• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.55-62
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• 2020

To estimate headwater stream temperature with seasonal variations, we analyzed precipitation, runoff and air temperature in experimental forest of Kangwon National University, Gangwon-do (2017~2018 years). The daily mean value of headwater stream temperature for spring was 6.9~17.7℃ and correlated with air temperature, that for summer and fall were 12.2~26.3℃ and 3.6~19.3℃, correlated with air temperature and runoff. Based on seasonal variations, we applied for stepwise multiple linear regression analyses to estimate headwater stream temperature with seasonal variations. The equations were headwater stream temperature(WT)_spring=(0.553×Air temperature)+(0.086×Runoff)+4.145 (R²=0.505; p<0.01), WT_summer=(0.756×Air temperature)+(-0.072×Runoff)+2.670 (R²=0.510; p<0.01), and WT_fall=(0.738×Air temperature)+(0.028×Precipitation)+2.660 (R²=0.844; p<0.01). The coefficient of determination (R²) was greater than when it was estimated by air temperature in all seasons and progressively increased from spring to winter. Therefore, we indicated difference on estimated magnitude of stepwise multiple linear regression, due to effects on headwater stream temperature of different environmental factors with seasonal variations. Furthermore, temporal factors with spatial characteristics (e.g., river versus headwater stream) could be recommended for estimating headwater stream temperature.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.345-355
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• 2007

PLS methods are suited for regressing q-variate Y variables on p-variate X variables even in the presence of multicollinearity problem among X variables. Consequently, they are useful for analyzing datasets with smaller number of observations compared to the number of variables, such as NIR(near-infrared) spectroscopy data in chemometrics. In this study, we propose two visualizing methods of p-variate X variables and q-variate Y variable that can be used in connection with PLS analysis.

• The korean journal of orthodontics
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• v.39 no.2
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• pp.112-119
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• 2009

Objective: To develop a mixed dentition analysis method in consideration of the normal variation of tooth sizes. Methods: According to the tooth-size of the maxillary central incisor, maxillary 1st molar, mandibular central incisor, mandibular lateral incisor, and mandibular 1st molar, 307 normal occlusion subjects were clustered into the smaller and larger tooth-size groups. Multiple regression analyses were then performed to predict the sizes of the canine and premolars for the 2 groups and both genders separately. For a cross validation dataset, 504 malocclusion patients were assigned into the 2 groups. Then multiple regression equations were applied. Results: Our results show that the maximum errors of the predicted space for the canine, 1st and 2nd premolars were 0.71 and 0.82 mm residual standard deviation for the normal occlusion and malocclusion groups, respectively. For malocclusion patients, the prediction errors did not imply a statistically significant difference depending on the types of malocclusion nor the types of tooth-size groups. The frequency of prediction error more than 1 mm and 2 mm were 17.3% and 1.8%, respectively. The overall prediction accuracy was dramatically improved in this study compared to that of previous studies. Conclusions: The computer aided calculation method used in this study appeared to be more efficient.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.2
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• pp.108-117
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• 2020

This study takes the Gyeongju Historic Areas Daereungwon Area as the research object, uses the Virtual Walkthrough method for virtual experience and evaluation, the visual characteristics were analyzed. To analyze landscape visual characteristics and to find out the relationship between image factors and visual preferences, the factor analysis and multiple regression analysis were conducted. The results are as follows: the results of preference analysis of the Daereungwon Area show that the preference of scene3 where located on the western boundary of Noseo-rl tumuli got the highest score, and the preference score of scene5 where located on the western boundary of Daereungwon less than three points. The results of factor analysis of visual characteristics, three factors were analyzed: regularity factor, spatiality factor and historical factor. The analysis of variance and multiple regression analysis results of the relationship between factor scores and visual preferences show that regularity factor was analyzed as the biggest factor that affects the visual preference of the Historical-cultural landscape Daereungwon Area. Virtual Walkthrough method has a strong three-dimensional and strong production of the real landscape scene, it's an effective method in landscape analysis. The results of research provides data and information for improving the visual quality of Historical-cultural landscape and it's expected to be applied in the future of landscape planning.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.87-97
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• 2008

The traditional trip-based modeling approach has assumed that a trip is generated for a purpose. However, the approach has not considered trips as a set of connected trips nor has it considered trip chaining. The purpose of this study is to identify general characteristics of trip chaining, and to explore relationships between trip purposes and trip chains using multivariate regression models. The data for this study come from the 2006 Seoul household travel diary survey. It is found that simple trip chains are dominant phenomena, and socio-economic characteristics such as occupation, income, age, and gender are closely related to types of trip chains. People aged less than 20, females, or high-income people are more likely to have a higher number of home-based trip chains. In addition, commute and school trips for workers and students respectively tend to be strongly associated with simple trip chains, while shopping and leisure trips for housewives tend to be related to simple trip chains.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.359-362
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• 2004

