• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.349-352
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• 2001

The transient response in TDFA(Thulium-Doped Fiber Amplifier) is theoretically investigated. The TDFA has the spectral gain band in 1.47 ${\mu}{\textrm}{m}$. The transient model includes the transient buildup of the population inversion, the pump power, the signal power and their transient variation along the fiber amplifier. The results of numerical analysis can predict the gain saturation and recovery time at the fiber amplifier. It also shows the gain saturation and recovery effect depending on the pumping and saturation rate.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.57-63
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• 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.190-197
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• 2004

This paper presents automated prediction of transient ischemic episodes using neural networks(NN) based pattern matching method. The learning algorithm used to train the multilayer networks is a modified backpropagation algorithm. The algorithm updates parameters of nonlinear function in a neuron as well as connecting weights between neurons to improve learning speed. The performance of the method was evaluated using ECG signals of the MIT/BIH long-term database. Experimental results for 15 records(237 ischemic episodes) show that the average sensitivity and specificity of ischemic episode prediction are 85.71% and 71.11%, respectively. It is also found that the proposed method predicts an average of 45.53［sec］ ahead real ischemia. These results indicate that the NN approach as the pattern matching classifier can be a useful tool for the prediction of transient ischemic episodes.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.311-313
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• 1992

Automated analysis of EEG invariably requires the inclusion of a signal conditioning filter. This paper investigates the EEG waveform distortions caused by the transient responses of the various types of signal conditioning filters. This study explicitly simulates the filter responses to the typical EEG waveform models, and compares the distortions.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.528-533
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• 2010

This paper describes a calculation method of source level of a ship transient noise, which is one of the important elements for the ship detection. Aim of transient noise measurements is to evaluate of acoustic energy due to singular occurrence, which is therefore defined as non-periodic and short termed events like an attack periscope, a rudder and a torpedo door. In generally, in the case of randomly spaced impulse, the spectrum becomes a broadband random noise with no distinctive pattern. Therefore, frequency analysis is not particularly revealing for type of signal. In the paper, it is performed in time domain to analyze a transient noise. However, a source level of transient noise is required an investigation for multiple frequency band. So, in order to calculate a source level of transient noise, a design of exponential weighting function, convolution, band pass filtering, peak detection, root mean square, and parameter compensation are applied. The effectiveness of this calculation scheme is studied through computer simulations and a sea test. Furthermore, an application of the method is applied in a real case.

• Structural Engineering and Mechanics
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• v.90 no.4
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• pp.417-428
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• 2024

Nanocomposite-reinforced concrete systems have gained increasing attention in bridge construction due to their enhanced mechanical properties and durability. Understanding the transient dynamics of these advanced materials is crucial for ensuring the structural integrity and performance of bridge infrastructure under dynamic loading conditions. This paper presents a comprehensive study of the measurement techniques employed for assessing the transient dynamics of nanocompositereinforced concrete systems in bridge construction applications. A numerical method, including modal analysis are discussed in detail, highlighting their advantages, limitations, and applications. Additionally, recent advancements in sensor technologies, data acquisition systems, and signal processing techniques for capturing and analyzing transient responses are explored. The paper also addresses challenges and opportunities in the measurement of transient dynamics, such as the characterization of nanocomposite-reinforced concrete materials, the development of accurate numerical models, and the integration of advanced sensing technologies into bridge monitoring systems. Through a critical review of existing literature and case studies, this paper aims to provide insights into best practices and future directions for the measurement of transient dynamics in nanocompositereinforced concrete systems, ultimately contributing to the design, construction, and maintenance of resilient and sustainable bridge infrastructure.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.2
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• pp.152-162
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• 2001

Laser-generated ultrasonic technique which is one of the reliable nondestructive evaluation techniques has been applied to evaluate the integrity of structures by analyzing the characteristics of signal obtained from surface crack. Therefore, the signal analysis of the laser-generated ultrasonics is absolutely necessary for the accurate and quantitative estimation of the surface defects. In this study, one-sided measurement by laser-generated ultrasonic has been applied to evaluate the depth of the surface-breaking crack in the materials. However, since the ultrasonic waveform excited by pulse laser is very difficult to distinguish the defect signals, it is necessary to consider the signal analyses of the transient waveform. Wavelet Transform(WT) is a powerful tool for processing transient signals with temporally varying spectra that helps to resolve high and low frequency transient components effectively. In this paper, the analyses of the surface-breaking crack of the ultrasonic signal excited by pulse laser are presented by employing the WT analyses.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.4
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• pp.34-41
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• 2003

A new technique for detecting parametric faults in mixed signal circuits is proposed Pseudo-random sequence from linear feedback shift register(LFSR) is fed to circuit-under-test (CUT) as stimulus and wavelets are used to compact the transient response under this stimulus into a small number of signature. Wavelet based scheme decomposes the transient response into a number of signal in different frequency bands. Each decomposed signal is compacted into a signature using digital integrator. The digital pulses from LFSR, owing to its pseudo-randomness property, are almost uniform in frequency domain, which generates multi-frequency response when passed through CUT. The effectiveness of this technique is demonstrated in our experimental results.

• Proceedings of the KSME Conference
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• 2001.06e
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• pp.294-298
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• 2001

Satellite propulsion system is employed for orbit transfer, orbit correction, and attitude control. The monopropellant feeding system in the low-earth-orbit satellite blowdowns fuel to the thrust chamber. The thrust produced by the thruster depends on fuel amount flowed into the combustion chamber. If the thruster valve be given on-off signal from on-board commander in the satellite, valve will be opened or closed. When the thrusters fire fuel flows through opened thruster valve. Instantaneous stoppage of flow in according to valve actuation produces transient pressure due to pressure wave. This paper describes transient pressure predictions of the KOMPSAT2 propulsion system resulting from latching valve and thrust control valve operations. The time-dependent set of the fluid mass and momentum equations are calculated by Method of Characteristics (MOC).

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.883-884
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• 2008

This paper presents a method for classification of underwater transient signals using, which employs a binary image pattern of the mel-frequency cepstral coefficients(MFCC) as a feature vector and a neural network as a classifier. A feature vector is obtained by taking DCT and 1-bit quantization for the square matrix of the MFCC sequences. The classifier is a feed-forward neural network having one hidden layer and one output layer, and a back propagation algorithm is used to update the weighting vector of each layer. Experimental results with some underwater transient signals demonstrate that the proposed method is very promising for classification of underwater transient signals.