• Title/Summary/Keyword: resampling

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Unmasking Multiple Outliers in Multivariate Data

  • Yoo Jong-Young
    • Communications for Statistical Applications and Methods
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    • v.13 no.1
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    • pp.29-38
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    • 2006
  • We proposed a procedure for detecting of multiple outliers in multivariate data. Rousseeuw and van Zomeren (1990) have suggested the robust distance $RD_i$ by using the Resampling Algorithm. But $RD_i$ are based on the assumption that X is in the general position.(X is said to be in the general position when every subsample of size p+1 has rank p) From the practical points of view, this is clearly unrealistic. In this paper, we proposed a computing method for approximating MVE, which is not subject to these problems. The procedure is easy to compute, and works well even if subsample is singular or nearly singular matrix.

Optimal Datum Unit Definition for Diagnostics of Journal Bearing System (저널베어링 상태 진단을 위한 최적의 데이터 분석 기준 설정)

  • Youn, Byeng D.;Jung, Joonha;Jeon, Byungchul;Kim, Yeon-Whan;Bae, Yong-Chae
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2014.10a
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    • pp.84-89
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    • 2014
  • Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.

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Permutation Analysis of Split-Half Reliability Coefficient

  • Um, Yonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.7
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    • pp.133-139
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    • 2017
  • In this paper, we describe a permutation procedure in which we compute a resampling probability value and empirical quantile limits for Split-Half measure of internal reliability. We use the Split-Half reliability coefficient given by two simple methods, the Spearman-Brown formula and the two-part coefficient alpha. The use of a permutation test for Split-Half reliability coefficient is highlighted as a valuable tool when the sample sizes are small and necessary assumptions cannot be met. The permutation tests for Split-Half reliability coefficient are illustrated with an example analysis of two survey data with a sample size of 15 and 35, respectively, and a hypothetical data with a sample size of 5.

Design of the Target Estimation Filter based on Particle Filter Algorithm for the Multi-Function Radar (파티클 필터 알고리즘을 이용한 다기능레이더 표적 추적 필터 설계)

  • Moon, Jun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.3
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    • pp.517-523
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    • 2011
  • The estimation filter in radar systems must track targets' position within low tracking error. In the Multi-Function Radar(MFR), ${\alpha}-{\beta}$ filter and Kalman filter are widely used to track single or multiple targets. However, due to target maneuvering, these filters may not reduce tracking error, therefore, may lost target tracks. In this paper, a target tracking filter based on particle filtering algorithm is proposed for the MFR. The advantage of this method is that it can track targets within low tracking error while targets maneuver and reduce impoverishment of particles by the proposed resampling method. From the simulation results, the improved tracking performance is obtained by the proposed filtering algorithm.

Detection of Rotor Bar Faults in Field Oriented Controlled Induction Motors

  • Akar, Mehmet
    • Journal of Power Electronics
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    • v.12 no.6
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    • pp.982-991
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    • 2012
  • In this study, a new method has been presented for the detection of broken rotor bar (BRB) faults in inverter driven induction motors controlled via Field Oriented Control (FOC). To this end, a FOC controlled induction motor with a BRB fault was modeled using the Matlab/Simulink program. Experiments were carried out using the prepared simulation model at various loads and operating speeds. The motor current and speeds were monitored for healthy, 1, 2 and 3 BRB faults. The Resampling Based Order Tracking Analysis (RB-OTA) method was applied to the monitored signals. The obtained results were compared by using the classic Fast Fourier Transform (FFT) method. When the obtained results were analyzed via the FFT method no information regarding any faults was determined in the run up or run down regions of the motor and the presented method gave very good results. The reliability of the proposed method was validated with experimental results. The main innovative part of this study is that the RB-OTA method was implemented on the induction motor current signal for detecting BRB faults.

