• Journal of Digital Convergence
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• v.16 no.10
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• pp.213-222
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• 2018

This study was conducted to derive the traffic accident risk index through the recognition of the elderly driver's driving pattern to reduce the traffic accident rate of elderly drivers and to reflect them in the renewal and return policy of driver's license accordingly. First, the traffic accident risk index is defined by analyzing the behavioral characteristics of older drivers to derive the major factors that lead to traffic accidents. Second, we present a method to measure the traffic accident risk index from the driving pattern of the elderly through the smart-phone, the camera and the distance sensor attached to the car. Finally, we derive three thresholds by computer simulation and determine the accident risk from the measured traffic accident risk index as four steps and suggest ways to ensure safe driving of older drivers. It is required to objectively assess the driving ability of an aged driver in accordance with the proposed method, and to induce the driver to reset the driver's license renewal cycle and voluntarily return the driver's license to minimize social costs due to increased traffic accidents.

• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.39-47
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• 2018

This paper confirms the risk of using smartphone through the analysis of collected usage pattern and proposes the smartphone intervention system in risk situations. In order to check the risk of smartphone usage, we made information collecting application and collected smartphone usage pattern from 11 experiment participants for two months. By analyzing smartphone usage pattern, we confirmed that about 12% of smartphone usage is being used in driving, walking, and on the street. In addition, we analyzed the response rate of smartphone notification in risk situations and confirmed that user responds the smartphone notifications in real-time even in risk situations. Therefore, it is required to present a system that intervenes the use of smartphone in order to protect smartphone users in risk situations. In this paper, we classify risk situations of using smartphone. Also, the proposed smartphone intervention system is designed to periodically detect risk situations. In risk situations, smartphone function can be restricted according to user setting of smartphone. And smartphone can be used normally when safe situation is restored.

• Korean Journal of Health Education and Promotion
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• v.14 no.2
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• pp.69-94
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• 1997

Recently, occurrence of alcohol-involved traffic accidents is increasing while all the accidents by violation of law except drunk driving. Traffic accidents by drunk driving has a great external cost. In detecting drunk driving, blood alcohol content Many studies reported close correlation between blood alcohol content and traffic accidents by drunk driving. The risk of traffic accidnet increases exponentially as blood alcohol content increases. To control traffic accidents by drunk driving, decide target population. Heavy drinkers are few and responsible for a small part of the loss while casual drinkers are many and responsible for a large part of the loss. Casual drinkers need to be included in the targer population for the control of traffic accident by drunk driving. Stragegies to reduce the quantity of alcohol consumed, change the pattern of drink, such as frequency of drinking, raise of perceived risk of accident need to be sought.

• Journal of Korean Academy of Nursing
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• v.20 no.1
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• pp.79-87
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• 1990

Clinical and epedemiologic studies of coronary heart disease(CHD)have from time to time over the last three decades found associations between prevalence of CHD and behavioral attributes and cigarette smoking. The main purpose of this study is reduced to major risk factor of coronary heart disease through prohibition of smoking and control of behavior pattern. The subjects consisted of 120 smokers and 90 non-smokers who were married men older than 30 years working in officers. The officers were surveyed by means of questionnaire September 26 through October 6, 1989. The Instruments used for this study was a self-administered measurement tool composed of 59 items was made through modifications of Jenkuns Activity Survery(JAS). The Data were analysed by SAS(Statistical Analsis System) program personal computer. The statistical technique used for this study were Frequency, x$^2$-test, t-test, ANOVA, Pearson Correlation Coefficient. The 15 items were chosen with items above 0.3 of the factor loading in the factor analysis. In the first factor analysis 19 factors were extracted and accounted for 86% of the total variance. However when the number of factors were limited to 3 in order to derive Jenkins classification, three factors were derived. There names are Job-Involvement, Speed & Impatience, Hard-Driving. Each of them includes 21 items, 21 and 9, respectively. The results of this study were as follow : 1. The score of the smoker group and non-smoker group in Job-Involvement(t＝5.7147, p＜0.0001), Speed & Impatience(t＝4.6756, p＜.0001), Hard-Driving(t＝8.0822, p＜.0001) and total type A behavior pattern showed statistically significant differences(t＝8.1224, p＜.0001). 2. The score of type A behavior pattern by number of cigarettes smoked daily were not statistically significant differences. 3. The score of type A behavior pattern by duration of smoking were not significant differences. It was concluded that the relationship between smokers and non - smokers of type A behavior pattern was statistically significant difference but number of cigarettes smoked daily and duration of smoking were not significant differences. Therefore this study is needed to adequate nursing intervention of type A behavior pattern in order to elevated to educational effect for prohibition of cigarette smoking.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.111-122
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• 2013

