• 대한간호학회지
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• 제3권2호
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• pp.15-30
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• 1973

Nursing education in Korea has made rapid progress recently. There is .: great deal of support with approval and encouragement of this progress. However, much disapproval of its validity has asserted some restraints on it. The aims of nursing education should be based on the principle that education is planned according to tile need much research has been made with such a viewpoint but much still remains unclear. The present study is aimed at establishing the needs for nursing manpower based on the biological demand for medical care. The needs for nursing manpower have been emphasized by many researchers and authorities on nursing education, and the prevailing medical trends also demand it. In this study, through the study of various hooks and records concerned, and the compiling of data analysis and questionnaires, I came to the following figures for the proposed needs of nursing manpower: There figures are greater than those calculated by another method by the government research program but it shows approximately the same final figure as that of the government report for the end of the target year. With these findings, I concluded that: 1) As the final purpose of the government medical project is to fulfill the needs of the national health (that is, to support the national needs for medical care), the plan of this project should follow the theory of biological demand for medical care, recognizing that the numbers will increase gradually. 2) Qualitative growth, based on the advanced and specialized nursing profession. should be promoted to meet the rapid growth of the medical needs of the nation in addition to promoting of investments for the facilities. and of the preparatory investments for education needs. 3) For efficient and economic utilization of nursing manpower, the improvement of wages, and the offering of free education is necessary. 4) Amendments to the low promising innovation and advancement of medical treatment; preparation of a national fund for medical care; and, changing of national attitudes to bring about greater concern are desirable.

• International journal of advanced smart convergence
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• 제7권1호
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2007년도 정기학술발표대회 논문집
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• pp.743-746
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• 2007

현재 국내에서는 많은 경제성장과 생활여건의 개선에 따라 기존주택의 재건축과 재개발이 증가하고 있다. 이에 따라 국내에서 발생하는 폐기물중 건설폐기물이 차지하는 비중은 점점 더 커져가고 있다. 따라서 정부나 민간에서는 건설폐기물의 발생량을 줄이기 위해 많은 노력을 하고 있다. 그러나 건설폐기물의 발생량을 정확히 예측하고 관리하기 위한 시스템의 개발에 대한 노력은 거의 없는 실정이다. 폐기물의 발생량을 예측하기 위한 기준의 미비로 인해 많은 사회적비용이 발생하고 있다. 따라서 본 연구에서는 공동주택을 대상으로 건설폐기물의 발생량을 쉽게 예측할 수 있는 방안을 제시한다. 그 방법으로는 원단위 할용, CAD도면의 활용, 3D object의 활용과 같이 현장여건에 따라 적절한 방법을 선택하여 적용할 수 있도록 하였다. 이 모듈은 사용자의 사용 목적에 따라 개별 모듈별로 사용하는 것이 가능하도록 구성하였다.

• 한국산학기술학회논문지
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• 제16권11호
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• pp.7781-7787
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• 2015

본 논문은 국내 양식 넙치 중장기 시장 규모 추정을 위해 구축된 수급전망모형을 개발한 내용과 이 모형을 이용하여 2015년-2017년 기간에 대해 시장 규모(수급 및 가격)를 예측한 내용을 소개하고 있다. 양식 넙치 수급전망모형은 단일품목 부분균형모형이며 동태 축차적 시뮬레이션 모형으로 개발되었고, 모형내 각 행태방정식은 계량경제학 방법을 이용하여 추정되었다. 중 장기 시장 규모 전망에 앞서 모형의 예측정확도는 RMSPE, MAPE, Theil의 불균등계수를 기준으로 검토되었다. 예측력 검토결과, 양식면적, 양성물량, 출하량, 도매가격은 모두 4% 이내의 양호한 오차율을 보였다. 국내 양식 넙치 시장 규모 전망결과, 생산량은 2015년 37,445톤, 2017년 42,561톤에 이를 것으로 전망되었고, 산지가격은 2015년 9,226원(1kg 기준), 2017년 10,191원될 것으로 전망되었다.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제1권3호
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• pp.133-142
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• 2012

쿠르노 모델은 경쟁적 전력시장을 게임이론 기반으로 모델링하기 위한 대표적인 모델이다. 이전 연구에서도 쿠르노 모델을 이용하여 전력시장을 모델링 하기 위한 다양한 시도가 이루어져 왔다. 쿠르노 모델은 몇 개의 주요 발전사업자들이 경쟁하고 그로 인해 시장지배력이 존재하는 과점 시장모델에 적합하다. 쿠르노 모델로 시장을 모델링함에 있어서는 우하향 하는 수요함수의 존재가 선결되어야 한다. 과점에서 시장참여자들은 시장지배력을 활용하여 그들의 이익을 극대화하려고 노력하지만, 우하향하는 시장수요함수에 의해 매출 역시 하락하기 때문에 적당한 지점에서 이러한 시장지배력의 행사를 제한하여야 한다. 스마트그리드에서는 실시간으로 변동하는 요금제와 다양한 전산기반 툴의 활용으로 인해 이러한 수요반응이 더욱 활성화될 것이고, 이 경우 쿠르노 모델은 수요반응 솔루션의 주요 모델로 활용될 것이다. 이에 본 논문은 실제 시장에서 계량경제학적인 접근으로 전력시장의 수요곡선을 추정하는 방법에 대해 제안한다.

