• 수산해양기술연구
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• 제55권2호
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• pp.129-137
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• 2019

This study was conducted to investigate the effects of underwater noise caused by pile driving during marine construction on fish. In this study, the three gray rockfish were released about 1 km away from the construction site of wind power generation on July 18, 2018 and traced using two acoustic telemetry techniques. The behavior of the fish was analyzed by calculating the moving distance, swimming speed and direction of the gray rockfish. In the results of the acoustic tracking using the ship, the rockfish moved about 2.11 km for about two hours at a speed of $0.28{\pm}0.14m/s$ (0.94 TL/s). The bottom depth of the trajectory of the rockfish was $1.0{\pm}0.6m$ on average. There was a significant directionality in swimming direction of the gray rockfish, and there was no significant correlation between the swimming direction and tidal current direction. Moving distance during 5 minutes (5MD) during pile driving and finishing operations between rock surface and bedrock were 0.94-0.96 times (76.0-77.0 m) and 1.81-2.73 times (146.0-219.5 m), respectively, compared with no pile driving. This study is expected to be used as a basic data of fish behavior research on underwater noise.

• 한국정보통신학회논문지
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• 제23권12호
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• pp.1492-1499
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• 2019

이 논문에서는 적응적 패럴랙스 베리어 방식에서, 시청영역을 제어할 수 있도록 사용자의 위치를 추적하는 방법을 제안한다. 얼굴자세에 강건한 양안거리 측정을 위해, 형태모델과 랜드마크 기반인 CLM으로 자세를 추정한다. 카메라와의 상관관계로, 거리와 수평위치를 거리로 변환한다. 사용자의 눈의 위치에 따라 적응적 패럴랙스 베리어의 화소간격을 조정하고, 베리어를 이동해 시청영역을 조정한다. 이 논문에서는 60cm부터 490cm의 범위에서 사용자를 추적하는 방법을 제안하고, 카메라 영상의 해상도에 따른 에러, 측정 가능 범위, fps를 측정하였다. 그 결과, 사용자를 평균 3.1642cm의 절대오차 범위내로 측정 가능하였으며, 영상의 해상도에 따라 320×240에서 약 278cm, 640×480에서 약 488cm까지, 그리고 1280×960에서 약 493cm까지를 측정할 수 있었다.

• 한국음향학회지
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• 제41권1호
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• pp.16-29
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• 2022

본 논문에서는 수중통신 장치가 수중에서 이동시 발생하는 도플러(Doppler) 편이를 극복하기 위한 도플러 편이 추정방법과 직접수열 확산대역 전송의 신호처리 방법을 제시한다. 제안한 방법은 도플러 편이에 강인하고, 자기 상관 특성이 우수한 64길이의 Frank 신호열을 두 번 반복하는 프리앰블을 사용하여 2단계로 도플러 편이를 추정한다. 또한, 제안한 방법을 직접수열 대역확산 전송을 사용하는 수중통신방식에 적용하여 수중이동통신용 패킷 설계와 RAKE 수신기를 설계한다. 설계한 확산대역 수중이동통신 변조방식은 데이터 심볼을 Differential-Quadrature Phase Shift Keying(DQPSK) 변조하여 수신시 위상추적이 필요 없고, RAKE 수신기에서 동위상 결합이 용이하게 할 수 있는 장점이 있다. 제안한 도플러 편이 추정방법을 포함하는 RAKE 수신방법은 약 17.5 m/s의 이동속도까지 가상으로 이동하는 송신기로부터 수신한 직접수열 대역 확산 신호를 성공적으로 수신한다.

