• Spatial Information Research
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• v.7 no.2
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• pp.255-269
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• 1999

This is an experimental study to translate the Korean digital topographic maps into distributable information-hide objects, which are designed with object-oriented development's key features ; encapsulation, polymorphism, inheritance, In order to achieve this goal , the characteristics of the data mode and inter-relationships of digital topographic maps are investigated . As a result, it is revealed that the current Korean digital topographic maps, which is organized into so many individual layers of mixed spatial and attributed data, have to explicit and concrete hierarchies in spatial data model and data definition . Due to this limitation , data layer stage and object class stage are integrated. And ISCO(the is-computer -of relationships) mechanism is mainly used to develop the objects of digital topogrpahic maps, which is implemented with spatial primitive classes. the designed objects are coded with JAVA and then testified in web interface.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.347-362
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• 2006

In this study, a 2-D flood inundation model was developed to evaluate the impact of levee failure in a natural basin for flood analysis. The model was applied to analyze the inundation flow from the levee break of Gamcheon river during the typhoon Rusa on October 31 through September 1, 2002. To verify the simulated results, wide range field surveys have been performed including the collection of NGIS database, land use condition, flooded area, and flow depths. Velocity distributions and inundation depths were presented to demonstrate the robustness of the model. Model results have good agreements with the observed data in terms of flood level and flooded area. The model is able to compute maximum stage and peak discharge efficiently in channel and protected lowland. Methodology considering radar-rainfall estimation using cokriging scheme, flood-runoff and inundation analysis in this study will contribute to the establishment of the national integrated flood disaster prevention system and the river or protect lowland management system.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.30-30
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• 2011

현재 우리나라는 수자원의 안정적인 확보와 효율적인 관리를 위하여 20년 단위의 수자원장기 종합계획을 수립하고 있으며, 향후 발생가능한 물의 과부족을 평가하는 물수급 분석을 통해 최적의 수자원관리 계획을 수립하고 있다. 하지만, 현재의 수자원장기종합계획에서는 미래 물수급 전망을 단일 값으로 제시하는 확정론적 기법을 적용하고 있으며, 과거 유출패턴이 미래에도 똑같이 재현된다는 가정 하에 물수급 분석을 수행한다. 이는 기후변화의 불확실성에 따른 물공급 시나리오의 다양성을 고려하지 않는 것을 뜻하며, 현재 다양한 GCM(Global Circulation Model)을 통해 제시되고 있는 미래 수자원 변동 전망을 물수급 분석에 반영하지 않고 있음을 말해 주는 것이다. 따라서, 본 연구에서는 기후변화에 따른 미래 자연유출량의 불확실성을 반영할 수 있는 물수급 전망 기법을 제안코자 한다. 먼저 국내유역에 적합한 GCM 시나리오들을 선정하였으며, 스케일상세화(downscaling) 기법을 통해 한강유역 중권역별 강우량, 증발산량 등의 일 단위 미래 수문기상 자료를 구축하였다. 다음으로, 앞서 구축한 기상자료를 개념적 강우-유출 모형인 TANK 모형에 입력하여 중권역별 미래 유출량을 산정하여 각 시나리오별 미래 유출량 변화를 전망하였다. 물수급 분석 모형으로는 한국건설기술연구원에서 미국 SEI-B와 제휴하여 개발한 통합수자원평가계획모형인 K-WEAP을 사용하였으며, 물수급 분석 결과를 바탕으로 중권역별 물공급 지수를 산정하여 제시하였다. 현재 대부분의 기후변화 연구에서는 GCM 시나리오를 직접 적용한 결과를 바탕으로 미래 수자원 전망 결과를 제시하고 있는데, 여기에는 GCM 자체의 불확실성은 물론 과거 관측 자료를 입력자료로 하는 기존 연구 방법론으로 부터의 급진적인 변화에 따른 연구 연속성의 문제 또한 존재한다. 따라서 본 연구에서는 GCM 유출량 시나리오의 직접 적용 대신 과거 유출 시나리오별 가중값을 산정하여 반영함으로서 GCM 모의 결과의 불확실성을 저감하는 방안을 제안하였다.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.569-578
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• 2020

