• Title/Summary/Keyword: maritime big-data

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Machine Learning Methodology for Management of Shipbuilding Master Data

  • Jeong, Ju Hyeon;Woo, Jong Hun;Park, JungGoo
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.428-439
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    • 2020
  • The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

A Study on the Effective VTS Communications Analysis by the Method of VCDF in Busan Port (VCDF 방식을 통한 효율적인 VTS 통신 데이터 분석에 관한 연구 - 부산항을 대상으로 -)

  • Kim, Bong-Hyun;Park, Young-Soo
    • 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.

Generative Adversarial Network Model for Generating Yard Stowage Situation in Container Terminal (컨테이너 터미널의 야드 장치 상태 생성을 위한 생성적 적대 신경망 모형)

  • Jae-Young Shin;Yeong-Il Kim;Hyun-Jun Cho
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.383-384
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    • 2022
  • Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

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USN's Efforts to Rebuild its Combat Power in an Era of Great Power Competition (강대국 간의 경쟁시대와 미 해군의 증강 노력)

  • Jung, Ho-Sub
    • Strategy21
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    • s.44
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    • pp.5-27
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    • 2018
  • The purpose of this paper is to look at USN's efforts to rebuild its combat power in the face of a reemergence of great powers competition, and to propose some recommendations for the ROKN. In addition to the plan to augment its fleet towards a 355-ships capacity, the USN is pursuing to improve exponentially combat lethality(quality) of its existing fleet by means of innovative science and technology. In other words, the USN is putting its utmost efforts to improve readiness of current forces, to modernize maintenance facilities such as naval shipyards, and simultaneously to invest in innovative weapons system R&D for the future. After all, the USN seems to pursue innovations in advanced military Science & Technology as the best way to ensure continued supremacy in the coming strategic competition between great powers. However, it is to be seen whether the USN can smoothly continue these efforts to rebuild combat strength vis-a-vis its new competition peers, namely China and Russian navy, due to the stringent fiscal constraints, originating, among others, from the 2011 Budget Control Act effective yet. Then, it seems to be China's unilateral and assertive behaviors to expand its maritime jurisdiction in the South China Sea that drives the USN's rebuild-up efforts of the future. Now, some changes began to be perceived in the basic framework of the hitherto regional maritime security, in the name of declining sea control of the USN as well as withering maritime order based on international law and norms. However, the ROK-US alliance system is the most excellent security mechanism upon which the ROK, as a trading power, depends for its survival and prosperity. In addition, as denuclearization of North Korea seems to take significant time and efforts to accomplish in the years to come, nuclear umbrella and extended deterrence by the US is still noting but indispensible for the security of the ROK. In this connection, the naval cooperation between ROKN and USN should be seen and strengthened as the most important deterrents to North Korean nuclear and missile threats, as well as to potential maritime provocation by neighboring countries. Based on these observations, this paper argues that the ROK Navy should try to expand its own deterrent capability by pursuing selective technological innovation in order to prevent this country's destiny from being dictated by other powers. In doing so, however, it may be too risky for the ROK to pursue the emerging, disruptive innovative technologies such as rail gun, hypersonic weapon... etc., due to enormous budget, time, and very thin chance of success. This paper recommends, therefore, to carefully select and extensively invest on the most cost-effective technological innovations, suitable in the operational environments of the ROK. In particular, this paper stresses the following six areas as most potential naval innovations for the ROK Navy: long range precision strike; air and missile defense at sea; ASW with various unmanned maritime system (UMS) such as USV, UUV based on advanced hydraulic acoustic sensor (Sonar) technology; network; digitalization for the use of AI and big data; and nuclear-powered attack submarines as a strategic deterrent.

A Study on the Development of ESG Indicators for Sustainable Smart Ports (지속가능한 스마트 항만을 위한 ESG 지표 개발에 관한 연구)

  • Jae-Hoon Lee;Myung-Hee Chang
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.296-297
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    • 2022
  • A smart port refers to a port built based on digital technologies such as IoT, big data, AI, and block chain, and refers to a port that minimizes waste of time, space and resources as the only means of survival of the port. Sustainability refers to 'environmental, economic, and social characteristics that enable people to continue to use the environment, ecosystem, or publicly used resources'. It contains the meaning of 'future sustainability' that can be maintained in the future. In the face of the 4th industrial revolution, interest and realization of smart port construction and sustainability are actively progressing around the world. In this study, core indicators of the ESG (Enviornment, Social, Governance) area, which are key elements of sustainable smart ports, were developed,

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A Study on Factors Influencing Intention to Use Big Data in Shipping and Port Company (해운항만기업의 빅데이터 사용의도에 영향을 미치는 요인에 관한 연구)

  • Lee, Joon-Peel;Chang, Myung-Hee
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2017.11a
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    • pp.136-137
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    • 2017
  • 4차 산업혁명시대가 도래함에 따라 해운항만기업에서 4차 산업혁명을 주도하는 ICT를 활용하기 위한 노력이 다양하게 전개되고 있다. 특히 해운항만물류분야에서는 IoT센서가 만들어내는 다양한 데이터를 분석하여 도출된 인사이트를 기반으로 업무효율성을 높이고자 빅데이터분석 기법을 적용하기 시작하고 있다. 본 연구에서는 해운항만기업들 중 빅데이터분석을 도입해서 활용하고 있거나, 빅데이터를 업무에 활용하기 위해 도입의도를 가지고 있는 기업의 종사자들을 대상으로 어떤 요인들이 빅데이터 사용의도를 높여주는 지에 대하여 실증분석.

