• 한국수자원학회논문집
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• 제49권5호
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• pp.399-410
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• 2016

유속계수는 상수도 설계, 운영, 유지관리 등의 과정에서 항상 현장 실정이 고려된 값이 사용되어야 한다. 본 연구는 광역상수도 정밀안전진단 과정에서의 174개 실측자료를 바탕으로 유속계수와 주요 인자 간의 관계를 통계적 기법을 활용하여 분석하였다. 이들 관계를 분석하기 위해서 교차분석, 일원배치 분산분석, 상관분석 등을 수행하였으며, 그 결과 유속계수와 사용년수 및 관경이 높은 상관관계를 나타내고 여러 범주형 자료 형태 영향인자 중에 내부도장재가 상대적으로 유속계수에 많은 영향을 주는 것으로 검토되었다. 반면 다중회귀분석의 결과에서는 사용년수, 관경 및 수종이 중요한 영향인자인 것으로 검토되었다. 군집분석 결과, 유속계수는 기본적으로 사용년수 약 20년, 관경 1500mm를 기준으로 분류되는 경향이 있었으며, 유속계수는 전반적으로 사용년수에 많은 영향은 받으나 대구경 관에서는 상대적으로 사용년수보다 관경에 많은 영향을 받는 것으로 검토되었다. 마지막으로 본 연구에서는 회귀분석과 군집분석을 사용하여 유속계수 산정식들을 제안하였으며, 이러한 추정식들은 추후 광역상수도의 유속계수 결정 및 사용 시에 판단기준이 될 수 있을 것으로 판단된다.

• 전기전자학회논문지
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• 제20권1호
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• pp.94-102
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• 2016

본 논문에서는 기계학습 알고리즘을 이용하여 다중물리(Multi-physics) 시뮬레이션의 반복 횟수를 획기적으로 줄일 수 있는 다중물리해석 예측 방법을 제안한다. 기존의 다중물리해석 시뮬레이션의 경우 소요되는 시간과 노력을 줄이기 위해 시뮬레이션 자체에 대한 방법과 환경 개선에 초점이 맞추어져 있으나 본 논문에서는 다중물리 시뮬레이션 결과를 기계학습 알고리즘으로 학습하여 추가적인 시뮬레이션을 수행하지 않고 학습된 기계학습 알고리즘을 사용하여 수십분에서 수시간에 걸리는 다중 물리 해석과 유사한 결과를 수초 내에 예측할 수 있음을 보였다. 기계학습 알고리즘 간의 성능을 비교하여 다중물리해석에 적합한 기계학습 알고리즘을 확인하였으며 가장 우수한 성능을 보인 가우시안 프로세스 회귀(Gaussian Process Regression)의 경우 100개 이하의 학습 샘플만으로도 우수한 예측 결과를 얻어낼 수 있음을 확인하였다. 제안하는 방식을 통해 시뮬레이션을 하고자 하는 모델의 형상이나 재질이 변경될 경우 기존의 시뮬레이션 결과로 학습된 알고리즘이 있다면 시뮬레이션을 반복 수행하기 전에 알고리즘을 이용하여 결과를 예측할 수 있어 시뮬레이션의 반복 횟수를 줄일 수 있을 것으로 기대한다.

• 수산해양교육연구
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• 제21권3호
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• pp.409-419
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• 2009

The purpose of this study was the examination of delinquency according to, narcissism, self-esteem, hostility and alienation of juvenile. For this, setting 172 students of an academic high school and 366 students of a vocational school(total 538) as the object of this study, the measures of Narcissistic Personality Scales, Self-Esteem Scales, Alienation Scales, and Delinquency Scales were inquired. The method of statistical analysis about these materials was composed of Two-way Analysis of Variance, One-way Analysis of Variance, and Multi-regression Analysis by using SPSS 10.0. The result, when delinquency was examined according to narcissism and self-esteem, in the case that narcissism was highest, self-esteem was lowest, delinquency was highest. When delinquency was examined according to narcissism and hostility, in the case that narcissism was highest, hostility was highest, delinquency was highest. When delinquency was examined according to narcissism and alienation, in the case that narcissism was highest, alienation was highest, delinquency was highest. And, when Multi-regression Analysis about the effect of narcissism, self-esteem, hostility and alienation on delinquency was administrated, the variation that affected delinquency significantly was narcissism, hostility and alienation. That is, we could look forward that the more narcissists feel hostility and alienation, the higher they have delinquency.

• 융합정보논문지
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• 제11권10호
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• pp.322-331
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• 2021

본 연구는 간호대학 신입생의 다문화수용성 수준을 파악하고 이에 영향을 주는 요인을 분석하고자 하였다. 연구 방법은 W 시 소재 K 대학 간호학과 1학년 학생 410명을 대상으로 2021년 3월 1일- 28일까지 설문조사하였고, 오픈소스 통계패키지 R을 이용하여 빈도, 신뢰도 분석, t-test, ANOVA, correlation, Multiple regression을 시행하였다. 연구결과 간호대학 신입생의 다문화수용성 수준은 평균 77.36점으로 다소 높은 다문화 수용성 능력을 가지는 것으로 나타났고, 다문화수용성 관련 요인의 영향을 분석한 결과 한국인 인정요건(𝛽=0.34, p<.001), 이주민에 대한 지각된 위협 인식(𝛽=0.29, p<.001), 다문화 교육 경험(𝛽=0.14, p<.001), 다문화 교육 적정 연령 인식(𝛽=0.20, p<.001)은 유의미하였다. 이러한 결과에 따라 간호대학생의 다문화 관련 정규 교육과정 및 프로그램을 개발하고 적극적으로 활용해야 할 필요가 있다.

