• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.435-447
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• 2019

In order to prevent unnecessary re-admission, it is necessary to intensively manage the groups with high probability of re-admission. For this, it is necessary to develop a re-admission prediction model. Two - year discharge summary data of one university hospital were collected from 2016 to 2017 to develop a predictive model of re-admission. In this case, the re-admitted patients were defined as those who were discharged more than once during the study period. We conducted descriptive statistics and crosstab analysis to identify the characteristics of rehospitalized patients. The re-admission prediction model was developed using logistic regression, neural network, and decision tree. AUC (Area Under Curve) was used for model evaluation. The logistic regression model was selected as the final re-admission predictive model because the AUC was the best at 0.81. The main variables affecting the selected rehospitalization in the logistic regression model were Residental regions, Age, CCS, Charlson Index Score, Discharge Dept., Via ER, LOS, Operation, Sex, Total payment, and Insurance. The model developed in this study was limited to generalization because it was two years data of one hospital. It is necessary to develop a model that can collect and generalize long-term data from various hospitals in the future. Furthermore, it is necessary to develop a model that can predict the re-admission that was not planned.

• Korean Journal of Remote Sensing
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• v.11 no.2
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• pp.1-16
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• 1995

This study is conducted to eveluate the potential of a GIS to assist an application problem. GIS has been applied to rainfall-runoff modeling over Soyang area. Various rainfall-runoff models have been developed over the years. A distributed rainfall-runoff model is selected because it considers the topographic characteristics over the basin. GIS can handle the spatial data to enhance the modeling. GRASS-a public domain GIS S/W-is used for GIS tools. Digital database is generated, including soil map, vegetation map, digital elevation model, basin and subbasin map, and water stream. The inpu data for the model has been generated and manupulated using GIS. The database, model and GIS are integrated for on-line operation. The inflow hydrographs are tested for the flood of Sept., 1990. This shows the promising results even without the calibration.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.3-15
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• 2022

In this study, we develop a simulation model for Supply Chain Management (SCM) of modular construction based steel bridge. To this end, first, Factory Production/Site Construction system data for the steel bridge construction were collected, and supply chain, entities, resources, processes were defined based on the collected data. After that, a steel bridge supply chain simulation model was developed by creating data, flowchart, and animation modules using Arena software. Finally, verification and validation of the model were performed by using animation check, extreme condition check, average value test, Little' s law test, and actual case value test. As a result, the developed simulation model appropriately expressed the processes and characteristics of the steel bridge supply chain without any logical errors, and provided accurate performance evaluation values for the target system. In the future, we expect that the model will faithfully play a role as a performance evaluation platform in developing management techniques for optimally operating the steel bridge supply chain.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1995.05a
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• pp.179-184
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• 1995

본 연구는 도시기능의 주요 요소인 주거단지 및 공업단지를 중심으로 환경부담을 최소화 시키면서도 에너지효율을 제고 시킬수 있는 방향으로 에너지적합형 지역개발사업 모형을 개발.제시하고자 하였다. 따라서 본고에서는 기존의 토지이용계획에 시스템적 관점의 에너지 및 환경관리를 통합하기 위한 에너지통합계획의 기본개념, 환경적으로 건전하고 지속가능한 개발(ESSD)을 위한 국내외동향 및 기술목록 사례를 소개하고, 주거단지 및 공업단지를 중심으로 "에너지이용합리화법(법률 제4426호)"에 의거한 기존의 에너지사용계획서의 보완방안 및 사례연구를 통한 에너지적합형 개발모형을 소개하고자 한다. 소개하고자 한다.

• Journal of Korean Library and Information Science Society
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• v.41 no.1
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• pp.121-147
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• 2010

The purpose of this study is to develop and prove service quality measurement model and indicators which are able to measure objectively service quality of digital libraries in Korea. Literature review and Delphi survey are used to investigate service quality dimensions. User perceived service quality performance was measured to validate DL-SQI model with three digital libraries. Finally DL-SQI(Digital Library-Service Quality Index) model was developed which is composed of four primary dimensions. The survey results reveal that reliability coefficient is 0.8 which means high reliability of survey and it suggests that DL-SQI model based on the above dimensions is proved through confirmatory factor analysis.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.273-292
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• 2017

