• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.1
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• pp.1-5
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• 2009

In this paper, we propose a method that applies Vector Fitting (VF) technique to the equivalent circuit model for RF passive components. These days wireless communication system is getting smaller and smaller. So EMI/EMC is an issue in RF. We can solve PI/SI (Power Integrity/Signal Integrity) that one of EMI/EMC problem apply IFFT for 3D EM simulation multiple with input signal. That is time consuming task. Therefore equivalent circuit model using RF passive component is important. VF schemes are implemented to obtain the rational functions. S parameters of the equivalent circuit model is compared to those of EM simulation in case of the microstrip line structure.

• Fibers and Polymers
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• v.7 no.2
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• pp.195-202
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• 2006

Tight-fitting clothing pattern reflecting the accurate information of the 3D body shape has been one of the challenges for garment industry, however, fitting problems still exist. The objectives of the paper is to develop a 2D pattern which fits tightly to the 3D human scan data for sports suits that need comfort and function for maximum performance. In this study, the user graphic interface application software for the semi-automatic garment pattern generation has been implemented using the triangle simplification scheme together with 2D projections of free-falling of 3D surface polygons keeping the original 3D surface area preservation. A typical application of the developed pattern to the functional body suits is presented and verification of the proposed method is also provided.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1232-1238
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• 2018

This paper proposes methods for improving mass spectral resolution for a gas chromatograph mass spectrometer. The slope signs of the 1st and 2nd fitting functions for the ion signal block of each mass index are obtained, and the unnecessary element signals in the ion signal block are removed. The spectrum can be obtained by obtaining the second-order fitting function of the reconstructed ion signal block using only the effective ion signals. In addition, the resolution of the mass spectrum can be improved by correcting the error caused by the shift of the spectral peak position. To verify the performance of the proposed methods, computer simulations were performed using the actual ion signals obtained from the GC-MS system under development. Simulation results show that the proposed method is valid.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.460-464
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• 2000

As device dimensions are lastly scaled down, impact ionization(I.I.) events are very important to analyze hot carrier transport in high energy region, and the exact model of impact ionization is demanded on device simulation. We calculate full band model by empirical pseudopotential method and the impact ionization rate is derived from modified Keldysh formula. We calculate impact ionization coefficients by full band Monte Carlo simulator to investigate temperature-and field-dependent characteristics of impact ionization for GaAs. Resultly impact ionization coefficients are In good agreement with experimental values at 300k. We know energy is increasing along increasing the field. while energy is decreasing along increasing the temperature since the phonon scattering rates for omission mode are very high at high temperature. The logarithmic fitting function of impact ionization coefficients is described as a second orders function for temperature and field. The residuals of the logarithmic fitting function are mostly within 5%. We know, therefore, logarithm of impact ionization coefficients has quadratic dependence on temperature and field, and we can save time of calculating the temperature- and field-dependent impact ionization coefficients.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.253-263
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• 2021

Machine learning is the process of constructing a cost function using learning data used for learning and an artificial neural network to predict the data, and finding parameters that minimize the cost function. Parameters are changed by using the gradient-based method of the cost function. The more complex the digital signal and the more complex the problem to be learned, the more complex and deeper the structure of the artificial neural network. Such a complex and deep neural network structure can cause over-fitting problems. In order to avoid over-fitting, a weight decay regularization method of parameters is used. We additionally use the value of the cost function in this method. In this way, the accuracy of machine learning is improved, and the superiority is confirmed through numerical experiments. These results derive accurate values for a wide range of artificial intelligence data through machine learning.

• Smart Structures and Systems
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• v.24 no.4
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• pp.475-490
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• 2019

The detection of structural damage without a priori information on the healthy state is challenging. In order to address the issue, the study presents a baseline-free approach to detect damage in beam structures based on an actual influence line. In particular, a multi-segment function-fitting calculation is developed to extract the actual deflection influence line (DIL) of a damaged beam from bridge responses due to a passing vehicle. An intact basis function based on the measurement position is introduced. The damage index is defined as the difference between the actual DIL and a constructed function related to the intact basis, and the damage location is indicated based on the local peak value of the damage index curve. The damage basis function is formulated by using the detected damage location. Based on the intact and damage basis functions, damage severity is quantified by fitting the actual DIL using the least-square calculation. Both numerical and experimental examples are provided to investigate the feasibility of the proposed method. The results indicate that the present baseline-free approach is effective in detecting the damage of beam structures.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.85-97
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• 1998

The existing edge detection methods can not represent the real edge of object at fitting point or detect the edge which has unsufficient connecting trait. Especially, the two-fold thick edge detected by these methods cannot coincide real boundary of subject and it's location. To overcome these problems, we introduce the Genetic Algorithm(GA) in edge detection. The energy function is the value of fixel's satisfaction degree to edge condition. And it consists of the fitness value to image formation type, fitness value to connecting trait to it's neighboring edge and evalulation function which can represents the edge at fitting point as one fixel. This method is superior to remove the noise in edge detection than the existing methods. And it also detects the clear and exact edge because it can find the one fixel which is located at fitting point and has strong connecting trait.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.252-257
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• 2000

An efficient method is developed for mold thermal cycle analysis in repeated forming process, which is well suited to the analysis in TV glass production. plunger, which is a mold to press-form the glass, undergoes temperature fluctuation during a cycle due to the repeated contact and separation from the glass, which attains a cyclic steady state in the end. If analyzed straightforwardly of this problem, it leads to more than 80 cycles to get reasonable solution, and it is yet hard to setup stopping creteria due to extremely slow convergence. An exponential fitting method is proposed to solve the problem, where an exponential function is found to best approximate temperature values of 3 consecutive cycles, and new cycle is restarted with the function value at infinite time. From numerical implementation, it is found that the method reduces the number of cycles dramatically to only $6{\sim}15$ cycles to reach accurate solution within $1^{\circ}$ error. A system for the analysis is contructed, in which the thermal analysis is performed by commercial software ANSYS, and the fitting of the result is done by IMSL library.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1063-1075
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• 2012

To locate an object accurately in the wireless sensor networks, the distance measure based on time-delay plays an important role. In this paper, we propose a maximum likelihood (ML) time-delay estimation algorithm in multi-path wireless propagation channel. We get the joint probability density function after sampling the frequency domain response of the multi-path channel, which could be obtained by the vector network analyzer. Based on the ML criterion, the time-delay values of different paths are estimated. Considering the ML function is non-linear with respect to the multi-path time-delays, we first obtain the coarse values of different paths using the subspace fitting algorithm, then take them as an initial point, and finally get the ML time-delay estimation values with the pattern searching optimization method. The simulation results show that although the ML estimation variance could not reach the Cramer-Rao lower bounds (CRLB), its performance is superior to that of subspace fitting algorithm, and could be seen as a fine algorithm.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.201-208
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• 2012

Accurately segmenting lumen border in intravascular ultrasound images (IVUS) is very important to study vascular wall architecture for diagnosis of the cardiovascular diseases. After each of IVUS image is transformed to a polar coordinated image, initial points are detected using wavelet transform. Then, lumen border is initialized as the set of important points using non parametric probability density function and smoothing function by removing outlier initial points occurred by noises and artifacts. Finally, polynomial curve fitting is applied to obtain real lumen border using filtered important points. The evaluation of proposed method was performed with related method and the proposed method produced accurate lumen contour detection when compared to another method in most types of IVUS images.