• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.51-57
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• 2007

Without human dynamics effects, the manually operated target tracking system has poor performance or instability in real environments. The tracking system is invalid when a human is added to the control loop as a real time delay, because input signals are generated by human operator to reduce the errors between target and gun. In this paper, we consider the human operator as a part of controller and modeling the human operator as a first-order model to generate the intentional force. But it is known that human modeling is not easy because of disturbance or noise of the vehicle while moving for the target. We performed a variety of experiments with real plant to identify the model's parameters and verify the proposed operator model's efficiency.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.119-125
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• 2017

In this paper, we propose a method that merges and splits players in the MeanShift tracking framework. The MeanShift tracking moves the center of tracking window to the maximum probability location given the target probability distribution. This tracking method has been widely used for real-time tracking problems because of its fast processing speed. However, it hardly handles occlusions in multiple object tracking systems. Occlusions can be usually solved by applying data association methods. In this paper, we propose a method that can be applied before data association methods. The proposed method automatically merges and splits the overlapped players by adjusting the each player's tracking map. We have compared the tracking performance of the MeanSfhit tracking algorithm and the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1096-1102
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• 2014

In remote gaze tracking system using infra-red LEDs, calibrating the position of reflected light is essential for computing pupil position in captured images. However, there are limitations in reducing errors because variable locations of head and unknown radius of cornea are involved in the calibration process as constants. This study purposes a gaze tracking method based on pupil-corneal reflection that does not require user-calibration. Our goal is to eliminate the correction process of glint positions, which require a prior calibration, so that the gaze calculation is simplified.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.19-30
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• 2019

Photovoltaic power generation requires MPPT algorithm to track stable and efficient maximum power output power point according to external changes such as solar radiation and temperature. This study implemented a model that could track MPP more quickly than original MPPT algorithm using artificial neural network. The proposed model finds the current and voltage of MPP using the original MPPT algorithm for various combinations of insolation and temperature for training data of artificial neural networks. The acquired MPP data was learned using the input node as insolation and temperature and the output node as the current and voltage. The Experiment results show tracking time of the original algorithms P&O, InC and Fuzzy were respectively 0.428t, 0.49t and 0.4076t for the 0t~0.3t range, and MPP tracking time of the proposed model was 0.32511t and it is 0.1t faster than the original algorithms.

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.231-242
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• 2009

The EPC-Discovery Service (EPC-DS) is a good representative of the RFID Track & Trace. But this mechanism has several problems. EPC-DS uses centralized server scheme which may arise bottle-neck state and that cannot provide detail trace information of a RFID object. In addition, a trace node requires direct access method to a RFID object or an element which has information of the RFID object for Track & Trace. In this paper, we propose a novel RFID Track & Trace mechanism which based on the SIP presence model and SIP event notification. This mechanism can provide detail trace information and monitoring function, and also can rid the bottle-neck section by combination of SIP methods instead of centralized element.

• Journal of IKEEE
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• v.1 no.1 s.1
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• pp.19-30
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• 1997

In this paper we design the optimal satellite-tracking antenna $H{\infty}$ control system using genetic algorithms. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithms with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H{\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust stability of closed-loop system. The effectiveness of this satellite-tracking antenna $H{\infty}$ control system is verified by computer simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.774-781
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• 2014

The radar measurements are composed of range, Doppler and angles which are expressed as polar-coordinate components. An approach to match the measurements with the states of target dynamics which are modeled in cartesian coordinates is to use the pseudo-measurements or the extended Kalman filter in order to solve the mismatching problem. Another approach is that the states of dynamics are modeled in polar coordinates and measurement equation is linear. However, this approach bears that we have to deal with a time-varying dynamics. In this study, it is proposed that the states of dynamics are expressed as polar-coordinate component and the system matrix of the dynamic equation is modeled as a time-invariant. Nonlinear terms that appear due to the proposed modeling are regarded as a system input. The results of a series of simulation runs indicate that the tracking filter that uses the proposed modeling is viable from the fact that the Doppler measurement is easy to be augmented in the measurement equation.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2396-2398
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• 2001

