Univariate Patterns in the Design of Multivariate Analysis Techniques for Geochemical Data Evaluation

1988 ◽  
pp. 113-130 ◽  
Author(s):  
Clifford R. Stanley ◽  
Alastair J. Sinclair
Keyword(s):  
Multivariate Analysis ◽  
Data Evaluation ◽  
Geochemical Data ◽  
Analysis Techniques

BUSINESS FAILURE PREDICTION USING ROUGH SETS: A COMPARISON WITH MULTIVARIATE ANALYSIS TECHNIQUES

1999 ◽  
Vol 04 (01) ◽  
Author(s):  
C. Zopounidis ◽  
M. Doumpos ◽  
R. Slowinski ◽  
R. Susmaga ◽  
A. I. Dimitras
Keyword(s):  
Multivariate Analysis ◽  
Rough Sets ◽  
Failure Prediction ◽  
Business Failure ◽  
Analysis Techniques

Multivariate Analysis of Stream Sediment Geochemical Data for Gold Exploration in Delijan, Iran

2018 ◽  
Vol 5 (2) ◽  
pp. 325-334
Author(s):  
Farid Javadnejad ◽  
◽  
Javad EskandariShahraki ◽  
Sanaz Khoubani ◽  
Elham Kalantari ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Stream Sediment ◽  
Geochemical Data ◽  
Gold Exploration

scholarly journals Rancidity Estimation of Perilla Seed Oil by Using Near-Infrared Spectroscopy and Multivariate Analysis Techniques

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Suk-Ju Hong ◽  
Shin-Joung Rho ◽  
Ah-Yeong Lee ◽  
Heesoo Park ◽  
Jinshi Cui ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Seed Oil ◽  
Prediction Models ◽  
Oxidation Process ◽  
Analysis Techniques ◽  
Peroxide Values ◽  
Perilla Seed

Near-infrared spectroscopy and multivariate analysis techniques were employed to nondestructively evaluate the rancidity of perilla seed oil by developing prediction models for the acid and peroxide values. The acid, peroxide value, and transmittance spectra of perilla seed oil stored in two different environments for 96 and 144 h were obtained and used to develop prediction models for different storage conditions and time periods. Preprocessing methods were applied to the transmittance spectra of perilla seed oil, and multivariate analysis techniques, such as principal component regression (PCR), partial least squares regression (PLSR), and artificial neural network (ANN) modeling, were employed to develop the models. Titration analysis shows that the free fatty acids in an oil oxidation process were more affected by relative humidity than temperature, whereas peroxides in an oil oxidation process were more significantly affected by temperature than relative humidity for the two different environments in this study. Also, the prediction results of ANN models for both acid and peroxide values were the highest among the developed models. These results suggest that the proposed near-infrared spectroscopy technique with multivariate analysis can be used for the nondestructive evaluation of the rancidity of perilla seed oil, especially the acid and peroxide values.

Acoustic Feature Analysis for Hypernasality Detection in Children

2008 ◽  
pp. 16-22
Author(s):  
Genaro Daza ◽  
Luis Gonzalo Sánchez ◽  
Franklin A. Sepúlveda ◽  
Castellanos D. Germán
Keyword(s):  
Feature Selection ◽  
Multivariate Analysis ◽  
Latent Variable ◽  
Search Algorithms ◽  
Feature Analysis ◽  
Automatic Identification ◽  
Acoustic Features ◽  
Acoustic Feature ◽  
Analysis Techniques ◽  
Heuristic Search Algorithms

The present work analyzes the statistical effectiveness of different acoustic features in the automatic identification of hypernasality. Acoustic features reflect part of information contained in perceptual analysis; in part, due to their estimation is derived directly or indirectly from the vocal cords behavior. Consequently, it is convenient to apply multivariate analysis techniques in determining the effectiveness of voice features. The effectiveness is studied by using multivariate analysis techniques that are meant for feature extraction and feature selection, as well (latent variable models, heuristic search algorithms).

Multivariate analysis techniques applied for the performance measurement of Federal University Hospitals of Brazil

2018 ◽  
Vol 126 ◽  
pp. 16-29 ◽  
Author(s):  
Maria Gabriela Mendonça Peixoto ◽  
Marcel Andreotti Musetti ◽  
Maria Cristina Angélico Mendonça
Keyword(s):  
Multivariate Analysis ◽  
Performance Measurement ◽  
University Hospitals ◽  
Analysis Techniques

Confirmation of Sources of Cotton Gin Noise by Multivariate Analysis Techniques

1982 ◽  
Vol 25 (4) ◽  
pp. 1050-1056 ◽  
Author(s):  
Weldon Laird ◽  
Roy V. Baker
Keyword(s):  
Multivariate Analysis ◽  
Analysis Techniques ◽  
Cotton Gin

scholarly journals Digital gap of the colombian tourism sector

DYNA ◽  
2020 ◽  
Vol 87 (213) ◽  
pp. 173-177
Author(s):  
Oscar José Ospino Ayala ◽  
Alexandra Barrios Sandoval ◽  
Ramon Antonio Matos Mareño
Keyword(s):  
Multivariate Analysis ◽  
Current Situation ◽  
Factorial Analysis ◽  
Objective Knowledge ◽  
Analysis Techniques ◽  
Annual Survey ◽  
Tourism Sector ◽  
Information And Communication ◽  
Digital Gap ◽  
Main Components

The purpose of this research is to know the current situation of digitization that exists in the Colombian tourism sector. For this, the data of the Annual Survey of Service-2018 were used, to which the multivariate analysis techniques of categorical main components and factorial analysis were applied, in the construction of an index that measures the digitization from the Technologies of the Information and communication. With the results of this application it was demonstrated that the techniques of multivariate analysis guarantee objective knowledge that allows the planning and implementation of strategies to face digital changes and generate innovation.

scholarly journals ATR-FTIR spectroscopy coupled with multivariate analysis techniques for the identification of DENV-3 in different concentrations in blood and serum: a new approach

RSC Advances ◽  
2017 ◽  
Vol 7 (41) ◽  
pp. 25640-25649 ◽  
Author(s):  
Marfran C. D. Santos ◽  
Yasmin M. Nascimento ◽  
Josélio M. G. Araújo ◽  
Kássio M. G. Lima
Keyword(s):  
Multivariate Analysis ◽  
Viral Load ◽  
Ftir Spectroscopy ◽  
Virus Infections ◽  
New Approach ◽  
Analysis Techniques

In most cases of virus infections the viral load is directly related to the intensity of the disease.

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