• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1365-1371
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• 2008

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in gneiss area, a prediction technique was developed by the use of a decision tree model. The slope hazards data of Seoul and Kyonggi Province were 104 sections in gneiss area. The number of data applied in developing prediction model was 61 sections except a vacant value. The statistical analyses using the decision tree model were applied to the entrophy index. As the results of analyses, a slope angle, a degree of saturation and an elevation were selected as the classification standard. The prediction model of decision tree using entrophy index is most likely accurate. The classification standard of the selected prediction model is composed of the slope angle, the degree of saturation and the elevation from the first choice stage. The classification standard values of the slope angle, the degree of saturation and elevation are $17.9^{\circ}$, 52.1% and 320m, respectively.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.599-604
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• 2005

As a public transportation possible to convey a large quantity, the railway is safe and keeps time, but it has hazards to cause a disaster if the accidents such as collision, derailment, and fire occur. So advanced countries carry out System Safety Plan with various program activities which have connected orders to maintain or improve safety level by finding hazards, evaluation, taking measures and practice, and improving problems. Especially they systematically manage hazards to cause railway accidents and the factors which possibly threat safety, using national classification of risk and causes with analysis of the related data such as establishing accident/incident data and safety regulations/standards. As executing railway safety regulations, domestic railway is currently trying to improve railway safety management system. The research of classification system of accidents/incidents is one thing to make railway safety management systems better. In this research, we reviewed hazardous factors of railway systems and classification of the causes as the beginning of system safety management, and we conducted study on development of railway accident classification based on findings of this research. The results are able to be used in identifying hazards and activities of systemic safety management at the step of railway accident report and investigation.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.22 no.2
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• pp.140-148
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• 2012

Objectives: This study was performed to provide harmonized guidelines on health and environmental classification criteria and its results of chemicals in Korea. Methods: Firstly, The history of GHS implementation in UN and Korea was reviewed. Secondly, the differences in classification criteria on health and environmental hazards among UN GHS and two Korean government agencies, Korea Ministry of Employment and Labour (KMoEL) and Korea Ministry of Environmental (KMoE). The classification results were compared between classifications of Korea Occupational Safety and Health Agency (KOSHA) based on KMoEL and classifications of Korea National Institute of Environmental Research (KNIER) based on KMoE. Finally, an inter-agency harmonization on the classification criteria and the results was suggested by comparing the classification results of 5 chemicals; Benzene, carbon disulfide, formaldehyde, toluene-2,4-diisocyanate, and trichloroethylene. Results: KMoEL and KMoE revised regulations on chemical management and published a Notices on GHS classification criteria according to UN GHS document. However, the hazard to the ozone layer contained in the latest edition of UN GHS document published in 2011 was not included yet. The differences in classifications of 5 chemicals between KOSHA and KNIER were 36.2% in health hazards and 23.4% in environmental hazards, respectively. In conclusion, we suggested that a new revision be needed to include newly contained hazard and inter-agency working party be organized to harmonize classification results.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.3
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• pp.209-220
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• 2022

Objectives: This study was performed to suggest how to re-establish criterion for toxic substances under the Chemical Control Act (CCA) in South Korea by comparing the GHS (Globally Harmonized System of Classification and Labeling of Chemicals) score and toxic properties. Methods: Toxic substances were classified into seven groups (Acute toxicity (1A), Chronic toxicity (2C), Environmental hazards (3E), Acute toxicity & chronic toxicity (4AC), Chronic toxicity & environmental hazards (5CE), Acute toxicity & environmental hazards (6AE), and Acute toxicity & chronic toxicity & environmental hazards (7ACE)) according to their toxic properties. The GHS score was calculated to sum up five toxicity indicators (health acute toxicity, health repeated toxicity, carcinogenicity, health other chronic toxicity and environmental hazards). Results: The GHS score of 7ACE was higher by 7 times that of 1A. 1A is the only group which has lower than the total GHS score. The highest score was 47, for sodium chromate (CAS no. 7775-11-3), which belongs to group 7ACE. This is classified as acute toxicity, carcinogenicity, germ cell mutagenicity, reproductive toxicity, and acute and chronic environmental hazard. On the other hand, the lowest score was 2.75, which was assigned to 177 chemicals belonging to group 1A. When the health acute toxicity indicator was omitted from the toxic criterion, toxic substances could be divided into the sub-groups 'human chronic hazards group' (HCG) and 'environmental hazards group' (EG) according to their GHS score and properties. Conclusions: The proposed criterion for toxic substances is to establish sub-groups defined as HCG and EG for separate control and that the 1A group be moved to substances requiring preparation for accidents under the CCA.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.1-6
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• 2005

To improve safety management of railway and cope with the factors to threat technical and social safety, we need to establish railway safety management system based on analysis of hazards and assessment of risk for railway system. So we have to conduct PHA(Preliminary Hazard Analysis) first to understand weak points and factors to possibly threat safety using analysis of related data such as past accident/incident data and safety regulation and classification standards of hazards/causes of railway accidents. Therefore in this research, we led types/dangerous events/causes of risks/factors of risks from hazard log developed based on railway accident classification and hazards of railway accident. PHA model for domestic railway system will be used in risk analysis and risk assessment of railway accident.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.233-242
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• 2009