• 대한청각학회지
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• 제25권3호
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• pp.131-137
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• 2021

Background and Objectives: The current study investigates pitch coding using frequency following response (FFR) among vocalists, violinists, and non-musicians for Indian Carnatic transition music stimuli and assesses whether their listening biographies strengthen their F0 neural encoding for these stimuli. Subjects and Methods: Three participant groups in the age range of 18-45 years were included in the study. The first group of participants consisted of 20 trained Carnatic vocalists, the second group consisted of 13 trained violinists, and the third group consisted of 22 non-musicians. The stimuli consisted of three Indian Carnatic raga notes (/S-R2-G3/), which was sung by a trained vocalist and played by a trained violinist. For the purposes of this study, the two transitions between the notes T1=/S-R2/ and T2=/R2-G3/ were analyzed, and FFRs were recorded binaurally at 80 dB SPL using neuroscan equipment. Results: Overall average responses of the participants were generated. To assess the participants' pitch tracking to the Carnatic music stimuli, stimulus to response correlation (CC), pitch strength (PS), and pitch error (PE) were measured. Results revealed that both the vocalists and violinists had better CC and PS values with lower PE values, as compared to non-musicians, for both vocal and violin T1 and T2 transition stimuli. Between the musician groups, the vocalists were found to perform superiorly to the violinists for both vocal and violin T1 and T2 transition stimuli. Conclusions: Listening biographies strengthened F0 neural coding, with respect to the vocalists for vocal stimulus at the brainstem level. The violinists, on the other hand, did not show such preference.

• Journal of Audiology & Otology
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• 제25권3호
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• pp.131-137
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• 2021

Background and Objectives: The current study investigates pitch coding using frequency following response (FFR) among vocalists, violinists, and non-musicians for Indian Carnatic transition music stimuli and assesses whether their listening biographies strengthen their F0 neural encoding for these stimuli. Subjects and Methods: Three participant groups in the age range of 18-45 years were included in the study. The first group of participants consisted of 20 trained Carnatic vocalists, the second group consisted of 13 trained violinists, and the third group consisted of 22 non-musicians. The stimuli consisted of three Indian Carnatic raga notes (/S-R2-G3/), which was sung by a trained vocalist and played by a trained violinist. For the purposes of this study, the two transitions between the notes T1=/S-R2/ and T2=/R2-G3/ were analyzed, and FFRs were recorded binaurally at 80 dB SPL using neuroscan equipment. Results: Overall average responses of the participants were generated. To assess the participants' pitch tracking to the Carnatic music stimuli, stimulus to response correlation (CC), pitch strength (PS), and pitch error (PE) were measured. Results revealed that both the vocalists and violinists had better CC and PS values with lower PE values, as compared to non-musicians, for both vocal and violin T1 and T2 transition stimuli. Between the musician groups, the vocalists were found to perform superiorly to the violinists for both vocal and violin T1 and T2 transition stimuli. Conclusions: Listening biographies strengthened F0 neural coding, with respect to the vocalists for vocal stimulus at the brainstem level. The violinists, on the other hand, did not show such preference.

• Smart Structures and Systems
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• 제31권4호
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• pp.393-407
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• 2023

To assess structural condition in a non-destructive manner, computer vision-based structural health monitoring (SHM) has become a focus. Compared to traditional contact-type sensors, the advantages of computer vision-based measurement systems include lower installation costs and broader measurement areas. In this study, we propose a novel computer vision-based vibration measurement and coarse-to-fine damage assessment method for truss bridges. First, a deep learning model FairMOT is introduced to track the regions of interest (ROIs) that include joints to enhance the automation performance compared with traditional target tracking algorithms. To calculate the displacement of the tracked ROIs accurately, a normalized cross-correlation method is adopted to fine-tune the offset, while the Harris corner matching is utilized to correct the vibration displacement errors caused by the non-parallel between the truss plane and the image plane. Then, based on the advantages of the stochastic damage locating vector (SDLV) and Bayesian inference-based stochastic model updating (BI-SMU), they are combined to achieve the coarse-to-fine localization of the truss bridge's damaged elements. Finally, the severity quantification of the damaged components is performed by the BI-SMU. The experiment results show that the proposed method can accurately recognize the vibration displacement and evaluate the structural damage.

• 대한의용생체공학회:의공학회지
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• 제44권4호
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• pp.255-263
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• 2023

Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.

