• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.51-61
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• 2020

The study aims to compare whether using Earnings Response Coefficient (ERC) is better than using the new concept of Accounting Earnings Response Coefficient (AERC) in determining the earnings quality response coefficient value. Also, the study seeks to explain the effect of company characteristics and corporate governance on AERC through voluntary disclosure and information asymmetry. Research samples include 69 manufacturing companies listed on the Indonesian Stock Exchange over the period 2014-2017. The data come from annual reports, stock market prices, CSPI, EPS, stock returns and market returns. The research model is tested using the structural equation model (SEM) with partial least square (PLS). The results showed the value of the earnings response coefficient produced by AERC and ERC was different. Earnings quality resulting from AERC regression by adding CFO values better reflects the actual earnings quality. These results are consistent with the concept built from the proposition about earnings quality at AERC, that quality earnings are informative accounting earnings. The theoretical findings of this study provide an explanation that operational cash flow plays a role in evaluating earnings quality, while providing reinforcement that the ERC regression model fails to detect stock market reactions to information relevant to the aggregated values of accounting earnings.

• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.761-767
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• 2011

The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at $4^{\circ}C$ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination ($R_p{^2}$) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.

• 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.

• Advances in environmental research
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• v.1 no.4
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• pp.257-276
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• 2012

QSAR models for chlorinated alkenes were developed between $E_{HOMO}$ and their chlorine and carbon content. The aim is to provide valid QSAR model which is statistically validated for $E_{LUMO}$ prediction. Different molecular descriptors, $N_{Cl}$, $N_C$ and $E_{HOMO}$ have been used to take into account relevant information provided by molecular features and physicochemical properties. The best model were selected using Partial Least Square (PLS) and Multiple Linear Regression (MLR) led to models with satisfactory predictive ability for a data set of 15 chlorinated alkene compounds.

• Journal of Biosystems Engineering
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• v.33 no.4
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• pp.269-275
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• 2008

This study was conducted to design an impedance sensor that can measure soil water content of soils. Partial least square regression (PLSR) was applied to soil impedance data preprocessed with a smoothing method. An optimal sub-spectrum size and wavelength range were determined by comparing the coefficient of determination ($R^2$) and root mean square error (RMSE) of the PLSR models obtained using soil impedance data. various PLS analysis. Based on the PLSR analysis, it would be concluded that the optimal spectrum measurement range was $32.0{\sim}50.0\;MHz$ with the optimal sub-spectrum size of about 18.5 MHz.

• Proceedings of the KSRS Conference
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• v.2
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• pp.909-912
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• 2006

In this paper a method for remotely-sensed assessment of eutrophication was experimented. The water samples were collected for analysis of COD (chemical oxygen demand) and nutrients concentration, and the remote sensing reflectance data at the sampling points were synchronously measured using above-water method in two cruises, which were conducted in the Pearl River Estuary in January 2003 and January 2004 respectively. Based on the in-situ data the local algorithms for estimation of concentration of nutrients (P and N) and COD were developed by Partial Least Squares (PLS) regression. The algorithms were then applied to atmospheric-corrected SeaWiFS data and the COD and nutrients concentration in Pearl River Estuary were estimated. And then the assessment of eutrophication was carried out by comparison of the estimated nutrients and COD value with the water quality standard. The results show that the whole estuary is seriously in eutrophication.

• Journal of the Korean Applied Science and Technology
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• v.16 no.1
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• pp.21-24
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• 1999

Sesame seed (Sesamum indicum L.) is an important seasoning in Korea and most korean consumer tend to eat the korean sesame seed as the best than other ones produced in oriental countries such as China and Japan. Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China and so on) of sesame seeds. Near-infrared spectroscopy among the many kinds of techniques could provide a rapid screening, low cost solution to discriminate geographical origin of sesame seed. The objective of this study is to determine if NIR technique could be used to discriminate between the korean sesame seed and non-korean sesame seed by using the new method. Rapid, precise and nondestructive analysis method for determination of the geographic origin of sesame seeds were discriminated relative accurately according to geographical origin using PLS regression method.

• YAKHAK HOEJI
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• v.48 no.3
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• pp.171-176
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• 2004

This study was described for measuring clinically relevant levels of glucose in undiluted plasma and whole blood by near-infrared (NIR) spectroscopy. Result from an initial measurement of major blood components powder was over-lapped the absorption bands of glucose at 1500-1600 nm. However, the NIR data of blood components were clearly separated by principle component analysis (PCA) space. By the use of partial least squares (PLS) regression, glucose concentrations in undiluted plasma and whole blood could be determined with standard errors of prediction (SEP) of 15 mg/dl and 76 mg/dl, respectively. Although these blood components possessed strong absorption bands that overlapped with the absorption bands of glucose, successful calibration models could be carried out.

• YAKHAK HOEJI
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• v.48 no.3
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• pp.177-181
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• 2004

Non-invasive blood glucose measurement from mouse tail was performed by near-infrared (NIR) spectroscopy. Three groups; normal, type I diabetes (insulin dependent diabetes mellitus, IDDM), type II diabetes (non-insulin dependent diabetes mellitus, NIDDM) group, were studied over a 10 weeks period with the collection of near-infrared (NIR) spectra. Spectral variations from long-term measurement (10 weeks) from dramatic and nonlinear changes in the optical properties of the live tissue sample were compensated by chemometrics techniques such as principle component analysis (PCA) and partial least squares (PLS) regression. The effect from mouse body temperature changes on NIR spectral data was also considered. This study showed that the compensation of variations from long-term measurement and temperature changes improved calibration accuracy of non-invasive blood glucose measurement.