• Title/Summary/Keyword: RANK

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WILCOXON SIGNED RANK TEST USING RANKED-SET SAMPLE

  • Kim, Dong-Hee;Kim, Young-Cheol
    • Journal of applied mathematics & informatics
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    • v.3 no.2
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    • pp.235-244
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    • 1996
  • Ranked-set sampling is useful when measurements are destructive or costly to obtain but ranking of the observations is rel-atively easy. The Wilcoxon signed rank test statistic based on the ranked-set sample is considered. We compared the asymptotic relative efficiencies of the RSS Wilcoxon signed rank test statistics with respect to the SRS Wilcoxon signed rank test statistic and the RSS sign test statistic. Throughout the ARE's the proposed test statistic is superior to the SRS Wilcoxxon signed rank test statistic and the RSS sign test statistic.

Signal Detection in Non-Additive Noise Using Rank Statistics: Signal-Dependent Noise and Random Signal Detection (비가산성 잡음에서 순위 통계량을 이용한 신호 검파 : 신호의존성 잡음과 확률 신호 검파)

  • 송익호;김상엽;김선용;손재철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.15 no.11
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    • pp.955-961
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    • 1990
  • Test statistics are obtained for detection of weak signals in signal-dependent noise using rank statistics. A generalized model is used in this paper in order to consider non-additivenoise as well as purely-additive noise. Locally optimum rank detectors for the model are shown to have similarity to locally optimum detectors and to be generalizations of these for the purely-additive noise model. A similar result is obtained for multi-input cases.

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Monitoring of Gene Regulations Using Average Rank in DNA Microarray: Implementation of R

  • Park, Chang-Soon
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1005-1021
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    • 2007
  • Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

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Multi-Objective Controller Design using a Rank-Constrained Linear Matrix Inequality Method (계수조건부 LMI를 이용한 다목적 제어기 설계)

  • Kim, Seog-Joo;Kim, Jong-Moon;Cheon, Jong-Min;Kwon, Soon-Mam
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.1
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    • pp.67-71
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    • 2009
  • This paper presents a rank-constrained linear matrix inequality (LMI) approach to the design of a multi-objective controller such as $H_2/H_{\infty}$ control. Multi-objective control is formulated as an LMI optimization problem with a nonconvex rank condition, which is imposed on the controller gain matirx not Lyapunov matrices. With this rank-constrained formulation, we can expect to reduce conservatism because we can use separate Lyapunov matrices for different control objectives. An iterative penalty method is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method.

CHARACTERIZATIONS OF BOOLEAN RANK PRESERVERS OVER BOOLEAN MATRICES

  • Beasley, Leroy B.;Kang, Kyung-Tae;Song, Seok-Zun
    • The Pure and Applied Mathematics
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    • v.21 no.2
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    • pp.121-128
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    • 2014
  • The Boolean rank of a nonzero m $m{\times}n$ Boolean matrix A is the least integer k such that there are an $m{\times}k$ Boolean matrix B and a $k{\times}n$ Boolean matrix C with A = BC. In 1984, Beasley and Pullman showed that a linear operator preserves the Boolean rank of any Boolean matrix if and only if it preserves Boolean ranks 1 and 2. In this paper, we extend this characterization of linear operators that preserve the Boolean ranks of Boolean matrices. We show that a linear operator preserves all Boolean ranks if and only if it preserves two consecutive Boolean ranks if and only if it strongly preserves a Boolean rank k with $1{\leq}k{\leq}min\{m,n\}$.

Development of An Automatic Incident Detection Model Using Wilcoxon Rank Sum Test (Wilcoxon Rank Sum Test 기법을 이용한 자동돌발상황검지 모형 개발)

