• 제목/요약/키워드: national framework data

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우리나라 국가공간정보기반의 표준 설정방안 (Approach on the Development of Standards for Korean National Spatial Data Infrastructure)

  • 김감래;김명호;박준
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2003년도 추계학술발표회 논문집
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    • pp.335-340
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    • 2003
  • Our country is projected the technical development studies, constructed the digital maps, developed standards, established rules, and educated users during the first NGIS plan. This National Geospatial Information Infrastructure is proceeding with the program as arranged. In the second NGIS plan, our government try to construct the framework data for the maximization of GIS utilization. But National Geospatial Information Infrastructure included some problems from view of data framework particularly. In this paper, we make a comparative study of foreign countries, analyze the cause of our problem, and present the standards for Korean National Spatial Data Infrastructure.

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기본지리정보 항목별 구출 우선순위 평가에 관한 연구 (Prioritizing the Building Order of the Geographic Framework Data)

  • 최윤수;전철민;김건수
    • 한국측량학회지
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    • 제22권3호
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    • pp.269-275
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    • 2004
  • 지리정보는 도시 및 국토의 이용 및 관리, 도시계획, 환경 및 재난관리, 교통ㆍ물류 등 국가, 공공기관뿐만 아니라 실생활에서도 광범위하게 활용되고 있다. 그러나 다양한 방법으로 각자의 필요성에 의하여 지리정보를 구축하고 있어 데이터간의 불일치, 불필요한 비용의 중복투자, 의사결정의 어려움 등의 문제점이 발생하였다. 이러한 문제점을 해결하기 위하여 국가적 차원에서 모든 지리정보를 공동으로 활용하기 위한 기본지리정보구축의 필요성이 대두되었다. 이에 따라 기본지리정보는 국가지리정보체계의구축및활용에관한법률에 8개 분야가 선정되었고 기본지리정보구축 추진협의회 협의를 거쳐 8개 분야의 세부 항목으로 19개 항목이 협의ㆍ선정되었다. 본 연구는 계층분석(Analytical Hierarchy Process)과 의사결정나무분석을 이용하여 19개 항목(도로, 철도, 해안선, 측량기준점 등)간의 상대적 중요도를 도출하였고 도출된 중요도에 따라 각 항목의 구축 우선순위를 그룹화하여 제시하였다. 본 연구 결과를 적용하여 기본지리정보 구축시 사업의 우선순위를 정하고 그 순위에 따라 추진함으로써 국가 예산을 효율적으로 집행할 수 있을 것으로 기대된다.

빅데이터 시장 분석을 위한 에코시스템 설계 (Design of Ecosystems to Analyze Big Data Market)

  • 이상원;박승범;신성윤
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2014년도 제49차 동계학술대회논문집 22권1호
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    • pp.433-434
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    • 2014
  • Big Data services is composed of Big Data user, Big Data service provider, and Big Data application provider. And it is possible to extend the service to interplay-reciprocal actions among three subjects such as providing, being provided, connecting, being connected, and so on. In this paper, we propose an ecosystems of Big Data and a framework of its service.

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Environment of Doing Business in East Asia : South Korean Experience

  • Malek, Jihene
    • 산경연구논집
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    • 제7권1호
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    • pp.19-25
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    • 2016
  • Purpose - The purpose of this paper is to aim to stress the importance of doing business environment in South Korean economy. The theoretical justification is based on neo-institutional theories and new business management including Porter's Model as main justifications of state intervention due to the market failures to promote a competitive environment of doing business. Research design, data and methodology - The methods to be taken is to provide a comparative performance analysis, and offer in terms of doing business and economic freedom sub-index complemented by Korean reforms diagnostics. Results - The main results underlined the key factors explain the success of business environment in South Korea such as: a simplified registration procedures, a target tax incentives, the removal of business barriers, the improvement of legislative and regulatory framework, target reforms, property right and technical norms, good governance and the quality of institution, a role of a well-functioning legal framework, a strong competition framework, and the transparency of regulation, etc. Conclusion - A competitive environment of doing business is based on the target national strategies, appropriate reforms responding to national needs and good governance system.

Dynamic reliability analysis framework using fault tree and dynamic Bayesian network: A case study of NPP

  • Mamdikar, Mohan Rao;Kumar, Vinay;Singh, Pooja
    • Nuclear Engineering and Technology
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    • 제54권4호
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    • pp.1213-1220
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    • 2022
  • The Emergency Diesel Generator (EDG) is a critical and essential part of the Nuclear Power Plant (NPP). Due to past catastrophic disasters, critical systems of NPP like EDG are designed to meet high dependability requirements. Therefore, we propose a framework for the dynamic reliability assessment using the Fault Tree and the Dynamic Bayesian Network. In this framework, the information of the component's failure probability is updated based on observed data. The framework is powerful to perform qualitative as well as quantitative analysis of the system. The validity of the framework is done by applying it on several NPP systems.

