• Korean Journal of Environment and Ecology
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• v.32 no.1
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• pp.39-46
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• 2018

Breeding bird surveys provide the reference information for understanding bird community structure and function in the ecosystem and conserving biodiversity. Recent rapid change of biodiversity due to climate change and other factors has made it necessary to utilize acoustic sensors for accuracy and spatial expansion of forest bird survey data and for time-series monitoring of forest birds. The objective of this study is to investigate the possibility of using acoustic recording sensor to evaluate the diversity of forest birds at breeding season by comparing and analyzing the recorded data of bird songs and field bird survey data. We conducted the site survey and recording in 186 points in 48 areas of 4 regions of Gombaeryeong and Jochimryeong around Jeombongsan Mountain and Jugryeong and Gochiryeong around Sobaeksan Mountain from May 2nd to 16th in 2013. The analysis of the correlation between the recording result and Bird Community Index based on the field survey showed that the number of bird species, population, and the number of bird songs by recording was significantly correlated to the number of species and population by field survey. Moreover, the number of bird species and the number of bird songs by recording showed a significant correlation to species diversity and species richness but no or low significant correlation to species evenness by the field study (observation and listing in parallel). As a result, it was possible to check species composition and species diversity of bird communities by analyzing acoustic recording data on the field. The acoustic recordings of bird songs in the breeding period were more reliable than the non-breeding period in the correlation of recording result and species diversity and for utilization.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.188-195
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• 2018

A new directional linear array structure and its signal processing method are presented to resolve the left/right ambiguity inherent in a linear array. The array structure combines an ordinary acoustic sensor array with a DIFAR (Directional Frequency Analysis and Recording) sensor array, keeping a linear array configuration and gaining a instantaneous left/right discrimination. It presents better PSRR (Port-Starboard Rejection Ratio) in low frequency band and low SNR (Signal to Noise Ratio) situation as compared with a conventional twin linear array, and good compromise to easily upgrade an existing linear array system to a new one with a left/right discrimination capability.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.3
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• pp.232-238
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• 2010

The moving ranges and behavior of four wild abalones, Haliotis discus hannai, were measured by an acoustic telemetry technique. The shape of the sea bottom of the experimental area was surveyed by a bathymetry system and three self-recording type acoustic receivers were used for monitoring the behavior and measuring the movement range. The abalones (WA1-WA4) attached acoustic tags were released and measured the movement during ten months. Three abalones (WA1, WA3 and WA4) were successively detected around the released point during the experiment and were moved to the V2 area where water depth is deeper than the V1 area. The change of inhabitation depth was also detected from the depth sensor of WA4. As the result, abalones were moved to deeper water area accordance with the decrease of the water temperature. The moved ranges of abalones were approximately 200 - 400m from the release point.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2E
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• pp.71-80
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• 2002

This paper suggests the Cardioid beamforming algorithm of the doublet sensors employing DIFAR (directional frequency analysis and recording) sensor signals in the frequency domain. The algorithm enables target bearing estimation using the signals from directional sensors. The algorithm verifies its applicability by successfully estimating bearings of a target projecting ten narrow-band signals in shallow water. The estimated bearings agree very well with those from GPS (global positioning system) data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1°∼ 6.7°and 13.3∼43.6°, respectively. Estimation errors are caused by SNR (signal to noise ratio) degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.