• Journal of Scientific & Technological Knowledge Infrastructure
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• s.6
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• pp.18-27
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• 2001

XML은 임의 형태 문서, 임의 응용에 대해 일반화 마크업(Markup)을 정의하기 위한 방법을 표준화하는 메타 언어(Meta Language)로서 기술적 문서 마크업을 생성하는 기법과 문서의 지능적 내용이나 체계를 정의하기 위한 언어를 제공하며, 다양한 응용들 사이에 구조화된 데이터를 상호 교환하기 위한 도구와 다양한 입력으로부터 출력의 내용, 구조, 조직을 표준화하기 위한 방법을 제공한다.

• Journal of Scientific & Technological Knowledge Infrastructure
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• s.9
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• pp.60-65
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• 2002

지식 정보의 생산을 활성화하기 위해서는 데이터의 수집 및 생성, 가공, 관리, 검색하는 기술과 지식정보와 지식 정보간의 연동, 지식정보와 이용자간의 유통 등의 지식정보 시스템과 관련된 기술을 상호 호환할 수 있도록 이에 관한 적절한 지침 및 표준이 필요하다.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.100-112
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• 2021

With the recent growth of the big data technology market, interest in visualization technology has steadily increased over the past few years. Data visualization is currently used in a wide range of disciplines such as information science, computer science, human-computer interaction, statistics, data mining, cartography, and journalism, each with a slightly different meaning. Big data visualization in smart cities that require multidisciplinary research enables an objective and scientific approach to developing user-centered smart city services and related policies. In particular, spatial-based data visualization enables efficient collaboration of various stakeholders through visualization data in the process of establishing city policy. In this paper, a user-centered spatial big data visualization expression request method was derived by examining the spatial-based big data visualization expression process and principle from the viewpoint of effective information delivery, not just a visualization tool.

• Journal of the Korean Society for information Management
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• v.37 no.4
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• pp.1-26
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• 2020

In today's increasingly data-intensive academic environment, data is becoming the foundation of academic communication as a research outcome rather than a research by-product. However, there is a limit to guaranteeing actual data reuse only by expanding the data supply or securing accessibility. In order to overcome this, it is necessary to understand the data reuse behavior and data needs in-depth. Therefore, this study attempted to identify the major data reuse behavior and data needs among researchers. To this end, the authors of KCI papers among the data reuse documents of the Korea Social Science Data Archive (KOSSDA) for the past 3 years were targeted. An in-depth interview was conducted with 12 researchers who accepted the interview. As a result, factors considered when reusing data were personal, economic, technical, and social aspects, and it was found that the data itself was used or contextual information of the data was used depending on the purpose of data reuse. The path to acquiring data is a web-based source of information, and a path through informal communication can also be found. In terms of the data needs, it was found that they prefer English, the United States, and institutional producers. Also they have a clear preference for quantitative data from an interviewer-filled interpersonal interview survey method, rich metadata along with raw data, and data that contains identification information. However, due to the lack of confidence in the value, it is negative for the use of data with controlled access and use, and it is difficult to confirm a clear preference because there is no similar data available for selection in terms of size and freshness.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.23-24
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• 2016

본 논문에서는 과학 데이터 특성을 고려한 아카이브 시스템 설계를 위한 Data Curation Profile을 분석한다. Data Curation Profile은 생명과학데이터, 천문우주 데이터, 지질 데이터화학데이터, 사회과학데이터 등과 같은 13개의 과학데이터로 이루어져 있다. 13개의 과학데이터의 분석된 내용을 바탕으로 아카이브 시스템 설계시 고려해야 할 과학데이터 특성을 도출하고 이를 아카이브 요소 기술과 연계한다.

• The Journal of Bigdata
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• v.6 no.2
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• pp.71-84
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• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.15-24
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• 2008

The data delivery confirmation method of MIL-STD-188-220C, which is a tactical wireless mobile Ad-Hoc communication protocol, is that a source node requires the end-to-end ack from all destination nodes and the data-link ack from 1-hop neighboring destination nodes and relaying nodes, regardless of the hop distance from a source node to destination nodes. This method has the problem to degrade the whole communication network performance because of excessive data traffic due to the duplicate use of end-to-end ack and data-link ack, and the collision among end-to-end acks on the wireless network in the case of confirming a data delivery within an 1-hop distance. In order to solve this problem, this paper has proposed the method to perform the data delivery confirmation with the improvement of communication network performance through the data traffic reduction by achieving the reliable data delivery confirmation requiring the only data-link ack within an 1-hop distance. The effects of the proposed method are analyzed in the two aspects of the data delivery confirmation delay time and the data delivery confirmation success ratio.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.881-886
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• 2018

Over the last several decades, the advances in computer engineering technology have led a new paradigm of data-intensive research in the field of scientific applications. A collaborative work environment for storing, sharing and analyzing data is required for researchers of geographical distance. The Korean government supports the Research & Education network(KREONET) and the Global Science experimental Data hub Center(GSDC) to strengthen the nation's competitiveness. The KREONET has upgraded its backbone to 100Gbps to accommodate demand to transfer data fast among the global major experimental sites. This paper introduces the test result between high performance nodes reserved for big data transfer.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.663-670
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• 2022

This study presents the method for integrating the software assets acquired before the weapon system software reliability test was not formed in the weapon system software development and management manual through JTDLS Batch II case. This paper describes the problems for applying manual's direction to JTDLS Batch II project, and decisions and expected effects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.523-533
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• 2019

The convergence of engineering and IT technology has brought many changes to the industry as well as academic research. In particular, computer simulation technology has evolved to a level that can accurately simulate actual physical phenomena and analyze them in real time. In this paper, we describe the CFD technology, which is mainly used in industry, and the post processor that uses the augmented reality which is emerging as the post-processing. Research on the visualization of fluid simulation results using AR technology is actively being carried out. However, due to the large size of the result data, it is limited to researches that are published in a desktop environment. Therefore, it is limitation that needs to be reviewed in actual space. In this paper, we discuss how to solve these problems. We analyze the fluid analysis results in the post-processing, and then perform optimizing data (more than 70%)to support operation in the mobile environment. In the visualization, lightweight data is used to perform real-time tracking using cloud computing, The analysis result is matched to the screen and visualized. This allows the user to review and analyze the fluid analysis results in an efficient and immersive manner in the various spaces where the simulation is performed.