• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.44-49
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• 2021

Domestic industrial accidents continue to increase, with 2,142 deaths in 2018, up by 185 (9.5%) from 1,957 deaths in 2017. Industrial accidents that cause loss of human lives pose a serious risk to businesses because of the strengthening of safety regulations and the changing public perception of social responsibility. Accordingly, to prevent industrial accidents, companies regularly conduct onsite safety activities and conduct education and training to raise awareness among employees. However, many such corporate activities are not conducted voluntarily and practically by employees but mostly by formal implementation. To discontinue this customary and passive behavior of employees and establish a mature safety culture, strengthening the execution power of safety management at the site is of paramount importance, and to this end, we aim to utilize the safety practice index (SPI). In this study, the SPI calculated on the basis of the results of the 2018 and 2019 risk management and safety activities of a site was compared with the reported safety accidents. The results confirmed that the SPI index can be used as a valid indicator for safety activities for accident prevention, such as strengthening leadership and safety policies to grade and manage safety management levels for a certain period of time or by a department or to convert weaknesses into strengths.

• Smart Media Journal
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• v.11 no.2
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• pp.31-38
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• 2022

Promptly predicting changes in the salinity in rivers is an important task to predict the damage to agriculture and ecosystems caused by salinity infiltration and to establish disaster prevention measures. Because machine learning(ML) methods show much less computation cost than physics-based hydraulic models, they can predict the river salinity in a relatively short time. Due to shorter training time, ML methods have been studied as a complementary technique to physics-based hydraulic model. Many studies on salinity prediction based on machine learning have been studied actively around the world, but there are few studies in South Korea. With a massive number of datasets available publicly, we evaluated the performance of various kinds of machine learning techniques that predict the salinity of the Nakdong River Estuary Basin. As a result, LightGBM algorithm shows average 0.37 in RMSE as prediction performance and 2-20 times faster learning speed than other algorithms. This indicates that machine learning techniques can be applied to predict the salinity of rivers in Korea.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.2
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• pp.185-192
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• 2022

Fisheries is known as a high-risk industry in Korea, and various efforts have been made to reduce occupational accidents. Trap fisheries represent crustacean production, accounting for 4.7% of total fisheries production and 10.7% of its production value, which is classified as a relatively high-risk industry. With the disaster insurance payment data of the National Federation of Fisheries Cooperatives (NFFC) from 2016 to 2020, the accident rate of the entire fishery, the accident rate of trap fisheries, and the type of disasters in the past five years were analyzed. As a result, the average fishery accident rate for the past five years was 5.31%, but it was high at 6.15% for coastal trap fisheries and 5.59% for offshore trap fisheries. Slips and trips, struck by objects and contact with machinery were the most common types of the accident according to the characteristics of the work, and hand injuries were analyzed the most. Additional efforts, including education for accident prevention, development of personal protective equipment and improvement of the working environment, are needed to prevent accidents caused by repeated types of disasters.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.577-585
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• 2023

This study applied ALOHA Program to predict the damage caused by fire and explosion predicted to occur from gas leakage at LPG stations and presented plans to prevent damages by diagramming the impact range and distance. The propane gas leakage from LPG stations causes human damage like breathing issues and property damage, including building destruction to residents in the surrounding areas. As a way to reduce this, first, the hazardous substance safety manager of the LPG station needs to check frequently whether the meters and safety valves are working properly to prevent leakage in advance. Second, the LPG stations' storage tanks should be worked by the person who received "hazardous substance safety manager training" under the provisions of the Act on the Safety Control of Hazardous Substances and has been appointed as a "hazardous substance safety manager" by the fire department. Third, LPG station's various safety device functions, such as overfill prevention devices, must be checked on a regular basis. Finally, wearing work clothes and shoes that prevent static electricity at LPG stations is highly recommended, as static can cause a fire when gas leaks.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.75-89
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• 2024

The objective of this study was to conduct research and analysis using Group Focus Interview to survey the between construction site workers and managers implementing for the Severe Accident Punishment Act. Focused on measures to improve safety management effectiveness for the effectiveness of establishing a safety management system. A plan to improve the efficient safety management system was presented to 50 construction industrial managers and workers. In order to ensure the industrial accident prevention policies appropriately, it is necessary to be aware of safety obligations for workers as well as business operators. In addition, despite the existence of a commentary on the Serious Accident Punishment Act, confusion in the field still persists, so in the event of a major accidents, the obligation to take safety and health education is strengthened, and effective case education is proposed by teaching actual accident cases suitable for actual working sites. It is necessary to make all training mandatory, and it is necessary to reconsider awareness through writing a daily safety log, awareness of risk factors, etc., and writing down risk information. Above all, at the construction ordering stage, it is necessary to keep the construction safety, request corrections and supplements for problems issues that arise, and consult between the orderer and the construction company about the problems issues. Rather than having only the construction company correct or supplement the safety management plan, the contents should be shared with supervisors and workers to establish a more practical solution. Results of this study will contribute to improving the effectiveness of the serious accident and construction safety management system.

