• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1296-1304
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• 2013

This study performed an analysis on power demand reduction effects exhibited by demand response programs, which are advanced from traditional demand-side management programs, in the smart grid environment. The target demand response systems for the analysis included incentive-based load control systems (2 month-ahead demand control system, 1~5 days ahead demand control system, and demand bidding system), which are currently implemented in Korea, and price-based demand response systems (mainly critical peak pricing system or real-time pricing system, currently not implemented, but representative demand response systems). Firstly, the status of the above systems at home and abroad was briefly examined. Next, energy saving effects and peak demand reduction effects of implementing the critical peak or real-time pricing systems, which are price-based demand response systems, and the existing incentive-based load control systems were estimated.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.3
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• pp.98-105
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• 2019

In the past 30 years, our aviation demand has been growing continuously. As such, the importance of the demand forecasting field is increasing. In this study, the factors influencing Korea's international air demand were selected, and the international air demand was analyzed, forecasted and reviewed through OLS multiple regression analysis. As a result, passenger demand was affected by GDP per capita, oil price and exchange rate, while cargo demand was affected by GDP per capita and private consumption growth rate. In particular, passenger demand was analyzed to be sensitive to temporary external shocks, and cargo demand was more affected by economic variables than temporary external shocks. Demand forecasting, OLS multiple regression analysis, passenger demand, cargo demand, transient external shocks, economic variables.

• Earthquakes and Structures
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• v.14 no.3
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• pp.203-214
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• 2018

Predictive demand and collapse fragility functions are two essential components of the probabilistic seismic demand analysis that are commonly developed based on statistics with enormous, costly and time consuming data gathering. Although this approach might be justified for research purposes, it is not appealing for practical applications because of its computational cost. Thus, in this paper, Bayesian regression-based demand and collapse models are proposed to eliminate the need of time-consuming analyses. The demand model developed in the form of linear equation predicts overall maximum inter-story drift of the lowto mid-rise regular steel moment resisting frames (SMRFs), while the collapse model mathematically expressed by lognormal cumulative distribution function provides collapse occurrence probability for a given spectral acceleration at the fundamental period of the structure. Next, as an application, the proposed demand and collapse functions are implemented in a seismic fragility analysis to develop fragility and consequently seismic demand curves of three example buildings. The accuracy provided by utilization of the proposed models, with considering computation reduction, are compared with those directly obtained from Incremental Dynamic analysis, which is a computer-intensive procedure.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1282-1289
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• 2011

The rail passenger demand for the railroad operations required a short-term demand rather than a long-term demand. The rail passenger demand can be classified according to the purpose. First, the rail passenger demand will be use to the restructure of line planning on the current operating line. Second, the rail passenger demand will be use to the line planning on the new line and purchasing the train vehicles. The objective of study is to analyze the travel behavior of rail passenger for modeling of short-term demand forecasting. The scope of research is the passenger of KTX. The travel behavior was analyzed the daily trips, origin/destination trips for KTX passenger using the ANOVA and the clustering analysis. The results of analysis provide the directions of the short-term demand forecasting model.

• Perspectives in Nursing Science
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• v.13 no.2
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• pp.81-87
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• 2016

Purpose: The aim of this study is to review the nurse demand forecasting methods in empirical studies published during 1991~2014 and suggest ideas to improve the validity in nurse demand forecasting. Methods: Previous studies on nurse demand forecasting methodology were categorized into four groups: time series analysis, top-down approach of workforce requirement, bottom-up approach of workforce requirement, and labor market analysis. Major methodological properties of each group were summarized and compared. Results: Time series analysis and top-down approach were the most frequently used forecasting methodologies. Conclusion: To improve decision-making in nursing workforce planning, stakeholders should consider a variety of demand forecasting methods and appraise the validity of forecasting nurse demand.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.113-123
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• 2006

Flash memory has been increasingly used in handhold devices not only for data storage, but also for code storage. Because NAND flash memory only provides sequential access feature, a traditionally accepted solution to execute the program from NAND flash memory is shadowing. But, shadowing has significant drawbacks increasing a booting time of the system and consuming severe DRAM space. Demand paging has obtained significant attention for program execution from NAND flash memory. But. one of the issues is that there has been no effort to bound demand paging cost in flash memory and to analyze the worst case performance of demand paging. For the worst case timing analysis of programs running from NAND flash memory. the worst case demand paging costs should be estimated. In this paper, we propose two different WCRT analysis methods considering demand paging costs, DP-Pessimistic and DP-Accurate, depending on the accuracy and the complexity of analysis. Also, we compare the accuracy butween DP-Pessimistic and DP-Accurate by using the simulation.

