It is challenging for conventional approaches to correctly discover aberrant values or outliers due to the significant fluctuation of this sort of data, which is influenced by Climate change and the environment. With accelerating industrial expansion and rising population density in Kolkata City, air pollution is continuously rising. This study involves two phases, in the first phase imputation of missing values and second detection of outliers using Statistical Process Control (SPC), and Functional Data Analysis (FDA), studies to achieve the efficacy of the outlier identification methodology proposed with working days and Nonworking days of the variables NO<sub>2</sub>, SO<sub>2</sub>, and O<sub>3</sub>, which were used for a year in a row in Kolkata, India. The results show how the functional data approach outshines traditional outlier detection methods. The outcomes show that functional data analysis vibrates more than the other two approaches after imputation, and the suggested outlier detector is absolutely appropriate for the precise detection of outliers in highly variable data.展开更多
介绍了多变量统计过程控制(multivariate statistical process control,MSPC)的基本概念和有关背景。描述了MSPC实施的基本流程以及常用统计量与控制图。强调了MSPC在药品生产过程中的重要作用,特别是中药领域,为药品生产过程质量控制...介绍了多变量统计过程控制(multivariate statistical process control,MSPC)的基本概念和有关背景。描述了MSPC实施的基本流程以及常用统计量与控制图。强调了MSPC在药品生产过程中的重要作用,特别是中药领域,为药品生产过程质量控制方法的选择提供参考。总结了MSPC的优势和不足,并展望了MSPC在药品生产和质量控制方面的发展趋势。展开更多
基金supported by National Natural Science Foundation of China(No.81072389,81373102,81473070 and 81402765)Research Found for the Doctoral Program of Higher Education of China(No.20113234110002)+4 种基金Key Grant of Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.10KJA330034)College Philosophy and Social Science Foundation from Education Department of Jiangsu Province of China(No.2013SJB790059,2013SJD790032)Research Foundation from Xuzhou Medical College(No.2012KJ02)Research and Innovation Project for College Graduates of Jiangsu Province of China(No.CXLX13_574)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘In the past few years, genome-wide association study （GWAS） has made great successes in identifying genetic susceptibility loci underlying many complex diseases and traits. The findings provide important genetic insights into understanding pathogenesis of diseases. In this paper, we present an overview of widely used approaches and strategies for analysis of GWAS, offered a general consideration to deal with GWAS data. The issues regarding data quality control, population structure, association analysis, multiple comparison and visual presentation of GWAS results are discussed; other advanced topics including the issue of missing heritability, meta-analysis, setbased association analysis, copy number variation analysis and GWAS cohort analysis are also briefly introduced.
基金Supported by the National High-Tech Development Program of China(No.863-511-920-011,2001AA411230).
文摘Multivariate statistical process monitoring and control (MSPM& C) methods for chemical process monitoring with statistical projection techniques such as principal component analysis (PCA) and partial least squares (PLS) are surveyed in this paper,The four-step procedure of performing MSPM &C for chemical process ,modeling of processes ,detecting abnormal events or faults,identifying the variable(s) responible for the faults and diagnosing the source cause for the abnormal behavior,is analyzed,Several main research directions of MSPM&C reported in the literature are discussed,such as multi-way principal component analysis (MPCA) for batch process ,statistical monitoring and control for nonlinear process,dynamic PCA and dynamic PLS,and on -line quality control by infer-ential models,Industrial applications of MSPM&C to several typical chemical processes ,such as chemical reactor,distillation column,polymeriztion process ,petroleum refinery units,are summarized,Finally,some concluding remarks and future considerations are made.
文摘In the present article we study the production of grape molasses. Data drawn from a specified biolaboratory, are properly analyzed in order to detect factors that affect significantly the Brix value and the volatile acidity of the final product. The ground that is used for planting and a variety of grapes have been taken into account. Off-line statistical quality control techniques have been employed and the outcomes are displayed and discussed in detail.
文摘A variety of factors affect air quality, making it a difficult issue. The level of clean air in a certain area is referred to as air quality. It is challenging for conventional approaches to correctly discover aberrant values or outliers due to the significant fluctuation of this sort of data, which is influenced by Climate change and the environment. With accelerating industrial expansion and rising population density in Kolkata City, air pollution is continuously rising. This study involves two phases, in the first phase imputation of missing values and second detection of outliers using Statistical Process Control (SPC), and Functional Data Analysis (FDA), studies to achieve the efficacy of the outlier identification methodology proposed with working days and Nonworking days of the variables NO<sub>2</sub>, SO<sub>2</sub>, and O<sub>3</sub>, which were used for a year in a row in Kolkata, India. The results show how the functional data approach outshines traditional outlier detection methods. The outcomes show that functional data analysis vibrates more than the other two approaches after imputation, and the suggested outlier detector is absolutely appropriate for the precise detection of outliers in highly variable data.
文摘介绍了多变量统计过程控制(multivariate statistical process control,MSPC)的基本概念和有关背景。描述了MSPC实施的基本流程以及常用统计量与控制图。强调了MSPC在药品生产过程中的重要作用,特别是中药领域,为药品生产过程质量控制方法的选择提供参考。总结了MSPC的优势和不足,并展望了MSPC在药品生产和质量控制方面的发展趋势。
