• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.626-648
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• 2021

Domestically, demands for multi-purpose performance venues which accommodate various performance genres have increased. However, those venues have limited capability and confined to a primary performance. The present work investigated various methods for controlling the acoustics of room for required performance genres by reviewing aurally presented and published materials. The method of varying the acoustics of a space is called Variable Acoustics, and adjusted in either passive and active ways. Passive control encompasses variable absorption, variable volume, coupled volume, and canopy reflectors, where the acoustics of a room is controlled in an architectural way. Active control includes In-line, Regenerative, and Hybrid systems where the acoustics of a room is manipulated electronically. The mechanism and application of each passive control system in existing venues are reviewed and their pros and cons are discussed. Also, the concept of each active systems and product applications are looked at through literature reviews. Lastly, some considerations that need to be taken into in the planning and design stage of a multi-purpose hall using Variable Acoustics are suggested.

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.371-376
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• 2020

Underwater acoustics, which is the study of the phenomena related to sound waves in water, has been applied mainly in research on the use of sound navigation and range (SONAR) systems for communication, target detection, investigation of marine resources and environments, and noise measurement and analysis. Underwater acoustics is mainly applied in the field of remote sensing, wherein information on a target object is acquired indirectly from acoustic data. Presently, machine learning, which has recently been applied successfully in a variety of research fields, is being utilized extensively in remote sensing to obtain and extract information. In the earlier parts of this work, we examined the research trends involving the machine learning techniques and theories that are mainly used in underwater acoustics, as well as their applications in active/passive SONAR systems (Yang et al., 2020a; Yang et al., 2020b; Yang et al., 2020c). As a follow-up, this paper reviews machine learning applications for the inversion of ocean parameters such as sound speed profiles and sediment geoacoustic parameters.

• Journal of Ocean Engineering and Technology
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• v.34 no.4
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• pp.277-284
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• 2020

Underwater acoustics, which is the study of phenomena related to sound waves in water, has been applied mainly in research on the use of sound navigation and range (SONAR) systems for communication, target detection, investigation of marine resources and environments, and noise measurement and analysis. The main objective of underwater acoustic remote sensing is to obtain information on a target object indirectly by using acoustic data. Presently, various types of machine learning techniques are being widely used to extract information from acoustic data. The machine learning techniques typically used in underwater acoustics and their applications in passive SONAR systems were reviewed in the first two parts of this work (Yang et al., 2020a; Yang et al., 2020b). As a follow-up, this paper reviews machine learning applications in SONAR signal processing with a focus on active target detection and classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.546-555
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• 2013

In this paper, we propose a novel method to enhance the harmonic components from the frequency lines of the passive sonar signals. For this, we first separate the stable frequency lines from unstable ones using mean and difference of spectral bins in the vernier analysis. Then we emphasize the harmonic components using autocorrelation-based postprocessing, and enhance them by reducing the background noise with the split-window two pass mean algorithm. Experimental results for real underwater acoustic data are presented with our discussions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.482-485
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• 2004

On the basis of theoretical studies on the effect of the cylinders attached to semi-infinite screens, the tangential sound power-transport parallel to the surface of the attached cylinder is minimized by means of a secondary sound field, which is generated from a part of the attached cylinder. The numerical study shows the possibility of deflecting the incident sound by minimizing the acoustic surface impedance of the upper sections. The acoustical shadow region was more pronounced in both near- and far-field compared to the passive case with rigid surface, i.e. without active control. For a relatively wide frequency range it was possible to enhance shielding effects only with few secondary sources and error microphones. In this paper effects of some control parameters on the actively controlled sound field near the top edge of noise barriers are studied. Results of numerical study and model measurements are shown and discussed.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.562-572
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• 2003

A matched-target model inversion method was developed for a passive sonar to estimate the position of moving targets. Based on the well known matched-field processing in underwater acoustics, the method finds target position by matching the measured target directions and frequencies with the corresponding values of the proposed target model. For the efficient and accurate estimations, the parameter searching was accomplished using a hybrid optimizing method, which first starts with a global optimization such as generic algorithm or simulated annealing then applies a local optimization of a simple down hill algorithm. The suggested method was testified using simulations for three different moving scenarios. The simulation results showed that the method is robust in convergence, even under the situation of over 5 times standard deviation of Gaussian distribution of measured error, and is practical in calculation time as well.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.50 no.4
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• pp.406-412
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• 2017

Vocalizations of the common dolphin Delphinus Delphis, were recorded from a single hydrophone while coastal visual survey was performed in the East Sea in March 2017. Like most Delphinidae, common dolphins produce whistles, echolocation clicks, and burst-pulsed calls, with repertoires that differ between species and geographically separated populations. This study focuses on using frequency analysis to classify sounds into three categories and to compare them with those of other common dolphin populations. The fundamental frequencies of the whistles were high in the 6 to 14 kHz range, while echolocation clicks were in the 40 to 90 kHz frequency band. These results are similar to high-energy distributions in the same frequency band in other regions. Based on this study of the acoustic characteristics of dolphins off the east coast of Korea, cetacean vocalizations can be classified using a database of cetacean sounds in Korea. In addition, this technique could improve data quality for visual whale surveys and could be applied to various other research subjects.