• Title/Summary/Keyword: 컨테이너 항만 분류

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A Study on Operation Efficiency of Container Port by Comparison of Similar Ports (동종 항만군 분류를 통한 컨테이너항만의 운영효율화 방안에 관한 연구)

  • 정태원;곽규석
    • Journal of Korean Society of Transportation
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    • v.19 no.1
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    • pp.7-16
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    • 2001
  • The Principle objective of this paper is to introduce a systematic approach to identifying similar container ports in Asia. For this, it analyses data on port facilities, port facility availability, port service level total container throughput, and economic index, by using Multidimentional Scaling (MDS) method. Based on the analysis it identifies five groupings of similar container ports in Asia within which Port comparison can be justifiably made, evaluates a present position of five groupings on the basis of factors used to compare container ports in Asia ; and finally proposes policy implications for operation efficiency of Pusan container port in comparison with Kaohsiung Port. The major implication is that both the Kaosuing and the Pusan port have to strengthen port facility to attract more traffic, and particularly, Pusan Port has to reinforce the number of berth, total length of berth. and yard areas.

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A Study on the Classification of Korean Container Ports (우리나라 컨테이너항만 분류에 관한 연구)

  • Kim, Byoung-Hong;Son, Hyun-Kyu;Nam, Ki-Chan;Choi, Hoon-Do
    • Journal of Navigation and Port Research
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    • v.34 no.8
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    • pp.641-647
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    • 2010
  • Container port development in Korea seems to be based on the policy of balanced regional development rather than demand and supply theory. The problem of overcapacity and low utilization faced by several ports such as Kwangyang, Ulsan New Port and Phohang Youngil New Port can back up this. Furthermore as some ports are located closely sharing the same domestic hinterland the revitalization of the ports is not easy resulting in wasting resources with both regional and national aspect. This study, therefore, aims at providing an empirical results for the container port classification of the 5 ports such as Busan, Kwangyang, Incheon, Pyeongtaek and Ulsan. For this several time series data for the ports such as transshipment containers, import and export containers, origin and destination countries, and local origin and destination are analysed. Based on the results of the analysis the 5 container ports are classified together with their practical roles, and the functional overlap of the port including Phohang was analysed.

컨테이너터미널의 에너지 소비 패턴 분석

  • Son, Ho-Seong;Choe, Yong-Seok
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2009.10a
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    • pp.7-8
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    • 2009
  • 컨테이너터미널에서 사용되는 하역시스템은 유류 및 전기 에너지를 주로 소모하는 특성을 가지고 있어 컨테이너의 작업량에 따라 에너지 소비가 증가하게 된다. 따라서 본 연구에서는 컨테이너터미널 운영사에서 하역작업시 장비별로 소비하는 에너지소비 패턴분석을 하고자 한다. 에너지소비 패턴을 분석하기 위해 하역장비별 에너지 소모량과 영역별 컨테이너 처리량을 상호비교 분석하였다. 그리고 컨테이너터미널에서 소비하는 에너지의 월별 소비패턴에서 정상적인 에너지 소비패턴과 비정상적인 에너지 소비패턴을 분류하는 방법을 도출하고 정상적인 에너지소비 패턴을 유도하기 위한 방안을 제시하고자 한다.

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A Study on Deep Learning Model for Container Load Status Monitoring (컨테이너 적재 상태 모니터링을 위한 딥러닝 모델 연구)

  • Oh, Seyeong;Jeong, Junho;Choi, Bulim;Yeon, Jeong Hum;Seo, Yonguk;Kim, Sangwoo;Youn, Joosang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.320-321
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    • 2022
  • 부두 내 컨테이너를 적재하는 과정에서 정렬 상태가 부정확한 경우 강풍으로 인한 안전사고가 발생할 가능성이 있다. 본 논문에서는 컨테이너 안전사고를 예방하기 위한 딥러닝 기반의 컨테이너 정렬 상태 분류 알고리즘을 제안한다. 제안하는 알고리즘은 정렬을 분류하는 기준을 제시하고 YOLO 기반의 모델을 구현했다. 추론 속도, 검출 정확도, 분류 정확도를 기준으로 각 모델의 성능을 평가했으며 성능 결과는 YOLOv4모델이 YOLOv3모델에 비해서 추론 속도는 느리지만, 검출 정확도와 분류 정확도는 높음을 보인다.

Shipping Container Load State and Accident Risk Detection Techniques Based Deep Learning (딥러닝 기반 컨테이너 적재 정렬 상태 및 사고 위험도 검출 기법)

  • Yeon, Jeong Hum;Seo, Yong Uk;Kim, Sang Woo;Oh, Se Yeong;Jeong, Jun Ho;Park, Jin Hyo;Kim, Sung-Hee;Youn, Joosang
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.11
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    • pp.411-418
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    • 2022
  • Incorrectly loaded containers can easily knock down by strong winds. Container collapse accidents can lead to material damage and paralysis of the port system. In this paper, We propose a deep learning-based container loading state and accident risk detection technique. Using Darknet-based YOLO, the container load status identifies in real-time through corner casting on the top and bottom of the container, and the risk of accidents notifies the manager. We present criteria for classifying container alignment states and select efficient learning algorithms based on inference speed, classification accuracy, detection accuracy, and FPS in real embedded devices in the same environment. The study found that YOLOv4 had a weaker inference speed and performance of FPS than YOLOv3, but showed strong performance in classification accuracy and detection accuracy.

