• Journal of the Korean Chemical Society
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• v.46 no.4
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• pp.309-317
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• 2002

A spectrofluorimetric method for the simultaneous determination of amino acids (tryptophan and tyrosine) based on the application of multivariate calibration method such as principal component regression and partial least squares (PLS) to luminescence measurements has been studied. Emission spectra of synthetic mixtures of two amino acids were obtained at excitation wavelength of 257 ㎚. The calibration model in PCR and PLS was obtained from the spectral data in the range of 280-500 ㎚ for each standard of a calibration set of 32 standards, each containing different amounts of two amino acids. The relative standard error of prediction ($RSEP_a$) was obtained to assess the model goodness in quantifying each analyte in a validation set. The overall relative standard error of prediction ($RSEP_m$) for the mixture obtained from the results of a validation set, formed by 6 independent mixtures was also used to validate the present method.

• Korean Chemical Engineering Research
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• v.45 no.6
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• pp.596-603
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• 2007

Rapid or on-line coal analysis is of great interest in coal industry as it would allow efficient plant operation. Multivariate analysis has been applied to near-infrared(NIR) spectra coal for investigating the relationship between coal properties(%) (moisture, ash, volatile matter, fixed carbon, carbon, hydrogen, nitrogen, oxygen, sulfur), heating value(kcal/kg) and corresponding near-infrared spectral data. The quantitative analysis was carried out by applying PLS(partial least squares regression) to determine a methodology able to establish a relationship between coal properties and NIR spectral data being applied mathematical pre-treatments for minimizing the physical features of the samples. As a results of the analysis, this technique is able to classify the species of coals and to predict the all coal properties except ash, nitrogen and sulfur. The efficient operation of coal fired power plant is expected owing to real time on-line coal analysis of moisture and heating value.

• Journal of the Korean Chemical Society
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• v.47 no.1
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• pp.19-25
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• 2003

A spectrophotometric method for the simultaneous determination of anionic and nonionic surfactant based on the application of multivariate calibration method such as principal component regression(PCR) and partial least squares(PLS) has been studied. The calibration models in PCR and PLS were obtained from the spectral data in the range of 400~700 nm for each standard of a calibration set of 26 standards, each containing different amounts of two surfactants. The relative standard error of prediction(RSEP$_{\alpha}$) was obtained to assess the model goodness in quantifying each analyte in a 5 validation samples which containing different amounts of two surfactants.

• Food Science and Biotechnology
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• v.16 no.3
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• pp.477-481
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• 2007

Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression were used to predict the amylose content of polished rice. Spectral reflectance data in a wavelength range of 1,000 to 2,500 nm were obtained with a commercial spectrophotometer for 60 different varieties of Korean rice. For a comparison of this spectroscopic method to a standard chemical analysis, the amylose contents of the tested rice samples were determined by the iodine-blue colorimetric method. The highest correlation for the rice amylose ($R^2=0.94$, standard error of prediction=0.20% amylose content) was obtained when using the FT-NIR spectrum data pre-treated with normalization, the first derivative, smoothing, and scattering correction.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6347-6350
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• 2013

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.430-437
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• 2008

Optical diffuse reflectance sensing in visible and near-infrared wavelength ranges is one approach to rapidly quantify soil properties for site-specific management. The objectives of this study were to investigate effects of preprocessing of reflectance data and determine the accuracy of the reflectance approach for estimating physical and chemical properties of selected Missouri and Illinois, USA surface soils encompassing a wide range of soil types and textures. Diffuse reflectance spectra of air-dried, sieved samples were obtained in the laboratory. Calibrations relating spectra to soil properties determined by standard methods were developed using partial least squares (PLS) regression. The best data preprocessing, consisting of absorbance transformation and mean centering, reduced estimation errors by up to 20% compared to raw reflectance data. Good estimates ($R^2=0.83$ to 0.92) were obtained using spectral data for soil texture fractions, organic matter, and CEC. Estimates of pH, P, and K were not good ($R^2$ < 0.7), and other approaches to estimating these soil chemical properties should be investigated. Overall, the ability of diffuse reflectance spectroscopy to accurately estimate multiple soil properties across a wide range of soils makes it a good candidate technology for providing at least a portion of the data needed in site-specific management of agriculture.

• YAKHAK HOEJI
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• v.49 no.2
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• pp.115-121
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• 2005

In this study, the performance of a portable NIR system and a FT NIR spectrometer were compared to determine water content of hairless mouse skin. The stratum corneum parts wer e separated from the epidermal tissues by trypsin solution. NIR diffuse reflectance spectra of hairless mouse skin were acquired using a fiber optic probe. In the near infrared, water molecules show two clear absorption bands at 1450 nm from first overtone of O-H stretching and 1940 nm from the combination involving O-H stretching and O-H deformation. It was found that the variations of O-H absorption band according to water content. Partial least squares regression (PLSR) was applied to develop a calibration model. The PLS model showed a good correlation between NIR predicted value and the absolute water content of separated hairless mouse skin, in vitro. For both the portable and the FT NIR spectrometer, These studies showed the possibility of a rapid and nondestructive skin moisture measurement using NIR spectroscopy. The portable NIR spectrometer with a photodiode arrays-microsensor could be more rapidly applied for the determination of water content with comparable accuracy with the performance of a FT spectrometer .

• Journal of Environmental Science International
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• v.29 no.5
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• pp.445-455
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• 2020

Fine dust is one of the most critical environmental issues in Korea, and the government recognizes the need to establish customized reduction policies based on regional characteristics. Several studies on air pollutants investigate whether factories affect the distribution of fine dust in a particular region. However, understanding the impact of the entire industry sector requires further investigation. This study identifies the impacts of industrial characteristics on fine dust levels of 141 municipalities across Korea in 2016. A total of 23 variables were used, of which 12 referred to industries and 11 to general characteristics of each city. Due to the high correlation between independent variables, partial least squares (PLS) regression models were used. The analysis identified 14 significant variables for PM10 and 13 for PM2.5. Therefore, the results suggest that local industrial characteristics can significantly influence fine dust levels and provide suggestions for establishing customized reduction policies based on local characteristics.

• Bulletin of the Korean Chemical Society
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• v.19 no.11
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• pp.1189-1193
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• 1998

The determination of total paraffin, naphthene, and aromatic (PNA) contents in naphtha samples, which were directly obtained from actual refining process, has been studied using near-infrared (NIR) spectroscopy. Each of the total PNA concentrations in naphtha has been successfully analyzed using NIR spectroscopy. Partial least squares (PLS) regression method has been utilized to quantify the total PNA contents in naphtha from the NIR spectral bands. The NIR calibration results showed an excellent correlation with those of conventional gas chromatography (GC). Due to its rapidity and accuracy, NIR spectroscopy is appeared as a new analytical technique which can be substituted for the conventional GC method for the quantitative analysis of petrochemical products including naphtha.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.253-263
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• 2018

Internet addiction in adolescents is an important social issue. In this study, sparse partial least-squares regression (SPLS) was applied to internet addiction data in Korean adolescent samples. The internet addiction score and various clinical and psychopathological features were collected and analyzed from self-reported questionnaires. We considered three PLS methods and compared the performance in terms of prediction and sparsity. We found that the SPLS method with the hierarchical likelihood penalty was the best; in addition, two aggression features, AQ and BSAS, are important to discriminate and explain latent features of the SPLS model.