• Title/Summary/Keyword: R-Map

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Hadoop and MapReduce (하둡과 맵리듀스)

  • Park, Jeong-Hyeok;Lee, Sang-Yeol;Kang, Da Hyun;Won, Joong-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.5
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    • pp.1013-1027
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    • 2013
  • As the need for large-scale data analysis is rapidly increasing, Hadoop, or the platform that realizes large-scale data processing, and MapReduce, or the internal computational model of Hadoop, are receiving great attention. This paper reviews the basic concepts of Hadoop and MapReduce necessary for data analysts who are familiar with statistical programming, through examples that combine the R programming language and Hadoop.

LIFTING T-STRUCTURES AND THEIR DUALS

  • Yoon, Yeon Soo
    • Journal of the Chungcheong Mathematical Society
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    • v.20 no.3
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    • pp.245-259
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    • 2007
  • We define and study a concept of $T^f$-space for a map, which is a generalized one of a T-space, in terms of the Gottlieb set for a map. We show that X is a $T_f$-space if and only if $G({\Sigma}B;A,f,X)=[{\Sigma}B,X]$ for any space B. For a principal fibration $E_k{\rightarrow}X$ induced by $k:X{\rightarrow}X^{\prime}$ from ${\epsilon}:PX^{\prime}{\rightarrow}X^{\prime}$, we obtain a sufficient condition to having a lifting $T^{\bar{f}}$-structure on $E_k$ of a $T^f$-structure on X. Also, we define and study a concept of co-$T^g$-space for a map, which is a dual one of $T^f$-space for a map. We obtain a dual result for a principal cofibration $i_r:X{\rightarrow}C_r$ induced by $r:X^{\prime}{\rightarrow}X$ from ${\iota}:X^{\prime}{\rightarrow}cX^{\prime}$.

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MRSPAKE : A Web-Scale Spatial Knowledge Extractor Using Hadoop MapReduce (MRSPAKE : Hadoop MapReduce를 이용한 웹 규모의 공간 지식 추출기)

  • Lee, Seok-Jun;Kim, In-Cheol
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.11
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    • pp.569-584
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    • 2016
  • In this paper, we present a spatial knowledge extractor implemented in Hadoop MapReduce parallel, distributed computing environment. From a large spatial dataset, this knowledge extractor automatically derives a qualitative spatial knowledge base, which consists of both topological and directional relations on pairs of two spatial objects. By using R-tree index and range queries over a distributed spatial data file on HDFS, the MapReduce-enabled spatial knowledge extractor, MRSPAKE, can produce a web-scale spatial knowledge base in highly efficient way. In experiments with the well-known open spatial dataset, Open Street Map (OSM), the proposed web-scale spatial knowledge extractor, MRSPAKE, showed high performance and scalability.

Derivation of information for R&D management with technology relation analysis (기술연관분석을 이용한 연구개발 의사결정 정보 도출 - 한국가스공사 연구개발사업 적용을 중심으로 -)

  • 오경준
    • Journal of Korea Technology Innovation Society
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    • v.3 no.3
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    • pp.67-84
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    • 2000
  • This paper expanded the usefulness of technology relation analysis by applying to R&D activities of Korea Gas Corporation (Kogas) at the corporate level. Technology relation analysis has been applied to assessment of R&D investments in telecommunication and construction industries in Korea. As empirical findings, technology map and technology spillover matrix of Kogas have been derived by technology similarity analysis. It has bee found that various useful information for R&D assessment could be acquired from the technology relation analysis at the corporate level.

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Effective Object Recognition based on Physical Theory in Medical Image Processing (의료 영상처리에서의 물리적 이론을 활용한 객체 유효 인식 방법)

  • Eun, Sung-Jong;WhangBo, Taeg-Keun
    • The Journal of the Korea Contents Association
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    • v.12 no.12
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    • pp.63-70
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    • 2012
  • In medical image processing field, object recognition is usually processed based on region segmentation algorithm. Region segmentation in the computing field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on R2-map information within the magnetic resonance (MR) theory. In this study, the experiment had been conducted using images including the liver region and by setting up feature points of R2-map as seed points for 2D region growing and final boundary correction to enable region segmentation even when the border line was not clear. As a result, an average area difference of 7.5%, which was higher than the accuracy of conventional exist region segmentation algorithm, was obtained.

