• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.80-92
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• 2008

Many predominant video coding tools in terms of coding efficiency were adopted in the latest video coding standard, H.264/AVC. Regardless of development of these predominant video coding tools such as the variable block-size motion estimation/compensation, intra prediction based on various directions, and so on, the discrete cosine transform has been continuously used starting from the early video coding standards. Generally, the correlation coefficient of the residual signal is usually less than 0.5 when this residual signal is actually encoded. In this interval of correlation coefficient, the discrete cosine transform does not show the optimal coding gain, and the discrete sine transform which is a sub-optimal transform when the correlation coefficient is in the interval from -0.5 to 0.5 can be used in conjunction with the discrete cosine transform in the video coding. In this paper, an alternative transform that alternatively uses the discrete sine transform and integer cosine transform in H.264/AVC by using rate-distortion optimization is proposed. The proposed method achieves a BD-PSNR gain of up to 0.71 dB compared to H.264/AVC JM 10.2 at relatively high bitrates.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.369-372
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• 2000

An overview on applications of wavelet transform in power systems presented in this paper. Wavelet transform is capable of making trade-offs between time and frequency resolutions, which is a property that makes it appropriate for the analysis of non stationary signal. In recent years, wavelet transform is widely accepted as a technology offering an alternative way due to its flexibility in representation of non-stationary signal even in power systems. This paper presents various applications of wavelet transform in power systems. Wavelet transform has been used by the authors in the field of power system protection for the classification of transient signals, and forecasting of short term loads and system marginal price and so on. Various research works carried out by many researchers in power systems are summarized.

• Nonlinear Functional Analysis and Applications
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• v.26 no.2
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• pp.381-392
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• 2021

During the last several decades, a great variety of fractional kinetic equations involving diverse special functions have been broadly and usefully employed in describing and solving several important problems of physics and astrophysics. In this paper, we aim to find solutions of a type of fractional kinetic equations associated with the (p, q)-extended 𝜏 -hypergeometric function and the (p, q)-extended 𝜏 -confluent hypergeometric function, by mainly using the Laplace transform. It is noted that the main employed techniques for this chosen type of fractional kinetic equations are Laplace transform, Sumudu transform, Laplace and Sumudu transforms, Laplace and Fourier transforms, P_𝛘-transform, and an alternative method.

• Economic and Environmental Geology
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• v.28 no.5
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• pp.527-533
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• 1995

A disadvantage of Fourier analysis is that frequency information can only be extracted for the complete duration of a signal f(t). Since the Fourier transform integral extends over all time, from $-{\infty}$ to $+{\infty}$), the information it provides arises from an average over the whole length of the signal. If there is a local oscillation representing a particular feature, this will contribute to the calculated Fourier transform $F({\omega})$, but its location on the time axis will be lost There is no way of knowing whether the value of $F({\omega})$ at a particular ${\omega}$ derives from frequencies present throughout the life of f(t) or during just one or a few selected periods. This disadvantage is overcome in wavelet analysis which provides an alternative way of breaking a signal down into its constituent parts. The main advantage of the wavelet transform over the conventional Fourier transform is that it can not only provide the combined temporal and spectral features of the signal, but can also localize the target information in the time-frequency domain simultaneously. The wavelet transform distinguishes itself from Short Time Fourier Transform for time-frequency analysis in that it has a zoom-in and zoom-out capability.

• Steel and Composite Structures
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• v.18 no.4
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• pp.889-907
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• 2015

This paper aims to present an alternative analytical method for transient vibration analysis of doubly-curved laminated shells subjected to dynamic loads. In the method proposed, the governing differential equations of laminated shell are derived using the dynamic version of the principle of virtual displacements. The governing equations of first order shear deformation laminated shell are obtained by Navier solution procedure. Time-dependent equations are transformed to the Laplace domain and then Laplace parameter dependent equations are solved numerically. The results obtained in the Laplace domain are transformed to the time domain with the help of modified Durbin's numerical inverse Laplace transform method. Verification of the presented method is carried out by comparing the results with those obtained by Newmark method and ANSYS finite element software. Also effects of number of laminates, different material properties and shell geometries are discussed. The numerical results have proved that the presented procedure is a highly accurate and efficient solution method.

