• Journal of the Korean Society of Radiology
• /
• v.11 no.4
• /
• pp.241-246
• /
• 2017

The existing fractal compression method is effective in generating an artificial shape by approximating its partial regions to a domain block by re-dividing the whole image into a domain region and dividing it into several domain blocks, but it is difficult to implement a computer. In this study, it is difficult to approximate a complex block such as a large-sized block and an affine transformation because a large amount of calculation is required in searching for a combination of similar blocks through a transformation, so a large amount of coding time is required.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.11 no.1
• /
• pp.79-87
• /
• 1991

An efficient numerical procedure for material and geometric nonlinear analysis of reinforced concrete shells under monotonically increasing loads through their elastic, inelastic and ultimate load ranges is developed by using the finite element method. The 8-node Serendipity isoparametric element developed by the degeneration approach including the transverse shear deformation is used. A layered approach is used to represent the steel reinforcement and to discretize the concrete behavior through the thickness. The total Lagrangian formulation based upon the simplified Von Karman strain expressions is used to take into account the geometric nonlinearity of the structure. The material nonlinearities are taken into account by comprising the tension, compression, and shear models of cracked concrete and a model for reinforcement in the concrete; and also a so-called smeared crack model is incorporated. The steel reinforcement is assumed to be in a uniaxial stress state and is modelled as a smeared layer of equivalent thickness. This method will be verified a useful tool to account for geometric and material nonlinearities in detailed analysis of reinforced concrete concrete shells of general form through numerical examples of the sequential paper( ).

• Journal of Korean Society of Transportation
• /
• v.22 no.2 s.73
• /
• pp.43-54
• /
• 2004

This study analyzes characteristics and applicability of genetic algorithms and genetic operators to optimize highway alignments. Genetic algorithms, one of artificial intelligence techniques, are fast and efficient search algorithms for generating, evaluation and finding optimal highway alignment alternatives. The performance of genetic algorithms as an optimal search tool highly depends on genetic operators that are designed as a problem-specific. This study adopts low mutation operators(uniform mutation operator, straight mutation operator, non-uniform mutation operator whole non-uniform mutation operator) to explore whole search spaces, and four crossover operators(simple crossover operator, two-point crossover operator, arithmetic crossover operator, heuristic crossover operator) to exploit food characteristics of the best chromosome in previous generations. A case study and a sensitivity analysis have shown that the eight problem-specific operators developed for optimizing highway alignments enhance the search performance of genetic algorithms, and find good solutions(highway alignment alternatives). It has been also found that a mixed and well-combined use of mutation and crossover operators is very important to balance between pre-matured solutions when employing more crossover operators and more computation time when adopting more mutation operators.

• Journal of Broadcast Engineering
• /
• v.17 no.3
• /
• pp.480-490
• /
• 2012

When interpolating chrominance signal, the H.264/AVC standard uses linear interpolation. In this paper, we suggest more effective method that uses a high precision filter, 6-tap FIR filter, 2-tap linear filter for chroma interpolation. The experimental result shows that the proposed method achieves the BD-Rate decrease without the PSNR decrease compared with Jm11.0kta2.7. The maximum BD-rate improvements on Y component are 1.3%, those of Cb and Cr components are 19.8%, 25.0%, respectively. The average BD-rate improvements on Y component are 0.5%, those of Cb and Cr components are 6.1%, 6.9%, respectively.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.5
• /
• pp.7-12
• /
• 2011

In this papwer, we propose a new feature extraction method, named as Class-augmented Kernel Principal Component Analysis (CA-KPCA), which can extract nonlinear features for classification. Among the subspace method that was being widely used for feature extraction, Class-augmented Principal Component Analysis (CA-PCA) is a recently one that can extract features for a accurate classification without computational difficulties of other methods such as Linear Discriminant Analysis (LDA). However, the features extracted by CA-PCA is still restricted to be in a linear subspace of the original data space, which limites the use of this method for various problems requiring nonlinear features. To resolve this limitation, we apply a kernel trick to develop a new version of CA-PCA to extract nonlinear features, and evaluate its performance by experiments using data sets in the UCI Machine Learning Repository.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.255-260
• /
• 2014

A new sustain driving waveform and its implementation method is proposed to improve the gray scale linearity by applying the sustain waveform for producing the strong and weak discharge in AC plasma display panel. The driving method to express the gray scale of AC PDP is the combination of the several subfield in one TV frame, and the luminance of the each subfield is decided by the number of the sustain pulses. As the same amount of the strong plasma discharge is produced when the sustain pulses are applied during a sustain period, it looks easy to express the linear gray scale ideally. However, it is difficult to express the real linear gray scale due to the production of the address and first sustain discharge irrelevant to gray scale expression in every subfleld. Therefore, a new sustain driving waveformis adopted to produce partially the weak discharge instead of the strong discharge by the modification of the sustain pulses shape during the sustain period and the gray scale expression is close to the linearity.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.7
• /
• pp.881-886
• /
• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.5
• /
• pp.504-511
• /
• 2014

