• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.335-343
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• 2019

As the regulations of ship exhaust gas have been strengthened recently, many measures are under consideration to reduce fuel consumption. Among them, research has been performed actively to develop a machine-learning model that predicts fuel consumption by using data collected from ships. However, many studies have not considered the methodology of the main parameter selection for the model or the processing of the collected data sufficiently, and the reckless use of data may cause problems such as multicollinearity between variables. In this study, we propose a method to predict the fuel consumption of the ship by using the principal component analysis to solve these problems. The principal component analysis was performed on the operational data of the 13K TEU container ship and the fuel consumption prediction model was implemented by regression analysis with extracted components. As the R-squared value of the model for the test data was 82.99%, this model would be expected to support the decision-making of operators in the voyage planning and contribute to the monitoring of energy-efficient operation of ships during voyages.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.1-9
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• 2022

Ship detection in synthetic aperture radar (SAR) images is an important application in marine monitoring for the military and civilian domains. Over the past decade, object detection has achieved significant progress with the development of convolutional neural networks (CNNs) and lot of labeled databases. However, due to difficulty in collecting and labeling SAR images, it is still a challenging task to solve SAR ship detection CNNs. To overcome the problem, some methods have employed conventional data augmentation techniques such as flipping, cropping, and affine transformation, but it is insufficient to achieve robust performance to handle a wide variety of types of ships. In this paper, we present a novel and effective approach for deep SAR ship detection, that exploits label-rich Electro-Optical (EO) images. The proposed method consists of two components: a data augmentation network and a ship detection network. First, we train the data augmentation network based on conditional generative adversarial network (cGAN), which aims to generate additional SAR images from EO images. Since it is trained using unpaired EO and SAR images, we impose the cycle-consistency loss to preserve the structural information while translating the characteristics of the images. After training the data augmentation network, we leverage the augmented dataset constituted with real and translated SAR images to train the ship detection network. The experimental results include qualitative evaluation of the translated SAR images and the comparison of detection performance of the networks, trained with non-augmented and augmented dataset, which demonstrates the effectiveness of the proposed framework.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.384-394
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• 2020

This paper proposes an outlier detection model based on machine learning that can diagnose the presence or absence of major engine parts through unsupervised learning analysis of main engine big data of a ship. Engine big data of the ship was collected for more than seven months, and expert knowledge and correlation analysis were performed to select features that are closely related to the operation of the main engine. For unsupervised learning analysis, ensemble model wherein many predictive models are strategically combined to increase the model performance, is used for anomaly detection. As a result, the proposed model successfully detected the anomalous engine status from the normal status. To validate our approach, clustering analysis was conducted to find out the different patterns of anomalies the anomalous point. By examining distribution of each cluster, we could successfully find the patterns of anomalies.

• Journal of Ocean Engineering and Technology
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• v.24 no.2
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• pp.74-81
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• 2010

Ship STEP is the international standard for the exchange of ship modeling data between heterogeneous systems. It is expected that STEP AP218 can be used for seamless data exchange between various CAD/CAM/CAE systems used in the shipbuilding design process. Although the conformance assessment for standards would maximize the performance and confidence about data exchanges, most research has been directed toward interoperability testing. ISO SC4/TC184 only provides the method for conformance testing, and it can be used with test cases on application protocols. Even though standards have been defined for conformance assessment and testing, there is no organization or association. CAD vendors have focused on interoperability testing for evaluation of the performance of their systems. In this paper, the conformance testing criteria for AP218 have been developed with abstract test cases of ship structures. The requested STEP translator was also reviewed with a developed item pool of testing criteria. The criteria methodology would be a guideline for the development of translators and interfaces. The item pool method of testing criteria for conformance assessment would increase performance and efficiency of data translators for Ship STEP and other standards.

