• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.628-632
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• 2005

Remote sensing through atmospheric turbulence had been hard works for a long time, because wavefront distortion due to the Earth's atmospheric turbulence deteriorates image quality. But due to the appearance of adaptive optics, it is no longer difficult things. Adaptive optics is the technology to correct random optical wavefront distortions in real time. For past three decades, research on adaptive optics has been performed actively. Currently, most of newly built telescopes have adaptive optical systems. Adaptive optical system is typically composed of three parts, wavefront sensing, wavefront correction and control. In this work, the wavefront sensing technology for adaptive optical system is treated. More specifically, shearing interferometers and Shack-Hartmann wavefront sensors are considered. Both of them are zonal wavefront sensors and measure the slope of a wavefront. . In this study, the shearing interferometer is made up of four right-angle prisms, whose relative sliding motions provide the lateral shearing and phase shifts necessary for wavefront measurement. Further, a special phase-measuring least-squares algorithm is adopted to compensate for the phase-shifting error caused by the variation in the thickness of the index-matching oil between the prisms. Shack-Hartmann wavefront sensors are widely used in adaptive optics for wavefront sensing. It uses an array of identical positive lenslets. And each lenslet acts as a subaperture and produces spot image. Distortion of an input wavefront changes the location of spot image. And the slope of a wavefront is obtained by measuring this relative deviation of spot image. Structures and measuring algorithms of each sensor will be presented. Also, the results of wavefront measurement will be given. Using these wavefront sensing technology, an adaptive optical system will be built in the future.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.299-308
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• 2011

In this study, we develop a pressure observer to measure the cylinder length of a harbor-construction robot. For the robot control, sensors are required to measure the length of a hydraulic cylinder. The cylinder-position sensor is relatively expensive when the operating environment prohibits external approaches for the measurement of the cylinder position. LVDT or linear scales are usually mounted on the outside of the cylinder, which causes poor durability on a construction site. We use a pressure sensor to indirectly estimate the length of the cylinder. The pressure sensor is mounted inside a hydraulic valve box so that it is protected by the box and easy to waterproof for an underwater robot. By treating oil as a compressible fluid, we derive the nonlinear pressure dynamics as a function of the cylinder position, velocity, and pressure. The recursive least squares (RLS) algorithm is applied to identify the dynamic parameters, and the pressure observer estimates the cylinder position through the pressure acting on the head and the rod of the hydraulic cylinder. The position accuracy is relatively low, but it is acceptable for a construction robot that handles large armor stones.

• Journal of Distribution Science
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• v.18 no.1
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• pp.107-121
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• 2020

Purpose: Shared mobility services are the most notable in the shared economy; however, they have yet to be activated in Korea due to various regulations and conflicts amongst stakeholders. Nevertheless, shared mobility has become an irresistible trend of the times, as it can cause a great deal of economic and environmental benefits. In this vein, the purpose of this study is to contribute to the revitalization of shared mobility services in Korea and to provide service providers with implications for developing consumer-oriented marketing strategies. Research design, data and methodology: Based on the reasons that the users do not use shared mobility service, the factors influencing the behaviors of shared mobility users are structured and analyzed in a reliable, technical and procedural manner. To this end, the theory of reasoned action (TRA) of Ajzen and Fisbbein, the initial trust model (ITM), task technology fit (TTF) and switching cost (SC) are adopted. A total of 202 questionnaires were collected from the respondents who were aware of shared mobility. Then statistical processing of the collected data used SmartPLS(v.3.2.8), a PLS-SEM (Partial Least Squares Structural Equation Modeling) analysis program. The steps of the analysis are as follows. First, a PLS-Algorithm analysis was performed to evaluate the measurement model, and a Bootstraping and Blindfolding analysis was performed to evaluate the structural model and verify the hypotheses. Second, a multi-group analysis (PLS-MGA) was conducted to further analyze the differences depending on whether or not users experienced shared mobility service. Results: The results showed that initial trusts model (ITM) and task technology fit (TTF) have positive effects on users' behaviors through the mediation of the intention to use. As opposed to the assumption, switching costs did not have negative moderating effects in relation to the intention to use and users' behaviors. The influence of IT self-efficacy was significant, depending on the prior experience to use shared mobility services. Conclusions: This study will contribute to the revitalization of domestic shared mobility services and the formulation of service providers' marketing strategies. In future studies, there is a need to explore, reconstruct, and validate factors other than the impact factors of the shared mobility services used in this research model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.3
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• pp.237-244
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• 2016