This paper presents a hybrid recognition method, which is based on the nonlinear histogram equalization and the multidimensional intensity variation of an images. The nonlinear histogram equalization based on a adaptively modified function is applied to improve the quality by adjusting the brightness of the image. The multidimensional intensity variation by considering the a extent of 4-step changes in brightness between the adjacent pixels is also applied to reflect accurately the attributes of image. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to comprehensively measure the similarity between the images. The NCC is considered by the intensity variation of each 2-direction(x-axis and y-axis) image. The proposed method has been applied to the problem for recognizing the 50-face images of 40*40 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the histogram equalization, or the linear histogram equalization, respectively.

• Magazine of the Korea Concrete Institute
• /
• v.8 no.6
• /
• pp.223-234
• /
• 1996

The purpose of this paper is to present an analysis method by using the finite element method which can exactly analyze load-deflection relationships, crack propagations. and stresses and strains of reinforcements, tendons, and concrete in behaviors of elastic. inelastic and ultimate ranges of reinforced and prestressed concrete slabs under monotonically increasing loads. For t h i s purpose, the m a t e r i a l and geometric nonlinearities are taken into account in this study. The total Lagrangian formulation based upon the simplified Von Karman strain expressions is used to take into account the geometric nonlinearities of the structure. The material nonlinearities are taken into account by comprising the tension, compression. and shear models of cracked concrete and models for reinforcements and tendons in the concrete : and also a so-called smeared crack model is incorporated. The reinforcements and t,endons are assumed to be in a uniaxial stress state and are modelled as smeared layers of equivalent thickness. For the verification of application and validity of the method proposed in this paper, several numerical examples are analyzcd and compared with experimental results. As a result, this method can successfully predict the nonlinear and inelastic behaviors throughout the fracture of reinforced and prestressed concrete slabs.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2012.05a
• /
• pp.116-116
• /
• 2012

하천유역 내의 인자를 이용하여 댐의 하천유량(stream flow)을 예측하는 일은 수문특성의 연구와 자연재해에 대한 대비 및 수공구조물과 방재시설의 설계 시 중요한 역할을 한다. 이러한 연구는 과거부터 활발히 이루어졌으며, 아직도 보다 높은 정확도의 결과를 얻기 위해 많은 연구들이 이루어지고 있다. 특히 기존의 유역 내 자료를 통해 비선형적 모델인 인공신경망(artificial neural network)을 이용한 하천유량을 예측하는 연구 역시 활발히 이루어지고 있다. 본 연구의 목적은 여러 유역인자들 중 하천유량에 가장 영향을 미치는 변수를 추출하고 보다 정확한 예측모델을 구축하는 것이다. 기존의 입력자료 선정기법중의 하나인 상호정보량(mutual information)과 수문기상자료의 비선형 동역학적 성분을 추출하는 웨이블렛 변환(wavelet transform)을 사용하여 인공신경망에 적용시켰다. 인공신경망을 적용하는 경우, 수문자료에 있어서 변수의 선택과 자료의 상태가 강우예측의 결과에 큰 영향을 미친다. 이러한 변수의 선택에 있어서 상호정보량을 바탕으로 한 인공신경망 입력변수 선택기법이 많이 사용되고 있다. 일반적으로 시계열자료는 경향성(trend), 주기성(periodicity) 및 추계학적 성분(stochastic component)의 선형조합으로 가정될 수 있으며, 특히 경향성과 주기성은 시계열 모형을 위해 제거되어야 할 결정론적 성분으로 취급한다. 즉. 수문 기상자료에 포함되어 있는 경향성과 주기성과 같은 비선형 동역학적 잡음(nonlinear dynamical noise)을 제거하고 입력자료의 카오스적 거동을 보이는 성분을 분리하기 위해 웨이블렛 변환을 사용하였다. 대상유역은 한강 유역에 포함되어 있는 충주댐으로 선택하였다. 유역 내 다양한 인자들과 하천유량사이의 상호정보량을 구해 영향력이 가장 큰 변수를 추출하고, 그 자료를 웨이블렛 변환을 적용하여 인공신경망의 입력자료로 사용하였다. 본 논문에서는 위와 같은 과정을 이용해 추정한 하천유량 결과와 기존의 방법인 상호정보량을 이용해 인공신경망을 적용한 결과를 실제자료와 비교하였다.