• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.606-610
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• 2004

Although time-frequency analysis is useful for dispersive wave analysis, conventional methods such as the short-time Fourier transform do not take the dispersion phenomenon into consideration in the tiling of the time-frequency domain. The objective of this paper is to develop an adaptive time-frequency analysis method whose time-frequency tiling is determined with the consideration of signal dispersion characteristics. To achieve the adaptive time-frequency tiling, each of time-frequency atoms is rotated in the time-frequency plane depending on the local wave dispersion. To carry out this adaptive time-frequency transform, dispersion characteristics hidden in a signal are first estimated by an iterative scheme. To examine the effectiveness of the proposed method, the flexural wave signals measured in a plate were analyzed.

• Journal of Welding and Joining
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• v.15 no.6
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• pp.41-48
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• 1997

For analyzing the characteristics of arc welding processes, an algorithm is necessary to determine the metal transfer mode, arc stability and weld quality. In this study, the weight of spatter during welding was selected for determining the arc stability, which is very relevant to the occurrence of spatter. Weld spatter occurs mainly at the moment when the short circuit is formed and also when it is broken causing the arc to restrike. Based on this fact, the arc stability can be determined by finding the suitable parameters of welding current and arc voltage which influence the weight of spatter. Through various welding experiments, the peak current, the arcing time, the short circuit time, the current and its slope at the start of short circuit were found mainly to influence the weight of spatter. For the convenient usage, an index was proposed by combining all these parameters. It was found that the index is very effective for determining the arc stability.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.37-39
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. Since the background noise presenting to record will introduce disturbance while we just want to get the stationary parameters to represent the corresponding speech section, in particular, a major source of error in automatic recognition system of isolated words is the inaccurate detection of beginning and ending boundaries of test and reference templates, thus we must find potent method to remove the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two simple time-domain measurements - short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Comparing with the conventional methods based on short-time energy and short-time zero-crossing rate, the novel approach based on time-domain Lyapunov Exponents(LEs) is low complexity and suitable for Digital Isolated Word Recognition System.

• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.511-520
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• 2003

In room acoustics, reverberation time is an important acoustic parameter. However it is often difficult to measure short reverberation times at low frequencies with a traditional band pass filter bank if the product of filter bandwidth (B) and reverberation time (T) is small. It it well known that the minimum permissible product of bandwidth and reverberation time of the traditional band pass filter is at least 16. This strict requirement makes it difficult to measure short reverberation times of an acoustic room at low frequencies exactly. In order to reduce this strict requirement, in the previous paper, the wavelet filter bank was developed and the minimum permissible product of bandwidth and reverberation time was replaced with 4. In the present paper it is demonstrated how the short reverberation times of an practical room at low frequencies are successfully measured by using the wavelet filter bank and the results are compared with the traditional method using a band past filer bank.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.375-378
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• 2009

The Spectrum Sensing Technology is the core technology of the Cognitive Radio (CR) System that is one of the future wireless communication technologies. This is the technology that temporarily allocates the frequency bandwidth by scanning surrounding wireless environments to keep licensed terminals and search the unused frequency bandwidth. In this paper, we proposed the efficient Spectrum Sensing Method using the Short Time Fourier Transform (STFT). The Cosine and DVB-H signal with the 6MHz bandwidth is used as the Input Signal. And we confirm the Spectrum Sensing result using Modified Periodogram Method, Welch's Method for compared with Short Time Fourier Transform Algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1077-1080
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• 2002

In building acoustics, reverberation time is an important acoustic parameter. However, it is often difficult to measure short reverberation times at low frequencies using the traditional band pass filter bank if the product of bandwidth (B) and reverberation time (T) is small. It is well known that the minimum permissible product of bandwidth and reverberation time of the traditional band pass filter is at least 16 ［F. Jacobsen, J. Sound Vib. 115, 163-170 (1987)]. This strict requirement makes it difficult to measure short reverberation times of an acoustic room at low frequencies exactly. In order to reduce this strict requirement, recently, the wavelet filter bank is developed and the minimum permissible product of bandwidth and reverberation time is replaced with 4 [S. K. Lee, J, Sound Vib. 252, 141-153 (2002)]. In the present paper, it is demonstrated how the short reverberation times at low frequencies are successfully measured by using the wavelet filter bank. In order to present this job, two synthetic signals and one measured signal are used for impulse responses of an acoustic room.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1419-1424
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• 2018

Very short-term electric load forecasting is essential for real-time power system operation. In this paper, a very short-term electric load forecasting technique applying the Kalman filter algorithm is proposed. In order to apply the Kalman filter algorithm to electric load forecasting, an electrical load forecasting algorithm is defined as an observation model and a state space model in a time domain. In addition, in order to precisely reflect the noise characteristics of the Kalman filter algorithm, the optimal error covariance matrixes Q and R are selected from several experiments. The proposed algorithm is expected to contribute to stable real-time power system operation by providing a precise electric load forecasting result in the next six hours.

• Journal of the Korean Home Economics Association
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• v.32 no.1
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• pp.31-46
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• 1994

the purpose of this study is to investigate (1) the real life of urban employed husbands and their wives(2) the balance between labor force reproduction and the labor force consumption(3) and the share of family responsibility by analysis patterns of their time use. Data for 227 couples were gatherd from using structured questionnaire and time diary. (1) Because of Husbands' long labor time and employed wives' roleoverload their social-cultural time is too short which means the pattern of their time use are very unbalanced type. (2) Regardless of wives' employment status husbands' housework time is too short which means that family responsibility is scarcely shared.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.2
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• pp.431-441
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• 2014

The effects of hull-girder vibration on the fatigue strength of a Post-Panamax container ship are discussed in the present paper. Firstly, the short-term sea states are categorized according to the occurrence probability of each sea state. Time histories of hull-girder stress in short-term sea states are calculated by means of a nonlinear simulation code of ship response assuming that the hull-girder is rigid and flexible. Then, the calculated stress peaks are processed by the rainflow counting method, where two different counting procedures are used based on the considerations of crack propagation behaviors. Finally, the fatigue damage in life time of the ship in each categorized short-term sea state is estimated by means of Miner's rule. Based on the calculated results, the effects of hull-girder vibrations on the fatigue damage are clarified by disaggregated damage from short-term sea state.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.83-86
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• 2001

In injection molding, short shot is one of the frequent and fatal defects. Experts of injection molding usually adjust process conditions such as injection time, mold temperature, and melt temperature because it is the most economic way in time and cost. However it is a difficult task to find appropriate process conditions for troubleshooting of short shot as injection molding process is a highly nonlinear system and process conditions are coupled. In this paper, a fuzzy neural network(FNN) has been applied to injection molding process to shorten troubleshooting time of short shot. Based on melt temperature and fill time, a reasonable initial mold temperature is recommended by the FNN, and then the mold temperature is inputted to injection molding process. Depending on injection molding result, specifically the insufficient quantity of an injection molded part, an appropriate mold temperature is recommend repeatedly through the FNN.