• 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.20 no.2
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• pp.159-162
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• 1999

Three different chemical compositions of total paraffin, total naphthene, total aromatic content in naphtha have been successfully analyzed using FT-Raman spectroscopy. Partial least squares (PLS) regression has been utilized to develop calibration models for each composition from Raman spectral bands. The PLS calibration results showed Blood correlation with those of gas chromatography (GC). Using PLS regression, the spectral information related to each composition has been successfully extracted from highly overlapped Raman spectra of naphtha.

• Food Science and Biotechnology
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• v.18 no.1
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• pp.60-65
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• 2009

Near infrared reflectance spectroscopy (NIRS) was used as a rapid and non-destructive method to determine the protein content in intact and ground seeds of pea (Pisum sativum L.) germplasms grown in Korea. A total of 115 samples were scanned in the reflectance mode of a scanning monochromator at intact seed and flour condition, and the reference values for the protein content was measured by auto-Kjeldahl system. In the developed ground and intact NIRS equations for analysis of protein, the most accurate equation were obtained at 2, 8, 6, 1 math treatment conditions with standard normal variate and detrend scatter correction method and entire spectrum (400-2,500 nm) by using modified partial least squares regression (n=78). External validation (n=34) of these NIRS equations showed significant correlation between reference values and NIRS estimated values based on the standard error of prediction (SEP), $R^2$, and the ratio of standard deviation of reference data to SEP. Therefore, these ground and intact NIRS equations can be applicable and reliable for determination of protein content in pea seeds, and non-destructive NIRS method could be used as a mass analysis technique for selection of high protein pea in breeding program and for quality control in food industry.

• 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.

• 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 Biosystems Engineering
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• v.38 no.1
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• pp.48-54
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• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.

• 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.

• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.805-836
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• 2017

China has become the group of two (G2) in almost fields including the scientific technology following the economic growth and joining the WTO in 2001. The main reason is that the government had strong intention for the industrialization of the scientific technology and connected the scientific technology and the economy. Typically, for analyzing the cause of the meteoric rise of China, the competitiveness of the scientific technology was analyzed by the entire score of the nation. However, in the case of China, there are differences in the pattern of the development between the eastern, central, and western province. Also, the industrialization and the competitiveness of the scientific technology are difference because each province established the decentralization of power. Therefore, it is more meaningful to analyze the main factors of Chinese economic growth on a province unit. In this study, therefore, we analyzed the competitive of R&D in China by 124 indexes in 31 areas. The data was analyzed by Partial least squares regression analysis. In conclusion, the scale of the area and the ability of R&D of the company are very important factors for total amount of production in the area. And the journals, patents, the transfer of technical know-how and the investment of R&D are main factors of the amount of export on the high-tech product. According to these results, the factors which make the difference in the industrialization and the competitiveness of the scientific technology in China were analyzed. Finally, it will be helpful to establish the policy for the development of the industrialization and the scientific technology in Korea.

• Analytical Science and Technology
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• v.16 no.2
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• pp.95-101
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• 2003

In this study, water content in the mixture of methanol and ethanol was nondestructively measured by near infrared (NIR) spectroscopy. Two types of NIR instruments, portable NIR system with a photo-diode array and scanning type NIR spectrometer were used and the calibration results were compared. Partial least squares regression (PLSR) was applied for the calibration and validation for the quantitative analysis. The calibration results from both instruments showed good correlation with actual values. The calibration with the use of PLS model predicted water concentration with a standard error of prediction (SEP) of 0.10% and 0.12% for photo diode array and scanning type, respectively. During 6 days, routine analyses for 3%, 5% and 7% water in ethanol solution with 2% methanol were performed to validate the robustness of the developed calibration model. The routine analyses showed good results with coefficient of variation (CV) of within 3% for both types of NIR spectrometers. This study showed that the rapid determination of water in the mixture of methanol and ethanol was successfully performed by NIR spectroscopy and the performance of the portable NIR system with a photo diode array detector was comparable to that of the scanning type NIR spectrometer.

• Korean Journal of Medicinal Crop Science
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• v.10 no.5
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• pp.340-343
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• 2002

Near infrared reflectance spectroscopy (NIRS) has become widely accepted for rapid quantitative analysis of components in some crops. Our object was to determine icariin contents in whole plant of Epimedium koreanum by using an NIRS system. Total 150 plant samples previously analyzed by HPLC were scanned by NIRS and 68 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed and a coefficient of determination in calibration and validation sets were 0.95 and 0.82, respectively. A comparison between NIRS estimation and HPLC value was performed with the remaining samples not included in the calibration and validation sets. Most of samples also showed a positive correlation like a validation set. Our results demonstrate that this developed NIRS equation can be practically used as a mass screening method for rapid quantification of icarin contents in Epimedium koreanum N.