• 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 Korean Society of Fisheries and Ocean Technology
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• v.59 no.4
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• pp.344-353
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• 2023

In the actual sea, the additional resistance due to external force such as wind, current and wave is accompanied, and the required power is added in response to these resistance. Especially when the ship is sailing at low speed, the effects of wind and current have a great impact on the safe control of the ship. Likewise, it is thought that the effects of wind and current have a great impact on the trawl ship control since the towing speed of a bottom trawl ship is a low speed of 3 to 4 knots. If the reduce of ship speed and the increase of engine power due to the influence of wind and current can be identified, the safe towing power can be calculated based on a given engine output. Thus, the appropriate size of a fishing gear can be determined. In this study, a total of 20 trawl operations were conducted for seasonal maritime research in the same research area according to the operation mode of propeller. Based on navigation data, trawl fishing data, and engine performance data acquired during the towing fishing gear, and data of ship speed, hull resistance, fishing gear resistance, wind force and current force according to an incidence angle were estimated. The overall power for these loads was calculated and compared with the measured engine power, and the effects of wind force and current force on the engine power were investigated.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.294-303
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• 2020

This study discusses data collection, calculation of wind and wave-induced resistance, and speed-power analysis of an 8,600 TEU container ship. Data acquisition system of the ship operator was improved to obtain the data necessary for the analysis, which was accomplished using SPA (Ship Performance Analysis, Park et al., 2019) in conformation with ISO15016:2015. From a previous operation profile of the container, the standard operating conditions of mean draft were 12.5 m and 13.6 m, which were defined with the mean stowage configuration of each condition. Model tests, including the load-variation test, were conducted to validate new ship performance and for the speed-power analysis. The major part of the added resistance of container ship is due to the wind. To check the reliability of wind-resistance calculation results, the resistance coefficients, added resistance, and speed-power analysis results using the Fujiwara regression formula (ISO15016:2015) and Computational fluid dynamics (Ryu et al., 2016; Jeon et al., 2017) analysis were compared. Wind speed and direction measured using an anemometer were used for wind-resistance calculation and the wave resistance was calculated using the wave-height and direction-data from weather information. Also, measured water temperature was used to calculate the increase in resistance owing to the deviation in water density. As a result, the SPA analysis using measured data and weather information was proved to be valid and able to identify the ship's resistance propulsion performance. Even with little difference in the air-resistance coefficient value, both methods provide sufficient accuracy for speed-power analysis. The differences were unnoticeable when the speed-power analysis results using each method were compared. Also, speed-power analysis results of the 8,600 TEU container ship in two draft conditions show acceptable trends when compared with the model test results and are also able to show power increase owing to hull fouling and aging. Thus, results of speed-power analysis of the existing 8,600 TEU container ship using the SPA program appropriately exhibit the characteristics of speed-power performance in deal conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1111-1118
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• 2013

In this paper, the disturbance applied to launcher hatch by ship motions is introduced to identify the vertical ship motion disturbance. Basically, ship motions are comprised of 6 degrees of freedom: roll, pitch, yaw, heave, surge and sway. In the case of the shipboard launcher hatch the coupled pitch, heave and roll are significant motions to be transformed to a vertical direction motion. The maximum acceleration values are obtained from the vertical motion model and the ship motion data in accordance with ship type and hatch location on the ship. We verify that the maximum pitch motion mainly influences the launcher hatch and also present the quantity of the maximum load disturbance by the ship's motion acceleration.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.447-453
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• 2019

Recently, environmental regulations have been strengthened for SOX, NOX, and CO2, which are ship exhaust gases. In addition, according to the 4th Industrial Revolution, research on autonomous ship technology has become active and interest in electric propulsion systems is increasing. This paper analyzes the power load characteristics of an electric propulsion ship, which is the basic technology for an autonomous ship, in terms of energy management. For the load analysis, data were collected for a 6,800 TEU container ship with a mechanical propulsion system, and the propulsion load was converted to an electric power load and clustered according to the characteristics using a SOM (Self-Organizing Map). As a result of the load analysis, it was confirmed that the load characteristics of the ship could be explained by the operation mode of the ship.

• Journal of Korea Ship Safrty Technology Authority
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• s.22
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• pp.54-64
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• 2007

This study is about the size and the number of toilets in the passenger ships. National regulations and other countries regulations were searched and analyzed. The toilets in the passenger ship, that are engaged in Busan City, Inchen City and Mokpo City were also searched and these present situation of the toilets were used with basic data of this study. Finally, we give a suggestion on the size and the number of toilets in the passenger ship.