By estimating conditional quantile functions of the response, quantile regression (QR) can provide comprehensive information of the relationship between the response and the predictors. In addition, kernel quantile regression (KQR) estimates a nonlinear conditional quantile function in reproducing kernel Hilbert spaces generated by a positive definite kernel function. However, it is infeasible to use the KQR in analysing a massive data due to the limitations of computer primary memory. We propose a divide and conquer based KQR (DC-KQR) method to overcome such a limitation. The proposed DC-KQR divides the entire data into a few subsets, then applies the KQR onto each subsets and derives a final estimator by aggregating all results from subsets. Simulation studies are presented to demonstrate the satisfactory performance of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.396-396
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• 2021

본 연구의 목적은 HSPF(hydrological simulation program-FORTRAN) 모형을 이용하여 기후변화에 따른 남한의 유출량 변화를 분석하는 데 있다. 상세화 작업을 수행한 13개의 GCM(global climate model)을 이용하여 기후변화 시나리오를 구축하여 미래 유출량을 추정하는 데 사용하였다. 미래 유출량을 생산하기 위해 앞에서 선정한 13개 GCM을 사용하여 수문기상자료를 구축하였다. 모의기간은 S0: reference period (1976-2005), S1: near future period (2011-2040), S2: mid-century period (2041-2070), S3: distance future period (2071-2100) 총 4개로 구분하였다. 공간적으로는 109개 중권역을 대상으로 HSPF 모형을 모의한 다음 최종적으로 남한을 대상으로 분석하였다. HSPF 모형의 매개변수 보검정은 장기간의 일별유량자료가 구축된 총 6개 댐 상류유역을 선정하여 수행하였다. 유출량은 기본적으로 강수량과 증발산량에 굉장히 영향을 받으며, 미래 수문기상자료를 분석한 결과 남한의 강수량과 증발산량이 모두 증가하는 경향을 보인다. 다만 강수량의 상대적인 변화가 증발산량의 변화보다 크기 때문에 전반적으로 미래 유출량을 증가하는 것으로 분석되었다. 특히 미래 강수량은 미래 변동성이 굉장히 큰 특징을 가지고 있으며 이러한 이유로 미래 유출량의 변동성도 큰 것으로 분석되었다. 계절적으로 살펴보면 여름과 가을의 미래 유출량이 증가하고 겨울에는 감소하는 것으로 분석되었다. 가을과 겨울의 변동성이 매우 큰 특징을 보이며 미래 극한 홍수와 가뭄의 출현 빈도가 높아질 것으로 보인다. 본 연구 결과는 남한의 기후변화 적응 대책을 수립하는 데 있어 기초자료로 활용할 수 있을 것으로 사료된다.

• Journal of Korean Home Economics Education Association
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• v.26 no.1
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• pp.1-16
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• 2014

The purpose of this research is to develop a theme-based integrated teaching/learning plan in clothing, food, and housing in home economics and to apply the developed process in classes for evaluation in order to identify the suitability in schools. The theme-based integrated teaching/learning plan developed on the basis of textbooks consist four sub-themes; choosing($1^{st}$ and $2^{nd)$ lessons), using($3^{rd}$ lesson), processing ($4^{th}$ lesson), and alternatives($5^{th}$ and $6^{th}$ lessons) under the main theme of 'green family life'. The results from 20 individual and group activities showed that the students actively solved the problems when the presented cases were related to their own lives or experiences. The opportunity to implement green life through activities motivated students' willingness to proceed in real life. However, it is vital to assist integrated thinking through various examples before beginning due to students with difficulties connecting the issue from one area to the other during the problem-focused activity. The students' ability to solve the activity workbook had been improved as the lessons continued. From the survey questions on the theme-based integrated lessons, all items associated with integration of clothing, foods, and housing were positively responded. Also, questions regarding general understanding, suitability and satisfaction on the teaching/learning process were marked positive. The conclusion could be that the integrated theme related to clothing, food, and housing in our life would be appropriate for green family life. The theme-based integrated teaching/learning plan is effective in understanding the occurrence of green family life in relation with clothing, food, and housing, identifying the practical ideas implementing green life in those areas, and improving the integrated ability to solve the green life related problems. However, this research has its weakness in generalizing the results due to its limited survey respondents and post-evaluation being the only assessment conducted.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.105-114
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• 2016

