• 한국산학기술학회논문지
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• 제15권3호
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• pp.1734-1739
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• 2014

본 논문에서는 변형된 DCRLH 구조의 전송선로를 이용하여 저지대역에서 나타나는 고조파 공진 특성을 제거하고, 큰 감쇄 특성을 갖는 마이크로스트립 저역통과 필터를 설계하고 제작하였다. 저역통과 필터는 통과대역 신호를 잘 전달하고 저지대역 감쇄특성을 키우기 위한 병렬 개방스터브 선로와 고조파 통과특성을 제거하기 위한 직렬 단락스터브 선로를 복합적으로 사용하여 구성하였다. 이렇게 구성함으로써 저지대역에서 나타나는 불필요한 고조파신호를 억제시킬 수 있었고, 필터의 대역통과 성능을 개선할 수 있었다. 제작된 저역통과필터는 1.5 GHZ 이내의 통과대역에서 삽입손실 1.26 dB, 정재파비 1.65, 그리고 1.84 GHz에서 2.18 GHz의 저지대역에서 100 dB 감쇄, 20 와트 전력테스트에서 양호 평가를 얻어 모든 면에서 스펙에서 정한 규정 값 이상의 우수한 성능을 가질 수 있었다.

• 한국음향학회지
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• 제42권4호
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• pp.305-312
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• 2023

기포 크기 분포를 음파 감쇄 손실을 이용하여 역산하기 위해 Physics-Informed Neural Network(PINN)을 사용하였다. 역산에 사용되는 선형시스템을 풀기 위해 이미지 처리 분야에서 선형시스템 문제를 해결한 Adaptive Learned Iterative Shrinkage Thresholding Algorithm(Ada-LISTA)를 PINN의 신경망 구조로 이용하였다. 더 나아가, PINN의 손실함수에 선형시스템 기반의 정규항을 포함함으로써 PINN의 해가 기포 물리 법칙을 만족하여 더 높은 일반화 성능을 가지도록 하였다. 그리고 기포 추정값의 불확실성을 계산하기 위해 딥앙상블 기법을 이용하였다. 서로 다른 초기값을 갖는 20개의 Ada-LISTA는 같은 훈련데이터를 이용하여 학습되었다. 이 후 테스트시 훈련데이터와 다른 경향의 감쇄 손실을 입력으로 사용하여 기포 크기 분포를 추정하였고, 추정값과 이에 대한 불확실성을 20개 추정값의 평균과 분산으로 각각 구하였다. 그 결과 딥앙상블이 적용된 Ada-LISTA는 기존 볼록 최적화 기법인 CVX보다 기포 크기 분포를 역산하는데 더 우수한 성능을 보였다.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.2854-2863
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• 2023

Objective: To present a hybrid approach that incorporates a constrained beam-hardening estimator (CBHE) and deep learning (DL)-based post-refinement for metal artifact reduction in dental cone-beam computed tomography (CBCT). Methods: Constrained beam-hardening estimator (CBHE) is derived from a polychromatic X-ray attenuation model with respect to X-ray transmission length, which calculates associated parameters numerically. Deep-learning-based post-refinement with an artifact disentanglement network (ADN) is performed to mitigate the remaining dark shading regions around a metal. Artifact disentanglement network (ADN) supports an unsupervised learning approach, in which no paired CBCT images are required. The network consists of an encoder that separates artifacts and content and a decoder for the content. Additionally, ADN with data normalization replaces metal regions with values from bone or soft tissue regions. Finally, the metal regions obtained from the CBHE are blended into reconstructed images. The proposed approach is systematically assessed using a dental phantom with two types of metal objects for qualitative and quantitative comparisons. Results: The proposed hybrid scheme provides improved image quality in areas surrounding the metal while preserving native structures. Conclusion: This study may significantly improve the detection of areas of interest in many dentomaxillofacial applications.

