• Journal of the Korean Institute of Navigation
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• v.11 no.2
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• pp.1-31
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• 1987

Nowadays, the transportation of almost all cargoes depends on sea routes in international trade. In the transaction of trade, cargo transportation must be completed on the base of two contrary objectives, one of which is to protect the vessel, cargoes and crew aborad her safely through every step of the transportation and the other is to pursue profits from the transaction of the trade. In spite of the great development of the modern techniques in shipbuilding today, many sea disaters of big merchant vessels have been occurring successively in winter seasons every year on the sea routes of the North Pacific Ocean. Whenever the accident of losing a vessel in rough sea occurred , many experts of the country to which the vessel belonged had tried to take out the reason of the missing without manifesting the exact cause of the unhappy occurrence. In this paper, we calculated ocean wave status along the route of the North Pacific Ocean theoretically concluded by us as optimum on the basis of weather and sea conditions. In the calculation, we used ITTC wave spectrum formula and meteorological data of "Winds '||'&'||' Waves of the north Pacific Ocean" edited by Ship Research Institute of Japan on the basic data assembled by World Meterological Organization through past 10 years. We selected three sample vessels of most common size in the North Pacific Ocean Routes, a container, a log carrier and a bulk carrier and applied tree sample vessels to the calculated sea conditions for getting the rolling angles of the vessels and stress exerting on the hulls. Examining the calculated results, we concluded as follows; 1. Under the condition of these status7 by beaufort scale, "heave to" maneuvering is the best and safest way to steer every vessel. 2. The most dangerous part of sea area along the west bound optimum route of the North Pacific Ocean in winter season, is the southern sea area of the Kamchatka peninsula.a peninsula.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.54-55
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• 2020

In 4th Industrial Revolution, technologies such as artificial intelligence, Internet of Things, and Big data are closely related to the maritime industry, which led to the birth of autonomous vessels. Due to the technical characteristics of the current vessel, the speed cannot be suddenly lowered, so complex communication such as the help of a tug boat, boarding of a pilot, and control of the vessel at the onshore control center is required to berth at the port. In this study, clustering analysis was used to resolve how to establish control criteria for vessels to enter port when autonomous vessels are operating. K-Means clustering was used to quantitatively stage the arrival pattern based on the accumulated AIS(Automatic Identification System) data of the incoming vessel, and the arrival phase using SOG(Speed over Ground), COG(Course over Ground), and ROT(Rate of Turn) Was divided into six phase.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.726-734
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• 2019

The current maritime industry is expected to have a significant impact on the role of maritime-related technologies and systems, especially seafarers, in the rapidly changing Fourth Industrial Revolution. The Maritime Autonomous Surface Ship (MASS) aims to reduce the number of safety accidents and improve seafarers' working environment. With regard to MASS, the International Maritime Organization has been trying to minimize unexpected impact in the maritime education and training sector by establishing international conventions such as the Standards of Training, Certification and Watchkeeping for Seafarers. However, domestic designated educational institutions have not yet established an education and training scheme to develop seafarers who will be on board for MASS. Therefore, this paper reviews the technology of MASS, analyzes the changes in education and training in order to upgrade the qualifications, and suggests the competencies of smart seafarers equipped with the integrated management ability required for Artificial Intelligence, Big Data, Cybersecurity, and the Digital System Revolution through education and training. In addition, this study provides basic information for the education and training of seafarers who are optimized for the rapidly changing technological environment.

• Special Issue of the Society of Naval Architects of Korea
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• 2013.12a
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• pp.35-41
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• 2013

Nowadays, automated modeling system for steel margin based on interactive user interface has been developed and applied to the production design stage. The system could increase design efficiency and minimize human error owing to recent CAD technique. However, there has been no approach to the pre-nesting design stage at all in early modeling process especially where ship model should be handled at more than two design stages using AVEVA Marine. A designer of the design stage needs artificial intelligence system beyond modeling automation when 3D model must be prepared in early modeling process using AVEVA Marine because they have focused on 2D nesting traditionally. In addition, they have a hard time figuring out the model prepared in previous design stage and modifying the model for steel purchase size in early modeling process. In this paper, artificial intelligence modeling system for automated application of steel margin in early modeling process using AVEVA Marine is developed in order to apply to the pre-nesting design stage that can detect effective segments before a calculation to find if a segment locates near block butt boundaries by filtering noise segments among lines, curves and surface intersections based on IT big data analysis.

