• Ocean Science Journal
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• v.41 no.3
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• pp.175-179
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• 2006

The Ieodo Ocean Research Station(IORS) is an integrated meteorological and oceanographic observation base which was constructed on the Ieodo underwater rock located at a distance of about 150 km to the south-west of the Mara-do, the southernmost island in Korea. The underwater ambient noise level observed at the IORS was similar to the results of the shallow water surrounding the Korean Peninsula (Choi et al. 2003) and was higher than that of deep ocean (Wenz 1962). The wind dependence of ambient noise was dominant at frequencies of a few kHz. The surface current dependence of ambient noise showed good correlation with the ambient noise in the frequency of 10 kHz. Especially, the shrimp sound was estimated through investigations of waveform and spectrum and its main acoustic energy was about 40 dB larger than ambient noise level at 5 kHz.

• Ocean and Polar Research
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• v.28 no.4
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• pp.459-465
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• 2006

Ambient noise as a background noise in the ocean has been well known for its the various and irregular signal characteristics. Generally, these signals we treated as noise and they are analyzed through stochastical level if they don't include definite sinusoidal signals. This study is to see how ocean ambient noise can be analyzed by the chaotic analysis technique. The chaotic analysis is carried out with underwater ambient noise obtained in areas near the Korean Peninsula. The calculated physical parameters of time series signal are as follows: histogram, self-correlation coefficient, delay time, frequency spectrum, sonogram, return map, embedding dimension, correlation dimension, Lyapunov exponent, etc. We investigate the chaotic pattern of noises from these parameters. From the embedding dimensions of underwater noises, the assesment of underwater noise by chaotic analysis shows similar results if they don't include a definite sinusoidal signal. However, the values of Lyapunov exponent (divergence exponent) are smaller than that of random noise signal. As a result we confirm the possibility of classification of underwater noise using Lyapunov analysis.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1
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• pp.49-56
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• 1994

In order to investigate the characteristics of oceanic rain noise, we measured ambient noise at a site on the east coast of the Korean Peninsula while it rained. Three hydrophones were placed at a depth of 30 m, 50 m, and 100 m respectively where the water depth was 200 m. The spectral characteristics of rain noise were carefully examined according to rainfall rates between 1.5 and 23.4 mm/h. And the dependence of spectral level on rainfall rate was investigated for various frequencies. Also, it was considered the generation mechanism of rain noise by means of observation of rain noise waveforms received by hydrophone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.405-411
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• 2020

Recently, studies on underwater communication, related to the development of underwater resources, disaster monitoring and defense, have been actively carried out. In the design of wireless communication systems, path loss is the most important information to derive a link budget that is required to guarantee communication reliability by calculating received power level for the given communication link. The underwater acoustic channel have different characteristics according to geographical location and relevant environmental factors such as water temperature, depth, wave height, algae, and turbidity. Subsequently, many research institutes aiming to develop underwater acoustic communication systems are researching actively on the underwater acoustic channels in various sea areas. In Korea, however, studies on the path loss of the acoustic channel are still insufficient. Therefore, in this study, the path loss of the acoustic channel are studied based on measurement data of the at-sea experiment conducted at Geohae-do, southern sea of Korea.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3
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• pp.3-9
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• 1998

해수중 주위잡음에 미치는 음속구조의 영향을 조사하기 위하여 다양한 수직 음속분 포를 가지는 경우에 대한 음파전달 모델의 결과를 논의하였다. 그리고 해수중 주위잡음의 실측자료를 이러한 모델결과와 비교하여 고찰하였다. 특히 표층 도파관(surface waveguide) 이 형성되는 조건에 대하여 조사하였다. 주위잡음의 실측자료와 모델결과를 비교한 결과, 표 층 도파관은 수심의 증가에 따라 음속이 증가하는 양의 음속 기울기를 가질 때 뿐만 아니라 음속이 어느 수심에서 급격히 감소하여 상하 두 층의 음속 균일층이 존재하는 환경에서도 잘 형성되고 있었다. 특히, 표층 도파관내의 주위잡음 레벨은 도파관 이심의 주위잡음 레벨 보다 높게 나타나고 있음을 실험적으로 확인할 수 있었다. 그리고 이러한 결과는 음파전달 모델에 의한 수치계산 결과로부터도 입증할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.341-348
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• 2020

The ability to extract useful information from an image, such as the human eye, is an interface technology essential for AI computer implementation. The building recognition technology has a lower recognition rate than other image recognition technologies due to the various building shapes, the ambient noise images according to the season, and the distortion by angle and distance. The computer vision based building recognition algorithms presented so far has limitations in discernment and expandability due to manual definition of building characteristics. This paper introduces the deep learning CNN (Convolutional Neural Network) model, and proposes new method to improve the recognition rate even by changes of building images caused by season, illumination, angle and perspective. This paper introduces the partial images that characterize the building, such as windows or wall images, and executes the training with whole building images. Experimental results show that the building recognition rate is improved by about 14% compared to the general CNN model.