• Geomechanics and Engineering
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• 제30권3호
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• pp.233-246
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• 2022

In this study, the city of Osijek is used as a case study area for low to medium seismicity regions with deep soil over deep geological deposits to determine horizontal PGA values. For this reason, we propose new regional attenuation equations for PGA that can simultaneously capture the effects of deep geology and local soil conditions. A micro-zoning map for the city of Osijek is constructed using the derived empirical scaling equations and compared to all prior seismic hazard estimates for the same area. The findings suggest that the deep soil atop deep geological sediments results in PGA values that are only 6 percent larger than those reported at rock soil sites atop geological rocks. Given the rarity of ground motion records for deep soils atop deep geological layers around the world, we believe this case study is a start toward defining more reliable PGA estimates for similar areas.

• 한국전자통신학회논문지
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• 제18권1호
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• pp.71-76
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• 2023

본 논문은 음향잡음감쇠기에서 신경망 구조의 Wiener 필터를 이용하여 비선형 잡음을 감쇠시키는 방법에 대하여 연구하였다. 이 시스템은 기존의 적응필터를 이용하는 대신 신경망 위너필터를 이용한 심층학습 알고리즘으로 비선형 잡음감쇠 성능을 개선한다. 128-neuron, 8-neuron 은닉층과 오차 역전파(back propagation) 알고리즘을 이용하여 비선형 잡음이 포함된 단일입력 음성신호로부터 음성을 추정한다. 본 연구에서 비선형 잡음에 대한 감쇠 성능을 검증하기 위하여 Keras 라이브러리를 사용한 시뮬레이션 프로그램을 작성하고 모의실험을 수행하였다. 모의실험 결과, 본 시스템은 비선형 잡음이 포함되어 있는 경우에도 위너필터 대신 FNN 필터를 사용하면 잡음감쇠 성능이 상당히 개선되는 것을 볼 수 있다. 이는 FNN 필터의 복잡한 구조가 어떤 형태의 비선형 특성도 잘 표현하기 때문이다.

• Journal of Positioning, Navigation, and Timing
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• 제10권1호
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• pp.55-66
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• 2021

In this paper, we propose a signal propagation modeling technique for generating a positioning fingerprint DB based on Long Term Evolution (LTE) signals. When a DB is created based on the location-based signal information collected in an urban area, gaps in the DB due to uncollected areas occur. The spatial interpolation method for filling the gaps has limitations. In addition, the existing gap filling technique through signal propagation modeling does not reflect the signal attenuation characteristics according to directions occurring in urban areas by considering only the signal attenuation characteristics according to distance. To solve this problem, this paper proposes a Deep Neural Network (DNN)-based signal propagation functionalization technique that considers distance and direction together. To verify the performance of this technique, an experiment was conducted in Seocho-gu, Seoul. Based on the acquired signals, signal propagation characteristics were modeled for each method, and Root Mean Squared Errors (RMSE) was calculated using the verification data to perform comparative analysis. As a result, it was shown that the proposed technique is improved by about 4.284 dBm compared to the existing signal propagation model. Through this, it can be confirmed that the DNN-based signal propagation model proposed in this paper is excellent in performance, and it is expected that the positioning performance will be improved based on the fingerprint DB generated through it.

• Ocean Systems Engineering
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• 제8권1호
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• pp.33-39
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• 2018

The paper presents a numerical underwater channel model developed in MATLAB for estimating the optical link budget between a light emitting diode (LED) based optical transmitter and a photo diode (PD) receiver when operated in the harbor, coastal and deep waters locations in the Bay of Bengal. The water samples are collected at different locations in the Bay of Bengal using a water sampler during an offshore research cruise. The optical attenuation, the main inherent parameter determining the range of the optical communication link is identified for the different waters using an underwater irradiance measurement system in the laboratory. The identified parameters are applied to the numerical model and found that a 10 W LED and a photo diode based system can provide the optical budget required for a horizontal underwater communication range of about 0.5, 14 and 35 m in the harbor, coastal and deep waters locations respectively. By increasing the transmitter power to 50 W, the operating range of the communication link could be increased up to 53 m in deep water locations in the Bay of Bengal.

