• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.311-314
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• 2007

Aerodynamic characteristics of an insect-type flapping wings were carried out to obtain the design parameters of Micro Hovering Air Vehicle. A pair of wing model was scaled up about 200 times and applied two pairs of 4-bar linkage mechanism to mimic the wing motion of a fruit fly(Drosophila). To verify the Weis-Fogh mechanism, a pair of wings revolved on the 'Delayed Rotation'. Lift and drag were measured in conditions of the Reynolds number based on wing tip velocity of about 1,200 and the maximum angle of attack of 40$40^{\circ}$. Inertia forces of a wing model were also measured by using a 99.98% vacuum chamber and subtracted on measured data in air. In the present study, high lift effect of Weis-Fogh mechanism was appeared in the middle of upstroke motion.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.56-64
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• 2006

This paper presents the development and application of a conducting shape memory polyurethane (CSMPU) actuator. While conventional shape memory polyurethanes were activated by external heat source, conducting shape memory polyurethanes introduced in 2004 are activated by electric power. Conducting shape memory polyurethane actuators were manufactured by adding carbon nano tube to conventional shape memory polyurethane. The main problem of the CSMPU developed in 2004 was bad dispersion of carbon nano tubes. In this paper, we tried to find how to solve the dispersion problem, and with a lot of elaborative works, conducting shape memory polyurethane actuators which had better electrical characteristics were developed. Then the actuation performance of the conducting shape memory polyurethane actuators was also measured and assessed. Finally, the possibility of applications were examined through the installation to Micro Air Vehicle.

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.242-249
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• 2019

Forearm electromyography (EMG) generated by wrist movements has been widely used to develop an electrical prosthetic hand, but EMG generated by finger movements has been rarely used even though 20% of amputees lose fingers. The goal of this study is to improve the classification performance of different finger movements using a deep learning algorithm, and thereby contributing to the development of a high-performance finger-based prosthetic hand. Ten participants took part in this study, and they performed seven different finger movements forty times each (thumb, index, middle, ring, little, fist and rest) during which EMG was measured from the back of the right hand using four bipolar electrodes. We extracted mean absolute value (MAV), root mean square (RMS), and mean (MEAN) from the measured EMGs for each trial as features, and a 5x5-fold cross-validation was performed to estimate the classification performance of seven different finger movements. A long short-term memory (LSTM) model was used as a classifier, and linear discriminant analysis (LDA) that is a widely used classifier in previous studies was also used for comparison. The best performance of the LSTM model (sensitivity: 91.46 ± 6.72%; specificity: 91.27 ± 4.18%; accuracy: 91.26 ± 4.09%) significantly outperformed that of LDA (sensitivity: 84.55 ± 9.61%; specificity: 84.02 ± 6.00%; accuracy: 84.00 ± 5.87%). Our result demonstrates the feasibility of a deep learning algorithm (LSTM) to improve the performance of classifying different finger movements using EMG.

• Structural Engineering and Mechanics
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• v.72 no.4
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• pp.421-432
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• 2019

In high-speed railway (HSR) system, the structure-borne noise inside viaduct at low frequency has been extensively investigated for its mitigation as a research hotspot owing to its harm to the nearby residents. This study proposed a novel acoustic optimization method for declining the structure-borne noise in viaduct-like structures by separating the acoustic contribution of each structural component in the measured acoustic field. The structural vibration and related acoustic sourcing, propagation, and radiation characteristics for the viaduct box girder under passing vehicle loading are studied by incorporating Finite Element Method (FEM) with Modal Acoustic Vector (MAV) analysis. Based on the Modal Acoustic Transfer Vector (MATV), the structural vibration mode that contributes maximum to the structure-borne noise shall be hereinafter filtered for the acoustic radiation. With vibration mode shapes, the locations of maximum amplitudes for being ribbed to mitigate the structure-borne noise are then obtained, and the structure-borne noise mitigation performance shall be eventually analyzed regarding to the ribbing conduction. The results demonstrate that the structural vibration and structure-borne noise of the viaduct box girder mainly occupy both in the range within 100 Hz, and the dominant frequency bands both are [31.5, 80] Hz. The peak frequency for the structure-borne noise of the viaduct box girder is mainly caused by $16^{th}$ and $62^{th}$ vibration modes; these two mode shapes mainly reflect the local vibration of the wing plate and top plate. By introducing web plate at the maximum amplitude of main mode shapes that contribute most to the acoustic modal contribution factors, the acoustic pressure peaks at the field-testing points are hereinafter obviously declined, this implies that the structure-borne noise mitigation performance is relatively promising for the viaduct.

