• Journal of Environmental Science International
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• v.28 no.6
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• pp.535-544
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• 2019

We computed parameters that affect velocity distribution by applying Chiu's two-dimensional velocity distribution equation based on the theory of entropy probability and acoustic doppler current profiler (ADCP) of Jungmun-stream, Akgeun-stream, and Yeonoe-stream among the nine streams in Jeju Province between July 2011 and June 2015. In addition, velocity and flow were calculated using a surface image velocimeter to evaluate the parameters estimated in the velocity observation section of the streams. The mean error rate of flow based on ADCP velocity data was 16.01% with flow calculated using the conventional depth-averaged velocity conversion factor (0.85), 6.02% with flow calculated using the surface velocity and mean velocity regression factor, and 4.58% with flow calculated using Chiu's two-dimensional velocity distribution equation. If surface velocity by a non-contact velocimeter is calculated as mean velocity, the error rate increases for large streams in the inland areas of Korea. Therefore, flow can be calculated precisely by utilizing the velocity distribution equation that accounts for stream flow characteristics and velocity distribution, instead of the conventional depth-averaged conversion factor (0.85).

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1048-1060
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• 2012

In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.227-230
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• 1999

Surface solar radiation over the sea is estimated using Visible and Infrared Spin Scan Radiometer data onbord Geostationary Meteorological Satellite(GMS) 5 for January, 1997 to December 1997 in clear and cloudy conditions. The hourly insolation is estimated with a spatial resolution of 5$\times$ 5 km grid. The island pyranometer belonging to the Japan Meteorological Agency is used for validation of the estimated insolation. It is shown that the estimated hourly insolation has RMSE(root mean square) error of 104 W/$m^2$. The variability of the hourly solar radiation was investigated on 3 areas over seas around Korean Peninsula. The solar radiation of East Sea is similar to Yellow Sea. The maximum value of solar radiation is on June of year. The maximum value in south sea is on August because weather is poor by low pressure and front in June

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.34-41
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• 2014

Through applying hostile radar signals that use stagger PRI to PRI transform in real time, we can analyze stagger PRI and calculate the future TOA for active cancellation by using measured TOA and estimated PRI. We shows the effect of the errors that are contained in PRI and measured TOA. Then, it will suggest the technique to improve the accuracy of estimated PRI and the TOA averaging method for reducing the effect of measured TOA error. Finally, we will show that accuracy of estimated future TOA that is calculated by proposed scheme is higher than that of future TOA that is simply calculated with TDOA and newest TOA through comparing RMSE performance.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.135-147
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• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.89-100
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• 1994

In this paper we consider a new estimator of mean residual life (MRL), based on the partial moment of the distribution. The parameters of a partial moment are estimated by its maximum likelihood estimators when the underlying distribution is known. Though the new estimator is not a consistent estimator of the MRL, it is shown to have smaller mean squared error than the well known empirical MRL estimator for certain parametric families. Numerical summaries of the mean squared errors of the new estimator are presented.

• Imaging Science in Dentistry
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• v.43 no.4
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• pp.267-272
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• 2013

Purpose: Demirjian's dental maturity scores and curves have been widely used for human age determination. Several authors have reported considerable differences between the true and estimated age based on the Demirjian curves, which have been accounted for by ethnicity. The purpose of the current study was to assess the role of ethnicity-specific dental maturation curves in age estimation of Saudi children. Materials and Methods: A sample of 452 healthy Saudi children aged 4 to 14 years were aged based on the original French-Canadian Demirjian curves and several modified Demirjian curves specified for certain ethnic groups: Saudi, Kuwaiti, Polish, Dutch, Pakistani, and Belgian. One-way ANOVA and a post hoc Scheff$\acute{e}$'s test were used to assess the differences between chronological age and dental age estimated by the different curves (P<0.05). Results: The curves designed for Dutch, Polish, Saudi, and Belgian (5th percentile) populations had a significantly lower error in estimating age than the original French-Canadian and Belgian (50th percentile) curves. The optimal curve for males was the Saudi one, with a mean absolute difference between estimated age and chronological age of 8.6 months. For females, the optimal curve was the Polish one, with a mean absolute difference of 7.4 months. It was revealed that accurate age determination was not related to certain ethnicity-specific curves. Conclusion: We conclude that ethnicity might play a role in age determination, but not a principal one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.623-625
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• 2012

The restoration of an image corrupted by Gaussian noise is an important task in image processing. There are many kinds of filters are proposed to remove Gaussian noise such as Gaussian filter, mean filter, weighted filter, etc. However, they perform not good enough for denoising and edge preservation. Hence, in this paper we proposed an adaptive weighted filter which considers spatial distance and the estimated variance of noise. We also compared the proposed method with existing methods through the simulation and used MSE(mean squared error) as the standard of judgement of improvement effect.

• Advances in Energy Research
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• v.8 no.2
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• pp.95-110
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• 2022

Wind energy can be utilized for the generation of electricity, due to significant wind potential at different parts of the world, some countries have already been generating of electricity through wind. Pakistan is still well behind and has not yet made any appreciable effort for the same. The objective of this work was to add some new strategies to calculate Weibull parameters and assess wind energy potential. A new approach calculates Weibull parameters; we also developed an alternate formula to calculate shape parameters instead of the gamma function. We obtained k (shape parameter) and c (scale parameter) for two-parameter Weibull distribution using five statistical methods for five different cities in Pakistan. Maximum likelihood method, Modified Maximum likelihood Method, Method of Moment, Energy Pattern Method, Empirical Method, and have been to calculate and differentiate the values of (shape parameter) k and (scale parameter) c. The performance of these five methods is estimated using the Goodness-of-Fit Test, including root mean square error, mean absolute bias error, mean absolute percentage error, and chi-square error. The daily 10-minute average values of wind speed data (obtained from energydata.info) of different cities of Pakistan for the year 2016 are used to estimate the Weibull parameters. The study finds that Hyderabad city has the largest wind potential than Karachi, Quetta, Lahore, and Peshawar. Hyderabad and Karachi are two possible sites where wind turbines can produce reasonable electricity.

• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.100-106
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• 1984

Traditional methods for estimating the location of underwater target, i.e. the triangulation method and the wavefront curvature method, have been utilized. The location of a target is defined by the range and the bearing, which estimates can be obtained by evaluating the time delay between neighboring sensors. Many components of error occur in estimating the target range, among which the error due to the fluctuation of heading angle is outstanding. In this paper, the wavefront curvature method was used. We considered the error due to the heading fluctuation as the $\beta$-density process, from which we analized the range estimates with $\beta$-density function exist in some finite limits, and its mean value and variation are depicted as a function of true range and heading fluctuation. Given heading angles and sensor separation, maximum estimated heading errors are presented as a function of true range.