• Journal of the Korea Safety Management & Science
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• v.18 no.4
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• pp.73-80
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• 2016

This study highlights the main effect of job demand, work shift, work environment and stressors on the railway traffic controller's health, and the moderating effect of work0life balance. The result of empirical analysis based on questionnaires received from 328 traffic controllers working at 10 railway operating companies indicates that job demand, work shift, work environment and stressors have significant effect on their health, among which stressors is a major factor. In the respect of moderating effect, WLB showed no significance except for job demand. This result implies that controller's health can not be enhanced through their individual family or leisure life. Therefore, effective countermeasures and policy to mitigate their health problems and heal their symptoms are urgent.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.161-163
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• 2006

This paper introduce the technology of peak demand reduction using automatic water tank pumping system on the apartment. That systems on the apartments installed water tank can control pumping(electricity) demand. Generally, system peak demand is occurred at the same time on workday and many water pumps consume electric power randomly. At this point, shift of operating time of water pump can reduce peak demand using automatic water tank pumping system. We were operating this system on some apartments for test of effect of peak demand reduction. and we represent result of demand shift. This result suggests that spread of the automatic water pumping system can contribute to reduce system peak demand and reduce system operation cost.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.44-48
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• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.3
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• pp.85-97
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• 2000

In this paper, static and dynamic shift control stategies of CVT speed ratio are suggested. For the static shift control, in order to operate engine on the optimal operating region, a fuzzy control logic is used. In the fuzzy logic, S- factor that is defined as a degree of sportiness is introduced. Simulation results show that the static shift control strategy based on the fuzzy logic selects the optimal operating point automatically between the economy and the sporty mode corresponding to the driver's desire and the driving condition. For the dynamic shift control strategy, a shift speed map is suggested which determines the shift sped as fast or slow based on Δi, the difference between the desired speed ratio id and the actual speed ratio i, and throttle opening. It is seen from the simulation results that the CVT shift speed is determined by the dynamic shift control strategy to provide appropriate performance and comfort for the driver's demand and driving condition. Additionally, experiments are performed to investigate the dynamic performance of the shift speed for the lift foot up. From the experimental results, it is found that improved shift feeling can be obtained by the dynamic shift control strategy when lift foot up occurs.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.12.1-12.12
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• 2023

Background: The purpose of this study is to investigate the relationship between job stress and impaired fasting glycemia (IFG) of male workers in a manufacturing industry. Methods: Data were collected from 5,886 male workers in a manufacturing industry who participated in the medical examination from June 19 to August 14, 2020 through self-reported questionnaires. The general characteristics of the subjects, shift work, high blood pressure, dyslipidemia, and job stress were included. Job stress was measured using the Korean Occupational Stress Scale (KOSS) consisting of 8 items and 43 questions. Multivariable logistic regression analysis was used to investigate the IFG association with job stress. Results: Among the various factors that can cause job stress, only high job demand was associated with a risk of IFG (odds ratio, 1.43; 95% confidence interval, 1.13-1.82) especially in non-shift worker. For all other factors, no statistically significant results were obtained. Conclusions: In this study of male workers engaged in the Korean steel manufacturing industry, the 'job demand' item among job stress of non-shift worker was related to IFG.

• IE interfaces
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• v.24 no.4
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• pp.351-361
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• 2011

Forecasting of electricity demand have difficulty in adapting to abrupt weather changes along with a radical shift in major regional and global climates. This has lead to increasing attention to research on the immediate and accurate forecasting model. Technically, this implies that a model requires only a few input variables all of which are easily obtainable, and its predictive performance is comparable with other competing models. To meet the ends, this paper presents an energy demand forecasting model that uses the variable selection or extraction methods of data mining to select only relevant input variables, and employs support vector regression method for accurate prediction. Also, it proposes a novel performance measure for time-series prediction, shift index, followed by description on preprocessing procedure. A comparative evaluation of the proposed method with other representative data mining models such as an auto-regression model, an artificial neural network model, an ordinary support vector regression model was carried out for obtaining the forecast of monthly electricity demand from 2000 to 2008 based on data provided by Korea Energy Economics Institute. Among the models tested, the proposed method was shown promising results than others.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.81-90
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• 2018

