• 한국전자파학회논문지
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• 제19권8호
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• pp.837-843
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• 2008

본 논문에서는 메타 재질을 이용하여 이중 대역에서 동작하는 전력 분배기를 제안하였다. 여기에서 사용된 메타 재질은 left-hand 특성을 인위적으로 캐패시터와 인덕터로 구현하고, 이것의 파라스틱 성분에 의한 Right-hand 성분이 추가된 CRLH 전송 선로로 구현하였다. 이러한 CRLH 전송 선로 특성을 이용하여 기존 Gysel이 고안한 전력 분배기와 결합하여 고 전력에서 사용이 가능하고 이중 대역에서 동작하는 전력 분배기를 제작하였다. 본 논문에서 제작한 전력 분배기는 0.88 GHz와 1.67 GHz 이중 대역에서 동작하고, 각 주파수에서 21.0 dB, 15.8 dB의 반사 계수와 3.83 dB, 3.64 dB의 삽입 손실을 확인하였다. 또한, 각 출력 포트 간의 위상차는 $3{\sim}6^{\circ}$됨을 확인하였다.

• 방송공학회논문지
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• 제18권1호
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• pp.1-9
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• 2013

모델 기반 카메라 추적에서 추적을 위해 사용되는 3차원 객체 모델의 정확도는 매우 중요하다. 하지만 3차원 객체의 실측 모델링은 일반적으로 정교한 작업을 요구할 뿐만 아니라, 오차 없이 모델링하기가 매우 어렵다. 반면에 오차를 포함하고 있는 3차원 객체 모델을 이용하더라도 모델링 오차에 의해서 계산되는 추적 오차와 실제 사용자의 육안으로 느끼는 추적 오차는 다를 수 있다. 이는 처리비용이 높은 정밀한 모델링 과정을 요구하지 않더라도 사용자가 느끼는 오차 허용 범위 내에서 추적을 위한 객체 모델링을 효과적으로 수행할 수 있기에 중요한 측면이 된다. 따라서 본 논문에서는 모델 기반 카메라 추적에서 모델링 오차에 따른 실제 정합 오차와 사용자의 육안으로 인지되는 정합 오차를 사용자 평가를 통해 비교 분석하고, 3차원 객체 모델링의 허용 오차 범위에 대해 논의한다.

• 한국멀티미디어학회논문지
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• 제21권5호
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• pp.626-637
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• 2018

Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.8-11
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• 2002

In this study, Automatic design program creates 3D solid models and constructs them. The method of making assembly model is two. One assembles the element made in automatic design program with hand, the other develops the automatic design program for creating assembly model. Automatic design program improves the convenience of user. In creating gears, involute ewe and Trochoidal fillet curve are made by mathematical development.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.208-217
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• 2021

3D-CNN is one of the deep learning techniques for learning time series data. However, these three-dimensional learning can generate many parameters, requiring high performance or having a significant impact on learning speed. We will use these 3D-CNNs to learn hand gesture and find the parameters that showed the highest accuracy, and then analyze how the accuracy of 3D-CNN varies through input data changes without any structural changes in 3D-CNN. First, choose the interval of the input data. This adjusts the ratio of the stop interval to the gesture interval. Secondly, the corresponding interframe mean value is obtained by measuring and normalizing the similarity of images through interclass 2D cross correlation analysis. This experiment demonstrates that changes in input data affect learning accuracy without structural changes in 3D-CNN. In this paper, we proposed two methods for changing input data. Experimental results show that input data can affect the accuracy of the model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1764-1769
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• 1991

Recently, dexterous mechanical hands have become of interest in the field of robotics. In this paper, a new symbolic C-Y notation is proposed for the kinematic modeling, and we solve the kinematics of a simplified model of POSTECH Hand 1, which is a 5 fingered, 20 degrees of freedom anthropomorphic hand. POSTECH Hand I is designed to have distinctive kinematic structure and the kinematic analysis of the hand is carried out using C-Y notation. To prove the feasibility of C-Y notation, D-H notation is also applied to the POSTECH Hand 1. In the inverse kinematic analysis, we neglect the fingertip geometry and assume the point contact with 3 degrees of freedom constraints. The configurations which optimize manipulability index[2] was obtained based on the simulation experiments on the SUN-4 graphic workstation using SUNPhigs graphic software.

