• Development and Reproduction
• /
• v.16 no.4
• /
• pp.309-314
• /
• 2012

This study was conducted to analyze the difference of body types within and between wild and farmed populations of olive flounder Paralichthys olivaceus using measured records of morphological traits. The results showed that surveyed traits and standard deviation were $1,355{\pm}742g$ of body weight, $48.01{\pm}7.79cm$ of total length, and $40.96{\pm}6.80cm$ of body length. Also body height, body shape index and condition factor were $17.19{\pm}3.43cm$, $9.99{\pm}0.74$ and $11.16{\pm}1.54$, respectively. As result of least squares mean and standard error for each trait assumed in this study, those of farmed population showed significantly higher than those of wild population in all traits, exclusively in total length and body length (p<0.01). Particularly, the values of the body height and the body weight of the farmed population were higher than those of the wild population in the same total length. And the phenotypic correlation coefficients of the body weight, the total length, the body length and the body height showed strong positive correlation in all populations. These result suggested that morphological differences exist in farmed and wild flounder. Therefore, introduction of wild flounder is essential for the future production to improve the body type of farmed flounder, and parental fish should be chosen by considering selection of commercially important traits in the production process.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.4102-4102
• /
• 2001

In multivariate analysis, absorbance spectrum is measured over a band of wavelengths. One does not often pay attention to the size of this wavelength band. However, it is desirable that spectrum is measured at only necessary wavelengths as long as the acceptable accuracy of prediction can be met. In this paper, the method of selecting an optimal band of wavelengths based on the loading vector analysis was proposed and applied for determining total protein in human serum using near-infrared transmission spectroscopy and PLSR. Loading vectors in the full spectrum PLSR were used as reference in selecting wavelengths, but only the first loading vector was used since it explains the spectrum best. Absorbance spectra of sera from 97 outpatients were measured at 1530∼1850 nm with an interval of 2 nm. Total protein concentrations of sera were ranged from 5.1 to 7.7 g/㎗. Spectra were measured by Cary 5E spectrophotometer (Varian, Australia). Serum in the 5 mm-pathlength cuvette was put in the sample beam and air in the reference beam. Full spectrum PLSR was applied to determine total protein from sera. Next, the wavelength region of 1672∼1754 nm was selected based on the first loading vector analysis. Standard Error of Cross Validation (SECV) of full spectrum (1530∼l850 nm) PLSR and selected wavelength PLSR (1672∼1754 nm) was respectively 0.28 and 0.27 g/㎗. The prediction accuracy between the two bands was equal. Wavelength selection based on loading vector in PLSR seemed to be simple and robust in comparison to other methods based on correlation plot, regression vector and genetic algorithm. As a reference of wavelength selection for PLSR, the loading vector has the advantage over the correlation plot since the former is based on multivariate model whereas the latter, on univariate model. Wavelength selection by the first loading vector analysis requires shorter computation time than that by genetic algorithm and needs not smoothing.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.57 no.1
• /
• pp.29-34
• /
• 2012

The objective of this study was to rapidly evaluate fatty acids in a collection of millet (Panicum miliaceum subsp. miliaceum) of different origins so that this information could be disseminated to breeders to advance germplasm use and breeding. To develop the calibration equations for rapid and nondestructive evaluation of fatty acid content, near-infrared reflectance spectroscopy (NIRs) spectra (1104-2494 nm) of samples ground into flour ($n$=100) were obtained using a dispersive spectrometer. A modified partial least-squares model was developed to predict each component. For foxtail millet germplasm, our models returned coefficients of determination ($R^2$) of 0.89, 0.89, 0.89, and 0.92 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively. The prediction of the external validation set (n=10) showed significant correlation between references values and NIRs values ($r^2$=0.64, 0.90, 0.79, and 0.89 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). Standard deviation/standard errors of cross-validation (SD/SECV) values were close to 3 (2.62, 2.40, 1.85, and 2.23 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). These results indicate that these NIRs equations are functional for the mass screening and rapid quantification of the oleic and total fatty acids characterizing millet germplasm. Among the samples, IT153514 showed an especially high content of fatty acids ($48.14mg\;g^{-1}$), whereas IT123909 had a very low content ($34.44mg\;g^{-1}$).

