• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.863-866
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• 2016

Background: Extensive efforts have been made to investigate c-KIT expression in lung cancer specimens and its correlation with clinical outcomes, but the issue remains unresolved. Thus, this study will be conducted to clarify the prognostic value of c-KIT expression in lung cancer patients. Materials and Methods: We will search Pubmed, SCOPUS, and ISI web of sciences with no restriction of language. Studies with any design (except case reports or case series) evaluating correlations of c-KIT expression with survival or outcome in patients with lung cancer will be included. The outcome measures will include all types of survival indexes, including overall survival rate and disease free survival using Kaplan-Meier analysis and hazard ratios. Study selection and data extraction will be performed by two independent researchers. Quality assessment (assessment of risk of bias) and data synthesis will be implemented using Stata software version 11.1. Results: No ethical issues are predicted. These findings will be published in a peer-reviewed journal and presented at national and international conferences. Conclusions: This systematic review protocol is registered in the PROSPERO International Prospective Register of Systematic Reviews, registration number = CRD42015023391.

• Journal of Labour Economics
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• v.35 no.2
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• pp.79-115
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• 2012

In the study, we try to get reliable estimates of intergenerational income mobility in Korea. At first, we show that the low estimates of previous studies are mainly due to sample selection problem. The direct estimations using OLS after correcting this problem show higher values than previous estimates. We also compute the attenuation bias by decomposing the variances of earnings into the variances of permanent and transitory components of earnings by the results of the regression. Additionally, we try to estimate the range of intergenerational mobility by comparing the OLS results with the results of the two samples instrumental variable estimation and the three samples instrumental variable estimation. The results of these estimations are a little higher than or similar to OLS results.

• Journal of Labour Economics
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• v.33 no.2
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• pp.53-89
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• 2010

Curricula relevant to labor market needs are often designed with the goals of individual employment and regional development at the forefront. This study provided information on regional scope by investigating the extent and determinants of the geographic mobility of vocational high school graduates and the effects of that mobility on first-job wage rates. Geographic mobility was defined as being employed in other provinces in which vocational schools were located. About 38% of graduates were employed in other provinces. Geographic mobility was positively related to gender and human capital such as health, course of study, vocational certificate, and job training. Mobility led to higher wage rates even after controlling for sample selection bias. The implication is that vocational high school curricula which focus excessively on provincial concerns may weaken a workforce's effectiveness.

• Ceramist
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• v.23 no.1
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• pp.16-26
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• 2020

Recently, polymer-metal composite (IPMC)-based ionic artificial muscle has been drawing a huge attention for its excellent soft actuator performance having outstanding soft actuator performance with efficient conversion of electrical energy to mechanical energy under low working voltage. In addition, light, flexible and soft nature of IPMC and high bending strain response enabled development of versatile sensor application in association with soft actuator. In this paper, current issues of IPMC were discussed including standardizing preparation steps, relaxation under DC bias, inhibiting solvent evaporation, and improving poor output force. Solutions for these drawbacks of IPMC have recently been suggested in recent studies. After following explanation of the IPMC working mechanism, we investigate the main factors that affect the operating performance of the IPMC. Then, we reviewed the optimized IPMC actuator fabrication conditions especially for the preparation process, additive selection for a thicker membrane, water content, solvent substitutes, encapsulation, etc. Lastly, we considered the pros and cons of IPMCs for sensor application in a theoretical and experimental point of view. The strategies discussed in this paper to overcome such deficiencies of IPMCs are highly expected to provide a scope for IPMC utilization in soft robotics application.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.83-91
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• 1997

A reactor vibration monitoring has been performed using neutron noise obtained from excore detectors for the safety operation, Traditionally, the spectral estimator based on Fourier analysis has been widely used in the noise analysis of the reactor system. If the bias is too severe, the resolution would not be adequate for a given application. One major motivation for the current interests in the parametric approach to spectral estimation is the apparent higher resolution achievable with these modern techniques. In considering an unbias, a consistency, an efficency, and a minimum lower bound of the statictic estimation, an AR model is appropriate for noise spectral estimation with sharp peaks but not deep valley. In order to select an appropriate model order, the lag value of autocorrleaton function is applied. Burg method to trace the vibration mode of RPV internal is the most sucuessful.

• Journal of Labour Economics
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• v.31 no.1
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• pp.29-57
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• 2008

We construct a unique panel data by using Korean Economically Active Population Survey (KEAPS) from 2003 to 2007 to estimate the returns to different types of job mobility among men. By adopting Mincer(1986)'s method, we estimate the wage change to job mobility after controlling the sample selection bias. There are four different types of job mobility that are concerned in the study: (1) voluntary job-to-job changes without experiencing unemployment, (2) voluntary job changes with experiencing unemployment, (3) involuntary job changes due to layoffs, and (4) involuntary job changes due to discharges. Our findings indicate that Korean men who changed jobs without experiencing unemployment realized wage gains of 7% while those who changed jobs through unemployment period lost 10% of their wages. Among those who changed jobs involuntarily and went through unemployment, the workers who discharged from the previous jobs realized substantially greater wage loss.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.561-570
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• 1998

The MLR(Multiple Linear Regression) models to estimate soluble solids content non-destructively were presented to make a selection of optimal photosensor utilized to measure the soluble solids content of apples. Visible and NIR absorbance in the 400 to 2498 nanometer(nm) wavelength region, soluble solids content(sugar content), hardness, and weight were measured for 400 apples(gala). Spectrophotometer with fiber optic probe was utilized for spectrum measurement and digital refractometer was used for soluble solids content. Correlation between absorbance spectrum and soluble solids content was analyzed to pick out the optimal wavelengths and to develop corresponding prediction model by means of MLR. For the coefficient of determination($R^2$) to be over 0.92, the MLR models out of the original absorbance were built based on 7 wavelengths of 992, 904, 1096, 1032, 880, 824, 1048nm, and the ones of the second derivative absorbance based on 5 wavelengths of 784, 1056, 992, 808, 872nm. The best model of the second derivative absorbance spectrum had $R^2$=0.91, bias= -0.02bx, SEP=0.28bx for unknown samples.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.571-582
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• 1998

The PLS(Partial Least Square) and ANN(Artificial Neural Network) were introduced to develop the soluble solids content prediction model of apples which is followed by making a subsequent selection of photosensor. For the optimal PLS model, number of factors needed for spectrum analysis were increased until the convergence of prediction residual error sum of squares. Analysis has shown that even part of the overall wavelength with no pretreatment may turn out better performing. The best PLS model was found in the 800 to 1,100nm wavelength region without pretreatment of second derivation, having $R^2$=0.9236, bias= -0.0198bx, SEP=0.2527bx for unknown samples. On the other hand, for the ANN model the second derivation led to higher performance. On partial range of 800 to 1,100nm wavelengh region, prediction model with second derivation for unknown samples reached $R^2$=0.9177, SEP=0.2903bx in contrast to $R^2$=0.7507, SEP =0.4622bx without pretreatment.

• Journal of Labour Economics
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• v.34 no.2
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• pp.53-77
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• 2011

The last decade has witnessed a surge of research interest in differences between regular and irregular workers in employment forms. Recent studies on estimating wage differentials between the two types of workers in employment forms have typically used the linear regression analysis. Our study utilizes a new methodology to estimate wage differentials between the two types of workers: data matching. Our method can perform better than the ordinary regression analysis because it carefully addresses the selection bias problem. Our results indicate that there is no significant difference in wage between regular and irregular workers.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.