• Korean Journal of Optics and Photonics
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• 제4권4호
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• pp.493-495
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• 1993

The frequency of the 633 nm internal mirror He-Ne laser has been stabilized by using the beat frequency and the intensity difference between two Zeeman split components in a transverse magnetic field. The frequency stability and the frequency temperature coefficient for the beat frequency method was $7.0{\times}10^{-11}$ and $170 kHz/^{\circ}C$, respectively, and those for the intensity difference was $1.1{\times}10^{-9}$ and $1.8 MHz/^{\circ}C$, respectively.

• Journal of KIISE:Software and Applications
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• 제35권10호
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• pp.616-626
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial feature information and the face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by combining the multiple frequency domains for each depth image and depth fusion using fuzzy integral. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. It is used as the reference point to normalize for orientated facial pose and extract multiple areas by the depth threshold values. In the second step, we adopt as features for the authentication problem the wavelet coefficient extracted from some wavelet subband to use feature information. The third step of approach concerns the application of eigenface and Linear Discriminant Analysis (LDA) method to reduce the dimension and classify. In the last step, the aggregation of the individual classifiers using the fuzzy integral is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) show the highest recognition rate among the regions, and the depth fusion method achieves 98.6% recognition rate, incase of fuzzy integral.

• Journal of Korea Multimedia Society
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• 제11권11호
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• pp.1501-1514
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial information. The face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by multiple frequency domains for each depth image using the modified fuzzy c-mean algorithm. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. And the second step takes into consideration of the orientated frontal posture to normalize. Multiple contour line areas which have a different shape for each person are extracted by the depth threshold values from the reference point, nose tip. And then, the frequency component extracted from the wavelet subband can be adopted as feature information for the authentication problems. The third step of approach concerns the application of eigenface to reduce the dimension. And the linear discriminant analysis (LDA) method to improve the classification ability between the similar features is adapted. In the last step, the individual classifiers using the modified fuzzy c-mean method based on the K-NN to initialize the membership degree is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) showed the highest recognition rate among the extracted regions, and the proposed classification method achieved 98.3% recognition rate, incase of fuzzy cluster.

• Journal of Broadcast Engineering
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• 제20권3호
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• pp.408-413
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• 2015

Recently, According to increasing interest to original sound Karaoke instrument, MIDI type karaoke manufacturer attempt to make more cheap method instead of original recoding method. The specific method is to make the original sound accompaniment to remove only the voice of the singer in the singer music album. In this paper, a system to separate vocal components from music accompaniment for stereo recordings were proposed. Proposed system consists of two stages. The first stage is a vocal detection. This stage classifies an input into vocal and non vocal portions by using SVM with MFCC. In the second stage, selective frequency subtractions were performed at each frequency bin in vocal portions. In this case, it is determined in consideration not only the energies for each frequency bin but also the phase of the each frequency bin at each channel signal. Listening test with removed vocal music from proposed system show relatively high satisfactory level.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.607-612
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• 1993

원심분리기는 용액 속에 있는 물질을 크기와 밀도 및 모양의 다름을 이용하여 용액으로부터 분리, 정제 및 순화하는 과학기계이며 처리량의 규모에 따라 공업용과 실험실용으로 분류된다. 공업용은 처리량이 많은 반면 실험실용은 처리량이 적으나 분리효과가 좋은 특징을 갖으며 회전속도에 의해 저속, 고속 및 초고속의 원심분리기로 나뉘어진다. 초고속 원심분리기는 최초(30년대)에 침전계수의 측정을 목적으로 연구개발을 시작하였다. 이의 용도에서 사용되는 초고속원심기를 분석용 초고속원심기라 부르나 이는 50년대 이후에 점차적으로 기술적 발전을 가져와 미소물질 분리를 위한 분리용 초고속원심기로 변천이 되어 생물학분야 이외에 항공기,선박,고속철도,석유탐지,원자력,섬유공업과 반도체등 여러 분야에 이용이 되고 있다.

• Journal of the Korean Society for Nondestructive Testing
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• 제21권1호
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• pp.39-45
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• 2001

Fourier transform has been one of the most common tools to study the frequency characteristics of signals. With the Fourier transform alone, however, it is difficult to tell whether signal's frequency contents evolve in time or not. Except for a few special cases, the frequency contents of most signals encountered in the real world change with time. Time-frequency analysis methods are developed recently to overcome the drawbacks of Fourier transform, which can represent the information of signals in time and frequency at the same time. In this study, damage process of a cross-ply carbon fiber reinforced plastic (CFRP) under monotonic tensile loading was characterized by acoustic emission. Different kinds of CFRP specimens were used to determine the characteristics of AE signals. Time-frequency analysis methods were employed for the analysis of fracture mechanisms in CFRP such as mix cracking, debonding, fiber fracture and delamination.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제4권2호
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• pp.77-82
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• 2011

In this paper, we investigate source separation algorithms for stereo audio mixed using amplitude panning method. This source separation algorithms can be used in various applications such as up-mixing, speech enhancement, and high quality sound source separation. The methods in this paper estimate the panning angles of individual signals using the principal component analysis being applied in time-frequency tiles of the input signal and independently extract each signal through directional filtering. Performances of the methods were evaluated through computer simulations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.295-299
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• 2004

본 논문에서는 주기 비안정 연속계의 해석을 위한 주파수 방법이 제안된다. 비안정시스템의 안정화를 위한 기존의 주파수 해석법을 일부 수정하여 연속계를 포함한 비안정 시스템에 적합하도록 수정하였으며, 직류모터와 동기발전기로 구성되어 있는 전기-기계 시스템에 적용하여 유용성을 보였다. 복잡한 비안정 연속계의 문제를 각 요소별 주파수 응답을 분리하고 조합하는 작업들을 통하여 쉽게 풀 수 있음을 보였다. 모터-발전기로 구성되어있는 전기-기계 시스템에서 발전기의 상호유도인덕턴스의 시간에 따른 주기적 변화와 장선(long electrical line)의 부하가 시스템의 불안정성을 야기함을 보였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제36권4호
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• pp.457-463
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• 2012

The basilar membrane (BM), one of organs of cochlea, has the specific positions of the maximum amplitude at each of related frequencies. This phenomenon is due to the geometry of BM. In this study, as the part of the research for the development of fully implantable artificial cochlea which is based on polymer membrane, parametric studies are performed to suggest the desirable artificial basilar membrane model which can detect wider range of frequency separation. The vibro-acoustic characteristics of the artificial basilar membrane are predicted through finite element analysis using commercial software Abaqus. Simulation results are verified by comparing with experimental results. Various geometric shapes of the BM and residual stress effects on the BM are investigated through the parametric study to enable a wider detectable frequency separation range.

• The Journal of the Acoustical Society of Korea
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• 제35권2호
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• pp.110-117
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• 2016

Passive sonar systems detect and classify the target by analyzing the radiated noises from vessels. If multiple noise sources exist within the sonar detection range, it gets difficult to classify each noise source because mixture of noise sources are observed. To overcome this problem, a beamforming technique is used to separate noise sources spatially though it has various limitations. In this paper, we propose a new method that uses a FDICA (Frequency Domain Independent Component Analysis) to separate noise sources from the mixture. For experiments, each noise source signal was synthesized by considering the features such as machinery tonal components and propeller tonal components. And the results of before and after separation were compared by using LOFAR (Low Frequency Analysis and Recording), DEMON (Detection Envelope Modulation On Noise) analysis.