• Journal of the Korean Ceramic Society
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• v.29 no.2
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• pp.136-142
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• 1992

The effects of cyclic stress, frequency and bias-pressure on densification of Al2O3 powder cyclic compaction are investigated. The effect of frequency was not significant on densification of Al2O3 powder under cyclic compaction. The higher the cyclic stress and the lower the bias pressure, the higher densification was achieved. To obtain a higher densification, cyclic compaction was more efficient than 1 stroke compaction. A densification equation was proposed to describe an cyclic time dependent pressure-volume relation for Al2O3 powder under cyclic compaction. This equation was obtained empirically, based on the pressure-volume equation proposed by Cooper and Eaton, the time dependent densification equation by Kim and Suh and experimental data for Al2O3 powder under cyclic compaction. The agreement between the proposed equation and experimental data for Al2O3 powder under cyclic compaction was very good.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.166-174
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• 1994

A critical evaluation is made of the spectral bias which occurs in the use of a laser doppler velocimeter(LDV). Two processing algorithms are considered for spectral estimates: the sample and hold interpolation method(SH) and the nonuniform Shannon reconstruction technique(SR). Assessment is made of these for varying data densities $(0.05{\le}d.d.{\le}5)$ and turbulence levels(t.i.=30%, 100%). As an improved version of the spectral estimator, the utility of POCS (the projection onto convex sets) has been tested in the present study. This algorithm is found useful to be in the region when $d.d.{\gep}3.$

• Korean Journal of Organic Agriculture
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• v.26 no.1
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• pp.33-41
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• 2018

The paper aims to estimate efficiency of watermelon by using a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. We use the input-output data for watermelon 107 farmers. The main results are as follows. The estimates of efficiency depends on the methodology. The estimates of general DEA is greater than the bootstrapping method. The technical efficiency and pure technical efficiency measure of watermelon is 0.72, 0.82 respectively. However the bias-corrected estimates are less than those of DEA. We know that the DEA estimator is an upward biased estimator. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.533-545
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• 2022

Collection of data on several variables, especially in the field of medicine, results in the problem of measurement errors. The presence of such measurement errors may influence the outcomes or estimates of the parameter in the model. In classification scenario, the presence of measurement errors will affect the intrinsic cum summary measures of Receiver Operating Characteristic (ROC) curve. In the context of ROC curve, only a few researchers have attempted to study the problem of measurement errors in estimating the area under their respective ROC curves in the framework of univariate setup. In this paper, we work on the estimation of area under the multivariate ROC curve in the presence of measurement errors. The proposed work is supported with a real dataset and simulation studies. Results show that the proposed bias-corrected estimator helps in correcting the AUC with minimum bias and minimum mean square error.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1053-1065
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• 2006

This paper proposes a method in one-way layouts for longitudinal data with informative drop-out. When dropouts are informative, that is, correlated with unobserved data and/or the previous observed data, the simple imputation methods such as 'last observation carried forward' (LOCF) methods would arise the bias of the testing models. The maximum likelihood procedure combined with a logit model for the drop-out process is proposed to test treatment effects for one factorial designs and compared with LOCF method in two examples.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.487-492
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• 2006

Jackknife estimators for parameters in the left truncated exponential model are presented. And we show that the generalized jackknife estimators are more efficient than others in terms of the bias and the mean squared error.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.869-878
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• 1998

In this paper, we propose some jackknife estimators for mean in the exponential model with grouped and censored data. Also, we compare the proposed jackknife estimators to other approximate estimators in terms of the mean square error and bias.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.91-97
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• 1997

Maximum likelihood and jackknife estimators of the location and scale parameters and right-tail probability in the truncated arcsine distribution are proposed, and we shall compare the performances of the proposed estimators in terms of bias and mean squared error.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.805-809
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• 2006

In this paper a shrinkage estimator for the measure of dispersion of the inverse Gaussian distribution with known mean is proposed. Also we compare the relative bias and relative efficiency of the proposed estimator with respect to minimum variance unbiased estimator.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.1
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• pp.203-217
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• 2021

Purpose: The purpose of this meta-analysis was to examine the high-level evidence of the effects of manual therapy on musculoskeletal diseases. Methods: Domestic databases were searched for studies that conducted clinical trials associated with manual therapy on chronic musculoskeletal diseases. A total of 591 studies published between 2005 and 2018 were identified, with 18 studies satisfying the inclusion data. The studies were classified according to patient, intervention, comparison, and outcome (PICO). The search outcomes were items associated with pain and physical function. The 18 studies included in the study were evaluated by using the R meta-analysis (version 4.0). The quality of 18 randomized control trials was evaluated by using the Cochrane risk of bias (ROB). The effect sizes were computed as the corrected standardized mean difference (SMD). Subgroup and meta-regression analyses were also used. Egger's regression test was carried out in order to analyze the publication bias. Cumulative meta-analysis and sensitivity analysis were also conducted in order to analyze the data error. Results: The following factors showed the large effect size of manual therapy on chronic musculoskeletal diseases: pain (Hedges's g = 2.66; 95% CI = 1.47 ~ 3.85), and physical function (Hedges's g = 2.15; 95% CI: 1.22 ~ 3.08). The subgroup analysis only showed a statistical difference in the type of manual therapy (pain) and outcome (physical function). No statistically significant difference was found in the meta-regression analysis. Publication bias was found in the data, but the results of the trim-and-fill method showed that such bias did not largely affect the obtained data. Furthermore, there were no data errors in the cumulative meta-analysis and sensitivity analysis. Conclusion: This study provides evidence for the effectiveness of manual therapy on chronic musculoskeletal diseases in pain and physical function. Subgroup analysis suggests that only the type of manual therapy for pain and the type of outcome for physical function differed in effect size.