• Proceedings of the KIEE Conference
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• summer
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• pp.660-662
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• 2004

Cooling demand in Korea has increased constantly. Furthermore, an evaluation and savings of cooling demand has impacted on summer DSM and investment in Korea. Absorbed cooling system uses gas. It could achieve reductions in summer peak load and increase gas demand simultaneously. However its efficiency rate is lower than electric system. Gas cooling system uses separate meter. Therefore we could analyze monthly cooling demand and derive annual uses pattern. This paper analyzes demand pattern of gas cooling and its effects on electricity savings. Also this paper presents the course of policy in electricity sector on spreading of gas cooling measures.

• Journal of Agricultural Extension & Community Development
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• v.30 no.1
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• pp.43-52
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• 2023

This study aims to examine the effects of GDP as a proxy variable of income, consumer price index as a proxy variable of price, and foot-and-mouth disease and avian influenza as derby variables on rural tourism demand. The independent variables in this research were gross domestic product(GDP), consumer price index(CPI), and dummy variable(DM) such as food & mouth disease & highly pathogenic avian influenza. Results showed that GDP affected tourism demand positively whereas DM influenced negatively. The study suggested that it was important for policy-mconsider GDP and DM when making decision on strategic tourism management. In conclusion, first, gross domestic product was found to have a statistically significant effect on rural tourism demand. Second, avian influenza was found to have a statistically negative effect on rural tourism demand. The results of this study can be used to establish a reasonable rural tourism policy in the future economic dimension.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.144-144
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• 2021

The rapid urbanization in many Asian countries has taken millions of people from the rural countryside to concentrated megacities, which eventually putting pressure on the existing water resources. The over-growing population and increasing living standard of people in the urban region of developed as well as developing countries such as Korea, China, Japan and India have witnessed a drastic change in terms of domestic water demand for the past few decades. In this study, we used the concept of potential surface water availability in the form of surface runoff for future vulnerability assessment. We focused on 42 megacities having population more than 5 million as per the United Nations (UN) census data 2020. The study shows that 30 out of 42 cities having more than 180L/p/d demand for domestic use based on various references. We have predicted the domestic water demand for all the cities on the basis of current per capita demand up to 2035 using UN projected population data. We found that the projected water demand in megacities such as Seoul, Busan, Shanghai, Ghuanzou are increasing because of high population as well as GDP growth rate. On the contrary, megacities of Japan considered in our stud shows less water demand in future due to decreasing trend of population. As per the past records provided by the local municipalities/authorities, we projected different scenarios based on the future supply for various megacities such as Chennai, Delhi, Karachi, Mumbai, Shanghai, Wuhan, etc. We found that the supply to demand ratio of these cities would be below 75% for future period and if such trend continues then the inhabitants will face serious water stress conditions. Outcomes of this study would help the local policy makers to adopt sustainable initiatives on urban water governance to avoid the severe water stress conditions in the vulnerable megacities.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.68-70
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• 2003

This paper proposes the demand-side management(DSM) monitoring system of high efficient end-use appliances considering demand-side bidding (DSB). The effect on the market propagation of high efficient appliances by demand side bidding is analysed. Seasonal Peak demand forecasting and propagation capacity of these appliances are analysed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1103-1111
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• 2011

This paper is developed to Energy Balance Flow show the flow of total energy resource be used nationally. The Energy Balance Flow is applicable of demand management factor through the analysis of foreign energy model of supply and demand and energy statistic data in the country. This study is based on and developed to Energy system management model is able to appraisal efficient of energy cost cutting, CO2 emission reduction and Energy saving at the national level calculated effect reached amount of primary energy to change of energy flow followed application of demand side management factor is able to appraisal quantitatively at the total energy to model of demand and supply.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1111-1115
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• 2014

With the increasing interest of a demand side management using a Smart Grid infrastructure, the demand resources and energy usage data management becomes an important factor in energy industry. In addition, with the help of Advanced Measuring Infrastructure(AMI), energy usage data becomes a Big Data System. Therefore, it becomes difficult to store and manage the demand resources big data using a traditional relational database management system. Furthermore, not many researches have been done to analyze the big energy data collected using AMI. In this paper, we are proposing a Hadoop based Big Data system to manage the demand resources energy data and we will also show how the demand side management systems can be used to improve energy efficiency.

• Journal of Korean Society of Forest Science
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• v.95 no.2
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• pp.203-208
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• 2006

This study compared the roundwood demand prediction accuracy of econometric and time-series models using Korean data. The roundwood was divided into softwood and hardwood by species. The econometric model of roundwood demand was specified with four explanatory variables; own price, substitute price, gross domestic product, dummy. The time-series model was specified with lagged endogenous variable. The dummy variable reflected the abrupt decrease in roundwood demand in the late 1990's in the case of softwood roundwood, and the boom of plywood export in the late 1970's in the case of hardwood roundwood. On the other hand, the prediction accuracy was estimated on the basis of Residual Mean Square Errors(RMSE). The results showed that the softwood roundwood demand prediction can be performed more accurately by econometric model than by time-series model. However, the hardwood roundwood demand prediction accuracy was similar in the case of using econometric and time-series model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.138-146
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• 2012

This paper studies the effect of information quality level and customer demand on performance measures in a supply chain. The information quality level compares 2 types, the information levels of a customer demand and a lead time. The customer demand process follows a general auto-correlated AR(1) process without seasonality. In the AR(1) process, ${\sigma}$ indicates the degree of demand fluctuation and ${\rho}$ means the trend of customer demand. ANOVA tests using a 5% significance level are performed in SPSS to examine significant performance changes among various cases.

• 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.

• Journal of Smart Tourism
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• v.2 no.3
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• pp.31-38
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• 2022

Understanding demand for travel websites can help hoteliers better evaluate their own multi-channel distribution and reputation management strategies. In this study, we estimated demand for eight major travel websites based on the user percentage in 3,120 U.S. counties. Results highlighted the importance of four types of factors: sociodemographic, economic, Internet use-related, and travel-related. Differences between websites were also compared based on estimated coefficients. For example, the demand for Expedia.com appeared to be driven by age, education background, income, and foreign travel history, whereas the demand for Hotels.com was driven by the proportion of the African American population and domestic travel history. Lastly, implications are provided.