• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3218-3226
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• 2009

A number of on-demand routing protocols for sensor networks have been proposed yet. However, the majority of proposed on-demand routing protocols for sensor networks are not suitable for a relatively poor wireless environment and sensor applications requiring reliable data transmission due to using a hop-count metric for their protocols. In this paper, we proposed a minimum LQI(Link Quality Indicator) based on-demand sensor network routing protocol that is suitable for a relatively poor wireless environment and implemented the proposed routing protocol on a TinyOS. We also compared the implemented protocol with typical hop count based routing protocol by carrying out performance experiments on a multi-hop testbed. The results from these experiments showed that the successful transmission rate of the proposed routing protocol is higher than that of typical hop count based routing protocol over a poor wireless link.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1799-1807
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• 2016

In this paper, we propose the automatic demand response systems which reduce the electric power consumption for the period automatically distinct from the existing passive demand response that a subscriber directly controls the energy consumption. The proposed systems are based on SEP 2.0 and consist of the demand response management program, the demand response server, and the demand response client. The demand response program shows the current status of the electric power use to a subscriber and supports the function which the administrator enables to creates or cancels a demand response event. The demand response server transmits the demand response event received from the demand response management program to the demand response client through SEP 2.0 protocol, and it stores the metering data from the demand response client in a database. After extracting the data, such as the demand response the start time, the duration, the reduction level, the demand response client reduces the electric power consumption for the period.

• Research in Community and Public Health Nursing
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• v.14 no.4
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• pp.587-597
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• 2003

Purpose: The purpose of this study was to estimate the demand and supply of visiting nursing services provided by health centers in urban area, aiming at strengthening infrastructure, which may improved the quality of life and health status of vulnerable population in the community. Methods: This study was conducted through nominal group discussion, focus group study. The demand and supply of visiting nursing were estimated by health economists based on the secondary analysis data from 25 health centers in Seoul. Result: Primary targets for the visiting nursing must be people who are homebound in the community. They can be classified into: a group of Level I: chronic patients who need visiting nursing care at least once a week: and a group of Level II: vulnerable families that need management periodically e. g. twice a month. Based on the estimation of demand for visiting nursing services in the community, the estimated supply required was $651{\sim}770$ visiting nurses including home health nurses in visiting nursing programs based on health centers in Seoul. Conclusions: The estimated demand and supply of visiting nursing are expected to provide basic data for establishing alternative policies on visiting nursing infrastructure that might be accomplished through demand-based visiting nursing programs by districts.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.991-994
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• 2016

This paper presents a load management method based on OpenADR of smart grid. Previous demand side algorithm is restricted on reducing peak power. But, in this paper we suggest a method of performing the energy-saving control according to the power price utilizing building automatic control system installed on the customer side in the case of hourly differential pricing signal is transmitted to the open automated demand response system. And, we showed the integrated demand management software for 3 buildings.

• Advances in concrete construction
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• v.9 no.4
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• pp.337-343
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• 2020

In the present study, by employing fragility analysis, the seismic vulnerability of a concrete girder bridge, one of the most common existing structural bridge systems, has been performed. To this end, drift demand model as a fundamental ingredient of any probabilistic decision-making analyses is initially developed in terms of the two most common intensity measures, i.e., PGA and Sa (T₁). Developing a probabilistic demand model requires a reliable database that is established in this paper by performing incremental dynamic analysis (IDA) under a set of 20 ground motion records. Next, by employing Bayesian statistical inference drift demand models are developed based on pre-collapse data obtained from IDA. Then, the accuracy and reasonability of the developed models are investigated by plotting diagnosis graphs. This graphical analysis demonstrates probabilistic demand model developed in terms of PGA is more reliable. Afterward, fragility curves according to PGA based-demand model are developed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1005-1012
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• 2021

Recently, the use of various location-based services-based location information systems using maps on the web has been expanding, and there is a need for a monitoring system that can check power demand in real time as an alternative to energy saving. In this study, we developed a deep learning real-time virtual power demand prediction web system using open source-based mapping service to analyze and predict the characteristics of power demand data using deep learning. In particular, the proposed system uses the LSTM(Long Short-Term Memory) deep learning model to enable power demand and predictive analysis locally, and provides visualization of analyzed information. Future proposed systems will not only be utilized to identify and analyze the supply and demand and forecast status of energy by region, but also apply to other industrial energies.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.86-93
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• 2015

Recently, ESS became efficient device to stabilize electric power supply system with the development SG related technology. In fact. there are some constraints to supply ESS, because of the high cost and required space, but rapid technology development for ESS will make it more useful soon. So, through this paper, we analyzed the benefit and demand effect when the battery is applied the building based on the measured energy consumption. After that, we got the conclusion that there is a volume limit in ESS application, in a benefit view point. And we realized that there is a demand violation, and the Cost-based BEMS is the best solution to enhance the effect of ESS application.

• Health Policy and Management
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• v.3 no.1
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• pp.146-168
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• 1993

The study was conducted to project supply and demand of the nurses till year 2010 based on analysis of supply and demand of nurses up to year 1991. Results of the study will provide invaluable information for nurses manpower planning as well as overall health manpower planning for the 21th century. It is projected that nurses will be oversupplied based on the current prductivity which is undesirable situation if the quality of care is considered, and undersupplied based on the the medical law as well as optimal productivity. Thus, it is desirable to increase active supply of nurses. One of the ways of increasing active supply would be increasing the size of training and education. But, considering low employment rate of nurses which is about 59% better way of solving problems related to nurses shortage would be improvement in nurses' employment rate. According to simulation study done as part of this study, if nurses' employment rate goes up to 80%, there is no need for increasing the size of training to meet the demand at the level of medical law.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• The Journal of Industrial Distribution & Business
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• v.7 no.3
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• pp.27-36
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• 2016

Purpose - Considering the importance of housing needs to real estate market, domestic studies on real estate prices from the perspective of demand are basically based on macro-data, but relatively few are associated with micro-data of urban real estate demand. We try to find a reliable relation of elasticity of demand and commercial housing market. Research design, data, and methodology - In this paper, we have derived housing demand theoretic method and have utilized micro-data of residential family housing survey of downtown area in Kunming City in October, 2015 to estimate income elasticity and price elasticity of housing demand respectively and make a comparative analysis. Results - The results indicate that income elasticity and price elasticity of families with owner-occupied housing are both larger than those of families with rental housing. Income elasticity of housing demand of urban residential families in Kunming is far below the foreign average and eastern coastal cities level, however, the corresponding price elasticity is far higher. Conclusions - We suggest that housing affordability of urban families in western China are constrained by the level of economic development, and the current housing price level has exceeded the economic affordability and psychological expectation of ordinary residents. Furthermore, noticing the great rigidity of housing demand, the expansion space of housing market for improvement and for commodity is limited.