• 한국광학회지
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• 제18권5호
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• pp.303-308
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• 2007

디지털 홀로그래피 현미경을 이용하여 반도체 공정에 사용되는 위상차 포토마스크의 결함을 측정하였다. 이러한 위상차 포토마스크는 위상차를 이용하여 반도체 문양을 만들기 때문에 일반 현미경으로는 패턴을 알 수 없을 뿐 아니라 위상마스크의 결함은 더욱더 찾기 어렵다. 디지털 홀로그래피 현미경을 이용하면 한 장의 홀로그램을 이용하여 위상차 포토마스크의 3차원 구조와 결함을 동시에 측정할 수 있다.

• 해양환경안전학회지
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• 제22권1호
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• pp.145-151
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• 2016

수온과 기후 지수 자료를 이용하여 한국주변해 상층부의 수온변동과 북태평양 기후체제와의 관계를 분석하였다. 1970, 1980 그리고 1990년대 후반에 발생한 기후체제전환은 해양생태계의 구조 변화에 중요한 영향을 끼쳤다. 북서태평양 대륙주변부에 위치한 우리나라 주변해역 또한, 10년 이상의 장주기적인 변화의 영향을 받지만, 해역별 반응은 다르다. 동해, 서해, 남해 상층부(10 m)의 경우 1988년의 기후체제전환은 3개 해역의 상층부 수온변화에서 동시에 나타난다. 반면, 1998년은 동해남부해역과 서해, 1976년의 기후체제전환은 전 해역의 겨울철 수온변화에서만 그 영향이 나타난다. 1998년 기후체제전환 이후, 서해, 동중국해, 동해 남부의 수온은 점차 감소하지만, 동해 북부해역은 1988년 기후체제전환 이후 증가하는 형태이다.

• 전기학회논문지
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• 제66권4호
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• pp.682-691
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• 2017

In this paper, we propose the fusion design methodology of both pedestrian detection and object tracking system realized with the aid of HOG-PCA based RBFNN pattern classifier. The proposed system includes detection and tracking parts. In the detection part, HOG features are extracted from input images for pedestrian detection. Dimension reduction is also dealt with in order to improve detection performance as well as processing speed by using PCA which is known as a typical dimension reduction method. The reduced features can be used as the input of the FCM-based RBFNNs pattern classifier to carry out the pedestrian detection. FCM-based RBFNNs pattern classifier consists of condition, conclusion, and inference parts. FCM clustering algorithm is used as the activation function of hidden layer. In the conclusion part of network, polynomial functions such as constant, linear, quadratic and modified quadratic are regarded as connection weights and their coefficients of polynomial function are estimated by LSE-based learning. In the tracking part, object tracking algorithms such as mean shift(MS) and cam shift(CS) leads to trace one of the pedestrian candidates nominated in the detection part. Finally, INRIA person database is used in order to evaluate the performance of the pedestrian detection of the proposed system while MIT pedestrian video as well as indoor and outdoor videos obtained from IC&CI laboratory in Suwon University are exploited to evaluate the performance of tracking.

• 동서간호학연구지
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• 제17권2호
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• pp.81-86
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• 2011

Purpose: The purpose of this study was to examine job involvement according to working pattern and daytime sleepiness in hospital nurses. Methods: At 2 hospitals in affiliation of university, after obtaining participant's consent form, data were collected from October to November, 2007. Twohundred fifty nurses participated in the study. Questionnaire consisted of Epworth Sleepiness Scale (ESS), Job Involvement. Collected data was analyzed with SPSS 14.0 program, which was used for frequency, percentage, mean, standard deviation, t-test and Pearson correlation coefficients. Results: Major findings of this study were as follows 1) The nurses for 3 shift work was 172 (68.8%), the nurses for 2 shift work was 3 (1.2%) and the nurses for day fixation was 75 (30.0%). 2) Mean of ESS was 5.94 (3.28), daytime sleepiness was 13.2% and Job involvement had a mean of $21.27.{\pm}4.61.3$) There were significant differences between shift work and day fixed work on ESS (t=4.33, p<.001), job involvement (t=6.54, p<.001). Higher ESS were significantly related to lower job involvement (r=-.185, p=.003). Conclusion: The finding of this study gives useful informations about sleep and work involvement of hospital nurses. It is need to develop systemic management for shift work nurses by hospital, nurse organization, and government.

