• Bulletin of the Korean Mathematical Society
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• v.45 no.3
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• pp.523-561
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• 2008

The purpose of this paper is to survey the use of the important method of scaling in analysis, and particularly in complex analysis. Applications are given to the study of automorophism groups, to canonical kernels, to holomorphic invariants, and to analysis in infinite dimensions. Current research directions are described and future paths indicated.

• Structural Engineering and Mechanics
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• v.14 no.3
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• pp.345-364
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• 2002

The scaling laws for vibration response of anti-symmetrically laminated plates are derived by applying the similitude transformation to the governing differential equations directly. With this approach, a closed-form solution of the governing equations is not required. This is a significant advantage over the method employed by other researchers where similitude transformation is applied to the closed-form solution. The scaling laws are tested by comparing the similitude fundamental frequencies to the theoretical fundamental frequencies determined from the available closed-form solutions. In case of complete similitude, similitude solutions from the scaling laws exactly agree with the theoretical solutions. Sometimes, it may not be feasible to select the model which obeys the similarity requirement completely, therefore partial similitude is theoretically investigated and approximate scaling laws are recommended. The distorted models in stacking sequences and laminated material properties demonstrate reasonable accuracy. On the contrary, a model with distortion in fiber angle is not recommended. The derived scaling laws are very useful to determine the vibration response of complex prototypes by performing the experiment on a model with required similarities.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.67-72
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• 2017

Deep learning neural network becomes very popular nowadays due to the reason that it can learn a very complex dataset such as the image dataset. Although deep learning neural network can produce high accuracy on the image dataset, it needs a lot of time to reach the convergence stage. To solve the issue, we have proposed a scaling method to improve the neural network to achieve the convergence stage in a shorter time than the original method. From the result, we can observe that our algorithm has higher performance than the other previous work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.790-809
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• 2019

The design of an efficient scaler to enhance the edge data is one of the most important issues in video signal applications, because the perceptual quality of the processed image is sensitively affected by the degradation of edge data. Various conventional scaling schemes have been proposed to enhance the edge data. In this paper, we propose an efficient scaling algorithm for this purpose. The proposed method is based on the discrete cosine transform-based interpolation filter (DCT-IF) because it outperforms other scaling algorithms in various configurations. The proposed DCT-IF incorporates weighting parameters that are optimized for training data. Simulation results show that the quality of the resized image produced by the proposed DCT-IF is much higher than that of those produced by the conventional schemes, although the proposed DCT-IF is more complex than other conventional scaling algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.452-472
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• 2019

Most existing wavelet-based multiplicative watermarking methods are affected by geometric attacks to a certain extent. A serious limitation of wavelet-based multiplicative watermarking is its sensitivity to rotation, scaling, and translation. In this study, we propose an image watermarking method by using dual-tree complex wavelet transform with a multi-objective optimization approach. We embed the watermark information into an image region with a high entropy value via a multiplicative strategy. The major contribution of this work is that the trade-off between imperceptibility and robustness is simply solved by using the multi-objective optimization approach, which applies the watermark error probability and an image quality metric to establish a multi-objective optimization function. In this manner, the optimal embedding factor obtained by solving the multi-objective function effectively controls watermark strength. For watermark decoding, we adopt a maximum likelihood decision criterion. Finally, we evaluate the performance of the proposed method by conducting simulations on benchmark test images. Experiment results demonstrate the imperceptibility of the proposed method and its robustness against various attacks, including additive white Gaussian noise, JPEG compression, scaling, rotation, and combined attacks.

• Bulletin of the Korean Chemical Society
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• v.17 no.2
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• pp.198-200
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• 1996

The resonance width may be directly determined by solving an eigenvalue equation for width operator which is derived in this work based on the method of complex scaling transformation. The width operator approach is advantageous to the conventional rotating coordinate method in twofold; 1) calculation can be done in real arithmetics and, 2) so-called θ-trajectory is not required for determining the resonance widths. Application to one- and two-dimensional model problems can be easily implemented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.65-68
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• 2001

RBFN has some problem that because the basis function isnt orthogonal to each others the number of used basis function goes to big. In this reason, the Wavelet Neural Network which uses the orthogonal basis function in the hidden node appears. In this paper, we propose the composition method of the actual function in hidden layer with the scaling function which can represent the region by which the several wavelet can be represented. In this method, we can decrease the size of the network with the pure several wavelet function. In addition to, when we determine the parameters of the scaling function we can process rough approximation and then the network becomes more stable. The other wavelets can be determined by the global solutions which is suitable for the suggested problem using the genetic algorithm and also, we use the back-propagation algorithm in the learning of the weights. In this step, we approximate the target function with fine tuning level. The complex neural network suggested in this paper is a new structure and important simultaneously in the point of handling the determination problem in the wavelet initialization.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.11-18
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• 2012

In this paper, the occurrence of a stopband phenomenon when an acoustic wave propagates through periodically corrugated ducts is discussed using theoretical and BEM analyses. A 2-D duct with sinusoidally corrugated upper and lower walls is considered. When the magnitude of the sinusoidal corrugation is sufficiently small compared to the duct's height, the wave equation is solved with the multiple scaling perturbation method. Then stopbands for Bragg and non-Bragg resonances are computed from the condition where frequency becomes a complex number. A 2-D BEM analysis is performed to compute insertion loss of the duct, and stopbands are confirmed as predicted by analytical analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.586-594
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• 2014

Maximizing the operating time by reducing the power consumption is important factor to operate sensor network under water networks. For efficient power consumption, dynamic voltage scaling method is available. This method operates low frequency when there is no workload. In case of abundant workload, high frequency operation completes hard work within short time, reducing power consumption. For this reason, complex cryptography should be computed in high frequency. In this paper, we apply dynamic voltage scaling method to cryptography and show performance evaluation. With this result, we can reduce power consumption for cryptography in under water communication.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.4
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• pp.252-258
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• 1987

Time periodic finite element solutions for sinusoidally excited electromagnetic field problems in moving media are presented. Solutions by the Galerkin method contain spurious oscillations when grid Peclet number is more than one. To suppress these oscillations an upwind finite element method using two different time periodic test functions is introduced. One is multiplied to second and first-order space derivative terma and the other to the time derivative term. Test functions are obtained from trial functions by adding or subtracting quadratic bias functions with appropriate scaling factors. Phase differences are considered between trial functions and bias functions. For simple interpretations of the phase differences, complex scaling factors are used. The proposed method is developed to give nodally exact solutions for uniform grid spacing in one dimensional problems. Based on the one dimensional results, a two dimensional upwinding scheme is also derived.