• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.106-116
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• 2024

Purpose: This paper conducts IoT and CCTV-based safety monitoring to analyze accidents and potential risks occurring at construction sites, and detect and analyze risks such as falls and collisions or abnormalities and to establish a system for early warning using devices like a walkie-talkie and chatbot service. Method: A safety management service model is presented through smart construction technology case studies at the construction site and review a relevant literature analysis. Result: According to 'Construction Accident Statistics,' in 2021, there were 26,888 casualties in the construction industry, accounting for 26.3% of all reported accidents. Fatalities in construction-related accidents amounted to 417 individuals, representing 50.5% of all industrial accident-related deaths. This study suggests implementing AI chatbot services for construction site safety management utilizing IoT-based health monitoring technologies in smart construction practices. Construction sites where stakeholders such as workers participate were demonstrated by implementing an artificial intelligence chatbot system by selecting major risk areas within the workplace, such as scaffolding processes, openings, and access to hazardous machinery. Conclusion: The possibility of commercialization was confirmed by receiving more than 90 points in the satisfaction survey of participating workers regarding the empirical results of the artificial intelligence chatbot service at construction sites.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.20 no.3
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• pp.168-174
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• 2010

South Korea's industrial injuries are decreasing overall in the last 32 years. Nevertheless, the fatal occupational injury rate is still higher than in developed countries. This study was conducted to help prevention strategies of occupational injuries for the Republic of Korea. Fatal occupational injury rates were obtained from "Industrial Accident Analysis"of the Korean Ministry of Labor. Poisson regression was used to assess time trends. Socioeconomic indicators were obtained from the Korea Labor Institute and the Statistics Korea. Fatal occupational injury rates were adjusted by year, and Pearson correlation analysis was used to assess the relationship between the socio-economic indicators and occupational injuries. In 1975, fatal occupational injury rate was 54.8 per 100,000 workers. With somewhat up and down, it was decreased to 21.0 in 2006. An annual rate of change for the years 1975-2006 was - 1.83%, and for the years 2002-2006 was -5.02%. As economic growth rate, paricipation rate for the age less than 25 and hours of work per week or year increased, fatal occupational injury rate also increased. Conversely, as GDP per capita, paricipation rate or employment rate for female, paricipation rate for the age 25 or more, hourly compensation costs for production workers and services output as percent of GDP increased, fatal occupational injury rate decreased. By the development of safety techniques and the adoption of more legislative constraints, developed economy reduce occupational injuries. Conversely, economic growth may raise occupational injuries. Therefore, prevention strategies are needed to manage both of them. We need to make an effort to prevent occupational injuries due to not only sexual differences, but also job differences between male and female. Preventive strategies are needed to consider the characteristics of younger workers. Addition to wage, other appropriate variables for work condition should be considered together. Extending work hours is need to be regulated with systemic methods.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.245-250
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• 2017

Flash floods is defined as the flooding of intense rainfall over a relatively small area that flows through river and valley rapidly in short time with no advance warning. So that it can cause damage property and casuality. This study is to establish the flash-flood warning system using 38 accident data, reported from the National Disaster Information Center and Land Surface Model(TOPLATS) between 2009 and 2012. Three variables were used in the Land Surface Model: precipitation, soil moisture, and surface runoff. The three variables of 6 hours preceding flash flood were reduced to 3 factors through factor analysis. Decision tree, random forest, Naive Bayes, Support Vector Machine, and logistic regression model are considered as big data methods. The prediction performance was evaluated by comparison of Accuracy, Kappa, TP Rate, FP Rate and F-Measure. The best method was suggested based on reproducibility evaluation at the each points of flash flood occurrence and predicted count versus actual count using 4 years data.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.249-259
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• 2014

This study has analyzed the factors that influence the safety consciousness of school bus drivers at Child Care Centers. To achieve this, 276 directors and drivers of owner-operator who drives the school bus at Child Care Centers in Chungnam, Chungbuk and Daejeon area were selected as study subjects. For the data analysis, PASW Statistics 18.0 was used. The main results of this study are as follows. The level of safety consciousness of directors and drivers of owner-operator were 6.46 and 6.82 respectively showing that drivers of owner-operator were significantly higher. Second, the factors that influence the safety consciousness were shown to be significantly different for each group. The factors that influence the safety consciousness of directors were shown in the order of whether or not the accident was experienced, safety-seeking motivation, sensation-seeking disposition, safety consciousness of caregivers, perception-motor skill. The factors that influence the safety consciousness of drivers of owner-operator were shown in the order of safety-seeking motivation, health status, daily driving hours, economic status, safety consciousness of caregivers. Based on these results, several ways were suggested to improve the safety consciousness of school bus drivers at Child Care Centers and prevent the traffic accidents.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.223-232
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• 2015

This study has analyzed the factors that influence the safety consciousness of elderly drivers. To achieve this, 307 elderly who drives commercial and non-commercial in Daejeon, Sejong, Chungnam and Chungbuk area were selected as study subjects. For the data analysis, PASW Statistics 18.0 was used. The main results of this study are as follows. The level of safety consciousness of commercial and non-commercial drivers were 6.49 and 6.93 respectively showing that drivers of non-commercial were significantly higher. Second, the factors that influence the safety consciousness were shown to be significantly different for each group. The factors that influence the safety consciousness of commercial drivers were shown in the order of safety-seeking motivation, economic status, daily driving hours, sensation-seeking disposition. The factors that influence the safety consciousness of non-commercial drivers were shown in the order of safety-seeking motivation, health status, whether or not the accident was experienced, sensation-seeking disposition. Based on these results, several ways were suggested to improve the safety consciousness of elderly drivers and prevent the traffic accidents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Journal of Korean Medicine Rehabilitation
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• v.25 no.2
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• pp.135-153
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• 2015