Active contour로 알려져 있는 snake는 반복적인 계산으로 이미지상에서 찾고자 하는 물체의 외곽선에 수렴하는 contour로 이미지 상의 물체의 외곽선으로부터 발생하는 외부 에너지(external energy)와 contour 자체로부터 기인하는 내부 에너지(internal energy)를 최소화하는 방향으로 움직인다. 그러나 물체의 윤곽선으로부터 발생하는 외부 에너지는 찾고자 하는 물체뿐만 아니라 주위의 다른 물체로부터도 발생하므로 만일 추적하고자 하는 물체의 주변에 다른 물체들이 존재한다면 snake은 올바르게 동작하지 않게 된다. 본 논문에서는 이러한 단점을 극복하기 위하여 물체의 색상정보를 이용하는 방식을 제안하였다. 물체의 색상 정보는 물체의 고유한 특성 중의 하나로 본 논문에서는 색상정보를 이용하여 원래의 이미지를 찾고자 하는 물체의 색상과 얼마나 유사한가를 나타내는 확률 이미지로 변환하였다. 이렇게 변환된 확률 이미지 상에서 snake 알고리즘을 적용함으로써 배경의 다른 물체로부터 발생하는 외부 에너지를 효과적으로 제거할 수 있다. 또한 본 논문에서는 물체가 이동함에 따라 변화하는 색상 정보를 지속적으로 갱신함으로써 물체의 추적이 효과적으로 이루어지도록 하였다.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.493-502
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• 2007

An on-line registration technique is presented to register multi-view range images for the 3D reconstruction of real objects. Using a range camera, we first acquire range images and photometric images continuously. In the range images, we divide object and background regions using a predefined threshold value. For the coarse registration of the range images, the centroid of the images are used. After refining the registration of range images using a projection-based technique, we use a modified KLT(Kanade-Lucas-Tomasi) tracker to match photometric features in the object images. Using the modified KLT tracker, we can track image features fast and accurately. If a range image fails to register, we acquire new range images and try to register them continuously until the registration process resumes. After enough range images are registered, they are integrated into a 3D model in offline step. Experimental results and error analysis show that the proposed method can be used to reconstruct 3D model very fast and accurately.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.212-212
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• 2023

비점오염원관리와 같이 장기적인 유역 관리 계획에서 유역 내 오염원 평가는 정말 중요하다. 유역 내 오염원 평가는 강우 유출에 의한 비점오염 발생원이 어디서 얼마나 발생시키는지에 대한 정량적인 조사가 필요하다. 유역 내의 오염원에 대한 정량적인 조사는 많은 비용과 시간이 필요하다. 이러한 비용과 시간을 줄이기 위해 유역단위 수리 수문 모델을 사용하고 있다. 유역단위 수리수문 모델은 HSPF (Hydrological Simulation Program in Fortran), SWAT (Soil and Water Assessment Tool), L-THIA ACN-WQ(The Long-term Hydrologic Impact Assessment Model with Asymptotic Curve Number Regression Equation and Water Quality model)등 다양한 모델이 사용되고 있다. 하지만 유역 모델을 통한 모의는 다양한 연산 과정을 진행하여 모의까지 많은 시간이 필요하다는 단점이 있다. 이에 따라 데이터 기반 모델링 기법(머신러닝/딥러닝)을 이용한 유출 및 수질 예측 연구가 많이 이루어지고 있다. 단순 머신러닝/딥러닝 기반 모델링 기법은 점(최종유출구)에서의 예측만 가능하여 최적관리 기법 적용 등과 같은 유역관리 방안을 적용하기 힘들다는 문제점이 있다. 따라서 본 연구에서 머신러닝/딥러닝을 통해 일부 수문 프로세스를 대체하고 소유역별 하도추적 기법을 연계하여 유량 및 수질 항목들의 모의가 가능한 하이브리드 모델을 개발하였다. 이는 머신러닝/딥러닝이 유역 모델의 일부 연산 과정을 대체하여 모의시간이 빠르며, 기존 머신러닝/딥러닝 예측 모델에서 평가가 어려웠던 유역 관리 방안 및 최적관리기법 적용 평가에도 활용이 가능할 것으로 판단이 된다.