• Journal of Korean Society of Forest Science
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• v.79 no.1
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• pp.16-20
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• 1990

Canonical correlation analysis was used to relate 17 soil-site variables to bamboo diameter, height, and internodal characteristics. The first canonical correlation was highly significant, explained much of the variance in both sets of variables, and the canonical variates made sense biologically. Surface soil depth, total nitrogen and percent organic matter had high positive correlations with the first soil-site canonical variate. Clay content (%) and cation exchange capacity were negatively correlated with the first soil-site canonical variate. Only 8 of predictor variables were considered relevant for predicting bamboo growth.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.114-119
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• 2009

본 논문에서는 수량화 방법과 AHP(Analytic Hierarchy Process) 기법을 사용하여 산사태 발생에 대한 통계적 예측모형을 구축하는데 목적이 있다. 수량화(Quantification) 방법은 질적변수에 수량을 부여하는 통계적 방법으로, 기 조사된 자료에 기반하여 분석을 수행하는 방법이다. 본 논문에서는 서구의 다변량분석 기법인 정준상관분석의 결과를 토대로 수량화 과정을 구체적으로 제안한다. 데이터에 기반한 수량화 방법과는 달리 AHP(Analytic Hierarchy Process) 기법은 일종의 다기준 의사결정을 위해 사용되는 기법으로, 설문자료에 기반한 분석법이다. 실제자료에 대한 분석으로 산사태 발생여부를 측정한 자료(한국지질자원연구원 제공)와 전문가 설문을 통해 수집된 자료를 이용하였다. 이들 자료에 대해 수량화 분석과 AHP분석을 통해 산사태 발생여부를 예측할 수 있는 두 종류의 평가표와 함께 로지스틱 회귀를 통한 통계적 예측모형을 개발하였으며, 두 모형간의 성능비교와 안정성 평가를 수행하였다.

• Bulletin of Food Technology
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• v.9 no.4
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• pp.87-93
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• 1996

NIR(근적외) 분광분석법이 참기름의 원산국 판별에 이용 가능 한지를 알아보기 위하여 32종의 시료에 대하여 NIR 분석을 실시한 후, 그 분광 데이터에 대하여 principal component analysis(주성분 분석)와 canonical variate analysis(정준판별분석)을 실시하였다. 10개의 주성분과 400-2500nm에서 second derivative log(1/R) 데이터를 이용할 경우, 제1 및 제2 정준판별함수는 3개 참기름 그룹(한국산 참깨로 제조한 13종의 참기름 그룹, 외국산 참깨로 제조한 10종의 국산 참기름 그룹 및 미지의 참깨로 제조한 9종의 참기름 그룹)을 판별하는데 가장 효과적이었다. 사용된 canonical variate analysis는 참기름 시료를 100%의 정확도로 그 지리적 출처를 분류하였다. 한편 second derivative log(1/R) spectra상의 파장범위 498-500, 668, 1698-1724, 2242-2256, 2302-2306, 2328 및 2348~2352nm에서 3개 그룹간에 현저한 차이가 발견되었다.

• Bulletin of Food Technology
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• v.10 no.1
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• pp.94-101
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• 1997

NIR(근적외) 분광분석법이 녹차의 원산국을 판별하는데 이용할 수 있는지를 알아보기 위하여 분쇄한 47종의 한국산 및 일본산 녹차에 대하여 NIR 분석을 실시한 후, 그 분광 데이터에 대하여 principal component analysis(주성분 분석 )와 canonical variate analysis(정준판별분석)을 실시하였다. 15개의 주성분과 1100~2500nm에서의 first derivative log(1/R) 데이터를 이용할 경우, 제1 및 제2 정준판별함수는 한국산 녹차 및 일본산 녹차를 판별하는데 가장 효과적이었다. 사용된 canonical variate analysis는 녹차 시료를 97.87%의 정확도로 그 지리적 출처를 판별하였다. 한편 first derivative log(1/R) spectra상의 파장범위 1674~1686, 1950~1992, 2014~2030및 2118~2158 nm에서 일본산 녹차와 3종의 한국산 녹차 그룹간에 현저한 차이가 발견되었다. 이 차이는 polyphenols, caffeine 및 amino acids와 같은 녹차의 주요성분과 관련되어 있지 않으며 주로 지리적 출처상의 차이에 기인한 것으로 판단되었다.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.227-228
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• 2009

This study proceeded to find the optimum mixing rate of a high strength concrete with 80MPa of the contribution and composite effect on the resistance to fire of the fibers were analyzed and the corresponding results were exploited to derive practical mix proportions. Also proceeded to propriety examination of limit value for optimum operating condition.

