• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.05a
• /
• pp.294-297
• /
• 2004

Mean squared error (MSE) is an effective criterion to combine the mean and the standard deviation responses in dual response surface optimization. The bias and variance components of MSE need to be weighted properly in the given problem situation. This paper proposes a systematic method to determine the relative weights of bias and variance in accordance with a decision maker's prior and posterior preference structure.

• Genomics & Informatics
• /
• v.15 no.1
• /
• pp.38-47
• /
• 2017

Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.2
• /
• pp.55-62
• /
• 2019

The stereo geometry establishment based on the precise sensor modeling is prerequisite for accurate stereo data processing. Ground control points are generally required for the accurate sensor modeling though it is not possible over the area where the accessibility is limited or reference data is not available. For the areas, the relative orientation should be carried out to improve the geometric consistency between the stereo data though it does not improve the absolute positional accuracy. The relative orientation requires conjugate points that are well distributed over the entire image region. Therefore the automatic conjugate point extraction is required because the manual operation is labor-intensive. In this study, we applied the method consisting of the key point extraction, the search space minimization based on the epipolar line, and the rigorous outlier detection based on the RPCs (Rational Polynomial Coefficients) bias compensation modeling. We tested different parameters of window sizes for Kompsat-2 across track stereo data and analyzed the RPCs precision after the bias compensation for the cases whether the epipolar line information is used or not. The experimental results showed that matching outliers were inevitable for the different matching parameterization but they were successfully detected and removed with the rigorous method for sub-pixel level of stereo RPCs precision.

• Human Ecology Research
• /
• v.57 no.2
• /
• pp.171-183
• /
• 2019

Convergence between technology and financial services is ubiquitous and widespread. Virtual banks represent an important aspect of financial markets that can generate value added for consumers and enhance the quality of financial services. This study explores the effect of innovation characteristics (relative advantage, compatibility, and perceived risk), consumer characteristics (status quo bias), and social mechanisms (network externality: complementarity, numbers of peers) on consumers' adoption intention and resistance to virtual banks. This study adopted an innovation resistance model with two dependent variables: adoption intention and resistance to virtual banks. An online self-administered survey was conducted and 532 or non-users of virtual banks aged 20 to 69 years old were analyzed. Frequency analysis, descriptive analysis, and hierarchical multiple regression indicated that status quo bias, relative advantage, perceived risk, complementarity, and number of peers insignificantly influence the adoption intention regarding virtual banks. Furthermore, status quo bias, relative advantage, perceived risk, and number of peers insignificantly influence the resistance to virtual banks. Female respondents have a lower adoption intention and higher resistance to virtual banks than male respondents. The findings suggest that the innovation resistance model can be useful in understanding consumers'adoption and resistance behavior as well as reveal that innovation characteristics, consumer characteristics, and social mechanism are important antecedent variables of the innovation adoption decision.

• Journal of the Korean Statistical Society
• /
• v.24 no.2
• /
• pp.507-518
• /
• 1995

The ordinary least squares based estiamte $S^2$ of the disturbance variance is considered in the linear regression model when the disturbances follow the first-order moving-average process. It is shown that $S^2$ is weakly consistent estimate for the disturbance varaince without any restriction on the regressor matrix X. Also, simple exact bounds on the relative bias of $S^2$ are given in finite sample sizes.

• Communications for Statistical Applications and Methods
• /
• v.17 no.4
• /
• pp.515-525
• /
• 2010

We investigated design-based properties of the ordinary least square estimator(OLSE) and the weighted least square estimator(WLSE) in a panel regression model. Given a complex data we derive the magnitude of the design-based bias of two estimators and show that the bias of WLSE is smaller than that of OLSE. We also conducted a simulation study using Korean welfare panel data in order to compare design-based properties of two estimators numerically. In the study we found the followings. First, the relative bias of OLSE is nearly two times larger than that of WLSE and the bias ratio of OLSE is greater than that of WLSE. Also the relative bias of OLSE remains steady but that of WLSE becomes smaller as the sample size increases. Next, both the variance and mean square error(MSE) of two estimators decrease when the sample size increases. Also there is a tendency that the proportion of squared bias in MSE of OLSE increases as the sample size increase, but that of WLSE decreases. Finally, the variance of OLSE is smaller than that of WLSE in almost all cases and the MSE of OLSE is smaller in many cases. However, the number of cases of larger MSE of OLSE increases when the sample size increases.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.4
• /
• pp.626-635
• /
• 2012

