• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.214-224
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• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.

• Journal of Music and Human Behavior
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• v.21 no.2
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• pp.107-134
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• 2024

This study aims to classify the semantic words commonly used to evaluate sound quality and to analyze their differences in reflecting the level of musical stimuli. Participants were thirty-one music majors in their 20s and 30s, with an average of 9.4 years of professional training. Each participant listened to nine pieces of music with variations in texture and instrument type and evaluated them using 18 pairs of semantic words describing sound quality. A factor analysis was conducted to group words influenced by the same latent factor, and a multivariate ANOVA determined the differences in ratings based on texture and instrument type. Radar charts were also drawn based on the identified sets of semantic words. The results showed that four factors were identified, and the word pairs 'soft-hard,' 'dull-sharp,' 'muddy-clean' and 'low-high' showed significant differences based on the level of musical stimuli. The radar charts effectively distinguished the sound quality evaluations for each music. These results indicate that developing Korean semantic words for sound quality evaluation requires a structure different from the previous categories used in Western countries and that linguistic and cultural factors are crucial. This study will provide foundational data for developing a verbal sound quality evaluation framework suited to the Korean context, while reflecting acoustic attributes in music listening.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1972.03a
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• pp.7-8
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• 1972

The effects of noise exposure are of two types: Nonauditory effects and auditory effects. Nonauditory effects of noise exposure are interference with communication by speech, sleeping and emotional behavior. The noise will cause the high blood pressure and rapid pulse, also that decrease the salivation and gastric juice. in experimentaly showed that the Corticoid hormon: Gonatotropic hormone were decrease and Thyrotropic hormoone is increase. Auditory effect of noise exposure. when the normal ear is exposed to noise at noise at hamful intensities (above 90㏈) for sufficiently long periods of time, a temoral depression of hearing results, disappearing after minutes or hours of rest. When the exposure longer or intesity greater is reached the Permanent threshold shift called noise-induced hearing loss. Hearing loss resulting from noise exposure presents legal as well as medical problems. The otologist who examines and evaluates the industrial hearing loss cases must be properly informed, not only concerning the otologic but also about the physical and legal aspects of the problems. The measurement of hearing ability is the most important part of a hearing conservation, both preplacement and periodic follow-up tests of hearing. The ideal hearing conservation program would be able to reduce or eliminate the hazardous noise at its source or by acoustic isolation of noisy working area and two ear protections (plugs and muff type) were developed for personal protection.