DEVELOPMENT OF STATE-LEVEL APPRAISAL INDICATORS OF SUSTAINABLE CONSTRUCTION IN TAIWAN

  • Rong-Yau Huang;Wei-Ting Hsu
    • 국제학술발표논문집
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    • The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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    • pp.292-298
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    • 2011
  • In this study we examine Taiwan's overall performance in accordance with sustainable construction by developing an appraisal indicator framework. The framework consists of five layers, from bottom to top: the indicator; the indicator category; the core cluster; the theme; and the overall performance. The procedure for the development of a sustainable construction indicator system is outlined. Finally, a framework consists of 3 themes, 10 core clusters, and 33 indicator categories are established. Following the established framework, 67 proper indicators are selected for each category in the framework, and data of the 53 indicators are collected respectively from a nation's statistical databank in Taiwan. Sustainable construction index aggregated step-by-step from the indicators, the indicator categories, the core clusters and the themes is computed to assess Taiwan's progress in sustainable construction. The preliminary results and the discussion are reported.

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Research on Forecasting Framework for System Marginal Price based on Deep Recurrent Neural Networks and Statistical Analysis Models

  • Kim, Taehyun;Lee, Yoonjae;Hwangbo, Soonho
    • 청정기술
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    • 제28권2호
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    • pp.138-146
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    • 2022
  • Electricity has become a factor that dramatically affects the market economy. The day-ahead system marginal price determines electricity prices, and system marginal price forecasting is critical in maintaining energy management systems. There have been several studies using mathematics and machine learning models to forecast the system marginal price, but few studies have been conducted to develop, compare, and analyze various machine learning and deep learning models based on a data-driven framework. Therefore, in this study, different machine learning algorithms (i.e., autoregressive-based models such as the autoregressive integrated moving average model) and deep learning networks (i.e., recurrent neural network-based models such as the long short-term memory and gated recurrent unit model) are considered and integrated evaluation metrics including a forecasting test and information criteria are proposed to discern the optimal forecasting model. A case study of South Korea using long-term time-series system marginal price data from 2016 to 2021 was applied to the developed framework. The results of the study indicate that the autoregressive integrated moving average model (R-squared score: 0.97) and the gated recurrent unit model (R-squared score: 0.94) are appropriate for system marginal price forecasting. This study is expected to contribute significantly to energy management systems and the suggested framework can be explicitly applied for renewable energy networks.

A case study of ECN data conversion for Korean and foreign ecological data integration

  • Lee, Hyeonjeong;Shin, Miyoung;Kwon, Ohseok
    • Journal of Ecology and Environment
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    • 제41권5호
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    • pp.142-144
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    • 2017
  • In recent decades, as it becomes increasingly important to monitor and research long-term ecological changes, worldwide attempts are being conducted to integrate and manage ecological data in a unified framework. Especially domestic ecological data in South Korea should be first standardized based on predefined common protocols for data integration, since they are often scattered over many different systems in various forms. Additionally, foreign ecological data should be converted into a proper unified format to be used along with domestic data for association studies. In this study, our interest is to integrate ECN data with Korean domestic ecological data under our unified framework. For this purpose, we employed our semi-automatic data conversion tool to standardize foreign data and utilized ground beetle (Carabidae) datasets collected from 12 different observatory sites of ECN. We believe that our attempt to convert domestic and foreign ecological data into a standardized format in a systematic way will be quite useful for data integration and association analysis in many ecological and environmental studies.

Content Distribution for 5G Systems Based on Distributed Cloud Service Network Architecture

  • Jiang, Lirong;Feng, Gang;Qin, Shuang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권11호
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    • pp.4268-4290
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    • 2015
  • Future mobile communications face enormous challenges as traditional voice services are replaced with increasing mobile multimedia and data services. To address the vast data traffic volume and the requirement of user Quality of Experience (QoE) in the next generation mobile networks, it is imperative to develop efficient content distribution technique, aiming at significantly reducing redundant data transmissions and improving content delivery performance. On the other hand, in recent years cloud computing as a promising new content-centric paradigm is exploited to fulfil the multimedia requirements by provisioning data and computing resources on demand. In this paper, we propose a cooperative caching framework which implements State based Content Distribution (SCD) algorithm for future mobile networks. In our proposed framework, cloud service providers deploy a plurality of cloudlets in the network forming a Distributed Cloud Service Network (DCSN), and pre-allocate content services in local cloudlets to avoid redundant content transmissions. We use content popularity and content state which is determined by content requests, editorial updates and new arrivals to formulate a content distribution optimization model. Data contents are deployed in local cloudlets according to the optimal solution to achieve the lowest average content delivery latency. We use simulation experiments to validate the effectiveness of our proposed framework. Numerical results show that the proposed framework can significantly improve content cache hit rate, reduce content delivery latency and outbound traffic volume in comparison with known existing caching strategies.