• Journal of Microbiology and Biotechnology
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• v.12 no.2
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• pp.345-348
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• 2002

A rapid spectrophotometric method for detecting the mucinase complex was developed. Bovine submaxillary mucin is cleaved by commercial mucinase between the oligosaccharide chain and the side chain of peptide linkage, thereby liberating the N-acetyl neuraminic acid (NANA). The release of NANA resulted in an increase of absorbance at 280 nm. The susceptibility to NANA by the new method was found to be at least 10-fold more sensitive than the thiobarbituric acid method. Moreover, the quantification of NANA released from mucin by commercial neuraminidase and partially purified Vibrio parahaemolyticus mucinase showed a good linear correlation in proportion to the concentration of the enzyme used. These results demonstrate that the rapid identification of mucin degradation can be determined by a spectrophotometric assay, thereby providing a new, fast, and sensitive method for assaying the bacterial mucinase complex.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.267-274
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• 2017

In this study was investigated of possibility using the recorded micro tremor data on ground level as ambient vibration input excitation data for investigation and application Operational Modal Analysis (OMA) on the bench-scale earthquake simulator (The Quanser Shake Table) for model steel structures. As known OMA methods (such as EFDD, SSI and so on) are supposed to deal with the ambient responses. For this purpose, analytical and experimental modal analysis of a model steel structure for dynamic characteristics was evaluated. 3D Finite element model of the building was evaluated for the model steel structure based on the design drawing. Ambient excitation was provided by shake table from the recorded micro tremor ambient vibration data on ground level. Enhanced Frequency Domain Decomposition is used for the output only modal identification. From this study, best correlation is found between mode shapes. Natural frequencies and analytical frequencies in average (only) 2.8% are differences.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.3063-3065
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• 2005

In the raper, the noise involved on the active circuit is identified using correlation function. In order to identify the unknown noise source location, signals from each points on the system are detected and the location is identified by a concept calico Noise Source Surface. The fault diagnosis method is suggested for each element by identifying the noise source in active circuit using SVM. Experiment is conducted to confirm the validity of the proposed method. Also a method to reduce and control the noise in the system signal by using Matrix Pencil Method is introduced.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.646-649
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• 2004

LiDAR(Light Detection and Ranging) system can record intensity data as well as range data. Recently, LiDAR intensity data is widely used for landcover classification, ancillary data of feature extraction, vegetation species identification, and so on. Since the intensity return value is associated with several factors, same features is not consistent for same flight or multiple flights. This paper investigated correlation between intensity and range data. Once the effects of range was determined, the single flight line normalization and the multiple flight line normalization was performed by an empirical function that was derived from relationship between range and return intensity

• Speech Sciences
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• v.7 no.2
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• pp.127-137
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• 2000

This paper presents a macro script to analyze numeric sounds by a speech analysis shareware, Praat, and analyzes those sounds produced by three students who were born and raised in Pusan. Recording was done in a quiet office. To make a meaningful comparison, dynamic time points in relation to the total duration of voicing segments were determined to measure acoustical values. Results showed that a strong correlation coefficient was found between the repetitive production of numeric sounds within and across the speakers. Very high coefficients among diphthongal numbers (0 and 6) which usually show wide formant variation were noticed. This supports that each speaker produced numbers quite coherently. Also, the frequency differences between the three subjects were within a perceptually similar range. To identify a speaker among others may require to find subtle individual differences within this range. Perceptual experiments by synthesized numeric sounds may lead to resolve the issue.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.343-345
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• 2005

In the study, the noise involved on the active circuit is identified using correlation function. In order to figure out the unknown location of noise source, signals from each sections in the system are collected and the location is identified by a concept called "Noise Source SUI-face". Experiment is conducted to confirm the validity of the proposed method. Also a method to reduce and control the noise in the system signal by using Matrix Pencil Method is introduced. Experiment is attempted to prove that the total noise of system can be reduced by controlling the external noise.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.476-479
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• 1992

This paper presents a neural network method for tuning PlD controller of a time-varying process. Three gains of PlD controller are tuned for a certain desirable response pattern by back-propagation neural network. The neural network is trained using changes of output features vs. changes of PlD gains. But sometimes it needs longer training time and larger structure to train the correlation between the process and controller on entire region of the process. The difficulty in system identification is that the inverse function of the system can not be clearly stated. To cope with the problem, we do not train the neural network to respond correctly for the entire regions but train for only local region where the system is heading toward by training the neural network and tuning of the PlD controller. It may be trained for fine-tuning itself. Simulation results show that the adaptive PID controller using neural network trained in the local area performs remarkably for time-varying second order process.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1990.10a
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• pp.3-8
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• 1990

소음/진동 문제를 해결하는 데 있어서 우선은 소음/진동원들의 위치를 알아 내고 그들 중에 비중이 가장 큰 소음/진동원을 파악하는 것이 중요하다. 다 입력/단일출력 모형을 이용한 소음/진동원 규명에 대한 방법에는 주파수 응 답함수를 이용하는 방법(frequency response function approach)과 부분 기여 도 함수(partial coherence function)를 이용하는 방법 등이 있는데, 입력들 사이의 상호상관(correlation)이 없는 경우에는 전자의 방법을 사용하여 출력 에 가장 큰 비중을 차지하는 소음/진동원을 알아낼 수 있으나 상호상관이 존 재하는 경우에는 후자의 방법을 사용하게 된다. 그러나 후자의 방법을 적용 함에 있어서도 기본적으로 소음/진동원들의 위치를 알아야 하는 것 이외에 그들 사이의 원인.효과관계(causaling), 또는 우선순위(rank)를 우선적으로 아 는 것이 중요한데 이는 입력들 사이의 우선순위를 어떻게 두느냐에 따라 해 석 결과가 다르게 나타나기 때문이다 [1,2,3]. 본 연구에서는 부분 기여도 함 수를 이용하여 소음/진동원을 규명할 때 그들 사이의 우선순위를 결정하는 방법을 제시하고 2입력/1출력 모형에 대해 적용하여 보았다.

• Structural Engineering and Mechanics
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• v.46 no.6
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• pp.853-868
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• 2013

The comparison of the effectiveness of artificial neural network (ANN) and linear regression (LR) in the prediction of strain in tie section using experimental data from eight high-strength-self-compact-concrete (HSSCC) deep beams are presented here. Prior to the aforementioned, a suitable ANN architecture was identified. The format of the network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of eleven and ten neurons in first and second TRAINLM training function was highly accurate and generated more precise tie strain diagrams compared to classical LR. The ANN's MSE values are 90 times smaller than the LR's. The correlation coefficient value from ANN is 0.9995 which is indicative of a high level of confidence.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.59.2-59.2
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• 2018

Recent studies of galaxy clusters have shown that the galaxy clusters in dense environment tend to have lower star formation rate in local universe with z < 1. However, this correlation is not significant in galaxy clusters with z > 1. The study of galaxy clusters around z=1 can yield insight into cosmological galaxy evolution. Nevertheless, the identification of galaxy clusters beyond the scope of immediate local universe requires wide field data in optical and near-infrared bands. By incorporating data from Canada-France-Hawaii Telescope Legacy Survey(CFHTLS) and Infrared Medium-Deep Survey(IMS), the photometric redshifts of galaxies in CFHTLS W2 field were calculated. Using spatial distribution and photometric redshifts, the galaxies in the field were divided into redshift bins. The image of each redshift bin was analyzed by measuring the number density within proper distance of 1Mpc. By comparing high density regions in consecutive redshift bins, we identified the cluster candidates and mapped the large-scale structure within the CFHTLS W2 field.