• The Korean Journal of Emergency Medical Services
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• v.6 no.1
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• pp.77-86
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• 2002

The purposes of this research which was conducted by surveying lost/added unit hours reports, unit hour demand analysis worksheets from prehospital care reports of two squads in Kyonggi Provincial Fire and Disaster Headquarters for 20 weeks (January 1, 2002 - May 20, 2002) are to get Unit Hour Utilizations. Call Demands such as Unit Hour Demand, Simple Average Demand, High Average Demand, Peak Average Demand, the High Actual Demand. The conclusions from this analysis were summarized as follows: (1) By revealing Unit Hour Produced 3223.9, Call Volume 964, Unit Hour Utilization 0.299 at the Squad A and Unit Hour Produced 3328.4, Call Volume 901, Unit Hour Utilization 0.271 at the Squad B induced Korean Squads to chance identification, definition, direction of Unit Hour Utilization. (2) By revealing Simple Average Demand 7.4 on Monday Tuesday, High Average Demand 9.6 on Tuesday Friday. Peak Average Demand 11.5 on Tuesday, the High Actual Demand 12 on Tuesday Wednesday at the Squad A and Simple Average Demand 6.8 on Sunday, High Average Demand 10.4 on Monday, Peak Average Demand 11.5 on Monday, the High Actual Demand 13 on Monday at the Squad B enabled Korean Squads to utilize System Status Management. (3) The Maximum Calls per Unit Hour were 115 for 23:00~23:59, the Minimum Calls per Unit Hour were 46 for 05:00~05:49 in two squads. The Maximum Calls per Unit Hour were 7.4 on Tuesday Saturday, the Minimum Calls per Unit Hour were 6.1 on Thursday at the Squad A. The Maximum Calls per Unit Hour were 7.3 on Monday Saturday, the Minimum Calls per Unit Hour were 5.6 on Thursday at the Squad B. (4) Analyzing demand for EMTs in the optimum emergency medical service of Korea, we have been able to utilize this Unit Hour Utilization in company with the established estimation methods such as international comparisons or the number of ambulances for scientific reasonable estimation. (5) These Call Demands which were limited to the demand time in this study will make us expect some following studies including demand time, demand time, demand map for Strategic Deployment.

• Journal of Korean Society of Rural Planning
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• v.15 no.1
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• pp.61-71
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• 2009

The objective of this research was to analyze the determinants of demand for residential settlements in rural societies. A significant aspect of the demand analysis was to consider depopulation classification as a moderating variable with a view to its role as an essential dividing factor of socioeconomic characteristics and physical environments of the areas of concern. The data collection for analysis was divided according to types of depopulation into the three categories of less developed, stagnated, and developed areas. For the cause and effect analysis between the residential demand and factors of settlement, the ordered probit model was applied. Significant determinants of settlement demand unfolded according to depopulation types. In the case of less developed areas, residential demand was affected significantly by the factors of daily life convenience and public facilities. Key settlement demand determinants of stagnated regions included the aspects of basic natural environment, daily life convenience and education. Meanwhile, key settlement demand determinants for developed areas included education and agriculture economic aspects. The importance-performance analysis was also applied to a set of settlement characteristics of rural communities to figure out the settlement factors requiring urgent endeavor to improve.

• Journal of the Earthquake Engineering Society of Korea
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• v.26 no.1
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• pp.31-38
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• 2022

Based on the nonlinear static analysis and the approximate seismic evaluation method adopted in "Guidelines for seismic performance evaluation for existing buildings, two methods to calculate strength demand for retrofitting individual structural walls in unreinforced masonry buildings are proposed." The displacement coefficient method to determine displacement demand from nonlinear static analysis results is used for the inverse calculation of overall strength demand required to reduce the displacement demand to a target value meeting the performance objective of the unreinforced masonry building to retrofit. A preliminary seismic evaluation method to screen out vulnerable buildings, of which detailed evaluation is necessary, is utilized to calculate overall strength demand without structural analysis based on the difference between the seismic demand and capacity. A system modification factor is introduced to the preliminary seismic evaluation method to reduce the strength demand considering inelastic deformation. The overall strength demand is distributed to the structural walls to retrofit based on the wall stiffness, including the remaining walls or otherwise. Four detached residential houses are modeled and analyzed using the nonlinear static and preliminary evaluation procedures to examine the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.396-400
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• 2005

This paper proposes the cost analysis on the energy efficient equipment when this equipment is participated in the demand-side bidding. Conventional demand-side bidding is exercised through load re-distribution. However if this load reduction is exercised by the use of high efficient equipment, its effect will be assumed to be more economical. This paper analyses this cost-benefit effect of high efficient equipment in the demand-side bidding.