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Big data/AI-based smart maritime logistics chatbot service (빅데이터/AI 기반 스마트 해상물류 챗봇 서비스)

  • Park, Sang-Jun;Lee, Yoon-Pyo;Jeong, Won-Seok;Choi, Yong-Tae;Hong, Jin-Won
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.1349-1352
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    • 2021
  • 본 학술지는 기존의 공공 행정서비스에서의 복잡한 업무처리를 간단하게 처리할 수 있는 FAQ 형태의 챗봇서비스를 제안한다. 본 논문이 제안하는 주요 특징은 다음과 같다. 버튼, 대화, STT(Speech To Text)를 통한 사용자 기반 UI/UX를 제공한다. 딥러닝을 통한 Synonym, Typo를 검출하여 가장 높은 정확도의 Entity로 변환해준다. 이를 통해, 사용자는 해상물류 서비스를 이용하는데 있어 부담감을 해소하고 편리함을 얻을 수 있다.

Research on the Prediction of Maritime Traffic Congestion based on Big Data (빅데이터 기반 선박 교통 혼잡도 예측에 관한 연구)

  • Jae-Yong Oh;Hye-Jin Kim
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2023.05a
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    • pp.15-16
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    • 2023
  • 해상교통관제 구역은 항만 시설을 사용하기 위한 입·출항 선박, 연안 해역을 이동하는 선박 등이 서로 복잡하게 운항하는 교통 패턴을 가지고 있다. 이를 안전하고 효과적으로 관리하기 위해 해상교통관제센터(VTS)에서는 선박을 실시간 모니터링하며 관제 업무를 수행하고 있지만, 교통 혼잡 상황에서는 업무 로드의 증가로 인해 관제 공백이 발생하기도 한다. 이에 교통 혼잡도 및 혼잡 구역을 예측한다면보다 효율적인 관제가 가능하지만 현재는 관제사의 경험에 전적으로 의존하고 있는 실정이다. 본 논문에서는 VTS 관점에서의 교통 혼잡을 정의하고, 과거 항적 데이터를 이용하여 항내 선박 교통 혼잡도 및 혼잡 구역을 예측하는 방법을 제안하였다. 또한, 실해역 데이터(대산항 VTS)를 적용하여 제안된 기술이 관제지원 도구로서 활용될 수 있는지 검토하였다.

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Requirements of Consistency Criteria for Cloud Computing Environments (클라우드 환경에서 응용에 따른 일관성 기준의 요구 사항)

  • Kim, Chi-Yeon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.732-735
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    • 2011
  • Cloud computing is a new paradigm that adopts a pay-as-you-go business model. So, clients can ues the various resources, although they have not own the resources. Already, three big players of IT industry, namely Amazon, Google and Microsoft, develop the many applications for cloud computing. In this paper, we describe the data consistency requirements for cloud computing. Data characteristics of cloud computing is replicated, distributed and large-scaled. And consistency and availability of data cannot be satisfied simultaneously. In this paper, we categorized the applications of cloud computing, and describe requirements of consistency criteria for applications. With this result, we can make the base of consistency criteria that can be adapted for cloud computing, in the near future.

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A study of an Architecture of Digital Twin Ship with Mixed Reality

  • Lee, Eun-Joo;Kim, Geo-Hwa;Jang, Hwa-Sup
    • Journal of Navigation and Port Research
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    • v.46 no.5
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    • pp.458-470
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    • 2022
  • As the 4th industrial revolution progresses, the application of several cutting-edge technologies such as the Internet of Things, big data, and mixed reality (MR) in relation to autonomous ships is being considered in the maritime logistics field. The aim of this study was to apply the concept of a digital twin model based on Human Machine Interaction (HMI) including a digital twin model and the role of an operator to a ship. The role of the digital twin is divided into information provision, support, decision, and implementation. The role of the operator is divided into operation, decision-making, supervision, and standby. The system constituting the ship was investigated. The digital twin system that could be applied to the ship was also investigated. The cloud-based digital twin system architecture that could apply investigated applications was divided into ship data collection (part 1), cloud system (part 2), analysis system/ application (part 3), and MR/mobile system (part 4). A Mixed Reality device HoloLens was used as an HMI equipment to perform a simulation test of a digital twin system of an 8 m battery-based electric propulsion ship.