Nearly a half of the accidents the old people had take place in home. Home safety will be more important than ever in rapidly increasing old aged in Korea. The purpose of this paper is to search the general characteristics of domestic accidents related to living environment of the old people experienced. The number of 248 respondents who had experienced of housing related accidents since recent 10 years were selected from 500 interviews with 65 years old and over during April 4th-26th, 2008. About a half of respondents had experienced home accidents. The entrance is the most common places the home accidents occurred, followed by bathrooms and stairs. flooring materials and raised floors are the most dangerous spots. Both places and dangerous objects are related each other. The place is also related to the type of dwelling. Slipping and tripping over most frequently happen in home accidents. It is related to the place like slipping in a bathroom or stairs, and tripping over in entrances. Mostly, legs and arms are injured by the home accidents. A safe home facilitates the old to live healthy and independent in their own places. A safe home for the old is a kind of new issues in Korea. Related policies and researches are about to sprout.
According to traffic accidents statistics, the number of fatalities, injuries and the rate of increase of traffic accidents have been decreasing over last 5-years. The fatality rate is 1.9 for total accidents but the fatality rate for single vehicle accidents shows a 7.9, which is 4 times greater than the average for all accidents. Single vehicle accidents, usually occur as a vehicle impacts a fixed objects on the roadside as the vehicle runs-off from the road. However, few researches have been conducted considering the accident severity of single vehicle accidents which impact to the fixed objects on the road. The single vehicle accident is directly related to the composition of road cross section, (since it is the required the minimum width of a road for all run-off-the-road vehicles to recover or come to a safe stop). Therefore, this study analyzes the influence of road cross section on traffic accidents to find out the severity of single vehicle accident. To analyze the road elements which are related to the accident severity, the Ordered Probit Model was used. As variables, the element of road cross section such as the radius(m), vertical curve(%), cross sectional grade(%), road width(m). number of climbing lane, median, and curb, were used (as was the 3-years of accidents data). This study found out that cross slope(%), road width(m), and the number of climbing lane are related to the severity of accident. The result of this study could be expected to improve the road safety and to be used as the base data for further road safety research.
Proceedings of the Korean Institute of Building Construction Conference
/
2020.11a
/
pp.55-56
/
2020
The construction industry has the highest occupational fatality and injury rates related to accidents of any industry. Accordingly, safety managers closely monitor to prevent accidents in real-time by installing surveillance cameras at construction sites. However, due to human cognitive ability limitations, it is impossible to monitor many videos simultaneously, and the fatigue of the person monitoring surveillance cameras is also very high. Thus, to help safety managers monitor work and reduce the occupational accident rate, a study on object recognition in construction sites was conducted through surveillance cameras. In this study, we applied to the instance segmentation to identify the classification and location of objects and extract the size and shape of objects in construction sites. This research considers ways in which deep learning-based computer vision technology can be applied to safety management on a construction site.
The 7,993 cases of Survey Report of Fatal Industrial Accidents conducted jointly by the MEOL and the KOSHA for the recent seven years(2007-2013) were categorized according to personal and occupational characteristics, industry types, business sizes, job types, activities at the time accident, types of accidents, material agents(assailing materials), unsafe conditions, and unsafe acts. And it is found that among the 72.2 percent of fatal occupational accidents in the construction and manufacturing industries are caused by falling, sticking, bumping and being caught under objects & overturning. For this study, through the empirical analysis on causes of fatal industrial accidents, was used to identity high risk groups based on total data of 7,993 victims of occupational accidents. An annual fatal occupational injury (FOI) rate per 10,000 workers was about 0.47‱. The middle-aged group and the elderly group showed the highest FOI rates per 10,000 workers (0.73‱, 0.80‱), and the daily workers showed the highest FOI rate (1.46‱), and the craft and related trades workers showed the highest FOI rate (2.17‱). In case of industry type the mining industry (7.26‱) showed the highest FOI rate, followed by the sewerage, waste management, materials recovery and remediation activity industry (3.91‱) and the construction industry (2.71‱). The primary high risk target group that requires a strategy designed to reduce fatal occupation injuries caused by falling and bumping & contact(collision) is the construction industry, and the secondary high risk target group in the construction industry is classified as the equipment, machine operating and assembling workers in the construction industry, those aged 50 years old and above need the prevention measures against bumping & contact(collision) and being caught under an object & falling(objects), while those aged less than 50 years old need prevention measures against falling(persons).