With approximately 20 million transportation card data entries of the metropolitan districts being generated per day, application of the data to management and policy interventions is becoming an issue of interest. The research herein attempts a model of the possibility of dynamic demand change predictions and its purpose is thereby to construct a Dynamic Passengers Trip Assignment Model. The model and algorithm created are targeted at city rail lines operated by seven different transport facilities with the exclusion of travel by bus, as passenger movements by this mode can be minutely disaggregated through card tagging. The model created has been constructed in continuous time as is fitting to the big data characteristic of transport card data, while passenger path choice behavior is effectively represented using a perception parameter as a function of increasing number of transfers. Running the model on 800 pairs of metropolitan city rail data has proven its capability in determining dynamic demand at any moment in time, in line with the typical advantages expected of a continuous time-based model. Comparison against data measured by the eye of existing rail operating facilities to assess changes in congestion intensity shows that the model closely approximates the values and trends of the existing data with high levels of confidence. Future research efforts should be directed toward continued examination into construction of an integrated bus-city rail system model.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.367-382
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• 2018

Prediction models for a corporate bond rating in existing studies have been developed using various models such as linear regression, ordered logit, and random forest. Financial characteristics help build prediction models that are expected to be contained in the assigning model of the bond rating agencies. However, the ranges of bond ratings in existing studies vary from 5 to 20 and the prediction models were developed with samples in which the target companies and the observation periods are different. Thus, a simple comparison of the prediction accuracies in each study cannot determine the best prediction model. In order to conduct a fair comparison, this study has collected corporate bond ratings and financial characteristics from 2013 to 2017 and applied prediction models to them. In addition, we applied the elastic-net penalty for the linear regression, the ordered logit, and the ordered probit. Our comparison shows that data-driven variable selection using the elastic-net improves prediction accuracy in each corresponding model, and that the random forest is the most appropriate model in terms of prediction accuracy, which obtains 69.6% accuracy of the exact rating prediction on average from the 5-fold cross validation.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.125-135
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• 2016

The purpose of this study was to construct and test a structural equation model of subjective quality of life in middle-aged men. The participants were 493 middle-aged men. Data were collected from September 10 to October 31, 2011. Collected data were analyzed using SPSS 19.0 and AMOS 19.0. Self-esteem, social support, family communication showed direct and indirect effect on subjective quality of life for middle-aged married men, and job satisfaction showed a direct effect on subjective quality of life. The structural regression model of middle-aged men's subjective quality of life was a good fit with the model. These results indicate that it is necessary to design intervention programs to increase self-esteem, social support, family communication and job satisfaction in order to increase middle-aged men's subjective quality of life.

• Spatial Information Research
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• v.17 no.3
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• pp.389-395
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• 2009

In spite of many numerical analysis of debris flow, a little information has been found out. In this paper the watershed is divided to apply rainfall runoff and to estimate debris flow integrating flow and soil article. We use the contour data to extract spatially distributed topographical information like stream channels and networks of sub-basins. A Quasi Digital Elevation Model (Q-DEM) is developed, integrated, and adopted to estimate runoff based on marked one. As a results, it has been found out that the debris flow was close to observed flow hydrograph. Because debris flow is finished in 30 second, it is important that we have to prepare its prior countermeasure to minimize the damage of debris flow. The GIS-linked model will provide effective information to plan river works for debris flow.