• 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.

• Journal of Korean Port Research
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• v.5 no.2
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• pp.19-37
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• 1991

This work aims to : establish a model of the container physical distribution system of Pusan port comprising 4 sub-systems of a navigational system, on-dock cargo handling/transfer/storage system, off-dock CY system and an in-land transport system : examine the system regarding the cargo handling capability of the port and analyse the cost of the physical distribution system. The overall findings are as follows : Firstly in the navigational system, average tonnage of the ships visiting the Busan container terminal was 33,055 GRT in 1990. The distribution of the arrival intervals of the ships' arriving at BCTOC was exponential distribution of $Y=e^{-x/5.52}$ with 95% confidence, whereas that of the ships service time was Erlangian distribution(K=4) with 95% confidence, Ships' arrival and service pattern at the terminal, therefore, was Poisson Input Erlangian Service, and ships' average waiting times was 28.55 hours In this case 8berths were required for the arriving ships to wait less than one hour. Secondly an annual container through put that can be handled by the 9cranes at the terminal was found to be 683,000 TEU in case ships waiting time is one hour and 806,000 TEU in case ships waiting is 2 hours in-port transfer capability was 913,000 TEU when berth occupancy rate(9) was 0.5. This means that there was heavy congestion in the port when considering the fact that a total amount of 1,300,000 TEU was handled in the terminal in 1990. Thirdly when the cost of port congestion was not considered optimum cargo volume to be handled by a ship at a time was 235.7 VAN. When the ships' waiting time was set at 1 hour, optimum annual cargo handling capacity at the terminal was calculated to be 386,070 VAN(609,990 TEU), whereas when the ships' waiting time was set at 2 hours, it was calculated to be 467,738 VAN(739,027 TEU). Fourthly, when the cost of port congestion was considered optimum cargo volume to be handled by a ship at a time was 314.5 VAN. When the ships' waiting time was set at I hour optimum annual cargo handling capacity at the terminal was calculated to be 388.416(613.697 TEU), whereas when the ships' waiting time was set 2 hours, it was calculated to be 462,381 VAN(730,562 TEU).

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.25-39
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• 2023

As the scope of supply chains expands globally, unpredictable risks continue to arise. The occurrence of these supply chain risks affects port cargo throughput and hinders port operation. In order to examine the impact of global supply chain risks on port container throughput, this study conducted an empirical analysis on the impact of variables such as the Global Supply Chain Pressure Index (GSCPI), Shanghai Container Freight Index (SCFI), Industrial Production Index, and Retail Sales Index on port traffic using the vector autoregressive(VAR) model. As a result of the analysis, the rise in GSCPI causes a short-term decrease in the throughput of Busan Port, but after a certain point, it acts as a factor increasing the throughput and affects it in the form of a wave. In addition, the industrial production index and the retail sales index were found to have no statistically significant effect on the throughput of Busan Port. In the case of SCFI, the effect was almost similar to that of GSCPI. The results of this study reveal how risks affect port cargo throughput in a situation where supply chain risks are gradually increasing, providing many implications for establishing port operation policies for future supply chain risks.

• Journal of Korea Port Economic Association
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• v.28 no.3
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• pp.73-89
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• 2012

As the environment surrounding ports is rapidly changing and ports competition in Southeast Asia has become more severe to secure cargo volumes, ports strive to enhance their competitiveness by improving the efficiency of operations. The operational efficiency of ports, plays a crucial role to improve a nation's. This study aims to analyze the efficiency of container port and its determinants during over five year(2006 to 2010) period using DEA-O and Tobit regression respectively. The results show that firstly, Gamman is the most efficient container terminal, followed by New Gamman container terminal and Hutchison Busan container terminal. Secondly, it is notable that the efficiency of Busan Newport is dramatically increasing, and finally, the yard productivity of the container port is only influencing determinant of all.

