• Journal of KSNVE
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• v.8 no.5
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• pp.841-848
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• 1998

In the gear manufacturing, tooth modification is usually applied for the prevention of tooth impact during the loading. In contrary, tooth profile error causes amplifying the whine noise which is cumbersome to reduce in the automobile gear box. So optimum quantity of the modifications must be obtained for the good performance in the vibrational sense. In this paper, a formulation to define the tooth curve by considering the profile manufacturing error and loading deformation of the gear tooth is suggested and the transmission error and loading deformation of the gear tooth is suggested and the transmission error with modified tooth in the gear system is evaluated. A pair of gear set is mathematically modelled. The equivalent excitation in the gear vibratonal model is formulated. For the experimental evaluaton on the derived transmission error function, a simple geared system is set up in which the gears are designed to give pre-designed tooth profile modification and manufactured by CNC Wire Cutting Machine. Under slow speed operaton, the transmission error of the gear pair is measured by using two rotational laser vibrometers, compared with the calculated one of which the result shows good agreement.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.824-833
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• 2006

In this paper, the image modelling of road's lane markings is established using view frustum(VF) model. From this model, a measurement system of lane markings and obstacles is proposed. The system also involve the real time processing of the 3D position coordinate and the distance data from the camera to the points on the 3D world coordinate by virtue of the camera calibration. In order to reduce their measurement error, an useful algorithm for which analyze the geometric variations due to traveling vehicle's fluctuation using VF model is proposed. In experiments, without correction, for instance, the $0.4^{\circ}$ of pitching rotation gives the error of $0.4{\sim}0.6m$ at the distance of 10m, but the more far distance cause exponentially the more error. We con finned that this algorithm can be reduced less than 0.1m of error at the same condition.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.996-1008
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• 2011

This paper proposes a PSNR estimation algorithm of H.264/AVC bitstream for hierarchical B-picture structure. The proposed method consists of a modeling method for DCT coefficients for I-pictures and an error estimation method for blocks encoded by skip mode. The modeling method selects an appropriate model between Laplacian and Cauchy model, and the error of skip mode is estimated from MSE values of reference pictures. Experimental results show that the modeling method predicts more accurate PSNR values than Laplacian and Cauchy model and the error estimation method of skip mode enhances PSNR estimation of hierarchical B-picture structure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2227-2232
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• 2013

To obtain the system requirement specification in the beginning of the precision guidance system development, the effectiveness and reliability analysis for the system are necessary. The main purpose of this research is to obtain the system requirement specification for the high speed unmanned underwater vehicles by carrying out the effectiveness analysis using the modeling and simulation scheme. The effectiveness is position error for target position. Reaching accuracy is expected to be affected by the navigation sensor parameter. Assume that the navigation sensors that is consist of inertial navigation system(INS) and doppler velocity log(DVL) is the parameter. To analyze the effectiveness of each parameter, Monte-Carlo numerical simulation is performed in this research. The effectiveness analysis is carried out using circular error probability(CEP) and variance analyze scheme. Considering the cost function, the specification of the navigation sensor is provided. The cost function is consist of the INS and DVL specification and the price of those sensors.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.1-7
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• 2018

In the two-dimensional (2D) modeling of electrical method, the potential in the space domain is reconstructed with the calculated potentials in the wavenumber domain using inverse Fourier transform. The inverse Fourier integral is numerically evaluated using the transformed potential at different wavenumbers. In order to improve the precision of the integration, either the logarithmic or exponential approximation has been used depending on the size of wavenumber. Two numerical methods have been generally used to evaluate the integral; interval integration and Gaussian quadrature. However, both methods do not consider the distance from the current source. Thus the resulting potential in the space domain shows some error. Especially when the distance from the current source is very small or large, the error increases abruptly and the evaluated potential becomes extremely unstable. In this study, we developed a new method to calculate the integral accurately by introducing the distance from the current source to the rescaled Gauss abscissa and weight. The numerical tests for homogeneous half-space model show that the developed method can yield the error level lower than 0.4 percent over the various distances from the current source.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.567-576
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• 2005

This paper proposes an image-based modeling method which recovers 3D models using projected line segments in multiple images. Using the method, a user obtains accurate 3D model data via several steps of simple manual works. The embedded nonlinear minimization technique in the model parameter estimation stage is based on the distances between the user provided image line segments and the projected line segments of primitives. We define an error using a finite line segment and thus increase accuracy in the model parameter estimation. The error is defined as the sum of differences between the observed image line segments provided by the user and the predicted image line segments which are computed using the current model parameters and camera parameters. The method is robust in a sense that it recovers 3D structures even from partially occluded objects and it does not be seriously affected by small measurement errors in the reconstruction process. This paper also describesexperimental results from real images and difficulties and tricks that are found while implementing the image-based modeler.

• Atmosphere
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• v.30 no.1
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• pp.17-30
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• 2020

KMA performed the special observation program to provide information about severe weather and to monitor typhoon PRAPIROON using the ship which called the Gisang 1 from 29 June 2018 to 4 July 2018 (UTC). For this period, upper-air was observed 21 times with 6 hour intervals using rawinsonde in the Gisang 1. We investigated the impact of upper-air observation data from the Gisang 1 on the performance of the operational convective scale model (we called LDAPS). We conducted two experiments that used all observation data including upper-air observation data from the Gisang 1 (OPER) and without it (EXPR). For a typhoon PRAPIROON case, track forecast error of OPER was lower than EXPR until forecast 24 hours. The intensity forecast error of OPER for minimum sea level pressure was lower than EXPR until forecast 12 hours. The intensity forecast error of OPER for maximum wind speed was mostly lower than EXPR until forecast 30 hours. OPER showed good performance for typhoon forecast compared with EXPR at the early lead time. Two precipitation cases occurred in the south of the Korean peninsula due to the impact of Changma on 1 July and typhoon on 3 July. The location of main precipitation band predicted from OPER was closer to observations. As assimilating upper-air data observed in the Gisang 1 to model, it showed positive results in typhoon and precipitation cases.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.9
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• pp.781-786
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• 2015

An aeroelastic stability can be degraded due to an aeroelastic modeling error and a structural uncertainty. Therefore it is necessary to predict the aeroelastic stability boundary considering an aeroelastic modeling error and a structural uncertainty. Robust aeroelastic analysis was proposed to predict the aeroelastic stability boundary considering these error and uncertainty. In the present study, the robust aeroelastic modeling and analysis were performed by using the ${\mu}$ analysis technique and the aeroelastic model of the control fin with modal approach and MSA. The computer program for the robust aeroelastic analysis was developed and verified by comparing its results with those of conventional aeroelastic analysis methods.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.515-526
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• 2009

Pricing based on proper risk has been one of main issues in auto insurance. In this paper, we review how the techniques of pricing in auto insurance have been developed and suggest a better approach which meets the existing risk statistically by comparison. The generalized linear model (GLM) method is discussed for pricing with different distributions. With GLM approach, the distribution of error assumed plays an main role for the best fit corresponding to the characteristics of dependent variables. Tweedie distribution is considered as one of error distributions in addition to widely used Gamma and Poisson distribution. With these different types of error assumption for estimating the proper premium in auto insurance, various modeling approaches are possible. In this paper, various modeling approaches with different assumptions for estimating proper risk is discussed and also real example is given by assuming different.