• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.97-106
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• 2001

In this paper, we design and implement complement based speech training system for voice disorder. The system consists of three level of training: precedent training, training for speech apprehension and training for speech enhancement. To analyze speech of voice disorder, we extracted speech features as loudness, amplitude, pitch using digital signal processing technique. Extracted features are converted to graphic interface for visual feedback of speech by the system.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.19-22
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• 2021

본 논문은 군과 경찰 등에서 수행하는 시뮬레이션 사격 훈련 중 스크린 사격과 VR 사격이 혼합된 복합 훈련 환경에서 사용할 수 있는 일체형 시뮬레이션 사격 서비스에 대해 연구하였다. 이 서비스는 스크린과 HMD에 투사되는 목표물에 대해 사격 훈련이 가능하도록 설계한 서비스로 하나의 가상공간에서 사용할 경우 스크린을 이용한 개인 사격 훈련과 VR을 이용한 팀 사격 훈련이 동시에 가능하다. 일체형 시뮬레이션 총기의 총구에 비가시 적외선 레이저 모듈을 장착하여 스크린 사격이 가능하도록 하고, 총열 상단에 HTC Vive Tracker를 장착하여 VR 사격에서 훈련자의 자세 및 위치를 인식하게 한다. 총열 하단에는 사용자의 행동을 제어하는 손잡이 형태의 인터페이스 모듈을 장착한다. 비가시 적외선 레이저 모듈과 인터페이스 모듈에서 발생한 신호는 일체형 시뮬레이션 총기의 총열에 장착한 무선 통신 모듈에 의해 블루투스 방식으로 통합 제어 장치로 전달되어 처리함으로써 혼합 환경에서 사용이 가능하다. 스크린 사격과 VR 사격이 동시에 가능한 혼합 환경에서 시험한 결과 운용이 가능한 것을 확인하였다. 일체형 시뮬레이션 사격 서비스는 기존 사람 중심의 훈련 서비스에서 자동차 또는 함정 등과 같은 조종 훈련 플랫폼과 연동하여 운용할 수 있는 기술 발전이 필요하다.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.4
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• pp.295-303
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• 2016

Rehabilitation of upper limb motor function of hemiplegic patient must maintain interest and demand a device for a quantitative evaluation of rehabilitation training. In this paper, we developed the device that is composed of arm cradle, handle, and balance ball for rehabilitation exercise. We have performed experiment for validity as to whether to use the rehabilitation device when tilting the upper extremity training device developed to measure changes in the EMG signal to the main upper limb muscles for 7 healthy volunteers. We have analyzed muscle activation signals on agonist and antagonist as a reference in the muscle contraction and relaxation in the upper limb extension and flexion when the balance-handle device is tilted to front-rear and left-right. The experimental results showed that a tendency of muscle activation of biceps, triceps, and deltoid used in upper limb motor function of hemiplegic patients from extension and flexion evaluation items of Fugl-Meyer Assessment(FMA). These results may be helpful for rehabilitation training for upper limb motor function of hemiplegic patients by utilizing a developed unit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.567-573
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• 2002

In this paper, we propose a new symbol time synchronization scheme suitable for the OFDM system with an interpolator. The proposed scheme performs the following three steps. In the first step, the coarse symbol time synchronization is achieved by continuously measuring the average power of the received envelope signal. Based on this average power, the detection possibility for the symbol time synchronization is determined. It the signal is sufficient for synchronization, we next perform a relatively accurate symbol time synchronization by measuring the correlation between a short training signal and the received envelope signal. Finally, an additional frequency synchronization is performed with a long training signal to correct symbol synchronization errors caused by the phase rotation. From the simulation results, one can see that the proposed synchronization scheme provides a good synchronization performance over frequency selective channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1B
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• pp.79-89
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• 2002

A synchronization method is presented for IEEE 802.11a wireless OFDM system. First the coarse symbol synchronization is achieved by measuring the moving power average of the received envelope signal. The detection probabilities and optimum thresholds for the symbol synchronization are derived. By measuring the correlation between the short training signal and received envelope signal, fine symbol synchronization can be acquired. And the frequency synchronization is achieved using long training signal. A symbol synchronization error causes a phase rotation of the constellation. After the compensation for fading channel, the rotation due to the symbol timing error can be corrected. With this method, synchronization can be well achieved over frequency selective channels.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.1 s.6
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• pp.57-62
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• 2005

In this paper, we propose a channel estimation method by impulse signal train in OFDM. In order to estimate the channel response, 4 impulse signals are generated and transmitted during one OFDM (Orthogonal Frequency Division Multiplexing) symbol. The intervals between the impulse signals are all equal in time domain. At the receiver, the impulse response signals are summed and averaged. And then, the averaged impulse response signal is zero padded and fast Fourier transformed to obtain the channel estimation. The BER performance of the proposed method is compared with those of conventional estimation method using the long training sequence in fast fading environments. The simulation results show that the proposed method improves by 3 dB in terms of Eb/No, compared with the conventional method.

• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.191-198
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• 1999

Biofeedback training is one of physiological self control methods for patients who has psychological problem and rehabilitational problem. It has been used to control blood pressure, heart rate, peripheral temperature, respiration, electromyography (ENG), and other biological signals-ENG, respiration, heat rate, peripheral temperature, skin conductance level-was developed in house. We applied this system to alcohol dependent patients to perform biofeedback training. In this experiment, the relaxation biofeedback training for alcohol dependent patient was carried out and the tension state for the change of biological signals were estimated using the fuzzy theory after relaxation biofeenback training. Eight alcohol dependent patients were agreed to participate in this experiment. Result showed that 1) the tension degree of patients were higher than the tension degree of normal subject. 2) The tension degree of patients were decreased as the training numbers were increased.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.83-90
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• 2019

Recently, the need to prevent or treat cognitive impairment in older adults has been arising. In particular, they tried to diagnose MCI as an early stage of Alzheimer's disease and to delay the progression to dementia through training cognitive function. Most of cognitive function training have been manufactured to game contents which related to several cognitive function, and it needs to be verified quantitatively whether subjects are paying attention to cognitive function training. Thus in this study, we measured and analyzed EEG signals while performing attention training game contents. As an analysis method, we utilized CI, which shows how much they are focusing on, and RI, which shows how stable they are. The result of this study can be seen that all the subjects' CI were increased, which means that the subjects performed game contents with concentration.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.345-345
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• 2013

한미 키리졸브 훈련에 따라 북한의 GPS 전파교란에 대비하여 동해안 속초지역에 운항중인 한빛호에 고성능 GNSS 수신기와 안테나를 설치 후 전파교란을 측정(2013. 3. 14 ~ 3. 21)하여, 원시정보(GPS/GLONASS의 추적 위성수, 위성배치(DOP), 위성신호세기)를 분석한 결과 GPS/GLONASS 위성신호와 유사한 주파수 전파 간섭은 발생하지 않은 것으로 측정 되었으며, 향후 지속적 측정을 통하여 위성신호와 비슷한 주파수 대역의 전파교란 대비 필요.