• Korean Journal of Breeding Science
• /
• v.42 no.5
• /
• pp.448-454
• /
• 2010

The objective of this study was to rapidly evaluate fatty acids in a collection of foxtail millet (Setaria italica (L.) P. Beauv) of different origins so that this information could be disseminated to breeders to advance germplasm use and breeding. To develop the calibration equations for rapid and nondestructive evaluation of fatty acid content, near-infrared reflectance spectroscopy (NIRs) spectra (1104-2494 nm) of samples ground into flour (n=100) were obtained using a dispersive spectrometer. A modified partial least-squares model was developed to predict each component. For foxtail millet germplasm, our models returned coefficients of determination ($R^2$) of 0.91, 0.89, 0.98 and 0.98 for strearic acid, oleic acid, linoleic acid, and total fatty acids, respectively. The prediction of the external validation set (n=10) showed significant correlation between references values and NIRs values ($r^2=0.97$, 0.91, 0.99 for oleic, linoleic, and total fatty acids, respectively). Standard deviation/standard error of cross-validation (SD/SECV) values were greater than 3 (3.11, 5.45, and 7.50 for oleic, linoleic, and total fatty acids, respectively). These results indicate that these NIRs equations are functional for the mass screening and rapid quantification of the oleic, linolenic, and total fatty acids characterizing foxtail millet germplasm. Among the samples, IT153491 showed an especially high content of fatty acids ($84.06mg\;g^{-1}$), whereas IT188096 had a very low content ($29.92mg\;g^{-1}$).

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1457-1469
• /
• 2017

Private education expenses is one of the key issues in Korea and there have been many discussions about it. Academically, most of previous researches for private education expenses have used multiple regression linear model based on ordinary least squares (OLS) method. However, if the data do not satisfy the basic assumptions of the OLS method such as the normality and homoscedasticity, there is a problem with the reliability of estimations of parameters. In this case, quantile regression model is preferred to OLS model since it does not depend on the assumptions of nonnormality and heteroscedasticity for the data. In the present study, the data from a survey on private education expenses, conducted by Statistics Korea in 2015 has been analyzed for investigation of the impacting factors for private education expenses. Since the data do not satisfy the OLS assumptions, quantile regression model has been employed in Bayesian approach by using gibbs sampling method. The analysis results show that the gender of the student, parent's age, and the time and cost of participating after school are not significant. Household income is positively significant in proportion to the same size for all levels (quantiles) of private education expenses. Spending on private education in Seoul is higher than other regions and the regional difference grows as private education expenditure increases. Total time for private education and student's achievement have positive effect on the lower quantiles than the higher quantiles. Education level of father is positively significant for midium-high quantiles only, but education level of mother is for all but low quantiles. Participating after school is positively significant for the lower quantiles but EBS textbook cost is positively significant for the higher quantiles.

• Journal of Korean Society of Forest Science
• /
• v.97 no.1
• /
• pp.45-52
• /
• 2008

The objectives of this study are to explain a supply plan of domestic softwood log by long-term prospect of MDF production to stably promote industry of MDF. For it, we developed the long supply function as Ordinary Least Squares Method. Between 2005 and 2050, it was estimated that quantity of domestic production of MDF increased from 1,653 thousand $m^3$ to 2,041 thousand $m^3$. In 2050, quantities of domestic softwood log used by raw materials to product MDF of 2,041 thousand $m^3$ were estimated to be used about 1,355 thousand $m^3$. Exampling Pinus rigida used presently by raw materials to product MDF, cutting area of it is estimated to be 10,828 ha per year. And larch is cutted about 9,160 ha per year. This study estimated annual softwood log cutting amount and total afforestation area at 2050 year by 3 scenarios which are 35%, 45% and 55% about use of domestic softwood log for MDF production. If we do a criterion of cutting area, we advantage to plant larch. But the species of trees are use and growth property. We think that the afforestation policy must be performed on the base of those to supply raw materials of MDF. Although government plans hardwood afforestation policy after cutting Pinus rigida, it needs to support and manage certainly afforestation area of softwoods to need to supply raw materials of MDF to stably promote industry of MDF.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.53 no.3
• /
• pp.244-250
• /
• 2008

