• 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.

• 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.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.395-409
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• 2014

Data limited, partial, or incomplete are known as an ill-posed problem. If the data with ill-posed problems are analyzed by traditional statistical methods, the results obviously are not reliable and lead to erroneous interpretations. To overcome these problems, we propose a dual generalized maximum entropy (dual GME) estimator for panel data regression models based on an unconstrained dual Lagrange multiplier method. Monte Carlo simulations for panel data regression models with exogeneity, endogeneity, or/and collinearity show that the dual GME estimator outperforms several other estimators such as using least squares and instruments even in small samples. We believe that our dual GME procedure developed for the panel data regression framework will be useful to analyze ill-posed and endogenous data sets.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.3
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• pp.211-215
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• 2004

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to determine tocopherol and tocotrienol contents in rice bran by using NIRS system. Total 80 rice bran samples previously analyzed by HPLC were scanned by NIRS and over 60 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed and coefficient of determination for tocopheyol and tocotyienol content were 0.975 and 0.984, respectively, in calibration sets. Each calibration equation was fitted to validation set that was performed with the remaining samples not included is the calibration set, which showed high positive correlation both in tocopherol and tocotrienol content file. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of tocopherol and tocotrienol contents in rice bran.

• 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.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.247-255
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• 2017

The study figured out the preference factors which should be considered for investor on decision making of unsold apartment and analyzed by comparing the difference according to the type. Then, it investigated the preference factors through the previous studies to analyze the influence factor of decision making and demonstrated the effects through the PLS (Partial Least Squares) regression. In addition, it separated the target type to tenants and construction firms and carried out the survey for comparing the preference factors of investor type. The result of analysis found out that tenants emphasis on preference factors such as the internal factor (1.141), conditional relaxation (1.114), environment factor (1.107), social factor (1.048), external factor (1.030), educational environment factor (1.010) and etc. Then, construction firms emphasis on preference factors such as the social factor (1.401), environment factor (1.251), conditional relaxation (1.133) and etc. In addition, common preferences factors are the conditional relaxation, social factor, environment factor.

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.184-193
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• 2014

Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of $R{_V}{^2}$, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ${\pm}0.487%$ wb, and 10.00, respectively. Conclusions: These results demonstrated that NIR spectroscopy and a PLSR model could be useful techniques for measuring rapidly and non-destructively the moisture content in red pepper powder.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.219-228
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• 2018

Purpose: This study evaluated the feasibility of a near-infrared spectroscopy technique for the rancidity prediction of soybean oil. Methods: A near-infrared spectroscopy technique was used to evaluate the rancidity of soybean oils which were artificially deteriorated. A soybean oil sample was collected, and the acid values were measured using titrimetric analysis. In addition, the transmission spectra of the samples were obtained for whole test periods. The prediction model for the acid value was constructed by using a partial least-squares regression (PLSR) technique and the appropriate spectrum preprocessing methods. Furthermore, optimal wavelength selection methods such as variable importance in projection (VIP) and bootstrap of beta coefficients were applied to select the most appropriate variables from the preprocessed spectra. Results: There were significantly different increases in the acid values from the sixth days onwards during the 14-day test period. In addition, it was observed that the NIR spectra that exhibited intense absorption at 1,195 nm and 1,410 nm could indicate the degradation of soybean oil. The PLSR model developed using the Savitzky-Golay $2^{nd}$ order derivative method for preprocessing exhibited the highest performance in predicting the acid value of soybean oil samples. onclusions: The study helped establish the feasibility of predicting the rancidity of the soybean oil (using its acid value) by means of a NIR spectroscopy together with optimal variable selection methods successfully. The experimental results suggested that the wavelengths of 1,150 nm and 1,450 nm, which were highly correlated with the largest absorption by the second and first overtone of the C-H, O-H stretch vibrational transition, were caused by the deterioration of soybean oil.

• 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.