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고장진단 기능을 갖는 선박 횡동요 감요 장치 용 제어시스템 개발
원문철(Moon-Cheal Won),류상현(Sang-Hyun Ryu),최광식(Kwang-Sik Choi),정윤호(Yun-Ho Jung),류재문(Jae-Moon Lew),지용진(Yong-Jin Ji) 한국해양공학회 2010 韓國海洋工學會誌 Vol.24 No.3
This paper summarizes the development of an ART control system panel with a touch screen and sensors to measure the roll and roll rate of ships. The control system hardware consists of two micro-processors, analog and digital I/O circuits, various relay circuits, etc. Sensor fusion and moving cross algorithms are implemented to accurately estimate the roll angle and roll period. In addition, the control system adapts a fault detection algorithm to inform users of ART system faults. A touch screen in the control panel can display the ART system states and faults. The performance of the developed system was verified on real sea trials.
Variational Auto Encoder와 비지도 학습을 이용한 사진 자동 분류 애플리케이션
김형욱(Hyoung-Uk Kim),김형진(Hyoung-Jin Kim),류재문(Jae-moon Ryu),정남주(Nam-Ju Jeong),전병규(Byoung-Gyu Jeon),고병철(Byoung Chul Ko) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6
This paper proposes a new image clustering system for travel application that combines the VAE (Variational Auto Encoder) algorithm for the encoder part and unsupervised learning. The encoder part of the VAE algorithm, which extracts features from images, is shown to outperform the image feature extraction performance of conventional CNNs (Convolutional Neural Networks). Although the VAE algorithm is suitable for feature extraction, it is not well-suited for image classification based on those features. Therefore, in this paper, a new algorithm called VC(VAE Cluster) is proposed by combining the VAE algorithms encoder with a clustering algorithm to classify the features extracted by the VAE algorithm. The proposed method leverages the features extracted by the VAE algorithm to perform classification, allowing images with similar features to be grouped together. This advantage enables image clustering without the need for manual labeling of each individual image. Through various tests, the proposed method demonstrates superior clustering performance compared to other existing methods.
김종순,이현옥,안소윤,구봉오,남건우,김호봉,류재관,류재문 대한정형도수치료학회 2005 대한정형도수물리치료학회지 Vol.11 No.2
The ulnar nerve extends down the arm, across the elbow, and into the hand. It provides sensation to the little and ring fingers and activates many of the small muscles in the hand. The determination of peripheral nerve conduction velocity is an important part of ulnar nerve evaluation. The electrodiagnostic value as neurophysiologic investigative procedure has been known for many years but normal value of digital nerve was not reported in korea. The purpose of this investigation was to measure the digital nerve conduction velocity of ulnar nerve for obtain clinically useful reference value and compare difference in each fingers and then compare with the other countries. 71 normal Korean volunteers (age, 19-65 years; 142 hands) examined who has no history of peripheral neuropathy, diabetic mellitus, chronic renal failure, endocrinedisorders, anti-cancer medicine, anti-tubercle medicine, alcoholism, trauma, radiculopathy. Nicolet Viking Ⅱ(EMG machine) was use for detected conduction velocity and amplitude of digital nerve in ulnar nerve. Data analysis was performed using SPSS. Descriptive analysis was used for obtain mean and standard deviation and independent t-test was used to compare with ring and little finger. Conduction velocity of the right ring finger was 57.44m/sec and little finger was 55.32msec. The left ring finger was 55.55msec and little finger was 54.11msec. Amplitude of the right ring finger was 30.28µV and little finger was 48.36µV. The left ring finger was 30.67µV and little finger was 57.76µV. There were significantly difference between ring and little in amplitude (p<.05) but there were no statistically difference between conduction velocity of ring and little finger (p>.05). The amplitude of little finger are greater than ring finger. The present results revealed that electodiagnosis can easily perform in little finger for digital nerve of ulnar nerve study.
김종순,이현옥,안소윤,구봉오,남건우,김영직,김호봉,류재관,류재문 대한정형도수치료학회 2005 대한정형도수물리치료학회지 Vol.11 No.2
The determination of peripheral nerve conduction velocity is and important part to electrodiagnosis. Its value as neurophysiologic investigative procedure has been known for many years but normal value of median and ulnar motor nerve was poorly reported in Korea. To evaluate of median and ulnar motor nerve terminal latency, amplitude of CMAP(compound muscle action potential), conduction velocity and F-wave latency for obtain clinically useful reference value. 71 normal volunteers(age,19-65 years;142 hands) examined who has no history of peripheral neuropathy, diabetic mellitus, chronic renal failure, endocrine disorders, anti-cancer medicine, anti-tubercle medicine, alcoholism, trauma, radiculopathy. Nicolet Viking Ⅱ was use for detected terminal latency, amplitude of CMAP, conduction velocity and F-wave latency of median and ulnar motor nerve. Data analysis was performed using SPSS. Descriptive analysis was used for obtain mean and standard deviation, independent t-test was used to compare between Rt and Lt side also compare between different in genders. The results are summarized as follows: 1. Median motor nerve terminal latency was right 3.00ms, left 2.99ms and there was no significantly difference between right and left side and genders. 2. Median motor nerve amplitude of CMAP was right 17.26mV, left 17.50mV and there was no significantly differences between right and left side and genders. 3. Median motor nerve conduction velocity was right 57.89m/sec, left 58.03m/sec and there was no significantly difference between right and left side and genders. 4. Median motor nerve F-wave latency was right 25.74ms, left 25.59ms and there was significantly differences between genders. 5. Ulnar motor nerve terminal latency was right 2.38ms, left 2.45ms and there was significantly differences between right and left side. 6. Ulnar motor nerve amplitude of CMAP was right 15.99mV, left 16.02mV and there was no significantly differences between right and left side and genders. 7. Ulnar motor nerve conduction velocity was right 60.35m/sec, left 59.73/sec and there was no significantly differences between right and left side and genders. 8. Ulnar motor nerve F-wave latency was right 25.53ms, left 25.57ms and there was significantly differences between genders.