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in crystalline rocks like gneiss, granite, and so on, a prediction model was developed by the use of a decision tree model. The classification standard of the selected prediction model is composed of the slope angle, the coefficient of permeability and the void ratio in the order. The computer program, SHAPP ver. 1.0 for prediction of slope hazards around an important national facilities using GIS technique and the developed model. To prove the developed prediction model and the computer program, the field data surveyed from Jumunjin, Gangneung city were compared with the prediction result in the same site. As the result of comparison, the real occurrence location of slope hazards was similar to the predicted section. Through the continuous study, the accuracy about prediction result of slope hazards will be upgraded and the computer program will be commonly used in practical.

• Environmental Analysis Health and Toxicology
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• v.21 no.2 s.53
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• pp.197-208
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• 2006

The hazards of chemicals can be classified using classification criteria that are based on physical, chemical and ecotoxicological endpoints. These criteria may be developed be iteratively, based on scientific or regulatory processes. A number of national and international schemes have been developed over the past 50 years, and some, such as the UN Dangerous Goods system or the EC system for hazardous substances, are in widespread use. However, the unnecessarily complicated multiplicity of existing hazard classifications created much unnecessary confusion at the user level, and a recommendation was made at the 1992 Rio Earth summit to develop a globally harmonized chemical hazard classification and compatible labelling system, including material safety data sheets and easily understandable symbols, that could be used for manufacture, transport, use and disposal of chemical substances. This became the globally harmonized system for the Classification and Labelling of Chemicals (GHS). The developmental phase of the GHS is largely complete. Consistent criteria for categorizing chemicals according to their toxic, physical, chemical and ecological hazards are now available. Consistent hazard communication tools such as labelling and material safety data sheets are also close to finalizations. The next phase is implementation of the GHS. The Intergovernmental Forum for Chemical Safety recommends that all countries implement the GHS as soon as possible with a view to have the system fully operational by 2008. When the GHS is in place, the world will finally have one system for classification of chemical hazards.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.80-88
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• 2017

Although hazard identification is one of the most important steps of safety management process, numerous hazards remain unidentified in the construction workplace due to the dynamic environment of the construction site and the lack of available resource for visual inspection. To this end, our previous study proposed the collective sensing approach for safety hazard identification and showed the feasibility of identifying hazards by capturing collective abnormalities in workers' walking patterns. However, workers generally performed different activities during the construction task in the workplace. Thereby, an additional process that can identify the worker's walking activity is necessary to utilize the proposed hazard identification approach in real world settings. In this context, this study investigated the feasibility of identifying walking activities during construction task using Wearable Inertial Measurement Units (WIMU) attached to the worker's ankle. This study simulated the indoor masonry work for data collection and investigated the classification performance with three different machine learning algorithms (i.e., Decision Tree, Neural Network, and Support Vector Machine). The analysis results showed the feasibility of identifying worker's activities including walking activity using an ankle-attached WIMU. Moreover, the finding of this study will help to enhance the performance of activity recognition and hazard identification in construction.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.45-54
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• 2008

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in gneiss area, a prediction technique was developed by the use of a decision tree model, which is one of the statistical analysis methods. The slope hazards data of Seoul and Kyonggi Province, which were induced by heavy rainfall in 1998, were 104 sections in gneiss area. The number of data applied in developing prediction model was 61 sections except a vacant value. Among these data, the number of data occurred slope hazards was 34 sections and the number of data non-occurred slope hazards was 27 sections. The statistical analyses using the decision tree model were applied to chi-square statistics, gini index and entrophy index. As the results of analyses, a slope angle, a degree of saturation and an elevation were selected as the classification standard. The prediction model of decision tree using entrophy index is most likely accurate. The classification standard of the selected prediction model is composed of the slope angle, the degree of saturation and the elevation from the first choice stage. The classification standard values of the slope angle, the degree of saturation and elevation are $17.9^{\circ}$, 52.1% and 320 m, respectively.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1378-1385
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• 2008

The probability of landslide hazards was predicted to natural terrain around the stone relics of Jinjeon-saji area, which is located in Yangyang, Kangwon Province. As the analysis results of field investigation, laboratory test and geology and geomorphology data, the effect factors of landslides occurrence were evaluated, and then the landslides prediction map was made up by use of prediction model considering the effect factors. The susceptibility of stone relics induced by landslides was investigated as the grading classification of occurrence probability using the landslides prediction map. In the landslides prediction map, the high probability area of landslides over 70% of occurrence probability was 3,489m3, which was 10.1% of total prediction area. If landslides are occurred at the high elevation area, the three stories stone pagoda of Jinjeon-saji (National treasure No.122) and the stone lantern of Jinjeon-saji (Treasure No.439) will be collapsed by debris flow.