• 한국통신학회논문지
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• 제38C권9호
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• pp.764-774
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• 2013

4세대 셀룰러 네트워크의 데이터양이 증가하면서, 사업자들은 이를 수용하기 위한 네트워크의 용량 문제에 직면하였다. 따라서, 이 문제를 해결하고자 저렴하고 낮은 전력으로 동작하는 펨토셀이 제안되었는데, 이것은 실내 음영지역의 해소 및 사용자의 서비스 품질을 향상시키는 장점을 갖는다. 그러나 펨토셀 네트워크는 소수의 셀에 많은 부하 (Load)가 집중될 가능성이 있다. 이를 해결하고자, 부하 분산 (Load balancing) 알고리즘 중 하나인 MLB (Mobility Load Balancing) 알고리즘이 제안되었다. 이 알고리즘은 부하 분산을 위해 셀 외곽의 사용자를 인접한 셀로 강제 핸드오버한다. 본 논문에서는 주기적으로 동작하는 MLB 알고리즘에서, 주기가 변했을 때 네트워크 성능 지표들이 어떻게 변화하는지를 확인한다. 실험 결과, 짧은 주기로 동작할 때 데이터 차단율이 낮고, 긴 주기로 동작할 때 핸드오버의 빈도가 낮으며 시간당 처리량 (Throughput)이 높은 것을 확인하였다. 이 결과를 바탕으로, 본 논문에서는 적응적 (Adaptive) 주기의 MLB 알고리즘을 제안하였다. 제안된 알고리즘은 긴 주기와 짧은 주기로 동작하는 알고리즘의 장점을 모두 포함하는 것을 실험적으로 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권1호
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• pp.371-384
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• 2019

Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.

• 천문학회보
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• 제40권1호
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• pp.71.1-71.1
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• 2015

We prensent the near-infrared(NIR) images of the asymmetric circumstellar disk around a T-Tauri star in the ${\rho}$ Ophiuchi star-forming region, and two faint stellar objects around central star. These results were obtainted with the Subaru Telescope with HiCIAO(the High-Contrast Instrument with Adaptive Optics) and IRCS(the InfraRed Camera and Spectrograph). The disk shows center-offset from the star and a strong morphological asymmetry along both the major and minor axis. The physical conditions in the disk is derived from the infrared visibilites results and the complete spectral energy distribution using HOCHUNK3D, Monte-Carlo radiative transfer code. Two companion candidates are separated by 11.6 arcsec(~1450 au at 125 parsec) and 4.34 arcsec(~540 au at 125 parsec). This could be the first case, which imaged both of planetary mass companions and disk around same star. We discuss physical structures of the disk, and probablity that two candidates are real companions.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.403-406
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• 2005

The purpose of this paper is to propose ways to remove false color noise (FCN) generated during de-mosaicing on RGB Bayer pattern images. In case of images sensors adapting Bayer pattern color filters array (CFA), de-mosaicing is conducted to recover the RGB color data in single pixels. Here, FCN phenomena would occur where there is clearer silhouette or contrast of colors. The FCN phenomena found during de-mosaicking process appears locally in the edges inside the image and the proposed method of eliminating this is to convert RGB color space to YCbCr space to conduct smoothing process. Moreover, for edges where different colors come together, censoring based smoothing technique is proposed as a way to minimize color blurring effect.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2016년도 하계학술대회
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• pp.361-363
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• 2016

