• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.1-18
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• 2003

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6B
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• pp.728-737
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• 2011

For the real time monitoring and tracking of shipping container which is one of the core objects for global logistics, Wireless Ad-Hoc Network technology might be needed in stacking environments such as ports, yards and ships. In this paper, we propose a container network routing protocol suitable for port or yard stacking environments which include some constraints such as shadow area problem from metal material, frequent movement of container, etc. With this protocol in which a mesh network algorithm is applied, every container data packet can be delivered to the sink node reliably even with frequent join/leave of container nodes. As soon as a node on path gets malfunction, alternative backup path is supported with notice to neighbor node, which makes constant total optimal path. We also verified that the performance of proposed protocol is better than AODV, one of previous major MANet(Mobile Ad-Hoc Network) protocol with a function for alternative path, which says the proposed protocol is better for frequent join/leave and variable link quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.349-356
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• 2004

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. In this paper we propose and evaluate a novel recognition algorithm for container identifiers that effectively overcomes these difficulties and recognizes identifiers from container images captured in various environments. The proposed algorithm, first, extracts the area containing only the identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper. Then a contour tracking method is applied to the binarized area in order to extract the container identifiers which are the target for recognition. In this paper we also propose and apply a novel ART2-based hybrid network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm performs better for extraction and recognition of container identifiers compared to conventional algorithms.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.88-95
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• 2003

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.183-188
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• 2002

The forecast of a container traffic has been very important for port and development. Generally, Statistic methods, such as moving average method, exponential smoothing, and regression analysis have been much used for traffic forecasting. But, considering various factors related to the port affect the forecasting of container volume, neural network of parallel processing system can be effective to forecast container volume based on various factors. This study discusses the forecasting of volume by using the neural, network with back propagation learning algorithm. Affected factors are selected based on impact vector on neural network, and these selected factors are used to forecast container volume. The proposed the forecasting algorithm using neural network was compared to the statistic methods.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.14-24
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• 2002

We focus on resource allocation planning in container terminal operation planning problems and present network design model and genetic algorithm. We present a network design model in which arc capacities must be properly dimensioned to sustain the container traffic. This model supports various planning aspects of container terminal and brings in a very general form. The integer programming model of network design can be extended to accommodate vertical or horizontal yard configuration by adding constraints such as restricting the sum of yard cranes allocated to a block of yards. We devise a genetic algorithm for the network design model in which genes have the form of general integers instead of binary integers. In computational experiments, it is found that the genetic algorithm can produce very good solution compared to the optimal solution obtained by CPLEX in terms of computation time and solution quality. This algorithm can be used to generate many alternatives of a resource allocation plan for the container terminal and to evaluate the alternatives using various tools such as simulation.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.100-104
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• 2008

Generally, it is difficult to find constant patterns on identifiers in a container image, since the identifiers are not normalized in color, size, and position, etc. and their shapes are damaged by external environmental factors. This paper distinguishes identifier areas from background noises and removes noises by using an ART2-based quantization method and general morphological information on the identifiers such as color, size, ratio of height to width, and a distance from other identifiers. Individual identifier is extracted by applying the 8-directional contour tracking method to each identifier area. This paper proposes a refined ART2-based RBF network and applies it to the recognition of identifiers. Through experiments with 300 container images, the proposed algorithm showed more improved accuracy of recognizing container identifiers than the others proposed previously, in spite of using shorter training time.

• Journal of Navigation and Port Research
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• v.28 no.7
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• pp.587-591
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• 2004

In order to measure the performance of resources in a port container terminal, we conducted a state transition network simulation to model various equipment processes. The processes that container cranes and transfer cranes perform are idle, wait, move, and work. Vehicles perform idle, wait, empty travel, and full travel. Because cranes, vehicles, and vessels are movable entities and all equipment is classified as either a customer or server, we separated the various stages of the process based upon the state transition network To validate the simulation results, a real system was used to illustrate the use of various measurements using the state transition network.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.529-538
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• 2018

The port industry is an important national industry which significantly affects Korea's imports and exports which are centered on economic structure. For instance, the Port of Busan, which handles 75% of domestic container freight volume, is expected to become increasingly critical for container liner routes. For this reason, there have been continued efforts to expand freight service to attract international freight volume. This study analyzes the structural characteristics of the port network connected to the Port of Busan by analyzing the pattern of the container liner route from 2012 to 2016 by using social network analysis. According to the Port of Busan's liner route network, the port with the highest degree of centrality, closeness centrality, and betweenness centrality was found to be the Port of Singapore. The comparison of Busan's annual container handling rank by countries and the port center network analysis of Port of Busan rank was found to be different. As a result, it was established that China's East Port, which occupies a high percentage of the volume of cargo handled by Port of Busan, is not a hub port of Busan when viewed on the Busan's container terminal liner network. In addition, even if the number of Port of Busan container liner service increases, it is estimated that the vessels to be added to the fleet will be limited to small to medium sized, or that Busan port has characteristic of a feeder port for the Port of Singapore, according to the network.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.141-149
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• 2024

This paper proposes a configuration automation technique to minimize service interruption time in the event of a corporate network access layer switch failure. The automation is achieved without the need for a separate external system, as the network setting information is stored in a container inside the switch, enabling rapid recovery without requiring separate storage. This approach ensures the continuity of network services and demonstrates the efficiency of configuration automation. The proposed technique improves corporate network stability by providing a quick response in the event of a failure.