• Journal of Advanced Navigation Technology
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• v.14 no.4
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• pp.571-577
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• 2010

Driving aircraft requires extremely complicated and detailed information processing. Pilots perform their tasks by selecting the information relevant to them. In this processing, spatial information presented simultaneously through crossmodal link is advantageous over the one provided in singular sensory mode. In this paper, probability to apply providing visual spatial information along with auditory information to enemy tracking system in aircraft navigation is empirically investigated. The result shows that auditory spatial information, which is virtually created through HRTF is advantageous to visual spatial information alone in attention processing. The findings suggest auditory spatial information along with visual one can be presented through crossmodal link by utilizing stereophonic sound such as HRTF. which is available in the existing simple stereo system.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.1-12
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• 2009

There exist some regular multiple relations in the intervals of notes when they are combined within one measure. This paper presents a method to find the exact measure positions in monophonic song based on those relations. In the proposed method the individual intervals are segmented at first and the rules that state the multiple relations are used to find the measure position. The measures can be applied as the foundational information for extracting beat and tempo of a song which can be used as background knowledge of automatic music transcription system. The proposed method exactly detected the measure positions of 11 songs out of 12 songs except one song which consist of monophonic voice song of the men and women. Also one can extract the information of beat and tempo of a song using the information about extracted measure positions with music theory.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.490-496
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• 2020

We present a method to improve the performance of the multi-channel Wiener filter in noisy environment. To build subspace-based multi-channel Wiener filter, in the case of single target source, the target speech component can be effectively estimated in the principal subspace of speech correlation matrix. The speech correlation matrix can be estimated by subtracting noise correlation matrix from signal correlation matrix based on the assumption that the cross-correlation between speech and interfering noise is negligible compared with speech correlation. However, this assumption is not valid in the presence of strong interfering noise and significant error can be induced in the principal subspace accordingly. In this paper, we propose to adjust the principal subspace vector using speech presence probability and the steering vector for the desired speech source. The multi-channel speech presence probability is derived in the principal subspace and applied to adjust the principal subspace vector. Simulation results show that the proposed method improves the performance of multi-channel Wiener filter in noisy environment.

• Geophysics and Geophysical Exploration
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• v.5 no.1
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• pp.18-22
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• 2002

As a single arrival traveltime, maximum energy arrival traveltime has been known as the most proper operator for Kirchhoff migration. In case of the model having the simple structure, both the first arrival traveltime and the maximum energy arrival traveltime can be used as the correct operators for Kirchhoff migration. However for some model having the complex and high velocity contrast structure, the migration using the first arrival traveltime can't give the correct depth section. That is, traveltime to be required in Kirchhoff migration is the maximum energy traveltime, but, needs considerably more calculation time than that of first arrival. In this paper, we propose the method for calculating the traveltime approximated to the maximum energy arrival using one-way wave equation. After defining the WAS(Wrap Around Suppression) factor to be used for calculating the first arrival traveltime using one-way wave equation as the function of lateral grid interval and depth and considering the delay time of source wavelet. we calculate the traveltime approximated to the maximum energy arrival. to verify the validity of this traveltime, we applied this to the migraion for simple structure and complex structure and compared the depth section with that obtained by using the first arrival traveltime.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.174-183
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• 2022

Acoustic radiation from a submerged elastic shell with an internal fluid surrounded by the bubble layer is studied with the modal theory. An omni-directional point source located on the center of the internal fluid is used as acoustic noise source. The unknown coefficients of modal solutions are solved using the interface conditions between media. To preserve the stability of the modal solution over wide frequency ranges, the scaled technique of modal solution is used. The bubble layer is modeled with four kinds of bubble distribution; uni-modal distribution, uniform distribution, normal distribution, and power-law distribution, based on the effective medium theory of Commander and Prosperetti. For each bubble distribution, the insertion losses are mainly calculated for the frequency. In addition, the numerical simulations are performed depending in the bubble void fraction, the material property of elastic shell, and the gap between the bubble layer and the elastic shell.

• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.357-364
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• 2008

For the purpose of possibility study on development of an acoustic tweezer using standing waves and very high frequency ultrasound focused beams, a system which can manipulate the position of particles in water has been constructed. It can move the particles to near focal point of a focused beam by the radiation force of standing waves, and then the particles would be trapped by the radiating force of the focused beam. The results show that micro sphere particles were trapped well at nodes of the standing waves and their position can be easily manipulated by frequency control. And, even though the radiation force by single focused beam pushes a particle away from the transducer, two focused confronted beams can trap it at near center.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.211-216
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• 2013

In general, smoothing filters regularize functions by reducing differences between adjacent values. The smoothing filters, therefore, can regularize inverse solutions and produce more accurate subsurface structure when we apply it to full waveform inversion. If we apply a smoothing filter with a constant coefficient to subsurface image or velocity model, it will make layer interfaces and fault structures vague because it does not consider any information of geologic structures and variations of velocity. In this study, we develop a selective smoothing regularization technique, which adapts smoothing coefficients according to inversion iteration, to solve the weakness of smoothing regularization with a constant coefficient. First, we determine appropriate frequencies and analyze the corresponding wavenumber coverage. Then, we define effective maximum wavenumber as 99 percentile of wavenumber spectrum in order to choose smoothing coefficients which can effectively limit the wavenumber coverage. By adapting the chosen smoothing coefficients according to the iteration, we can implement multi-scale full waveform inversion while inverting multi-frequency components simultaneously. Through the successful inversion example on a salt model with high-contrast velocity structures, we can note that our method effectively regularizes the inverse solution. We also verify that our scheme is applicable to field data through the numerical example to the synthetic data containing random noise.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.