• Journal of Sensor Science and Technology
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• v.14 no.1
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• pp.33-41
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• 2005

For more convenient electrode-electrolyte interface impedance analysis in biosensor, a stand-alone impedance measurement system is required. In our study, we developed a PC-based portable system to analyze impedance of the electrochemical cell using microprocessor. The devised system consists of signal generator, programmable amplifiers, A/D converter, low pass filter, potentiostat, I/V converter, microprocessor, and PC interface. As a microprocessor, PIC16F877 which has the processing speed of 5 MIPS was used. For data acquisition, the sampling rate at 40 k samples/sec, resolution of 12 bit is used. RS-232 with 115.2 kbps speed is used for the PC communication. The square wave was used as stimuli signal for impedance analysis and voltage-controlled current measurement method of three-electrode-method were adopted. Acquired voltage and current data are calculated to multifrequency impedance signal after Fourier transform. To evaluate the implemented system, we set up the dummy cell as equivalent circuit of which was composed of resistor, parallel circuit of capacitor and resistor connected in parallel and measured the impedance of the dummy cell; the result showed that there exist accuracy within 5 % errors and reproduction within 1 % errors compared to output of Hioki LCR tester and HP impedance analyzer as a standard product. These results imply that it is possible to analyze electrode-electrolyte interface impedance quantitatively in biosensor and to implement the more portable high speed impedance analysis system compared to existing systems.

• Journal of Navigation and Port Research
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• v.35 no.1
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• pp.45-49
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• 2011

The recent trend for numerical experiment requires more higher resolution and accuracy. Generally, in the wave field calculation, it starts with a large region formulation first and follows by a separated detailed region formulation by more denser grids for the main interest area considering the geographical and bathymetrical variation. The wave fields resulted from the large region calculation is being introduced into the detail region calculation as the incident waves. In this process there exists a problem of continuity. In order to get over such problem, method of variable gridding system or spectrum sampling, etc., is being used. However, it seems not enough to examine and analyze the related numerical errors. Therefore, it is investigated in this study the field applicability of the most pervasive use of wave model, the nested SWAN model. For this purpose, we made model experiment for two coastal harbours with different tidal environment, and compared and analyzed the result. From the analysis, it was found that both the extracted values, near the boundaries of the large and detail region and the nested formulation of SWAN model, show almost the same and no different between those with different tidal environment conditions. However it is necessary for reducing the numerical errors to set the boundaries for the detailed region outside of the rapid bathymetric change and deeper region.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Korea journal of population studies
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• v.20 no.1
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• pp.5-25
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• 1997

The historical study reveals that our ancestors had maintained a system which could produce data on the number of population and households as well as on their characteristics. For example, such data on age structure of the population, number of births, number of deaths by age & sex, number of in & out migrants were found in an historical document for the year 755. The main purposes of maintaining the system at that time were taxation and conscription. As the system evolves, another function of identifying the legal status of people was also added. Looking into the figures for those days reveals that ommission rates of the number of population and households were high. Thus, in an effort to obtain a reliable data, the annual population survey system was introduced as of 1 September 1896. This date is now cerebrated as the Statistics Day. Since then, the survey system has been diversified. At the present time, there are three major data sources which produce the statistics on population and households: Civil Registration System (vital statistics), Resident Registratiton System (migration statistics) and Population Census. However, these three systems are found to have some problems to produce the accurate data. There are some inherent problems in the registration systems such as problems in its coverage, accuracies in contents and timeliness in reporting the vital events and publishing the results. The population census has also non-sampling errors such as errors in coverage, response and non-response. Apart from the above mentioned problems, there are also conflicting problems arised from having different three data source. We can find some overlapping problems in laws and difficulties in comparative studies between regions. In the future, these problems should be taken into consideration for the improvement of the quality of statistics on population and households.

• The Korean Journal of Cytopathology
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• v.19 no.2
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• pp.111-118
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• 2008

Background : Cervicovaginal cytology is a screening test of uterine cervical cancer. The sensitivity of cervicovaginal cytology is less than 50%, but studies of cytologic/histologic correlation are limited. We analyzed the diagnostic accuracy of cervicovaginal cytology in the detection of the squamous epithelial lesions of the uterine cervix and investigate the cause of diagnostic discordance. Materials and Methods : We collected a total of 481 sets of cervicovaginal cytology and biopsies over 5 years. The cytologic diagnoses were categorized based on The Bethesda System and the histologic diagnoses were classified as negative, flat condyloma, cervical intraepithelial neoplasia (CIN) I, CIN II, CIN III, or squamous cell carcinoma. Cytohistologic discrepancies were reviewed. Results: The concordance rate between the cytological and the histological diagnosis was 79.0%. The sensitivity and specificity of cervicovaginal cytology were 80.6% and 92.6%, respectively. Its positive predictive value and negative predictive value were 93.7% and 77.7%, respectively. The false negative rate was 19.4%. Among 54 false negative cytology cases, they were confirmed by histology as 50 flat condylomas, 2 CIN I, 1 CIN III, and 1 squamous cell carcinoma. The causes of false negative cytology were sampling errors in 75.6% and interpretation errors in 24.4%. The false positive rate was 7.4%. Among 15 false positive cytology cases, they were confirmed by histology as 12 atypical squamous cells of undetermined significance (ASCUS) and 3 low grade squamous intraepithelial lesions (LSIL). The cause of error was interpretation error in all cases. The overall diagnostic accuracy of cervicovaginal cytology was 85.7%. Conclusions : Cervicovaginal cytology shows high overall diagnostic accuracy and is a useful primary screen of uterine cervical cancer.