Journal of the Korean Society of Marine Environment & Safety
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v.27
no.7
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pp.1004-1010
/
2021
Ship-floating object accidents can lead not only to a delay in ship's operations, but also to large scale casualties. Hence, preventive measures are required to avoid them. This study analyzed the spatiotemporal aspects of such collisions based on the data on ship-floating object accidents in sea areas in the last five years, including the collisions in South Korea's territorial seas and exclusive economic zones. We also provide basic data for related research fields. To understand the distribution of the relative density of accidents involving floating objects, the sea area under analysis was visualized as a grid and a two-dimensional histogram was generated. A multinomial logistic regression model was used to analyze the effect of variables such as time of day and season on the collisions. The spatial analysis revealed that the collision density was highest for the areas extending from Geoje Island to Tongyeong, including Jinhae Bay, and that it was high near Jeongok Port in the West Sea and the northern part of Jeju Island. The temporal analysis revealed that the collisions occurred most frequently during the day (71.4%) and in autumn. Furthermore, the likelihood of collision with floating objects was much higher for professional fishing vessels, leisure vessels, and recreational fishing vessels than for cargo vessels during the day and in autumn. The results of this analysis can be used as primary data for the arrangement of Coast Guard vessels, rigid enforcement of regulations, removal of floating objects, and preparation of countermeasures involving preliminary removal of floating objects to prevent accidents by time and season.
Kim, Insoo;Lee, Kyung-Suk;Kim, Hyo-Cher;Chae, Hye-Seon;Kim, Kyungsu;Choi, Dong-Phil
Journal of Environmental Health Sciences
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v.43
no.1
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pp.42-54
/
2017
Objectives: The present study was conducted to investigate farm work environments among farmers and examine the level of management of safety and health, and to subsequently produce study result to serve as foundational data for the development of guidelines on safety and health as part of the improvement of farming work environments among farmers raising Korean native cattle. Methods: The present study conducted a survey on farm work environments and the management of safety and health with 407 farmers engaged in Korean native cattle farming in selected regions in eight provinces. It also visited 10 farmers to verify the current status of farm work. Results: The survey results showed that 16.4% of the respondents experienced safety-related accidents due to farm work. The locations of the accidents were inside the cattle shed (71.4%) and facilities outside the cattle shed (19.6%). The types of accident showed collision with animals (35.7%), collision or contact with obstacles (27.1%), and musculoskeletal accidents due to heavy object handling (12.9%). The causes of the accidents were cattle (38.3%), cultivators and tractors (25.4%), facility tools in cattle sheds (9.0%), and slippery floors (6.0%). The damaged areas were hand (21.0%), spine (19.8%), lower limb (18.5%), and foot (17.3%). A self-diagnostic survey on respiratory diseases showed that 11.5% of the respondents experienced respiratory-related symptoms. The survey on safety and health during farm work showed that wearing personal protective equipment and response to emergency situations, which were needed to prevent safety-related accidents, were relatively low compared to the level of recognition of the need and awareness of safety issues. Furthermore, the field survey identified the current status of safety and health issues such as prevention management of collision accidents with cattle, how to handle heavy objects, and wearing of personal protective equipment. Conclusions: The present study identified safety-related accidents and problems in the management of safety and health among Korean native cattle farmers. In order to address the problem, it is necessary to not only provide guidelines on safety and health management which are appropriate to the characteristics of Korean native cattle farming work, but also to study the development of personal protective equipment.