PURPOSES : The purpose of this system (Rear Lighting System) is to provide illumination for the driver to operate the commercial vehicle safely after dark in highway, to increase the conspicuity of the vehicle, and especially be suggesting the finest observable improvement method, depending on color and pattern of rear lighting system of truck for midnight highway traffic. METHODS : Rear lightning system as an improving way for forward commercial vehicles lighting the securing sight from human factors and the surrounding environment in midnight driving. For this one, basic materials were collected from the data analysis about many types of problems, and filed investigation for establishing Driving Simulator. also taking statistic test to human volunteers after finding recognizable distance of them. RESULTS : As a result, color with the highest visuality is amber followed by green-red-blue as in order for all road types. Especially almost no difference is found between red and green, also when the light is turn off, recognizable distances is wide difference compared to turn on the light. One more thing about study per pattern, upper and entire lighting have similar recognizable distances, but under lighting shows short distance with difficulty securing sight from medians. And straight section shows similar recognizable distances. By finding visuality improvement method depending on color and pattern of supplement taillight, it is expected to suggest quantitative judgement standard for introducing regulation and improvement of supplement taillight. CONCLUSIONS : Night time vehicle conspicuity to the rear is provided by rear position lamps. this study is showed that the color of light ramp is not important to be safe driving, most important is to turn on the light, recognizable distances is big different compared to turn off the rear light, so when the drivng dark in highway, have to turn on the light for reducing risk.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.103-109
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• 2012

Digital speedometer which is supposed to provide the basic data for analyzing human factors of drivers has a limitation for human behavior studies of drivers, because it records limited driving information including GPS velocities. Besides, Black Box, which is currently being actively commercialized in the market, records mostly vehicles' risky patterns rather than drivers' behaviors. As a result, it also shows a limit to analyze dangerous driving patterns. This study performed a risky driving study for human factor analysis. This study conducted before and after comparisons for real time warning study using a risky driving judgment device. The analysis was conducted based on Longitudinal acceleration, Lateral acceleration, and Yaw rate of vehicles.

• Journal of Environmental Science International
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• v.22 no.2
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• pp.173-185
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• 2013

In order to clarify the impact of wildfire and its thermal forcing on atmospheric wind and temperature patterns, several numerical experiments were carried out using three dimensional atmospheric dynamic model WRF with wildfire parametrization module SFIRE. Since wind can accelerate fire spread speed, the moving speed of fireline is faster than its initial values, and the fireline tends to move the northeast, because of the wind direction and absolute vorticity conservation law associated with driving force induced by terrain. In comparison with non-fire case, the hydraulic jump that often occurs over downwind side of mountain became weak due to huge heat flux originated by surface wildfire and wind pattern over downwind side of mountain tends to vary asymmetrically with time passing. Therefore temporal variation of wind pattern should be catched to prevent the risk of widfire.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.1-6
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• 2020

In this study, we propose an association inference model based on data bias optimization for road hazard detection. This is a mining model based on association analysis to collect user's personal characteristics and surrounding environment data and provide traffic accident prevention services. This creates transaction data composed of various context variables. Based on the generated information, a meaningful correlation of variables in each transaction is derived through correlation pattern analysis. Considering the bias of classified categorical data, pruning is performed with optimized support and reliability values. Based on the extracted high-level association rules, a risk detection model for personal characteristics and driving road conditions is provided to users. This enables traffic services that overcome the data bias problem and prevent potential road accidents by considering the association between data. In the performance evaluation, the proposed method is excellently evaluated as 0.778 in accuracy and 0.743 in the Kappa coefficient.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.114-126
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• 2016

Domestic risk factors that are thought to be correlated with highly pathogenic avian influenza (HPAI) outbreak are migratory birds and moving objects such as poultry farm vehicles. In particular, the commercial vehicles that routinely circulate the local and/or remote poultry farms produce are thought to be major HPAI risk factors in South Korea. In this study, the driving histories of the vehicles belonging to poultry farms and/or commercial companies registered in the Korea Animal Integrated System (KAHIS) were analyzed using statistical and social networking tools in a Geographic Information System (GIS) in order to understand the pattern of the HPAI (H5N8) outbreak that occurred in 2014 in South Korea. Based on the 2014 HPAI outbreak patterns, HPAI-infected poultry farms were categorized according to geological features. The HPAI-infected poultry farms were categorized as 'regional-accumulation', 'regional-distribution', 'metropolitan-accumulation', 'metropolitan-distribution' and 'national-distribution' in endemic or non-endemic regions. We were able to categorize most HPAI-infected poultry farms into the five proposed categories, but further studies are required to categorize all such farms. Based on this categorization system, we propose efficient but economical prevention boundaries in South Korea. We strongly believe that our research could hugely impact government decisions to estimate the prevention area.