The purpose of this study was to measure fundamental data required for the prediction of milling ratios, and to develop regression models to predict the head rice ratio of milled rice using NIR spectra of hulled rice. A total of 81 rice samples used in this study were collected from Jeongeup, Jeonbuk province in 2006. NIR spectra were measured using one mode of measurement, reflection. The reflectance spectra were measured in the wavelength region of 400-2500 nm with an NIR spectrophotometer "NIRSystems 6500" (Foss, Silverspring, USA). Calibration equations were developed by the modified partial least squares (MPLS), partial least squares (PLS), and principal components regression (PCR). Math treatments were 1-4-4-1, 1-10-10-1, 2-4-4-1, and 2-10-10-1. The software used was WinISI (Infrasoft International, State College, USA). Automatic head rice production and quality checking system used was "SY2000-AHRPQCS" (Ssangyong, Korea). The calibration was made with the first derivative and the spectrum designated was in 8 nm interval. The determination coefficients of head rice ratios were 0.8353, 0.8416 and 0.5277 for the MPLS, PLS and PCR, respectively. Those obtained with 20 nm interval were 0.8144, 0.8354 and 0.6908 for the MPLS, PLS and PCR, respectively. The calibration was made with second derivative that spectrum designated was 8 nm in interval. The determination coefficients of head rice ratios were 0.7994, 0.8017 and 0.4473 for the MPLS, PLS and PCR, respectively. Those with 20 nm interval were 0.8004, 0.8493 and 0.6609 for the MPLS, PLS and PCR, respectively. These results indicate that the accuracy of determination coefficient for MPLS and PLS is higher than that of PCR.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.53 no.1
• /
• pp.15-20
• /
• 2008

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 measure anthocyanin contents in black colored soybean by using NIRS system. Total 300 seed coat of black colored soybean samples previously analyzed by HPLC were scanned by NIRS and over 250 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed in which the coefficient of determination for anthocyanin pigment C3G, D3G and Pt3G content was 0.952, 0.936, and 0.833, respectively. Each calibration equation was applied to validation set that was performed with the remaining samples not included in the calibration set, which showed high positive correlation both in C3G and D3G content file. In case Pt3G, the prediction model was needed more accuracy because of low $R^2$ value in validation set. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of C3G and D3G contents in black colored soybean.

• Journal of Korea Water Resources Association
• /
• v.41 no.3
• /
• pp.243-249
• /
• 2008

Continuous stirred tank reactor(CSTR) model which can be applied to control and management of the surface flow wetland is developed to simulate the water quality in this research. The model solution is obtained from the optimization model using the least-squares and 4th-order Runge-Kutta methods. The model is applied to simulate BOD and TSS in the wetland database of U.S. EPA, in which the hydraulic and water quality data are enough and the number of pond is just one for simple analysis of running results. The model is tested in two different cases, one constant volume case and another constant volume and flow rate case considering only reaction term, mass flux term and both reaction and mass flux terms respectively. It is found that the model simulates the real water quality very well with both reaction and mass flux terms rather than only reaction term and the settling velocity of TSS becomes $0.3{\sim}0.4\;m/d$. The model can be applied in wetlands treatment efficiently.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.4
• /
• pp.215-222
• /
• 2019

The heat conduction problem with discontinuous material coefficients generally consists of the conservative equation, boundary condition, and interface condition, which should be additionally satisfied in the solution procedure. This feature often makes the development of new numerical schemes difficult as it induces a layered singularity in the solution fields; thus, a special approximation is required to capture the singular behavior. In addition to the approximation, the construction of a total system of equations is challenging. In this study, a wedge function is devised for enriching the approximation, and the interface condition itself is embedded in the moving least squares(MLS) derivative approximation to consistently satisfy the interface condition. The heat conduction problem is then discretized in a strong form using the developed derivative approximation, which is named as the interface immersed MLS difference method. This method is able to efficiently provide a numerical solution for such interface problems avoiding both numerical quadrature as well as extra difference equations related to the interface condition enforcement. Numerical experiments proved that the developed numerical method was highly accurate and computationally efficient at solving the heat conduction problem with interfacial jump as well as the problem with a geometrically induced interfacial singularity.