Statistical approaches in literature: An application of principal component analysis and factor analysis to analyze the different arrangements about the Quran’s Suras

2020 ◽  
Author(s):  
Yanwen Wang ◽  
Javad Garjami ◽  
Milena Tsvetkova ◽  
Nguyen Huu Hau ◽  
Kim-Hung Pho
Keyword(s):  
Data Mining ◽  
Principal Component Analysis ◽  
Factor Analysis ◽  
Data Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Holy Quran ◽  
The Holy Quran ◽  
Statistical Approaches

Abstract Data mining, statistics, and data analysis are popular techniques to study datasets and extract knowledge from them. In this article, principal component analysis and factor analysis were applied to cluster thirteen different given arrangements about the Suras of the Holy Quran. The results showed that these thirteen arrangements can be categorized in two parts such that the first part includes Blachère, Davood, Grimm, Nöldeke, Bazargan, E’temad-al-Saltane and Muir, and the second part includes Ebn Nadim, Jaber, Ebn Abbas, Hazrat Ali, Khazan, and Al-Azhar.

Data Mining in Analysis of Biomechanical Signals

2009 ◽  
Vol 147-149 ◽  
pp. 588-593 ◽  
Author(s):  
Marcin Derlatka ◽  
Jolanta Pauk
Keyword(s):  
Data Mining ◽  
Principal Component Analysis ◽  
Cerebral Palsy ◽  
Spina Bifida ◽  
Decision Tree ◽  
Principal Component ◽  
Data Preprocessing ◽  
Component Analysis ◽  
Kernel Principal Component Analysis

In the paper the procedure of processing biomechanical data has been proposed. It consists of selecting proper noiseless data, preprocessing data by means of model’s identification and Kernel Principal Component Analysis and next classification using decision tree. The obtained results of classification into groups (normal and two selected pathology of gait: Spina Bifida and Cerebral Palsy) were very good.

Reaction Monitoring in Explorative Organic Synthesis Using Fiber-Optical NIR Spectroscopy and Principal Component Analysis

1996 ◽  
Vol 50 (12) ◽  
pp. 1541-1544 ◽  
Author(s):  
Hans-René Bjørsvik
Keyword(s):  
Principal Component Analysis ◽  
Data Analysis ◽  
Latent Variables ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Quantitative Information ◽  
Chemistry Laboratory ◽  
Reaction Profile

A method of combining spectroscopy and multivariate data analysis for obtaining quantitative information on how a reaction proceeds is presented. The method is an approach for the explorative synthetic organic laboratory rather than the analytical chemistry laboratory. The method implements near-infrared spectroscopy with an optical fiber transreflectance probe as instrumentation. The data analysis consists of decomposition of the spectral data, which are recorded during the course of a reaction by using principal component analysis to obtain latent variables, scores, and loading. From the scores and the corresponding reaction time, it is possible to obtain a reaction profile. This reaction profile can easily be recalculated to obtain the concentration profile over time. This calculation is based on only two quantitative measurements, which can be (1) measurement from the work-up of the reaction or (2) chromatographic analysis from two withdrawn samples during the reaction. The method is applied to the synthesis of 3-amino-propan-1,2-diol.

Sign in / Sign up

Export Citation Format

Share Document