• 원예과학기술지
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• 제32권1호
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• pp.105-114
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• 2014

본 연구에서는 UV-VIS spectrophotometer를 이용한 total carotenoids, flavonoids, phenolics 함량 데이터와 FT-IR 스펙트럼 데이터를 다변량통계분석법을 통하여 기능성 성분 함량이 높은 아프리칸 얌 고속 선발 시스템을 구축하였다. 62개 아프리칸 얌의 total carotenoids 함량은 $0.01-0.91{\mu}g{\cdot}g^{-1}$ dry wt 나타냈다. Total flavonoids와 phenolics 함량은 $12.9-229.0{\mu}g{\cdot}g^{-1}$ dry wt와 $0.29-5.2mg{\cdot}g^{-1}$ dry wt로 각각 나타났다. 아프리칸 얌은 FT-IR 스펙트럼상의 1700-1500, 1500-1300, $1,100-950cm^{-1}$, 부위에서 중요한 스펙트럼 변화가 나타났다. 이 부위는 각각 amide I과 II을 포함하는 아미노산 및 단백질계열의 화합물, phosphodiester group을 포함한 핵산 및 인지질 그리고 단당류나 복합 다당류를 포함하는 carbohydrates 계열의 화합물들의 질적, 양적 정보를 반영하는 부위이다. PCA 분석과 PLS-DA 분석에서 62개 아프리칸 얌은 유연성이 높은 종으로 3개의 그룹을 형성하였다. 아프리칸 얌의 FT-IR 스펙트럼 데이터와 UV-VIS spectrophotometer을 이용한 total carotenoids, flavonoids, phenolics 함량 데이터 간에 PLS regression 분석하였다. Total carotenoids, flavonoids, phenolics 함량 성분의 실측 값과 예측 값간에 상관계수($R^2$)가 각각 0.83, 0.86, 0.72로 나타났다. 이 결과, 아프리칸 얌으로부터 FT-IR 스펙트럼을 이용한 total carotenoids, flavonoids, phenolics 함량 예측이 가능하였다. 본 연구에서 확립된 대사체 수준에서 아프리칸 얌의 유용 기능성 성분 함량 예측 모델링을 통해 품종, 계통의 신속한 선발 수단으로 활용이 가능할 것으로 예상된다.

• Asian-Australasian Journal of Animal Sciences
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• 제26권10호
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• pp.1388-1398
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• 2013

The present study investigated the contribution of carcass traits on carcass prices of Holstein steers in Korea. Phenotypic data consisted of 76,814 slaughtered Holsteins (1 to 6 yrs) from all over Korea. The means for live body weight at slaughter (BWT), chilled carcass weight (CWT), dressing percentage (DP), quantity grade index (QGI), eye muscle area (EMA), backfat thickness (BF) and marbling score (MS), carcass unit price (CUP), and carcass sell prices (CSP) were 729.0 kg, 414.2 kg, 56.79%, 64.42, $75.26cm^2$, 5.77 mm, 1.98, 8,952.80 Korean won/kg and 3,722.80 Thousand Korean won/head. Least squares means were significantly different by various age groups, season of slaughter, marbling scores and yield grades. Pearson's correlation coefficients of CUP with carcass traits ranged from 0.12 to 0.62. Besides, the relationships of carcass traits with CSP were relatively stronger than those with CUP. The multiple regression models for CUP and CSP with carcass traits accounted 39 to 63% of the total variation, respectively. Marbling score had maximum economic effects (partial coefficients) on both prices. In addition, the highest standardized partial coefficients (relative economic weights) for CUP and CSP were calculated to be on MS and CWT by 0.608 and 0.520, respectively. Path analyses showed that MS (0.376) and CWT (0.336) had maximum total effects on CUP and CSP, respectively; whereas BF contributed negatively. Further sub-group (age and season of slaughter) analyses also confirmed the overall outcomes. However, the relative economic weights and total path contributions also varied among the animal sub-groups. This study suggested the significant influences of carcass traits on carcass prices; especially MS and CWT were found to govern the carcass prices of Holstein steers in Korea.

