• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.33-36
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• 2003

Principal component analysis (PCA) was used to improve image classification by the unsupervised classification techniques, the K-means. To do this, I selected a Landsat TM scene of Jeju Island, Korea and proposed two methods for PCA： unstandardized PCA (UPCA) and standardized PCA (SPCA). The estimated accuracy of the image classification of Jeju area was computed by error matrix. The error matrix was derived from three unsupervised classification methods. Error matrices indicated that classifications done on the first three principal components for UPCA and SPCA of the scene were more accurate than those done on the seven bands of TM data and that also the results of UPCA and SPCA were better than those of the raw Landsat TM data. The classification of TM data by the K-means algorithm was particularly poor at distinguishing different land covers on the island. From the classification results, we also found that the principal component based classifications had characteristics independent of the unsupervised techniques (numerical algorithms) while the TM data based classifications were very dependent upon the techniques. This means that PCA data has uniform characteristics for image classification that are less affected by choice of classification scheme. In the results, we also found that UPCA results are better than SPCA since UPCA has wider range of digital number of an image.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.10
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• pp.68-73
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• 2020

The proportion of airline accidents caused by human factors is steadily increasing. The aviation industry has made considerable progress in reducing the accident rate; however, since the early 1980s, the accident rate has remained constant. Due to airspace congestion, the safety margins of these existing safety promotion methods are gradually decreasing; thus, new methods to prevent accidents and quasi-accidents must be devised. Causative factors of aviation accidents include increased air traffic due to increased air demand, increased cumulative working hours due to long-distance flights, and complicated flight environments. Accidents often occur when several small errors accumulate in the normal course of operation, rather than after a single error. Accordingly, in this study, the impacts on air navigation due to human error by aviation maintenance personnel and varying international standards (i.e., KOCA vs. F.A.A vs. EASA) analyzed, and the relationship between human decision-making and behavior was investigated. The resulting safety analysis and alternatives were presented to prevent aviation maintenance accidents and cognitive ergonomics errors.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.11-18
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• 2015

PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.885-898
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• 2012

In this paper, we consider Bayesian approaches to partially linear models, in which a regression function is represented by a semiparametric additive form of a parametric linear regression function and a nonparametric regression function. We make a comparative study on the performance of widely used Bayesian partially linear models in terms of empirical analysis. Specifically, we deal with three Bayesian methods to estimate the nonparametric regression function, one method using Fourier series representation, the other method based on Gaussian process regression approach, and the third method based on the smoothness of the function and differencing. We compare the numerical performance of three methods by the root mean squared error(RMSE). For empirical analysis, we consider synthetic data with simulation studies and real data application by fitting each of them with three Bayesian methods and comparing the RMSEs.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.429-436
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• 2014

This paper proposes three methods of the time synchronization for Pseudolite and GPS and analyzes pseudolite time synchronization error factors for software based performance evaluation on proposed time synchronization methods. Proposed three time synchronization methods are pseudolite time synchronization station construction method, method by using UTC(KRIS) clock source and GPS timing receiver based time synchronization method. Also, we analyze pseudolite time synchronization error factors such as errors of pseudolite clock and reference clock, time delay as clock transmission line, measurement error of time interval counter and error as clock synchronization algorithm to design simulation platform for performance evaluation of pseudolite time synchronization.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.109-110
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• 2006

Various parametric methods, Larson-Miller (L-M), Orr-Sherby-Dorn (O-S-D), Manson-Haferd (M-H) parameters, and minimum commitment method (MCM), were used to predict longer rupture time from short-term creep data. A number of the creep data were collected through literature surveys and experimental data produced in KAERI for predicting the creep type of type 316LN SS. Polynomial equations for predicting the creep life were obtained by the time-temperature parameters (TTP) and the MCM. standard error (SE) and standard error or mean (SEM) values were compared for the each method with temperatures. The TTP methods were good in the creep-life prediction, but the MCM was much superior to the TTP ones at $700^{\circ}C\;and\;750^{\circ}C$. The MCM was found to be lower in the SE values compared to the TTP methods

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.2 s.257
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• pp.160-165
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• 2007

To predict long-term creep life from short-term creep life data, various parametric methods such as Larson-Mille. (L-M), Orr-Sherby-Dorn (O-S-D), Manson-Haferd (M-H) parameters, and a Minimum Commitment Method (MCM) were suggested. A number of the creep data were collected through literature surveys and experimental data produced in KAERI. The polynomial equations for type 316LN SS were obtained by the time-temperature parameters (TTP) and the MCM. Standard error (SE) and standard error of mean (SEM) values were obtained and compared with the each method for various temperatures. The TTP methods showed good creep-life prediction, but the MCM was much superior to the TTP ones at $700^{\circ}C$ and $750^{\circ}C$. It was found that the MCM were lower in the SE values when compared to the TTP methods.

• Korean Journal of Optics and Photonics
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• v.8 no.1
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• pp.73-79
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• 1997

We analyzed the variation of the focus error signal with the effect of land and groove, wavefront error, and optical system parameter variation for the knife-edge and astigmatism methods on the Land/Groove recordable optical disc, using a numerical simulation method. We verified causes of the zero-cross-shift that took place by the effect of land and groove by analyzing the diffraction beam including defocus wavefront errors. We also found that the sensitivty of the focus error signal was reduced by the effect of land and groove in the astigmatism method, as in the analysis of the focus error signal with the each order of the diffraction beam.

• Land and Housing Review
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• v.9 no.4
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• pp.33-42
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• 2018

As a radiant heating panel gets more popularity, the need to study on evaluation method of thermal output of the panel also becomes increasing. Generally, the chamber using method is applied to evaluate the thermal output through an experiment. However, the chamber using method cannot be used due to the limitations on space and cost. EN1264 addresses the test equipment to evaluate the thermal output by using simpler experimental setup, and introduces application method in detail. However, there is not enough description of control methods to meet the experiment condition, and it is difficult to meet this when practical experiment. Therefore, this paper analysed the control error factors of when the thermal output experiment is performed. When EN1264 method is applied to evaluate the thermal output of the radiant floor heating panel, the error factor which is caused by the characteristic of test equipment cannot be removed by the control methods of chamber using method. In addition, the error factor can be occurred at the element which is located out of the control system. These possible error factors are defined as the characteristic error factors.

• Nuclear Engineering and Technology
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• v.16 no.1
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• pp.21-28
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• 1984

The reduction of the truncation error including numerical diffusion, has been one of the most important tasks in the development of numerical methods. The stream line method is used to cancel cross numerical diffusion and some of the non-diffusion type truncation error. The two-step stream line method which is the combination of the stream line method and finite difference methods is developed in this work for the solution of the govern ing equations of incompressible buoyant turbulent flow. This method is compared with the finite difference method. The predictions of both classes of numerical methods are compared with experimental findings. Truncation error analysis also has been performed in order to the compare truncation error of the stream line method with that of finite difference methods.