Objectives The purpose of this study was to investigate the characteristics of inpatients who were admitted to Korean medicine hospital due to low back pain. Methods The current study was designed as a retrospective chart review to investigate descriptive characteristics of LBP patients. The clinical records of 601 patients who were hospitalized for treatment of LBP in Cheonan Korean Medicine Hospital, Daejeon University from 1st, January, 2013 to 31th, December, 2013 were analyzed. Results 1. Most frequently given diagnosis was sprain and strain of lumbar (45.93%). 2. Female outnumbered male patients in all disease groups except fracture of lumbar spine. 3. In distribution according to age, sprain and strain of lumbar, HNP of L-spine and lumbago with sciatica were most frequent at 30s, fracture of lumbar spine was most frequent at 50s and spinal stenosis was most frequent at 70s. 4. The most frequently motive for low back pain was traffic accident (35.4%) 5. Patients with no related medical history were 76.95% 6. 0~1week interval between onset and visit to Korean Medicine Hospital was most frequent in all disease groups. 7. 50.85% of patients went through treatment at medical institutions before the admitting to Korean Medicine Hospital. 8. The average admission days of female was higher than male's. And age goes up, average duration of admission was longer. 9. In most (74.59%) of the patients, symptoms were more than improved. 10. Most frequently prescribed examination was X-ray (65.13%). 11. Most frequently prescribed herb medicine was whal-lak-tang (Huoluo-tang). Conclusions In most (74.59%) of the patients, symptoms were more than improved, especially in sprain and strain of lumbar and lumbago with sciatica. But Patients with a local hospital statistic is not be representative of the incidence of the population. In order to obtain more accurate statistics, it is necessary to compare analysis collect statistics from other medical hospitals.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.3
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• pp.15-28
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• 2008

According to the accident statistics published by the National Police Agency in 2006, it can be recognized that drivers' characteristics and driving behaviors are the most causational factors on the traffic accidents. At present, although many recording tools such as digital speedometer or black box are distributed in the market to meet social requests of decreasing traffic accidents and increasing safe driving behaviors, it is also true that it still lacks in obvious categories for dangerous driving types and then, the efficiency of the categories to be studied has been low. In this study, dangerous driving types are redefined. They are grouped into 7 classifications in the first level, and the seven classifications are regrouped into 16 in more detail. To verify the redefined dangerous driving types, a Data-logger is developed to receive and analyze the data that occur from the driving behaviors of the test vehicle. The developed Data-logger can be used to construct a real time warning system and safe driving management system with dangerous driving patterns based on acceleration, deceleration, Yaw rate, image data, etc.

• Journal of the Korean Society of Safety
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• v.27 no.4
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• pp.101-107
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• 2012

The statistics of industrial accident reported by ministry of Employment and Labor denoted a significant increase of musculoskeletal disorders(MSDs) after 1993, and showed the higher incident rate by 71.3% over the overall worker's disorders. Also, it was expected that Korean society will become the post-aged society in 2026 with 20.8% of elderly who is over 65 years old. The reports suggest possible problems caused by the older worker known to have reduced working ability than the young counterparts. On this basis, the goal of this study was to investigate the relationship between MSDs symptoms and work ability in the shipbuilding industry. To achieve this goal, this study distributed a questionnaire for total 1,244 shipbuilding employers, and used 910 employers' reports which revealed validity for this study. The questionnaire included the MSDs symptoms report developed by the Korean Occupational Safety and Health Association(KOSHA) and the work ability index(WAI) developed by Finnish Institute of Occupational Health(FIOH). Results showed no relationship between MSDs symptoms and age, years of work and exercise. Also, the work ability was increased until 44 years old, but it was decreased after that time because of the reduced physical capacity. Meanwhile, the years of work and exercise have positive correlation with work ability. However, the results revealed significant relationships between WAI and age, years of work, task characteristics and exercise. All together, the MSDs symptoms have a close relationship with the work ability in that the work ability of workers with the MSDs symptoms was reduced. This study may suggest the needs of more efforts and attention on the MSDs prevention to increase the work ability.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.198-206
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• 2014

According to the statistics of the National Police Agency, red light running (RLR) crashes represent a significant safety issue throughout Korea. This study deals with the RLR crashes occurred at signalized intersections in Cheongju. The objectives of this study are to comparatively analyze the characteristics of between RLR crashes and the Non-RLR crashes, and to find out factors using a Binary Logistic Regression(BLR) model. In pursuing the above, the study gives particular attentions to testing the differences between the above two groups with the data of 2,246 RLR/ 3,884 Non-RLR crashes (2007-2011). The main results are as follows. First, many RLR crashes were occurred in the nighttime and in going straight. Second, the difference between RLR and Non-RLR crashes were clearly defined by crash type, maneuver of vehicle before crash, age of driver (30s, 50s), alcohol use and accident pattern. Finally, a statistically significant model (Hosmer and Lemeshow test : 7.052, p-value : 0.531) was developed through the BLR model.