• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1162-1169
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• 2007

In this paper, we proposed a container identifier recognition method for containers used in harbors. After converting a real container image to a gray image, edges are detected from the gray image applying Prewitt mask and candidate identifier area is extracted using morphological features of individual identifier for identifying containers. Because noises are included in the extracted candidate identifier area, noises are eliminated and each identifier is separated using 4-directional edge tracking algorithm and Grassfire algorithm. Each identifier in the noise-free candidate identifier area is recognized using FCM-based row RBF network for discriminating containers. We used 300 real container images for experiment to evaluate the performance of the proposed method, and we could verify the proposed method is better than a conventional method.

• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.161-166
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• 2002

In view of the great disparity between forecasts of Shanghai port container handling capacity and its real results, we choose a dynamic forecast method by the causality model dynamic compensation to predict Shanghai port container handling capacity. And we forecast Shanghai port container handling capacity by using this method. We have made a satisfactory achievement, which provides a more reliable and practical way to forecast container handling capacity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12B
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• pp.1349-1358
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• 2009

Because of the limitation of supporting power, the current WSN(Wireless Sensor Network) Technologies whose one of the core attributes is low power consumption are the best solution for shipping container networking in stack environment such as on vessel. So it is effective to use the Wireless Sensor Network Technology. In this case, many nodes join in the network through a sink node because there are difficulties to get big money and efforts to set up a lot of sink node. It needs clustering-based proactive protocol to manage many nodes. But it shows low reliability because they have effect on radio frequency in metal obstacle environments(interference, distortion, reflection, and etc) like the intelligent container. In this paper, we proposed an improved Modified LEACH Protocol for stableness radio frequency environment. In the proposed protocol, we tried to join the network and derived stable topology composition after the measuring of link quality. Finally, we verified that the proposed protocol is composing more stable topology than previously protocol in metal obstacle environment.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1209-1214
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• 2010

In these days, rail container service is being more important because it has relatively simple network. In addition, small lot sizes of shipment, frequent shipment, and demand for flexible service are important characteristics in rail container transportation. Efficient container operation at terminals is important in reducing transportation costs and load/unload time. This paper describes the assigning track of freight trains in the railway freight terminal. The paper addresses the operational requirements and facility restrictions to construct a mathematical model for track assignment. In addition, it suggests several types of objectives for the model.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1398-1404
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• 2018

High-performance computing (HPC) provides to researchers a powerful ability to resolve problems with intensive computations, such as those in the math and medical fields. When an HPC platform is provided as a service, users may suffer from unexpected obstacles in developing and running applications due to restricted development environments and dependencies. In this context, operating system level virtualization can be a solution for HPC service to ensure lightweight virtualization and consistency in Dev-Ops environments. Therefore, this paper proposes three types of typical HPC structure for container environments built with HPC container and Docker. The three structures focus on smooth integration with existing HPC job framework, message passing interface (MPI). Lastly, the performance of the structures is analyzed with High Performance Linpack benchmark from the aspect of performance degradation in network communications under Docker.

• Journal of Navigation and Port Research
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• v.32 no.8
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• pp.675-683
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• 2008

This paper develops a framework of combining Balanced Scorecard (BSC) and Quality Function Deployment (QFD) using Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) and evaluates the performance factors of container terminals using the framework. This study designs a BSC of container terminals and then transforms this into QFD in order to determine the priority of performance factors. This paper provides a modified QFD model and shows a causal relationship among perspectives of BSC to find out critical performance factors of container terminals. This modified QFD model is different from traditional models in that a correlation and relation matrix is presented. This combination of BSC and QFD with AHP and ANP helps to create more realistic and accurate representation of QFD models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1205-1214
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• 2021

Edge Computing is used as a solution to the cost problem and transmission delay problem caused by network bandwidth consumption that occurs when IoT/CPS devices are integrated into the cloud by performing artificial intelligence (AI) in an environment close to the data source. Since edge computing runs on devices that provide high-performance computation and network connectivity located in the real world, it is necessary to consider application integrity so that it is not exploited by cyber terrorism that can cause human and material damage. In this paper, we propose a technique to protect the integrity of edge computing applications implemented in a script language that is vulnerable to tampering, such as Python, which is used for implementing artificial intelligence, as container images and then digitally signed. The proposed method is based on the integrity protection technology (Docker Contents Trust) provided by the open source container technology. The Docker Client was modified and used to utilize the whitelist for container signature information so that only containers allowed on edge computing devices can be operated.

• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.43-60
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• 2010

The purpose of this paper is to show the clustering measurement way for Korean container terminals by using neural network based SOM(Self Organizing Map). Inputs[Number of Employee, Quay Length, Container Terminal Area, Number of Gantry Crane], and output[TEU] are used for 3 years(2002,2003, and 2004) for 8 Korean container terminals by applying both DEA and SOM models. Empirical main results are as follows: First, the result of DEA analysis shows the possibility for clustering among the terminals and reference terminals except Gamcheon and Gwangyang terminals because of the locational closeness. Second, the result of neural network based SOM clustering analysis shows the positive clustering in clustering positions 1, 2, 3, 4, and 5. Third, the results between SOM clustering and DEA clustering show the matching ratio about 67%. The main policy implication based on the findings of this study is that the port policy planner of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the clustering measurement way for the Korean container terminals using neural network based SOM with DEA models for clustering Korean ports and terminals.

• Structural Engineering and Mechanics
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• v.50 no.1
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• pp.105-119
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• 2014

This study presents a steel container crane movement analysis and assessment based on structural health monitoring (SHM). The accelerometers are used to monitor the dynamic crane behavior and a 3-D finite element model (FEM) was designed to express the static displacement of the crane under the different load cases. The multi-input single-output nonlinear autoregressive neural network with external input (NNARX) model is used to identify the crane dynamic displacements. The FEM analysis and the identification model are used to investigate the safety and the vibration state of the crane in both time and frequency domains. Moreover, the SHM system is used based on the FEM analysis to assess the crane behavior. The analysis results indicate that: (1) the mean relative dynamic displacement can reveal the relative static movement of structures under environmental load; (2) the environmental load conditions clearly affect the crane deformations in different load cases; (3) the crane deformations are shown within the safe limits under different loads.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.50-54
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• 2010

A Container Security Device (CSD) which is different existing RFID Tag strengthens the physical security as mounted inside the container and the information security as encrypts doubly a data. CSD must use the resources efficiently in order to operate with the battery. Therefore, it needs low-power mechanism which repeats the sleep period and channel scan period. However, by adjusting these periods, the trade-off occurs between energy efficiency and network connectivity. In this paper, we implement low-power CSD and resolve this problem by adjusting beacon period and channel scan time. As a result, We guarantee the network connectivity 95% or more and maximum life up to 16 days using common AA batteries.