• Journal of the Korean Statistical Society
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• 제26권1호
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• pp.101-116
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• 1997

This is primarily an expository paper that presents several nonparametric procedures for testing exponentiality against certain monotonicity properties of the mean residual life function, tests against the trend change in such function attract a great deal of attention of late in reliability analysis. In this note, we present some of the known testing procedures regarding the behavior of mean residual life function. These tests are also compared in terms of asymptotic relative efficiency and empirical power against a few alternatives. The tests based on incomplete data are also briefly discussed.

• Communications for Statistical Applications and Methods
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• 제23권1호
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• pp.33-45
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• 2016

Variance components should be estimated based on mean change when the mean of the observations drift gradually over time. Consistent estimators for the variance components are studied for a particular modeling situation with some underlying functions or drift. We propose a new variance estimator with Fourier estimation of variations. The consistency of the proposed estimator is proved asymptotically. The proposed procedures are studied and compared empirically with the variance estimators removing trends. The result shows that our variance estimator has a smaller mean square error and depends on drift patterns. We estimate and apply the variance to Nile River flow data and resting state fMRI data.

• 한국공간구조학회논문집
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• 제20권1호
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• pp.69-77
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• 2020

In this paper, the mean and fluctuating pressure coefficients derived from the results of wind tunnel tests on closed and open dome roofs were analyzed. The distribution characteristics of the fluctuating pressure according to the opening ratio and the height change were discussed. The analysis results showed that when the roof is open, the overall wind pressure decreases due to the open space, but more fluctuation occurred than the closed dome roof.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• 전기학회논문지
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• 제57권5호
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• pp.866-874
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• 2008

Motor frequency can be measured by a hall sensor. Among the many hall sensors, a linear type hall sensor is good at high accuracy frequency measuring problem. However, in general, this linear type hall sensor has DC offset which can vary along sensor's operating voltage change. Therefore, In motor frequency measurement problem using the linear hall sensor, it needs an estimator that can estimate frequency and DC offset simultaneously. In this paper, we propose the least mean square estimator to estimate motor frequency. To verify its performance, we compare the LMS estimator with a commercial analog tachometer. Experimental results shows the proposed LMS estimator works well in varying frequency and stationary DC offset.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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• pp.467-468
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• 1998

Impulsive noise appears as black and/or white spots in an image. It is usually caused by errors during the image acquisition or transmission through communication channels. This paper presents a study on the impulsive noise reduction filter of digital image. A much more effective method for removing impulse noise is weighted median filtering. But it loses some information by changing center value with no condition. We propose some new technique to change center value with some conditions. In this paper, the performance of conditional weighted median filter is compared to the commonly used median filter, mean filter, max/min filter, and weighted median filter. A quantitative comparison is performed on MSE (Mean Square Error), RMSE (Root Mean Square Error), and SNR (Signal to Noise Ratio). Proposed conditional weighted median filter can yield better performance than regular filters.

• 대기
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• 제20권2호
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• pp.211-219
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• 2010

The interannual variability of the tropical Indian Ocean SST is investigated by analyzing the ocean assimilation data. It is significant that since 1970, ENSO events frequently followed the Indian Ocean Dipole event. The SST tendency due to the dynamical SST advections over the tropical Indian Ocean sufficiently overwhelms that due to other thermodynamic process during the fall and winter of ENSO. Especially, the strong cooling due to the anomalous vertical advection by the mean upwelling and the warming due to the horizontal advection are attributed to the cold SST during the fall and the warm SST during the winter, respectively. The significant warming between winter and spring over the southwestern Indian Ocean turns out to be due to the vertical advection of the mean subsurface temperature by the anomalous upwelling during the winter and the vertical advection of the anomalous subsurface temperature by the mean upwelling from winter to spring. We speculate that when the Indian Ocean Dipole events concurred with the ENSO, the surface wind is so strong enough as to generate the change in the SST dynamically and overwhelm the SST changes associated with other effects.

• 한국음향학회:학술대회논문집
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• 한국음향학회 2000년도 학술발표대회 논문집 제19권 2호
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• pp.243-246
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• 2000

This paper addresses a new technique of measuring the mean flow velocity not only over the cross sectional area but also along the pipe by exploiting the acoustic plane waves in the pipe. When fluid flows in the pipe and two plane waves propagate oppositely through the medium in it, the flow velocity causes a change of the wave number of the plane waves. The wave number of the positive going plane wave decreases but oppositely that of negative going one increases in comparison to no flow of the medium in the pipe. Theoretical backgrounds of this method are in details discussed and measurement results of the mean flow velocity are illustrated to reveal the feasibility and effectiveness of the suggested technique.

• Water Engineering Research
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• 제3권3호
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• pp.195-202
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• 2002

The mean is generally used as a point estimator in water-quality data. Unfortunately, the nonnormal and skewed distributions of data hinder the direct application of the mean, which is inappropriate statistics in this case. The use of robust statistics such as L, M, and R-estimators are recommended and become more efficient. The median (L-estimator), the biweight (M-estimator), and the Hodges-Lehmann method (R-estimator) are briefly introduced and applied in this paper. From the actual data analyses, it is known that the median does not guarantee robustness for a small number of data sets, and robust measures of location or the arithmetic mean without outliers are highly recommended if the distribution has tails or outliers. Care must be taken to measure the location because water quality level within a water body can change depending on the selected point estimator.

• Food Science and Biotechnology
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• 제17권6호
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• pp.1352-1356
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• 2008

Bootstrap method, a computer-intensive statistical technique to estimate the distribution of a statistic was applied to deal with uncertainty and variability of the experimental data in stochastic prediction modeling of microbial growth on a chill-stored food. Three different bootstrapping methods for the curve-fitting to the microbial count data were compared in determining the parameters of Baranyi and Roberts growth model: nonlinear regression to static version function with resampling residuals onto all the experimental microbial count data; static version regression onto mean counts at sampling times; dynamic version fitting of differential equations onto the bootstrapped mean counts. All the methods outputted almost same mean values of the parameters with difference in their distribution. Parameter search according to the dynamic form of differential equations resulted in the largest distribution of the model parameters but produced the confidence interval of the predicted microbial count close to those of nonlinear regression of static equation.