• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.843-856
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• 2023

The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.826-833
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• 2023

Purpose: We suggest the need to utilize ESG in the safety field to prevent serious industrial accidents. Method: The Serious Accident Punishment Act, a strong serious accident prevention system, was reviewed through a review of previous research. And through comparative analysis of serious accident data from the United States and Korea, the main causes of accidents in the domestic chemical industry were derived. Result: It was determined that there was a need to induce voluntary safety management by companies through ESG management along with the Serious Accident Punishment Act, which aims to prevent corporate accidents. Through statistical analysis of accident data, it was confirmed that the scale of damage and number of deaths in domestic accidents was greater than in the United States. The reason was interpreted to be that there are many accidents caused by human causes in the country. Conclusion: In order to compensate for the lack of voluntariness in corporate safety management as well as the Serious Accident Punishment Act and encourage active safety management, the proportion of 'ESG safety evaluation' must be expanded. By using ESG as an indirect social sanction, we can expect companies to voluntarily and actively manage safety and expand safety investments in the safety field.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.619-629
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• 2023

Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.5-11
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• 2023

Economic damage is occurring due to landslides and debris flows that occur when the ground artificially created for roads or photovoltaic power generation facilities is weakened by rainfall such as torrential rain. In order to understand the stability of the artificially created ground, it is very important to check the ground information such as the compositional state and mechanical characteristics of the stratum. However, since most of the investigation sites are steep slopes or there are no access roads, it is not easy to enter the drilling equipment commonly used to check ground information and perform standard penetration tests. In this study, a dynamic cone penetration test (DCP) device using a miniaturized auger drilling equipment and an automatic drop device was developed to check the cone resistance value and the dynamic cone penetration test value and analyze the correlation with the standard penetration test value to confirm its applicability at the mountain solar power generation site. As a result, the cone resistance value is q_d = 0.46 N and the dynamic cone penetration test value is N_d = 1.58 N, confirming a value similar to the results of existing researchers to secure its reliability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.526-532
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• 2023

Falls are fatal accidents that occur more than 420,000 times a year worldwide. Therefore, to study patients with falls, we found the association between extrinsic injury codes and principal diagnosis S-codes of patients with falls, and developed a prediction model to predict extrinsic injury codes based on the data of principal diagnosis S-codes of patients with falls. In this study, we received two years of data from 2020 and 2021 from Institution A, located in Gangneung City, Gangwon Special Self-Governing Province, and extracted only the data from W00 to W19 of the extrinsic injury codes related to falls, and developed a prediction model using W01, W10, W13, and W18 of the extrinsic injury codes of falls, which had enough principal diagnosis S-codes to develop a prediction model. 80% of the data were categorized as training data and 20% as testing data. The model was developed using MLP (Multi-Layer Perceptron) with 6 variables (gender, age, principal diagnosis S-code, surgery, hospitalization, and alcohol consumption) in the input layer, 2 hidden layers with 64 nodes, and an output layer with 4 nodes for W01, W10, W13, and W18 exogenous damage codes using the softmax activation function. As a result of the training, the first training had an accuracy of 31.2%, but the 30th training had an accuracy of 87.5%, which confirmed the association between the fall extrinsic code and the main diagnosis S code of the fall patient.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.533-539
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• 2023

This study aimed to analyze patients hospitalized for injuries who fell using the data from 2020 to 2021 at institution A located in Gangneung-si, Gangwon-do, using codes for causes of injury. After classifying 20 codes from W00 to W19, which are external cause codes for fall patients, the most frequently occurring W18, W01, W10, and W13 were analyzed. The external cause of injury code W18 was other falls on the same plane, with the highest frequency of S72 and Z47, S72 being a fracture of the femur, and Z47 being orthopedic follow-up treatment. The external injury code W01 was determined to be a fall on the same plane due to slipping, tripping, and tripping, and like W18, S72, a fracture of the femur, and Z47, orthopedic follow-up treatment, were frequently reported. In W10, intracranial injuries such as concussion and epidural hemorrhage due to a fall on the stairs, S06, were common. Lastly, in W13, 91% of cases occurred in people in their 40s to 70s due to falls from buildings or structures, confirming that they occur frequently in middle-aged people, Z47 had the most frequent orthopedic follow-up treatment, and S72 had a fracture of the femur. It was found to be the second most common. In this way, the frequency of falling patients was analyzed, and the age and main diagnosis code at which most falls occurred were analyzed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.83-89
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• 2024

