• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2103-2123
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• 2018

Ships built today are larger in scale and feature more complex structures. The ever-evolving systems used on board a ship require vast amounts of data processing. In the future, with the advent of smart ships, unmanned ships and other next-generation ships, the volumes of data to be processed will continue to increase. Yet, to date, ship data has been processed using wired networks. Placed at fixed locations, the nodes on wired networks often fail to process data from mobile devices. Despite many attempts made to use Wi-Fi on ships just as on land to create wireless networks, Wi-Fi has hardly been available due to the complex metal structures of ships. Therefore, Wi-Fi on ships has been patchy as the ship-wide total Wi-Fi coverage has not properly implemented. A new ship-wide wireless network environment is part of the technology conducive to the shipbuilding industry. The wireless network environment should not only serve the purpose of communication but also be able to manage and control multiple features in real-time: fault diagnostics, tracking, accident prevention and safety management. To better understand the characteristics of wireless frequencies for ships, this paper tests the widely used TETRA, UHF and Wi-Fi and sheds light on the features, advantages and disadvantages of each technology in ship settings. The proposed deployment of a Super Wi-Fi network leveraging the legacy UHF system of TMS generates a ship-wide wireless network environment. The experimental findings corroborate the feasibility of the proposed ship-wide Super Wi-Fi network environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1853-1858
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• 2015

The existence communications of vessel focused on voice, FAX, ISDN, etc. using satellite on the existent most communications on the ships, and recently, the ships need high quality smart communication service environments. In the results of experiments using the existent system, it could access on board, but in the closed room of vessel, was impossible to access e-mail and smart apps except voice communication. In the present paper, we implemented a novel communication system that can access voice, text, e-mail, file, vessel monitoring apps, etc. It consists of a convergent communication terminal combined with satellite and communication for Smartphone, and smart communication environment on the closed room. As the results, we can access a variety of smart communication in anywhere on board.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.82-89
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• 2023

Due to the characteristics of ship structure, the compartment structure is complicated and narrow, so safety accidents frequently occur during the work process. The main causes of accidents include structural collisions, falling objects, toxic substance leaks, fires, explosions, asphyxiation, and more. Understanding the on-site conditions of workers during accidents is crucial for mitigating damages. In order to ensure safety, the on-site situation is monitored using CCTV in the ship, but it is difficult to prevent accidents with the existing method. To address this issue, a smart safety helmet equipped with location identification and voice/video communication capabilities is being developed as a safety technology. Additionally, the smart safety helmet incorporates environmental sensors for temperature, humidity, vibration, noise, tilt (gyro sensor), and gas detection within the work area. These sensors can notify workers wearing the smart safety helmet of hazardous situations. By utilizing the smart safety helmet and environmental sensors, the safety of workers aboard ships can be enhanced.

• Journal of Navigation and Port Research
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• v.40 no.3
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• pp.97-103
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• 2016

The precise prediction of ships propulsion performance is very important to find out the ships optimum route. This paper describes the development of computer program to generate the database of propulsion performance for the ships optimum routing system. The propulsion performance of ship in the sea is caused by not only ships conditions such as drift and hull roughness, but also various sea conditions such as wave and wind. These prediction methods of added resistance are based on the ships speed trial analysis methods of the ISO 15016:2002 standard, and a few prediction methods of the wind and hull roughness are supplemented. These prediction methods have been applied to the comprehensive computer program. And the database calculation for the research ice breaker the Araon has been carried out, which shall be used for the calculation of optimum route. Furthermore, this program shall be used for the route optimization in global shipping routes.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.7-16
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• 2022

The targets of cyber-attacks are not limited to the websites and internal IT systems of shipping agencies. Ships and ports have become important targets for cyber attackers. This paper examines the current state of ship network security, introduces the International Maritime Organization's resolution on ship network security management, and summarizing the cyber-attacks in maritime so the readers can have a general understanding of maritime environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.447-463
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• 2022

Artificial Intelligence (AI) technology is a major technology that develops smart ships into autonomous ships in the marine industry. Autonomous ships recognize a situation with the information collected without human judgment which allow them to operate on their own. Existing ship systems, like control systems on land, are not designed for security against cyberattacks. As a result, there are infringements on numerous data collected inside and outside the ship and potential cyber threats to AI technology to be applied to the ship. For the safety of autonomous ships, it is necessary to focus not only on the cybersecurity of the ship system, but also on the cybersecurity of AI technology. In this paper, we analyzed potential cyber threats that could arise in AI technologies to be applied to existing ship systems and autonomous ships, and derived categories that require security risks and the security of autonomous ships. Based on the derived results, it presents future directions for cybersecurity research on autonomous ships and contributes to improving cybersecurity.

• Smart Structures and Systems
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• v.15 no.2
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• pp.315-334
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• 2015

A main goal of this study is to propose a damage detection technique to detect and localize damages of a top-tensioned riser. In this paper, the top-tensioned finite element (FE) model is considered as an analytical model of the riser, and a vibration-based damage detection method is proposed. The present method consists of a FE model updating and damage index method. In order to accomplish the goal of this study, first, a sensitivity-based FE model updating method using natural frequencies and zero frequencies is introduced. Second, natural frequencies and zero frequencies of the axial mode on the top-tensioned riser are estimated by eigenvalue analysis. Finally, the locations and severities of the damages are estimated from the damage index method. Three numerical examples are considered to verify the performance of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.692-712
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• 2022

Buoys used for Aid to Navigation systems are widely used to guide the sea paths and are powered by batteries, requiring continuous battery replacement. However, since human labor is required to replace the batteries, humans can be exposed to dangerous situation, including even collision with shipping vessels. In addition, Maritime sensors are installed on the route signs, so that these are often damaged by collisions with small and medium-sized ships, resulting in significant financial loss. In order to prevent these accidents, maritime object detection technology is essential to alert ships approaching buoys. Existing studies apply a number of filters to eliminate noise and to detect objects within the sea image. For this process, most studies directly access the pixels and process the images. However, this approach typically takes a long time to process because of its complexity and the requirements of significant amounts of computational power. In an emergent situation, it is important to alarm the vessel's rapid approach to buoys in real time to avoid collisions between vessels and route signs, therefore minimizing computation and speeding up processes are critical operations. Therefore, we propose Fast Connected Component Labeling (FCCL) which can reduce computation to minimize the processing time of filter applications, while maintaining the detection performance of existing methods. The results show that the detection performance of the FCCL is close to 30 FPS - approximately 2-5 times faster, when compared to the existing methods - while the average throughput is the same as existing methods.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.1-5
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• 2012

Recently, with increasing container ships' volume continuously, the conceptual design "Smart Harbor" of newly logistics processing system has been suggested. It is necessary to estimate resistance and horsepower for the selection of an appropriate propulsor at the initial design stage of Smart Harbor. In this study, CFD and the circulating water channel of the University of Ulsan are employed for estimating the resistance of the Smart Harbor Crane Ship with 1/100 scaled model. Two turbulent models are used. One is realizable k-${\varepsilon}$and the other is Reynolds stress turbulence model. In addition, the effects of the change in y+ and the number of meshes are considered during analysing.

• 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.