• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.173-181
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• 2007

In this paper, we propose a moving target localization algorithm using acoustic spectrograms. A time-versus-frequency spectrogram provide a information of trajectory of the moving target in underwater. For a source at sufficiently long range from a receiver, broadband striation patterns seen in spectrogram represents the mutual interference between modes which reflected by surface and bottom. The slope of the maximum intensity striation is influenced by waveguide invariant parameter ${\beta}$ and distance between target and sensor. When more than two sensors are applied to measure the moving ship-radited noise, the slope and frequency of the maximum intensity striation are depend on distance between target and receiver. We assumed two sensors to fixed point then form a circle of apollonios which set of all points whose distances from two fixed points are in a constant ratio. In case of three sensors are applied, two circle form an intersection point so coordinates of this point can be estimated as a position of target. To evaluates a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program.

• Journal of Animal Science and Technology
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• v.47 no.4
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• pp.697-702
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• 2005

The aim of this study was to divide vocalizations of laying hens (Hy-Line Brown) into general vocalizations (GVs), heat stress-related vocalization (HSV), and cold stress-related vocalizations (CSVs) and to determine if they are classified by the discriminant function analysis method. Thirty laying hens, 65-wk-old, were recorded using digital video recorders 2 times from 10:00 to 14:00 h in each thermal environment (thermoneutral: $22.0{\pm}1.8^{\circ}C$, too hot: $32.0{\pm}2.0^{\circ}C$, too cold: $8.0{\pm}1.9^{\circ}C)$ after a 7 day acclimation period. When the laying hens were not recorded, they were kept in thermoneutral conditions. The GVs, HSV, and CSVs were divided based on the shapes of spectrums and spectrograms. The GVs, HSV, and CSVs were identified as 5, 1, and 3 types, respectively. Pitch, intensity, duration, formant 1, formant 2, formant 3, and formant 4 among the thermal environment-related vocalizations were significantly different (P<0.001). The discrimination rate determined by discriminant function analysis was 86.2%. These results suggest that HSV and CSVs are present and may be used as an indicator of the thermal environment.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.6 no.4
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• pp.249-258
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• 2001

Compressional wave velocity and electrical resistivity of muddy sediments in the southeastern inner shelf of Korea were studied using nine piston core samples. The acoustic and physical properties were measured with 10 cm depth interval. Sediment structures were examined by x-radiographs of the cored sediments. Subbottom profiles were obtained by a high-resolution acoustic subbottom profiler. Acoustic turbid layers are clearly seen on the profiles, and x-radiographs of the sediments showed degassying structures formed by gas escaping. On the basis of x-radiographic images, velocities, electrical resistivities and physical properties, the sediments are divided into gassy and non-gassy sediments. The presence of gas and degassying structures result in a marked variation in velocity and electrical resistivity. It can be concluded that velocity and electrical resistivity arep arameter to recognize gassy sediment. The velocity is important parameter to indicate gassy sediment.

• The Journal of the Acoustical Society of Korea
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• v.24 no.2
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• pp.103-110
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• 2005

Providing adequate amount of spatial impression for spaciousness) has been known to be one of the most important design considerations for the good acoustics of rooms for music. and the measurement, of room acoustics using parameters. such as LEF and IACC, forms an essential part of such evaluation. However. it is unavoidable to use different transducers (figure of eight microphones. head and torso) for the measurement of each parameter and it tends to make the measurement procedure complicated. The Present work tried to provide a simpler way to measure these binaural room acoustic parameters including monaural ones with a single measurement system using both spatial information collected through a 5-channel microphone and a trained neural network. A computer simulation program, CATT-Acoustic V7.2. which allowed us to obtain exactly the same spatial information as a 5-channel microphone was used. since it requires quite a large amount of data for practical training of a neural network. Since each reflection has different energy. delay and direction, energy should be integrated properly. the concept of ray tracing method was applied inversely in this work. Also applying weightings according to the delay times was considered in this work. Finally, predicted results were compared with the measured data md their correlations were analyzed and discussed.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.91-100
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• 2023

Reverberation time (T60) is a typical acoustic parameter that provides information about reverberation. Since the impacts of reverberation vary depending on the frequency bands even in the same space, frequency-dependent (FD) T60, which offers detailed insights into the acoustic environments, can be useful. However, most conventional blind T60 estimation methods, which estimate the T60 from speech signals, focus on fullband T60 estimation, and a few blind FDT60 estimation methods commonly show poor performance in the low-frequency bands. This paper introduces a modified approach based on Attentive pooling based Weighted Sum of Spectral Decay Rates (AWSSDR), previously proposed for blind T60 estimation, by extending its target from fullband T60 to FDT60. The experimental results show that the proposed method outperforms conventional blind FDT60 estimation methods on the acoustic characterization of environments (ACE) challenge evaluation dataset. Notably, it consistently exhibits excellent estimation performance in all frequency bands. This demonstrates that the mechanism of the AWSSDR method is valuable for blind FDT60 estimation because it reflects the FD variations in the impact of reverberation, aggregating information about FDT60 from the speech signal by processing the spectral decay rates associated with the physical properties of reverberation in each frequency band.