This paper presents a nonlinear Moving Least Squares(MLS) difference method for material nonlinearity problem. The MLS difference method, which employs strong formulation involving the fast derivative approximation, discretizes governing partial differential equation based on a node model. However, the conventional MLS difference method cannot explicitly handle constitutive equation since it solves solid mechanics problems by using the Navier's equation that unifies unknowns into one variable, displacement. In this study, a double derivative approximation is devised to treat the constitutive equation of inelastic material in the framework of strong formulation; in fact, it manipulates the first order derivative approximation two times. The equilibrium equation described by the divergence of stress tensor is directly discretized and is linearized by the Newton method; as a result, an iterative procedure is developed to find convergent solution. Stresses and internal variables are calculated and updated by the return mapping algorithm. Effectiveness and stability of the iterative procedure is improved by using algorithmic tangent modulus. The consistency of the double derivative approximation was shown by the reproducing property test. Also, accuracy and stability of the procedure were verified by analyzing inelastic beam under incremental tensile loading.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.128-135
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• 2009

Techniques for tracking the same region of physical space with the temporal sequences of images by matching the contours of constant phase show robust and stable performance in relative to the tracking techniques using or assuming the constant intensity. Using this property, we describe an algorithm for obtaining the robust motion parameters caused by the global camera motion. First, we obtain the optical flow based on the phase of spacially filtered sequential images on the region in a direction orthogonal to orientation of each component of gabor filter bank. And then, we apply the least squares method to the optical flow to determine the affine motion parameters. We demonstrate hat proposed method can be applied to the vision based pointing device which estimate its motion using the image including the display device which cause lighting condition varieties and noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.147-152
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• 1995

실험에 의한 모우드 해석 방법들은 1980년대부터 활발히 연구되어 많은 새로운 방법들이 개발되어 발표되었다. 그러나 개발된 대부분의 방법들은 측정된 데이타를 일괄처리하는 밸치(또는 off-line) 방법들이다. 최근에는 시간에 따라서 변하는 구조물의 동특성을 규명하는 분야에 모우드 해석 방법이 응용되어 사용되고 있다. 이러한 응용분야에서는 모우드 변수들의 변화되는 값을 새로운 데이타가 샘플링 될 때마다 그 값들을 수정하면서 추정할 수 있는 회귀적인(recursive 또는 on-line) 방법을 사용하여야 한다. Davies와 Hammond[1]는 회귀적 선형 자승법(Recursive Least Squares : RLS)을 이용하여 모우드 변수를 구하고 이를 벧치방법인 Instrumental Variable 방법과 Fourier 방법의 결과와 비교하였다. 그러나, 그 결과에서 보여준것처럼 RLS 방법은 잡음 대 시호비가 낮을 때에만 모우드 변수 값들을 정확하게 추정할 수 있었다. Sundararajan과 Montgomrey[2]는 회귀적 선형 최소자승 격자필터(lattice filter)를 이용하여 구조물의 차수(order)와 고유진동형, 그리고 진폭을 결정한 후 이를 토대로 회귀적 gradient형태의 방정식 오차 규명 방법(equation-error identification algorithm)에 의하여 모우드 변수들을 추정하였다. 이 방법은 2차원 격자구조물의 모우드 변수 추정에 사용되었으며, 또한 적응모우드제어에도 성공적으로 이용되었다. 그러나, 이 방법도 잡음 대 신호비가 낮은 환경에서만 사용할 수 있다는 단점이 있다. 위에서 언급한 방법들은 모두 RLS 방법을 기초로 하여 개발되었으나, RLS 방법은 전형적인 결정적(deterministic)방법으로서 잡음이 섞인 데이타를 처리하기에는 부적절한 방법임이 널리 알려진 사실이다[3]. 최근에 Ben Mrad와 Fassois[4]는 신호에 잡음이 존재하여도 이를 잘 처리할 수 있는 확률적(stochastic) 방법을 개발하여 기존의 결정적 방법들과 그 결과를 비교하였다. 그러나, 개발된 방법은 응답 신호에 백색잡음(white noise)이 섞이는 특수한 경우에만 사용할 수 있게 만들어져서 이 방법의 실질적인 적용에는 어려움이 있다. 본 연구에서는 기존의 방법들의 단점을 극복할 수 있는 새로운 회귀적 모우드 변수 규명 방법을 개발하였다. 이는 Fassois와 Lee가 ARMAX모델의 계수를 효율적으로 추정하기 위하여 개발한 뱉치방법인 Suboptimum Maximum Likelihood 방법[5]를 기초로 하여 개발하였다. 개발된 방법의 장점은 응답 신호에 유색잡음이 존재하여도 모우드 변수들을 항상 정확하게 구할 수 있으며, 또한 알고리즘의 안정성이 보장된 것이다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.4
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• pp.321-330
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• 1999