현재 차량 내 운전자에게 편의성과 안전성을 제공하는 시스템이 활발히 개발 중이고 향후 ADAS(Advanced Driver Assistance System)와 스마트 자동차에서 영상 정보를 이용한 물체 추적과 분석은 매우 중요한 부분을 차지하고 있다. 영상에서 얻을 수 있는 정보 중 현재 도로의 이정표 정보는 중요한 분석 정보로 사용된다. 하지만 국내 도로표지판 검출 연구의 경우 유럽과 북미와 비교하여 연구 개발이 활발히 진행되고 있지 않다. 국내의 경우 도로 이정표에서 영문자뿐만 아니라 한글 문자 정보까지 포함하고 있어 검출이 쉽지 않다. 또한 비교적 밝고 잡음이 적은 검출하기 좋은 환경에서는 검출이 잘 되지만 명암이 뚜렷하지 않고 잡음이 많은 환경에서는 도로 이정표 문자 검출이 어렵다. 이에 본 논문에서는 CLAHE(Contrast-Limited Adaptive Histogram Equalization) 방법을 적용하여 영상이 어둡고 잡음이 많은 환경에서 국내 도로 이정표의 문자 정보를 얻는다. 실험 결과, 기존 방법에 비해 문자 영역 검출 성능이 향상되었다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2016년도 하계학술대회
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• pp.260-263
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• 2016

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted leastsquaresfiltering with iCAM06, for showing more perceptual high dynamic range images in conventional display, while avoiding visual halo artifacts. We decompose high dynamic range image into base layer and detail layer. The base layer has large scale variation, it is obtained by using weighted least squares filtering, and then the base layer incorporates iCAM06 model. Then, adaptive compression on the base layer according to human visual system. Only the base layer reduces contrast, and preserving detail. The resultshows more perceptual color appearance and preserve fine detail, while avoiding common artifacts.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.1450-1454
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• 2006

Empirical mode decomposition (EMD) is applied to analyze time series characterized with nonlinearity and nonstationarity. This decomposition could be utilized to construct finite and small number intrinsic mode functions (IMF) that describe complicated time series, while admitting the Hilbert transformation properties. EMD has the capability of being adaptive, capture local characteristics, and applicable to nonlinear and nonstationary processes. Unlike discrete wavelet transform (DWT), IMF eliminates spurious harmonics and retains meaningful instantaneous frequencies. Examples based on data representing natural phenomena are given to demonstrate highlight the power of this method in contrast and comparison of other ones. A presentation of the energy-frequency-time distribution of these signals found to be more informative and intuitive when based on Hilbert transformation.

• Structural Engineering and Mechanics
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• 제12권1호
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• pp.51-69
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• 2001

Whereas the potential of static inelastic analysis methods is recognised in earthquake design and assessment, especially in contrast with elastic analysis under scaled forces, they have inherent shortcomings. In this paper, critical issues in the application of inelastic static (pushover) analysis are discussed and their effect on the obtained results appraised. Areas of possible developments that would render the method more applicable to the prediction of dynamic response are explored. New developments towards a fully adaptive pushover method accounting for spread of inelasticity, geometric nonlinearity, full multi-modal, spectral amplification and period elongation, within a framework of fibre modelling of materials, are discussed and preliminary results are given. These developments lead to static analysis results that are closer than ever to inelastic time-history analysis. It is concluded that there is great scope for improvements of this simple and powerful technique that would increase confidence in its employment as the primary tool for seismic analysis in practice.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.315-317
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• 2006

In this paper, we design a terminal sliding mode controller based on neural network for nonlinear systems with uncertainties. Terminal sliding mode control (TSMC) method can drive the tracking errors to zero within finite time. Also, TSMC has the advantages such as improved performance, robustness, reliability and precision by contrast with classical sliding mode control. For the control of nonlinear system with uncertainties, we employ the self-recurrent wavelet neural network(SRWNN) which is used for the prediction of uncertainties. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out simulations to illustrate the effectiveness of the proposed control.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.456-465
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• 2006

The problem of recursive filtering far linear discrete-time systems with uncertainties is considered. A new suboptimal filtering algorithm is herein proposed. It is based on the fusion formula, which represents an optimal mean-square linear combination of local Kalman estimates with weights depending on cross-covariances between local filtering errors. In contrast to the optimal weights, the suboptimal weights do not depend on current measurements, and thus the proposed algorithm can easily be implemented in real-time. High accuracy and efficiency of the suboptimal filtering algorithm are demonstrated on the following examples: damper harmonic oscillator motion and vehicle motion constrained to a plane.