• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.21 no.2
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• pp.63-73
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• 2017

Segmenting the image into multiple regions is at the core of image processing. Many segmentation formulations of an images with multiple regions have been suggested over the years. We consider segmentation algorithm based on the multi-phase level set method in this work. Proposed method gives the best result upon other methods found in the references. Moreover it can segment images with intensity inhomogeneity and have multiple junction. We extend our method (GLIF) in [T. Dultuya, and M. Kang, Segmentation with shape prior using global and local image fitting energy, J.KSIAM Vol.18, No.3, 225-244, 2014.] using a multiphase level set formulation to segment images with multiple regions and junction. We test our method on different images and compare the method to other existing methods.

• Journal of the Korean Regional Science Association
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• v.15 no.1
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• pp.23-43
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• 1999

The strategy of regional industrial specialization is empirically evaluated by examining the relationship between regional industrial structures and economic performances. The regional industrial structure is measured by three industrial diversity indices such as ogive approach, entropy maximizing approach, and economic growth and employment instability in 12 regions is analyzed. According to the time series analysis, we found that the region with more diversified industrial structure experiences more stable in employment. Otherwise, the growth rate of the region with more simplified industrial structure is higher. Therefore, the strategy of industrial specialization is implemented in order to pursuit a rapid economic growth in the short run.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.4
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• pp.394-407
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• 2016

The spatial air pollution distribution of the Ulsan metropolitan region (UMR) was analyzed using monitoring data and high-resolution numerical simulations. A three-year (2011~2014) analysis for the average concentrations from the 13 air quality monitoring sites in the UMR showed that $SO_2$ and $PM_{10}$ levels in industrial regions were much higher than those in other regions, whereas spatial differences of $NO_2$ and CO concentrations were not significant. In particular, elevated $O_3$ concentrations were clearly found at urban sites near petrochemical complex area. Results from high-resolution simulations by CMAQ model performed for four months of 2012 showed large spatial variations in grid-average pollutant concentrations between industrial areas and other areas in the UMR, which displayed significant changes with wind pattern by season. It was noted that the increases of $SO_2$ and $PM_{10}$ levels were limited in costal industrial areas or over the area nearby the sea in all seasons. Modeled $O_3$ concentrations were quite low in industrial areas and main urban roads with large $NO_x$ emissions. However, the model presented that all pollutant concentrations were significantly increased in the urban residential areas near the industrial complexes in summer season with increase of southerly wind.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.75-100
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• 2023

Over the past few decades, globalization has been shifting economic power upward to transnational actors on the one hand, and downward to subnational or regional spaces on the other. This phenomenon has resulted in the centrality of territorially delimited subnational regions acting as critical loci of economic governance within a complex and globally distributed value chain of trade and service flows. Within this broader context of industrial restructuring are economic regions that span national borders in their collective assets. The paper focuses on investigating the economic competitiveness and productivity of cross-border (or binational) economic regions. Using the conceptual framework of economic clusters, an econometric model that measures proxies of geographic proximity of firms in the life sciences cluster, and a new binational economic model, the paper examines the key characteristics, potentials and constraints of economic competitiveness and productivity in a cross-border region comprising counties in Western New York and regional municipalities in Southern Ontario. The findings demonstrate the direct and indirect benefits of closer cross-border economic cooperation. The paper then concludes with some policy observations about leveraging cross-border economic clusters for strategic industrial cooperation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2713-2719
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• 2012

According to increasing of various location-based services, distributed data stream processing techniques have been widely studied to provide high scalability and availability. In previous researches, in order to balance the load of distributed nodes, the geographic characteristics of spatial data stream are not considered. For this reason, distributed operations for adjacent spatial regions increases the overall system load. We propose a operation allocation scheme considering the characteristics of spatial operations to effectively processing spatial data stream in distributed computing environments. The proposed method presents the efficient share maximizing approach that preferentially distributes spatial operations sharing the common query regions to the same node in order to separate the adjacent spatial operations on overlapped regions.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.2
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• pp.41-47
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• 2007

A fine segmentation algorithm is proposed for extracting objects in an image, which have both weak boundaries and highly non-convex shapes. The image has simple background colors or simple object colors. Two concepts, geometric attraction-driven flow (GADF) and edge-regions are combined to detect boundaries of objects in a sub-pixel resolution. The main strategy to segment the boundaries is to construct initial curves close to objects by using edge-regions and then to make a curve evolution in GADF. Since the initial curves are close to objects regardless of shapes, highly non-convex shapes are easily detected and dependence on initial curves in boundary-based segmentation algorithms is naturally removed. Weak boundaries are also detected because the orientation of GADF is obtained regardless of the strength of boundaries. For a fine segmentation, we additionally propose a local region competition algorithm to detect perceptible boundaries which are used for the extraction of objects without visual loss of detailed shapes. We have successfully accomplished the fine segmentation of objects from images taken in the studio and aphids from images of soybean leaves.

• Earthquakes and Structures
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• v.4 no.6
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• pp.629-647
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• 2013

Loading protocols have been developed for quasi-static cyclic testing of structures and components. However, it is uncertain if protocols developed for conditions of intense ground shaking in regions of high seismicity would also be applicable to regions of low-moderate seismicity that are remote from the tectonic plate boundaries. This study presents a methodology for developing a quasi-static cyclic displacement loading protocol for experimental bracing evaluation of cold-formed steel stud shear walls. Simulations presented in the paper were based on conditions of moderate ground shaking (in Australia). The methodologies presented are generic in nature and can be applied to other regions of similar seismicity conditions (which include many parts of China, Korea, India and Malaysia). Numerous response time histories including both linear and nonlinear analyses have been generated for selected earthquake scenarios and site classes. Rain-flow cycle counting method has been used for determining the number of cycles at various ranges of normalized displacement amplitude. It is found that the number of displacement cycles of the loading protocol increases with increasing intensity of ground shaking (associated with a longer return period).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.885-892
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• 2013

In this paper, we propose a method of effectively segmenting character regions by using texture and depth features in 3D stereoscopic images. The suggested method is mainly composed of four steps. The candidate character region extraction step extracts candidate character regions by using texture features. The character region localization step obtains only the string regions in the candidate character regions. The character/background separation step separates characters from background in the localized character areas. The verification step verifies if the candidate regions are real characters or not. In experimental results, we show that the proposed method can extract character regions from input images more accurately compared to other existing methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.655-661
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• 2017

It is a very important task to extract character regions contained in various input color images, because characters can provide significant information representing the content of an image. In this paper, we propose a new method for extracting character regions from various input images using MCT features and an AdaBoost algorithm. Using geometric features, the method extracts actual character regions by filtering out non-character regions from among candidate regions. Experimental results show that the suggested algorithm accurately extracts character regions from input images. We expect the suggested algorithm will be useful in multimedia and image processing-related applications, such as store signboard detection and car license plate recognition.

• Current Research on Agriculture and Life Sciences
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• v.32 no.4
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• pp.215-223
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• 2014

This study examines the contribution level of greenhouse gas(GHG) emission reduction and installation costs of renewable energy facilities. The GHG emission forecasts and industrial structures in the 16 regions of Korea are then analyzed to identify the proper supply of renewable energy sources for each region. The results show that water power is the most effective and efficient renewable energy source to reduce GHG emissions, followed by sunlight, wind power, geothermal heat, and solar heat, respectively. The 16 regions are then categorized into 4 groups based on their GHG emission forecast and industrial structure: high emission and manufacturing group, low emission and manufacturing group, low emission and service group, and high emission and service group. The proper supply of renewable energy sources for each group is then determined based on the contribution level and cost efficiency of GHG emission reduction.