• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.505-509
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• 2012

본 연구의 목적은 천해 환경에서의 파형이 점착성 유사의 이동량에 미치는 영향을 살펴보는 것이다. 이를 위하여 이상적인 진동흐름(Oscillatory Flow)을 가정하고 점착성 유사의 이동에 적합한 1DV 모형을 적용하였다. 이상적인 진동흐름을 가정할 때는 다양한 파형을 고려하기 위해 왜곡되거나 비대칭적인 조건을 적용하였다. 크기와 밀도가 변화하는 점착성 유사의 응집현상을 고려하기 위해 기존에 개발된 응집현상 모형을 1DV 모형에 결합하였다. 2차 스토크스파 조건을 모사하기 위해 왜곡된 진동흐름, 톱니파를 모사하기 위해 비대칭 진동흐름 조건을 선택하였다. 수치모의 결과, 왜곡된 진동흐름 조건에서의 점착성 유사 이동량은 흐름의 왜곡도에 큰 영향을 받는 것으로 나타났다. 반면 가는 비점착성 유상의 경우는 왜곡도와 주목할 만한 관계를 보이지 않았다. 비대칭 진동흐름의 경우는 점착성 유사와 비점착성 유사가 서로 다른 방향을 나타내었다. 앞쪽으로 기운 비대칭 진동흐름 조건에서 점착성 유사의 이동량이 뒤쪽 방향으로 발생하는 반면 비점착성 유사는 흐름이 기운 방향과 동일한 방향으로 유사량을 나타내었다. 이러한 현상의 원인으로는 Phase-lag 효과가 고려되었다. 유사의 침강속도와 농도 프로파일의 변화, 물의 유동 조건 등은 복합적인 상호작용을 통해 Phase-lag 효과를 강화시키고 점착성 유사와 비점착성 유사의 이동량이 서로 다른 특성을 나타내게 하는 것으로 고려된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.681-684
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• 2015

Power amplifier is an essential component for transmitting signals to a remote receiver in wireless communication systems. Power amplifier is a non-linear device in general, and the nonlinear distortion becomes severer as the output power increases. The nonlinearity results in spectral regrowth, which leads to adjacent channel interference, and decreases the transmit signal quality. To linearize power amplifiers, many techniques have been developed so far. Among the techniques, digital pre-distortion is known as the most cost and performance effective technique. However, the linearization performance falls down abruptly when the power amplifier operates in its saturation region. This is because of the severe nonlinearity. To relieve this problem, this paper proposes a new adaptive predistortion technique. The proposed technique controls the adaptive algorithm based on the power amplifier input level. Specifically, for small signals, the adaptive predistortion algorithm works normally. On the contrary, for large signals, the adaptive algorithm stops until small signals occur again. By doing this, wrong coefficient update by severe nonlinearity can be avoided. Computer simulation results show that the proposed method can improve the linearization performance compared with the conventional digital predistortion algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.4
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• pp.65-71
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• 2007

Doherty amplifier has more efficiency and distortion than general amplifier. These distortion classified amplitude distortion and phase distortion, memory effect distortion. This paper reports on an attempt to investigate, model and quantity the contribution of the electrical nonlinearity effects and the thermal memory effects to a doherty amplifier's distortion generation and suggests thermal memory effect compensator for pre-distorter. Also this paper reports on the development of an accurate dynamic expression of the instantaneous junction temperature as a function of the instantaneous dissipated power. The parameters of suggested model suppress thermal memory effects doherty amplifier with pre-distorter. Pre-distorter with electrothermal memory effect compensator for doherty amplifier enhanced ACLR performance about 22 dB than general doherty amplifier. Experiment results were mesured by 50W LDMOS Doherty amplifier and pre-distorter with electrothermal memory effect compensator was simulated by ADS.

• Korean Journal of Optics and Photonics
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• v.30 no.6
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• pp.237-242
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• 2019

A compact virtual-reality (VR) device with wider field of view provides users with a more realistic experience and comfortable fit, but VR lens distortion is inevitable, and the amount of distortion must be measured for correction. In this paper, we propose two different full-field distortion-measurement methods, considering the characteristics of the VR device. The first is the distortion-measurement method using multiple images based on camera calibration, which is a well-known technique for the correction of camera-lens distortion. The other is the distortion-measurement method by measuring lens distortion at multiple measurement points by rotating a camera. Our proposed methods are verified by measuring the lens distortion of Google Cardboard, as a representative sample of a commercial VR device, and comparing our measurement results to a simulation using the nominal values.

• Korean Journal of Optics and Photonics
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• v.31 no.2
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• pp.88-95
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• 2020

In this study, we present methods to quantitatively analyze and correct the distortions and biocular parallaxes in a head-up display (HUD). To analyze asymmetrical distortions, five kinds of distortions are proposed and evaluated at five eye positions of an eyebox. The differences between distortions evaluated at the four corners of the eyebox and that at the center are defined as the relative distortions, which occur due to head motion of the driver. We also define the convergence and divergence parallaxes at six biocular positions in the eyebox to quantitatively analyze them. Using these analytical methods, we constrain the degree of biocular parallaxes and distortion changes with eye position to be small, so that an optical system nearly free from them can be obtained by optimization design for HUD optics.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.31-38
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• 2009

Lens distortion is inevitable phenomenon in machine vision system. More and more distortion phenomenon is occurring in order to choice of lens for minimizing cost and system size. As shown above, correction of lens distortion is critical issue. However previous lens correction methods using camera model have problem such as nonlinear property and complicated operation. And recent lens correction methods using neural network also have accuracy and efficiency problem. In this study, I propose new algorithms for correction of lens distortion. Distorted image is divided based on the distortion quantity using k-means. And each divided image region is corrected by using neural network. As a result, the proposed algorithms have better accuracy than previous methods without image division.