• Journal of Biosystems Engineering
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• 제34권3호
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• pp.197-203
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• 2009

This study was performed to develop a nondestructive determination technology for sugar content in sweet persimmons, and the main research results included the following. In order to determine sugar content in sweet persimmons, a dual side reflex was adopted, and the study was to measure sugar content using a reflectance spectrum for 2 parts because it was difficult to determine representative sugar content due to a great deviation in sugar content according to the part of sweet persimmons. To predict sugar contents of sweet persimmon, PLSR and PCR models were compared with a few preprocess methods. As a result, PLSR had $R^2$=0.67, SEP=0.42 brix, LV=11, and PCR had $R^2$=0.65, SEP=0.41 brix, PC=16. SNV method was the best among preprocess methods for predicting sugar contents.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4102-4102
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• 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.

• 응용통계연구
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• 제30권5호
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• pp.633-645
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• 2017

본 연구는 컨테이너선의 연료 소비 패턴의 발견을 위해 운항데이터 분석의 통계적 절차를 제안한다. 우리는 현 시점의 연료 소비를 발견하기 위해 연료 소비에 영향을 미치는 변수들을 파악하는 동시에 예측 모델을 개발 및 적용하는 것을 목적으로 한다. 선박의 데이터는 크게 운항데이터와 기기데이터로 분류할 수 있으며, 운항데이터는 항로, 항해 정보, 대수속도, 대지속도, 바람과 같은 외력에 대한 정보 등이 있고, 기기데이터는 엔진출력, RPM, 연료 소모량, 기기들의 온도 및 압력 등이 있다. 본 연구에서, 우리는 선박에 미치는 외력의 영향을 Beaufort Scale (BFS)을 기준으로 구분한 후에 PLS 회귀분석을 통한 예측 모델을 개발하였다.

• 한국작물학회지
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• 제54권1호
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• pp.29-35
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• 2009

The aim of the present study was to update the calibration that is used for the measurement of the total nitrogen content in the rice plant samples by using the visible and near infrared spectrum. Before the equation merge, correlation coefficient of calibration equation for nitrogen content on each rice parts was 0.945 (Leaf), 0.928 (Stem), and 0.864 (Whole plant), respectively. In the calibration models created by each part in the rice plant under the various regression method, the calibration model for the leaf was recorded with relatively high accuracy. Among of those, the calibration equation developed by Partial least squares (PLS) method was more accurate than the Multiple linear regression (MLR) method. The calibration equation was sensitive based on variety and location variations. However, we have merged and enlarged various of the samples that made not only to measure the nitrogen content more accurately, but also later sampling populations became more diversified. After merging, $R^2$ value becomes more accurate and significantly to 0.950 (L.), 0.974 (S.), 0.940 (W.). Also, after removal of outlier, R2 values increased into 0.998, 0.995, and 0.997. In view of the results so far achieved, Standard error of prediction (SEP) and SEP (C) were reduced in the stem and whole plant. Biases were reduced in the leaf, stem as well as whole plant. Slopes were high in the stem. Standard deviation reduced in the stem but $R^2$ was high in the stem and whole plant. Result was indicated that calibration equation make update, and updating robust calibration equation from merge function and multi-variate calibration.

• 분석과학
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• 제11권1호
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• pp.47-53
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• 1998

본 연구는 당뇨병 진단방법의 개선을 위하여 채혈을 직접적으로 하지 않고 혈당을 측정할 수 있도록 하기 위하여 근적외선 분광법을 적용하였다. 본 연구를 위하여 근적외선 분광법을 이용하여 1 mg/dL에서 200 mg/dL 사이의 표준 시료 80개 글루코오스 흡수 스팩트럼을 측정하고 이를 정량하여 표준 농도와의 상관관계를 비교하였을 때 1.8 mg/dL 오차범위에서 매우 우수하였다. 그리고 실제 혈액중에 존재할 수 있는 전해질 및 피부에 의한 산란의 영향을 연구하였을 때 모두 2.8 mg/dL 및 3.8 mg/dL의 표준오차를 나타내었다. 특히 실제 피부에 적용하기 위하여 검량곡선에 비직선성을 유발하는 빛의 산란 현상에 관한 모델링을 통하여 정확도를 향상시키는 통계적인 방법을 제시하였다.

