• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.577-586
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• 2018

In this study, traffic safety technology was developed for rural areas by reviewingthe relevant literature and data from the Traffic Accident Analysis System for the Chungcheong region.The goal is to reduce traffic accidents in small regional cities and rural areas in Korea. A road shoulder recognition light was developed to fit the pedestrian characteristics of the people using transportation in rural areas. It also minimizes damage to crops due to light pollution from traffic lights and street lights, and it supplements problems of damage from collision with vehicles and agricultural machines. The efficiency of the technology developed in this study was verified by comparing and analyzing the number of traffic accidents and the saved cost before and after its installation. A test bedwas established based on rural areas and is being evaluated for its applicability and effectiveness. It is expected that the reliability of such facilities could be improved through continuous studies, data collection, and analysis.

• Journal of the Korean Geotechnical Society
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• v.40 no.5
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• pp.93-101
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• 2024

Numerical analysis methods are widely used to assess the safety of hydrogen storage facilities; however, obtaining data under various conditions poses significant challenges. This study aims to expand the dataset using oversampling algorithms and utilize these enhanced datasets as diverse input parameters for numerical analysis. The oversampling techniques applied include SMOTE, Borderline-SMOTE, ADASYN, and CTGAN, with data amplified by factors of 2, 5, and 100 relative to the original dataset. This approach increases data volume based on the characteristics of the existing data, which may consequently introduce outliers. To address this, statistical methods such as the 3-sigma rule and the confidence level method are employed to identify and remove outliers beyond the normal distribution range. The reliability of the conditions generated through data amplification and outlier analysis is evaluated by comparing them with trends observed in the original dataset. Additionally, the SHAP algorithm is utilized to analyze changes in the importance values of each parameter. The SHAP values derived from the original dataset and those processed through AI techniques and outlier analysis exhibit similar trends, validating the proposed methodologies. The methods proposed in this paper are applicable not only to hydrogen storage facilities but also to the systematic construction of data for assessing the stability of various geotechnical structures.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.238-246
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• 2021

Collision of small vessels such as fishing boats cause great personal injury. Prior to this study, the collision prevention algorithm was developed to assess the collision risk and make the collision alarm. However, a service provided for safety, such as a collision warning, not only prevents risks, but also requires a certain degree of user satisfaction to function effectively. In this study, the collision prevention algorithm for small vessels was improved to be more practical, and the effects of the improvement were confirmed by applying the algorithm. A survey conducted on the users of the collision warning service confirmed the user requirements for improving the accuracy of the collision warning system and reducing the volume and number of alarms. Accordingly, the algorithm was improved for user satisfaction, and the actual vessel experiment was performed applying the improved algorithm in an actual maritime environment. As a result, the frequency of alarm occurrence decreased compared to former algorithm, but the alarm was relatively steadily generated in dangerous situations. It was analyzed that the accuracy and practicality of the collision alarm were improved. If the practicality and reliability of the improved algorithm are verified in the further study, it will be able to effectively contribute to the prevention of collisions of small vessels.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1098-1105
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• 2021

The International Maritime Organization has steadily strengthened environmental regulations on nitrogen oxides and carbon dioxide emitted from marine vessels. Consequently, the demand for electric propulsion vessels based on eco-friendly elements has increased. To this end, research and development has been steadily conducted for various vessels. In electric propulsion systems, a redundancy configuration is typically adopted to increase reliability and facilitate the onboard arrangement. Furthermore, studies have been actively conducted to ensure the safety of electric propulsion systems through the combination with digital twin technology. A digital twin can be used to predict outcomes in advance by implementing real-world equipment or space in a virtual world like twins, integrating real-world information and data with the virtual world, and performing computer simulations of situations that can occur in a real environment. In this study, we perform failure modes and effects analysis (FMEA) to validate the electric power management system (PMS) redundancy scheme for the digital twin technology development of electric propulsion vessels. Then, we propose the role and algorithm of PMS as a compensation function for preventing primary and secondary damages caused by a single equipment failure of the PMS and preventing additional damages by analyzing the impact on the entire system under real vessel operating conditions based on the redundancy FMEA suggested for the ship classification and certification. We verified the improvement in propulsion conservation through tests.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.77-84
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• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3B
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• pp.360-374
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• 2004

The OSPF protocol is the most widely used Interior Gateway Routing Protocol. Therefore, for the reliability of behavior of gigabit swiching routers, it is essential to guarantee the interoperability and the safety of the OSPF protocol. In this paper, we analyze the standard document of the OSPF protocol, so that we provide a formal specification that specifies the protocol behaviors by detailed design level using the algebraic formal method. By referring available source codes of the OSPF protocol, we supplement the formal specification to express more detailed behaviors that is not specified definitely in the standard. We also formally verify the interoperability and the safety of the protocol state machine of the specification. By showing that the formal specification specify all of the states and the transition events that appear in the standard document of the OSPF protocol, we prove that the state machine has the completeness, and prove it has the interoperability. To prove that the specification of the protocol has the safety, we formally verify the reachability, the liveness, the livelock-free property, and the deadlock-free property. As a result, we prove the protocol has the consistency. The specification and the validation are also effective to the OSPF Version 3 that inherit the protocol mechanism of the OSPF Version 2.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.54-62
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• 2017

This paper describes the behavior and failure probability of the basic structural members in a fire for the fire safety assessment of offshore structures. A fire safety assessment can be accomplished by comparing the fire resistance of the members with the fire severity of the heat load due to fire. The fire severity is represented as the maximum temperature of the members using the Eurocode 1 standard fire curve and heat transfer equation. On the other hand, the fire resistance is the limiting temperature calculated by a simplified formula in the case of simple structural members. Considering the complexity of FPSOs and offshore structures, a general-purpose structural analysis program should be used and the limiting temperature obtained by analyzing the structural strength of the members through an elasto-plastic analysis with a large deflection, and compared with the maximum temperature. Also, the equality of these two methods of evaluating the fire resistance was confirmed by comparing them. Following three criteria, the strength, serviceability and stability, three failure modes, namely the first failure of a hinge, large deflection and buckling, were chosen. The failure temperature was verified for each failure mode. using the AFOSM method in the equation of the fire severity and fire resistance, thereby giving the failure probability of the member. By applying these processes to the example of a beam and plate, the behavior of the structure and failure (temperature?) of each failure mode can be determined.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.92-102
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• 2020

Porous pavement (PP) has attracted attention as a new alternative measure against road traffic noise. PP refers to pavement that reduces the fines in the asphalt mixture to form voids. These voids can reduce traffic accidents and friction noise. For active application, verification of the noise reduction effect is required. In this study, the noise reduction of single-layer PP(SLPP) and double layer PP(DLPP) was analyzed. First, the Sejong section was selected, and traffic noise was measured using the SPB method on the roadside. The traffic volume, speed, and mixing ratio of large vehicles were measured. As a result, the DLPP was evaluated to be 7.95 dB(A) smaller on average and 7.57dB(A) smaller at the 95% reliability level than the SLPP. The traffic volume was more influential than the speed and the mixing rate of large vehicles. As the traffic volume increased, the noise increased, but the difference in noise between the two pavements decreased gradually. The results showed that the most effective way to reduce road traffic noise is to change the road pavement rather than reduce traffic speed, restrict traffic for heavy vehicles, or reduce traffic volume.