• The Korean Journal of Air & Space Law and Policy
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• v.17
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• pp.111-132
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• 2003

The air transport industry is the most important as means of human exchange between the countries. Because the spread effect and the durability by aviation cooperation between the countries are much higher than any other industry, a research about air transport industry is very important to allied industry field as well as national policy about International cooperation and integration. Specially, according to the economic interchange with North Korea becomes active, the role of air transport as related traffic network with North Korea becomes more important. The number of flights is increasing sharply after South-North summit meeting, and two sides established and are using temporary direct route between South-North Korea. When we consider that the number of flights utilizing temporary direct route is increasing every year, It is not desirable to use temporary routes continuously because the current agreement between South and North cant be reliable far the case of unexpected circumstance. In addition, the current agreement is not based on the international standards. The paper is to study the condition to promote the coordination of civil aviation in the whole Korean peninsula. As known, the aviation system in North Korea is mainly operated by military unit. The study will review the current status of air transport system of South and North and the effective way of cooperation of civil aviation between both sides. The cooperation between governments as well as between airlines is studied. The establishment of Air Traffic Service Agreement is going to be handled heavily because the stable air traffic service is the most required base for the operation of air transport. The authors also try to find a way to support the development of infrastructure of aviation industry in North Korea.

• Journal of the Korean association of regional geographers
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• v.12 no.5
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• pp.540-556
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• 2006

The purpose of this paper is to analyze a process of formation of an ethnic community in the global era, taking an example of foreign workers in Igok-Dong, Dalseo-gu, Taegu. Previous studies suggest that playing a role as a hub of culture, resources and ethnic networks an ethnic community becomes an imagined space where its members can feel "us". Through this imagined space, ethnic people communicate and exchange information with each other and establish transnational linkages between their origin and destination countries or the third countries. In my research in Igok-Dong it was observed that ethnic shops had become the centers of the community of foreign workers and helped them connect with their own ethnic people from wider areas than their residence. Partly because of such networks exclusively focused on their own ethnics, there was little connection developed between foreign workers and locals. A social distance between the two parties may turn into antagonism as the ethnic community grows in number. Since it is foreseen that demands for foreign workers will continue to rise in Igok-Dong it is necessary to seek ways to achieve a more inclusive and harmonious multi-ethnic society for both foreign workers and locals.

• Journal of the Korean association of regional geographers
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• v.9 no.4
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• pp.505-518
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• 2003

The purpose of this paper is to review Post-Fordist urban economic theories that have tackled the recent changes of urban economies in large cities in the world since 1980s, so that we can conceptualise the changes of urban economies in Korean cities. In the perspective of the Post-Fordist urban economic theories, the recent changes of urban economies in the world are deeply related to the transformation of capitalist world economic system from Fordism to Post-Fordism. To see these changes which can be called as the new urbanization process in the economic aspect, we will focus especially such theories as new industrial space (district) theory based on the flexible specialization paradigm, informational city theory based on the information and communication mode paradigm, and cluster and regional innovation theory based on the institution and network paradigm. Also we will consider the social polarization process and dual city phenomena that have been observed for the most part of big cities in the world.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.4
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• pp.277-286
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• 2002

Most of the problems in dealing with the tunnel construction are the uncertainties and complexities of the stress conditions and rock strengths in ahead of the tunnel excavation. The limitations on the investigation technology, inaccessibility of borehole test in mountain area and public hatred also restrict our knowledge on the geologic conditions on the mountainous tunneling area. Nevertheless an extensive and superior geophysical exploration data is possibly acquired deep within the mountain area, with up to the tunnel locations in the case of alternative design or turn-key base projects. An appealing claim in the use of artificial neural networks (ANN) is that they give a more trustworthy results on our data based on identifying relevant input variables such as a little geotechnical information and biological learning principles. In this study, error back-propagation algorithm that is one of the teaching techniques of ANN is applied to presupposition on Rock Mass Ratings (RMR) for unknown tunnel area. In order to verify the applicability of this model, a 4km railway tunnel's field data are verified and used as input parameters for the prediction of RMR, with the learned pattern by error back propagation logics. ANN is one of basic methods in solving the geotechnical uncertainties and helpful in solving the problems with data consistency, but needs some modification on the technical problems and we hope our study to be developed in the future design work.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.140-148
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• 2009

Recent advances in communication and multimedia technologies make it possible to provide video-on-demand(VOD) services and people can access video servers over the Internet at any time using their electronic devices, such as PDA, mobile phone and digital TV. Each device has different processing capabilities, energy budgets, display sizes and network connectivities. To support such diverse devices, multiple versions of videos are needed to meet users' requests. In general cases, VOD servers cannot store all the versions of videos due to the storage limitation. When a device requests a stored version, the server can send the appropriate version immediately, but when the requested version is not stored, the server first converts some stored version to the requested version, and then sends it to the client. We call this conversion process transcoding. If transcoding occurs frequently in a VOD server, the CPU resource of the server becomes insufficient to response to clients. Thus, to admit as many requests as possible, we need to maximize the CPU availability. In this paper, we propose a new algorithm to select versions from those stored on disk using a branch and bound technique to maximize the CPU availability. We also explore the impact of these storage management policies on streaming to heterogeneous users.

