• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.6
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• pp.760-767
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• 2014

An experimental study is carried out to investigate the effect of jet stream in the gab of rectangular cylinders with different length in a parallel arrangement by using PIV method in a circulating water channel. The height(h) of the rectangular cylinder and the gap between the cylinder is 10mm, and the width(B) which is 300mm. The length of the model for flow direction was applied to 30mm, 60mm, 90mm & 120mm, The aspect ratio of a model on the basis of height(H=30mm) is 1, 2, 3 and 4. Reynolds number $Re=1.4{\times}10^4$, $Re=2.0{\times}10^4$, $Re=2.9{\times}10^4$ based on the height(H) of model for the distance of tidal distributions as of water depth have been applied during the whole experiments. The measurement area was set to 5H rear of the cylinder. As a result, Vortex size in the wake area were increased as velocity increased. and high aspect ratio increased through-flow velocity component in the near wake. Velocity deficit increased highly after near-wake area and low aspect ratio.

• Journal of the Korea Institute of Construction Safety
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• v.2 no.1
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• pp.36-44
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• 2019

$21^{st}$ century is digitally civilized era. Technologies such as AI, Iot, Big Data, Mobile and etc makes this era digitally advanced. These advancement of the technology greatly impacted detection range of the radar. Human's eye sight can see about 20Km and hear 20 ~ 20000 Hz. These limitations can be overcome using radar. This radar technology is used in military, aircraft, ship, vehicle and etc. to replace human eye. However, radar technology is capable of making False Alarm Rate. This document will propose the fix of these problems. Radar's distortion includes beam refraction, diffraction and reflection. These inaccurate data result in deterioration of human judgements and my cause various casualties and damages. Radar goes through annual testing to test how many false alarm is being produced. Normal radar usually makes 10 to 20 False alarms. In emergency situation, if operator were to follow this false alarm, this might result in following false object or take 12 more seconds to follow the right object. This problem can be overcome by using different radar data from different places and angles. This helps reduces False Alarm rate and track the object twice as fast.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.810-819
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• 2017

The purpose of this study is to evaluate port use and the distribution of risk factors in 15 major ports in Korea, delineating the risk of each port after classifying the ports into four risk groups based on estimated risks. The placement of response vessels is then analyzed accordingly. Based on the results, danger was estimated to be especially high in ports where large-scale petrochemical facilities are located, such as Yeosu Gwangyang ports (1.85), Ulsan port (1.33) and Daesan port (1.25). The ports showing the next highest degree of danger were Pusan (0.95) and Incheon (0.83), which have significant vessel traffic, followed by Mokpo (0.71) and Jeju (0.49), which expanded their port facilities recently and saw an increase in large vessel traffic. Next is Masan (0.44), for which many fishing permits in the vicinity. When the relative ratios of each port were graded based on the Yeosu Gwangyang Ports, which showed the highest risk values, and risk groups were classified into four levels, the highest risk groups were Yeosu Gwangyang, Ulsan, Daesan and Pusan, with Incheon, Mokpo, Jeju, and Masan following. Pyeongtaek Dangjin, Pohang, Gunsan, and Donghae Mukho were in the mid-range danger group, and the low risk groups were Samcheonpo, Okgye, and Changsungpo. Among these, all response vessel placement ports specified by current law were above the mid-range risk groups. However, we can see that ports newly included in mid-range risk group, such as Mokpo, Jeju, and Donghae Mukho, were excluded from the pollution response vessel placement system. Therefore, to prepare for marine pollution accidents these three ports should be designated as additional response vessel placement ports.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.18-26
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• 2019

The Maritime Labour Convention, 2006, (MLC) aimed to ensure decent working conditions for seafarers and entered into force on August 20, 2013. It was considered as the fourth pillar in the maritime sector. This paper evaluates how the MLC has been implemented in the field and what issues were addressed in the shipping industry. To achieve this, statistical analysis was conducted using inspection data of Port State Control (PSC) carried out by the Paris MOU and the Tokyo MOU during 2010-2012 and 2014-2016 for deficiencies under the MLC and International Labour Organization (ILO) No. 147 Convention. This study compared pre-2013 and post-2013 deficiency data according to ship's age, size (gross tonnage) and type. The results showed that, although the deficiencies reported by the Tokyo MOU during 2014-2016 were nearly double those from 2010-2012, the deficiency share against total deficiencies for the Tokyo MOU remained two thirds of those for the Paris MOU. This study suggests that the Tokyo MOU should strengthen its inspection efforts on MLC and ILO should provide clear references, such as guidelines and a unified interpretation for national discretions under the MLC for the purpose of harmonized PSC inspections. Additionally, it would be desirable to consolidate the deficiency coding system for the MLC by deleting the codes for the ILO No. 147 Convention, which was incorporated into the MLC. It would also be beneficial to add new deficiency codes for social security, including seafarers' leave and repatriation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.5
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• pp.527-534
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• 2019

