• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.7
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• pp.891-897
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• 2013

In this study, the compressive deformation behaviors of aluminum alloy under high strain rates were investigated by means of a SHPB test. An acoustic emission (AE) technique was also employed to monitor the signals detected from the deformation during the entire impact by using an AE sensor connected to the specimen with a waveguide in real time. AE signals were analyzed in terms of AE amplitude, AE energy and peak frequency. The impacted specimen surface and side area were observed after the test to identify the particular features in the AE signal corresponding to the specific types of damage mechanisms. As the strain increased, the AE amplitude and AE energy increased whereas the AE peak frequency decreased. It was elucidated that each AE signal was closely associated with the specific damage mechanism in the material.

• The Journal of the Acoustical Society of Korea
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• v.32 no.4
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• pp.287-293
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• 2013

We present a parametric array signal generating system using $3{\times}16$ transducer array which is composed of multi-resonant frequency transducers of 20kHz and 32.5kHz. To drive transducer array, sixteen channel amplifier using LM1875 chips is designed and implemented, and the PXI system based on the LabView 8.6 for arbitrary signal generation and analysis is used. Using the proposed system, we measure sound pressure level and beam pattern of difference frequency and verify the nonlinear effect of difference frequency. The theoretical absorption range and the Rayleigh distance are 15.51m and 1.933m, respectively and we verify that sound pressure of difference frequency is accumulated and increased at the near-field shorter than the Rayleigh distance. We verify that the beam pattern of the measured difference frequency and the beam pattern obtained by the superposition of two primary frequencies are similar, and high directional parametric signal was generated.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.333-340
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• 2003

Doppler processing is the heart of pulsed Doppler radar. It gives a clutter elimination and coherent integration. With the improvement of digital signal processors (DPSs), the implementation using them is more widely used in radar systems. Generally, so as for Doppler processor to process the input data in real time, a parallel processing concept using multiple DSPs should be used. This paper implements a programmable Doppler processor, which consists of MTI filter, DFB and square-law detector, using 8 ADSP21060s. Formulating the distribution time of the input data, the transfer time of the output data and the time required to compute each algorithm, it estimates total processing time and the number of required DSP. Finally, using the TSG that provides radar control pulses and simulated target signals, performances of the implemented Doppler processor are evaluated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.957-964
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• 2010

In this paper, we propose an indoor positioning algorithm based on 3 points near field angle-of-arrival estimation without side information. The conventional angle-of-arrival based positioning scheme requires the distance between the listener and the center of two points which is obtained by a received signal strength based range estimation. However, a received signal strength is affected by structure of room, placement of furniture, and characteristic of signal, these effects cause a large error to estimation of angle. In this paper, the proposed positioning scheme based on near field angle-of-arrival estimation can be used to estimate the position of listener without a prior distance information, just using time-difference-of-arrival information given from 3 points microphones. The performance of the proposed scheme is shown by cumulative distribution function of root mean squared error.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1388-1398
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• 2012

SAR(Synthetic Aperture Radar) systems can provide images of wide coverage in day, night, and all-weather conditions. However wideband SAR systems are known to be vulnerable to interferences from other devices operating at in-band or adjacent spectrums and this may lead to image corruptions. In this paper, a SAR point target simulator is developed that provides performance analysis on image distortion caused by interferences from other devices. Interference signals are generated based on the experimental data observed from acquired SAR raw data. Simulation results include typical SAR performance measures such as spatial resolution, peak to sidelobe ratio and integrated sidelobe ratio. Finally, SAR target simulations are performed and shown to correspond to the image corruptions found in real SAR missions affected by RF interferences.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.246-253
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• 2003

The initiation and growth of short fatigue cracks in the simulated aircraft structure with a series of rivet holes was detected by acoustic emission (AE). The location and the size of short tracks were determined by AE source location techniques and the measurement with traveling microscope. AE events increased intermittently with the initiation and growth of short cracks to form a stepwise increment curve of cumulative AE events. For the precise determination of AE source locations, a region-of-interest (ROI) was set around the rivet holes based on the plastic zone size in fracture mechanics. Since the signal-to-noise ratio (SNR) was very low at this early stage of fatigue cracks, the accuracy of source location was also enhanced by the wavelet transform do-noising. In practice, the majority of AE signals detected within the ROI appeared to be noise from various origins. The results showed that the effort of structural geometry and SNR should be closely taken into consideration for the accurate evaluation of fatigue damage in the structure.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.251-258
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• 2019

