• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.127-128
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• 2022

The construction industry has a higher disaster rate than other industries, so safety education and management are highly important. In order to reduce the construction accident rate, it is necessary to study the key safety management factors reflecting the characteristics of the construction industry, where there are differences in processes and manpower input for each process, and a small number of managers. Therefore, in this study, key safety management factors for each Process of construction were derived through cross-analysis between safety accident types and accident occurrence objects through disaster case data. The extracted key safety management factors are expected to provide useful information for safety education and supervision of construction sites.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.95-103
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• 2019

Safety and welfare of forestry is very poor because of poor working environment, decreasing workforce and budget, and aging. These have brought many accidents and casualties. The accident rate in the field of forestry were about 2.83 times higher than average of an entire industry and mortality rate were 1.84 times higher than it. The most reason among the mortality accident was caught in, under or between objects and struck by objects. In analysis of 60 serious accident cases, the number of occurrence s of caught in, under or between objects and struck by objects were the highest. We suggest education, engineering, environment, and enforcement methods which is first aid education and emergency response system, equipment of combined IoT technologies and sensors, and certification and career program on the basis of the results.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.53-63
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• 2011

The repetitive occurrence of similar accident is one of the biggest feature in construction disasters. Similar accident cases provide direct information for finding risk of scheduled activities and planning safety countermeasure. Many systems are developed to retrieve and use past accident cases by researchers. However, these researches have some limitations for performing too much retrieval to obtain results considering construction site conditions or not reflecting characteristics of safety planning steps or both. To overcome these limitations, this study proposes accident case retrieval system that can search similar accident cases. It also helps safety planning using information retrieval and building information modeling. The retrieval system extracts BIM objects and composes a query set combining BIM objects with site information DB. With past accident cases DB compares a query set, it seeks the most similar case. And results are provided to safety managers. Based on results of this study, safety managers can reduce excessive query generation. Furthermore, they can be easy to recognize risk of a construction site by obtaining coordinations of objects where similar accidents occurred.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.143-149
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• 2017

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.

• Journal of the Korean Society of Safety
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• v.24 no.1
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• pp.69-77
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• 2009

This paper reports the aging driver traffic accident severity modeling results. For the modeling, Poisson regression approach is applied using the data set obtained from the Korea Transportation Safety Authority's simulator-based driver aptitude test results. The test items include the estimations of moving objects' speed and stopping distance, drivers' multi-task capability, and kinetic depth perception and so on. The resulting model with the response variable of equivalent property damage only(EPDO) indicated that EPDO is significantly influenced by moving objects' speed estimation and drivers' multi-task capabilities. More interestingly, a comparison with the younger driver model revealed that the degradation of such capabilities may result in severer crashes for older drivers as suggested by the higher estimated parameters for the older driver model.

• Journal of the Ergonomics Society of Korea
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• v.28 no.4
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• pp.101-107
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• 2009

In this study 1,079 occupational accident reports were used to examine the characteristics and causes of occupational injuries in the small-sized textile companies with less than 50 employees. These data were analyzed in terms of age of injured person, work experience, accident type, injury type, and agency of accident. The results show that there are some patterns: (1) injuries occur more frequently in the 40~49yr age group; (2) about half of all accident occurred during the first year of employment; (3) there is a higher percentage of sick people leaving in the 29~90day range; (4) 'caught in and between objects' represents the leading accident type; (5) the most common type of incidence is related to the machinery; (6) 'lower back injuries' is the leading type of occupational disorder. These results can be used to develop more effective accidental occupational injury prevention programs for small-sized textile industries.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.744-751
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• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.133-140
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• 2006

This paper suggests to reclassify railroad accident types and to standardize them as the standardized code for the railroad safety management system. The existing railroad accident types in both domestic and foreign cases have been carefully analyzed in the beginning. Based on the case studies, the new railroad accident types are classified into 9 classes which are not overlapped one another and 9 classes have been subdivided into 40 different accident patterns. All these patterns are linked with 9 different accident objects and 6 accident locations. Therefore, this study suggested the combination of 4 distinct code factors: accident class, accident pattern, accident object, and accident location to standardize them. In addition, inter-operation between the proposed codes and the existing accident types is suggested. This code will play a major role in the railroad safety management system composed of accident prevention, accident preparedness, accident response, and accident recovery.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.36-45
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• 2009

Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

• Journal of the Korean Institute of Gas
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• v.16 no.5
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• pp.21-27
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• 2012

The loss of life and property due to accidents in the research facilities or the laboratories of the university occurs steadily and the necessity of laboratory accident prevention is proposed. Above all, the main work to laboratory accident prevention is a systematic analysis of laboratories accidents. Analyzing reports or researches on industrial accidents in Korea had been carried out but these researches or reports did not based on laboratory accidents analysis. To the establishment of the accident prevention countermeasure in laboratory, a questionnaire sheet has been developed in this study. The questionnaires to survey the accident cases were gathered by electronic mail and visit survey from the laboratories and universities. The data of accident cases from the questionnaires was analyzed and discussed on accident distribution by season, the type of accident classification, the type of occurrence, the objects that caused the accident and laboratory accident by the damage incurred etc.. These results of this study can be used as basic data to the safety security and laboratory accident prevention of the laboratory worker.