Of 2,740 industries in Jeonbug area which are covered by industrial insurance policy, 462 facilities which the accidents related to industry occured during the year of 1979 were studied. and the results are summarized as follows: 1. The accidents related to industry occured in 462 industries of the total 2,740 industrial facilities in Jeonbug area as of 1979. 2. The incidence rate of accident per 1,000 workers was 34.3 (49.2 in male workers and 12.8 in female workers), the frequency rate of the total industries in jeonbug area was 13.36, and severity rate was 1.3. 3. The frequency rates and severity rates by type of industry in study area were quite different to compare with those of national rates. 4. The incidence rate of construction industry was 223.6 per 1,000 workers, and that of transportation-communication industries were 78.6. 5. The proportion of industrial accidents of $20{\sim}24$ age group was 22.1 per cent of the total accidents, and the proportions decreased according to age increase. 6. The incidence rate in the industry having less than 49 workers was 20.6 per 1,000 workers, that of industry with $50{\sim]99$ workers was 26.7, that of industry with $100{\sim}199$ was 51.9, that of industry with $200{\sim}499$ was 80.2 and that of with more than 500 worker was 40.7. 7. The accidents which occured in the workers with experience of less than one year was 69.4 per cent of the total accidents, otherwise, the longer the workers have worked the less accident they have. 8. The most accidents occured in tile shift between 10 to 12 o'clock, and 16 to 18 hour 9. The primary causes of the industrial accidents were found to be collisions, machinery falling objects and falls. 10. The site of injury by type of industry were quite different, and the major site of injury was finger. 11. The laceration and open injuries of the accidents related to industry were 37.2 per cent of the total cases, and fractures or dislocations were 23.5 per cent, and contusions were 6.5 per cent. 12. Death rate of industrial accident was 5.0 per 10,000 workers, and those of industry were 47.6 in transportation, 42.8 in construction industry, 24.4 in mine industry, and 2.0 in manufacturing industry.
International conference on construction engineering and project management
/
2022.06a
/
pp.744-751
/
2022
Construction is among the most dangerous industries with numerous accidents occurring at job sites. Following an accident, an investigation report is issued, containing all of the specifics. Analyzing the text information in construction accident reports can help enhance our understanding of historical data and be utilized for accident prevention. However, the conventional method requires a significant amount of time and effort to read and identify crucial information. The previous studies primarily focused on analyzing related objects and causes of accidents rather than the construction activities. This study aims to extract construction activities taken by workers associated with accidents by presenting an automated framework that adopts a deep learning-based approach and natural language processing (NLP) techniques to automatically classify sentences obtained from previous construction accident reports into predefined categories, namely TRADE (i.e., a construction activity before an accident), EVENT (i.e., an accident), and CONSEQUENCE (i.e., the outcome of an accident). The classification model was developed using Convolutional Neural Network (CNN) showed a robust accuracy of 88.7%, indicating that the proposed model is capable of investigating the occurrence of accidents with minimal manual involvement and sophisticated engineering. Also, this study is expected to support safety assessments and build risk management systems.
Proceedings of the Korean Institute of Building Construction Conference
/
2019.11a
/
pp.40-41
/
2019
The purpose of this study is to analyze the vocabulary related to safety accidents based on the reports recorded on the violation of safety rules at the construction sites. We used Word2Vec and Topic Model as natural language processing techniques to analyze the safety accidents presented in the reports of the large enterprise. The words that appeared based on the occupational accident types such as the fall, falling objects, and others were derived and visualized. We derive the frequency and similarity of the words and topics of the accident that occur at the construction site. In future studies, we will be able to proceed with the generation of texts from pictures based on images and this reports.
Ahn, Ki Ok;Kim, Jae Eun;Jang, Hye Young;Jung, Koo Young
Journal of Trauma and Injury
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v.19
no.1
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pp.1-7
/
2006
Purpose: Injury is a leading cause of morbidity and mortality for children. As an injury prevention measure, the differences in external causes of severe pediatric injuries based on ICECI were analyzed according to age groups. Methods: A retrospective study was performed for pediatric patients under 15 years of age, who had been admitted to the emergency department with severe injuries from January 1998 to December 2004. The external causes of injury were investigated according to the ICECI: intent, mechanisms, places of occurrence, objects/substances producing injury, and related activities. The patients were divided into four groups based on age: infant (<0 year), toddler (1~4 years), preschool age (5~8 years), and school age (9~15 years). Results: The injury mechanisms, the places of occurrence and the related objects/substances vary with the age groups. The most common subtype of traffic accidents was pedestrian injury in pre-school age group. Falls most frequently occurred in the toddler group. But falls from a height of less than l meter height (6 patients) occurred only in the infant group. The most common place of occurrence in the infant group was the home, and that of other groups was the road. The related objects/substances for falls, for example, household furnitures and playground equipment depended on the age group. Conclusion: The age-group specific characteristics of severe pediatric injury were analyzed successfully through the ICECI. Therefore, when establishing a plan for the prevention of pediatric injury, consideration must be given to the differences in the external causes of injuries according to age group.
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