• 한국해양공학회지
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• 제36권5호
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• pp.313-325
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• 2022

Recently around the world, coastal erosion is paying attention as a social issue. Various constructions using low-crested and submerged structures are being performed to deal with the problems. In addition, a prediction study was researched using machine learning techniques to determine the wave attenuation characteristics of low crested structure to develop prediction matrix for wave attenuation coefficient prediction matrix consisting of weights and biases for ease access of engineers. In this study, a deep neural network model was constructed to predict the wave height transmission rate of low crested structures using Tensor flow, an open source platform. The neural network model shows a reliable prediction performance and is expected to be applied to a wide range of practical application in the field of coastal engineering. As a result of predicting the wave height transmission coefficient of the low crested structure depends on various input variable combinations, the combination of 5 condition showed relatively high accuracy with a small number of input variables defined as 0.961. In terms of the time cost of the model, it is considered that the method using the combination 5 conditions can be a good alternative. As a result of predicting the wave transmission rate of the trained deep neural network model, MSE was 1.3×10^-3, I was 0.995, SI was 0.078, and I was 0.979, which have very good prediction accuracy. It is judged that the proposed model can be used as a design tool by engineers and scientists to predict the wave transmission coefficient behind the low crested structure.

• 한국전자통신학회논문지
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• 제18권6호
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• pp.1103-1108
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• 2023

본 논문에서는 음향신호의 배경잡음을 감쇠하기 위한 새로운 알고리즘을 제안한다. 이 알고리즘은 이산 웨이블릿 변환(DWT: Discrete Wavelet Transform) 후 기존의 적응필터를 대신 FNN(: Full-connected Neural Network) 심층학습 알고리즘을 이용하여 잡음감쇠 성능을 개선하였다. 입력신호를 단시간 구간별로 웨이블릿 변환한 다음 1024-1024-512-neuron FNN 딥러닝 모델을 이용하여 잡음이 포함된 단일입력 음성신호로부터 잡음을 제거한다. 이는 시간영역 음성신호를 잡음특성이 잘 표현되도록 시간-주파수영역으로 변환하고 변환 파라미터에 대해 순수 음성신호의 변환 파라미터를 이용한 지도학습을 통하여 잡음환경에서 효과적으로 음성을 예측한다. 본 연구에서 제안한 잡음감쇠시스템의 성능을 검증하기 위하여 Tensorflow와 Keras 라이브러리를 사용한 시뮬레이션 프로그램을 작성하고 모의실험을 수행하였다. 실험 결과, 제안한 심층학습 알고리즘을 사용하면 기존의 적응필터를 사용하는 경우보다 30%, STFT(: Short-Time Fourier Transform) 변환을 사용하는 경우보다는 20%의 평균자승오차(MSE: Mean Square Error) 개선효과를 얻을 수 있었다.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2004년도 학술대회지
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• pp.257-262
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• 2004

A series of preliminary model tests are performed to find out the wave attenuating effect of the pneumatic breakwater of environment friendly type, which is a bubble screen generated by releasing compressed air from a submerged multiple parallel manifold Rising bubbles induce vertical current, which produces horizontal currents flowing away from the bubble-screen area in both directions. Near bottom, the corresponding currents flow toward the bubble screen, thus completing the circulation pattern. The surface current moving against the direction of wave propagation causes some attenuation of the waves. It becomes more effective as the relative depth (d/ L) increases (short-period waves in deep water). With the same air-discharge, the multiple parallel manifold can be more effective for the attenuation of longer waves through optimum arrangement of manifold number. installation depth, manifold gap, etc. The pneumatic breakwater will give a wide utilization as a device for protecting harbor facilities and as a simple, mobile breakwater.