• 한국전산유체공학회:학술대회논문집
• /
• 2011.05a
• /
• pp.261-265
• /
• 2011

An adaptive wavelet transformation method with high order accuracy is proposed to allow efficient and accurate flow computations. While maintaining the original numerical accuracy of a conventional solver, the scheme offers efficient numerical procedure by using only adapted dataset. The main algorithm includes 3rd order wavelet decomposition and thresholding procedure. After the wavelet transformation, 3rd order of spatial and temporal accurate high order interpolation schemes are executed only at the points of the adapted dataset. For the other points, high order of interpolation method is utilized for residual evaluation. This high order interpolation scheme with high order adaptive wavelet transformation was applied to unsteady Euler flow computations. Through these processes, both computational efficiency and numerical accuracy are validated even in case of high order accurate unsteady flow computations.

• Proceedings of the Materials Research Society of Korea Conference
• /
• 2010.05a
• /
• pp.39.2-39.2
• /
• 2010

Recently, hot stamping process has been paid attention greatly by automobile makers in accordance with the fuel efficiency and environmental issues as well as crash safety issue. The hot-stamped parts, however, demand extreme mechanical properties such as tensile strength of over 1470 MPa or equivalently Vickers hardness of around 450. In this work, to meet the demand efficiently, a method to predict mechanical property of hot-stamped parts based on numerical phase transformation scheme has been proposed associated with the thermo-mechanical coupled finite element analysis. This work deals with various phase transformation equations and validates them to select appropriate model for 0.2C-0.1Si-1.4Mn-0.5Cr-0.01Mo-0.002B steel sheet. The authors show that an efficient method saving time and cost to develop hot-stamped automobile parts ensuring suitable mechanical properties such as Vickers hardness and strength.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.20 no.2
• /
• pp.85-93
• /
• 2002

Recently, the flatbed scanner is widely used to input color original copy in printing industry. In the process of RGB-to-CMY transformation for the scanned colors using the look-up table(LUT) based on the color gamut of the actual output device, however, the problem that some colors in the original out of the gamut cannot be printed, may occur. In this study, another color transformation method applicable to any kind of originals using the new LUT with extended gamut based on the ideal output device, was examined and proposed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.10C
• /
• pp.968-974
• /
• 2009

In this paper, we present a skipping method of transformation and quantization process using skip blocks estimation in fast H.264 video encoder. In order to reduce the complexity, we estimate skip mode blocks using integer discrete cosine transform and quantization and a skipping condition is derived by the analysis of those processes. The experimental result show that the proposed algorithm has effective estimations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.10a
• /
• pp.579-582
• /
• 2001

Vector Transformation is a new method unified vector quantization and coding. So far, codebook generation applied to coding was LBG algorithm. But using the advantage of SOFM(Self-Organizing Feature Map) based on neural network can improve a system's performance. In this paper, we generated VTC(Vector Transformation Coding) codebook applied with SOFM algorithm and compare the result for several coding rates with LBG algorithm. The problem of Vector quantization is complicated calculation and codebook generation. So, to solve this problem, we used neural network approach method.

• ETRI Journal
• /
• v.35 no.4
• /
• pp.714-717
• /
• 2013

Peak power reduction techniques in orthogonal frequency division multiplexing (OFDM) has been an important subject for many researchers for over 20 years. In this letter, we propose a side-information-free technique that is based on the concept of random variable (RV) transformation. The suggested method transforms RVs into other RVs, aiming to reshape the constellation that will consequently produce OFDM symbols with a reduced peak-to-average power ratio. The proposed method has no limitation on the mapping type or the mapping order and has no significant effect on the bit error rate performance compared to other methods presented in the literature. Additionally, the computational complexity does not increase.

• Proceedings of the KAIS Fall Conference
• /
• 2010.05a
• /
• pp.257-260
• /
• 2010

In this paper, we propose the computation reduction methods of LSP(Line spectrum pairs) transformation that is mainly used in CELP vocoders. In order to decrease the computational time in real root method the characteristic of four proposed algorithms is as the following. First, scheme to reduce the LSP transformation time uses mel scale. Developed the second scheme is the control of searching order by the distribution characteristic of LSP parameters. Third, scheme to reduce the LSP transformation time uses voice characteristics. Developed the fourth scheme is the control of searching interval and order by the distribution characteristic of LSP parameters. As a result of searching time, computational amount, transformed LSP parameters, SNR, MOS test, waveform of synthesized speech, spectrogram analysis, searching time is reduced about 37.5%, 46.21%, 46.3%, 51.29% in average, computational amount is reduced about 44.76%, 49.44%, 47.03%, 57.40%. But the transformed LSP parameters of the proposed methods were the same as those of real root method.

• Journal of Mechanical Science and Technology
• /
• v.20 no.2
• /
• pp.191-196
• /
• 2006

This paper presents the application of techniques of differential transformation method (DTM) to analyze the transverse vibration of a uniform Euler-Bernoulli beam under varying axial force. The governing differential equation of the transverse vibration of a uniform Euler-Bernoulli beam under varying axial force is derived and verified. The varying axial force was extended to the more general case which was high polynomial consisted of many terms. The concepts of DTM were briefly introduced. Numerical calculations are carried out and compared with previous published results. The accuracy and the convergence in solving the problem by DTM are discussed.

• ETRI Journal
• /
• v.41 no.1
• /
• pp.109-116
• /
• 2019

This paper explores new techniques that are based on a hidden-layer linear transformation for fast speaker adaptation used in deep neural networks (DNNs). Conventional methods using affine transformations are ineffective because they require a relatively large number of parameters to perform. Meanwhile, methods that employ singular-value decomposition (SVD) are utilized because they are effective at reducing adaptive parameters. However, a matrix decomposition is computationally expensive when using online services. We propose the use of an extended diagonal linear transformation method to minimize adaptation parameters without SVD to increase the performance level for tasks that require smaller degrees of adaptation. In Korean large vocabulary continuous speech recognition (LVCSR) tasks, the proposed method shows significant improvements with error-reduction rates of 8.4% and 17.1% in five and 50 conversational sentence adaptations, respectively. Compared with the adaptation methods using SVD, there is an increased recognition performance with fewer parameters.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.667-670
• /
• 2013

Noise is unwanted in high quality images, but it can aid image tampering. For example, noise can be intentionally added in image to conceal tampered regions or to create special visual effects. It may also be introduced unknowingly during camera imaging process, which makes the noise levels inconsistent in splicing images. In this paper, we present an image forgery detection method using a noise dependent watershed transformation. Image is segmented into objects for initial noise estimation by the watershed transformation, and different noise level in objects are estimated to obtain final decision result. Experimental results of the proposed method on natural images are presented.