수중에서 사용되는 음향변환기의 성능은 사용환경 뿐만 아니라 많은 설계변수들의 조합에 의해 결정되며, 이들 설계변수들의 영향은 서로 선형 독립적이지 않은 경우가 대부분이다. 따라서 음향변환기의 최적성능을 구현하기 위해서는 각 설계변수들의 개별영향 뿐만 아니라 강호작용에 의한 영향을 동시에 고려하여야 한다. 본 연구에서는 tonpilz 변환기에 대하여 유한 요소 해석을 통하여 설계변수들이 중심 주파수, 대역폭, 음압 및 충격력에 미치는 영향을 파악하였고, 그 결과들의 통계적 다중 회귀분석을 통하여 중심 주파수 대역폭 음압 및 충격력을 이들 설계변수들의 함수로 도출하였다. 나아가 제한 최적화 기법을 이용하여 주어진 사용 환경에서 동작하면서 최대 음압을 구현할 수 있는 변환기의 최적 구조를 자동으로 결정할 수 있는 프로그램을 개발하였다. 본 연구에서 개발된 최적화 프로그램은 다중 설계변수들의 상호효과를 충분히 반영할 수 있으며, 유사한 기능의 여타 음향변환기 설계에 직접 응용이 가능할 것이다.

• Journal of Families and Better Life
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• v.12 no.1
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• pp.49-61
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• 1994

본 논문은 아동의 도덕성 발달에 영향을 미치는 요인들에 관한 연구이다. 아동적 도 덕성 발달에 관한 경험적 모델은 기존 경험적 연구들을 기초로하여 설정되었다. 모델에 포 함된 변인들은 미시체계환경 중간체계환경 거시체계환경으로 범주화 하였다. 미시체계환경 은 심리적으로 근접하기 때문에 어린이의 도덕성 발달에 다른 체계보다 더 강한 영향을 미 치리라 가정하였다 다중회귀분석기법으로 아동의 도덕성 발달에 영향을 미치는 요인의 순효 과를 검증한 결과는 다음과 같았다. (1) 모델에서 대부분 이론적 변인들은 아동의 도덕성 점 수에 유의미했으나 (2) 그 중에서는 미시체계환경은 아동의 도덕성 발달에 가장 유의미한 변인으로 나타났다. 특히 부모와의 의사소통정도는 아동의 도덕성발달에 대단히 중요한 요 인으로 나타났다.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.441-453
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• 2008

We analyzed Korean professional basketball and baseball players salary under the assumption that it depends on the personal records and contribution to the team in the previous year. We extensively used data visualization tools to check the relationship among the variables, to find outliers and to do model diagnostics. We used multiple linear regression and regression tree to fit the model and used cross-validation to find an optimal model. We check the relationship between variables carefully and chose a set of variables for the stepwise regression instead of using all variables. We found that points per game, number of assists, number of free throw successes, career are important variables for the basketball players. For the baseball pitchers, career, number of strike-outs per 9 innings, ERA, number of homeruns are important variables. For the baseball hitters, career, number of hits, FA are important variables.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.107-117
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• 1999

A comparison of a neural network approach with the conventional statistical methods, multiple regression and band ratio analyses, for the estimation of water quality parameters in presented in this paper. The Landsat TM image of Lake Daechung acquired on March 18, 1996 and the thirty in-situ sampling data sets measured during the satellite overpass were used for the comparison. We employed a three-layered and feedforward network trained by backpropagation algorithm. A cross validation was applied because of the small number of training pairs available for this study. The neural network showed much more successful performance than the conventional statistical analyses, although the results of the conventional statistical analyses were significant. The superiority of a neural network to statistical methods in estimating water quality parameters is strictly because the neural network modeled non-linear behaviors of data sets much better.

• Proceedings of the Korean Society for Information Management Conference
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• 2016.08a
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• pp.39-43
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• 2016

본 연구의 목적은 공공도서관 직원의 독서활동이 직무만족도와 조직몰입도에 어떠한 영향을 미치는지를 분석하는 것이다. 이는 기업에서 직원의 독서활동을 활성화하여 조직의 경쟁력을 높이는 경영기법인 독서경영과 문화경영이 직원의 직무만족과 조직몰입을 높인다는 선행연구들의 결과를 기반으로 하였다. 이에 서울시 동북부 지역 지자체 운영 공공도서관의 직원을 대상으로 설문조사를 실시하였으며, 신뢰도 분석과 다중회귀분석을 통하여 데이터를 분석하였다. 분석 결과, 공공도서관 직원의 독서량, 독서시간이 직무자체 만족도에 유의한 영향을 미쳤으며, 이용자 독서모임 참여 기간이 사회적 인식 만족도에 영향을 미치는 것으로 나타났다. 조직몰입에 대해서는 독서시간이 정서적 몰입도에, 이용자 독서모임 참여 기간은 지속적 몰입도와 규범적 몰입도에 유의한 영향을 미치고 있었다.