• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.259-265
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• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• Journal of the Korean Chemical Society
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• v.53 no.6
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• pp.717-726
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• 2009

Multivariate models were developed for the simultaneous spectrophotometric determination of copper (II), nickel (II) and zinc (II) in water with 1-(2-thiazolylazo)-2-naphthol as chromogenic reagent in the presence of Triton X-100. To overcome the drawback of spectral interferences, principal component regression (PCR) and partial least square (PLS) multivariate calibration approaches were applied. Performances were validated with several test sets, and their results were then compared. In general, no significant difference in analytical performance between PLS and PCR models. The root mean square error of prediction (RMSEP) using three components for $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ were 0.018, 0.010, 0.011 ppm, respectively. Figures of merit such as sensitivity, analytical sensitivity, limit of detection (LOD) were also estimated. High reliability was achieved when the proposed procedure was applied to simultaneous determination of $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ in synthetic mixture and tap water.

• Korean Chemical Engineering Research
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• v.56 no.2
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• pp.229-239
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• 2018

The purpose of this study was to effectively produce the biosugar from cell wall of lipid extracted microalgae (LEA) by using microwave-assisted pretreatment without enzymatic hydrolysis process. Response surface methodology (RSM) was applied to optimization of microwave-assisted pretreatment conditions for the production of biosugar based on enzyme-free process from LEA. Microwave power (198~702 W), extraction time (39~241 sec), and sulfuric acid (0~1.0 mol) were used as independent variables for central composite design (CCD) in order to predict optimum pretreatment conditions. It was noted that the pretreatment variables that affect the production of glucose (C6) and xylose (C5) significantly have been identified as the microwave power and extraction time. Additionally, the increase in microwave power and time had led to an increase in biosugar production. The superimposed contour plot for maximizing dependent variables showed the maximum C6 (hexose) and C5 (pentose) yields of 92.7 and 74.5% were estimated by the predicted model under pretreatment condition of 700 w, 185.7 sec, and 0.48 mol, and the yields of C6 and C5 were confirmed as 94.2 and 71.8% by experimental validation, respectively. This study showed that microwave-assisted pretreatment under low temperature below $100^{\circ}C$ with short pretreatment time was verified to be an effective enzyme free pretreatment process for the production of biosugar from LEA compared to conventional pretreatment methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.625-637
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• 2020

In order to decide the naval ship weapon system acquisition for national policy/market economy activities, the decision makers can determine policy based on current technology level/concentration/utilization. For this, the decision makers apply the major common technology field analysis using patents data. As a method for collecting patent data, we can collect patent data of domestic mobile carriers through the Korea Intellectual Property Rights Information System of Korean Intellectual Property Office. As a result, we collected 14,964 patents/352 International Patent Classification(IPC) types. Based on these data, we performed three analysis processes (SNA, PCA, ARIMA, Text Mining) and got each result from extracting 58 IPC types of SNA and 7 IPC types of PCA. Based on the analysis results, we have confirmed that 7 IPC(B63B, H01M, F03D, B01D, H02K, B23K, H01H) types are the Major Common Technology Distribution of domestic Defense Companies.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.95-101
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• 2008

Modeling of stock prices forecast has been considered as one of the most difficult problem to develop accurately since stock prices are highly correlated with various environmental conditions including economics and political situation. In this paper, we propose a agent system approach to predict Korea Composite Stock Price Index (KOSPI) using neural network and statistical methods. To minimize mean of prediction error and variation of prediction error, agent system includes sub-agent modules for feature extraction, variables selection, forecast engine selection, and forecasting results analysis. As a first step to develop agent system for KOSPI forecasting, twelve economic indices are selected from twenty two basic standard economic indices using principal component analysis. From selected twelve economic indices, prediction model input variables are chosen again using best-subsets regression method. Two different types data are tested for KOSPI forecasting and the Prediction results showed 11.92 points of root mean squared error for consecutive thirty days of prediction. Also, it is shown that proposed agent system approach for KOSPI forecast is effective since required types and numbers of prediction variables are time-varying, so adaptable selection of modeling inputs and prediction engine are essential for reliable and accurate forecast model.