• 한국농공학회논문집
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• 제61권5호
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• pp.101-108
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• 2019

The domestic duck industry is the sixth-largest among the livestock industries. However, 34.3% of duck houses were the duck houses arbitrarily converted from plastic greenhouses. This type of duck house was difficult to properly manage internal air temperature and humidity environment. Humidity environment inside duck houses is an important factor that directly affects the productivity and disease occurrence of the duck. Although the humidity environments of litters (bedding materials) affect directly the inside environment of duck houses, there are only few studies related to humidity environment of litters. In this study, evaporation rates from litters were evaluated according to air temperature, relative humidity, water contents of litters, and wind speed. The experimental chamber was made to measure evaporation rates from litters. Temperature and humidity controlled chamber was utilized during the conduct of the laboratory experiments. Using the measured data, a multi linear regression analysis was carried out to derive the calculation formula of evaporation rates from litters. In order to improve the accuracy of the multi linear regression model, the partial vapor pressure directly related to evaporation was also considered. Variance inflation factors of air temperature, relative humidity, partial vapor pressure, water contents of litters, and wind speed were calculated to identify multicollinearity problem. The Multiple $R^2$ and adjusted-$R^2$ of regression model were calculated at 0.76 and 0.71, respectively. Therefore, the regression models were developed in this study can be used to estimate evaporation rates from the litter of duck houses.

• Journal of Information Technology Applications and Management
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• 제17권3호
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• pp.135-150
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• 2010

Interactivity has been referred to as an important element promoting students' active participation in virtual classes. Assuming that interactivity cannot be defined by a single dimension, this study proposes multi-dimensional interactivity. Multi-dimensional interactivity includes all types of interactivity in e-learning. This study explored multi-dimensional interactivity which affects learners' satisfaction with e-learning. Data were collected from 132 students who had attended e-learning courses and the relationship between multi-dimensional interactivity and learners' satisfaction levels were tested through regression analysis. The result of this study showed that mechanical, reactive, and creative interactivity were positively related to learners' satisfaction. However, social interactivity seemed not to be related to learners' satisfaction. This study provides new insights on interactivity and verifies the importance of the multi-dimensional interactivity. The result of this study is expected to provide practical implications for interactivity strategies in e-learning.

• 대한가정학회지
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• 제45권1호
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• pp.51-61
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• 2007

The purpose of this study was to examine if multi-shop's store image affects store loyalty and brand switching. Two hundred fifty females and males who have purchased fashion products in multi-shop participated in this survey. For data analysis, descriptive statistics, factor analysis, Pearson's correlation and regression analysis were used for this study. The results were as followed. First, respondents' the most favorite multi-shop was MUE, followed by Boon the shop and ABC mart. Second, store image was classified into four factors such as store atmosphere, service of store, store recognition and product variety. Store loyalty was classified into five factors such as emotional relationship, pursue of novelty, trust about salesperson, satisfaction about service, and active loyalty. Third, result revealed that 'product variety' and 'store atmosphere', 'store recognition', 'service of store' accounted for 39.6% of the explained varience in store loyalty, and 'store recognition' accounted for 4% of the explained varience in brand switching behavior, while 'trust about salesperson', 'pursue of novelty' accounted for 5% of the explained varience in brand switching behavior. Based on these results, multi-shop's fashion marketing strategy would be suggested.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.393-393
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• 2021

도시화는 도시 호우 유출 발생으로 인한 수질 악화를 초래했고 문제를 해결하기 위해 본 연구에서는 보다 정확한 설계를 위해 그린인프라(Green Infrastructure, GI)의 구조적 특성과 수문학적인 특성을 이용해 어떤 인자들이 설계에 필요한지 상관관계를 통해 분석하였다. GI의 종류 중 저류지와 저류연못의 총부유사량(Total Suspended Solids, TSS)와 총인 (Total Phosphorous, TP)의 유입수, 유출수, 비점오염원 농도, 수문학적인 특성 그리고 GI의 구조적 특성을 Ordinary Least Squares regression(OLS)과 Multi Linear Regression(MLR) 방법을 적용하였다. GI의 구조적인 특성은 한 BMP마다 달라지지 않으나 호우사상의 데이터 개수에 의한 편향이 있을 수 있다. 이런 문제를 해결하기 위해 일정한 범위를 가지고 무작위로 데이터를 추출하는 방법과 이상치를 제외하는 방법을 사용하여 모델에 적용하였다. 이러한 OLS와 MLR 모델들의 정확도를 PBIAS(Percent Bias), NSE(Nash-Sutcliffe efficiency), RSR(RMSE-observations standard deviation ratio)을 통해 분석할 수 있다. 연구 결과 유입수의 비점오염원의 농도뿐만 아니라 수문학적 특성과 GI의 구조적 특성이 함께 들어갈 시 더 좋은 상관관계를 가지고 있음을 알 수 있다. 저류지가 저류연못보다 모델의 성능평가 면에서 좋은 값을 가지고 있지만 특성별 상관관계는 저류연못이 더 뚜렷한 결과를 보여준다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.116-119
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• 2005

As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.