• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1528-1528
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• 2001

Ginseng cultivated in different country or growing condition has generally different components such as saponin and protein, and it relates to efficacy and action. Protein content assumes by nitrogen content in ginseng radix. Nitrogen content could be determined by chemical analysis such as kjeldahl or extraction methods. However, these methods require long analysis time and result environmental pollution and sample damage. In this work we investigated possibility of non-destructive determination of nitrogen content in ginseng radix using near-infrared spectroscopy. Ginseng radix, root of Panax ginseng C. A. Meyer, was studied. Total 120 samples were used in this study and it was consisted of 6 sample sets, 4, 5 and 6-year-old Korea ginseng and 7, 8 and 9-year-old China ginseng, respectively. Each sample set has 20 sample. Nigrogen content was measured by electronic analysis. NIR reflectance spectra were collected over the 1100 to 2500 nm spectral region with a InfraAlyzer 500C (Bran+Luebbe, Germany) equipped with a halogen lapmp and PbS detector and data were collected every 2 nm data point intervals. The calibration models were carried out by multiple linear regression (MLR) and partial least squares (PLS) analysis using IDAS and SESAME software. Result of electronic analysis, Korean ginseng were different mean value in nitrogen content of China ginseng. Ginseng tend to generally decrease the nitrogen content according as cultivation year is over 6 years. The MLR calibration model with 8 wavelengths using IDAS software accurately predicted nitrogen contents with correlation coefficient (R) and standard error of prediction of 0.985 and 0.855%, respectively. In case of SESAME software, the MLR calibration with 9 wavelength was selected the best calibration, R and SEP were 0.972 and 0.596%, respectively. The PLSR calibration model result in 0.969 of R and 0.630 of RMSEP. This study shows the NIR spectroscopy could be applied to determine the nitrogen content in ginseng radix with high accuracy.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1529-1529
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• 2001

The watercore in apple is very important factor in storage and sorting of fruit. Most consumers tend to prefer the apple included watercore in immediately after harvest, however the watercore causes fruit flesh to brown during storage and lose the worth after all. But it is practically impossible to judge to the naked eye whether an apple has watercore or not. Therefore, the rapid, accurate and non-destructive analysis method for discrimination of watercore should be settled without delay. In this study we attempted the discrimination and quantitative analysis of watercore in apple fruit using near-infrared transmittance spectroscopy ‘Fuji’ apple fruits produced in Kyungpook of Korea was used in this experiment. The watercore content in apple was evaluated by graphic treatment of culled slice sections(10 mm). NIR transmittance spectra were collected over the 500 to 1000 nm spectral region with a spectrometer (Sentronic Co., Germany). The calibration models were carried out by partial least squares (PLS) analysis between NIR spectra data of apples and chemical data of watercore content. The spectra were different in absorbance between apple included watercore and not included one. Apple included watercore had higher absorption band than sample not included one at 732 and 820 nm. The calibration model seems to be accurate to predict the watercore content in apple fruit, the correlation coefficient (R) and root mean square error of prediction (RMSEP) were 0.99 and 0.93%, respectively. This result indicates that the PLSR calibration model by using NIR transmittance spectroscopy could be used for discrimination of watercore in apple fruit.

• Journal of Preventive Medicine and Public Health
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• 제50권4호
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• pp.240-250
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• 2017

Objectives: Subjective life expectancy (SLE) has been found to show a significant association with mortality. In this study, we aimed to investigate the major factors affecting SLE. We also examined whether any differences existed between SLE and actuarial life expectancy (LE) in Korea. Methods: A cross-sectional survey of 1000 individuals in Korea aged 20-59 was conducted. Participants were asked about SLE via a self-reported questionnaire. LE from the National Health Insurance database in Korea was used to evaluate differences between SLE and actuarial LE. Age-adjusted least-squares means, correlations, and regression analyses were used to test the relationship of SLE with four categories of predictors: demographic factors, socioeconomic factors, health behaviors, and psychosocial factors. Results: Among the 1000 participants, women (mean SLE, 83.43 years; 95% confidence interval, 82.41 to 84.46 years; 48% of the total sample) had an expected LE 1.59 years longer than that of men. The socioeconomic factors of household income and housing arrangements were related to SLE. Among the health behaviors, smoking status, alcohol status, and physical activity were associated with SLE. Among the psychosocial factors, stress, self-rated health, and social connectedness were related to SLE. SLE had a positive correlation with actuarial estimates (r=0.61, p<0.001). Gender, household income, history of smoking, and distress were related to the presence of a gap between SLE and actuarial LE. Conclusions: Demographic factors, socioeconomic factors, health behaviors, and psychosocial factors showed significant associations with SLE, in the expected directions. Further studies are needed to determine the reasons for these results.

