• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.86-88
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• 2003

New cities and industrial complexes are being developed actively according to the government's policy. To determine the size of investment, number of power lines and substations for stable power supply to newly developed industrial complexes, the accurate estimation of power demand is necessary. "The standards for the estimation of power demands in newly developed residential and industrial complexes" established by KEPCO in 1991 have been used up to now. But the background for the estimation of power demands is weak and the accuracy has not been verified. Also, it has been passed above 10 years since their establishment and the social & economic situations have changed a lot, which requires an urgent revision. Through this survey and analysis of existing areas, new standards that will enable more accurate estimation of power demands in new cities and industrial complexes to be developed in the future are established by calculating the some kinds of power demand factors.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• 지역사회간호학회지
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• 제14권4호
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• pp.587-597
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• 2003

Purpose: The purpose of this study was to estimate the demand and supply of visiting nursing services provided by health centers in urban area, aiming at strengthening infrastructure, which may improved the quality of life and health status of vulnerable population in the community. Methods: This study was conducted through nominal group discussion, focus group study. The demand and supply of visiting nursing were estimated by health economists based on the secondary analysis data from 25 health centers in Seoul. Result: Primary targets for the visiting nursing must be people who are homebound in the community. They can be classified into: a group of Level I: chronic patients who need visiting nursing care at least once a week: and a group of Level II: vulnerable families that need management periodically e. g. twice a month. Based on the estimation of demand for visiting nursing services in the community, the estimated supply required was $651{\sim}770$ visiting nurses including home health nurses in visiting nursing programs based on health centers in Seoul. Conclusions: The estimated demand and supply of visiting nursing are expected to provide basic data for establishing alternative policies on visiting nursing infrastructure that might be accomplished through demand-based visiting nursing programs by districts.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.798-805
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• 2005

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expect it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. Above factors make the sales dynamic and unstable. We develop a time series model to evaluate the sales patterns with stockpiling and short term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• 한국경영과학회지
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• 제31권2호
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• pp.157-167
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• 2006

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expects it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. These factors make the sales dynamic and unstable. In this paper we develop a time series model to evaluate the sales patterns with stockpiling and short-term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• 환경정책연구
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• 제7권1호
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• pp.101-118
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• 2008

본 논문은 환경산업에 의한 노동수요 창출에 대해 알아보았다. 이를 위해 정부에서 발표하는 통계, 특히 환경부의 환경산업조사통계를 기초로 하여 오차항에 대한 다양한 가정을 통해 부분균형적인 단일 노동수요함수를 추정하여 보았다. 추정결과 환경산업의 환경부문 매출액 증가를 통한 노동수요 탄력도는 최소 0.193에서 최대 0.256에 해당하는 것으로 계산되어 각 산업별 환경기업들의 10억원의 매출증가를 통해 7.7에서 10.3명의 노동수요가 증가하는 것으로 계측되었다. 이는 특히 정부의 정책지원이 환경산업의 총매출액 1%에 해당하는 금액의 매출증가를 유도한다면 연간 $1,600{\sim}2,300$명의 직접 고용을 증대시키는 것으로 계측되었다. 그러나 안타깝게도 환경산업 노동력의 많은 부문이 단순노무직으로 구성되어 있어 향후 환경산업의 발전을 극대화하고 우리나라 경제성장의 중추 산업으로 육성하기 위해서는 정부의 기술개발과 수요증대에 대한 지속적인 지원이 필요하다 하겠다. 결국 이러한 정책적인 지원이 우리나라의 지속가능발전의 가능성을 극대화할 것이다.

• 자원ㆍ환경경제연구
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• 제14권4호
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• pp.893-921
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• 2005