• Journal of Ocean Engineering and Technology
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• v.20 no.2 s.69
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• pp.8-15
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• 2006

Guided-waves-based mortar-filled steel pipe inspection is carried out through using EMAT (Electro magnetic acoustic transducer) and wavelet transform. Possibly existing anomalies such as separation (or void) and inclusion are made in the fabricated mortar-fled steel pipes: these anomalies are infected. Since guided waves have the long range inspection capability, EMAT has its own advantages over the conventional PZT (Piezoelectric zirconate titanate), and wavelet transform gives the multi-resolution on time-frequency domain results, the suggested technique gives an alternative way for inspecting mortar-filled steel pipes, which are popularly used for supporting marine structures such as piers, wharfs, moles, and dolphins. Through this study, it is show that the suggested technique is promising for detecting the amounts of separations and inclusions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.83-89
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• 2016

The group formation problem of the machine and part is a critical issue in the planning stage of cellular manufacturing systems. The machine-part grouping with alternative process plans means to form machine-part groupings in which a part may be processed not only by a specific process but by many alternative processes. For this problem, this study presents an algorithm based on self organizing neural networks, so called SOM (Self Organizing feature Map). The SOM, a special type of neural networks is an intelligent tool for grouping machines and parts in group formation problem of the machine and part. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. In the proposed algorithm, output layer in SOM network had been set as one-dimensional structure and the number of output node has been set sufficiently large in order to spread out the input vectors in the order of similarity. In the first stage of the proposed algorithm, SOM has been applied twice to form an initial machine-process group. In the second stage, grouping efficacy is considered to transform the initial machine-process group into a final machine-process group and a final machine-part group. The proposed algorithm was tested on well-known machine-part grouping problems with alternative process plans. The results of this computational study demonstrate the superiority of the proposed algorithm. The proposed algorithm can be easily applied to the group formation problem compared to other meta-heuristic based algorithms. In addition, it can be used to solve large-scale group formation problems.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1207-1214
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• 1995

We present an optimized integer cosine transform(OICT) as an alternative approach to the conventional discrete cosine transform(DCT), and its fast computational algorithm. In the actual implementation of the OICT, we have used the techniques similar to those of the orthogonal integer transform(OIT). The normalization factors are approximated to single one while keeping the reconstruction error at the best tolerable level. By obtaining a single normalization factor, both forward and inverse transform are performed using only the integers. However, there are so many sets of integers that are selected in the above manner, the best OICT matrix obtained through value minimizing the Hibert-Schmidt norm and achieving fast computational algorithm. Using matrix decomposing, a fast algorithm for efficient computation of the order-8 OICT is developed, which is minimized to 20 integer multiplications. This enables us to implement a high performance 2-D DCT processor by replacing the floating point operations by the integer number operations. We have also run the simulation to test the performance of the order-8 OICT with the transform efficiency, maximum reducible bits, and mean square error for the Wiener filter. When the results are compared to those of the DCT and OIT, the OICT has out-performed them all. Furthermore, when the conventional DCT coefficients are reduced to 7-bit as those of the OICT, the resulting reconstructed images were critically impaired losing the orthogonal property of the original DCT. However, the 7-bit OICT maintains a zero mean square reconstruction error.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.25-28
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• 2001

A theory of binary wavelets has been recently proposed by using two-band perfect reconstruction filter banks over binary field . Binary wavelet transform (BWT) of binary images can be used as an alternative to the real-valued wavelet transform of binary images in image processing applications such as compression, edge detection, and recognition. The BWT, however, requires large amount of computations since its operation is accomplished by matrix multiplication. In this paper, a fast BWT algorithm which utilizes filtering operation instead or matrix multiplication is presented . It is shown that the proposed algorithm can significantly reduce the computational complexity of the BWT. For the decomposition and reconstruction or an N ${\times}$ N image, the proposed algorithm requires only 2LN$^2$ multiplications and 2(L-1)N$^2$addtions when the filter length is L, while the BWT needs 2N$^3$multiplications and 2N(N-1)$^2$additions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.484-490
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• 2008

For CSLDV, the Chebyshev demodulation (or polynomial) technique and Hilbert transform approach have been used for mode shape reconstruction with harmonic excitation. In this paper, the Hilbert-Huang transform approach was applied as an alternative to impact excitation cases in terms of a numerical approach. The vibration of the tested structure is modeled using impulse response functions. In order to verify this technique, a simply supported beam was chosen as the test rig. With additional innovative steps which are the ideal-band pass filter and the nodal point determination, Hilbert-Huang transformation can be used for a good mode shape reconstruction even in the impact excitation case.