This paper aims to develop an evaluation model for library mobile services in terms of service quality. First, a literature review of the service quality evaluation model and the mobile library service evaluation was conducted. Then, based on the analysis, the evaluation model consisting of 4 quality dimensions, 10 quality factors, 39 quality measurement items was developed. Delphi method was applied to verify the validity of the model. Finally, a final model consisting of 4 quality dimensions, 9 quality factors, and 37 quality measurement items was derived. The evaluation model proposed in this study can be used as a measure of library mobile service quality and can be used as a guideline for improvement of library mobile service.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.687-699
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• 2001

A 2-dimensional numerical sediment transport model has been developed by using erosion rates observed by SEDFLUME. The model un boundary-fitted coordinate can reduce inaccuracy of sediment model with accurate erosion data. Suspended transport and bed load transport are included in the model together. The model results gave good agreement with particle size distributions in 1-d channel and was more accurate than that of HIDAS of 1-dimensional model. The model applied to an enlarging channel to check model performance in 2-dimensional domain. Bed coarsening reduced erosion and deposition.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1742-1746
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• 2008

지금까지의 대부분의 2차원 수리해석 모형은 상류와 사류가 혼재된 불연속적인 천이류 흐름을 해석하기에 계산의 정확도 및 현실성에서 많은 문제를 보이고 있으며, 특히 계산과정에서 나타날 수 있는 마른하도의 처리에 있어서 많은 어려움을 겪고 있다. 본 연구의 목적은 유한체적기법을 사용하여 상류와 사류가 혼재하는 불연속적인 하천 천이류를 안정적으로 해석하기 위해 개발된 고정확도 수치모형의 자연하도 적용에 있으며, 또한 마른 하도로 전파되는 흐름 모의 및 계산과정에서 나타날 수 있는 마른하도 처리의 어려움을 해결함으로써 모형의 정확도와 안정성을 검증하여 실제 하천에서의 모형 적용성을 검토함에 있다. 이를 위해 본 연구에서는 흐름의 전파양상을 정확하게 반영할 수 있는 상류이송기법인 Godunov 기법과 관심격자의 좌우 격자 정보를 모두 사용하는 대표적 중앙차분기법인 Beam-Warming 기법의 장점을 모두 반영한 가중평균흐름률 (Weighted Average Flux) 기법을 사용하여 사각격자망의 구성을 통해 자연하도에 적용시킬 수 있는 2차원 유한체적모형을 개발하고자 하였고, 개발된 모형의 안정성, 정확도, 적용성을 검증하기 위해 직사각형 수로, 큰 사행비를 가진 만곡수로에 적용하고, 그 결과를 수리모형 실험결과와 비교, 분석하였다.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.89-97
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• 2009

In this study, a two-dimensional unstructured finite volume model based on the shallow-water equations and well-balanced HLLC scheme is developed. The model is verified by applying to various one- and two-dimensional problems related to the analyses of dam-break wave. The predicted numerical results agree very well with available analytical solutions and laboratory measurements. The model provides slightly more accurate results compared with the existing models.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.485-485
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• 2021

최근 세계적인 기상이변으로 자연재해의 발생빈도 증가는 물론 이로 인한 피해가 점차 다양화 및 대형화되어 가고 있는 추세이다. 재난으로 인한 피해는 발생지역 피해뿐만 아니라 국가 경제 전반에 큰 영향을 미치는 특징이 있다. 우리나라의 자연재해 중 대설은 다른 자연재해에 비해 발생빈도는 낮지만 광역적인 피해를 유발하며, 피해 면적에 비해 피해액 규모가 크다. 또한 현재에는 강원권이 가장 취약한 것으로 취약성 분석 결과에서 보여주지만, 미래에는 강원권, 충청권, 호남권을 연결하는 축으로 취약지역이 확대될 것으로 전망된다. 본 연구에서는 현재 사회 전반에서 다양하게 활용되고 있는 머신러닝 기법을 이용하여 우리나라 대설피해액을 예측하는 대설피해 예측모형을 개발하고자 하였다. 머신러닝 기법으로는 랜덤포레스트, 서포트 벡터 머신, 인공신경망 기법을 이용하였고, 모형에 사용한 변수는 기상관측자료, 사회·경제적 요소 등을 활용하여 모형을 개발하였다. 결과적으로 기존연구에서 다중회귀모형을 이용하여 개발된 예측모형과 본 연구에서 3개의 머신러닝 기법으로 개발된 예측모형의 예측력을 비교 분석하였고, 예측력이 가장 높은 모형을 제시하였다. 본 연구결과를 활용하여 모형의 개선 및 데이터 품질 개선이 이루어진다면 향후 대설피해에 대한 개략적인 대비가 가능할 것으로 기대된다.