본 연구는 1992년~2002년 기간 동안 한국 제조업의 환경오염방지활동이 노동수요에 미치는 효과를 제조업 노동수요함수 추정을 통해 확인하여 보았다. 추정에 있어서 전통적인 의미에서의 생산기술과 생산 과정에서 발생하는 환경오염물질을 방지하는 기술에 따른 노동수요효과를 식별하는 문제가 제기되었다. 이러한 문제를 해결하기 위해 Morgenstern et al. (2002)이 제안한 방식을 원용하였으나 Morgenstern et al. (2002)의 방식 역시 생산기술과 오염물질발생 간의 내생적인 문제를 해결하기에는 적합하지 않았다. 따라서 고정효과 모형의 이단계 추정방식(fixed effect IV estimation)을 통해 환경오염방지기술에 따른 노동수요 변화 효과를 식별하였다. 추정결과를 보면 1992년~2002년 기간 동안 우리나라 제조업의 환경오염방지활동은 노동수요를 증가시켜 왔으며 특히 우리나라 제조업의 환경오염방지비용이 총생산비의 1% 내외를 차지하여 왔음을 고려할 때 동 기간 동안 환경오염방지활동은 기업의 생산 활동에 큰 부담은 아니었음을 노동수요 변화를 통하여 확인할 수 있었다. 그러나 전통적인 노동수요변화의 요소인 실질임금과 생산량 변화에 따른 노동수요효과보다는 환경오염방지활동에 따른 노동수요변화효과가 상대적으로 작은 것으로 나타났다. 향후 환경오염방지비용이 총생산비용에서 차지하는 비중의 관점에서 적절한 노동수요를 유지하기 위한 환경오염방지활동비용의 범위를 알아보는 것은 좋은 연구주제가 될 것이다.

• 대한교통학회지
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• 제23권7호
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• pp.7-15
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• 2005

고속도로 통행수요함수를 추정하기 위하여 시계열자료를 이용하여 회귀분석을 시도하였다. 기존의 연구들이 시계열자료를 이용하여 통행수요함수를 추정함에도 시계열자료의 특성을 고려하지 않았다는 점에서 한계가 있었는데 본 연구에서는 이를 고려한 모형을 제시하였다. 고속도로 통행수요에 영향을 미치는 다양한 물리적 및 사회 경제적 변수를 선택하여 통행수요함수 추정을 시도하였다. 이를 위해 개별 변수들에 대해 단위근 검정을 하였고 공적분 검정을 시도하여 개별 변수들간의 관계를 고찰하였다. 그리하여 벡터오차수정모형을 이용하여 고속도로 통행수요함수를 추정하였는데 실질 GDP가 증가하면 고속도로 이용대수가 증가하는 것으로 나타났다. 그리고 실질 통행료가 증가하면 고속도로 이용대수가 감소하는 것으로 나타나서 일반적인 예측과 일치하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3249-3257
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• 2015

The smart convergence environment, in which all industries are converged around ICT infrastructure -- with the eventual inclusion of both industry and culture -- looms. With the emergence of new convergence industries such as smart medicine, smart cities, and smart automobiles, the ICT infrastructure is recognized as the foundation of the overall economy. As such, the importance of the next generation of information and communication construction businesses, which constructs the ICT infrastructure, is highlighted under the smart convergence paradigm environment; various multilateral policies to foster the information and communication construction business -- led by the Ministry of Science, ICT, and Future Planning -- are being implemented. Like other infrastructure industries, however, the estimation of the demand function of the information and communication construction business overall is essential for effectively establishing promotional policies for information and communication construction businesses. However, there has been no study which theoretically estimates the market demand function in the information and communication construction business thus far. The pursuit of a creative economy is a national agenda, as the significance of accelerating the ICT infrastructure is emphasized. Therefore, this paper seeks to estimate quantitatively the demand function in the information and communication construction business using empirical data and a statistical model and then to present policy implications which will aid the development of the information and communication construction business.

• 대한안전경영과학회지
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• 제9권1호
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• pp.175-186
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• 2007

The employment permit system for foreigners, which stresses introduction of foreign work force in a legal manner rather than in the position of being trainees, is anticipated to efficiently improve introduction and the overall management system of foreign work force and related difficulties such as illegal alien problems, absurdity on sending laborers overseas. In this paper, a prospective model of supply and demand of work force has been developed basing on various categories of industries and patterns about nationally practical foreign employees to look over efficient supply and demand of work force suiting employment of foreigner among foreign work force policies. To propose the prospective model, we have derived industry- and pattern-related matrixes of foreign laborers basing on Inter-Industry Analysis Method put forth by Professor Leontiyef in 1930, and through the derived matrix assessed repercussions concerning overall domestic industries and foreigner types and decided yearly weight; the capacity of supply and demand of foreign laborers can be compared through proposed statistical estimation and government estimation by combining the determined weight with yearly incomes of foreign laborers. This paper has thoroughly considered the particularity of our employment permit system for foreigners and applied the Weibull distribution and incorporated the dependence of foreign laborers during the limited period of 3 years to the industry relation analysis, ultimately proposing an efficient supply and demand method about domestic foreign work force.