• 복식
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• 제64권6호
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• pp.161-175
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• 2014

This paper investigates the differences between characteristics of street fashions due to regional and cultural differences in southern and northern region of China. Beijing and Shenzhen were chosen as representative cities for the two areas. Empirical research and literature study were performed for this study. Empirical studies were performed by using a total of 708 images of dresses, which were collected through direct imaging. Through discussion with experts, the collected data were classified into five categories; Modern trendy, Romantic, Easy casual, Ethnic, and Classical/Traditional. The data was analyzed by using cross tabulation and frequency analysis. Content analysis for each category was also conducted. As a consequence of this study, a significant difference between Beijing and Shenzhen were observed. As a city, which puts emphasis on practicality and modernity, Beijing showed a higher frequency of modern and trendy style than the other city. On the other hand, Shenzhen showed a higher frequency of romantic style and was distinguished as a city of femininity and decorative preference of fashion style. This study intends to contribute to the academic community of Chinese fashion and to help Korean clothing companies to be launched in Chinese market in the future.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• Journal of Forest and Environmental Science
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• 제32권2호
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• pp.149-157
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• 2016

Understanding regional characteristics in forest fire occurrence is important to establish effective forest fire prevention policy in Korea. This study analyzed the characteristics of forest fires occurred in 16 administrative districts for recent 25 years (1990~2014) to examine regional characteristics in forest fire occurrence. Forest fire occurrence reflects regional characteristics depending on climatic factors as well as region's society-cultural factors. Results showed that the first cause of forest fire occurrence was carelessness by human activities throughout all administrative districts, however, the second cause depends on regional characteristics. As the results of forest fire occurrence period analyzed for 10 days, the most forest fires occurred in the southern region during January to March, while forest fires in the northern region occurred mostly during March to April. We classified forest fire occurrence patterns into three types (centralized: Gyeonggi-do, dispersal: Busan, horizontally distributed: Gyeongsangnam-do) by multi-temporal analysis for forest fire occurrence period.

• 한국병원경영학회지
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• 제22권3호
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• pp.46-60
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• 2017

The purpose of this study is to analyze the difference of productivity according to environmental factors among 25 Regional base public hospitals. Also this study is to propose a method to improve the productivity of Regional base public hospitals in the future by improving the public performance and stable management performance by studying the productivity variables affecting profitability. The survey period was based on the last three years, and 25 Regional base public hospitals were selected for the survey. The dependent variable is the total capital medical marginal profitability and the medical profit marginal profitability which are the indicators of profitability. The independent variable, productivity, is classified into three indicators: capital productivity, labor productivity, and value added productivity. The ANOVA analysis method was used to analyze the productivity difference according to the frequency factor and the environmental factors of the Regional base public hospitals. Finally, we conducted a hierarchical regression analysis to examine the productivity variables affecting profitability. The results of this study showed that there were differences in productivity due to environmental factors such as hospital size, competition in the local medical market, and differences in management performance. The difference in productivity and profitability depending on the environmental factors suggests that it is difficult for Regional base public hospitals in each regional base to perform a balanced public service. In order to overcome this, it is necessary to provide balanced medical services such as government financial support expansion, regional medical demand forecasting and facility infrastructure construction.

• 한국수자원학회논문집
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• 제41권3호
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• pp.325-340
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• 2008

본 연구는 저수량 지역 빈도분석(regional low flow frequency analysis)을 수행하기 위하여 일반최소자승법(ordinary least squares method)을 이용한 Bayesian 다중회귀분석을 적용하였으며, 불확실성측면에서의 효과를 탐색하기 위하여 Bayesian 다중회귀분석에 의한 추정치와 t 분포를 이용하여 산정한 일반 다중회귀분석의 추정치의 신뢰구간을 비교분석하였다. 각 재현기간별 비교결과를 보면 t 분포를 이용하여 산정된 평균 추정치와 Bayesian 다중회귀분석에 의한 평균 추정치는 크게 다르지 않았다. 그러나 불확실성 측면에서 평가해볼 때 신뢰구간의 상한추정치와 하한추정치의 차이는 Bayesian 다중회귀분석을 사용한 경우가 기존 방법을 사용한 경우보다 훨씬 작은 것으로 나타났으며, 이로부터 저수량(low flow) 지역 빈도분석을 수행하는 경우 Bayesian 다중회귀분석이 일반 회귀분석보다 불확실성을 표현하는데 있어서 우수하다는 결과를 얻을 수 있었다. 또한 낙동강 유역에 2개의 미계측 유역을 선정하고 구축된 Bayesian 다중회귀모형을 적용하여 불확실성을 포함한 미계측 유역에서의 저수량(low flow)을 추정하였으며 이와 같은 방법이 미계측 유역에서의 저수(low flow) 특성을 나타내는 데 있어서 효과적일 수 있음을 입증하였다.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2007년도 정기총회 및 학술발표대회
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• pp.575-578
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• 2007

