• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.29-40
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• 1999

The distribution center location and routing problem involves interdependent decisions among facility, transportation, and inventory decisions. The design of distribution system affects the customers' purchase decision by sets the level of customer service to be offered. Thus the lower product availability may cause a loss of demand as falls off the customers' purchase intention, and this is related to the firm's profit reduction. This study considers the product availability of the distribution centers as the measure of the demand level change of the demand points, and represents relation between customer service and demand level with linear demand function. And this study represents the distribution center location and routing to demand point in order to maximize the total profit that considers the products' sales revenue by customer service, the production cost and the distribution system related costs.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.4
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• pp.179-185
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• 2007

In this paper, the method of computing demand rate with respect to a transformer capacity is proposed and addressed to predict a future demand rate. The simulation data are taken from switchgears of a real medium voltage transformer. Data taken from the electrical instrument at 22.9 kVY power receiving panels are employed to evaluate the correlation between demand rate and power usage of transformer. It is verified a usefulness with respect to an proposed index of demand rate for transformer by using a least square error of regressive modeling, As a result of investigation and simulation on the spot to a few buildings, it is considered that there is necessity to make a partial amendment of demand rate being applicable currently for electrical energy saving in domestic.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.149-151
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• 2005

Recently, power supply-demand instability due to the dramatic increase in power usage suchas air-conditioning load at summertime has brought forecasts of decrease in power supply capability. Therefore improving the load factor through systematic load management, in other words, Direct Load Control became necessary. Direct Load Control(DLC) system is kind of a load management program for stabilization of electric power supply-demand. It's purpose is limiting the demand of the demand side selected at peak load or other time periods. The paper presented a Design of Direct Load Controller for control the amount of power demand in demand side. The proposed Controller is cheaper and has ability of storing more power data than pre-existing device.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.11
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• pp.636-642
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• 2009

Energy consumption data are surveyed and measured to develop energy demand models for hospital buildings as part of a complete package. Daily consumption profiles for electricity, heating, cooling and hot water are surveyed for 14 carefully chosen hospitals to establish energy demand patterns for a time span of a year. Then the hourly demand patterns of the 4 loads are field-measured for different seasons and statistically analyzed to provide higher resolution models. Used in conjunction with energy demand models for other types of buildings, the high resolution of 8760 hour energy demand models for a hospital for a typical year will serve as building blocks for the comprehensive model that allows the estimation of the combined loads for arbitrary mixtures of buildings.

• Journal of Agricultural Extension & Community Development
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• v.3 no.2
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• pp.177-195
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• 1996

This study examines the demand for agricultural information at farm level, using Probit and Logit models. 646 farmers are surveyed with a questionnaire to attain the data and 441 of them have responded. The demand functions for computers, agricultural softwares, and agricultural databases at from level have been derived and used to project the demand for agricultural information in year $2001{\sim}2004$. Results find that only 5.89% of farmers have PCs at farm and rarely use the agricultural databases and softwares in 1994. The low demand figures are mostly due to the difficulty of using the PCs, databases, and softwares. The demand figures will increase in early 2000`s with 15.46% of farmers having PCs. User Friendly developed softwares and databases, and education for using agricultural information are necessary to increase the demand figures.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.720-723
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• 1996

The recent summer power peak crisis has been caused by excessive use of cooling loads at daily peak time in summer. The yearly load shape of KEPCO has gradually became very steep valley. Under this situation, more efficient DSM(Demand Side Management) tools are fully required for summer peak clipping and shaving. In this paper, the KEPCO's Jeju-Do model project for DSM, especially for Demand Controller, is presented. Demand Controller was evaluated to have the very high economical efficiency against the investment in equipment, as compared with another DSM tools. There were some serious problem to apply Demand Controller to many customers in the aspect to synchronization with KEPCO's watthour meter. But these problems have solved by Keyin's new Demand Controller using vision algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.445-450
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• 2007

NAND 플래시 메모리 기반의 실시간 임베디드 시스템에서는 일반적으로 shadowing 기법을 통해 프로그램을 수행한다. 그러나 shadowing 기법은 시스템의 부팅 시간을 증가시키고 불필요한 DRAM 영역을 차지한다는 단점 때문에 자원 제약이 심한 실시간 임베디드 시스템에는 적합하지 않다. 이에 대한 대안 중 하나는 demand paging 기법을 활용하는 것이다. 단, demand paging 환경에서는 page fault에 의한 시간 지연 때문에 태스크의 최악 실행 성능을 예측하기 어렵다. 따라서 본 논문에서는 NAND 플래시 메모리 기반의 실시간 임베디드 시스템에서 demand paging 비용을 고려한 태스크 최악 성능 분석 기법을 제안한다. 제안하는 기법은 각 태스크에 대해 demand paging 비용을 계산하고, 이를 전통적인 WCRT 분석 기법과 결합하는 방법을 사용한다. 또한 demand paging 비용과 WCET 분석을 독립적으로 고려함으로써, 최악의 경우에도 분석 결과의 안정성을 보장하고 기존의 방법에 비해 분석 복잡도를 줄였다.

• Journal of Preventive Medicine and Public Health
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• v.16 no.1
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• pp.113-120
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• 1983

The main objective of this case study is to develop demand forecasting model for durg inventory control in a university hospital. This study is based on the pertinent records during the period of January 1975 to August 1981 in the pharmacy and stock departments of the hospital. Through the analysis of the above records the author made some major findings as follows: 1. In A.B.C. classification, the biggest demand (A class) consists of 9 items which include 6 items of antibiotics. 2. Demand forecasting level of an index or discrepancy in A class drug compared with real demand for 6 months is average 30.4% by X-11 Arima method and 84.6% by Winter's method respectively. 3. After the correcting ty the number of bed, demand forecasting of drug compared with real demand for 6 months is average 23.1% by X-11 Arima method and 46.6% by Winter's method respectively.

• Proceedings of the KIEE Conference
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• summer
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• pp.162-164
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• 2004

Electrical power peak demand of Republic of Korea is annually growing and the peak demand has occurred in the summer. It is difficult that we handle with constructing power plants and increasing generation capacity to cope with a suddenly increased demand due to the cost problem, difficulty to find the new plant site, and the spread of the NIMBY. The alternative of the above problem is to efficiently manage demand of electrical power. Accordingly, load shedding of a section of demand side management is investigated. First we surveyed a trend of research in the domestic and overseas, for load curtailment and demand response program. After reviewing several demand response programs, the future research direction for load shedding in emergency and normal operation is introduced.

• Journal of the Korea Safety Management & Science
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• v.18 no.4
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• pp.161-169
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• 2016

In this research, we propose efficient demand forecasting scheme for intermittent demand. For this purpose, we first extensively analyze the drawbacks of the existing forecasting methods such as Croston method and Syntetos-Boylan approximation, then using these findings we propose the new demand forecasting method. Our goal is to develop forecasting method robust across many situations, not necessarily optimal for a limited number of specific situations. For this end, we adopt combining forecasting method that utilizes unbiased forecasting methods such as simple exponential smoothing and simple moving average. Various simulation results show that the proposed forecasting method performed better than the existing forecasting methods.