The Mid-long Range R&D Planning of Railway Technology and Policy Recommendations (철도기술 연구개발 중장기계획수립($2008{\sim}2012$)결과와 정책적 시사점)

  • Park, Man-Soo;Park, Su-Dong;Yu, Sung-Yun;Kim, Jong-Wook
    • Proceedings of the KSR Conference
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    • 2007.11a
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    • pp.1796-1816
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    • 2007
  • Recently, started to apply a strategy of selection and concentration in the construction and transportation R&D for the effective utilization of limited R&D resources. The department of construction and transportation planned the construction and transportation R&D innovative road map by the future 10 years technical requirement under the first year on the innovation of the construction and transportation technology from last year. The innovative road map which is a strategic and long term master plan integrated a construction and transportation suggested a vision as value createar for a improvement of living quality in the future. And made a specific goal that is the seventh construction technology level and the fifth transportation technology level in the world. The department of construction and transportation is planning a mid- long range planing of the construction and transportation R&D as following measurement of innovative road map. KICTEP and KISTEP planned a mid- long range R&D planing of the transportation system, logistics, aviation, railway for the last year. Introducing a methodology used a mid- long range plan and main results of the future railway R&D plan. And suggesting a politic comments for the effectively propelling railway R&D projects.

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The LR-Tree : A spatial indexing of spatial data supporting map generalization (LR 트리 : 지도 일반화를 지원하는 공간 데이터를 위한 공간 인덱싱)

  • Gwon, Jun-Hui;Yun, Yong-Ik
    • The KIPS Transactions:PartD
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    • v.9D no.4
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    • pp.543-554
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    • 2002
  • GIS (Geographic Information Systems) need faster access and better visualization. For faster access and better visualization in GIS, map generalization and levels of detail are needed. Existing spatial indexing methods do not support map generalization. Also, a few existing spatial indexing methods supporting map generalization do not support ail map generalization operations. We propose a new index structure, i.e. the LR-tree, supporting ail map generalization operations. This paper presents algorithms for the searching and updating the LR-tree and the results of performance evaluation. Our index structure works better than other spatial indexing methods for map generalization.

Feature Points Detection based on R2-map for Efficiency Liver Recognition (효율적인 간 인식을 위한 R2-map 기반의 특징점 검출 방법)

  • Eun, Sung-Jong;WhangBo, Taeg-Keun
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06c
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    • pp.385-387
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    • 2012
  • MR 영상에서 간의 인식은 간에 존재하는 질병을 파악하는 것뿐만 아니라 간에 대한 치료 방법이나 수술방법을 결정하는 중요한 정보를 제공한다. 이러한 일반적인 간의 인식 방법은 영역 분할 알고리즘을 기반으로 처리되어진다. IT분야에서의 영역 분할 알고리즘은 대부분 밝기 정보, 형태 정보, 패턴 분석 등 다양한 입력 정보의 컴퓨팅 처리를 통해 처리되어 진다. 그러나 이러한 컴퓨팅 방법으로는 앞서 언급된 입력정보들이 의미가 없을 경우, 영역 분할에 많은 제약이 따르게 된다. 따라서 본 논문은 이러한 컴퓨팅 처리의 근본적인 제약사항을 해결하고자, MR 이론의 R2-map정보 기반의 효과적인 영역 분할 방법은 제안하였다. 본 방법은 간 영역이 포함된 영상에서 실험하였으며, R2-map맵의 일부 특징점을 Region growing의 Seed point로 설정하여 경계가 모호하더라도 영역 분할이 가능하게끔 하였다. 해당 영상의 실험 결과 8.5%의 평균 오차로 일반적인 영역 분할 알고리즘에 비해 높은 정확도가 산출되었다.