• 제목/요약/키워드: Data Component

검색결과 4,956건 처리시간 0.034초

Estimation of a Bivariate Exponential Distribution with a Location Parameter

  • 홍연웅;권용만
    • Journal of the Korean Data and Information Science Society
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    • 제13권2호
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    • pp.243-250
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    • 2002
  • This paper considers the problem of estimating parameters of the bivariate exponential distribution with a location parameter for a two-component shared parallel system using component data from system-level life test terminated at the time of the prespecified number of system failure. In the system-level life testing, there are three patterns of failure types ; 1) both component failed 2) both component censored 3) one is failed and the other is censored. In the third case, we assume that the failure time might be known or unknown. The maximum likelihood estimators are obtained for the case of known/unknown failure time when the other component is censored.

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도시철도 CBD 기반의 유지보수 BOM 시스템 개발 (Development of BOM System Using Component Based of Urban Transit)

  • 이호용;한석윤;박기준;서명원
    • 한국철도학회논문집
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    • 제7권4호
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    • pp.406-411
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    • 2004
  • BOM(Bill of Materials) is a listing or description of raw materials, parts, and assemblies that define a product. In order to evaluate the performance of proposed BOM management system, which is very important to maintenance information system of urban transit. We develop component based BOM data and rule-set to design data structure that is mutually independent and integrated efficiently. It divides data whit management interface using component technology. The component based master BOM have advantage in database size and flexibility. Flexibility is measured as the number of updating records in accordance with added new product or engineering change. In database size, component based BOM is the best. we develop master BOM management system in web environment.

Improvement on Fuzzy C-Means Using Principal Component Analysis

  • Choi, Hang-Suk;Cha, Kyung-Joon
    • Journal of the Korean Data and Information Science Society
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    • 제17권2호
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    • pp.301-309
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    • 2006
  • In this paper, we show the improved fuzzy c-means clustering method. To improve, we use the double clustering as principal component analysis from objects which is located on common region of more than two clusters. In addition we use the degree of membership (probability) of fuzzy c-means which is the advantage. From simulation result, we find some improvement of accuracy in data of the probability 0.7 exterior and interior of overlapped area.

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Evaluation of Water Quality Using Multivariate Statistic Analysis in Busan Coastal Area

  • Kim, Sang-Soo;Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • 제15권3호
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    • pp.531-542
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    • 2004
  • Principal component analysis and cluster analysis were conducted to comprehensively evaluate the water quality of Busan coastal area with the data collected seasonally by the analysis of surface water at 10 stations from 1997 to 2003. We noted that the first principal component was regarded as a factor related with the input of nutrient-rich fresh water and the second principal component as meteorological characteristics. Also we obtained that water qualities of station 4 and 9 were different from those of other stations in Busan coastal area.

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Numerical Investigations in Choosing the Number of Principal Components in Principal Component Regression - CASE II

  • Shin, Jae-Kyoung;Moon, Sung-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제10권1호
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    • pp.163-172
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    • 1999
  • We propose a cross-validatory method for the choice of the number of principal components in principal component regression based on the magnitudes of correlations with y. There are two different manners in choosing principal components, one is the order of eigenvalues(Shin and Moon, 1997) and the other is that of correlations with y. We apply our method to various data sets and compare results of those two methods.

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Efficient point cloud data processing in shipbuilding: Reformative component extraction method and registration method

  • Sun, Jingyu;Hiekata, Kazuo;Yamato, Hiroyuki;Nakagaki, Norito;Sugawara, Akiyoshi
    • Journal of Computational Design and Engineering
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    • 제1권3호
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    • pp.202-212
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    • 2014
  • To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components' accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components' accuracy by comparing each component's point cloud data scanned by laser scanners and the ship's design data formatted in CAD cannot be processed efficiently when (1) extract components from point cloud data include irregular obstacles endogenously, or when (2) registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles' shadows. The ICP (Iterative Closest Point) algorithm conducts a registration of the two sets of data after the proper registration's direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