• Journal of Navigation and Port Research
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• v.28 no.8
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• pp.709-714
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• 2004

This paper first tries to analyze total sea transport costs for the transshipment in Busan Port in comparison with direct transport to 4 Chinese Ports, Dalian, Tinajin, Qingdao and Shanghai, based on vessel operation scenarios. The results found that the transshipment in Busan port for the 4 Chinese ports are more expensive than the direct calling to the 4 ports, which implies that Busan port needs to make compensation as an incentive to the carriers providing transshipment service to it in order to keep their royalty. For the compensation, it suggested a method of calculating the Container Terminal Facilities Leasing Fee to levy additional revenue by port authority.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.344-350
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• 2022

Due to the increase in container cargo volume, the congestion of container terminals is increasing and the waiting time of gate in-out trucks has significantly lengthened at container yards and gates, resulting in severe inefficiency in gate in-out truck operations as well as port operations. To resolve this problem, the Busan Port Authority and terminal operator provide services such VBS, terminal congestion information, and expected operation processing time information. However, the visible effect remains insufficient, as it may differ from actual waiting time.. Thus, as basic data to resolve this problem, this study presents deep learning based average gate in-out truck waiting time prediction models, using container gate in-out information at Busan New Port. As a result of verifying the predictive rate through comparison with the actual average waiting time, it was confirmed that the proposed predictive models showed high predictive rate.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.57-65
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• 2010

This paper describes the method of efficient container number recognition in colored container image with number plate at ATC(Automatic Transfer Crane) in container terminal yard. At the Sinseondae terminal gate in Busan, the container number recognition system is installed by "intelligent port-logistics system technology development", that is government research and development project. It is the method that it sets up the tunnel structure inside camera on the gate and it recognizes the container number in order to recognize the export container cargo automatically. However, as the automation equipment is introduced to the container terminal and the unmanned of a task is gradually accomplished, the container number recognition system for the confirmation of the object of work is required at ATC in container terminal yard. Therefore, the container number recognition system fitted for it is necessary for ATC in container terminal yard in which there are many intrusive of the character recognition through image including a sunlight, rain, snow, shadow, and etc. unlike the gate. In this paper, hardware components of the camera, illumination, and sensor lamp were altered and software elements of an algorithm were changed. that is, the difference of the brightness of the surrounding environment, and etc. were regulated for recognize a container number. Through this, a shadow problem, and etc. that it is thickly below hung with the sunlight or the cargo equipment were solved and the recognition time was shortened and the recognition rate was raised.

• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.1-19
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• 2010

This paper focuses measuring the efficiency of container yards on container terminals in Busan (Gasungdae, Shinsundae, Gamman, New Gamman, Uam, Gamchon, PNC) and Gwangyang(GICT, KEC, Dongbu, KIT) using Data Envelopment Analysis(DEA) approach. Container terminals in Busan and Gwangyang play an important role in the region's economic development. The results show that Shinsundae was an efficient DMU during the period of 2007 to 2009, while Gamman, New Gamman and PNC were efficient terminals in 2009. The very inefficient terminals were shown to be GICT, KEC, Dongbu and KIT. GICT(2009), KEC(2009), Dongbu(2008-2009), KIT(2009) on Gwangyang Port were found to be relatively the inefficient terminals in terms of the returns to scale. This study also finds that the efficiency of Shinsundae terminal was so high as to be abel to keep its efficiency in spite of the additional increase of the inputs from 2007 to 2009. Gamman terminal was in the decreasing returns to scale in 2009, while the other terminals were in the increasing returns to scale. It means that we are able to improve the efficiency of the Gamman terminal with increasing returns to scale through enlarging the scale.

• Journal of Korea Port Economic Association
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• v.25 no.3
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• pp.207-228
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• 2009

The purpose of this paper is to analyze the concentration effect of Busan container terminal. Productivity and efficiency have played key role to attract more cargo to a port because these are important factors to select liners’ calling port in vessel deployment. It means that productivity directly links with the liners’ vessel operation cost. The main results of this paper are as follows: the port concentration by terminal integration can improve the port's external image with recovering tariff competitiveness and also facilitate economic effect of size through efficient management.