• Korea journal of population studies
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• v.9 no.2
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• pp.93-105
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• 1986

The historical study reveals that our ancestors had maintained a system which could produce data on the number of population and households as well as on their characteristics. For example, such data on age structure of the population, number of births, number of deaths by age & sex, number of in & out migrants were found in an historical document for the year 755. The main purposes of maintaining the system at that time were taxation and conscription. As the system evolves, another function of identifying the legal status of people was also added. Looking into the figures for those days reveals that ommission rates of the number of population and households were high. Thus, in an effort to obtain a reliable data, the annual population survey system was introduced as of 1 September 1896. This date is now cerebrated as the Statistics Day. Since then, the survey system has been diversified. At the present time, there are three major data sources which produce the statistics on population and households: Civil Registration System (vital statistics), Resident Registratiton System (migration statistics) and Population Census. However, these three systems are found to have some problems to produce the accurate data. There are some inherent problems in the registration systems such as problems in its coverage, accuracies in contents and timeliness in reporting the vital events and publishing the results. The population census has also non-sampling errors such as errors in coverage, response and non-response. Apart from the above mentioned problems, there are also conflicting problems arised from having different three data source. We can find some overlapping problems in laws and difficulties in comparative studies between regions. In the future, these problems should be taken into consideration for the improvement of the quality of statistics on population and households.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1295-1303
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• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1039-1052
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• 2009

Radar measurement with high temporal and spatial resolutions can be a valuable source of data, especially in the areas where rain gauge installment is not practical. However, this kind of data brings with it many errors. The objective of this paper is to propose a method to evaluate statistically the quantitative and qualitative accuracy at different radar ranges, temporal intervals and raingage densities and use a bias adjustment technique to improve the quality of radar rainfall for the purpose of hydrological application. The method is tested with the data of 2 storm events collected at Jindo (S band) and Kwanak (C band) radar stations. The obtained results show that the accuracy of radar rainfall estimation increases when time interval rises. Radar data at the shorter range seems to be more accurate than the further one, especially for C-band radar. Using the Monte Carlo simulation experiment, we find out that the sampling error of the bias between radar and gauge rainfall reduces nonlinearly with increasing raingage density. The accuracy can be improved considerably if the real-time bias adjustment is applied, making adjusted radar rainfall to be adequately good to apply for hydrological application.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1329-1346
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• 2016

Korea Health Panel (KHP) data and Korea National Health and Nutrition Examination Survey (KNHANES) data are collected by self-assess and self-report for individual's health status and medical use. Previous studies have claimed that the reliability for prevalence rates and health life expectancies obtained from these data should be validated. National Health Insurance Services in Korea recently released a sample cohort DB that contain all data related to the use of medical facilities for all entire Korea citizens. It has been shown that disease-specific prevalence rates calculated from these data are representative and reliable for the entire population. In this paper, we evaluate the reliability of prevalence rates derived from self-reported data such as KHP and KNHANES by comparing to the prevalence rates from the sample cohort DB. We found that both KHP and KNHANES underestimate prevalence rates and in turn overestimate health life expectancies. Moreover, the general trends of health life expectancies might be distorted (except for the sample cohort DB) because of sampling and non-sampling errors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.121-126
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• 2017

Recently, a lot of people use touch-pen devices such as smart phones and tab computers. To generate the picture and text, a user can give input or control the touch-pen device through simple or multi-touch gestures by touching the screen with a special stylus pen and/or one or more fingers. The accuracy and response time from the moment of contact with the touch board is very important to the touch device. Therefore, research is needed to find a way of removing the noise included in the touch signal quickly and efficiently. In this paper, we propose a method for removing a noise mixed in with a touch point coordinate which has been caused by a input pen on the touch screen. For effective filtering, the fast sampling of the coordinate corresponding to the noise from the input signal is required primarily. Secondly the total compensation of the touch coordinates using the characteristics of the B-Spline curve is applied to correct coordinates of the points. This method can ensure a real-time response than other algorithms. The applied performance evaluation method is comparing error pixels with evaluation values by dividing 10 intervals on the touch pad diagonally. Usually the average error is 7.1 pixels but our proposed method shows an average 4.1 errors. Therefore, our proposed touch pen method can express the input signal on the coordinates more correctly.