• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.331-336
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• 2004

In order to strengthen the competitiveness of port against calling for the huge vessel and reducing the shipping service time, the productivity of container terminal must be improved. This productivity variously results according to the kinds of productivity evaluation model, input elements like yard, equipment, employee, facility, etc,. But, it is discussed that the productivity is measured by partial productivity evaluation model or general input elements. Therefore, we measured for the productivity of the container terminal using the Developed the data Envelopment Analysis (DEA), which is developed in order to evaluate the relative efficiency of decision making units - it's difficult to clear cause and effect between input and output. We measured the whole productivity of container terminal in Busan according to decision of the correct input elements. And we investigated the change of the productivity measurement result according to input elements, presents more accurate productivity evaluation model in container terminal.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.353-359
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• 2007

Effective plan and operation managements can be established in advance if the traffic volume of container ship will be forecasted in the trend for container port's cargo volume to increase. At the viewpoint for marine traffic the number of incoming and outgoing container ship can be presumed in the long run and organised rational plan to deal the demand of marine traffic on the basis. Therefore, the paper estimated the future traffic volume of incoming and outgoing container ship for Busan, Gwangyang, and Incheon port on a forecasting data basis of container volume suggested in the national ports base plan. The trends of volume per ship on container were estimated with ARIMA models and seasonal index was computed. Thus the traffic volume of container ship in the future was estimated computing with volume per ship in 2011,2015, and 2020 respectively.

• Journal of Korea Port Economic Association
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• v.32 no.3
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• pp.47-66
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• 2016

Once it has been built, a container terminal is impossible to move to another location. It is hard to rectify wrong decisions in a container terminal. This highlights the importance of decision making for a container terminal. The port management about a container terminal has developed from a cargo interface location between sea and land transport, to the standardization of information and procedures due to globalization among global shipping and terminal operators. This research focuses on the current states of market and management for global container terminal operators by investigating up-to-date data for them. The current market states for global container terminal operators are analyzed by using by Herfindahl-Hirschman Index. The analyses of current management states for global container terminal operators are divided into profitability analysis, activity analysis, and bankruptcy risk analysis. Finally, global container terminal operators are clustered into three groups by the current management states.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.23-30
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• 2022

The failure of the reefer container causes a great loss of cost, but the current reefer container alarm system is inefficient. Existing studies using simulation data of refrigeration systems exist, but studies using actual operation data of refrigeration containers are lacking. Therefore, this study classified the causes of failure using actual refrigerated container operation data. Data imbalance occurred in the actual data, and the data imbalance problem was solved by comparing the logistic regression analysis with ENN-SMOTE and class weight with the 2-stage algorithm developed in this study. The 2-stage algorithm uses XGboost, LGBoost, and DNN to classify faults and normalities in the first step, and to classify the causes of faults in the second step. The model using LGBoost in the 2-stage algorithm was the best with 99.16% accuracy. This study proposes a final model using a two-stage algorithm to solve data imbalance, which is thought to be applicable to other industries.

• The Journal of Bigdata
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• v.6 no.2
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• pp.85-98
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• 2021

The pandemic of COVID-19 further promoted the imbalance in the volume of imports and exports among countries using containers, which worsened the shortage of empty containers. Since it is important to secure as many empty containers as the appropriate demand for stable and efficient port operation, measures to predict demand for empty containers using various techniques have been studied so far. However, it was based on long-term forecasts on a monthly or annual basis rather than demand forecasts that could be used directly by ports and shipping companies. In this study, a daily and weekly prediction method using an actual artificial neural network is presented. In details, the demand forecasting model has been developed using multi-layer perceptron and multiple linear regression model. In order to overcome the limitation from the lack of data, it was manipulated considering the business process between the loaded container and empty container, which the fully-loaded container is converted to the empty container. From the result of numerical experiment, it has been developed the practically applicable forecasting model, even though it could not show the perfect accuracy.

• Ocean Systems Engineering
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• v.12 no.2
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• pp.225-245
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• 2022

More and more shipping containers are falling into the sea due to bad weather. Containers lost at sea negatively affect the shipping line, the trader and the consumer, and the environment. The question of locating and recovering dropped containers is a challenging engineering problem. Model-testing of small-scaled container models is proposed as an efficient way to investigate their falling trajectories to salvage them. In this study, we first build a standard 20-ft container model in SOLIDWORKS. Then, a three-dimensional (3D) geometric model in the STL (Standard Tessellation Language) format is exported to a Stratasys F170 Fused Deposition Modeling (FDM) printer. In total, six models were made of acrylonitrile styrene acrylate (ASA) and printed for the purpose of testing. They represent three different loading conditions with different densities and center of gravity (COG). Two samples for each condition were tested. The physical models were dropped into the towing tank of University of New Orleans (UNO). From the experimental tests, it is found that the impact of the initial position after sinking can cause a certain initial rolling velocity, which may have a great impact on the lateral displacement, and subsequently affect the final landing position. This series of model tests not only provide experimental data for the study of the trajectory of box-shape objects but also provide a valuable reference for maritime salvage operations and for the pipeline layout design.

• Journal of Korean Port Research
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• v.11 no.2
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• pp.145-156
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• 1997

The purpose in this study is development of model for the Container Terminals of Pusan Port, First of all, Quantitive and Qualititve factors are characterized which effects on Physical Distribution System in Container Terminals. The System Dynamics method is used to develope the model by using these factor. This model is able to present the timinig of investment in Container Terminals of Pusan Port. Six models are showed by change of parameters in System Dynamics, in this paper. In the model, Five feedback loop were found. Loop 1 : Number of Liners$\rightarrow$Number of Congested ships$\rightarrow$Port's Charges$\rightarrow$Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$The will to investment of government$\rightarrow$Length of berth→Number of Liners. Negative loop was acquired. Loop 2 : Port's Charge$\rightarrow$Economic of Port$\rightarrow$The will to Private management$\rightarrow$Efficiency for Port's Operation$\rightarrow$Port's Charges. Positive loop was acquired. Loop 3 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Information Service$\rightarrow$Support service for port's user$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 4 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Extent of stacking area$\rightarrow$Number of handling equipmint$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 5 : Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$Econmic of Port$\rightarrow$Support service for port's user$\rightarrow$Export & Import Cargo Volumes. Positive loop was acquired. System's level variables were selected as followings ; Number of Liners, Number of Congested ships, Export & Import Carge Volumes, Length of berth, and Port's Charges. As result of simmulation of model, fluctuation of respective year was found in level variables. This fluctuation can be used properly to present timing of investment.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.04a
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• pp.122-129
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• 1995

The seismic behavior of a rectangular liquid container with high damping laminated rubber bearing is investigated through the scaled model tests. The results are compared with those for non-isolated model, and those by analytical methods. It is shown that the optimum dynamic properties of isolation system can reduce the acceleration response in the superstructure significantly and prevent the amplification of sloshing height.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.171-174
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• 2000

This paper presents an approach to determine the vehicle fleet size for container shuttle service in a stochastic working environment. The shuttle service can be defined as the repetitive travel between the designated places during working period. The initial number of vehicles is temporarily calculated using the transportation model. Simulation is carried out in order to investigate dynamic behavior of container shuttle. Finally, the equation for estimating the vehicle fleet size is obtained through the multiple regression model based on simulation results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.473-476
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• 1996

In order to reduce the number of rehandles during the loading operation of export containers in port container terminals, the storage location of each arriving container should be determined considering of its weight. We formulate the problem by a dynamic programming model to get the optimal storage location.