• 전기학회논문지
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• 제68권1호
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• pp.27-35
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• 2019

There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3571-3587
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• 2021

For accurately analysing and forecasting the social networks of China's political, economic and social power elites, it is necessary to develop a database that collates their information. The development of such a database involves three stages: data definition, data collection and data quality maintenance. The present study recommends distinctive solutions in overcoming the challenges that occur in existing comparable databases. We used organizational and event factors to identify the Chinese power elites to be included in the database, and used their memberships, social relations and interactions in combination with flows data collection methodologies to determine the associations between them. The system can be used to determine the optimal relationship path (i.e., the shortest path) to reach a target elite and to identify of the most important power elite in a social network (e.g., degree, closeness and eigenvector centrality) or a community (e.g., a clique or a cluster). We have used three social network analysis tools (i.e., R, UCINET and NetMiner) in order to find the important nodes in the network. We compared the results of centrality rankings of each tool. We found that all three tools are providing slightly different results of centrality. This is because different tools use different algorithms and even within the same tool there are various libraries which provide the same functionality (i.e., ggraph, igraph and sna in R that provide the different function to calculate centrality). As there are chances that the results may not be the same (i.e. centrality rankings indicating the most important nodes can be varied), we recommend a comparison test using different tools to get accurate results.

• 노동경제논집
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• 제43권4호
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• pp.1-34
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• 2020

글로벌 금융위기 이후 전통적인 실업률의 유용성에 대한 의문이 제기되었으며, 본 연구는 2015년부터 통계청이 공식적으로 발표하고 있는 고용보조지표의 활용 가능성에 대해 살펴보았다. 이를 위해 고용보조지표의 정의를 2003년부터 2014년까지 경제활동인구조사 원자료에 소급 적용하여 고용보조지표를 추산하고, 이를 활용한 노동시장 유휴생산능력 지표에 대한 실증분석을 시도하였다. 실증분석 결과, 보완적 고용지표를 활용한 고용률갭이 여타 노동시장 유휴생산능력 지표에 비해 총산출갭과의 상관성이 높을 뿐만 아니라, 인플레이션에 대한 예측력 개선효과도 비교적 뚜렷한 것으로 나타나, 보완적 고용지표를 활용한 고용률 기반 지표의 유용성이 상대적으로 높음을 시사한다고 할 수 있다.

• 한국병원경영학회지
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• 제25권4호
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• pp.60-75
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• 2020

Purpose: This study aims to develop a cost model for NRP (Nursing Residency Program) operation and ultimately provide evidence for financial factors for NRP operation in the future by simulating a cost model. Methodology: This study developed a model for the NRP education cost calculation model based on the review of Hansen's model, which has systematically reported on the development and operation of NRP, and discussions with nursing education experts at a university-affiliated hospital. With the simulation, it was intended to predict nurses' supply and demand in the long term and to calculate changes in long-term education costs. Findings: Firstly, turnover model, term model, cost model necessary for calculating a model for the NRP education cost calculation model was set up. Secondly, the simulation showed the following results; 1) the proportion of newly graduated nurses less than 5 years of working decreases gradually over time, which will make the composition of nurses more balanced. 2) In the first year of the partial introduction of NRP, the cost of training new nurses was about 2.1 times higher than before. After the introduction, the training cost in the 13th year began to be lesser than before the introduction, and in the 25th year, it decreased by 28.1% compared to before the introduction. Practical Implications: Firstly, NRP would be an effective way to solve the higher turnover and frequent departure of new nurses and the imbalance of nurses' composition. Secondly, although the costs of NRP are incurred in the early stages, in the end, NRP training costs are reduced compared to before the introduction of NRP. It is necessary to systematically understand the contribution effect of NRP by analyzing the economic value of NRP considering financial and non-monetary returns in the future and providing a basis for decision-making related to NRP implementation.

• 대한토목학회논문집
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• 제41권3호
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• pp.317-325
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• 2021

1988년 부산에서 처음 발병된 소나무재선충병(Pine Wilt Disease, PWD)은 우리나라 소나무에 막대한 피해를 주고 있는 심각한 질병이다. 정부에서는 2005년 소나무재선충병 방제특별법을 제정하고 피해지역의 소나무 이동 금지와 방제를 시행하고 있다. 하지만, 기존의 예찰 및 방제방법은 산악지형에서 동시다발적이고 급진적으로 발생하는 소나무재선충병을 줄이기에는 물리적, 경제적 어려움이 있다. 따라서 본 연구에서는 소나무재선충병 감염의심목을 효율적으로 탐지하기 위해 무인항공기를 이용한 영상자료를 바탕으로 딥러닝 객체인식 예찰 방법의 활용가능성을 제시하고자 한다. 소나무재선충병 피해목을 관측하기 위해서 항공촬영을 통해 영상 데이터를 획득하고 정사영상을 제작하였다. 그 결과 198개의 피해목이 확인되었으며, 이를 검증하기 위해서 접근이 불가한 급경사지나 절벽과 같은 곳을 제외하고 현장 조사를 진행하여 84개의 피해목을 확인할 수 있었다. 검증된 데이터를 가지고 분할방법인 SegNet과 검출방법인 YOLOv2를 이용하여 분석한 결과 성능은 각각 0.57, 0.77로 나타났다.