The 'Hyper-connected society' in which all objects such as people, device, place are connected via networks and share information being realized. As the information and communication environment changes, spatial information also faces a significant challenge. Korean government is striving to meet the social demand for spatial information that will bring 'Hyper-connectivity' such as autonomous vehicles, drones. Until now, however, it has only partially responded to urgent demand and has not prepared a fundamental countermeasure. In order to effectively and actively respond to the demand for spatial information that is needed in the Hyper-connected society, a strategy that can lead to mid- to long-term fundamental changes is needed. The purpose of this study is to analyze the future demand and application characteristics of spatial information confronted with a big paradigm shift called 'Hyper-connected society', and to search spatial information strategy that can cope with the demand of spatial information in future society.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1116-1120
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• 2014

With the shift of the energy paradigm from supply side management to demand side management, demand resource management and demand response plays an important role in the energy industry. As a consequency, a lot of researches have been done to provide a suitable demand response system. However, most of the demand response systems are based on the propriety products that cannot be modified. In this paper, we are proposing an automated demand response system using an EnerNOC provided open source code. We implemented the demand response server (VTN) and demand response client (VEN), and validated the OpenADR2.0 compliances using the open source code. We also used an Arduino microcontoller to demonstrate the communication schemes to control various devices.

• Journal of the Korean Dietetic Association
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• v.29 no.1
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• pp.13-30
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• 2023

This study investigates the effect of working hours on the dietary behaviors and dietary quality of male industrial workers employed in rotating shifts. The survey was conducted from February to March 2022, enrolling 209 male workers operating in rotational shifts at industries in the Chungcheongnam-do region. Eating behavior and health awareness were investigated during the morning shift, afternoon shift, and night shift for the same subjects. The shift timings were found to be associated with dietary behavior, which had an impact on the dietary quality of workers. Negative effects of shift timings on diet and health were also perceived by the shift workers. The frequency of alcohol consumption was high during the morning shift, and the frequency of night time snack intake was high during the afternoon shift. During the night shift, there was decreased vegetable intake and increased ramyeon intake. Compared to the morning shift, a significant decrease in dietary quality scores was found during the night shift. The workers recognized that rotating shift work negatively affected health, eating habits and sleep. There was a high demand for providing a variety of menus and healthy night snacks in the company cafeteria. When nutritional counseling and educational health services were provided, the willingness to participate was high. Therefore, to improve the health and dietary quality of shift workers, there is a need to provide diets suitable for the working environment and the characteristics, and to provide nutrition management services.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.97-110
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• 2009

The objective of this research was to develop a rural settlement demand model to analyze the determinants of settlement demand of urban residents. The point aimed at from model development was deriving stated preference of potential consumers towards rural settlement through setting a hypothetical market, and using settlement subsidy as a surrogate variable for price in the demand model. The adequate demand model deducted from hypothetical market data was derived from the basis of Hanemann's utility difference theory. In the rural settlement demand model, willingness to accept was expressed by a function of settlement subsidy. Data utilized in the analysis was collected from surveys of households nationwide. According to inferred results of the demand model, settlement subsidy had a significant influence on increasing demand for rural settlement. A significant common element was found among variables affecting demand increase through demand curve shift. The majority group of those with high rural settlement demand sought agricultural activity as their main motive, due to harsh urban environments aggravated by unstable job market conditions. Subsequently, restriction of income opportunities in rural areas does not produce an entrance barrier for potential rural settlers. Moreover, this argument could be supported by the common trend of those with high rural settlement demand generally tending to have low incomes. Due to such characteristics of concerned groups of rural settlement demand, they tended to react susceptibly to the subsidy provided by the government and local autonomous entities.