• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2497-2500
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• 2003

본 논문에서는 저속으로 회전하는 모터의 속도를 추정함에 있어서 속도 관측기를 이용하고 적절한 보상을 통해 가속/감속 운전 시에도 속도 추정 성능을 개선시킨다. 가속도 정보를 이용한 보상을 통해, 모터 인코더카운터 값으로부터 발생하는 양자화 오차를 줄인다. 가속/감속 운전시 인코더 펄스에 의한 평균속도는 펄스가 발생한 시점에서 불연속일 수밖에 없게 된다. 제안된 방식은 이 불연속적인 평균속도를 가속도 보상을 통해 연속적으로 증감하는 보상된 속도를 얻고 이를 다시 관측기 입력에 보상하여 양자화 오차를 감소시킨다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.1
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• pp.85-92
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• 2005

The motion of flexseal bearing for movable nozzle has inherent nonlinear characteristics due to floating rotational center and compression by combustion pressure of solid motor. To perform precise attitude control in spite of these characteristics, the TVC actuation system requires counter potentiometer as an extra position feedback sensor of movable nozzle to form a compensated control loop. The prototype TVC actuation system, test equipments and compensated controller are newly designed, manufactured and tested in consideration of counter potentiometer. On the basis of integration test, the inherent characteristics of movable nozzle and control characteristics of its TVC actuation system are analyzed and summarized in this paper.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.320-324
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• 2011

A digital technique is adopted to calibrate the current mismatch of the charge pump (CP) in phase-locked loops. A 2 GHz charge pump PLL (CPPLL) is used to justify the proposed calibration technique. The proposed digital calibration technique is implemented simply using a counter. The proposed calibration technique reduces the calibration time by up to a maximum of 50% compared other with techniques. Also by using a dual-mode CP, good current matching characteristics can be achieved to compensate $0.5{\mu}A$ current mismatch in CP. It was designed in a standard $0.13{\mu}m$ CMOS technology. The maximum calibration time is $33.6{\mu}s$ and the average power is 18.38mW with 1.5V power supply and effective area is $0.1804mm^2$.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.347-352
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• 2021

In this paper, we propose a method for finding feature subsets that are effective for classification in an input dataset by using a multi-agent reinforcement learning method. In the field of machine learning, it is crucial to find features suitable for classification. A dataset may have numerous features; while some features may be effective for classification or prediction, others may have little or rather negative effects on results. In machine learning problems, feature selection for increasing classification or prediction accuracy is a critical problem. To solve this problem, we proposed a feature selection method based on reinforced learning. Each feature has one agent, which determines whether the feature is selected. After obtaining corresponding rewards for each feature that is selected, but not by the agents, the Q-value of each agent is updated by comparing the rewards. The reward comparison of the two subsets helps agents determine whether their actions were right. These processes are performed as many times as the number of episodes, and finally, features are selected. As a result of applying this method to the Wisconsin Breast Cancer, Spambase, Musk, and Colon Cancer datasets, accuracy improvements of 0.0385, 0.0904, 0.1252 and 0.2055 were shown, respectively, and finally, classification accuracies of 0.9789, 0.9311, 0.9691 and 0.9474 were achieved, respectively. It was proved that our proposed method could properly select features that were effective for classification and increase classification accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.585-590
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• 2012

In this paper, a system using vibrating wire sensor and zigbee wireless network has been implemented to monitor and manage the structure. The implemented strain controller drives vibrating wire sensor and computes strain from measuring frequency of the output signal. Temperature sensor is included to compensate strain by temperature. Using two axis acceleration sensor of strain controller can measure the direction of strain or deformation. To measure strain more effectively, wired and wireless communication function is included in this device. As results of experiments, it is shown that the developed system can be effectively applied to measure strain of the structure.

• Journal of IKEEE
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• v.22 no.3
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• pp.638-644
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• 2018

In this paper, we develop a measurement system that uses 3D Scintillator and NaI(TI) Detector to 3-dimensionally identify the location of multiple radiation sources in moving vehicle loads. The radiation measurement system consists of radiation measurement (plastic scintillator), 2-channel Pulse Counter Board, nuclide analysis (NaI(TI) detector) and 1 channel MCA Board. The source locator algorithm calculates the coordinate value of the ratio of the CPS value($1/r^2$) of the source according to the angle(${\theta}$) in inverse proportion to the square of the distance(X, Y) through the SVM classification. The coordinate values are input every predetermined period of the spectrum, and after analyzing the spectrum per unit cycle, the position of the nuclide at the time is calculated by determining whether or not the nuclide is present in the remaining part except for the background area. As a result of the position discrimination test, the error within the international standard of ${\pm}1m$ was shown. Thus, the utility of the proposed system has been demonstrated.