Automation of observation and positioning of fiducial marks is made possible with the application of image matching technique, developed through the cooperative research effort of computer vision and digital photogrammetry. The major problem in such automation effort is to minimize the computing time and to increase the positional accuracy. Except for scanning and ground control surveying, the interior orientation process was automated in this study, through the development of an algorithm which applies the image matching and image processing techniques. The developed system was applied to close-range photogrammetry and the analysis of the results showed 54% improvement in processing time. For fiducial mark observation during interior orientation, the Laplacian of Gaussian transformation and the Hough transformation were applied to determine the accurate position of the center point, and the correlation matching and the least squares matching method were then applied to improve the accuracy of automated observation of fiducial marks. Image pyramid concept was applied to reduce the computing time of automated positioning of fiducial mark.

• Geophysics and Geophysical Exploration
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• v.2 no.4
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• pp.191-201
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• 1999

The interpretation of resistivity data has, so far, mainly been made under the assumption that the earth is of relatively simple structure and then using one or two-dimensional inversion scheme. Since real earth structure and topography are fully three-dimensional and very complicated In nature, however, such assumptions often lead to misinterpretation of the earth structures. In such situations, three-dimensional inversion is probably the only way to get correct image of the earth. In this study, we have developed a three-dimensional inversion code using the finite element solution for the forward problem. The forward modeling algorithm simulates the real field situation with irregular topography. The inverse problem is solved iteratively using the least-squares method with smoothness constraint. Our inversion scheme employs ACB (Active Constraint Balancing) to enhance the resolving power of the inversion. Including Irregular surface topography in the inversion, we can accurately define the earth structures without artifact in the numerical tests. We could get reasonable image of earth structure by Inverting the real field data sets taken over highway bridge construction site.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.205-213
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• 2011

The Long Term Evolution (LTE) system is designed to provide a high quality data service for fast moving mobile users. It is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the training samples which are systematically built within the transmitting data. Either a preamble or a lattice type is used for the distribution of training samples and the latter suits better for the multipath fading channel environment whose channel frequency response (CFR) fluctuates rapidly with time. In the lattice-type structure, the estimation of the CFR makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time-and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. All interpolation schemes should rely on the pilot estimates only, and thus, their performances are bounded by the quality of pilot estimates. However, the additive noise give rise to high fluctuation on the pilot estimates, especially in a communication environment with low signal-to-noise ratio. These high fluctuations could be monitored in the alternating high values of the first forward differences (FFD) between pilot estimates. In this paper, we analyzed statistically those FFD values and propose a postprocessing algorithm to suppress high fluctuations in the noisy pilot estimates. The proposed method is based on a localized adaptive moving-average filtering. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification. It is shown that the mean-squared error (MSE) between the actual CFR and pilot estimates could be reduced up to 68% from the noisy pilot estimates.

• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.27-34
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• 1997

3-D image modeling is in high demand for automated visual inspection and non-destructive testing. It also can be useful in biomedical research, medical therapy, surgery planning, and simulation of critical surgery (i.e. cranio-facial). Image processing and image analysis are used to enhance and classify medical volumetric data. Analyzing medical volumetric data is very difficult In this paper, we propose a new image modeling method based on tetrahedrization to improve the visualization of three-dimensional medical volumetric data. In this method, the trivariate piecewise linear interpolation is applied through the constructed tetrahedral domain. Also, visualization methods including iso-surface, color contouring, and slicing are discussed. This method can be useful to the correct and speedy analysis of medical volumetric data, because it doesn't have the ambiguity problem of Marching Cubes algorithm and achieves the data reduction. We expect to compensate the degradation of an accuracy by using an adaptive sub-division of tetrahedrization based on least squares fitting.