Most of single frequency GPS receivers utilize low-quality crystal oscillators. If a lowquality crystal oscillator is utilized as the time reference of a GPS receiver, the receiver's clock bias grows very fast due to its inherent low precision and poor stability. To prevent the clock bias becoming too large, large clock jumps are intentionally injected to the clock bias and the time offset for clock steering purpose. The abrupt changes in the clock bias and the time offset, if not properly considered, induce serious accuracy degradation in relative differential positioning. To prevent the accuracy degradation, this paper proposes an efficient and systematic method to eliminate the undesirable clock jump effects. Experiment results based on real measurements verify the effectiveness of the propose method.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.32 no.1
• /
• pp.21-30
• /
• 2022

Objectives: The purpose of this study is to suggest an optimal method by comparing the analysis methods of work environment measurement datasets including left-censored data where one or more measurements are below the limit of detection (LOD). Methods: A computer program was used to generate left-censored datasets for various combinations of censoring rate (1% to 90%) and sample size (30 to 300). For the analysis of the censored data, the simple substitution method (LOD/2), β-substitution method, maximum likelihood estimation (MLE) method, Bayesian method, and regression on order statistics (ROS)were all compared. Each method was used to estimate four parameters of the log-normal distribution: (1) geometric mean (GM), (2) geometric standard deviation (GSD), (3) 95th percentile (X95), and (4) arithmetic mean (AM) for the censored dataset. The performance of each method was evaluated using relative bias and relative root mean squared error (rMSE). Results: In the case of the largest sample size (n=300), when the censoring rate was less than 40%, the relative bias and rMSE were small for all five methods. When the censoring rate was large (70%, 90%), the simple substitution method was inappropriate because the relative bias was the largest, regardless of the sample size. When the sample size was small and the censoring rate was large, the Bayesian method, the β-substitution method, and the MLE method showed the smallest relative bias. Conclusions: The accuracy and precision of all methods tended to increase as the sample size was larger and the censoring rate was smaller. The simple substitution method was inappropriate when the censoring rate was high, and the β-substitution method, MLE method, and Bayesian method can be widely applied.

• The Journal of the Acoustical Society of Korea
• /
• v.23 no.5
• /
• pp.383-389
• /
• 2004

In this paper. we propose the bias compensation methods and the eigenvoice method using the mean of dimensional eigenvoice to improve the performance of rapid speaker adaptation based on eigenvoice under mismatch between training and test environment. Experimental results for vocabulary-independent word recognition task (using PBW 452 DB) show that the proposed methods yield improvements for small adaptation data. We obtained about 22∼30% relative improvement by the bias compensation methods as amount of adaptation data varied from 1 to 50, and obtained 41% relative improvement in error rate by the eigenvoice method using the mean of dimensional eigenvoice with only single adaptation word.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2008.06a
• /
• pp.37-37
• /
• 2008

Hydrogenated nanocrystalline Si (nc-Si:H) thin films were prepared by plasma enhanced chemical vapor deposition (PECVD). The films were deposited with a radio frequency power of 100 W, while substrates were exposed to direct current (DC) biases in the range from 0 to -400 V. The effects of the DC bias on the formation of nanoscale Si crystallites in the films and on their optical characteristics were investigated. The size of the Si crystallites in the films ranges from ~ 1.9 to ~ 4.1 nm. The relative fraction of the crystallites in the films reached up ~ 56.5 % when the DC bias of -400 V was applied. Based on the variation in the structural, chemical, and optical features of the films with DC bias voltages, a model for the formation of nanostructures of the nc-Si:H films prepared by PECVD was suggested. This model can be utilized to understand the evolution in the size and relative fraction of the nanocrystallites as well as the amorphous matrix in the nc-Si:H films.