• Journal of Biosystems Engineering
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• 제36권5호
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• pp.369-376
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• 2011

The overall goal of this study was to examine the feasibility of predicting firmness of pear fruit by analyzing laser-induced light backscattering images. Thirty-five image analysis characteristics extracted from the laser-induced light backscattering images were used to build partial least squares regression (PLSR) models for predicting firmness of pear fruit. Experiments were conducted with three sets of pear samples which were in same "Shingo" cultivar, harvested in a same season, but produced in different counties. In every experiments with fruit samples produced in a same county, the correlation coefficients of prediction ($r_p$) and root mean square errors of prediction (RMSEP) of the models were 0.550~0.761 and 4.039~6.154 N, respectively. In an experiment with mixed fruit samples produced in different counties, the $r_p$ and RMSEP of the model were 0.669 and 5.02 N, respectively. The experiment results indicate that the analysis of laser-induced light backscattering images could be a useful tool for predicting firmness of pear fruit nondestructively.

• Journal of Biosystems Engineering
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• 제33권4호
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• pp.260-268
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• 2008

Optical diffuse reflectance sensing has potential for rapid and reliable on-site estimation of soil properties. For good results, proper calibration to measured soil properties is required. One issue is whether it is necessary to develop calibrations using samples from the specific area or areas (e.g., field, soil series) in which the sensor will be applied, or whether a general "factory" calibration is sufficient. A further question is if specific calibration is required, how many sample points are needed. In this study, these issues were addressed using data from 42 paddy fields representing 14 distinct soil series accounting for 74% of the total Korean paddy field area. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination ($R^2$) root mean square error of prediction (RMSEP), and RPD, the ratio of standard deviation to RMSEP. When sample data from a soil series were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.03 to 3.32, compared with results from calibration models not including data from the test soil series (calibration without site-specific information). Higher $R^2$ values were also obtained in most cases. Including some samples from the test soil series (hybrid calibration) generally increased RPD rapidly up to a certain number of sample points. A large portion of the potential improvement could be obtained by adding about 8 to 22 points, depending on the soil properties to be estimated, where the numbers were 10 to 18 for pH, 18-22 for EC, and 8 to 22 for total C. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.

• 한국항공우주학회지
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• 제32권4호
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• pp.43-52
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• 2004

본 논문에서는 아리랑 1호의 실제 비행데이터를 이용하여 지상에서 정밀궤도결정을 수행한 후 얻을 수 있는 성능에 대해 분석하였다. 분석에 사용된 궤도결정 알고리즘은 바예 시안 최소자승법을 작용한 배치필터이며, 궤도결정 정밀도 평가를 위해 중첩법 (Overlap Method) 을 이용하였다. 또한, 미국 NORAD 의 TLE (Two-Line Element) 및 지상추적 데이터를 이용한 궤도결정 결과들과의 비교, 분석도 수행하였다. 궤도결정 정밀도에 영향을 미칠 수 있는 요인, 즉 관측데이터 종류 및 탑재시계 편류 (On-Board Time Drift)에 의한 정밀도 변화에 대해서도 분석되어졌다. 본 연구결과, 중첩법 평가에 의한 30시간 GPS 항행해 위치 성분만을 이용한 궤도결정 정밀도는 5m RMS 수준이었으며, GPS 항행해 중 속도 성분은 궤도결정 시 사용하지 않는 것이 바람직하며, 타 관측데이터를 이용한 궤도결정 결과와의 비교를 통해 심각한 시각 바이어스에 의한 뚜렷한 정밀도 저하는 없음을 알 수 있었다.

• 응용통계연구
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• 제29권3호
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• pp.471-485
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• 2016

회귀모형의 대표적인 추정법인 최소제곱법은 오차항의 분포가 정규분포를 따르고 이상치가 없는 상황에서는 최적이지만, 자료가 회귀모형의 가정을 만족하지 않을 경우 또는 이상치를 포함하는 경우와 같이 자료가 오염된 상황에서는 왜곡된 추정 결과를 준다. 따라서 이상치에 민감한 최소제곱법의 단점을 보완하기 위해 다양한 로버스트 추정방법이 제안되었다. 본 논문에서는 MLE를 기반으로 제안된 M 추정량, 순서형 통계량을 기반으로 제안된 L 추정량, 잔차의 순위를 기반으로 제안된 R 추정량 계열에서 높은 붕괴점 또는 높은 효율을 갖는 대표적인 추정량들을 다양한 모의실험을 통해 비교 연구하였다. 추정량의 성능을 비교하는데 효율성 뿐만 아니라 편의, 분산을 포함한 분포를 살펴보았다. 그 결과 실제 데이터 적용에는 MM 추정량과 GR 추정량이 좋은 성능을 가진 것으로 보였다.

