• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.95-101
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• 2021

Marine Incidents based on Heinrich's law are very important in preventing accidents. However, marine Incident data are mainly qualitative and are used to prevent similar accidents through case sharing rather than statistical analysis, which can be confirmed in the marine Incident-related data posted in the Korea Maritime Safety Tribunal. Therefore, this study derived quantitative results by analyzing the causes of marine incidents during berthing using various methods of statistical analysis. To this end, data involving marine incidents from various shipping companies were collected and reclassified for easy analysis. The main keywords were derived via primary analysis using text mining. Only meaningful words were selected via verification by an expert group, and time series and cluster analysis were performed to predict marine incidents that may occur during berthing. Although the role of an expert group was still required during the analysis, it was confirmed that quantitative analysis of marine incidents was feasible, and iused to provide cause and accident prevention information.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.741-747
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• 2022

Fatigue lowers an individual's ability and makes it difficult to perform work. As fatigue accumulates, concentration decreases and thus the possibility of causing a safety accident increases. Awareness of fatigue is subjective, but it is necessary to quantitatively measure the level of fatigue in the actual field. In previous studies, it was proposed to measure the level of fatigue by expert judgment by adding objective indicators such as bio-signal analysis to subjective evaluations such as multidisciplinary fatigue scales. However this method is difficult to evaluate fatigue in real time in daily life. This paper is a study on the fatigue classification model that determines the fatigue level of workers in real time using speech data recorded in the field. Machine learning models such as logistic classification, support vector machine, and random forest are trained using speech data collected in the field. The performance evaluation showed good performance with accuracy of 0.677 to 0.758, of which logistic classification showed the best performance. From the experimental results, it can be seen that it is possible to classify the fatigue level using speech signals.

• The Korean Journal of Emergency Medical Services
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• v.27 no.2
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• pp.7-17
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• 2023

Purpose: This study aimed to identify the factors that contribute to head injuries among drivers of personal mobility devices and provide insights into safety perceptions. Methods: This retrospective study analyzed data of 221 trauma patients obtained from electronic medical records and the National Emergency Department Information System (NEDIS) over one year, from August 1, 2021, to July 31, 2022. The patients, all in their 20s and 30s, presented to a single emergency medical center following personal mobility device accidents (motorcycles, electric scooters, and bicycles). Results: Among motorcycle riders, 18.2% were not wearing helmets, while the percentage of e-scooter riders not wearing helmets was 87.5%. Wearing a helmet was associated with a 71.2% lower likelihood of head injuries (OR=0.288, CI=0.163 to 0.509, p=0.000). Of the personal mobility devices, motorcycles had a 0.431 times lower odds ratio for head injury compared to e-scooters (p=0.009), and there was no significant difference between e-scooters and bicycles (p=0.776). Conclusion: It is imperative to strengthen safety regulations by mandating helmet use for riders of personal mobility devices. A system to enhance driving enforcement for electric scooters, which are increasingly popular among young adults, should also be established.

• Informatization Policy
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• v.30 no.1
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• pp.67-88
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• 2023

The expansion of the scope of product liability is necessary because the industrial environment has changed following the enactment of the Product Liability Act. Unlike human-coded algorithms, artificial intelligence is black-boxed according to machine learning, and even developers cannot explain the results. In particular, since the cause of the problem by artificial intelligence is unknown, the responsibility is unclear, and compensation for victims is not easy. This is because software or artificial intelligence is a non-object, and its productivity is not recognized under the Product Liability Act, which is limited to movable property. As a desperate measure, productivity may be recognized if it is stored or embedded in the medium. However, it is not reasonable to apply differently depending on the medium. The EU revise the product liability guidelines that recognize product liability when artificial intelligence is included. Although compensation for victims is the value pursued by the Product Liability Act, the essence has been overlooked by focusing on productivity. Even if an accident occurs using an artificial intelligence-adopted service, however, it is desirable to present standards according to practical risks instead of unconditionally holding product responsibility.

• Archives of Plastic Surgery
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• v.50 no.1
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• pp.37-41
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• 2023

Background The coronavirus disease 2019 (COVID-19) outbreak has had a major impact worldwide. Several countries have implemented restrictions on social interaction ("social distancing"). Several studies have reported that the epidemiology of trauma patients, such as those with facial bone fractures, has changed after COVID-19 pandemic. This study aimed to further explore these specific changes. Methods This was a retrospective study of patients who presented to a single institution with facial bone fractures between January 1, 2016, and December 31, 2020. Baseline patient demographics, clinical information, type of fracture, etiology, and operative management were compared before and after COVID-19. Results Of all cases, 3,409 occurred before COVID-19, and 602 occurred after COVID-19. Since the outbreak of COVID-19, the number of patients with facial fractures has not decreased significantly. A significant increase was noted in fractures that occurred outdoors (p < 0.001). However, a decrease was observed in operative management between the groups (p < 0.001). There was no significant difference in the proportion of assault, fall-down, industrial accident, or roll-down. In contrast, the proportion of traffic accidents and slip-down categories increased significantly (p < 0.05). Moreover, a significant decrease was found in the proportion of the sports category (p = 0.001) Conclusions It was confirmed through this study that COVID-19 pandemic also affected epidemiology of facial fractures. Focusing on these changes, it is necessary to develop safety measures to reduce facial fractures.

