• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1923-1928
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• 2017

This paper is a study on error correction for three-dimensional shape reconstruction based on factorization method. The existing error correction method based on factorization has a limitation of correction because it is optimized globally. Thus in this paper, we propose our new method which can find and correct the only major error influence factor toward three-dimensional reconstructed shape instead of global approach. We define the error-influenced factor in two-dimensional re-projection deviation space and directly control the error components. In addition, it is possible to improve the error correcting performance by recursively applying the above process. This approach has an advantage under noise because it controls the major error components without depending on any geometric information. The performance evaluation of the proposed algorithm is verified by simulation with synthetic and real image sequence to demonstrate noise robustness.

• Journal of the Korean Society of Tobacco Science
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• v.35 no.1
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• pp.1-6
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• 2013

Near InfraRed Spectroscopy(NIRS) is a quick and accurate analytical method to measure multiple components in tobacco manufacturing process. This study was carried out to develop calibration equation of near infrared spectroscopy for the prediction of the amount of chemical components and hot water solubles(HWS) of reconstituted tobacco leaf. Calibration samples of reconstituted tobacco leaf were collected from every lot produced during one year. The calibration equation was formulated as modified partial least square regression method (MPLS) by analyzing laboratory actual values and mathematically pre-treated spectra. The accuracy of the acquired equation was confirmed with the standard error of prediction(SEP) of chemical components in reconstituted tobacco leaf samples, indicated as coefficient of determination($R^2$) and prediction error of sample unacquainted, followed by the verification of model equation of laboratory actual values and these predicted results. As a result of monitoring, the standard error of prediction(SEP) were 0.25 % for total sugar, 0.03 % for nicotine, 0.03 % for chlorine, 0.16 % for nitrate, and 0.38 % for hot water solubles. The coefficient of determination($R^2$) were 0.98 for total sugar, 0.97 for nicotine, 0.96 for chlorine, 0.98 for nitrate and 0.92 for hot water solubles. Therefore, the NIRS calibration equation can be applicable and reliable for determination of chemical components of reconstituted tobacco leaf, and NIRS analytical method could be used as a rapid and accurate quality control method.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.24-32
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• 1996

A rigorous theory for modeling, analysis, optimum nonseparable filter bank in multidimensional M-band quantized subband codec are developed in this paper. Each pdf-optimized quantizer is modeled by a nonlinear gain-plus-additive uncorrelated noise and embedded into the subband structure. We then decompose the analysis/synthesis filter banks into their polyphase components and shift the down-and up-samplers to the right and left of the analysis/synthesis polyphase matrices respectively. Focusing on the slow clock rate signal between the samplers, we derive the exact expression for the output mean square quantization error by using spatial-invariant analysis. We show that this error can be represented by two uncorrelated components : a distortion component due to the quantizer gain, and a random noise component due to fictitious uncorrelated noise at the uantizer. This mean square error is then minimized subject to perfect reconstruction (PR) constraints and the total bit allocation for the entire filter bank. The algorithm gives filter coefficients and subband bit allocations. Numerical design example for the optimum nonseparable orthonormal filter bank is given with a quincunx subsampling lattice.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.6
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• pp.306-313
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• 2006

A three dimensional adaptive finite element refinement algorithm is developed for non-linear magnetostatic field problems. In the method, the edge elements are used for finite element formulation, and the local error in each element is estimated from the fact that the tangential components of magnetic field intensity and the normal components of magnetic flux density should be continuous at the interface of the two adjacent elements. Based on the estimated error, the elements which have big error are divided into several elements using bisection method. The effectiveness of the developed algorithm is proved through numerical examples.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3246-3252
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• 1994

The vibration of meshing gear system is originated form teeth deformation, teeth contact ratio, profile error, etc. The gear vibration is classified as whine vibration during meshing and as rattle vibration during idling. In this study, the whine vibration is investigated under the assumption of piecewise linearity of elastic stiffness due to the variation of meshing. Numerical, theoretical and experimental investigations show the existence of the superharmonic components of the second and the third order. consistently It can be concluded that the superharmonic components in whine vibration of meshing gear is originated from the stiffness variation. It also shows that the higher order harmonics are reduced on the increase of motor speed.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.111-115
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• 2020

In this paper, I proposed an effective technique for accurately predicting pixel values using edge components. Adjacent pixel values are similar to each other. That is, generally, similarity exists between adjacent pixels in an image. In the proposed algorithm, edge components are detected using the surrounding pixels in the first step, and pixel values are estimated using the edge components in the second step. Therefore, the prediction accuracy of the pixel value is improved and the prediction error is reduced. Pixel value prediction is a necessary technique for various applications such as image magnification and confidential data concealment. Experimental results show that the proposed method has higher prediction accuracy and fewer prediction error. Therefore, the proposed technique can be effectively used for applications such as image magnification and confidential data concealment.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.87-100
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• 2005

In order to construct confidence intervals on the sum of variance components in a simple regression model with unbalanced nested error structure, alternative confidence intervals using Graybill and Wang(1980) and generalized inference concept introduced by Tsui and Weerahandi(1989) are proposed. Computer simulation programmed by SAS/IML is performed to compare the simulated confidence coefficients and average interval lengths of the proposed confidence intervals. A numerical example is provided to demonstrate the confidence intervals and to show consistency between the example and simulation results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.7
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• pp.1288-1295
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• 2002

The column-type sensing element in building and mechanical construction parts was designed as three forces and three moments sensor by attaching strain gages approximately. Compared to conventional multi-component sensor, the designed sensor has high stiffness and low cost. The radius of the column was designed analytically and compared with finite element analysis. The interference errors between components were minimized by using addition and subtraction procedure of signals. The fabricated sensor was tested by using a deadweight force standard machine and a six-component force calibration machine. The calibration results showed that the 6-component forces and moments sensor had interference error less than 7.3 % between $F_x$ and $M_x$ components, and 5.0 % in case of other components.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.632-635
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• 2002

In this paper, a general procedure to determine machine tool errors from the on-machine measurement (OMM) data is described. First, a parameterized error model of a machine tool is illustrated by approximating error components as linear function of axis positions, and a modified error model is proposed which includes backlash effects. To determine the unknown model coefficient vectors of the forward and backward error model, an artifact with 8 cutes is made and calibrated on CMM. Then, lower-left and upper-right cube corners are measured with a touch-trigger probe mounted on the machine tool spindle. Measured error data are used to determine the coefficient vectors. The positioning errors in the XY plane at the fixed z position are simulated for the forward and backward error model.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.129-134
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• 1995

The ordinary least square estimator of the disturbance variance in the pooled cross-sectional and time series regression model is shown to be asymptotically unbiased without any restrictions on the regressor matrix when the disturbances follow an equicorrelated error component models.