• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.486-491
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• 1996

The purpose of present study is to propose a improved damage detection and assessment algorithm that has its basis on the method of system identification. This method allows the use of composite data which is constitute of static displacements and eigenmodes. In the dynamic test, thecurvature and slope of mode shape are introduced to formulate the error responses. The effectiveness of the proposed staristical system identification method is investigated through simulated and experimental studies. Real test data obtained from measurements are used to identify the actual location of damage and to revise the design variables in a concrete structure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.3
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• pp.945-959
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• 1996

In this paper, a comprehensive computer model is described which can be used to generate the volumetric error map combining the machine parametric errors and the measurement prove error, for most types of CMMs and axis configurations currently in use.

• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.85-99
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• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.368-375
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• 2023

In this study, we examined the error characteristic and bias correction method for one-month temperature forecast data produced through joint development between the Rural Development Administration and the H ong Kong University of Science and Technology. For this purpose, hindcast data from 2013 to 2021, weather observation data, and various environmental information were collected and error characteristics under various environmental conditions were analyzed. In the case of maximum and minimum temperatures, the higher the elevation and latitude, the larger the forecast error. On average, the RMSE of the forecast data corrected by the linear regression model and the XGBoost decreased by 0.203, 0.438 (maximum temperature) and 0.069, 0.390 (minimum temperature), respectively, compared to the uncorrected forecast data. Overall, XGBoost showed better error improvement than the linear regression model. Through this study, it was found that errors in prediction data are affected by topographical conditions, and that machine learning methods such as XGBoost can effectively improve errors by considering various environmental factors.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.69-76
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• 2020

In this paper, the problem of determining the optimal time to market of software was studied using error correction time, an indicator of error correction difficulty. In particular, it was intended to modify the assumption that error detection time and correction time are independent in the software reliability growth model considering the existing error correction time, and to establish a general framework model that expresses the correlation between error detection time and correction time to determine when the software will be released. The results showed that it was important from an economic perspective to detect errors that took time to correct early in the test. It was concluded that it was very important to analyze the correlation between error detection time and error correction time in determining when to release the optimal software.

• Particle and aerosol research
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• v.7 no.1
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• pp.31-44
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• 2011

The hourly volatile organic compounds(VOCs) concentrations between 2005 and 2008 at Bulgwang photochemical assessment monitoring station were investigated to establish a method for quality assurance and quality control(QA/QC) procedure. Systematic error, erratic error, and random error, which was manifested by outlier and highly fluctuated data, were checked and removed. About 17.3% of the raw data were excluded according to the proposed QA/QC procedure. After QA/QC, relative standard deviation for representing 15 species concentrations decreased from 94.7-548.0% to 63.4-125.8%, implying the QA/QC procedure is proper. For further evaluation about the adequacy of QA/QC procedure, principal components analysis(PCA) was carried out. When the data after QA/QC procedure was used for PCA, the extracted principal components were different from the result from the raw data and could logically explain the major emission sources(gasoline vapor, vehicle exhaust, and solvent usage). The QA/QC procedure based on the concept of errors is inferred to proper to be applied on VOCs. However, an additional QA/QC step considering the relationship between species in the atmosphere needs to be further considered.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.219-222
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• 2017

This study aimed to demonstrate the effect of feedback type on users' subjective responses in a voice user interface. Feedback type is classified depend on information characteristic it involves; verification feedback and elaboration feedback. Error type is categorized as recognition error and performance error. Users' subjective assessment about system, feedback acceptance, and intention to use were measured as dependent variables. The results of experiment showed that feedback type has impacts on the subjective assessment(likeability, habitability, system response accuracy) of VUI, feedback acceptance, and intention to use. the results also demonstrated an interaction effect of feedback type and error type on the feedback acceptance. It leads to the conclusion that VUI should be designed with the elaboration feedback about error situation.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.231-245
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• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.336-342
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• 1994

This paper presents an useful technique for assessing the volumetric error in multi_axis machine tools using the kinematic double ball bar and 3 dimensional spherical contouring. The developed system proposes the 3 dimensional spherical contour for the error analysis. The developed system input the measured radial data, analysing the volumetric errors such as positional, strightness, angle, and squareness errors, etc. The developed system has been tested in a practical machine tool, and showed high

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.187-188
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• 2008

주기적으로 제어 성능을 평가하고, 평가 결과에 따라서 제어시스템의 제어기 상수를 최적화하거나 제어 밸브와 같은 제어기기의 문제점들을 사전에 개선하고자하는 노력이 있어왔다. 제어성능 평가방법은 제어목표 값에 대한 추종성을 평가하는 Set Point Analysis 방법을 주로 사용한다. 평가 지표는 Integral Absolute Error(IAE)와 같은 Error Integral 값과 Minimum Variance 방법이 실용적으로 사용된다. 본 논문에서는 평가 대상시스템으로 원자력발전소의 수위 제어시스템중 하나를 선정하고 Control Performance Assessment를 수행하였다. 이를 기반으로 대상 시스템의 제어모델링을 바탕으로 한 Minimum Integral Error를 만족하는 제어기 상수를 구하였으며 새로운 상수를 제어기에 설정한 후 다시 성능을 평가하였다. 평가 결과, 제어시스템의 제어 성능 평가 지표를 사용한 제어 루프의 평가와 예방 조치가 실제적으로 발전소의 안정적 운전에 유용하다는 것을 입증하였다.