• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1110-1127
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• 2022

To improve the training efficiency and generalization performance of a support vector machine (SVM) in a large-scale set, an optimal SVM learning method based on adaptive sparse sampling and the granularity shift factor is presented. The proposed method combines sampling optimization with learner optimization. First, an adaptive sparse sampling method based on the potential function density clustering is designed to adaptively obtain sparse sampling samples, which can achieve a reduction in the training sample set and effectively approximate the spatial structure distribution of the original sample set. A granularity shift factor method is then constructed to optimize the SVM decision hyperplane, which fully considers the neighborhood information of each granularity region in the sparse sampling set. Experiments on an artificial dataset and three benchmark datasets show that the proposed method can achieve a relatively higher training efficiency, as well as ensure a good generalization performance of the learner. Finally, the effectiveness of the proposed method is verified.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.11-19
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• 2019

In this paper, a new Scene-based Nonuniformity Correction (SBNUC) method is proposed by applying Image Roughness-like and Spatial Noise cost functions on deep neural network structure. The classic approaches for nonuniformity correction require generally plenty of sequential image data sets to acquire accurate image correction offset coefficients. The proposed method, however, is able to estimate offset from only a couple of images powered by the characteristic of deep neural network scheme. The real world SWIR image set is applied to verify the performance of proposed method and the result shows that image quality improvement of PSNR 70.3dB (maximum) is achieved. This is about 8.0dB more than the improved IRLMS algorithm which preliminarily requires precise image registration process on consecutive image frames.

• Biomolecules & Therapeutics
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• v.30 no.2
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• pp.179-183
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• 2022

Traditionally, pathologists microscopically examine tissue sections to detect pathological lesions; the many slides that must be evaluated impose severe work burdens. Also, diagnostic accuracy varies by pathologist training and experience; better diagnostic tools are required. Given the rapid development of computer vision, automated deep learning is now used to classify microscopic images, including medical images. Here, we used a Inception-v3 deep learning model to detect mouse lung metastatic tumors via whole slide imaging (WSI); we cropped the images to 151 by 151 pixels. The images were divided into training (53.8%) and test (46.2%) sets (21,017 and 18,016 images, respectively). When images from lung tissue containing tumor tissues were evaluated, the model accuracy was 98.76%. When images from normal lung tissue were evaluated, the model accuracy ("no tumor") was 99.87%. Thus, the deep learning model distinguished metastatic lesions from normal lung tissue. Our approach will allow the rapid and accurate analysis of various tissues.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.131-139
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• 2015

This study suggests that the application of split screen as visual media can attain the effect of diversity through providing rich information and accepting diverse contents as gorgeous aesthetics. Single images are analyzed as appropriate to a demanded concentration genre such as news and dramas, entertainment. In contrast, images with natural images and ads images those are more appropriate and analyzed as the genre of the split-screen which is highly efficiency to the contents and also highly efficiency to the spatial diversification. In introducing various genres of digital contents into split screen, the synergy of contents is induced by placement in consideration of the characteristics of split screen position. In order to increase the concentration of the split-screen image, using the left area and right area above it, can increase the effectiveness of the content.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.115-121
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• 2016

Recently, it has become an important problem to extract semantic objects from videos, which are useful for improving the performance of video compression and video retrieval. In this thesis, an automatic extraction method of moving objects of interest in video is suggested. We define that an moving object of interest should be relatively large in a frame image and should occur frequently in a scene. The moving object of interest should have different motion from camera motion. Moving object of interest are determined through spatial continuity by the AMOS method and moving histogram. Through experiments with diverse scenes, we found that the proposed method extracted almost all of the objects of interest selected by the user but its precision was 69% because of over-extraction.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.33-48
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• 2024

This study aims to establish the scope and statistics of the K-address information industry in Korea, estimating its size and prospects and estimates the economic effects through K-address information industry based on Input-Output analysis. Considering the characteristics and sectoral structure of the K-address information industry, the study delineates the scope and specific sectors, constructing sectoral statistics linked to the KSIC and the Bank of Korea's industrial classification. The study estimates the sectoral industry size, taking into account potential markets. Furthermore, it analyzes the economic impact of each sector within the K-address information industry. To figure out the economic effects, the study conducts Input-Output analysis by setting the K-address information industry as an exogenous sector in the input-output table. The results indicate that the overall size of the K-address information industry is estimated to grow from 406.1 billion KRW in 2021 to 3.65 trillion KRW in 2030. The economic effects of the K-address information industry vary by sector, emphasizing the importance of synergies and integration with related sectors, particularly those with significant inducement effects in high value-added manufacturing and service sectors. Furthermore, the industry's sensitivity to economic fluctuations is evident through the input-output analysis of inter-industry chain effects.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.61-75
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• 2023

In this paper, we design and experiment a 5G-based metaverse motion synchronization system with configuration of a mobile motion capture studio that has not been commercialized at home and abroad. As a result of the experiment, the average value of the latency test measurement using Wi-Fi is 0.134 seconds faster than the average latency test measurement value using the 5G network. Existing motion capture studios have spatial limitations as the motion capture range is limited to the Wi-Fi communication range. However, the 5G-based metaverse motion synchronization system configures a mobile motion capture studio so that motion performers can solve the spatial limitations by expanding the motion capture communication range indefinitely regardless of time and place. Therefore, it is possible to implement realistic metaverse contents by displaying a realistic and natural digital human because it is free from spatial constraints. The system which was tested in this paper can create a new business model by converging next-generation technologies that are receiving attention related to the digital virtual world, such as motion capture + 5G + digital human twin + metaverse. And it allows for research and develop a next-generation metaverse-based broadcasting solution at a recent time when the business value of digital human and metaverse technologies and functions has been proven and related sales are growing in earnest.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.58-72
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• 2021

In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.

• Spatial Information Research
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• v.8 no.2
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• pp.191-201
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• 2000

Recently, tourism industry is on the trend of expanding its activity arena, boosted by revitalization of regional economy and reorganization of urban environment, undertaken for the purpose of place marketing. However, Korea has not been able to develop a variety of tourism itineraries that can attract the interest of tourists because most tourism resources are isolated with single function. This constraint has prevented tourism industry in Korea from attaining competitiveness. In attempting to overcome this constraint, this study seeks to develop tourism itineraries by constructing and utilizing database on historical and cultural tourism resources based on the case of Kangneung City. Through the construction of information system on historical and cultural resources and tourism support facilities, optimal tourism itineraries that take into account maintenance conditions, types, values, lodging availabilities and accessibility of tourism resource areas can be developed. Moreover, it is expected that this information system will have a high level of usage in the future, for it can provide a wide range of tourism services on the internet and education materials as well as facilitate resources management.

• Journal of Digital Contents Society
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• v.11 no.2
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• pp.195-201
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• 2010

Globalization, conversions, and OSMU (One Source Multi Use) in modern cultural industry is expanding fast, and global competition is soaring with a changing environment today. In fact, the development of one nation depends on its cultural creativity. Yet, there is an increasing need for a connection between space and culture since globalization homogenizes a nation's unique cultural identity and provides low level of utilization in digital cultural contents in terms of saving, conserving and maintaining data. In order to invigorate the cultural industry, there must be some information that provides public culture contents, which they can be freely searched, displayed, and re-produced. Ultimately, these public culture contents should be able to provide Culture Space. This text discusses how individuals produce the Culture Space, which provides digital information of time and space, from a relationship between culture and space. It also introduces the public Culture Contents service framework in order to provide culture information and combined Culture Contents.