• Korean Chemical Engineering Research
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• v.54 no.5
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• pp.621-629
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• 2016

Recently, the researches on quantitative structure activity relationship (QSAR) for describing toxicities or activities of chemicals based on chemical structural characteristics have been widely carried out in order to estimate the toxicity of chemicals in multiuse facilities. Because the toxicity of chemicals are explained by various kinds of molecular descriptors, an important step for QSAR model development is how to select significant molecular descriptors. This research proposes a statistical selection of significant molecular descriptors and a new QSAR model based on partial least square (PLS). The proposed QSAR model is applied to estimate the logarithm of partition coefficients (log P) of 130 polychlorinated biphenyls (PCBs) and lethal concentration ($LC_{50}$) of 14 PCBs, where the prediction accuracies of the proposed QSAR model are compared to a conventional QSAR model provided by OECD QSAR toolbox. For the selection of significant molecular descriptors that have high correlation with molecular descriptors and activity information of the chemicals of interest, correlation coefficient (r) and variable importance of projection (VIP) are applied and then PLS model of the selected molecular descriptors and activity information is used to predict toxicities and activity information of chemicals. In the prediction results of coefficient of regression ($R^2$) and prediction residual error sum of square (PRESS), the proposed QSAR model showed improved prediction performances of log P and $LC_{50}$ by 26% and 91% than the conventional QSAR model, respectively. The proposed QSAR method based on computational toxicology can improve the prediction performance of the toxicities and the activity information of chemicals, which can contribute to the health and environmental risk assessment of toxic chemicals.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2011.10a
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• pp.255-269
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• 2011

The purpose of study has to analyze with non destructive method for researching the tool that could be measured with the status of record written on Hanji speedily. Because the original record should be destructed for analyzing with previous method in the case of the paper record, it was to develop the tool based on non destructive method for overcoming such limit. The study was used with FT NIR (Fourier transform NIR) for analyzing the Hanji for being written and preserved. The FT NIR spectrometer that of NIR spectrometer has the better performance of precision and accuracy than dispersive NIR spectrometer was used. Also the wavelength of FT-NIR was measured with 12,500 to 4,000 $cm^{-1}$, and the integrating sphere as diffuse reflectance type was used for analyzing Hanji. The moisture and acidity (pH) of chemical factors as quality evaluated factor of Hanji was studied for the correlation of NIR spectrum. And then The NIR spectrum was pretreated for showing the coefficients of optimum correlation. MSC and First derivative of Savitzky - Golay was used as pretreated method, and the coefficients of optimum correlation were shown by PLSR(Partial least square regression). And the coefficients of optimum correlation were calculated by PLSR(Partial least square regression). The correlation coefficients of acidity had 0.92 on NIR spectra without pretreatment. Also the SEP of acidity was 0.24. And then The NIR spectra with pretreatment would have more good correlation coefficients ($R^2=0.98$) and more good SEP(=019) on acidity. Therefore the data of correlation coefficients ($R^2$) and SEP with pretreatment was shown to be superior. And NIR spectra data of first derivative had best linearity on the correlation coefficients ($R^2=0.99$) and also SEP(=0.45) was superior. Therefore the correlation coefficients and SEP of first derivative had better than those of NIR spectra of no pretreatment. As such result, it was possible to evaluate the record status of Hanji speedily with integrated sphere and NIR analyzer as non destructive method.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.304-309
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• 2006

Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

• Journal of The Korean Society of Grassland and Forage Science
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• v.34 no.3
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• pp.214-218
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• 2014

This study was conducted to assess the feasibility of near-infrared reflectance spectroscopy (NIRS) as a rapid and reliable method for the estimation of crude protein (CP) fractions in forage legume mixtures (sudangrass and pea mixture, and kidney bean and potato mixture). A total of 178 samples were collected and their spectral reflectance obtained in the range of 400~2,500 nm. Of these, 50 samples were selected for calibration and validation, and 35 samples were used for calibration of the data set, and the modified partial least square regression (MPLSR) analysis was performed. The correlation coefficient ($r^2$) and the standard error of cross-validation (SECV) of the calibration models in the CP fractions, A, B1, B2, B3, and C, were 0.94 (1.05), 0.92 (0.74), 0.96 (0.95), 0.91 (0.42), and 0.83 (0.38), respectively. Fifteen samples were used for equation validation, and the $r^2$ and the standard error of prediction (SEP) were 0.87 (1.45), 0.91 (0.49), 0.94 (1.13), 0.36 (0.96), and 0.74 (0.67), respectively. This study showed that NIRS could be an effective tool for the rapid and precise estimation of CP fractions in forage legume mixtures.

• Journal of the Korean Society of Food Culture
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• v.35 no.2
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• pp.193-200
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• 2020

This study was conducted to understand the sensory characteristics and consumer acceptance for the commercially available clear broth for noodles. Totally, eight different clear broth samples were evaluated in this study. Seven trained panelists developed and evaluated sensory characteristics in the descriptive analysis. Significant differences (p<0.05) were obtained for all 28 attributes evaluated. Descriptive data was obtained by performing multivariate analysis of variance to identify differences between samples. Principal component analysis (PCA) was performed on the mean values of descriptive attributes obtained in the descriptive analysis, and summarizes the sensory characteristics of clear broth for noodles. PCA of the clear broths revealed that the first two principal components are responsible for 80.66% variations. For sensory testing, 160 consumers were recruited, and their acceptance for each sample was assessed. Consumer data was obtained by applying partial least square-regression (PLSR) to establish the relationship between the descriptive data and the consumer acceptance data.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.789-800
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• 2020

