• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.179-196
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• 2021

Port congestion rate at Busan Port has increased for three years. Port congestion causes container reconditioning, which increases the dockyard labor's work intensity and ship owner's waiting time. If congestion is prolonged, it can cause a drop in port service levels. Therefore, this study proposed an anomaly detection method using ARIMA(Autoregressive Integrated Moving Average) model with the daily volume data from 2013 to 2020. Most of the research that predicts port volume is mainly focusing on long-term forecasting. Furthermore, studies suggesting methods to utilize demand forecasting in terms of port operations are hard to find. Therefore, this study proposes a way to use daily demand forecasting for port anomaly detection to solve the congestion problem at Busan port.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.379-382
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• 2017

Shipping and logistics safety, security system is strengthening worldwide, the development of shipping and logistics safety security core technology for national security logistics system construction has been carried out. In addition, it is necessary to localize the Array Detection System, which is a core component of the container search machine, to cope with the 100% pre-inspection of the container scheduled for 2018 in the United States. In this paper, we propose a test software program developed by using TI-RTOS (Texas Instruments - Real Time Operating System) with a test digital signal processing board which is developed self development.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1478-1489
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• 2006

This paper describes system to extract ISO codes in container image. A container ISO code recognition system for real-time processing is made of 5 core parts which are container ISO code detection and image acquisition, ISO code region extraction, individual character extraction, character recognition and database. Among them, the accuracy of ISO code extraction can affect significantly the accuracy of system recognition rate, and also the more exact extraction of ISO code is required in various weather and environment conditions. The proposed system produces binary of the ISO code's template lesions using an adaptive thresholding, extracts candidate regions containing distribution of ISO code, and recognizes ISO codes as detecting a final region through the verifications by using character distribution characteristics of ISO code among the extracted candidates. Experimental results reveal that ISO codes can be efficiently extracted by the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1380-1386
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• 2007

This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is blacker white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm. Experiments using real images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.471-477
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• 2004

In this study, we introduce a 3-dimensional simulation to support the Design on ACT(Automated Container Terminal). This simulation system developed to simulate virtual operations of ACT using 3-dimensional simulation and animate the simulated results with real time. And the developed system applied an object-oriented design and C++ programming to increase the reusability and extensibility. We select several items of performance evaluation for objects used in ACT in terms of problem detection, problem forecast, and logic feasibility, and provide evaluation points for the design of ACT.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.41-59
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• 2015

Information systems has been developed and used in various business area, therefore there are abundance of history data (log data) stored, and subsequently, it is required to analyze those log data. Previous studies have been focusing on the discovering of relationship between events and no identification of anomaly instances. Previously, anomaly instances are treated as noise and simply ignored. However, this kind of anomaly instances can occur repeatedly. Hence, a new methodology to detect the anomaly instances is needed. In this paper, we propose a methodology of LAPID (Local Anomaly Process Instance Detection) for discriminating an anomalous process instance from the log data. We specified a distance metric from the activity relation matrix of each instance, and use it to detect API (Anomaly Process Instance). For verifying the suggested methodology, we discovered characteristics of exceptional situations from log data. To demonstrate our proposed methodology, we performed our experiment on real data from a domestic port terminal.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.639-646
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• 2017

The purpose of this study is to present the algorithm to minimize the image noise caused by deterioration of high X-ray container inspection equipment and the faulty detection sensors, and to improvement quality of the container inspection images using MATLAB Toolbox. The daily checking images for the container inspection were used with the subject images and the noise caused by the horizontal and vertical images was evaluated with Root Mean Square (RMS) method, which is the most basic evaluation method of digital radiation image. Also, quality of the improved images was evaluated compared to quality of the orignal images. As a result, all RMS value of the improved images was lower then the original images by a mean of 13.5% in the horizontal images and 18.2% in the vertical images respectively. Also so did RMS value of the improved container images, by a mean of 13.4% in the horizontal images and 19.1% in the vertical images respectively. These findings can be verified objectively and visually and they would help the reading process of the container images be effective in Korea Customs Service.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.39-51
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• 2024

This paper proposes a novel approach to enhance the security of container-based systems by analyzing system calls to dynamically detect race conditions without modifying the kernel. Container escape attacks allow attackers to break out of a container's isolation and access other systems, utilizing vulnerabilities such as race conditions that can occur in parallel computing environments. To effectively detect and defend against such attacks, this study utilizes eBPF to observe system call patterns during attack attempts and employs a AdaBoost model to detect them. For this purpose, system calls invoked during the attacks such as Dirty COW and Dirty Cred from popular applications such as MongoDB, PostgreSQL, and Redis, were used as training data. The experimental results show that this method achieved a precision of 99.55%, a recall of 99.68%, and an F1-score of 99.62%, with the system overhead of 8%.

• Convergence Security Journal
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• v.24 no.2
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• pp.19-29
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• 2024

A crypto-jacking attack is an attack that infringes on the availability of users by stealing computing resources required for cryptocurrency mining. The target of the attack is gradually diversifying from general desktop or server environments to cloud environments. Therefore, it is essential to apply a crypto-minor detection technique suitable for various computing environments. However, since the existing detection methodologies have only been detected in a specific environment, comparative analysis has not been properly performed on the methodologies that can be applied to each environment. Therefore, in this study, classification criteria for conventional crypto-minor detection techniques are established, and a complex and integrated detection framework applicable to the cloud environment is presented through in-depth comparative analysis of existing crypto-minor detection techniques based on different experimental environments and datasets.

• Structural Engineering and Mechanics
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• v.26 no.2
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• pp.179-190
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• 2007

Damage detection based on measured vibration data has received intensive studies recently. Frequently, the damage to a structure may be reflected by a change of some system parameters, such as a degradation of the stiffness. In this paper, we apply a method to nondestructively locate and estimate the severity of damage in corrosion pipeline for which a few natural frequencies or mode shapes are available. The method is based on the strain modal sensitivity ratio (SMSR) and the orthogonality conditions sensitivities (OCS) applied to vibration features identified during the monitoring of the pipeline. The advantage of these methods is that it only requires measuring few modal parameters. The SMSR-based and OCS-based damage detection methods are illustrated using computer-simulated and laboratory testing data. The results show that the current method provides a precise indication of both the location and the extent of corrosion pipeline.