• Journal of the Ergonomics Society of Korea
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• v.24 no.1
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• pp.9-17
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• 2005

81.1% of traffic accidents is attributed to the drivers. In this regard, D/E model is a practical and effective method in terms of the cost and time in evaluating the road hazardousness. To examine the validity of the threshold values by the levels of demand We selected 10 subjects and collected their physiological signals while they were driving on Honam Highway (Jeonju ${\leftrighttarro}$ Hoideog section). Based on the collected data, the hazardous road condition was evaluated using the new threshold values of the effort level determined by cluster analysis. In applying the D/E model, a decision method based on the demand level was suggested, using a traffic accident prediction model. Additionally, the limit value of the effort level was determined using the drivers' physiological signal data collected at the highway. A comparison analysis of the two D/E models revealed no significant difference: The existing method and the clustering method determined 9 and 7 hazardous road zones, respectively, while actual traffic accidents were reported in 6 and 4 zones, respectively among the predicted road hazardous zones. However, the latter method suggested a more scientific and rational basis in determining the limit value of the Effort level. In conclusion, although D/E model has a great merit as a pioneering method to reflect human factors in evaluating the road hazardousness, it is believed that this method could be improved by a more dynamic method that considers the traffic conditions and the individual physiological signal of the drivers simultaneously in determining a better limit.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.95-105
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• 2009

Traffic accidents on highways are likely to happen when there is an imbalance in the complex relationships among key elements such as road geometries, driver related factors, and mechanical performances. The Demand-Effort Model (DEM), which evaluates highway safety, can be explained by the imbalance, which occurs when the level of demand of the driver's attention to the road environment exceeds that of the response from the driver. This study suggests a new model that improves the reliability of the current DEM through the reinterpretation on the physiological signals with the help of the Neural Network Model (NNM). The data were collected from 149 subjects, who drove a test vehicle on the Yongdong, Honam, and Seohaean Expressways in Korea. Three important results could be drawn from the recursive tests as follows; (1) Only 5 out of 10 parameters on the physiological signals which are currently used were proven to be meaningful through the Normality Test, Cluster Analysis, and Mann-Whitney Analysis. (2) The revised DEM, which internally uses the NNM, showed more reliable results than existing DEM. Group 1, which is based on the new DEM showed 80.0% of accuracy in measuring the level of driver's efforts, however, that of Group 2 based on the current DEM was 74.3%. (3) Field tests on the Honam Expressway showed lower 'type II error' with the new DEM (40.5%) than the old DEM (58.8%). The DEM is designed as a quick and easy way to determine highway safety prior to the minute road safety audit (RSA) by a professional audit team. Then a new DEM, which is based on the NNM, needs to be considered since it showed higher reliability and lower error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.469-474
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• 2020

This study explains the characteristics of micro-insurance based on the theoretical model of health insurance, such as the low demand of low-income people and the lower demand of higher risk aversion. In particular, these characteristics contradict the existing insurance theory which states that the lower the income, the higher the risk aversion, and the higher the demand for insurance. This study postulates a two-period model focusing on health insurance, contrary to a one-period model assumed in existing studies. As a result, first, we show that the decrease in income leads to a decrease in the preventive effort for illness. Second, we offer a model for micro-insurance in which the individual chooses a partial insurance under an actuarially fair insurance premium, while full insurance is optimal in existing studies. Third, we also show that the insurance demand decreases when the outlook for the future improves. Fourth, we finally show that the lack of trust and default risk of the insurer decrease the insurance demand as risk aversion increases.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.35-39
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• 2003

Effort has been given to improve demand forecast methodology of rail system since it can have great impact on project evaluation of rail system investment. However most of demand forecast softwares developed in western countries where concerns have been provided mostly to private transport and they should be updated in order to reflect our country's situation accurately. Therefore, this paper aims, especially focusing on rail system, to do comparison analysis of oversea's passenger demand forecast softwares and provide some ideas to develop the updated demand forecast system which enables to reflect our country's situation accurately. Main conclusions are that we will need to have well described model for real situation. So we will have to study for these aspects for travel demand forecasting system and develop the package architecture.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1232-1255
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• 2011

