• Journal of Korean Physical Therapy Science
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• v.22 no.2
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• pp.43-47
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• 2015

Background : Many factors affect foot and ankle biomechanics during walking, including gait speed and anthropometric characteristics. This study examined the effect of walking speed on peak plantar pressure during the walking. Method : Thirty two normal healthy subjects (16 men, 16 women) were recruited. Peak plantar pressure was investigated using pressure distribution platforms (Pedoscan system) under the hallux heads of the first, second, and third metatarsal bones, and heel. Result : The results also suggest that slow walking speeds may decrease forefoot peak plantar pressure in patients with peripheral neuropathy who have a high risk of skin breakdown under the forefoot(p<0.05). Conclusion : The results also suggest that slow walking speeds may decrease forefoot peak plantar pressure in patients with restricted low extremity range of motion who have a high risk of skin breakdown under the forefoot.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.102-114
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• 2018

The Railway Safety Management System is based on risk management and the basic purpose of risk management is safety management activities to prevent railway accidents and operational obstacles in advance. In order to manage risk, an acceptable risk standard must be established. This risk criterion is used to evaluate the railway risk with both frequency and severity. In the case of overseas railway or other industrial sectors, various factors are reflected in the main variables that constitute the occurrence frequency, but this is no the case in the domestic railway sector. In particular, the current risk assessment criteria in the railway sector remain at a level that exploits the incidents that have occurred in the past and the severity of the property damage and it dose not properly reflect complex and diverse environmental and situational changes in railway operations. Therefore, in this study, it is possible to calculate the potential occurrence of future events instead of occurrence frequency as a component of the risk assessment criteria, focusing on the High-Speed Railway. In addition to the property damage to the consequence, we suggest a rational methodology, development direction, and theoretical implications for constructing accurate and reasonable risk criteria including actual damage such as human injury and time loss.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.91-106
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• 2024

Around the world, many countries experiencing the issue of shrinking cities are continually expanding high-speed rail networks to enhance regional accessibility and address imbalances. This study analyzed the effects of high-speed train operations on the age-specific population migration in South Korean municipalities from 2012 to 2019, taking into account the risk levels of shrinking cities. For this purpose, an analysis was conducted using age-specific net in-migration population as the dependent variable, employing the spatial panel autoregressive model. The research results indicated that the influence of high-speed rail on regional population inflow varies depending on the risk level of shrinking city. In other words, high-speed railway operations had positive effects on population inflow in the capital areas and some major cities, while explained population outflow in the other regions. High-speed railways particularly exerted a significant impact on the inflow of the young and middle-aged population, representing the working age, but this effect was also limited to regions with a low risk of shrinkage. The findings of this study emphasize the importance of considering planned population and industrial attraction when installing high-speed rail with the goal of achieving regional balanced development and mitigating shrinkage. The results of this study also suggest the need for subsequent research to explore factors that positively influence population structure and inflow based on the level of shrinkage risk in each region, as well as the introduction of new policies tailored to the specific situations of each local government.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.130-139
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• 2017

The crop damage caused by strong wind was predicted using the wind speed data available from Korean Meteorological Administration (KMA). Wind speed data measured at 19 automatic weather stations in 2012 were compared with wind data available from the KMA's digital forecast. Linear regression equations were derived using the maximum value of wind speed measurements for the three-hour period prior to a given hour and the digital forecasts at the three-hour interval. Estimates of daily maximum wind speed were obtained from the regression equation finding the greatest value among the maximum wind speed at the three-hour interval. The estimation error for the daily maximum wind speed was expressed using normal distribution and Weibull distribution probability density function. The daily maximum wind speed was compared with the critical wind speed that could cause crop damage to determine the level of stages for wind damage, e.g., "watch" or "warning." Spatial interpolation of the regression coefficient for the maximum wind speed, the standard deviation of the estimation error at the automated weather stations, the parameters of Weibull distribution was performed. These interpolated values at the four synoptic weather stations including Suncheon, Namwon, Imsil, and Jangsu were used to estimate the daily maximum wind speed in 2012. The wind damage risk was determined using the critical wind speed of 10m/s under the assumption that the fruit of a pear variety Mansamgil would begin to drop at 10 m/s. The results indicated that the Weibull distribution was more effective than the normal distribution for the estimation error probability distribution for assessing wind damage risk.

