• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.761-769
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• 2017

Accurately extracting the axle distribution information of a passing vehicle from bridge dynamic responses experiences a key and challenging step in non-pavement bridge weigh-in-motion (BWIM). In this article, the wavelet transformation is adopted and the wavelet coefficient curve is used as a substitute for dynamic response. The driving frequency is introduced and expanded to multi-axle vehicle, and the wavelet coefficient curve on specific scale corresponding to the driving frequency is confirmed to contain obvious axle information. On this basis, an automatic method for axle distribution information identification is proposed. The specific wavelet scale can be obtained through iterative computing, and the false peaks due to bridge vibration can be eliminated through cross-correlation analysis of the wavelet coefficients of two measure points. The integrand function that corresponds to the maximum value of the cross-correlation function is used to identify the peaks caused by axles. A numerical application of the proposed axle information identification method is carried out. Numerical results demonstrate that this method acquires precise axle information from the responses of an axle-insensitive structure (e.g., girder) and decreases the requirement of sensitivity structure of BWIM. Finally, an experimental study on a full-scale simply supported bridge is also conducted to verify the effectiveness of this method.

• Journal of Power System Engineering
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• v.7 no.2
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• pp.23-28
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• 2003

It is very important to analyze the torsional vibration for the propulsion shafting of ship. The authors have developed the transfer stiffness coefficient method(TSCM) as a vibration analysis algorithm. The concept of the TSCM is based on the successive transfer of stiffness coefficient. The effectiveness of the TSCM was verified through many applications. In this paper, the TSCM is applied to the torsional free vibration analysis for the propulsion shafting of an actual shin with a diesel engine. In order to calculate the additional torsional stresses of the propulsion shafting the torsional forced vibration for the shafting is analyzed by using both the modal analysis method and the results of the torsional free vibration analysis by the TSCM. The accuracy of the present method is confirmed by comparing with the vibration analysis results of engine maker.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.82-89
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• 2001

To design a structural or a mechanical system with the best performance, the main procedure of a typical design usually consists of repeated modifications of design parameters and the investigation of the system response for each set of these parameters. But this procedure requires much time, effort and experience. Sensitivity analysis can provide systematic information for improving performance of a system. The author has studied on the development of the structural analysis algorithm and suggested recently the transfer stiffness coefficient method(TSCM). This method is very suitable algorithm to a personal computer because the concept of the TSCM is based on the transfer of the nodal stiffness coefficients which are related to force and displacement vectors at each node. In this paper, a new sensitivity analysis algorithm using the concept of the TSCM is formulated for the computation of state variable sensitivity in static problems. The trust of the proposed algorithm is confirmed through the comparison with the computation results using existent sensitivity analysis algorithm and reanalysis for computation models.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.807-816
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• 2015

In general, the water stage-discharge relationship curve is established based on the assumptions of linearity and homoscedasticity. However, the relationship between the water stage and discharge is affected from geomorphological factors, which violates the basic assumptions of the water stage-discharge relationship curve. In order to reduce the error due to the violations, the curve is divided into several sections based on the manager's judgement considering change of cross-sectional shape. In this research, the objective-splitting criteria of the curve is proposed based on the measured data without the subjective decision. First, it is assumed that the coefficient of variation follows the normal distribution. Then, if the newly calculated coefficient of variation is outside of the 95% confidential interval, the curve is divided. Namely, the groups is divided by the characteristics of the coefficient of variation and the reasonable criteria is provided for establishing a multi-segmented rating curve. To validate the proposed method, it was applied to the data generated by three artificial power functions. In addition, to confirm the applicability of the proposed method, it is applied to the water stage and discharge data of the Muju water stage gauging station and Sangegyo water stage gauging station. As a result, it is found that the automatically divided rating curve improves the accuracy and extrapolation accuracy of the rating curve. Finally, through the residual analysis using Shapiro-Wilk normality test, it is confirmed that the residual of water stage-discharge relationship curve tends to follow the normal distribution.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.1
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• pp.9-18
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• 2003

In static analysis of a variety of structures, the matrix method of structural analysis is the most widely used and powerful analysis method. However, this method has drawback requiring high-performance computers with many memory units and fast processing units in the case of analyzing accurately structures with a large number of degrees-of- freedom. Therefore, it's very difficult to analyze these structures accurately in personal computers. For overcoming the drawback of the matrix method of structural analysis, authors suggest the transfer stiffness coefficient method(TSCM). The TSCM is very suitable to a personal computer because the concept of the TSCM is based on the transfer of the stiffness coefficient for an analytical structure. In this paper, the static analysis algorithm for frame structures is formulated by the TSCM. We confirm the validity of the TSCM through the comparison of computation results by the TSCM, the NASTRAN, the matrix method of structural analysis and the analytical solution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.122-125
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• 1998

In this article, a reduction method for nominal variables is presented and its use illustrated. Factor analysis model (FAM) generally enables us to reduce variables having interval or ratio scale based on their correlation coefficients. We developed an extensive method that makes FAM applicative to the case of nominal variables which does not give correlation coefficients, but only the degree of association. Cramer's V coefficient is a well-established measure that provides the strength of association for nominal variables with a range of [0,1]. When Cramer's V coefficient can logically substitute for correlation coefficient, FAM would be extensively used for reduction of nominal variables.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.108-114
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• 2008

In this paper, we proposed robust blind watermarking algorithm using texture block coefficient based on discrete cosine transform(DCT). The proposed method embedded all of watermark signals into DC component of $8\times8$ block DCT in order to robust various external attack The texture block coefficient was composed absolute value of DCT coefficients. Experiment showed that the proposed method better than conventional methods in the invisibility and various attack such as dithering, cropping, and scaling.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.12
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• pp.1663-1673
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• 2002

In the present paper, flow and heat transfer characteristics of confined impinging slot jets have been numerically investigated using a SIMPLE-based segregated SUPG finite element method. For laminar jets, it is shown that the skin friction coefficient obtained from the present SUPG formulation approaches the grid-independent Galerkin solution inducing negligible false diffusion in the flow field when a moderate number of grid points are used. For turbulent jets, the k-$\omega$turbulence model is adopted. The streamwise mean velocity and the heat transfer coefficient respectively agree very well with existing experimental data within limited ranges of parameters.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2448-2450
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• 1998

For the exact classification of the arm motion this paper proposes EMG pattern recognition method with neural network. For this autoregressive coefficient, linear cepstrum coefficient, and adaptive cepstrum coefficient are selected for the feature parameter of EMG signal, and they are extracted from time series EMG signal. For the function recognition of the feature parameter a radial basis function network, a field of neural network is designed. For the improvement of recognition rate, a number of radial basis function network are combined in parallel, comparing with a backpropagation neural network an existing method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.28-34
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• 2010

In this paper, we proposed an algorithm for utilizing visual information for non-contact predicting method of friction coefficient. Coefficient of friction is very important in driving on road and traversing over obstacle. Our algorithm is based on terrain classification for visual image. The proposed method, non-contacting approach, has advantage over other methods that extract material characteristic of road by sensors contacting road surface. This method is composed of learning group(experiment, grouping material) and predicting friction coefficient group(Bayesian classification prediction function). Every group include previous work of vision. Advantage of our algorithm before entering such terrain can be very useful for avoiding slippery areas. We make experiment on measurement of friction coefficient of terrain. This result is utilized real friction coefficient as prediction method. We show error between real friction coefficient and predicted friction coefficient for performance evaluation of our algorithm.