DEVELOPMENT OF OPEN GIS COMPONENT SOFTWARE

  • Choi, Hae-Ock;Kim, Kwang-Soo;Lee, Jong-Hun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.188-193
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    • 1999
  • Technology of GIS evolved as a means of assembling and analyzing diverse spatial data. Many systems have been developed, and almost of systems are proprietary. There is a lots of lack of interoperability and reusability between them. This paper describes the development of Open GIS component software. The developing system have an end in view of GIS tool software which is interoperable and reusable. To increase the interoperability and reusability, the system is based on the OGC(Open GIS Consortium)'s Open GIS Simple Features Specification for OLE/COM. The OGC's specification is announced to increasing the full interoperability of various geospatial data and geoprocessing resources. With the Open specification, component based software ensures the reusability. We implement three kinds of component: Geometry component, Spatial Reference System Component, and MapBase Component. The first two components are compatible to the OGC's specification and the third one is designed to GIS tool software for variant GIS applications. The Open GIS component software system is developed on object-oriented computing environment, ATL/COM and Visual C++. As we made application programs using Visual Basic, the advantages of component based Open GIS software was proved.

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STUDY OF SPECTRAL ENERGY DISTRIBUTION OF GALAXIES WITH PRINCIPAL COMPONENT ANALYSIS

  • Kochi, Chihiro;Nakagawa, Takao;Isobe, Naoki;Shirahata, Mai;Yano, Kenichi;Baba, Shunsuke
    • 천문학논총
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    • 제32권1호
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    • pp.209-211
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    • 2017
  • We performed Principle Component Analysis (PCA) over 264 galaxies in the IRAS Revised Bright Galaxy Sample (Sanders et al., 2003) using 12, 25, 60 and $100{\mu}m$ flux data observed by IRAS and 9, 18, 65, 90 and $140{\mu}m$ flux data observed by AKARI. We found that (i)the first principle component was largely contributed by infrared to visible flux ratio, (ii)the second principal component was largely contributed by the flux ratio between IRAS and AKARI, (iii)the third principle component was largely contributed by infrared colors.

원전 신뢰도 DB 시스템을 이용한 표준형 원전 통합 기기 신뢰도 데이터 분석 및 적용 (An Integrated Approach of Component Reliability Data on Korea Standard Nuclear Power Plants Using PRinS)

  • 전호준;황석원;지문구
    • 한국안전학회지
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    • 제26권6호
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    • pp.85-89
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    • 2011
  • Component reliability data were analyzed by using PRinS(Plant Reliability data information System) based on the latest operating experiences of eight KSNPs(Korea Standard Nuclear Power plants), and these new data were applied to the KSNP PSA models. In addition, the existing PSA models were revised for reflecting as-built and as-operated plant conditions. As a result of newly performing PSA in this paper, CDF and LERF were estimated 26.1% and 18.2% lower than the existing values, respectively. It was identified that the risk measures decreased not because of revising the models but because of applying the new component reliability data. The result and the method of this paper could be used when generating plant specific data and performing the living PSA in the future.

Empirical decomposition method for modeless component and its application to VIV analysis

  • Chen, Zheng-Shou;Park, Yeon-Seok;Wang, Li-ping;Kim, Wu-Joan;Sun, Meng;Li, Qiang
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제7권2호
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    • pp.301-314
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    • 2015
  • Aiming at accurately distinguishing modeless component and natural vibration mode terms from data series of nonlinear and non-stationary processes, such as Vortex-Induced Vibration (VIV), a new empirical mode decomposition method has been developed in this paper. The key innovation related to this technique concerns the method to decompose modeless component from non-stationary process, characterized by a predetermined 'maximum intrinsic time window' and cubic spline. The introduction of conceptual modeless component eliminates the requirement of using spurious harmonics to represent nonlinear and non-stationary signals and then makes subsequent modal identification more accurate and meaningful. It neither slacks the vibration power of natural modes nor aggrandizes spurious energy of modeless component. The scale of the maximum intrinsic time window has been well designed, avoiding energy aliasing in data processing. Finally, it has been applied to analyze data series of vortex-induced vibration processes. Taking advantage of this newly introduced empirical decomposition method and mode identification technique, the vibration analysis about vortex-induced vibration becomes more meaningful.