Several types of mathematical analysis methods are used for port waterway risk assessment based on marine traffic volume. In Korea, a marine traffic congestion model that standardizes the size of the vessels passing through the port waterway is applied to evaluate the risk of the waterway. For example, when marine traffic congestion is high, risk situations such as collisions are likely to occur. However, a scientific review is required to determine if there is a correlation between high density of maritime traffic and a high risk of waterway incidents. In this study, IWRAP Mk2(IALA official recommendation evaluation model) and a marine traffic congestion model were used to analyze the correlation between port waterway risk and marine traffic congestion in the same area. As a result, the linear function of R2 was calculated as 0.943 and it was determined to be significant. The Pearson correlation coefficient was calculated as 0.971, indicating a strong positive correlation. It was confirmed that the port waterway risk and the marine traffic congestion have a strong correlation due to the influence of the common input variables of each model. It is expected that these results will be used in the development of advanced models for the prediction of port waterway risk assessment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.787-797
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• 2020

The marine officer plays a pivotal role in the shipping organization as a professional who performs a complex and diverse function. On the sea, unlike land duty, the possibility of turnover increases due to characteristics such as living in isolated spaces, continuous shift work during a set sailing period, high intensity work tension, stress, and social isolation. In this study, the impact of the organization's civic actions on the intention of turnover as a mediator of organizational immersion was divided into three groups of large companies, small and medium-sized enterprises, and public enterprises to check the differences between each category in a structural manner. Analysis showed that there were statistically significant differences between the groups in loyalty and turnover intention when the sub-factors of organizational commitment and organizational citizen behavior of the marine officer, and the size of turnover intention were included. Organization citizen behavior did not directly affect turnover intention, but when indirect effects were included, there was an effect through loyalty, and relationship-oriented organizational citizen behavior negatively affected turnover intention through loyalty. Excluding public enterprises, the non-standardization path coefficients were -0.229±0.117 and -0.319±0.068, respectively, showing a statistically significant effect in large companies and SMEs. These results indicate that in order to lower the employee turnover intention in large corporations and small and medium-sized shipping companies, it is necessary to consider not only organizational citizen behavior but also measures to increase organizational commitment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.820-829
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• 2020

Because ships have limited support from land, it is necessary to equip them with automatic external defibrillators (AEDs) in preparation for the incidences of cardiac arrest patients and to properly place and manage AEDs. The seafarer must have the ability to use the AEDs. This is a study to identify the placement and management of AEDs in order to increase the utilization of AEDs in ships, analyze the ability of seafarers to use AEDs and their intention to use it, and suggest improvement plans. The study was conducted from September 9, 2019, to February 20, 2020, and a total of 244 ships and 244 seafarers were surveyed. The data were analyzed by the frequency, percentage, and chi-square test using SPSS WIN 23.0 program. As a result, most of the ships with one AED number were identified, and some ships with insufficient AED placement and management were also identified. A total of 142 seafarers (58.2 %) had experience in participating in AED education; 136 seafarers (55.7 %) had intention to use AEDs; and the most barrier factor was "I don't know how to use" (63.0 %). The intention to use AEDs was high among seafarers in the position of the captain, navigator, and deck department personnel, and when they had an experience in AED training and the training period was less than six months, they were active in using AEDs. In addition, efforts to raise an awareness and education of AEDs are required for occupational groups other than navigators who are not willing to use AEDs in ships, and it is necessary to review appropriate retraining cycles through an evaluation of the seafarer's ability to use AEDs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.587-596
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• 2021

Naval battleships have systems to perform special purposes, such as the Command and Fire Control System (CFCS). Some of the this equipment should be equipped with an Uninterruptible Power System (UPS ) to ensure operational continuity and the backup of important data, even during unexpected power outages caused by problems with the ship's power generator. Heavy combat losses can occur if the equipment cannot satisfy the function. Therefore, it is important to design a stable UPS. The battery and Battery Management System (BMS) are two of the most important factors for designing a stable UPS. A power outage will be encountered if the battery and BMS are not stable. The customer will be exposed to abnormal situations, loss of important tactical data, and inability to operate some of the CFCS. As a result, an enhanced safety system should be designed. Thus, this study implemented and verified the improved system in terms of three methods, such as comparative analysis of the batteries, improvement about leakage current of the circuit, and tests of the aggressive environmental resistance to improve the UPS for CFCS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.22-28
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• 2021

This is a basic study on the development of deep learning-based algorithms to detect smoke before the smoke detector operates in the event of a ship fire, analyze and utilize the detected data, and support fire suppression and evacuation activities by predicting the spread of smoke before it spreads to remote areas. Proposed algorithms were reviewed in accordance with the following procedures. As a first step, smoke images obtained through fire simulation were applied to the YOLO (You Only Look Once) model, which is a deep learning-based object detection algorithm. The mean average precision (mAP) of the trained YOLO model was measured to be 98.71%, and smoke was detected at a processing speed of 9 frames per second (FPS). The second step was to estimate the spread of smoke using the coordinates of the boundary box, from which was utilized to extract the smoke geometry from YOLO. This smoke geometry was then applied to the time series prediction algorithm, long short-term memory (LSTM). As a result, smoke spread data obtained from the coordinates of the boundary box between the estimated fire occurrence and 30 s were entered into the LSTM learning model to predict smoke spread data from 31 s to 90 s in the smoke image of a fast fire obtained from fire simulation. The average square root error between the estimated spread of smoke and its predicted value was 2.74.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.