• Microbiology and Biotechnology Letters
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• v.46 no.4
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• pp.320-325
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• 2018

Hepatitis E virus (HEV) infection accounts for 20 million annual infections worldwide. HEV can be fatal in approximately 20-30% of pregnant women. HEV infections are normally self-limiting and mostly asymptomatic. However, in patients with insufficient immunity, such as acquired immunodeficiency syndrome patients, chronic and often fatal infections may ensue. Therefore, it is likely that host immune responses, especially interferon responses, play a critical role in HEV infection control. Here, we report that an HEV-encoded non-structural protein down-regulates type I interferon response. In addition, some other immune genes involved in the induction of type I interferon may be regulated as well. Detailed molecular mechanisms are currently being studied.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.3
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• pp.185-195
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• 2021

The flapping-wing micro air vehicle (FW-MAV) in this study utilizes the cambered wings made of quite flexible material. Similar to the flying creatures, the present cambered wing uses three different materials at its leading edge, vein, and membrane. And it is constrained in various conditions. Since passive rotation uses the flexible nature of the wing, it is important to select an appropriate material for a wing. A three-dimensional fluid-structure interaction solver is developed for a realistic modeling of the cambered wing. Then a parametric study is conducted to evaluate the aerodynamic performance in terms of the elastic modulus of leading edge and vein. Consequently, the elastic modulus plays a key role in enhancing the aerodynamic performance of FW-MAVs.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.105-119
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• 2003

일반적인 로봇시스템은 자신이 이동해야 할 목표 지점을 자율적으로 생성할 수 없으므로 어떤 다른 시스템의 정보를 이용하여 주변을 탐색하거나 장애물을 인식하고 식별하여 자신의 제어전략을 수립한다. 그러므로 본 논문에서 제시한 시스템은 초소형 비행체를 이용하여 주위 환경과 자율 이동로봇의 위치 정보를 탐색할 수 있도록 시스템을 구성하였다 이러한 시스템의 성능은 로봇이 위치하고 있는 주위의 불완전한 정보로부터 적절한 결론을 유도해 낼 수 있어야 한다. 그러한 비선형적인 문제는 현재까지도 문제 해결을 위해 많은 연구가 진행되고 있다. 본 연구에서는 자율이동로봇의 행동 환경을 공간상의 제약을 받지 않는 비선형 시스템인 초소형 비행체에 극초단파(UHF16채널) 영상장치를 이용하여 호스트 PC로 전송하고 호스트 PC는 로봇의 현재 위치, 이동해야 할 목표위치, 장애물의 위치와 형태 등을 분석한다. 분석된 결과 파라메타는 RF-Module을 이용해서 로봇에 전송하고, 로봇은 그 데이터를 분석하여 동작하게 된다. 로봇이 오동작 또는 장애물로 인해 정확한 목적지까지 도달하지 못할 때 호스트 PC는 새로운 최단경로를 생성하거나 장애물을 회피 할 새로운 전략을 로봇에게 보내준다. 본 연구에 적용한 알고리즘은 초소형 비행체에서 탐지한 불완전한 영상정보에서도 비교적 신뢰도 놀은 결과를 보이는 A* 알고리즘을 사용하였다 적용한 알고리즘은 실험을 통하여 실시간으로 정보를 처리할 수 있었으며, 자율 이동로봇의 충돌회피나 최단 경로 생성과 같은 문제를 실험을 통하여 그 성능과 타당성을 검토하였다.delta}textitH]$를 도출하였다.rc}C$에서 30 ㎫의 압력으로 1시간동안 행하였다 소결한 시편들은 직사각형 형태로 가공하였으며 표면은 0.5$\mu\textrm{m}$의 다이아몬드 입자로 연마하였다. XRD, SEM 및 TEM을 이용하여 상분석 및 미세조직관찰을 행하였다. 파괴강도는 3중점 굽힘 법으로 (3-point bending test) 측정하였다. 이때 시편 하부의 지지 점간의 거리는 30mm, cross-head 속도는 0.5 mm/min으로 하였고 5개의 시편을 측정하여 평균값을 구하였다.ell/\textrm{cm}^3$, 혼합재료 3은 0.123$\ell/\textrm{cm}^3$, 0.017$\ell/\textrm{cm}^3$, 혼합재료 4는 0.055$\ell/\textrm{cm}^3$, 0.016$\ell/\textrm{cm}^3$, 혼합재료 5는 0.031$\ell/\textrm{cm}^3$, 0.015$\ell/\textrm{cm}^3$, 혼합재료 6은 0.111$\ell/\textrm{cm}^3$, 0.020$\ell/\textrm{cm}^3$로 나타났다. 3. 단일재료의 악취흡착성능 실험결과 암모니아는 코코넛, 소나무수피, 왕겨에서 흡착능력이 우수하게 나타났으며, 황화수소는 펄라이트, 왕겨, 소나무수피에서 다른 재료에 비하여 상대적으로

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.