Resampling-based Test of Hypothesis in L1-Regression

  • Kim, Bu-Yong
    • Communications for Statistical Applications and Methods
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    • v.11 no.3
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    • pp.643-655
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    • 2004
  • L$_1$-estimator in the linear regression model is widely recognized to have superior robustness in the presence of vertical outliers. While the L$_1$-estimation procedures and algorithms have been developed quite well, less progress has been made with the hypothesis test in the multiple L$_1$-regression. This article suggests computer-intensive resampling approaches, jackknife and bootstrap methods, to estimating the variance of L$_1$-estimator and the scale parameter that are required to compute the test statistics. Monte Carlo simulation studies are performed to measure the power of tests in small samples. The simulation results indicate that bootstrap estimation method is the most powerful one when it is employed to the likelihood ratio test.

Improved Sampling Method For Volume Rendering (Volume Rendering를 위한 향상된 Sampling 방법)

  • 박재영;이병일;최흥국
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.213-216
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    • 2000
  • 본 논문에서는 volume rendering 기법을 이용하여 2차원 MRI 영상들을 합성하여 3차원 영상 만들 때 보다 해상도를 높이기 위한 개선된 sampling방법을 소개한다 2차원 슬라이스 영상들이 3차원으로 재구성할 때 voxel 기반으로 렌더링을 하기 때문에 오브젝트의 내부 영역까지도 볼 수 있는 것이 volume rendering의 가장 큰 장점이다. 따라서 영상을 재구성하는 과정에서 보다 향상된 interpolation을 적용시켜서 공간 해상도를 향상시키면 보다 명확하게 오브젝트 내부 정보를 살펴 볼 수 있다. 본 논문에서는 nearest neighbor 이나 linear 같은 interpolation으로 sampling한 방법보다 cubic interpolation을 3차원 공간에서 적용 시켜서 보다 resampling이 잘 되도록 하여 해상도를 향상시켜 보았다. 이렇게 향상된 Interpolation 적용시켜서 렌더링할 때 얼마나 오브젝트 내부 영역이 잘 가시화가 되었는지 transfer function을 적용시켜서 오브젝트 내부 정보를 렌더링 해보았고, 임의의 축으로 오브젝트을 잘라서 2D 단면 영상으로 출력해 보았다. 보다 향상된 interpolation을 적용시켜서 resampling을 하면 영상 해상도가 개선되었음을 볼 수 있었다.

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Empirical Mode Decomposition (EMD) and Nonstationary Oscillation Resampling (NSOR): I. their background and model description

  • Lee, Tae-Sam;Ouarda, TahaB.M.J.;Kim, Byung-Soo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2011.05a
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    • pp.90-90
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    • 2011
  • Long-term nonstationary oscillations (NSOs) are commonly observed in hydrological and climatological data series such as low-frequency climate oscillation indices and precipitation dataset. In this work, we present a stochastic model that captures NSOs within a given variable. The model employs a data-adaptive decomposition method named empirical mode decomposition (EMD). Irregular oscillatory processes in a given variable can be extracted into a finite number of intrinsic mode functions with the EMD approach. A unique data-adaptive algorithm is proposed in the present paper in order to study the future evolution of the NSO components extracted from EMD.

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Stormwater Quality simulation with KNNR Method based on Depth function

  • Lee, Taesam;Park, Daeryong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.557-557
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    • 2015
  • To overcome main drawbacks of parametric models, k-nearest neighbor resampling (KNNR) is suggested for water quality analysis involving geographic information. However, with KNNR nonparametric model, Geographic information is not properly handled. In the current study, to manipulate geographic information properly, we introduce a depth function which is a novel statistical concept in the classical KNNR model for stormwater quality simulation. An application is presented for a case study of the total suspended solids throughout the entire United States. Total suspended solids concentration data of stormwater demonstrated that the proposed model significantly improves the simulation performance rather than the existing KNNR model.

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Permutation Test for the Equality of Several Independent Cronbach's Alpha Coefficients

  • Um, Yonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.6
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    • pp.159-164
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    • 2019
  • The statistical inference of Cronbach's alpha measure of internal reliability is known to be inaccurate when sample size is small and the assumption of normality is violated. In this paper, we describe the permutation method in which we compute resampling p-values for testing the difference between two or more independent Cronbach's alpha coefficients. When the over-all permutation test is significant, we also make pairwise post-hoc comparisons using permutaion method. The permutation tests for the equality of two independent Cronbach's alpha coefficients and three independent Cronbach's alpha coefficients are illustrated with an example analysis of survey data.