• Food Science of Animal Resources
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• v.29 no.1
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• pp.132-139
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• 2009

The objective of this study was to investigate the most effective analysis methods for palatability grading of Hanwoo beef by comparing the results of discriminant analysis with sensory data. The sensory data were obtained from sensory testing by 1,300 consumers evaluated tenderness, juiciness, flavor-likeness and overall acceptability of Hanwoo beef samples prepared by boiling, roasting and grilling cooking methods. For the discriminant analysis with one factor, overall acceptability, the linear discriminant functions and the non-parametric discriminant function with the Gaussian kernel were estimated. The linear discriminant functions were simple and easy to understand while the non-parametric discriminant functions were not explicit and had the problem of selection of kernel function and bandwidth. With the three palatability factors such as tenderness, juiciness and flavor-likeness, the canonical discriminant analysis was used and the ability of classification was calculated with the accurate classification rate and the error rate. The canonical discriminant analysis did not need the specific distributional assumptions and only used the principal component and canonical correlation. Also, it contained the function of 3 factors (tenderness, juiciness and flavor-likeness) and accurate classification rate was similar with the other discriminant methods. Therefore, the canonical discriminant analysis was the most proper method to analyze the palatability grading of Hanwoo beef.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.201-208
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• 2021

This study aims to provide the relevant basis upon which prediction of dyslipidemia should be made based on body information. Using the National Health Insurance big data (3,312,971 people) canonical correlation analysis was performed between body information and lipid-profile. Body information included age, height, weight and waist circumference, while the lipid-profile included total cholesterol, triglycerides, HDL cholesterol and LDL cholesterol. As a result, when the waist circumference and the weight are large, triglycerides increase and HDL cholesterol level decreases. In terms of age, weight, waist circumference, and HDL cholesterol, the canonical variates (the degree of influence) were significantly different according to sex. In particular, the canonical variate was dramatically changed around the forties and fifties in women in terms of weight, waist circumference, and HDL cholesterol. The canonical correlation results of the health care big data presented in this study will help construct a predictive model that can evaluate an individual's health status based on body information that can be easily measured in a non-invasive manner.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.885-894
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• 2006

The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

• Journal of dental hygiene science
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• v.10 no.5
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• pp.307-314
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• 2010

This study aimed to measure such features of emotional responses perceived by students as learning climate, department living stress, and perceived helplessness to analyze their effects on major satisfaction among students at the department of dental hygiene; to do this, a survey was conducted with 431 students, regardless of college year, who were at the department of dental hygiene in four colleges in Gyeonggi Province, Daejeon, and Chungcheong Province. An existing emotion scale which went through the generalization process was used to draw a multiple model in the combination form in order to collect emotional factors affecting college students' satisfaction with their major, which had existed as a hypothetical proposition, and make overall interpretation of relevance through the explainable, predictable modeling process by measuring emotional factors and phenomenal description of the level of general perception. The results showed that major satisfaction was very significantly affected by emotional features among students at the department of dental hygiene, which needs to be treated as an important factor to enhance expertise related to major learning and improve students' living.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.88-94
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• 2014

The seasonal predictability of the intensity of the Northeast Asian summer monsoon is low while that of the western North subtropical high variability is, when state-of-the-art general circulation models are used, relatively high. The western North Pacific subtropical high dominates the climate anomalies in the western North Pacific-East Asian region. This study discusses the predictability of the western North Pacific subtropical High variability in the National Centers for Environmental Prediction Climate Forecast System (NCEP CFS). The interannual variability of the Northeast Asian summer monsoon is highly correlated with one of the western North Pacific subtropical Highs. Based on this relationship, we suggest a seasonal prediction model using NCEP CFS and canonical correlation analysis for Northeast Asian summer precipitation anomalies and assess the predictability of the prediction model. This methodology provides significant skill in the seasonal prediction of the Northeast Asian summer rainfall anomalies.