• The KIPS Transactions:PartC
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• v.11C no.6 s.95
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• pp.843-850
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• 2004

As mobile devices prevail, requests for various services using mobile devices have increased. Requests for application services that require large data space such as multimedia, game and database [1] specifically have greatly increased. However, mobile appliances have difficulty in applying various services like a wire environment, because the storage capacity of one is not enough. Therefore, research (5) which provides remote storage service for mobile appliances using iSCSI is being conducted to overcome storage space limitations in mobile appliances. But, when iSCSI is applied to mobile appliances, iSCSI I/O performance drops rapidly if a iSCSI client moves from the server to a far away position. In the case of write operation, $28\%$ reduction of I/O performance occurred when the latency of network is 64ms. This is because the iSCSI has a structural quality that is very .sensitive to delay time. In this paper, we will introduce an intermediate target server and localize iSCSI target to improve the shortcomings of iSCSI performance dropping sharply as latency increases when mobile appliances recede from a storage server.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.26-41
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• 2012

This study investigates the time-space characteristics of intra-urban passenger flows in the Metropolitan Seoul area. In particular, we analyze the relationships between transit ridership and land use through the use of the subway passenger flow data obtained from the transit transaction databases. For this purpose, the strength of each subway station, i.e., the number of total in-coming and out-going passengers at each station, in the morning, afternoon, and evening, is calculated and visualized, which reflects urban land use patterns. Then the subway stations are classified into four groups via a hierarchical analysis of the in-coming and out-going passenger flows at 353 stations. Each group appears to have characteristic properties according to the region, e.g., residential areas and central business districts. This has been confirmed by the analysis which probes explicitly the relationship between the local socio-economic variables and station groups. This analysis, disclosing the inter-relationship between the subway network and urban land use, may be useful at various stages in urban as well as transportation planning, and provides analytical tools for a wide spectrum of applications ranging from impact evaluation to decision-making and planning support.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.115-127
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• 2021

With the development of science and technology around the world, the realm of cyberspace, following land, sea, air, and space, is also recognized as a battlefield area. Accordingly, it is necessary to design and establish various elements such as definitions, systems, procedures, and plans for not only physical operations in land, sea, air, and space but also cyber operations in cyberspace. In this research, the importance of cyber targets that can be considered when prioritizing the list of cyber targets selected through intermediate target development in the target development and prioritization stage of targeting processing of cyber operations was selected as a factor to be considered. We propose a method to calculate the score for the cyber target and use it as a part of the cyber target prioritization score. Accordingly, in the cyber target prioritization process, the cyber target importance category is set, and the cyber target importance concept and reference item are derived. We propose a TIR (Target Importance Rank) algorithm that synthesizes parameters such as Event Prioritization Framework based on PageRank algorithm for score calculation and synthesis for each derived standard item. And, by constructing the Stuxnet case-based network topology and scenario data, a cyber target importance score is derived with the proposed algorithm, and the cyber target is prioritized to verify the proposed algorithm.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1693-1705
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• 2023

Rural areas, which account for about 90% of the country's land area, are increasing in importance and value as a space that performs various public functions. However, facilities that adversely affect residents' lives, such as livestock facilities, factories, and solar panels, are being built indiscriminately near residential areas, damaging the rural environment and landscape and lowering the quality of residents' lives. In order to prevent disorderly development in rural areas and manage rural space in a planned manner, detection and monitoring of hazardous facilities in rural areas is necessary. Data can be acquired through satellite imagery, which can be acquired periodically and provide information on the entire region. Effective detection is possible by utilizing image-based deep learning techniques using convolutional neural networks. Therefore, U-Net model, which shows high performance in semantic segmentation, was used to classify potentially hazardous facilities in rural areas. In this study, KOMPSAT ortho-mosaic optical imagery provided by the Korea Aerospace Research Institute in 2020 with a spatial resolution of 0.7 meters was used, and AI training data for livestock facilities, factories, and solar panels were produced by hand for training and inference. After training with U-Net, pixel accuracy of 0.9739 and mean Intersection over Union (mIoU) of 0.7025 were achieved. The results of this study can be used for monitoring hazardous facilities in rural areas and are expected to be used as basis for rural planning.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.