• Journal of Navigation and Port Research
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• v.39 no.3
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• pp.199-207
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• 2015

In ports of Korea, the marine traffic flow is congested due to a large number of vessels coming in and going out. In order to improve the safety and efficiency of these vessels, South Korea is operating with a Vessel Traffic Service System, which is monitoring its waters for 24 hours. However despite these efforts of the VTS (Vessel Traffic Service) officers, collisions are occurring continuously, the risk situation is analyzed that occurs once in about 20 minutes, the risk may be greater. It investigated to reduce these accidents by providing a safety standard for collision danger in a timely manner. Thus, this study has developed a risk prediction module to predict risk in advance. This module can avoid collision risk to adjust the speed and course of ship using a risk evaluation model based on ship operator's risk perspective. Using this module, the ship operators and VTS officers can easily be identified risks in complex traffic situations, so they can take an appropriate action against danger in near future including course and speed change. To verify the effectiveness of this module, this paper predicted the risk of each encounter situation and confirmed to be capable of identifying a risk changes in specific course and speed changes at Busan coastal water.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.139-147
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• 2015

This study deals with actual commuting distance and influence of risk factors depending on commuting distance and mode in order to reestablish actual commuting zone of primary school students. Data mining analysis(CHAID) was applied for this reestablishment using survey results from 6,927 primary school students in Seoul Metro. Six risk factors; convenience level of commuting path condition, convenience level of road crossing condition, vehicle speed on commuting path, segregation level between commuter and vehicle, congestion level of commuting path, and public security level and two mode; walking and cycle are considered in the analysis. As the results of CHAID analysis, commuting distance was divided into four zones; Internal Zone(0.491km under), External Zone(0.492 ~ 1.492km, 1.493 ~ 2.699km), Commutable Zone(2.70km over), and awareness level on safety is declined as commuting distance is increased. The risk factor affecting on safety is recognized differently by students depending on commuting distance and mode. For students commuting by walking, vehicle speed on commuting path and convenience level of commuting path condition are recognized as the prime risk factor within Internal Zone and Commutable Zone, respectively. For students commuting by cycle, convenience level of road crossing condition and vehicle speed on commuting path are recognized as the prime risk factor within Commutable Zone. Analysis results show that improved plan and program for commuting path for primary school students are required considering actual commuting distance and method.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.58-63
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• 2013

It is very difficult to evaluate the impact speed, who caused the accident and what the injury risk of the vehicle occupants was from the outcome of the accident. That's the main reason why there are so many insurance fraud related to vehicle accident. In this study, a vehicle crash accident suspected to an insurance fraud had been reconstructed to evaluate crash speed and the relationship between the crash accident and passenger injury risk. To do this, the scene was reconstructed based on accident investigation report and three vehicle crash tests were done at 27kph, 37kph and 70kph. The crash speed of 27kph and 37kph were chosen based on the damaged vehicle and 70kph was chosen based on the driver's statement. Based on the damage of vehicle and dummy injury measure, impact speed is estimated around 20 to 30kph and the dummy measures show that the passengers are not seems to be severely injured in this speed range.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.16 no.2
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• pp.137-149
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• 2012

We propose an efficient method to measure the insurance risk of causality insurance companies by using the CreditRisk+ methodology. This method is superior to previous methods in several aspects. Its computation speed is very fast and the input data form is simple. It is able to aggregate both credit risk and insurance risk, so the insurance company can manage the risk in combined manner. In this paper, we propose a mathematical method to obtain the aggregate loss distribution of portfolios having correlation among products or business lines as a general case, and then suggest its implementation algorithm. Finally we apply this method to the real data from Korea Insurance Development Institute (KIDI) and discuss its availability to real applications.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.960-967
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• 2009

Power supply system of electric railway has a diversity of safety problems since it should supply high electric power to the trains moving high speed with a lot of passengers on board. This paper provides a risk assessment approach to safety management of the electric railway facilities. Construction of database from field accident information, risk assessment and management of the risk are carried out systematically to ensure the safety. The risk assessment includes hazard identification, cause analysis by FTA(Fault Tree Analysis), consequence analysis by EVA(Event Tree Analysis), and loss analysis. In terms of the severity and the probability of the accidents deduced by these analyses, the risk of the accidents is assessed by using a risk matrix designed for electric railway facilities. Based on the risk assessment, possible risk mitigation options are identified and evaluated by analyzing their impact on the risk reduction and their cost benefit ratio. The long-term safety of the electric railway facilities can be ensured by renewal of the risk assessment and the risk mitigation option analysis with continuous accident database update. The proposed approach is applied to the electric railway facilities of Korean railway based on the accident data from 2002 to 2008.