  • 이상민;이승환
    • Journal of Korean Society of Transportation
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    • v.20 no.6
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    • pp.81-98
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    • 2002
  • 본 연구는 Wilcoxon Rank Sum Test 기법을 이용한 자동 돌발상황 검지 모형을 개발하는 것이다. 본 연구의 수행을 위하여 고속도로에 설치된 루프 차량 검지기(Loop Vehicle Detection System)에서 수집된 점유율 데이터를 사용하였다. 기존의 검지모형은 산정하기가 까다로운 임계치에 의하여 돌발상황을 검지하는 방식이었다. 반면 본 연구 모델은 위치와 시간대 교통 패턴에 관계없이 모형을 일정하게 적용하며, 지속적으로 돌발상황 지점과 상·하류의 교통패턴을 비교 검정 기법인 Wilcoxon Rank Sum Test 기법을 사용하여 돌발상황 검지를 수행하도록 하였다. 연구모형의 검증을 위한 테스트 결과 시간과 위치에 관계없이 정확하고 빠른 검지시간(돌발 상황 발생 후 2∼3분)을 가짐을 알 수 있었다. 또한 기존의 모형인 APID, DES, DELOS모형과 비교검증을 위하여 검지율 및 오보율 테스트를 수행한 결과 향상된 검지 능력(검지율 : 89.01%, 오보율 : 0.97%)을 나타남을 알 수 있었다. 그러나 압축파와 같은 유사 돌발상황이 발생되면 제대로 검지를 하지 못하는 단점을 가지고 있으며 향후 이에 대한 연구가 추가된다면 더욱 신뢰성 있는 검지모형으로 발전할 것이다.

An Implementation of the Ranking Algorithm for Web Documents based on Link Analysis (링크 분석에 기반한 웹 문서 중요도 평가 알고리즘의 구현)

  • Lim, Sung-Chae
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2010.07a
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    • pp.75-78
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    • 2010
  • 웹 검색에는 기존의 정보검색(Information Retrieval) 시스템에서와 다르게 문서 간 하이퍼링크 정보를 바탕으로 각 웹 문서의 고유 중요도를 추정하는 방식이 자주 이용된다. 링크 분석에 기반한 알고리즘 중 PageRank 알고리즘은 구글의 웹 검색 서비스에 적용된 것으로 알려져 있다. 이런 PageRank 알고리즘에 따라 중요도를 계산하는 경우 색인된 웹 문서수가 증가함에 따라 계산에 필요한 CPU 자원의 사용도 함께 증가하며, 문서 수가 수 억 페이지에 달하면 하나의 서버에서는 계산을 수행할 수 없다는 문제가 있다. 본 논문에서는 이런 문제점을 해소하기 위해 여러 대의 서버를 PageRank 계산 용 클러스터로 사용할 수 있는 방법을 제시한다. 제시된 방법은 고속의 LAN을 이용하여 여러 대의 서버를 연결하고 반복적인 행렬 계산을 병렬로 수행할 수 있어 계산 시간을 단축시킬 수 있다. 이런 서버 클러스터 구현을 위해 멀티 쓰레딩 프로그램이 작성되었으며, PageRank 계산에 사용되는 행렬 데이터를 적은 양의 메모리만으로 표현 가능하도록 하였다.

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Factor Rank and Its Preservers of Integer Matrices

  • Song, Seok-Zun;Kang, Kyung-Tae
    • Kyungpook Mathematical Journal
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    • v.46 no.4
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    • pp.581-589
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    • 2006
  • We characterize the linear operators which preserve the factor rank of integer matrices. That is, if $\mathcal{M}$ is the set of all $m{\times}n$ matrices with entries in the integers and min($m,n$) > 1, then a linear operator T on $\mathcal{M}$ preserves the factor rank of all matrices in $\mathcal{M}$ if and only if T has the form either T(X) = UXV for all $X{\in}\mathcal{M}$, or $m=n$ and T(X)=$UX^tV$ for all $X{\in}\mathcal{M}$, where U and V are suitable nonsingular integer matrices. Other characterizations of factor rank-preservers of integer matrices are also given.

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Combustion Technology for Low Rank Coal and Coal-Biomass Co-firing Power Plant (저급탄 석탄화력 및 석탄-바이오매스 혼소 발전을 위한 연소 기술)

  • Lee, Donghun;Ko, Daeho;Lee, Sunkeun;Baeg, Guyeol
    • 한국연소학회:학술대회논문집
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    • 2013.06a
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    • pp.129-132
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    • 2013
  • The low rank coal combustion and biomass-coal co-firing characteristics were reviewed on this study for the power plant construction. The importance of using low rank coal(LRC) for power plant is increasing gradually due to power generation economy and biomass co-firing is also concentrated as power source because it has carbon neutral characteristics to reduce green-house effect. The combustion characteristics of low rank coal and biomass for a 310MW coal firing power plant and a 100MW biomass and coal co-firing power plant were studied to apply into actual power plant design and optimized the furnace and burner design.

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Low-Rank Representation-Based Image Super-Resolution Reconstruction with Edge-Preserving

  • Gao, Rui;Cheng, Deqiang;Yao, Jie;Chen, Liangliang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.9
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    • pp.3745-3761
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    • 2020
  • Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.