• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.931-941
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• 2020

There is a growing interest this paper for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This study was conducted to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry (2D) was open for an optimization. Therefore, the first objective was to identify the aerodynamic performance of such curvy twin sails. The secondary objective was to estimate the effect of the sail's spacing and shapes. A viscous Navier-Stokes flow solver was used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results indicated that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail was an important parameter. The spacing is 0.035 L, 0.07 L, and 0.14 L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21 L, 0.28 L, and 0.35 L. Significantly, the spacing 0.28 L shows the maximum high pressure at the lower area and the small low pressure area at leading edges. Therefore, the highest lift was generated.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.491-500
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• 2022

It has been noted that an accurate estimation of wind loads on offshore structures such as an FLNG (Liquefied Natural Gas Floating P roduction Storage Offloading Units, LNG FPSOs) with a large topside plays an important role in the safety design of hull and mooring system. Therefore, the present study aims to develop a computational model for estimating the wind load acting on an FLNG. In particular, it is the sequel to the previous research by the author. The numerical computation model in the present study was modified based on the previous research. Numerical analysis for estimating wind loads was performed in two conditions for an interval of wind direction (α), 15° over the range of 0° to 360°. One condition is uniform wind speed and the other is the NPD model reflecting the wind speed profile. At first, the effect of sand-grain roughness on the speed profile of the NPD model was studied. Based on the developed NPD model, mesh convergence tests were carried out for 3 wind headings, i.e. head, quartering, and beam. Finally, wind loads on 6-degrees of freedom were numerically estimated and compared by two boundary conditions, uniform speed, and the NPD model. In the present study, a commercial RANS-based viscous solver, STAR-CCM+ (ver. 17.02) was adopted. In summary, wind loads in surge and yaw from the wind speed profile boundary condition were increased by 20.35% and 34.27% at most. Particularly, the interval mean of sway (45° < α <135°, 225° < α < 315°) and roll (60° < α < 135°, 225° < α < 270°) increased by 15.60% and 10.89% against the uniform wind speed (10m/s) boundary condition.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.1023-1035
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• 2022

In the current situation where clearly the ship officer is avoiding boarding, the purpose of this study is to investigate the satisfaction of onboard training in shipping companies during the COVID-19 situation and to suggest plans to improve onboard training. Furthermore, by improving satisfaction, students of maritime university can improve their career awareness as a ship officer in the future. The survey was conducted with the cadets of Mokpo Maritime University after completion of onboard training in shipping companies. The questionnaire contains seven factors: education administration, education contents, officer, facility, education ef ect, education satisfaction and career awareness. The survey analysis results indicated that the satisfaction with education administration and education effect was relatively low, and the satisfaction differed by gender and vessel type. In addition, hypothesis verification revealed that the education contents did not have a positive effect on education satisfaction and career awareness. Furthermore, a great correlation existed between education satisfaction and career awareness. We suggested that education and promotion must be improved before onboard training. In addition, the officer must be educated on the method to teach cadets and establish a training plan such that the officer can systematically guide the cadets with an educator mindset.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1059-1066
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• 2021

In Korea, the importance of marine activities is great, and automatic weather observation facilities are operating on land to investigate abnormal weather phenomena caused by industrialization; however, the number of facilities at sea is insufficient. Marine survey ships are operated to establish marine safety information, but there are many places where marine survey ships are difficult to access and operating costs are high. Therefore, a small, unmanned vessel capable of marine surveys must be developed. The sail has a significant impact on the sailing performance, so much research has been conducted. In this study, the camber effect, which is a design variable of the twin curvy sail known to have higher aerodynamic performance than existing airfoil shapes, was investigated. Flow analysis results for five cases with different camber sizes show that the lift coefficient is highest when the camber size is 9%. Curvy twin sails had the highest lift coefficient at an angle of attack of 23° because of the interaction of the port and starboard sails. The port sail had the highest lift coef icient at an angle of attack of 20°, and the starboard sail had the lowest lift coef icient at an angle of attack of 15°. In addition, the curvy twin sail had a higher lift coefficient than NACA 0018 at all angles of attack.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1252-1258
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• 2022

The exhaust gas from the marine engines include a quantity of water vapor and particulate matter. The total particulate matter includes filterable particulate matter (FPM) and condensable particulate matter (CPM) that condense after releasing into the atmosphere. The portion of CPM is higher than that of FPM that is removable through the filter before discharging. An experimental setup for waste heat and water recovery and removal of CPM in the exhaust gas was tested using an industrial gas boiler in the laboratory. The water and CPM in the exhaust gas were removed through the first stage of cooling method and further removed through the second stage of absorption method. The efficiencies of water recovery were 73% after the first stage of cooling method and 90% after the second stage of absorption method. At the same time, the CPM was removed by 80-90% through the processes. The waste heat recovered could be used to process heat, and the water recovered could be used to process water in the ship. Furthermore, the CPM, which is a major source of the particulate matter but not subject to administrative regulation, could be removed effectively.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.71-80
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• 2024

In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.57-67
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• 2024

This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.