The objective of this study is to analyze the regionalization of point rainfall by statistical methods for regional frequency analysis of the rainfall. The rainfall data used in this study are annual maximum rainfall at 57 stations during the period of more than 30 years for 12 durations(10min, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24hr) in Korea. The Mann-Whitney U test, Kruskal-Wallis one-way analysis of variance of nonparametric test the principal component and the cluster analysis have been performed to analyze the regionalization of rainfall. The results of this study are as follows; (1) The region which hydrological homogeneous is accepted does not exist for whole duration in Korea. (2) The result of nonpametric test shows that hydrological homogeneous regions of point rainfall are divided by 5 regions. (3) In case of cluster analysis hydrological homogeneous regions of point rainfall are divided by 6 regions and 4 other areas.

• 한국수자원학회논문집
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• 제49권5호
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• pp.451-458
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• 2016

본 연구에서는 미계측유역에서의 빈도홍수량을 추정하기 위해 지역홍수빈도분석의 표준방법인 지수홍수법을 이용하였다. 이를 위해 충주댐 상류유역을 대상으로 공간확장한 22개 지점의 연최대홍수량 자료을 활용하였으며, 구축된 다지점의 자료계열을 이용하여 지수홍수법의 주요인자인 평균홍수량의 지역화 과정를 수행하였다. 지역화를 위한 방법으로는 홍수량과 유역면적과의 관계가 멱함수 법칙(power law)를 따른다는 이론에 근거한 경험관계를 유도하였다. 충주댐 상류유역 전체를 하나의 그룹, 3개의 중권역을 각각 하나의 그룹으로 구분하여 분석하였다. 도출된 결과에 따르면 평균홍수량과 유역면적과의 관계를 멱함수 법칙으로 설명할 수 있었다. 또한, 미계측 지점의 홍수량 추정시에는 가까운 계측지점 즉, 직상하류 유역의 비유량의 관계를 사용하는 것이 타당함을 증명하였다. 따라서, 미계측 유역을 위한 지역빈도해석은 지역홍수빈도해석 절차 자체도 중요하지만, 지역의 세밀한 구분과 그에 따른 지역화 경험관계 개발과정도 중요한 절차임을 확인할 수 있었다.

• 대한토목학회논문집
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• 제37권1호
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• pp.29-41
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• 2017

확률강수량 산정은 하천관리, 수공구조물 설계 및 위험도 분석에 있어 중요한 기초적인 자료 중 하나이다. 실무에서는 대표지속시간에 대해서 지점빈도해석을 통해 확률강수량을 추정하고 이를 지속시간에 대해서 회귀분석을 실시하여 IDF (intensity-duration-frequency) 곡선을 작성한다. 이들 IDF곡선을 활용하여 기타 지속시간에 대해서는 내삽 또는 외삽으로 보간 하여 확률강수량 추정이 이루어지고 있다. 우리나라의 경우 상대적으로 자료 연한이 짧은 점을 고려한다면, 보다 정확하고 신뢰성 있는 확률강수량 산정 기법의 필요성이 대두되고 있다. 이러한 이유로 본 연구에서는 Bayesian GLM 모형을 통하여 자료의 확률분포 매개변수의 Scaling 특성을 고려할 수 있는 지역빈도해석 모형을 개발하였다. 모형 적용결과 개별지점에서 효과적인 매개변수 추정뿐만 아니라, 유역전체의 특성을 대표하는 매개변수 추정이 가능하였다. 본 연구결과를 통해 도출된 IDF 곡선은 향후 다양한 수자원분야의 기초자료로 활용될 수 있을 것으로 기대되며, 미계측유역 또는 지속시간별 자료가 불충분한 지역에 대해서도 활용이 가능할 것으로 판단된다.

• 물과 미래
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• 제50권1호
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• pp.18-25
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• 2017

• 한국수자원학회논문집
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• 제33권S1호
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• pp.157-163
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• 2000