• Advances in Computational Design
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• 제7권2호
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• pp.113-128
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• 2022

Water consumption is strongly affected by numerous factors, such as population, climatic, geographic, and socio-economic factors. Therefore, the implementation of a reliable predictive model of water consumption pattern is challenging task. This study investigates the performance of predictive models based on multi-layer perceptron (MLP), multiple linear regression (MLR), and support vector regression (SVR). To understand the significant factors affecting water consumption, the stepwise regression (SW) procedure is used in MLR to obtain suitable variables. Then, this study also implements three predictive models based on these significant variables (e.g., SWMLR, SWMLP, and SWSVR). Annual data of water consumption in Thailand during 2006 - 2015 were compiled and categorized by provinces and distributors. By comparing the predictive performance of models with all variables, the results demonstrate that the MLP models outperformed the MLR and SVR models. As compared to the models with selected variables, the predictive capability of SWMLP was superior to SWMLR and SWSVR. Therefore, the SWMLP still provided satisfactory results with the minimum number of explanatory variables which in turn reduced the computation time and other resources required while performing the predictive task. It can be concluded that the MLP exhibited the best result and can be utilized as a reliable water demand predictive model for both of all variables and selected variables cases. These findings support important implications and serve as a feasible water consumption predictive model and can be used for water resources management to produce sufficient tap water to meet the demand in each province of Thailand.

• 한국지하수토양환경학회지:지하수토양환경
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• 제21권4호
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• pp.30-41
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• 2016

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

• International Journal of Aeronautical and Space Sciences
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• 제14권4호
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• pp.297-309
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• 2013

Design optimization is a mathematical process to find an optimal solution through the use of formal optimization algorithms. Design plays a vital role in the engineering field; therefore, using design tools in education and research is becoming more and more important. Recently, numerical design optimization in fluid mechanics, which uses computational fluid dynamics (CFD), has numerous applications in the engineering field, because of the rapid development of high-performance computing resources. However, it is difficult to find design optimization software and contents for educational purposes in aerospace engineering. In the present study, we have developed an aerodynamic design framework specifically for an airfoil, based on the EDucation-research Integration through Simulation On the Net (EDISON) portal. The airfoil design framework is composed of three subparts: a geometry kernel, CFD flow analysis, and an optimization algorithm. Through a seamless interface among the subparts, an iterative design process is conducted. In addition, the CFD flow analysis and the design framework are provided through a web-based portal system, while the computation is taken care of by a supercomputing facility. In addition to the software development, educational contents are developed for lectures associated with design optimization in aerospace and mechanical engineering education programs. The software and content developed in this study is expected to be used as a tool for e-learning material, for education and research in universities.

• 한국축산식품학회지
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• 제40권5호
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• pp.860-861
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• 2020

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.336-336
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• 2023

가뭄은 가장 심각한 기상 재해 중 하나로 농업 생산, 사회경제 등 다양한 분야에 영향을 미친다. 국내의 경우 광주·전남지역이 1990년대 이후 30년 만에 제한 급수 위기에 처하는 역대 최악의 가뭄으로 지역민들은 심각한 피해가 발생하였다. 유럽의 경우 2022년 당시 500년 만에 찾아온 가뭄으로 인해 3분의 2에 해당하는 지역이 피해를 입었으며, 미국 서부 지역은 2000년부터 2021년까지 1200년 만에 가장 극심한 대가뭄을 겪은 것으로 나타났다. 지구온난화에 따른 기후변화로 인해 가뭄의 빈도와 강도가 증가함에 따라 피해도 커질 것으로 예상된다. 가뭄의 부정적인 영향으로 인해 정확하고 신뢰할 수 있는 가뭄 예측 기술이 필요하다. 본 연구에서는 가뭄예측을 위한 입력변수로서 GPM IMERG (The Integrated Multi-satellitE Retrievals for GPM) 강수량 자료와 NOAA에서 제공하는 8가지 북반구 대기패턴 자료 간의 상관성을 분석하였다. 입력변수 간의 상관성과 중장기 가뭄 예측을 위하여 딥러닝 모델 중 시계열 데이터에서 높은 예측 성능을 보이는 LSTM(Long Short Term-Memory)을 적용하여 가뭄을 예측하고자 한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.337-337
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• 2023