• Journal of Environmental Science International
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• v.30 no.10
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• pp.789-802
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• 2021

This study analyzed the characteristics of high PM_2.5 episodes that meets the concentration criteria of Emergency Reduction Measures Plan (ERMP) in Busan during the 2015-2020, and compared with those in Seoul. As a first step, the CAPSS-2017 emission data was employed to analyze the emission differences between Busan and Seoul, and pointed out that Busan emission included the dominance of ship emissions (37.7%) among total PM_2.5 city emissions, whereas fugitive PM_2.5 emission was the highest in Seoul. These emission characteristics are indicating that the controlling action plan should be uniquely applied to cope with ERMP in each region. We selected extremely high PM_2.5 episode days that meet the criteria of ERMP levels. In Busan, Ulsan, and Gyeongnam region, 15, 16, and 8 days of extremely high PM_2.5 cases were found, respectively, whereas Seoul showed approximately doubling of occurrences with 37 cases. However, the occurrences in summer season indicated big differences between two cities: the proportion of summer-season occurrence was 13-25% in Busan, whereas no single case have occurred in Seoul. This is suggesting the needs of comprehensive summer emission reduction plan with focusing on sulfur reduction to effectively cope with the ERMP levels in summer in the southeastern region, including Busan.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.799-806
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• 2018

In this paper, we analyzed the communication distances in the flat and spherical earth model using the main specifications of the wireless communication device under development to be installed in the unmanned surface vehicle(USV). We installed the wireless communication device on the test ship and the actual communication test was performed in the South Sea of Korea, it compared the experimental result with the simulated results. If the installation altitude of the transmitting and receiving antennas is low, there is not the big difference between the two models. However, when the altitude of one of the two antennas is high, the spherical earth model has similar results to the experimental data. As the altitude of the antenna installation increases, fading occurs in a certain section. We expect that this fading can be overcome through antenna technologies such as space diversity.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.4
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• pp.311-318
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• 2016

The VTS concept was located as a principal methods of maritime safety administration in world's major harbors and expected to become the pivotal role for the future of the maritime and harbor society with e-Navigation epoch. If recent limelight concept of big-data has been included in aspect of information gathering and analysis with various studies, it's required advanced studies to improve the information analysis capability and application range of the data that can be mining by the VTS. In this study, contrast to other studies that aimed quantitative analysis as communication number, it can be mining the time information and each of the communication VTS for the target vessel, including qualitative analysis, such as the purpose or the type of communication. This comparison across multiple items of the collected information, and presenting the VTS data mining model (VCDF) that can be analyzed for the purpose of analyzing way, type and number of communication by ship's type, also number of violations through VTS communication. First, In Busan port case, it shows frequently information service and shows frequently communicating with particular types of vessels. Second, Passive VTS carried out notwithstanding many kinds of traffic violations due to communication congestion. This arranged information can be used as data for the analysis, as possible the level of traffic for VTSO situational awareness, which pointed to the 'workloads' in 'IALA Guideline' and could be used as a database for future research of e-Navigation.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.78-80
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• 2021

This study is based on Degree of Recognition and AHP surveys for experts, this study investigates changes in the demand of seafarers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships(MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in seafarers' skills. It also analyzes and proposes a plan for cultivating seafarers accordingly. As a result of Degree of Recognition and AHP analysis, it is analyzed that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but jobs such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore based control.By evaluating the importance of change factors in the duties of seafarers in Maritime Autonomous Surface Ships, this study provides information on seafarers educational institutions response strategies for nurturing seafarers and prioritization of resource allocation, etc. The importance of factors was compared and evaluated to suggest changes in the duties of seafarers and methods of nurturing seafarers according to the introduction of Maritime Autonomous Surface Ships.It is expected that this study is meaningful as it systematically derived the duties and competency factors of seafarers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.