• The Journal of Engineering Geology
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• v.6 no.1
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• pp.1-13
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• 1996

The fracture transmissivity($T_f$) is the most important parameter of fracture in assessing groundwater flow in fractured rock masses by using the DFN(Discrete Fracture Network) modeling. $T_f$, the most sensitive parameter m DFN modeling, is dependent upon aperture, size and filling characteristics of each fracture set. In the field test, the accuracy of $T_f$ can be increased with Borehole Acoustic Scanning (Televiewer) and Fixed Interval Length(FIL) test in constant head. $T_f$ values measured from FIL test was modified and estimated by each fracture set on the basis of the Cubic Law and the information of aperture and filling characteristics obtained from Televiewer. The modified $T_f$ results in the increase of confidence and reliability of modeling results including the amount of tunnel inflow.And, this approach would reduce the uncertaintity of the assessment for groundwater flow in fractured rock masses using the DFN modeling.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.919-926
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• 2013

The acoustic signal from a distance sound source in an enclosed space often produces reverberant sound that varies depending on room impulse response. The estimation of the level of reverberation or the quality of the observed signal is important because it provides valuable information on the condition of system operating environment. It is also useful for designing a dereverberation system. This paper proposes a speech quality estimation method based on the harmonicity of received signal, a unique characteristic of voiced speech. At first, we show that the harmonic signal modeling to a reverberant signal is reasonable. Then, the ratio between the harmonically modeled signal and the estimated non-harmonic signal is used as a measure of standard room acoustical parameter, which is related to speech clarity. Experimental results show that the proposed method successfully estimates speech quality when the reverberation time varies from 0.2s to 1.0s. Finally, we confirm the superiority of the proposed method in both background noise and reverberant environments.

• Journal of the Korean Wood Science and Technology
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• v.48 no.1
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• pp.32-40
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• 2020

While the utilization of wood as a raw material in related industries has been increasing with the population increasing, the availability of wood from natural forests has continued to decline. An alternative to this situation is the manufacture of particleboard from non-wood lignocellulose materials through the modification of sandwich particleboard (SPb) using bamboo strands as reinforcement. In this study, strandsof belangke bamboo (Gigantochloa pruriens W) and tali bamboo (Gigantochloa apus) were utilized. The non-wood particles included sugar palm fibers, cornstalk, and sugarcane bagasse. The board was made in a three-layer composition of the face, back, and core in a ratio of 1: 2: 1. The binder used was 8% isocyanate resin. The sheet was pressed at a temperature of 160℃ for 5 min under a pressure of 3.0 N/㎟. Testing included physical and mechanical properties based on the JIS A 5908 (2003) standard, while acoustic testing was based on ISO 11654 (1997) standards. The results showed that using bamboo strands as reinforcement has an effect on the mechanical and physical properties of SPb. Almost all the types of boards met the JIS A 5908 (2003) standards, with the exception of thickness swelling (TS) and internal bond (IB) parameters. Based on the thickness swelling parameter, the C-type board exhibited the best properties. Overall, the B-type board thatused a belangke bamboo strand for the surface and sugarcane bagasse as the core underwent the best treatment. Based on the acoustical parameter, boards using a tali bamboo strand for the surface and sugar palm fiber as the core (E-type board) exhibited good sound absorption properties.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1103-1108
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• 2023

In this paper, we propose a new algorithm for attenuating the background noises in acoustic signal. This algorithm improves the noise attenuation performance by using the FNN(: Full-connected Neural Network) deep learning algorithm instead of the existing adaptive filter after wavelet transform. After wavelet transforming the input signal for each short-time period, noise is removed from a single input audio signal containing noise by using a 1024-1024-512-neuron FNN deep learning model. This transforms the time-domain voice signal into the time-frequency domain so that the noise characteristics are well expressed, and effectively predicts voice in a noisy environment through supervised learning using the conversion parameter of the pure voice signal for the conversion parameter. In order to verify the performance of the noise reduction system proposed in this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed. As a result of the experiment, the proposed deep learning algorithm improved Mean Square Error (MSE) by 30% compared to the case of using the existing adaptive filter and by 20% compared to the case of using the STFT(: Short-Time Fourier Transform) transform effect was obtained.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.