• Korean Security Journal
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• no.21
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• pp.95-120
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• 2009

This study was designed to investigate the relationship between the stages of exercise behavior change and physical self-concept and self-efficacy of security employees in hotel casinos. The sampling was drawn from employees at 8 casinos which had more than 30 employees. Participants were selected by convenience sampling method and they completed questionnaires about Physical Self-Concept and Self- Efficacy by self-administration method under supervision of trained researchers SPSS 16.0 (Statistical Package for the Social Science) was used for data analysis in the present study. Reliability and validity were examined for the present study. The principle component factor analysis and varimax rotation were used for the present study. Eigen value 1.0 was the criterion for selecting factors. Chi-square (X) 2 test was utilized for measuring the difference in gender and types of job duties at the stages of exercise behavior change. One-way ANOVA was employed to examine the relationship between the stages of exercise behavior change as an independent variable and physical self-concept and self-efficacy as dependent variables. The Scheffe method was used to determine mean differences of groups as a follow-up test. Multiple regression analysis was utilized to test the difference of physical self-concept as dependent variable and self-efficacy as independent variable. To verify hypothesis for the study, a statistical significance level of $\alpha$=.05 was used. The results were as follow: first, there were differences found for gender and types of job responsibilities in the stages of exercise behavior change. Secondly, as security employees progressed through the stages of exercise behavior change, their physical self-concept and self-efficacy improved. Finally, physical activity and body fat had significant main effects on self-efficacy.

• Horticultural Science & Technology
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• v.32 no.1
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• pp.105-114
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• 2014

We established a high throughput screening system of African yam tuber lines which contain high contents of total carotenoids, flavonoids, and phenolic compounds using ultraviolet-visible (UV-VIS) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. The total carotenoids contents from 62 African yam tubers varied from 0.01 to $0.91{\mu}g{\cdot}g^{-1}$ dry weight (wt). The total flavonoids and phenolic compounds also varied from 12.9 to $229{\mu}g{\cdot}g^{-1}$ and from 0.29 to $5.2mg{\cdot}g^{-1}$dry wt. FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate the 62 African yam tuber lines into three separate clusters corresponding to their taxonomic relationship. The quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds from African yam tuber lines were established using partial least square regression algorithm from FT-IR spectra. The regression coefficients ($R^2$) between predicted values and estimated values of total carotenoids, flavonoids and phenolic compounds were 0.83, 0.86, and 0.72, respectively. These results showed that quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from FT-IR spectra of African yam tuber lines with higher accuracy. Therefore we suggested that quantitative prediction system established in this study could be applied as a rapid selection tool for high yielding African yam lines.

• Korean Journal of Food Science and Technology
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• v.28 no.4
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• pp.616-623
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• 1996

Eum Yang Kwak, the aerial part of Epimedium koreanum, is widely used as a folk medicine for stimulant in man, tonic, and hypotensive purpose. The plant contains icariin (a specific flavonoid), magnoflorine (an alkaloid) and tannin, but their contents are not known until now. In this paper, a quantitative analysis method for them was developed. Determination of icariin and magnoflorine was successfully achived by high performance liquid chromatography equipped with a UV detector in the ranges of $0.1{\sim}0.4\;mg$ and $0.002{\sim}0.1\;mg\;per\;ml$ sample, respectively. Extraction of the plant was carried out with water or 50% ethanol using different decocting temperatures and times. Icariin was well extracted either by water ($100^{\circ}C$, 3hr) or 50% ethanol ($85^{\circ}C$, 1hr), and its content in the plant was measured to be 0.94%. On the other hand, magnoflorine was fully extracted by 50% ethanol ($85^{\circ}C$, 1hr), and its content was determined to be 0.16%. Therefore, decoction of the medicinal plant with water at $100^{\circ}C$ for 3hr turned out to be recommendable for the best extraction.