가뭄은 가장 심각한 기상 재해 중 하나로 농업 생산, 사회경제 등 다양한 분야에 영향을 미친다. 국내의 경우 광주·전남지역이 1990년대 이후 30년 만에 제한 급수 위기에 처하는 역대 최악의 가뭄으로 지역민들은 심각한 피해가 발생하였다. 유럽의 경우 2022년 당시 500년 만에 찾아온 가뭄으로 인해 3분의 2에 해당하는 지역이 피해를 입었으며, 미국 서부 지역은 2000년부터 2021년까지 1200년 만에 가장 극심한 대가뭄을 겪은 것으로 나타났다. 지구온난화에 따른 기후변화로 인해 가뭄의 빈도와 강도가 증가함에 따라 피해도 커질 것으로 예상된다. 가뭄의 부정적인 영향으로 인해 정확하고 신뢰할 수 있는 가뭄 예측 기술이 필요하다. 본 연구에서는 가뭄예측을 위한 입력변수로서 GPM IMERG (The Integrated Multi-satellitE Retrievals for GPM) 강수량 자료와 NOAA에서 제공하는 8가지 북반구 대기패턴 자료 간의 상관성을 분석하였다. 입력변수 간의 상관성과 중장기 가뭄 예측을 위하여 딥러닝 모델 중 시계열 데이터에서 높은 예측 성능을 보이는 LSTM(Long Short Term-Memory)을 적용하여 가뭄을 예측하고자 한다.

• 한국과학교육학회지
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• 제11권2호
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• pp.87-101
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• 1991

Science-Technology-Society curricula have been developed in several countries for the last 20 years. Those curricula were focused on social aspects of science, i.e., value-laden knowledge and scientific enterprise, and society-related scientific and technological issues, i.e., energy, pollution, natural resources. The major teaching models employed in those curricula were problem solving and decision making, which required the following teaching techniques: teacher as a manager, small group discussion, controversy as a motivational force for substantive learning, and sufficient factual information into the discussion. Further researches are to be made to ascertain whether or not the expectations of the curricula might be realized in practice. It was shown that most Korean biology teachers considered the STS-related goal of science education as more important than the other goals. Based upon the findings, some recommendations for development of Korean STS curriculum were made as follows: 1. The contents of the STS curricula are to be organized with the integrated mode; 2. The major teaching models throughout the contents are to be problem solving and decision making. These are considered to provide students with the opportunities to involve in debates on practical issues and to draw consensus from them; 3. Some degree of flexibility should be provided on teachers' implementation of the curriculum in terms of contents, teaching techniques etc.; 4. To increase the practicality of the curriculum, teachers should be involved in the development of the curriculum and the relevant research; and 5. Contents to be included in STS curriculum were suggested by some science educators, but the more systematic study is required in this respect.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.227-230
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• 2009

본 논문에서는 유비쿼터스 네트워크에서 요구되는 다양한 장치의 통합 연동의 방안을 제안한다. 다양한 장치의 연동은 최근에 사용되어지는 고성능의 멀티미디어장치 뿐만 아니라 기존의 가정에서 사용되고 있는 저성능의 단순 가전기기까지 모든 종류의 장치 연결에 제약이 없어야 한다. 이에 본문에서는 기존의 저성능 가전기기를 대상으로 표준 미들웨어를 활용하여 네트워크 프로토콜의 연동을 통해 효율적인 장치의 연결과 제어 관리의 제공을 목적으로 한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.237-240
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• 2009

본 논문에서는 HIS(병원 정보 시스템) 환경에서 의료 및 주변 기기들의 다양한 솔루션과 미들웨어를 통합할 수 있는 프레임워크 기반에서 환자 기초, 의료 정보의 전달 구조를 정의하였다. OSGi 번들 형태로 HL7(Health Level 7) 기반의 메시지 전달 구조의 설계하고 다른 장치 제어 번들과의 효율적인 상호 운용을 보이고자 한다.

• 한국병원경영학회지
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• 제14권2호
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• pp.75-98
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• 2009

As the organizational environments are changing, organizational innovation has become a critical success factor for the healthcare organizations. Although there are lots of successful innovation cases in other industries, healthcare organization's management innovation cases are rare in Korea. This case study is focused on successful change process of a Maeumsarang psychiatric hospital. Main findings are: (a) virtuous cycle of healthcare service innovation and organizational innovation, (b) intensive training and learning, (c) usage of external resources, (d) high commitment HRM system, (e) CEO leadership, and (f) synchronization of planning and execution. Based on these findings, managerial implications are derived and future research directions are proposed.