• Journal of Korean Society of Disaster and Security
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• v.6 no.1
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• pp.65-72
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• 2013

In this study, the early suicide prevention program was applied to the elementary school students and compared the prior & post effect of the program, and verified the status of psychology change like emotional status, or temptation to take a suicide, and presented the possibility as a suicide prevention program. The period of adolescence is the very unstable period in the process of growth being cognitively immature, emotionally impulsive period. It is the period emotionally unstable and unpredictable possible to select the method of suicide as an extreme method to escape the reality, or impulsive problem solving against small conflict or dispute situation. Many stress of the student such as recent nuclear family, expectation of parents to their children, education problem, socio-environmental elements, individual psychological factor lead students to the extreme activity of suicide in recent days. In this study, the scope of stress experienced in the elementary school as well as idea and degree of temptation regarding suicide by the suicide prevention program were identified, and through prevention program such as meditation training, breath training and through experience of anger control, emotion-expression, self overcome and establish positive self-identity and make understanding Self-control, Self-esteem & preciousness of life based on which the effect to suicide prevention was analyzed. The study was made targeting 51 students of 2 classes of 6th grade of elementary school of Goyang-si and processed 30 minutes every morning focused on through experience & activity of the principle & method of brain science. The data was collected for 20 times before starting morning class by using Suicide Probability Scale(herein SPS-A) designed to predict effectively suicide Probability, suicide risk prediction scale, surveyed by 7 areas such as Positive outlook, Within the family closeness, Impulsivity, Interpersonal hostility, Hopelessness, Hopelessness syndrome, suicide accident. Analytical methods and validation was used the Wilcoxon's signed rank test using SPSS Program. Though the process of program in short period, but there was a effective and positive results in the 7 areas in the average comparison. But in the t-test result, there was a different outcome. It indicated changes in the 3 questionnaires (No.7, No.14, No.19) out of 31 SPS-A questionnaires, and there was a no change to the rest item. It also indicated more changes of the students in the class A than class B. And in case of the class A students, psychological changes were verified in the areas of Hopelessness syndrome, suicide accident among 7 areas after the program was processed. Through this study, it could be verified that different results could be derived depending on the Student tendency, program professional(teacher in charge, processing lecturer). The suicide prevention program presented in this article can be a help in learning and suicide prevention with consistent systematization, activation through emotion and impulse control based on emotional stress relief and positive self-identity recovery, stabilization of brain waves, and let the short period program not to be died out but to be continued connecting from childhood to adolescence capable to make surrounding environment for spiritual, physical healthy growth for which this could be an effective program for suicide prevention of the social problem.

• Korean Security Journal
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• no.58
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• pp.81-106
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• 2019

This study analyzed safety management system against disasters perceived by local residents of Chungcheongbuk-do and then examined the policy directions to be considered in order for local governments to improve the safety level of residents and build an effective safety management system against disasters. The findings were as follows. First, in their recognition of risks of safety against disasters, recognition on the possibility of the occurrence of natural disasters was higher than that of social disasters or safety accidents. Secondly, also in the aspect of the importance of category of safety management against disasters, they recognized that of natural disasters far higher than others. Third, they showed satisfaction higher than average with basic job performance of local governments related with safety management, whereas they showed relatively less satisfaction with the aspects of check and publicity of risk factors, and short-term restoration system out of phased job performance. Fourth, in the aspect of capability of local governments for safety management against disasters, they rated positively capability of the responsible departments and the professionality, whereas they relatively underestimated the scale or budget of safety-related organizations. Fifth, the policy directions to be taken for safety against disasters by local governments included strengthening of regular education like experience-based training, expansion of education among local residents, more support for relevant facilities and resources, activation of residents-participating campaigns, improvement of apparatus and personnel treatment related with firefighting and security, frequent patrol and oversight, more exercises against disasters. So, to strengthen safety management system against disasters in local governments and build a effective responding system may need to extend programs assisting vulnerable class to safety against disasters, build a community-friendly safety management system, extend the cooperation system by participation of residents, enhance collaboration and support system with safety-related bodies like police, firefighters.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.202-217
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• 2022

Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.