• Journal of Korea Port Economic Association
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• v.32 no.3
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• pp.123-137
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• 2016

In order to address the crisis of the regional employment structure caused by the recent restructuring of the shipbuilding industry, this study estimates the shipbuilding industry's Employment Linkage Effect(ELE) across regions and industries. Consequently, the study uses the hypothetical extraction method on the shipbuilding industry from the 2013 Regional Input-output Table. The analysis results are as follows. First, the shipbuilding industry's ELE across industries is estimated at its highest in wholesale and retail, followed by shipment, other manufacturing, project supporting service, machine and equipment manufacturing, and metal product manufacturing. These industries either have a high employment to GDP ratio or are directly related to the shipbuilding industry in terms of production activities. Second, the Southeastern Korea's ELE on South Jeolla Province is very low, and, accordingly, South Jeolla Province is isolated in the employment structure of the shipbuilding industry. Therefore, when the government establishes measures to tackle the crisis of employment caused by the shipbuilding industry's restructuring, it should prioritize identifying such regional employment structures, as demonstrated above, and incorporate them into the regional industry policy.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.111-122
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• 2015

This study purposed on introducing a new automated solution for detecting railway tracks and reconstructing track models from the mobile laser scanning data. The proposed solution completes following procedures; the study initiated with detecting a potential railway region, called Region Of Interest (ROI), and approximating the orientation of railway track trajectory with the raw data. At next, the knowledge-based detection of railway tracks was performed for localizing track candidates in the first strip. In here, a strip -referring the local track search region- is generated in the orthogonal direction to the orientation of track trajectory. Lastly, an initial track model generated over the candidate points, which were detected by GMM-EM (Gaussian Mixture Model-Expectation & Maximization) -based clustering strip- wisely grows to capture all track points of interest and thus converted into geometric track model in the tracking by detection framework. Therefore, the proposed railway track tracking process includes following key features; it is able to reduce the complexity in detecting track points by using a hypothetical track model. Also, it enhances the efficiency of track modeling process by simultaneously capturing track points and modeling tracks that resulted in the minimization of data processing time and cost. The proposed method was developed using the C++ program language and was evaluated by the LiDAR data, which was acquired from MMS over an urban railway track area with a complex railway scene as well.