• Journal of Animal Science and Technology
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• 제65권3호
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• pp.519-534
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• 2023

Rumination in cattle is closely related to their health, which makes the automatic monitoring of rumination an important part of smart pasture operations. However, manual monitoring of cattle rumination is laborious and wearable sensors are often harmful to animals. Thus, we propose a computer vision-based method to automatically identify multi-object cattle rumination, and to calculate the rumination time and number of chews for each cow. The heads of the cattle in the video were initially tracked with a multi-object tracking algorithm, which combined the You Only Look Once (YOLO) algorithm with the kernelized correlation filter (KCF). Images of the head of each cow were saved at a fixed size, and numbered. Then, a rumination recognition algorithm was constructed with parameters obtained using the frame difference method, and rumination time and number of chews were calculated. The rumination recognition algorithm was used to analyze the head image of each cow to automatically detect multi-object cattle rumination. To verify the feasibility of this method, the algorithm was tested on multi-object cattle rumination videos, and the results were compared with the results produced by human observation. The experimental results showed that the average error in rumination time was 5.902% and the average error in the number of chews was 8.126%. The rumination identification and calculation of rumination information only need to be performed by computers automatically with no manual intervention. It could provide a new contactless rumination identification method for multi-cattle, which provided technical support for smart pasture.

• Journal of Cardiovascular Imaging
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• 제31권2호
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• pp.98-104
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• 2023

BACKGROUND: We aimed to investigate left ventricular (LV) global longitudinal strain (GLS) in end-stage renal disease patients and its change after kidney transplantation (KT). METHODS: We retrospectively reviewed patients who underwent KT between 2007 and 2018 at two tertiary centers. We analyzed 488 patients (median age, 53 years; 58% male) who had obtained echocardiography both before and within 3 years after KT. Conventional echocardiography and LV GLS assessed by two-dimensional speckle-tracking echocardiography were comprehensively analyzed. Patients were classified into three groups according to the absolute value of pre-KT LV GLS (|LV GLS|). We compared longitudinal changes of cardiac structure and function according to pre-KT |LV GLS|. RESULTS: Correlation between pre-KT LV EF and |LV GLS| were statistically significant, but the constant was not high (r = 0.292, p < 0.001). |LV GLS| was widely distributed at corresponding LV EF, especially when the LV EF was > 50%. Patients with severely impaired pre-KT |LV GLS| had significantly larger LV dimension, LV mass index, left atrial volume index, and E/e' and lower LV EF, compared to mildly and moderately reduced pre-KT |LV GLS|. After KT, the LV EF, LV mass index, and |LV GLS| were significantly improved in three groups. Patients with severely impaired pre-KT |LV GLS| showed the most prominent improvement of LV EF and |LV GLS| after KT, compared to other groups. CONCLUSIONS: Improvements in LV structure and function after KT were observed in patients throughout the full spectrum of pre-KT |LV GLS|.

• 한국환경생태학회지
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• 제28권2호
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• pp.253-262
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• 2014

본 연구는 식생경관의 생태학적 해석을 통한 질적 경관평가방법의 모색을 위해 설악산국립공원을 대상으로 생태계 형성위계에 따른 우수 경관자원을 추출한 후 추출된 자원의 시각적 노출량과 탐방객의 탐방로 선호도와의 관계성을 분석하였다. 설악산국립공원을 대상으로 생태학적 해석을 통해 선정한 우수경관 요소로는 아고산식생대와 고지대 바위군, 계곡 낙엽활엽수림, 암반지역 소나무 토지극상, 대경목군락지, 화목류 및 단풍류 우점군락지, 아고산대 침엽수 군락지이다. 연구 결과 탐방로 선호도와 상관성이 있는 우수 경관자원으로는 대경목군락지의 면적, 화목류 우점군락의 면적, 아고산 침엽수군락의 면적이 탐방로의 선호도에 긍정적 영향을 주는 것으로 나타났다. 본 연구에서는 탐방로의 가시권과 우수 경관자원의 분석을 통해 자연지역에서의 일반적 탐방로의 소개에서 나아가 경관자원의 가시성을 바탕으로 특정 탐방로의 특정 탐방시기를 제시할 수 있음을 확인하였다. 일부 경관자원의 가시성이 탐방로 선호에 긍정적 역할을 하고 있었는데 자연환경에서 복잡한 경관요소의 종합적인 가시권 면적보다는 특정 경관의 가시권 면적이 탐방로 선호도에 영향을 주며 단순히 자연지역의 넓은 면적이 시야에 들어오는 지역을 선호하지는 않는 것으로 나타났다.