• 한국산학기술학회논문지
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• 제14권11호
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• pp.5730-5736
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• 2013

본 연구는 뇌졸중 환자에게 고유수용성 신경근 촉진법의 체간 패턴 훈련과 체중 이동 훈련이 하지 근 활성도와 정적 균형 능력에 어떠한 영향을 미치는지 알아보기 위하여 실시하였다. 본 연구에는 총 20명의 뇌졸중 환자가 참여하였으며, 대상자들은 무작위 추출법으로 고유수용성 신경근 촉진법의 체간 패턴 훈련군 10명과 체중 이동 훈련군 10명으로 각각 배정되었다. 모든 대상자들은 전통적 물리치료를 6주 동안 주 5회, 하루 30분씩 시행하였으며, 고유수용성 신경근 촉진법의 체간 패턴 훈련과 체중 이동 훈련을 하루에 20분씩 각각 추가적으로 실시하였다. 연구 결과 고유수용성 신경근 촉진법의 체간 패턴 훈련이 체중 이동 훈련에 비해 마비측 하지의 대퇴직근, 비복근의 활성도와 정적 균형 능력에서 유의한 차이를 보였다(p<.05). 이것으로 고유수용성 신경근 촉진법의 체간 패턴 훈련이 체중 이동 훈련에 비해 뇌졸중 환자의 회복에 효과적이었다고 할 수 있다. 따라서 고유수용성 신경근 촉진법의 체간 패턴훈련은 뇌졸중 환자에게 적용 가능한 유익한 훈련이 될 수 있을 것이다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.42-45
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• 2003

This paper describes a new iris recognition method using shift-invariant subbands. First an iris image is preprocessed to compensate the variation of the iris image. Then, the preprocessed iris image is decomposed into multiple subbands using a shift invariant wavelet transform. The best subband among them, which have rich information for various iris pattern and robust to noises, is selected for iris recognition. The quantized pixels of the best subband yield the feature representation. Experimentally, we show that the proposed method produced superb performance in iris recognition.

• 전자공학회논문지A
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• 제32A권4호
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• pp.24-31
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• 1995

In this paper, the dual-mode burst-error-correcting decoding algorithm is adapted to the multiple trellis-coded .pi./4 shift QPSK in order to achieve the improvement of bit error rate (BER) performance over fading channels. The dual-mode adaptive decoder which combines maximum likelihood decoding with a burst detection scheme usually operates as a Viterbi decoder and switches to time diversity error recovery whenever an uncorrectable error pattern is identified. Rayleigh fading channels and Rician fading channels having the Rician parameter K=5dB are used in computer simulation, and the simulation results are compared with those of interleaving techniques. It is shown that under the constraint of the fixed overall memory quantity, the dual-mode adaptive decoding scheme gains an advantage in the BER performance with respect to interleaving strategies.

• 한국자동차공학회논문집
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• 제4권3호
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• pp.10-21
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• 1996

In this study, as a strategy to improve shift characteristics, the authors developed a new style pressure modulator which can reduce shock torque during power shift by modulating the pattern of pressure increase in the cylinder for actuating the clutch. The remarkable merits of this new pressure modulator lie in its structural simplicity and durability, because the modulator is only composed of a poppet type valve and a few orifices. The usefulness of the new pressure modulator is confirmed by experiments and numerical analyses on a clutch control hydraulic system simplified for easy test. Also, the excellency of the transmission with the new pressure modulator is verified by experiments on a test bench for simulating the running power train of an excavator.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.397-401
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• 1995

ESPI(Electronic Speckle Pattern Interfermetry) is an optical technique to measure surface deforamtion of engineering components and materials in industrial ares. This optical method is capable of providing full-field results with high spatial resolution, high speed and is the non-contact technique. One of important application aspects using electronic speckle pattern interferometry is to generate contours of a diffuse object in order to provide data for 3-D shape analysis and topography measurement. The contouring method by modified dual-beam speckle pattern interferometry is proposed. We introduce a shift of the illumination beams through optical fiber in order to obtain the contour fringe patterns. The speckle pattern correlation technique is suitable for providing measurement range from millimeters to several centimeters. The complete geometric analysis of the contoretical and experimental results are obtained.

• 대한전기학회논문지:전력기술부문A
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• 제48권11호
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• pp.1464-1471
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• 1999

This paper introduces complex-valued competitive learning neural network for spatio-temporal pattern recognition. There have been quite a few neural networks for spatio-temporal pattern recognition. Among them, recurrent neural network, TDNN, and avalanche model are acknowledged as standard neural network paradigms for spatio-temporal pattern recognition. Recurrent neural network has complicated learning rules and does not guarantee convergence to global minima. TDNN requires too many neurons, and can not be regarded to deal with spatio-temporal pattern basically. Grossberg's avalanche model is not able to distinguish long patterns, and has to be indicated which layer is to be used in learning. In order to remedy drawbacks of the above networks, unsupervised competitive learning using complex umber is proposed. Suggested neural network also features simultaneous recognition, time-shift invariant recognition, stable categorizing, and learning rate modulation. The network is evaluated by computer simulation with randomly generated patterns.