• 한국식품영양학회지
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• 제30권4호
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• pp.719-727
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• 2017

The objective of this study was to investigate the effect of alcohol content in Makgeolli made with Chinese matrimony vine (M-CMV) on the sensory profile and consumer acceptability. The M-CMVs were prepared with 6, 7, 8, and 9% alcohol content. Descriptive analysis of M-CMV was performed with six trained panelists. Thirteen attributes were generated and their intensities were alcohol content dependent. The consumer acceptance test was conducted with 57 consumers. M-CMV samples with 7% alcohol had the highest acceptance rate (5.8) followed by 6% M-CMV (5.6). Commercial rice Makgeolli (CRM) had the lowest consumer acceptance. Consumers were divided into two groups by clustering analysis. The majority of consumers (n=38) preferred M-CMV and did not like the commercial sample. Only 19 consumers indicated high acceptance ratings for CRM. However, these consumers also preferred 6 and 7% M-CMV. Partial least-squares regression analysis revealed moderate attribute intensities were related to greater consumer acceptability. The optimal alcohol content for the greatest consumer acceptance predicted by linear regression was 6.7%.

• 농업과학연구
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• 제50권4호
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• pp.675-696
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• 2023

Terpenoids, also referred to as terpenes, are a large family of naturally occurring chemical compounds present in the essential oils extracted from medicinal plants. In this study, a nondestructive methodology was created by combining ATR-FT-IR (attenuated total reflectance-Fourier transform infrared), and Raman spectroscopy for the terpenoids assessment in medicinal plants essential oils from ten different geographical locations. Partial least squares regression (PLSR) and support vector regression (SVR) were used as machine learning methodologies. However, a deep learning based model called as one-dimensional convolutional neural network (1D CNN) were also developed for models comparison. With a correlation coefficient (R²) of 0.999 and a lowest RMSEP (root mean squared error of prediction) of 0.006% for the prediction datasets, the SVR model created for FT-IR spectral data outperformed both the PLSR and 1 D CNN models. On the other hand, for the classification of essential oils derived from plants collected from various geographical regions, the created SVM (support vector machine) classification model for Raman spectroscopic data obtained an overall classification accuracy of 0.997% which was superior than the FT-IR (0.986%) data. Based on the results we propose that FT-IR spectroscopy, when coupled with the SVR model, has a significant potential for the non-destructive identification of terpenoids in essential oils compared with destructive chemical analysis methods.

• 한국산업정보학회논문지
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• 제24권4호
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• pp.99-112
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• 2019

시대의 변화에 따라 교육 시장의 모습도 변화하고 있다. 국내 대학들은 학령인구의 감소에 따른 위기극복의 방안으로 외국인 유학생을 유치하기 위한 노력을 기울이고 있다. 우리나라 유학생 중 가장 큰 비중을 차지하고 있는 중국인 유학생은 우리나라 대학에서 주요한 학생 구성원이 되고 있다. 중국인 유학생은 본국을 떠나 새로운 환경에 적응하면서 다양한 어려움에 직면하게 된다. 본 연구는 중국인 유학생들의 학업적 요인과 정서적 요인이 대학생활 적응도와 대학생활 만족도에 미치는 영향을 검증하는데 그 목적이 있다. 이를 위해 부산소재 4년제 D대학에 재학중인 중국인 유학생 128명을 대상으로 자료를 수집하였으며, 자료분석은 PLS(Partical least squares)을 사용하여 경로분석을 실시하였다. 연구결과는 다음과 같다. 첫째, 학업적 요인인 교수 요인과 교직원의 관심정도는 대학생활 적응도에 유의한 영향을 미쳤으나, 한국어 구사 능력은 대학생활 적응도에 유의한 영향을 나타내지 않았다. 둘째, 정서적 요인인 향수병은 대학생활 적응도에 유의한 영향을 나타냈으나, 문화적응 스트레스는 대학생활 적응도에 유의한 영향을 미치지 않는 것으로 나타났다. 셋째, 대학생활 적응도는 대학생활 만족도에 유의한 영향이 입증되었다. 이러한 결과를 토대로 본 연구의 의의와 한계점 및 향후 연구 방안에 대해 논의하였다.