• Journal of the Korean Institute of Gas
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• v.27 no.1
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• pp.13-22
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• 2023

As an alternative to environmental pollution generated from fossil fuels currently in use, research is being actively conducted to use hydrogen that does not cause air pollution. As fire and explosion accidents caused by hydrogen leakage have occurred until recently, research on safety is needed to commercialize hydrogen on ships, which are special environments. In this study, a seasonal alternative scenario for each season and the worst scenario were assumed in the event of a leakage accident while a hydrogen fuel cell propulsion ship equipped with a hydrogen storage tank was navigating at JangSaengPo port in Ulsan. In order to consider environmental variables, the damage impact range was derived through ALOHA and probit analysis based on the annual average weather data for 2021 by the Korea Meteorological Administration and on geographic information data from the National Statistical Office. Radiation showed a wider damage range than that of Overpressure and Flame in both the alternative and worst-case scenarios, and as a result of probit analysis, a fatality rate of 99% was confirmed in all areas.

• The Journal of Bigdata
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• v.7 no.1
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• pp.89-97
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• 2022

Various efforts are needed to prevent accidents because ship collisions can cause various negative situations such as economic losses and casualties. Therefore, research to prevent accidents is being actively conducted, and in this study, new leading indicators for preventing ship collision accidents is proposed. In previous studies, the risk of collision was expressed in consideration of the distance between ships in a specific sea area, but there is a disadvantage that a new model needs to be developed to apply this to other sea areas. In this study, the density-based ship domain DESD (Density-based Empirical Ship Domain) including the environment and operating characteristics of the sea area was defined using AIS (Automatic Identification System) data, which is ship operation information. Deep clustering is applied to two-dimensional DESDs created for each sea area to cluster the seas with similar operating environments. Through the analysis of the relationship between clustered sea areas and ship collision accidents, it was statistically tested that the occurrence of accidents varies by characteristic of each sea area, and it was proved that DESD can be used as a leading indicator of accidents.

• Convergence Security Journal
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• v.22 no.2
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• pp.59-66
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• 2022

Recently, smart home technology has been developed with a great response due to the convenience of home automation. Smart home technology provides various services by connecting various Internet of Things (IoT) and sensors to a home network through wired/wireless networks. In addition, the smart home service easily and conveniently controls lighting, energy, environment, and door cameras through a wall pad. However, while it has become a social issue due to the recent hacking accident of wall pads, personal information leakage and privacy infringement are expected. Accordingly, it is necessary to prepare preventive and countermeasures against security vulnerability factors of wall pads. Therefore, this study expects that it can be used as basic data for future smart home application and response technology development by examining the weak causes and countermeasures related to wall pads.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.5
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• pp.95-101
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• 2023

Recent persistent coastal developments have expanded recreational areas and enhanced accessibility. However, this growth has also led to a rise in safety incidents. These accident factors can be divided into human-made and natural types. The latter is comprised of dynamic factors like waves, tides, sea fogs, and winds. While institutions like the Korea Meteorological Administration and the Korea Hydrographic and Oceanographic Agency already offer data on these dynamic factors, the resolution is often insufficient for a precise assessment of localized risks. In this study, to overcome these limitations, we utilized the dynamic information from existing open systems to construct a high-resolution numerical simulation. Through this, we developed an automated module to predict dynamic factors in localized coastal activity areas. Particularly during the module's construction, we compared and reviewed the numerical prediction results for waves with observed wave heights.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.566-573
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• 2024

Applying autonomous driving technology to construction sites is very difficult due to safety issues. However, the application of various positioning and sensing devices, such as cameras and radars, to construction equipment is very active. Based on these technological trends, the government is making various efforts, including the Serious Accident Punishment Act and support for industrial safety management expenses, to reduce the incidence of accidents caused by construction equipment and industrial vehicles. And, related industries have been developing various safety equipment over the past few years and applying them to the field. In this paper, we investigate the current status of safety equipment-related technologies currently applied to construction equipment and industrial vehicles, and propose a direction for the development of safety technology in construction equipment based on artificial intelligence. Improving the safety and work efficiency of construction equipment based on the technology proposed in this paper should be reviewed through simulation in the future.