After the end of the service of Internet Explorer, the use of ActiveX ended, and the Non-ActiveX policy spread. HTML5 is used as a standard protocol for web pages established based on the Non-ActiveX policy. HTML5, developed in the W3C(World Wide Web Consortium), provides a better web application experience through API, with various elements and properties added to the browser without plug-in. However, new security vulnerabilities have been discovered from newly added technologies, and these vulnerabilities have widened the scope of attacks. There is a lack of research to find possible security vulnerabilities in HTML5-applied websites. This paper proposes a model for detecting tags and attributes with web vulnerabilities by detecting and analyzing security vulnerabilities in web pages of public institutions where plug-ins have been removed within the last five years. If the proposed model is applied to the web page, it can analyze the compliance and vulnerabilities of the web page to date even after the plug-in is removed, providing reliable web services. And it is expected to help prevent financial and physical problems caused by hacking damage.

• Information Systems Review
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• v.19 no.4
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• pp.27-42
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• 2017

With the rapid development in network, graphic technology, and digital technology, content industry is emerging as an important industry for new cultural development and economic development. The development in digital content technology has remarkably expanded the generation and distribution of contents, thereby creating new value and extending into a large distribution market. However, the ease of distribution and duplication, which characterizes digital technology, has increased the circulation of illegal contents due to illegal copying, theft, and alteration. The damage caused by this illegal content is severe. Currently, a copyright protection system targeting online sites is available. By contrast, no system has been established for offline companies that sell offline genuine content, which compete with online companies. The demand for content of overseas tourists is increasing due to the Korean wave craze. Nevertheless, many offline content providers have lost competitiveness due to illegal content distribution with online companies. In this study, we analyzed the case and status of similar copyright certification systems in Korea and overseas through previous research and studied a system to certify the offline genuine contents business. In addition to the case analysis, we focused on interviews obtained through in-depth interviews with the copyright stakeholders. We also developed a certification framework by establishing the certification domain, certification direction, and incentive of the certification system for offline businesses with genuine content. Selected certification direction is ethical, open, inward, store, and rigid (post evaluation). This study aimed to increase awareness among consumers about the use of genuine content and establish a transparent trading order in a healthy content market.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.41-51
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• 2024

If an underground accident occurs, the cause must be quickly identified and human and material damage reduced. The Underground Accident Investigation Committee is responsible for identifying the causes of accidents and preparing response plans to prevent similar accidents from occurring in the future. The law stipulates that the Underground Accident Investigation Committee can operate from a minimum of 6 months to a maximum of 9 months after an accident occurs. However, the operation schedule of the Underground Accident Investigation Committee seems difficult to cite the accident investigation report to the construction project currently in progress at the same time project. In this study, the Underground Accident Investigation Committee seeks to establish a strategy for developing technology that can shorten data collection and analysis, which previously took 3 months, to less than 1 month. As a result of the research, five areas of technology development identified, ground data collection and transmission technology, ground safety data generation technology, digital twin-based underground safety analysis and visualization technology, digital twin-based geo-ambulance construction and operation technology, and digital twin-based geo-ambulance standardization and legal system. research was able to be conducted. If the proposed technology is developed, it is expected to contribute to reducing accident scenes through faster decision making than before.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.1-11
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• 2024

Bridges crack and become damaged due to age and external factors such as earthquakes, lack of maintenance, and weather conditions. With the number of aging bridge on the rise, lack of maintenance can lead to a decrease in safety, resulting in structural defects and collapse. To prevent these problems and reduce maintenance costs, a system that can monitor the condition of bridge and respond quickly is needed. To this end, existing research has proposed artificial intelligence model that use sensor data to identify the location and extent of cracks. However, existing research does not use data from actual bridge to determine the performance of the model, but rather creates the shape of the bridge through simulation to acquire data and use it for training, which does not reflect the actual bridge environment. In this paper, we propose a bridge safety determination edge AI model that detects bridge abnormalities based on artificial intelligence by utilizing acceleration data from bridge occurring in the field. To this end, we newly defined filtering rules for extracting valid data from acceleration data and constructed a model to apply them. We also evaluated the performance of the proposed bridge safety determination edge AI model based on data collected in the field. The results showed that the F1-Score was up to 0.9565, confirming that it is possible to determine safety using data from real bridge, and that rules that generate similar data patterns to real impact data perform better.