This study aims to examine the effect of perceived usefulness (PU), perceived ease of use (PEU), trust (TR), subjective norm (SN), and attitude (AT) on customer's Intention to Adopt Internet Banking (IAIB) at Islamic banks and conventional banks before and during the Covid-19 pandemic in Indonesia. The research model is based on the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). This study involves 213 respondents for Islamic banks and 410 respondents for conventional banks from 25 provinces in Indonesia. Data was analyzed using partial least square (PLS) regression with the Structural Equation Model (SEM) method. The result of data analysis confirms several hypotheses taken from the literature. The results before the Covid-19 pandemic showed that AT and SN influence IAIB in Islamic banks. Whereas in conventional banks, AT, PU, SN, and TR influence IAIB. While during the Covid-19 pandemic, it shows that the AT, PU, IB, SN, and customer TR influence IAIB in Islamic banks and conventional banks. From the analysis, it was found that the PEU variable did not have a significant effect on the intention of customers of Islamic banks and conventional banks to use Internet banking.

• Food Science of Animal Resources
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• v.42 no.4
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• pp.672-688
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• 2022

The objective of this study was to explore the potential of front face fluorescence spectroscopy (FFFS) as rapid, non-destructive and inclusive technique along with multi-variate analysis for predicting meat adulteration. For this purpose (FFFS) was used to discriminate pure minced beef meat and adulterated minced beef meat containing (1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%) of chicken meat as an adulterant in uncooked beef meat samples. Fixed excitation (290 nm, 322 nm, and 340 nm) and fixed emission (410 nm) wavelengths were used for performing analysis. Fluorescence spectra were acquired from pure and adulterated meat samples to differentiate pure and binary mixtures of meat samples. Principle component analysis, partial least square regression and hierarchical cluster analysis were used as chemometric tools to find out the information from spectral data. These chemometric tools predict adulteration in minced beef meat up to 10% chicken meat but are not good in distinguishing adulteration level from 1% to 5%. The results of this research provide baseline for future work for generating spectral libraries using larger datasets for on-line detection of meat authenticity by using fluorescence spectroscopy.

• Journal of Animal Science and Technology
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• v.65 no.5
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• pp.1081-1093
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• 2023

This study aimed to compare meat quality traits between Berkshire and crossbreed (Landrace × Yorkshire × Duroc), and to investigate the relationship between meat quality traits and fatty acid composition. 20 Berkshire and 20 crossbreed pigs were used to compare pork loin quality and to determine the relationship between measured variables. 23 variables were measured including proximate composition, pH, drip loss and cooking loss, Warner-Bratzler shear force, and fatty acid composition. Berkshire had higher moisture content, pH, water-holding capacity, saturated fatty acids, and redness than the crossbreed pig (p < 0.05). The fat content and polyunsaturated fatty acid were low (p < 0.05) in Berkshire. Correlation analysis showed a negatively correlation between moisture and fat content, and a positively correlation between saturated fatty acid and fat content. Moreover, saturated fatty acid and polyunsaturated fatty acid were negatively correlated. As a result of factor analysis and partial least square regression, saturated fatty acid and polyunsaturated fatty acid were estimated to be the main factors affecting quality characteristics of pork. Pig breed is associated with differences in meat quality, and fatty acid composition can have an effect on meat quality parameters.

• Journal of the Korean Chemical Society
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• v.56 no.2
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• pp.236-245
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• 2012

The main mycobacterial infection in human is tuberculosis caused by Mycobacterium tuberculosis. Tuberculosis is the leading infectious cause of death in the world. Therefore there is continuing and compelling need for new and improved treatment for tuberculosis. The entire logic towards design of new compounds containing 4-hydroxy-N'-(1,3-thiazoldin- 2-yldene)benzohydrazide moiety is basically for superior antimycobacterial activity. The recent advances in QSAR and computer science have provided a systematic approach to design a structure of any compound and further, the biological activity of the compound can be predicted before synthesis. The 3D-QSAR studies for the set of 4-hydroxy-N'-(1,3-thiazoldin- 2-yldene)benzohydrazide and their derivatives were carried out by using V-life MDS (3.50). The various statistical methods such as Multiple Linear Regression (MLR), Partial Least Square Regression (PLSR), Principle Component Regression(PCR) and K nearest neighbour (kNN) were used. The kNN showed good results having cross validated $r^2$ 0.9319, $r^2$ for external test set 0.8561 and standard error of estimate 0.2195. The docking studies were carried out by using Schrodinger GLIDE module which resulted in good docking score in comparison with the standard isoniazid. The designed compounds were further subjected for synthesis and biological evaluation. Antitubercular evaluation of these compounds showed that (4.a), (4.d) and (4.g) found as potent inhibitor of H37RV.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3931-3943
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• 2014

Domestic industrial complexes have more loss competitiveness due to their deterioration length and environmental problems. Therefore, it is necessary to suggest the direction of realignment as advanced industrial estates and establish new alternative plans for improving the quality of public and environmental designs as well as reinforcing the competitive power. This study examined the design planning factors affecting the service users' satisfaction in the Seoul Digital Industrial Complex through a PLS regression model. The research result showed that 12 crucial design planning factors out of a total 31 planning factors have a more than 1.0 VIP. In addition, 8 comparatively important planning aspects that were measured between 0.9 and 1.0 were also investigated. These factors were the strategic design planning factors estimating the quantitative priority while enforcing the design improvement project and they should be considered as a useful material for strengthening the competitive power of the Seoul Digital Industrial Complex.