• 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.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.778-780
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• 1996

The predictive maximum demand controllers often bring about large number of control actions during the every integrating period and/or undesirable load-disconnecting operations during the begining stage if the integrating period. To solve these problems, a fuzzy predictive maximum demand control algorithm is proposed, which determines the sensitivity if control action by urgency if the load interrupting action along with the predicted demand reading to the target or the time arriving at the end stage if the integrating period. A prototype controller employing the proposed algorithm also is developed and its performances are tested by PROCOM SYSTEMS Corperation of Korea.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.403-420
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• 1997

In this paper, we examine the effect of production uncertainty to production control policies. First, we examine two famous production control policies, namely, MRP and JIT from the view point of shop floor control perspective, and analyze the differences between them due to demand fluctuations and activity time variations. Second, we conduct simulation studies on MRP and JIT to draw out the effects of demand fluctuations and activity time variations. Demand fluctuations are further classified into demand lumpiness and demand irregularity. And, activity time variations are further classified into stationary time variations and non-stationary time variations. Experimental results show that, in terms of demand fluctuations, MRP is affected by demand lumpiness, but JIT by demand irregularity. And we also see that both MRP and JIT are influenced by stationary time variation with respect to activity time variations.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1993.10a
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• pp.107-110
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• 1993

This paper presents the technical requirements and configuration of power demand control system in office building Generally, the peak power demand is occurred in cooling period. For power demand control in existing building, the most effective control points are the motors for air handling units.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.185-190
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• 1993

In this paper, we investigate the effect of production uncertainty - especially demand fluctuation and activity time variation, to production control policies. First, we examine three famous production control policies, namely, MRP, JIT, OPT, from shop floor control perspective and analyze the difference among them. Based on these, simulation studies are performed to draw out the effects of demand fluctuation which are classified into demand lumpiness and demand irregularity, and, the effects of activity time variation which are classified into standard time variation and non-standard time variation. Experimental investigation shows that, in terms of demand fluctuations, MRP is affected by demand lumpiness, but JIT by demand irregularity. And we also see that both MRP and JIT are influenced by standard time variation with respect to activity time variations.

• Korea Journal of Hospital Management
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• v.11 no.2
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• pp.32-60
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• 2006

Based on the Job Demand-Control model which was proposed by R. A. Karasek, this study was designed to investigate the relationships among job demand, job control, and job burnout of nurses. In addition, the other aim of the present study was to test the moderating or buffering role of social supports in the relationship between the job demand and job burnout. The analysis based on data collected from 239 nurses who are working in two general hospitals has produced the following results. We found that job demand was primarily related to the exhaustion component of burnout, whereas (lack of) job control was related to the disengagement dimension of burnout. And social supports from the supervisor attenuated the disengagement, whereas social supports from the colleague diminished the exhaustion. But, we found no interaction effects that were expected in the hypotheses. Specifically, social supports didn't buffer the negative effects of job demand on burnout, while job control had the moderating effect which was in opposite direction. The implications of these analyses and limitations of the study were then discussed.

• 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.

• Safety and Health at Work
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• v.14 no.1
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• pp.85-92
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• 2023

Background: Presenteeism is closely related to work performance, work quality and quantity, and productivity at work. According to the job demand-control-support model, job demand, job control, and support play important roles in presenteeism. The present study investigated job characteristics profiles based on the job demand-control-support model and identify the association between job characteristics profiles and presenteeism. Methods: This secondary data analysis used the Sixth Korean Working Condition Survey, a nationwide cross-sectional dataset. The study included 25,361 Korean wage workers employed in the workplace with two or more workers. Participants were classified into four job characteristics profiles based on the job demand-control-support model, using latent profile analysis, and logistic regression was performed to examine the association between study variables. Results: Overall, 11.0 % of study participants reported experience of presenteeism in the past 12 months. Age, sex, location, monthly income, shift work, work hours, health problems, and sleep disturbances were significantly associated with presenteeism. The rate of presenteeism was the highest in the passive isolate group. The passive collective, active collective, and low-stain collective groups had a 23.0%, 21.0%, and 29.0% lower likelihood of experiencing presenteeism, respectively, than the passive isolate group. Conclusions: The job demand-control-support profiles and the risk of presenteeism were significantly associated. The most significant group that lowered the experience of presenteeism was the low-strain collective group, which had a low level of demand and high levels of control and support. Therefore, we need a policy to reduce job demand and increase job control and support at the organizational and national levels.

• Journal of the Korean Home Economics Association
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• v.48 no.8
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• pp.13-26
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• 2010

This study tested the path model with regard to how certain variables (control attribution, demand-control-support of activity, and control strategy) affected the elderly workers' subjective well-being(swb). In the path model, the exogenous variables were internal and external control attribution. We used demand-control-support of activity, and primary and secondary control strategies as mediating variables. The endogenous variable was each elderly worker's swb. Study participants were 205 elders participating in an "education activity". We used descriptive statistical analysis, Pearson's correlation and hierarchical multiple regression to examine data collected from structured interviews with the participants. Path analysis revealed the followings: First, secondary control strategy was the strongest predictor of participants' swb but internal control attribution, demand of activity, and support of activity also positively affected participants' swb. Second, internal control attribution indirectly affected the participants' swb. Finally primary control strategy negatively affected on the participants' swb.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.427-431
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• 1994

The objective of this paper is to provide an inventory control policy for the system that carries a single item with a multiple demand classes, when the demand is Poisson distributed random variable. The inventory control process includes the process of determining the reorder point, and the process of inventory control during the lead time. The goal of the optimization process is to achieve the service level of each demand class as well as the system-wide total service level at a preset desired service level while sustaining a minimum average inventory.