• Journal of the Korean Institute of Rural Architecture
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• v.19 no.3
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• pp.33-41
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• 2017

Recently, it is recognized that the increase of return farmers is an important task to revitalize rural areas. There is a growing need to improve the housing environment in rural areas by expanding rental housing supply in order to increase return farmers. The purpose of the study is to forecast the rural rental housing demand based on the questionnaire survey and to suggest the rural rental housing supply in the public sector. The rural rental housing demand consists of demand for rural residents and demand for return farmers. The survey was conducted for rural residents and potential return farmers. The rural rental housing demand was analyzed by using prospect of rural residents and return farmers in the future and the rate of intention to move into rural rental house derived from the survey. In this study, rural rental housing demand which does not take into consideration the rent level and rural rental house demand considering it are presented respectively.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.11
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• pp.39-49
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• 2011

Smart Grid has two main objectives on both supply and demand aspects which are to distribute the renewable energy sources on supply side and to develop realtime price responses on demand side. Renewable energy does not consume fossil fuels, therefore it improves the eco-friendliness and saves the cost of power system operation at the same time. Demand response increases the flexibility of the power system by mitigating the fluctuation from renewable energies, and reduces the capacity investment cost by shedding the peak load to off-peak periods. Currently Smart Grid technologies mainly focus on energy monitoring and display services but it has been proved that enabling technologies can induce the higher demand responses through many pilot projects in USA. On this context, this paper provides a price responsive algorithm for HEMS (home energy management system) on the real time pricing environment. This paper identifies the demand response as a core function of HEMS and classifies the demand into 3 categories of fixed, transferable, and realtime responsive loads which are coordinated and operated for the utility maximization or cost minimization with the optimal usage combination of three kinds of demand.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.74-78
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• 2015

With the improvement of living standards and economic development, electricity consumption continues to grow. The electricity is a special energy which is hard to store, so its supply must be consistent with the demand. The objective of electricity demand forecasting is to make best use of electricity energy and provide balance between supply and demand. Hence, it is very important work to forecast electricity demand with higher precision. So, various forecasting methods have been developed. They can be divided into five broad categories such as time series models, regression based model, artificial intelligence techniques and fuzzy logic method without considering special-day effects. Electricity demand patterns on holidays can be often idiosyncratic and cause significant forecasting errors. Such effects are known as special-day effects and are recognized as an important issue in determining electricity demand data. In this research, we developed the power demand forecasting method using ELM(Extreme Learning Machine) for special day, particularly, lunar new year and Chuseok holiday.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.3
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• pp.75-85
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• 2021

This study evaluated variations in the paddy rice water demand based on the continuous changing in rice transplanting period and ponding depth at the four study paddy fields, which represent typical rice producing regions in Korea. Total 7 scenarios on rice transplanting periods were applied while minimum ponding depth of 0 and 20 mm were applied in accordance with maximum ponding depth ranging from 40 mm to 100 mm with 20 mm interval. The weather data from 2013 to 2019 was also considered. The results indicated that the highest rice water demand occurred at high temperature and low rainfall region. Increased rice transplanting periods showed higher rice water demand. The rice water demand for 51 transplanting days closely matched with the actual irrigation water supply. In case of ponding depth, the results showed that the minimum ponding depth had a proportional relationship with rice water demand, while maximum ponding depth showed the contrary results. Minimum ponding depth had a greater impact on rice water demand than the maximum ponding depth. Therefore, these results suggest that increasing the rice transplanting period, which reflects the current practice is desirable for a reliable estimation of rice water demand.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.2
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• pp.45-56
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• 2012

This paper considers a supply chain consisting of a component manufacturer and a product manufacturer. The component manufacturer provides components for the product manufacturer based on a vendor-managed inventory type of supply contract, and also faces demands from the market with the option of to accept or reject each incoming demand. Using the Markov decision process model, we examine the structure of the optimal production control and inventory rationing policy. Two types of heuristics are presented. One is the fixed-buffer policy and the other uses two linear functions. We implement a computational study and present managerial insights based on the observations.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.1-11
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• 2021

In this study, we analyze the automotive chip ecosystem that recently caused the global supply shortage, and attempt to derive policy implications for us from the conclusion. Automotive chips are critical parts that control various systems so that a vehicle can drive itself or operate with electricity. The current shortage in supply and demand for automotive chips is due to the inconsistency between supply and demand between automotive chip companies and car manufacturers. To promote the automotive chip industry, new investment incentives, tax cuts, and human resource training are needed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.220-226
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• 2021

In supply chain, there are a variety of different uncertainties including demand, service time, lead time, and so forth. The uncertainty of demand has been commonly studied by researchers or practitioners in the field of supply chain. However, the uncertainty of upstream supply chain has also increased. A problem of uncertainty in the upstream supply chain is the fluctuation of the lead time. The stochastic lead time sometimes causes to happen so called the order crossover which is not the same sequences of the order placed and the order arrived. When the order crossover happens, ordinary inventory policies have difficult to find the optimal inventory solutions. In this research, we investigate the lead time distribution in case of the order crossover and explore the resolutions of the inventory solution with the order crossover.

• Journal of Korean Society for Quality Management
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• v.36 no.4
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• pp.93-101
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• 2008

The rare metals, used for semiconductors, PDP-LCS and other specialized metal areas necessarily, has been playing a key role for the Korean economic development. Rare metals are influenced by exogenous variables, such as production quantity, price and supplied areas. Nowadays the supply base of rare metals is threatened by the sudden increase in price. For the stable supply of rare metals, a rational demand outlook is needed. In this study, focusing on the domestic demand for chromium, the uncertainty and probability materializing from demand and price is analyzed, further, a demand forecast model, which takes into account various exogenous variables, is suggested, differing from the previously static model. Also, through the OOS(out-of-sampling) method, comparing to the preexistence ARIMA model, ARMAX model, multiple regression analysis model and ECM(Error Correction Mode) model, we will verify the superiority of suggested model in this study.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.96.6-96
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• 2001

A high peak power demand at substations will result under Moving Block Signalling (MBS) when a dense queue of trains begins to start from a complete stop at the same time in an electrified railway system. This may cause the power supply interruption and in turn affect the train service substantially. In a recent study, measures of Starting Time Delay (STD) and Acceleration Rate Limit (ARL) are the possible approaches to reduce the peak power demand on the supply system under MBS. Nevertheless, there is no well-defined relationship between the two measures and peak power demand reduction (PDR). In order to attain a lower peak demand at substations on different traffic conditions and system requirements, an expert system is one of the possible approaches to procure the appropriate use of peak demand reduction measures ...

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.169-181
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• 2011

The cooperation between universities and IT industry in producing IT manpower of quality is urgently called for to create the effective labor pool of supply and finally balance its supply and demand. Korean Government launched a program where industrial demand-driven curriculums are developed and applied to universities. This paper proposes a design technique of meta-modeling demand-driven curriculums and courses, based on the 3D software space and the software development process. This technique is proven to result in extensibility, flexibility and quality improvement in software design. Therefore, we expect that the proposed technique makes curriculums and courses possible to be continuously improved in many aspects.