• Journal of Computational Design and Engineering
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• 제3권3호
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• pp.286-294
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• 2016

In this paper we present an efficient technique for sketch-based 3D modeling using automatically extracted image features. Creating a 3D model often requires a drawing of irregular shapes composed of curved lines as a starting point but it is difficult to hand-draw such lines without introducing awkward bumps and edges along the lines. We propose an automatic alignment of a user's hand-drawn sketch lines to the contour lines of an image, facilitating a considerable level of ease with which the user can carelessly continue sketching while the system intelligently snaps the sketch lines to a background image contour, no longer requiring the strenuous effort and stress of trying to make a perfect line during the modeling task. This interactive technique seamlessly combines the efficiency and perception of the human user with the accuracy of computational power, applied to the domain of 3D modeling where the utmost precision of on-screen drawing has been one of the hurdles of the task hitherto considered a job requiring a highly skilled and careful manipulation by the user. We provide several examples to demonstrate the accuracy and efficiency of the method with which complex shapes were achieved easily and quickly in the interactive outline drawing task.

• The Journal of Advanced Prosthodontics
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• 제12권5호
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• pp.307-315
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• 2020

PURPOSE. The purpose of this study was to evaluate the occurrence of displacement while tightening the screw of scan bodies, which were compared according to the material type. MATERIALS AND METHODS. Three types of scan bodies whose base regions were made up of polyether ether ketone (PEEK) material [Straumann Group, Dentium Group, and Myfit (PEEK) Group] and another scan body whose base region was made up of titanium material [Myfit (Metal) Group] were used (15 per group). The reference model was fabricated by aligning the scan body library on the central axis of the implant, and moving this position by the resin model. The screws of the scan bodies were tightened to the implant fixture with torques of 5 Ncm, 10 Ncm, and a hand tightening torque. After the application of the torque, the scan bodies were scanned using a laboratory scanner. To evaluate the vertical, horizontal, and 3-dimensional (3D) displacements, a 3D inspection software program was used. To examine the difference among groups, one-way analysis of variance and Tukey's HSD post hoc test were used (α=.05). RESULTS. There were significant differences in 3D, vertical, and horizontal displacements among the different types of scan bodies (P<.001). There was a significantly lower displacement in the Straumann group than in the Myfit (PEEK) and Dentium groups (P<.05). CONCLUSION. The horizontal displacement in all groups was less than 10 ㎛. With the hand tightening torque, a high vertical displacement of over 100 ㎛ occurred in PEEK scan bodies (Myfit and Dentium). Therefore, it is recommended to apply a tightening torque of 5 Ncm instead of a hand tightening torque.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권3호
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• pp.216-220
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• 2007

Camera calibration in machine vision is the process of determining the intrinsic camera parameters and the three-dimensional (3D) position and orientation of the camera frame relative to a certain world coordinate system. On the other hand, Takagi-Sugeno-Kang (TSK) fuzzy system is a very popular fuzzy system and approximates any nonlinear function to arbitrary accuracy with only a small number of fuzzy rules. It demonstrates not only nonlinear behavior but also transparent structure. In this paper, we present a novel and simple technique for camera calibration for machine vision using TSK fuzzy model. The proposed method divides the world into some regions according to camera view and uses the clustered 3D geometric knowledge. TSK fuzzy system is employed to estimate the camera parameters by combining partial information into complete 3D information. The experiments are performed to verify the proposed camera calibration.

• Design & Manufacturing
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• 제13권2호
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• pp.6-11
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• 2019

In this study, we constructed the mathematical model to evaluate the roundness for plastic injection mold parts with complicated 3D curvatures. Mathematically we started off from the equation of circle and successfully derived an analytical solution so as to minimize the area of the residuals. On the other hand, we employed the numerical method the similar optimization process for the comparison. To verify the mathematical models, we manufactured and used a ball valve type plastic parts to apply the derived model. The plastic parts was fabricated under the process conditions of 220-ton injection mold machine with a raw material of polyester. we experimentally measured (x, y) position using 3D contact automated system and applied two mathematical methods to evaluated the accuracy of the mathematical models. We found that the analytical solution gives better accuracy of 0.4036 compared to 0.4872 of the numerical solution. The numerical method however may give adaptiveness and versatility for optional simulations such as a fixed center.