• 응용통계연구
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• 제23권5호
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• pp.967-975
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• 2010

데이터마이닝 분야에서의 회귀모형에는 연관성이 높은 설명변수들이 포함되어 다중공선성을 유발하는 경우가 많은데, 다중공선성이 야기하는 문제를 해결하기 위하여 주성분회귀분석을 적용할 수 있다. 이 분석에서는 적절한 주성분을 선정하는 과정이 핵심인데, 기존의 선정방법들은 다중공선성을 잘 해결하지 못하거나 모형의 적합성을 저하시킨다는 지적을 받고 있다. 따라서 본 논문에서는 다중공선성 문제와 적합성 저하 현상을 동시에 해결할 수 있는 새로운 선정방법을 제안하였다. 다중공선성에 의해 최소제곱추정량의 분산이 팽창되는 문제를 주성분회귀에 의해 해결할 수 있지만, 주성분의 일부를 선정함에 따라 발생하는 편의도 동시에 통제해야 한다. 따라서 주성분회귀추정량의 평균제곱오차를 최소가 되게 하는 상태지수를 측정하고, 이 값에 영향을 미치는 주요 요인들을 컨조인트분석에 의해 파악하여 주성분 선정기준 모형을 구축하였다. 선정기준의 상한과 하한을 설정하고, 상태지수가 상한을 초과하면 해당 주성분을 제외시키고, 하한에 미달하면 해당 주성분을 포함시킨다. 그리고 상한과 하한 사이의 상태지수에 대응하는 주성분들에 대해서는 일반화선형검정을 순차적으로 적용하여 주성분을 선정하는 방법이다.

• Asian-Australasian Journal of Animal Sciences
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• 제17권1호
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• pp.63-67
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• 2004

In order to evaluate the nutritive value of the forage plants in South Sulawesi, Indonesia, 266 samples (61 grasses and 65 legumes grown in the dry season, 60 grasses and 80 legumes grown in the rainy season) were collected from the highland and the lowland in 1998 to 2000, and were subjected to the determination of mineral composition. The mean contents of Ca, Mg, P, Na and K in grasses were 0.6, 0.3, 0.5, 0.1 and 2.3%, respectively, and in legumes were 1.8, 0.5, 0.8, 0.1 and 1.7%, respectively. The least-squares analysis of variance demonstrated as follows; For the grasses, Ca content was significantly affected by the year${\times}$season, year${\times}$altitude, and the season${\times}$altitude interactions. Mg content was significantly affected by year and season and P content was significantly affected by altitude, year and by the year${\times}$altitude interaction. For the legumes, Ca content was significantly affected by altitude and the year${\times}$season, season${\times}$altitude and the year${\times}$altitude interactions and Mg content was significantly affected by season or altitude and by the year${\times}$season interaction. These results indicate that Ca content of forage plants grown at the lowland in rainy season was higher than at the highland in dry season. Mg content of forage plants grown at the lowland in dry season was higher than at the highland in rainy season and P content of forage plants grown in the highland was higher than in the lowland.

• Asian-Australasian Journal of Animal Sciences
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• 제14권11호
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• pp.1516-1519
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• 2001

The data consisted of 369 lactation records for calvings over a sixteen-year period (1972-1987) and included only cows that had normal milk records. The data were analysed using a linear model containing the fixed effects of parity, year of calving and season of calving. The least squares means${\pm}$S.E. were $1,273{\pm}58.4kg$ for milk yield, and for post-partum body weight (kg) at 2, 3 and 4 months after calving were $343.40{\pm}3.96$, $346.10{\pm}4.10$ and $352.54{\pm}4.26$, respectively. With the exception of season of calving, the effects of parity and year of calving were significant (p<0.01) on the performance of the animals. Thus, the mean-milk yields 1162, 1351 and 1350, were similar for pre-, peak- and post rainy seasons, respectively. On the other hand, as parity increased from 1 to 3, milk yield also increased, but thereafter, there was a gradual decline in milk yield. Similarly, post-partum body weight also increased with parity. However, no consistent pattern for year effect was observed which probably was a reflection of the variation in climatic conditions, or forage quality and/or availability. The phenotypic correlations between milk yield and post-partum body weights were negative and small (ranging from -0.01 to -0.08). However, high milk production in cows was associated with longer calving interval. The implications from the phenotypic correlations are suggestive of one or two possibilities. Firstly, selection for increased body weight may actually result in decreased milk yield. Also, a substantial genetic antagonism may exist between milk yield and fertility in the crossbred cows. Therefore, it is important that selection to improve milk production should take into consideration the reproductive performance of the cows.