In the future, various products are created in various fields using artificial intelligence. In this age, it is a very important problem to know the operation principle of artificial intelligence learning method and to use it correctly. This paper introduces artificial intelligence learning methods that have been known so far. Learning of artificial intelligence is based on the fixed point iteration method of mathematics. The GD(Gradient Descent) method, which adjusts the convergence speed based on the fixed point iteration method, the Momentum method to summate the amount of gradient, and finally, the Adam method that mixed these methods. This paper describes the advantages and disadvantages of each method. In particularly, the Adam method having adaptivity controls learning ability of machine learning. And we analyze how these methods affect digital signals. The changes in the learning process of digital signals are the basis of accurate application and accurate judgment in the future work and research using artificial intelligence.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.741-747
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• 2022

Fatigue lowers an individual's ability and makes it difficult to perform work. As fatigue accumulates, concentration decreases and thus the possibility of causing a safety accident increases. Awareness of fatigue is subjective, but it is necessary to quantitatively measure the level of fatigue in the actual field. In previous studies, it was proposed to measure the level of fatigue by expert judgment by adding objective indicators such as bio-signal analysis to subjective evaluations such as multidisciplinary fatigue scales. However this method is difficult to evaluate fatigue in real time in daily life. This paper is a study on the fatigue classification model that determines the fatigue level of workers in real time using speech data recorded in the field. Machine learning models such as logistic classification, support vector machine, and random forest are trained using speech data collected in the field. The performance evaluation showed good performance with accuracy of 0.677 to 0.758, of which logistic classification showed the best performance. From the experimental results, it can be seen that it is possible to classify the fatigue level using speech signals.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.552-558
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• 2024

In dispersion management, which involves additionally inserting a dispersion compensation fiber of an appropriate length to eliminate or reduce the chromatic dispersion of a single-mode fiber, determining the form of the dispersion map, which is the cumulative dispersion profile according to the transmission distance, is the most basic and important. In this paper, the various symmetric dispersion map based on trapezoids applied to dispersion-managed links combined with mid-span spectral inversion (MSSI), which compensates for the distortion caused by Kerr nonlinear effects through optical phase conjugation in the middle of the entire transmission link are proposed, and the effect of each dispersion map on distortion compensation of wavelength division multiplexed (WDM) signals is analyzed. Although the degree of compensation varies depending on the factors that determine the detailed shape of the proposed trapezoid-shaped dispersion map and RDPS (residual dispersion per span), overall, it was confirmed that distortion compensation for signals with a small extinction ratio was more effective than distortion compensation for WDM channel signals with a large extinction ratio.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.171-174
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• 2005

본 논문에서는 인가의 인지학적인 두뇌 원리인 대뇌피질과 해마 신경망을 공학적으로 모델링하여 얼굴 영상의 특징 벡터들을 고속 학습하고, 각 영상의 최적의 특징을 구성할 수 있는 해마 학습 알고리즘(Hippocampal Learning Algorithm)을 개발하여 RFID를 이용한 생체인식 시스템을 제안한다. 입력되는 얼굴 영상 데이터들은 NMF(Non-negative Matrix Factorization)를 이용하여 특징이 구성되고, 이러한 특징들은 해마의 치아 이랑 영역에서 호감도 조정에 따라서 반응 패턴으로 이진화 되고, CA3 영역에서 자기 연상 메모리 단계를 거쳐 노이즈를 제거한다. CA3의 정보를 받는 CA1영역에서는 단층 신경망에 의해 단기기억과 장기기억으로 나누어서 저장되고 해당 특징의 누적 개수가 문턱치(threshold)를 만족하면 장기 기억 장소로 저장시키도록 한다. 위와 같은 개념을 바탕으로 구현되는 RFID 생체인식 시스템은 특징의 분별력과 학습속도면에서 우수한 성능을 보일 수 있다.