A Study on the Direction of the Introduction of Korean Autonomous Co-operation Driving Vehicle (한국형 자율협력주행차량의 도입 방향성에 관한 연구)

  • Lee, Seung-Pil;Kim, Hwan-Seong
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2020.11a
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    • pp.161-162
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    • 2020
  • Major advanced ports around the world are preparing for environmental regulations such as increased efficiency of ports and low emission of pollutants in ports by utilizing fourth industrial technologies and ICT technologies such as AI, big data, self-driving cars and connected cars. It is also investing in developing fully unmanned terminals to solve the problem of workforce reduction caused by avoidance of 3D industries. However, the introduction of advanced technology is being delayed in domestic ports, which has led to a drop in port efficiency. In addition, port safety accidents have also occurred frequently, seriously affecting port marketing. Thus, the characteristics and types of each container terminal in Korea were analyzed and the factors for introducing autonomous cooperative driving were classified into five section factors and 15 division factors. Hierarchically classified factors will be surveyed on workers working in shipping lines, port construction, container terminals and related ministries.

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Research on Artificial Intelligence Based Shipping Container Loading Safety Management System (인공지능 기반 컨테이너 적재 안전관리 시스템 연구)

  • Kim Sang Woo;Oh Se Yeong;Seo Yong Uk;Yeon Jeong Hum;Cho Hee Jeong;Youn Joosang
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.9
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    • pp.273-282
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    • 2023
  • Recently, various technologies such as logistics automation and port operations automation with ICT technology are being developed to build smart ports. However, there is a lack of technology development for port safety and safety accident prevention. This paper proposes an AI-based shipping container loading safety management system for the prevention of safety accidents at container loading fields in ports. The system consists of an AI-based shipping container safety accident risk classification and storage function and a real-time safety accident monitoring function. The system monitors the accident risk at the site in real-time and can prevent container collapse accidents. The proposed system is developed as a prototype, and the system is ecaluated by direct application in a port.

A Cause and Effect Analysis on the Application of Remodeling Technology of Container Terminals - the Case of Gwangyang Port - (컨테이너터미널 리모델링 기술적용 인과분석 - 광양항 사례 -)

  • Choi, Yong-Seok
    • Journal of Korea Port Economic Association
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    • v.26 no.1
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    • pp.105-130
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    • 2010
  • Container terminals in Gwangyang Port are facing in domestically and internationally a lot of changes including opening of Busan New Port and China ports. Compared to new ports, container terminals in Gwangyang Port possess old equipment and facilities. Therefore, in order for Gwangyang Port to maintain its service level and remain competitive, it needs to undergo remodeling to enhance productivity economically. Remodeling activities should be implemented on a continual basis by developing and applying new technologies such as those for gate system, yard system, berth system. In order to review the alternative, we performed questionnaire survey and expert interview. From the results of analysis, we suggested remodeling technology alternatives, priority of remodeling and improvement effect by remodeling introduction stage.

A Study on Improving Performance of Object Detection Model using K-means based Anchor Box Method in Edge Computing Enviroment (엣지 컴퓨팅 환경에서 K-means 기반 앵커박스 선정 기법을 활용한 물체 인식 모델 성능 개선 연구)

  • Seyeong Oh;Junho Jeong;Joosang Youn
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.539-540
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    • 2023
  • 최근 물체 인식 모델의 성능을 개선하기 위한 다양한 연구가 진행 중이다. 본 논문에서는 K-means 기반 앵커박스 선정 기법을 적용한 새로운 물체 인식 모델 성능 개선 방법을 제안한다. 제안된 방법은 항만 내 설치된 컨테이너 사고를 예방하기 위한 컨테이너 사고위험도 분류 모델에 적용하여 성능 평가를 하였다. 특히, 컨테이너 사고위험도 분류 모델은 작은 물체를 인식해야 하며 이런 환경에서는 기존 물체 인식 모델 성능이 낮게 나타난다. 본 논문에서는 제안한 K-means 기반 앵커박스 선정 기법을 적용하여 물체 인식 모델 성능이 개선됨을 확인하였디.

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Exploratory Study on Enhancing Cyber Security for Busan Port Container Terminals (부산항 컨테이너 터미널 사이버 보안 강화를 위한 탐색적 연구)

  • Do-Yeon Ha;Yul-Seong Kim
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.437-447
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    • 2023
  • By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.