• Journal of Platform Technology
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• v.11 no.6
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• pp.68-78
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• 2023

In this paper, the color distortion in images with haze would be analyzed. When haze is included in the scene, the color signal reflected in the scene is accompanied by color distortion due to the influence of transmittance according to the haze component. When the influence of haze is excluded by a conventional de-hazing method, the distortion of color tends to not be sufficiently resolved. Khoury et al. used the dark channel priority technique, a haze model mentioned in many studies, to determine the degree of color distortion. However, only the tendency of distortion such as color error values was confirmed, and specific color distortion analysis was not performed. This paper analyzes the characteristic of color distortion and proposes a restoration method that can reduce color distortion. Input images of databases used by Khoury et al. include Macbeth color checker, a standard color tool. Using Macbeth color checker's color values, color distortion according to changes in haze concentration was analyzed, and a new color distortion model was proposed through modeling. The proposed method is to obtain a mapping function using the change in chromaticity by step according to the change in haze concentration and the color of the ground truth. Since the form of color distortion varies from step to step in proportion to the haze concentration, it is necessary to obtain an integrated thought function that operates stably at all stages. In this paper, the improvement of color distortion through the proposed method was estimated based on the value of angular error, and it was verified that there was an improvement effect of about 15% compared to the conventional method.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.51-54
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• 2000

차세대 초고속 무선 전송을 위한 OFDM (orthogonal frequency division multiplexing) 방식에서는 전송 신호의 진폭이 큰 PAPR (peak-to-average power ratio)을 갖게 되어 송신기에서 사용되는 고출력 증폭기의 비선형성에 의해 큰 왜곡을 받게 된다. 이러한 왜곡의 보상을 위하여 우리는 고정점 반복 (fixed point iteration)에 기반한 사전왜곡기 (predistorter)를 제안하였으나, 이는 고출력 증폭기의 특성이 변화하지 않는다는 가정에서 구현되었다. 본 논문에서는 구간 선형 근사에 기반하여 고출력 증폭기의 시변 특성을 추종하는 새로운 기법과 이렇게 근사된 고출력 증폭기 특성을 이용하는 적응적인 고정점 반복 사전왜곡기의 구현을 제안한다. 모의실험 결과, 제안된 고출력 증폭기 근사 방법은 랜덤한 증폭기 특성 변화를 매우 효과적으로 추종하며 이러한 근사 결과를 이용한 고정점 반복 사전왜곡기는 우수한 성능을 보임을 확인하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.192-193
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• 2017

본 논문에서는 비디오 영상 압축 왜곡 제거를 위해 Generative Adversarial Network (GAN)을 적용한 컨벌루션 뉴럴 네트워크 (CNN) 모델을 제안한다. GAN 모델의 생성 모델 (Generator)은 노이즈가 아닌 High Efficiency Video Coding (HEVC)로 압축된 영상을 입력 받은 뒤, 압축 왜곡이 제거된 영상을 출력하며, 분류 모델 (Discriminator)은 원본 영상과 압축된 영상을 입력 받은 뒤, 원본 영상과 압축 왜곡이 포함된 압축된 영상을 분류한다. 분류 모델은 5 개 층을 쌓은 컨벌루션 뉴럴 네트워크 구조를 사용하였고, 생성 모델은 5 개 층을 쌓은 SRCNN 구조와 VDSR 구조를 기반으로 한 두 개의 모델을 이용한 실험을 통해 얻은 결과를 비교하였다. 비디오 영상 압축 왜곡 제거 실험을 위해 원본 비디오 영상을 HEVC 을 이용하여 2Mbps, 4Mbps 로 압축된 영상을 사용하였으며, 압축된 영상 대비 왜곡이 제거된 영상을 얻을 수 있었다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.70-72
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• 2016

본 논문에서는 기존의 인지적 영상 압축 기법에 사용되었던 Just Noticeable Distortion(JND) 모델이 압축과정에서 생기는 왜곡인 양자화 왜곡에 적합하지 않는 다는 것을 보이고, 그 한계점을 해결하기 위하여 Just Noticeable Blur(JNB)의 개념을 적용하여 영상 압축에 적합한 모델을 제시하였다. 주파수 공간에서 영상의 복잡도 특징을 나타내는 Spectral Contras Index(SCI) 값을 사용해서 영상의 DCT 블록별 JNB 를 추정하고 이를 기반으로 영상의 DCT 계수 값을 감소시켜 최신의 DCT 기반 JND 를 적용한 인지적 압축 영상에 비해 더 낮은 PSNR 을 가지면서 왜곡도 인지되지 않는 영상을 얻을 수 있었다. 새롭게 제시한 모델을 적용하면 인지적 영상압축에서 기존의 방법보다 더 낮은 비트율로 유사한 인지적 화질 성능을 발휘할 것으로 예상된다.