• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1379-1383
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• 2005

Introducing the market into the electricity industry lets the multiple participants get into new competition. These multiple participants of the market need new business strategies for providing value added services to customer. Therefore they need the accurate customer information about the electricity demand. Demand characteristic is the most important one for analyzing customer information. In this study load profile data, which can be collected through the Automatic Meter Reading System, are analyzed for getting demand patterns of customer. The load profile data include electricity demand in 15 minutes interval. An algorithm for clustering similar demand patterns is developed using the load profile data. As results of classification, customers are separated into several groups. And the representative curves for the groups are generated. The number of groups is automatically generated. And it depends on the threshold value for distance to separate groups. The demand characteristics of the groups are discussed. Also, the compositions of demand contracts and standard industrial classification in each group are presented. It is expected that the classified curves will be used for tariff design, load forecasting, load management and so on. Also it will be a good infrastructure for making a value added service related to electricity.

• 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 housing association
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• v.14 no.6
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• pp.41-50
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• 2003

The parking problem is caused by the parking demand. The ratio of parking demand at multi-family housing sites has been increased significantly, therefore several parking problems have occurred. The goal of this study is to investigate the parking demand per housing size of public-sized apartments, and to prepare that with the architectural regulations about parking supply. According to the results of this study, the parking demand of the small size housing unit(exclusive size：60 $m^2$ below) shows 1.09 car per the unit. and that of the medium size housing unit(exclusive size：60 $m^2$ over 85 $m^2$ below) shows 1.34 car per the unit. The parking demand of the small size housing unit was exceeded 56% more than the legal supply limit, and the parking demand of the medium size housing unit was exceeded 34% more. It is means that the level of architectural regulation about parking supply was not enough than the parking demand. So, it needs recon-sideration about the architectural regulations of parking supply.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.265-284
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• 2011

The purpose of this study is to analyze the demand for telemedicine and telehealthmanagement services, which are key elements of home based u-health. The conjoint analysis, which is a conventional method for demand analysis for newly introduced products, is employed, utilizing the survey data on 500 seoul citizens. Further, multivariate probit model is used to estimate the demand. The result shows that the demand for telemedicine services is greater than that of telehealthmanagement services. Further, home-based u-health services will play a role as a complementary for face-to-face medical treatments, rather than a substitute. Meanwhile, the demand for home-based u-health services is found to be very sensitive to price.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.43-48
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• 2014

With the energy paradigm shift from supply side management to demand side management, many researches have been done on demand side resource management and demand response. At the same time, Obix, BacNet-WS and OPC-UA are popularly used in buildings and industry energy management system. However, it is not easy to interchange the data and information among the systems cause a variety of protocols are used in buildings and factories. Therefore, in this paper, we are proposing an open business platform not only to integrate and manage the demand resources using various protocols and standards, but also to allow to plug-ins a new business service on top of the platform.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.31
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• pp.59-72
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• 1994

This paper deals with ordering policies of consumable goods which have large demand rates in a multi-level distribution system. The system we are concerned consists of one Central Distribution Center(CDC) and N non-identical Regional Distribution Centers(RDCs) which have different demand rates, minimum fillrates, leadtimes, etc. The customer demand on the RDC is stationary poisson and the RDCs demand on the CDC is superposition of Q-stage Erlang distributions. We approximate the RDCs and CDC demand distribution to nomal in order to enhance the efficiency of algorithm. The relevant costs include a fixed ordering cost and inventory holding cost, and backorder cost. The objective is to find a continuous-review ordering policy that minimizes the expected average costs under constraints of minimum fill rates of RDCs and maximum allowable mean delay of CDC. We developed an algorithm for determining the optimal ordering policies of the CDC and the RDCs. We verified and compared the performance of the algorithm through the simulation using the algorithm result as the input parameters.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.61-73
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• 2019

In 2019, 5G mobile communication technology will be commercialized. From the viewpoint of technological innovation, 5G service can be applied to other industries or developed further. Therefore, it is important to measure the demand of the Internet of things (IoT) because it is predicted to be commercialized widely in the 5G era and its demand hugely effects on the economic value of 5G industry. In this paper, we applied Bayesian method on regression model to find out the demand of 5G IoT service, wearable service in particular. As a result, we confirmed that the Bayesian regression model is closer to the actual value than the existing regression model. These findings can be utilized for predicting future demand of new industries.

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.689-699
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• 2020

This study investigates the effect of life settlement on the monopolistic insurance market. In particular, we consider liquidity cost, which is the cost incurred to the insurer to meet the request of surrender, and trading cost, which is the transaction cost of the policyholders for the settlement. We first show that the introduction of a life settlement can increase insurance demand and enhance consumer welfare even when the trading cost is higher than the liquidity cost. That is, even if the settlement market is less efficient than the insurance market, both insurance demand and consumer welfare can be increased. Second, the insurer's profit can also be increased when settlement is introduced because not only can the insurer save the liquidity cost but also the demand of insurance increases. Lastly, insurance demand does not always decrease when both costs increase. Depending on the population distribution over the liquidity risk, the demand of insurance can be increased or decreased.

• Journal of Energy Engineering
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• v.18 no.2
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• pp.114-124
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• 2009

The Ministry of Knowledge and Economy (MKE) establishes the Basic Plan for Long-Term Electricity Supply and Demand(BPE) biannually, a governmental plan for the stable electricity supply. This study investigated the effects of the electric demand forecast on the energy mix. A simplified simulation model was developed, which replaces the WASP program developed by the KPX and verified by comparing both results. Three different electric demand scenarios were devised based upon the 2005 electric demand forecast: Proper, 5 % higher, and 5% lower. The simplified model calculates the energy mix for each scenario of the year 2005. Then it calculates the energy mix for the proper electric demand forecast of the year 2007 using the energy mixes of the three scenarios as the initial conditions, so that it reveals the effect of electric demand forecast of the previous BPE on the energy mix of the next BPE. As the proper electric demand forecasts of the year 2005 and 2007 are the same, there is no change in the previous and the next BPEs. However when the electric demand forecasts were 5% higher in the previous BPE and proper in the next BPE, some of the planned power plant construction in the previous BPE had to be canceled. Similarly, when the electric demand forecasts were 5% lower in the previous BPE and proper in the next BPE, power plant construction should be urgently increased to meet the increased electric demand. As expected the LNG power plants were affected as their construction periods are shorter than coal fired or nuclear power plants. This study concludes that the electric demand forecast is very important and that it has the risk of long term energy mix.