• Korean Journal of Optics and Photonics
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• v.18 no.5
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• pp.303-308
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• 2007

We report here on the application of a digital holographic microscope as a metrology tool for the inspection and the micro-topography reconstruction of different micro-structures of phase shift photo-mask (PSM). The lithography by phase shift photo-mask uses the interference and the pattern of the PSM is not imaged by general optical microscope. The technique allows us to obtain digitally a high-fidelity surface topography description of the phase shift photo-mask with only one hologram image acquisition, allowing us to have relatively simple and compact set-ups able to give quantitative information of PSM.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.1
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• pp.145-151
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• 2016

Temperature variability at the upper layer related to climate regime shifts in the Korean waters was illustrated using water temperature, climate index. Three major climate regime shifts (CRS) in 1976, 1988 and 1998 in north Pacific region had an significant influence on the major marine ecosystems structure pattern. Three marginal seas around Korean peninsula; East Sea, East China Sea and Yellow Sea also got important impact from this kind of decadal shift. We used 10m sea water temperatures in four regions of Korean waters since 1950 to detect major fluctuation patterns both seasonally and also decadal shift. 1988 CRS was occurred in all of the study areas in most seasons however, 1998 CRS was only detected in the Yellow Sea and in the southern part of the East Sea. 1976 CRS was detected in all of the study area mainly in winter. After 1998 CRS, the water temperature in the southern part of the East Sea, East China Sea and Yellow Sea were going into decreased pattern; however, in the northern part of the East Sea, it was further shifted to increasing pattern which was started from 1988 CRS period.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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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.

• Journal of East-West Nursing Research
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• v.17 no.2
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5730-5736
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• 2013

The study was conducted to determine the effect of trunk pattern training in proprioceptive neuromuscular facilitation(PNF) and weight-shift training on the muscle activity and static balance in patients with hemiplegia due to stroke. Twenty patients with hemiplegia due to stroke were assigned to the trunk pattern training in PNF group(n=10) or weight-shift training group(n=10). Both groups were executed conventional treatment for 5 times per week for 6 weeks 30 minutes per session. Each group performed additional training for 20 minutes. Post training, compared to the weight-shift training group, trunk pattern training in PNF group showed significantly increased on muscle activity of rectus femoris, gastrocnemius and static balance(p<.05). These results support the perceived benefits of trunk pattern training in PNF to augment on the static balance and muscle activity of stroke patients. Therefore, trunk pattern training in PNF is feasible and suitable for stroke patients.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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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.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.4
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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.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.3
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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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.