Three-way principal component analysis applied to noodles sensory data analysis

2011 ◽  
Vol 106 (1) ◽  
pp. 125-130 ◽  
Author(s):  
Christophe B.Y. Cordella ◽  
Riccardo Leardi ◽  
Douglas N. Rutledge
1996 ◽  
Vol 50 (12) ◽  
pp. 1541-1544 ◽  
Author(s):  
Hans-René Bjørsvik

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measurements, which can be (1) measurement from the work-up of the reaction or (2) chromatographic analysis from two withdrawn samples during the reaction.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.


2016 ◽  
Vol 4 (2) ◽  
pp. 139-144 ◽  
Author(s):  
Miroslav Vasilev ◽  
Ira Taneva ◽  
Margarita Velikova ◽  
Ralitsa Mihova

Author(s):  
Yanwen Wang ◽  
Javad Garjami ◽  
Milena Tsvetkova ◽  
Nguyen Huu Hau ◽  
Kim-Hung Pho

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.


2016 ◽  
Author(s):  
Sven-Oliver Borchert

Die vorliegende Arbeit befasst sich mit Aspekten einer modernen Bioverfahrenstechnik am ­Beispiel von Prozessen zur Herstellung rekombinanter potentieller Malariavakzine. Dabei ­wurden zwei quasi-kontinuierliche Prozesse aus herkömmlichen Batch-Unit Operationen auf­gebaut, in denen die Anwendung von Process Analytical Technology im Vordergrund steht. Das Hauptaugenmerk dieser Arbeit lag dabei auf einer Implementierung der Multivariate Data ­Analysis zum Monitoring und zur Evaluierung des zyklischen Prozessablaufes und seiner Reproduzierbarkeit. Im Bereich der Principal Component Analysis wurde die Methode der Prozessüberwachung mit dem Golden Batch-Tunnel angewendet. Mit dem Golden Batch-Ansatz ­wurden Methoden zur Prozessprädiktion implementiert und mit einer Model Predictive Multi­variate Control auch zur Steuerung von realen Prozesses erprobt. Darüber hinaus wurde die MVDA zur Prädiktion von Medienkomponenten sowie deren zellspezifische Reaktionsraten aus klassischen Onli...


2012 ◽  
Vol 118 ◽  
pp. 51-61 ◽  
Author(s):  
Lingli Deng ◽  
Kian-Kai Cheng ◽  
Jiyang Dong ◽  
Julian L. Griffin ◽  
Zhong Chen

2018 ◽  
Vol 72 (1) ◽  
pp. 17-29
Author(s):  
Erika Fecková Škrabul’áková

Abstract In the present paper, we propose a heuristic for identifying the key supplier of a company. In order to develop the supplier’s evaluation tool, we use the multicriterial data analysis. The main statistical instrument here is the principal component analysis. Using the data from all realized orders of a chosen company in Slovakia from the year 2017, we identify its key supplier. Hence, this study helps to close the gap between theoretical work on principal component analysis and actual practice. The importance of the present work underlines the fact that the company is planning to sign an exclusive contract with the recommended supplier.


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