• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1538-1542
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• 2005

This study is to secure more accurate data of the discharge on the measurement by gaining a reliable hydrological data through the comparison the present method of measuring them and the other way that is based ISO. This study suggests the applicable measurement method of the discharge that has reliance through general elements and the analysis of uncertainty by comparing and assaying the data of the Hyung San River that is measured by the present standard. The result of this study makes us realize that we should complement the measurement method of the discharge securing the reliable and accurate hydrological data Hydrological data is very important things to perform domestic river works or install some structure in river or coast. Securing reliable and accurate hydro-data and making a thesis should go on in other to do any construction in river or coast.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.773-779
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• 2015

We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2002-2007
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• 2010

The objective of this study is the developement monitoring measurement using global positioning digital datalogger system for monitoring measurement of railway construction sites. For the replacement of current passive data communication, Global positioning digital datalogger system using active communication is studied for the first time with in a country. Therefore data communication method and analyzing program of automatic measurement data is developed for the global positioning automatic digital datalogger system. The results of this study will be using real time automatic monitoring measurement of railway structures.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.713-723
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• 2019

Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.7
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• pp.261-271
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• 1986

This paper describes a method for the state estimation considering current measurement component and detection of the bad data. The state values are estimated by weighted least square method in which measurement vector included bus injection current and line current. The bad data are detected using standardized variable of normal distribution and identified using sensitivity coefficients. When the bad data were occured by the bad measurement values. The results of the application to the model power system reveal the effectiveness of the presented algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.9
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• pp.83-89
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• 2013

Power distribution system has been changed from radial system to closed loop or mesh system due to connection of distributed generation growth. Data from distribution equipments which are installed at distribution line is required to be accurate for the performance of DMS(Distribution Management System). This paper analyzes the voltage measurement data from distribution equipment. However, the results of the analysis are confirmed to have some errors in voltage measurement data from distribution equipment. These errors come from aging of voltage sensor in distribution equipment and inaccurate data transfer to FRTU(feeder remote terminal unit) through the controller. The main problem is that the voltage measurement data of distribution equipment can not be assessed after it's first installation at the distribution line. The voltage measurement accuracy assessment system is to assess the voltage measurement data from distribution equipment on hot-line. This study had a field test to verify the performance of system.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1645-1651
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• 2016

A lot of data, particularly in the medical field, contain variables that have a measurement error such as blood pressure and body mass index. On the other hand, recently smoothing methods are often used to solve a complex scientific problem. In this paper, we study a Bayesian curve-fitting under functional measurement error model. Especially, we extend our previous model by incorporating covariates free of measurement error. In this paper, we consider penalized splines for non-linear pattern. We employ a hierarchical Bayesian framework based on Markov Chain Monte Carlo methodology for fitting the model and estimating parameters. For application we use the data from the fifth wave (2012) of the Korea National Health and Nutrition Examination Survey data, a national population-based data. To examine the convergence of MCMC sampling, potential scale reduction factors are used and we also confirm a model selection criteria to check the performance.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.150-157
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• 2020

In this study, an algorithm was developed to validate the seismic acceleration measurement data of the seismic acceleration measurement system using measurement data from public buildings currently in operation. Through the results of the study, an algorithm was developed to detect errors and abnormalities in the measurement data itself and the process of generating real-time data (MMA/sec) and event measurement data (MiniSEED), which are the main data generated by the system, and the basic data for determining the direction of inspection through measurement data analysis. It is expected that this will be used as a guideline to determine whether or not the seismic acceleration measurement system, which was managed as receiving/not receiving, is inspected and abnormal types of conditions.

• Wind and Structures
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• v.31 no.1
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• pp.21-29
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• 2020

The wind field measurement of severe winds such as hurricanes (or typhoons), thunderstorm downbursts and other gales is important issue in wind engineering community, both for the construction and health monitoring of the wind-sensitive structures. Although several wireless data transmission systems have been available for the wind field measurement, most of them are not specially designed for the wind data measurement in structural wind engineering. Therefore, the field collection is still dominant in the field of structural wind engineering at present, especially for the measurement of the long-term and high-frequency wind speed data. In this study, for remote wind field measurement, a novel wireless long-term and high-frequency wind data acquisition system with the functions such as remote control and data compression is developed. The system structure and the collector are firstly presented. Subsequently, main functions of the collector are introduced. Also novel functions of the system and the comparison with existing systems are presented. Furthermore, the performance of this system is evaluated. In addition to as the wireless transmission for wind data and hardware integration for the collector, the developed system possesses a few novel features, such as the modification of wind data collection parameters by the remote control, the remarkable data compression before the data wireless transmission and monitoring the data collection by the cell phone application. It can be expected that this system would have wide applications in wind, meteorological and other communities.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.114-118
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• 2021

In this research, the dimensional error of the measured specimen according to the measurement method was analyzed for the length, angle, radius of curvature and diameter using a projector which is used in industry. One-way analysis was performed on each data tested 30 times using a statistical technique. Through the experiment, it was found that an error occurred in each data when measuring the length and radius of curvature according to the measurement method, and the null hypothesis that no error occurred when measuring the angle and length was established. Based on this experimental data, the automatic measurement when measuring the projector causes less measurement error, so automatic measurement is recommended when measuring a small product. Also, an optimal measuring method is suggested for securing reliability on formulations of measurement automation.