• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.4
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• pp.331-338
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• 2004

This paper describes capability of utilizing ground control points(GCPs) obtained from 1:1,000 and 1:5,000 digital vector maps to correct image coordinates which have errors due to bais rational polynomial coefficient(RPC) of IKONOS Geo-level stereo images. The accuracy of the bias-corrected images was improved to approximately 4m and 2m in planimetry and height, respectively. The accuracy was also compared with results from using GCPs obtained by GPS surveying. In consequence, bias-compensated IKONOS sereo imagery was evaluated to satisfy generating topographic map 1:10,000.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.95-101
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• 2020

We studied the Implementation and design of inertial sensor that enables to improve performance by reduce the noise of rotor which Angle of inclination. Analyze model equation including motion equation and error, signal processing filter algorithm on high frequency bandwidth with eliminates error using estimation of error coefficient method is was designed and the prototype inertial sensor showed the pick off noise up to 0.2 mV and bias error performance of about 0.06 deg/hr by the experiments. Accordingly, we confirmed that the design of inertial sensor was valid for high rotation.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.5
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• pp.1-9
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• 2003

To predict the powering performance of full scale ships from the towing tank tests, resistance, propeller open water and self-propulsion tests are conducted. Model tests inevitably include the experimental error defined as the sum of two types of uncertainties, bias and precision errors. The induced errors in each element of model test are propagated through various routes and correlated with one another. The correlation coefficients are very important in the uncertainty analysis. The coefficient gives a direction(increase or decrease) for a value of error in individual elements. If the coefficient is not used accurately, the error bounds of the individual elements are overestimated or underestimated. In this study, the new methodology is applied to the uncertainty analysis of HMRI's towing tank tests, thus error bounds of each element is suggested and verified by several repetitive experiments.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.111-118
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• 2011

This paper suggests a ratio-cum product estimator of a finite population mean using information on the coefficient of variation and the fcoefficient of kurtosis of auxiliary variate in stratified random sampling. Bias and MSE expressions of the suggested estimator are derived up to the first degree of approximation. The suggested estimator has been compared with the combined ratio estimator and several other estimators considered by Kadilar and Cingi (2003). In addition, an empirical study is also provided in support of theoretical findings.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.155-164
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• 2011

This paper suggests two ratio-cum-product estimators of finite population mean using known coefficient of variation and co-efficient of kurtosis of auxiliary characters. The bias and mean squared error of the proposed estimators with large sample approximation are derived. It has been shown that the estimators suggested by Upadhyaya and Singh (1999) are particular case of the suggested estimators. Almost ratio-cum product estimators of suggested estimators have also been obtained using Jackknife technique given by Quenouille (1956). An empirical study is also carried out to demonstrate the performance of the suggested estimators.

• Journal of Korean Academy of Nursing
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• v.38 no.3
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• pp.403-409
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• 2008

Purpose: This study was performed to identify the relationship between optimistic bias about health crisis and health behavior of Korean adults in a crisis of health, and to prepare baseline data for developing a health education and promotion program. Methods: Study subjects were 595 aged from 19 to 64 who live in Korea. Data were collected through questionnaires administered by one interviewer. Descriptive statistics and Pearson's correlation coefficient were calculated using the SPSS program. Results: The average score for optimistic bias about health crisis was 2.69, and that for health behavior was 107.05. The optimistic bias about health crisis showed a significantly positive correlation with health behavior (r=.187, p=.000). Conclusion: To make our results more useful, it is necessary to identity the causal relationship between health attitudes as an explanatory variable and optimistic bias as an outcome variable. In addition, a relatively low score in optimistic bias from this research compared to other studies must be explained through further studies considering unique Korean cultural background. Moreover, research of the relationship between optimistic bias about health crisis and health behavior looking at people who don't have good health behaviors is needed.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.61-71
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• 2015

Quantitative variability of AMSR2 (Advanced Microwave Scanning Radiometer 2) soil moisture data shows that the remotely sensed soil moisture is underestimated during Spring and Winter seasons and is overestimated during Summer and Fall seasons. Therefore the bias correction of the remotely sensed data is essential for the purpose of water resource management. To enhance their applicability, the bias of AMSR2 soil moisture data was corrected using ground observation data at Cheorwon Chuncheon, Suwon, Cheongju, Jeonju, and Jinju sites. Test statistics demonstrated that the correlation coefficient R is improved from 0.107~0.328 to 0.286~0.559 and RMSE is improved from 9.46~14.36 % to 5.38~9.62 %. Bias correction using ground network data improved the applicability of remotely sensed soil moisture data.

• Journal of Biosystems Engineering
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• v.23 no.1
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• pp.1-12
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• 1998

This study was intended to investigate experimentally the effect of inflation pressure on tractive performance of bias-ply tires for agricultural tractors. Traction tests were conducted at the three velocities of 3, 4, and 5.5km/h under few different surface conditions using a 13.6-28 6PR bias-ply tire as driving wheel of the test tractor. When the inflation pressure was reduced from 250kPa to 40kPa by a decrement of either 30 or 50kPa depending upon the test surface conditions, some of the test results showed that the tractive coefficient and efficiency were increased maximally by 40% and 17％, respectively, at 20% slippage. However, it was failed to derive any consistent rules depicting the effect of inflation pressure of bias ply tires on the tractive performance of tractors.

• Survey Research
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• v.7 no.2
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• pp.53-69
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• 2006

Weights can be made and imposed in both sample design stage and analysis stage in a sample survey. While in design stage weights are related with sample data acquisition quantities such as sample selection probability and response rate, in analysis stage weights are connected with external quantities, for instance population quantities and some auxiliary information. The final weight is the product of all weights in both stage. In the present paper, we focus on the weight in analysis stage and investigate the effect of such weights imposed on the weighted mean when estimating the population mean. We consider a finite population with a pair of fixed survey value and weight in each unit, and suppose equal selection probability designs. Under the condition we derive the formulas of the bias as well as mean square error of the weighted mean and show that the weighted mean is biased and the direction and amount of the bias can be explained by the correlation between survey variate and weight: if the correlation coefficient is positive, then the weighted mein over-estimates the population mean, on the other hand, if negative, then under-estimates. Also the magnitude of bias is getting larger when the correlation coefficient is getting greater. In addition to theoretical derivation about the weighted mean, we conduct a simulation study to show quantities of the bias and mean square errors numerically. In the simulation, nine weights having correlation coefficient with survey variate from -0.2 to 0.6 are generated and four sample sizes from 100 to 400 are considered and then biases and mean square errors are calculated in each case. As a result, in the case or 400 sample size and 0.55 correlation coefficient, the amount or squared bias of the weighted mean occupies up to 82% among mean square error, which says the weighted mean might be biased very seriously in some cases.

• Journal of Astronomy and Space Sciences
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• v.28 no.4
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• pp.267-271
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• 2011

I developed an enhanced correction method for Ricean bias which occurs in linear polarization measurement. Two known methods for Ricean bias correction are reviewed. In low signal-to-noise area, the method based on the mode of the equation gives better representation of the fractional polarization. But a caution should be given that the accurate estimation of noise level, i.e. ${\sigma}$ of the polarized flux, is important. The maximum likelihood method is better choice for high signal-to-noise area. I suggest a hybrid method which uses the mode of the equation at the low signal-to-noise area and takes the maximum likelihood method at the high signal-to-noise area. A modified correction coefficient for the mode solution is proposed. The impact on the depolarization measure analysis is discussed.