• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.34 no.1
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• pp.52-61
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• 1998

We studied behaviour pattern of anchovy (Engraulis japonicus) shoal by a method of shoal echo integration and tested species identification by a method of artificial neural network using the acoustic data collected in the East China Sea in March 1994 and in the southern coastal waters of the East Sea of Korea in March 1995. Between areas, frequency distribution of 10 shoal descriptors was different, which showed characteristics of shoal behaviour in size, bathymetric position and acoustic strength. The range and mean of shoal size distribution in length and height was wider and bigger in the southern coastal waters of the East Sea than in the East China Sea. Relative shoal size of China Sea. Fractal dimension of shoal was almost same in both areas. Mean volume reverbration index of shoal was 3 dB higher in the southern coastal waters of the East Sea than in the East China Sea. The depth layer of shoal distribution was related to bottom depth in the southern coastal waters of the East Sea, while it was between near surface and central layer in the East China Sea. Principal component analysis of shoal descriptors showed the correlation between shoal size and acoustic strength which was higher in the southern coastal waters of the East Sea, than in the East China Sea. Correlation was also found among the bathymetric positions of shoal to some degree higher in the southern coastal waters of the East Sea than in the East China Sea. The anchovy shoal of two areas was identified by artificial neural network. The contribution factor index (Cio) of the shoal descriptors between two areas were almost identical feature. The shoal volume reverberation index (Rv) was showed the highest contribution to the species identification, while shoal length and shoal height showed relatively high negative contribution to the species identification.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.37-43
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• 2021

Using the acoustic features of speech, important social and linguistic information about the speaker can be obtained, and one of the key features is the dialect. A speaker's use of a dialect is a major barrier to interaction with a computer. Dialects can be distinguished at various levels such as phonemes, syllables, words, phrases, and sentences, but it is difficult to distinguish dialects by identifying them one by one. Therefore, in this paper, we propose a lightweight Korean dialect classification model using only MFCC among the features of speech data. We study the optimal method to utilize MFCC features through Korean conversational voice data, and compare the classification performance of five Korean dialects in Gyeonggi/Seoul, Gangwon, Chungcheong, Jeolla, and Gyeongsang in eight machine learning and deep learning classification models. The performance of most classification models was improved by normalizing the MFCC, and the accuracy was improved by 1.07% and F1-score by 2.04% compared to the best performance of the classification model before normalizing the MFCC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1077-1085
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• 2020

In order to Mine Countermeasure (MCM), the search is carried out for the expected mine zone. At this time, mine hunting uses Autonomous Unmanned Vehicle(AUV), taking into account the danger of mine and the stability of our forces. Sonar system for identifying buried mines are equipped with Side Scan Sonar(SSS) or Synthetic Aperture Sonar(SAS). This paper describes the analysis of mine hunting effects according to the commercial SSS characteristics. Based on the characteristics of each SSS, the insonified area and recognition probability were modeled, and the analysis was performed according to the search pattern of the AUV. AUV's search pattern defines three patterns depending on the presence or absence of SSS or shaded areas. The analysis results derived search time and detection probability for each search pattern, and finally, the improvement of search depending on the presence or absence of side injection or shaded area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.

• Journal of the Korean Society for Nondestructive Testing
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• v.16 no.3
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• pp.174-183
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• 1996

Acoustic emission(AE) response during stress corrosion cracking(SCC) of Inconel 600 alloy has been monitored to study the AE detectability of crack generation and growth by comparing the crack behavior with AE parameters processed, and to evaluate the applicability as a nondestructive evaluation(AE) by measuring the minimum crack size detectable with AE. Variously heat-treated specimens were tensioned by constant extension rate test(CERT) in various extension rate to give rise to the different SCC behavior of specimens. The AE amplitude level generated from intergranular stress-corrosion cracking(IGSCC) is higher than those from ductile fracture and mechanical deformation, which means the AE amplitude can be a significant parameter for distinguishing the An source. AE can also provide the effective means to identify the transition from the small crack initiation and formation of dominant cracks to the dominant crack growth. Minimum crack size detectable with AE is supposed to be approximately 200 to $400{\mu}m$ in length and below $100{\mu}m$ in depth. The test results show that AE technique has a capability for detecting the early stage of IGSCC growth and the potential for practical application as a NDE.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.472-482
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• 2019

This paper describes the stabilization of underwater TAS winch system Deploy/Recover operation performance. TAS winch installed on the stern of submarine performs to deploy/recover sensor, towing cable and rope tail which is deployed from the stern and separated from submarine itself. Also TAS winch provides transmission path of power to the sensor and data transmitting/receiving path which data are acquired from underwater environment like sound, depth and temperature. At the step of TAS winch evaluation test, sporadic standstill and rotating speed oscillation phenomenon were occurred. Winch motor provides the available torque to deploy/recover TAS and root cause analysis to the winch motor was done to find exact reason to sporadic malfunction. When winch motor was disassembled, eccentricity of rotor, slip-ring and the other composition part for winch motor were found. These might cause magnetic field distortion. To make TAS winch system more stable and block magnetic field distortion, this paper suggests methods to enhance fixing status installed in winch motor. For reliable data acquisition for TAS winch operation, the deploy/recover function of the improved type of TAS winch was verified in LBTS making similar condition with sea status. At the end of stage, improved type of TAS winch was tested on some functions not only deploy/recover function, but sustainability of TAS operation on specific velocity, steering angle of submarine in the sea trial. Improved type of TAS winch was verified in accordance with design requirement. Also, validity of suggested methods were verified by the sea trial.