• Title/Summary/Keyword: comparison method

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Comparison of Land Use Change Detection Methods with Satellite Image (위성영상을 이용한 토지이용 변화 검색기법 비교연구)

  • Park, Soon-Ho;Kim, Woo-Kwan
    • Journal of the Korean association of regional geographers
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    • v.5 no.1
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    • pp.137-150
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    • 1999
  • Five land use change detection methods were applied to 1994 and 1997 Landsat Thematic Mapper (TM) images of Pook-Gu, Taegu city to determine the land-cover changes between the two dates. The two images were coregistred to UTM coordinates. A post-classification comparison method was the most commonly used quantitative method of change detection. A pre-classification comparison method was more effective method to change detection of land cover than a post-classification comparison method. Two indices were used to assess the accuracies of the studied methods. A image differencing method was found to be most accurate for detecting change verse no change among five land use change detection methods. The difference image of band 2 was found to be most accurate. The overall accuracy and Kappa index agreement of the difference image of band 2 were 0.810 and 0.447.

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Studies on Sensory Evaluation -[Part II] Trio Paired Comparison- (관능검사(官能檢査)에 관(關)한 연구(硏究) -[제2보(第2報)] 3각1대비교법(3角1對比較法)에 대하여-)

  • Hong, Jin
    • Applied Biological Chemistry
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    • v.20 no.3
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    • pp.270-278
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    • 1977
  • In case of sensory evaluation with multi-samples and long-period, in spite of using method with good sensitivity, quality differences among samples could net be detected well because of panel's fatigue and tiredness. So new method to reduce panel's sense of psychological and physiological responsibility, "Trio Paired Comparison", is designed, and New Modified Scheffe's Method 2 as the statistical method for a test of "Trio Paired Comparison" is proposed. And also in this paper problems and countermeasures in applicating "Trio Paired Comparison" are considered.

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Nonparametric Multiple Comparison Procedure Using Alignment Method Under Randomized Block Design (랜덤화 블록 모형에서 정렬 방법을 이용한 비모수 다중비교법)

  • Han, Ji-Ung;Kim, Dong-Jae
    • The Korean Journal of Applied Statistics
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    • v.19 no.3
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    • pp.555-564
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    • 2006
  • Friedman rank-sum multiple comparison procedure is often applied to nonparametric multiple comparison method under randomized block design. Since this method does not use between-block information, we propose, in this paper, nonparametric multiple comparison procedures employing aligned method suggested by Hedges and Lehmann(1962) under randomized block design. The proposed procedure and Friedman procedure are compared by Monte Carlo simulation study.

A Bayesian Approach to Paired Comparison of Several Products of Poisson Rates

  • Kim Dae-Hwang;Kim Hea-Jung
    • Proceedings of the Korean Statistical Society Conference
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    • 2004.11a
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    • pp.229-236
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    • 2004
  • This article presents a multiple comparison ranking procedure for several products of the Poisson rates. A preference probability matrix that warrants the optimal comparison ranking is introduced. Using a Bayesian Monte Carlo method, we develop simulation-based procedure to estimate the matrix and obtain the optimal ranking via a row-sum scores method. Necessary theory and two illustrative examples are provided.

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A Logical Framework of Comparison Shopping Effectiveness and Comparison Challenge Methodology

  • Lee, Jae-Won
    • Proceedings of the CALSEC Conference
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    • 2005.03a
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    • pp.130-134
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    • 2005
  • This research describes the comparison broker's role and its effectiveness measurement using a developed logical framework of comparison shopping service. And verifies that seller-led comparison challenge method provide comparison information of products to buyers more efficiently. In electronic commerce, buyer's satisfaction of purchase (S) can be defined as an interactive function between seller's competitiveness vector (P) of products that supplied to the market, and buyer's informed level vector (B) of products that is known from a lot of sources. Then the buyer's informed level can be changed through the information analysis among products by transformation process using comparison matrix (C). So the role of comparison shopping is to construct a comparison matrix and to serve it to the buyers, and to change the buyer's informed level. The changed informed level influences a buyer's satisfaction, that improved satisfaction of purchase is defined as the effectiveness of comparison shopping. As a perfect provision and usage of comparison matrix is impossible cause of cognitive limit, the most efficient method for improving the comparison effectiveness is the comparison challenge that detects the comparison elements of the largest buyer's information efficiency, and then to be compared between elementary products selectively. This research verifies the substantial superiority of comparison challenge through television market data experiments.

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Search Vector Method for Solution Domain Renewal

  • Toriumi, Fujio;Takayama, Jun-ya;Ohyama, Shinji;Kobayashi, Akira
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.61-64
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    • 2003
  • A band function model paired comparison method (BMPC method) is a kind of a paired comparison methods. Considering the human ambiguities, the BMPC method expressing the human judgment characteristics as a monotonous increase function with some width. Since function types are not specified in a BMPC method, the solution is obtained from inequalities, and the solution is given as a domain. To solve the simultaneous inequalities, the sequential renew method is used in the previous BMPC method. However, the sequential renew method requires much computational effort and memories. Generally, in BMPC method, it is able to solve only a paired comparison table which has less 12-13 samples. For that purpose, a new fast solution algorithm is required. In this paper, we proposed a new “search vector method” which renews the solution domain without creating new edge vectors. By using the method, it is able to decrease the necessary memory spaces and time to solve. The proposed method makes it able to solve more than 15 samples paired comparison inspections which are impossible to solve by previous method.

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The Comparison Analysis of an Estimators of Nonlinear Regression Model using Monte Carlo Simulation (몬테칼로 시뮬레이션을 이용한 비선형회귀추정량들의 비교 분석)

  • 김태수;이영해
    • Journal of the Korea Society for Simulation
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    • v.9 no.3
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    • pp.43-51
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    • 2000
  • In regression model, we estimate the unknown parameters by using various methods. There are the least squares method which is the most general, the least absolute deviation method, the regression quantile method and the asymmetric least squares method. In this paper, we will compare each others with two cases: firstly the theoretical comparison in the asymptotic sense and then the practical comparison using Monte Carlo simulation for a small sample size.

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A single-carrier comparison PWM for Voltage Control of Vienna Rectifier (단일 반송파를 이용한 비엔나 정류기의 전압 제어)

  • Yoon, Byung-Chul;Kim, Hag-Wone;Cho, Kwan-Yuhl;Lim, Byung-Kuk
    • The Transactions of the Korean Institute of Power Electronics
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    • v.17 no.2
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    • pp.129-134
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    • 2012
  • In this paper, a new simple PWM method for Vienna rectifier is proposed. The previous SVPWM method for Vienna rectifier is very complex and difficult to implement. To solve these problems, a new single-carrier comparison PWM method for voltage control of Vienna rectifier is proposed. Because of using the only single carrier, implementation of the proposed PWM is very simple. In the proposed PWM method, carrier comparison parts of the PWM block is only changed from the 2 level PWM control block. The usefulness of the proposed PWM method is verified by the simulation and experiment.

Sample Size Comparison for Non-Inferiority Trials

  • Kim, Dong-Wook;Kim, Dong-Jae
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.411-418
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    • 2007
  • Sample size calculation is very important in clinical trials. In this paper, we propose sample size calculation method for non-inferiority trials using sample size calculation method suggested by Wang et al.(2003) based on Wilcoxon's rank sum test. Also, sample size comparison between parametric method and proposed method are presented.

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