This paper proposes a model for demand forecasting that will require less effort in the process of utilizing the new product diffusion model while also allowing for more objective and timely application. Drawing upon the theoretical foundation provided by the hype cycle model and the consumer adoption model, this proposed model makes it possible to estimate the maximum market potential based solely on bibliometrics and the scale of the early market, thereby presenting a method for supplying the major parameters required for the Bass model. Upon analyzing the forecasting ability of this model by applying it to the case of the hybrid car market, the model was confirmed to be capable of successfully forecasting results similar in scale to the market potential deduced through various other objective sources of information, thus underscoring the potentials of utilizing this model. Moreover, even the hype cycle or the life cycle can be estimated through direct linkage with bibliometrics and the Bass model. In cases where the hype cycles of other models have been observed, the forecasting ability of this model was demonstrated through simple case studies. Since this proposed model yields a maximum market potential that can also be applied directly to other growth curve models, the model presented in the following paper provides new directions in the endeavor to forecast technology diffusion and identify promising technologies through bibliometrics.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.3
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• pp.1-7
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• 2015

Korea's electricity supply and demand policy has focusing on electricity demand side management instead of the expanding supply and a lot of effort for LED(Light Emitting Diode) at the time. This paper calculated the optimal subsidy for LED spread. For this purpose, it analyzed the impact on spread of the lighting appliances each subsidy level from BDM(Bass Diffusion Model) and predicted the number of lighting appliances according to subsidy level in the future. The case study is calculated susidy for satisfaction of LED target using the suggested model in the future and verified availability.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.15-22
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• 2009

There exist some limits when we forecast urban railway demand by traditional 4 step model. The first reason is that the model based on socioeconomic data by an administrative unit, 'Dong', yields a 'Dong' unit trip matrix. But a 'Dong' often has two or more stations. The second reason is that urban railway demand by station would be affected rather by station access area on foot than by a 'Dong' unit. So the model based on 'Dong' characteristic data have some inaccuracies in itself. Owing to the limits of the model based on 'Dong' unit data, there exits some difficulty in forecasting urban railway demand by station. So this paper studied two alternatives. The first is to forecast the demand by using the data of station access area on foot rather than 'Dong' unit data. This needs too much time and effort to collect data and analyse them, while the accuracy of the model didn't improve a lot. The second is to adjust the location of 'Dong' centroid and the length of centroid connector link. By this way we can reflect the characteristics of station access area on foot under traditional 4 step model. Comparing the expected demand to the observed data for each station, the result looks like very similar.

• Korean Journal of Health Education and Promotion
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• v.12 no.1
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• pp.22-46
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• 1995

This is an effort to project health care resources in need for the elderly in the future when advanced transportation systems would greatly reduce geographical accessibility to health care services for the rural elderly. Two areas, Kimhae and Chuncheon, were selected for the study. Projection of health professionals and health care institutions for the elderly were made based on the analysis for the morbidity and illness behavior reported to two data sources, National Survey for the Elderly in 1992 by Korea Institute for Health and Social Affairs and beneficiary data by Korea Medical Insurance Cooperation for those living in the study areas in 1992. Projected number of health professionals and health care institutions were estimated for each area under study in years of 2010 and 2030, with those in a Japanese being used as a standard. Policy implications were discussed.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.145-153
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• 2008

This study proposes a facility location model in consideration of spatial coverage and travel cost as an effort to make objective and effective decisions of natural gas filling stations. The proposed model is developed for fixed stations and consists of two stages. The first stage employs a heuristic algorithm to find a set of locations which satisfy the spatial coverage constraints determined by the maximum travel distance between the filling stations and bus depots. In the second stage, the optimal location of filling stations is determined based on the minimum travel cost estimated by using a modified transportation problem as well as the construction and maintenance costs of the filling stations. The applicability of the model is analyzed through finding the optimal location of filling stations for the city of Anyang, a typical medium-sized city in metropolitan Seoul, based on the demand of natural gas buses. This study is expected to help promote the spread of natural gas buses by providing a starting point of a objective and reasonable methodological perspective to address the filling station location problem.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.129-138
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• 2006

After Seoul has introduced semi-public bus management system(public management-private operation), the Seoul Metro Government needs a scientific management tool for optimal scheduling for bus routes, to reduce unnecessary operations and provide demand responsive service. As a product of this effort, this paper proposes a heuristic model that could minimize total passenger waiting time under the constraints, such as number of vehicles, working conditions, max load point, minimax headway. etc. For verifying the validity of the proposed model, it is applied to an existing bus route. It results that headways in rush hours become decreased and the passenger waiting time could be decreased. In conclusion. it is thought that the Proposed model contributes to efficiency of bus operation.