• Nuclear Engineering and Technology
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• 제51권3호
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• pp.719-722
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• 2019

Gamma-ray images generally suffer from a lot of noise because of low photon detection in the gamma camera system. The purpose of this study is to improve the image quality in gamma-ray images using a gamma camera system with a fast nonlocal means (FNLM) noise reduction algorithm with an acceleration function. The designed FNLM algorithm is based on local region considerations, including the Euclidean distance in the gamma-ray image and use of the encoded information. To evaluate the noise characteristics, the normalized noise power spectrum (NNPS), contrast-to-noise ratio (CNR), and coefficient of variation (COV) were used. According to the NNPS result, the lowest values can be obtained using the FNLM noise reduction algorithm. In addition, when the conventional methods and the FNLM noise reduction algorithm were compared, the average CNR and COV using the proposed algorithm were approximately 2.23 and 7.95 times better than those of the noisy image, respectively. In particular, the image-processing time of the FNLM noise reduction algorithm can achieve the fastest time compared with conventional noise reduction methods. The results of the image qualities related to noise characteristics demonstrated the superiority of the proposed FNLM noise reduction algorithm in a gamma camera system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.302-305
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• 1999

Twin-servo mechanism is used to increase the payload capacity and speed of high precision motion control system. In this paper, we propose a robust synchronizing motion control algorithm to cancel out the skew motion of twin-servo system caused by different dynamic characteristics of two driving systems and the vibration generated by high accelerating and decelerating motions. This proposed control algorithm consists of separate feedback motion control algorithm of each driving system and skew motion compensation algorithm between two systems. Robust model reference tracking controller is proposed as a separate motion controller and its disturbance attenuation property is shown. For the synchronizing motion, skew motion compensation algorithm is designed, and the stability of whole Closed loop system is proved based on passivity theory.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.993-995
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• 1996

This paper proposes an adaptive Filtered-X LMS algorithm with robustness. The proposed system updates filter parameters to keep the performance even if the conventional Active Noise Control (ANC) system well does not work. As a result of the computer simulation, the proposed system has all the advantage of the system using the conventional Filtered-X LMS algorithm. Also some results from the proposed algorithm present that the system is stable when the Adaptive filter does not work. Therefore, the proposed system using the Adaptive Filtered-X LMS algorithm must have much advantage than the system using the conventional algorithm in the side of the stability and performance.

• International Journal of Air-Conditioning and Refrigeration
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• 제12권3호
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• pp.123-130
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• 2004

Control algorithms for an absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. Simulation results showed energy savings and the effective controls of an absorption air conditioning system.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권8호
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• pp.344-351
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• 2002

The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response. We use the proposed algorithm to solve parameter optimization problems. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore the usefulness of memory-cell mechanism in immune algorithm is without. This paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verified performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. The results of Computer simulations represent that the proposed immune algorithm shows a fast convergence speed and a good control performances under the varying system parameters.

• 한국통신학회논문지
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• 제33권6B호
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• pp.450-455
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• 2008

본 논문에서는 기존의 EPC Class 1 RFID 시스템에서의 태그 인식 절차와 태그 충돌 방지 알고리즘을 분석하였으며, 태그 인식 속도를 향상시키기 위한 고속 충돌 방지 알고리즘을 제안한다. 고속 충돌 방지 알고리즘에서는 태그 인식 과정에서 태그의 충돌 정보를 이용하고, 기존의 알고리즘에서 존재하던 불필요한 절차를 생략하였다. 성능 평가를 위하여 기존의 알고리즘과 제안한 알고리즘을 수학적으로 분석하였고, 이를 시뮬레이션으로 검증하였다. 결과에 따르면, 고속 충돌 방지 알고리즘이 기존의 알고리즘에 비해 상당한 성능향상을 보임을 확인할 수 있었다.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.989-995
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• 2015

Due to the recent increase of the importance and demand of security services, the importance of a surveillance monitor system that makes an automatic security system possible is increasing. As the market for surveillance monitor systems is growing, price competitiveness is becoming important. As a result of this trend, surveillance monitor systems based on an embedded system are widely used. In this paper, an object detection algorithm based on an embedded system for a surveillance monitor system is introduced. To apply the object detection algorithm to the embedded system, the most important issue is the efficient use of resources, such as memory and processors. Therefore, designing an appropriate algorithm considering the limit of resources is required. The proposed algorithm uses two background models; therefore, the embedded system is designed to have two independent processors. One processor checks the sub-background models for if there are any changes with high update frequency, and another processor makes the main background model, which is used for object detection. In this way, a background model will be made with images that have no objects to detect and improve the object detection performance. The object detection algorithm utilizes one-dimensional histogram distribution, which makes the detection faster. The proposed object detection algorithm works fast and accurately even in a low-priced embedded system.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.580-590
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• 2018

Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.

• 설비공학논문집
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• 제16권11호
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• pp.1035-1043
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• 2004

For a long road tunnel, a tunnel ventilation system may be used in order to reduce the pollution level below the required level. To control the tunnel pollution level, a closed loop control algorithm may be used. The feedforward prediction algorithm and the cascade control algorithm were developed to regulate the CO level in a tunnel. The feedforward prediction algorithm composed of the traffic estimation algorithm and the CO density prediction algorithm, and the cascade control algorithm composed of the jet fan control algorithm and the air velocity setpoint algorithm. The verification of control algorithms was carried out by dynamic models developed from the actual tunnel data. The simulation results showed that control algorithms developed for this study were effective for the control of the tunnel ventilation system.

• Journal of international Conference on Electrical Machines and Systems
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• 제3권4호
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• pp.465-471
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• 2014

This paper proposes a new switching algorithm for an active clamp snubber to improve the efficiency of a module integrated converter system. This system uses an active clamp method for the snubber circuit for the efficiency and reliability of the system. However, the active clamp snubber circuit has the disadvantage that system efficiency is decreased by switch operating time because of heat loss in resonance between the snubber capacitor and leakage inductance. To address this, this paper proposes a new switching algorithm. The proposed algorithm is a technique to reduce power consumption by reducing the resonance of the snubber switch operation time. Also, the snubber switch is operated at zero voltage switching by turning on the snubber switch before main switch turn-off. Simulation and experimental results are presented to show the validity of the proposed new active clamp control algorithm.