• Structural Engineering and Mechanics
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• 제3권4호
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• pp.359-372
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• 1995

This study presents an efficient method for optimum design of plate and shell structures, when the design variables are continuous or discrete. Both sizing and shape design variables are considered. First the structural responses such as element forces are approximated in terms of some intermediate variables. By substituting these approximate relations into the original design problem, an explicit nonlinear approximate design task with high quality approximation is achieved. This problem with continuous variables, can be solved by means of numerical optimization techniques very efficiently, the results of which are then used for discrete variable optimization. Now, the approximate problem is converted into a sequence of second level approximation problems of separable form and each of which is solved by a dual strategy with discrete design variables. The approach is efficient in terms of the number of required structural analyses, as well as the overall computational cost of optimization. Examples are offered and compared with other methods to demonstrate the features of the proposed method.

• 드라이브 ㆍ 컨트롤
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• 제15권3호
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• pp.29-35
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• 2018

This paper presents the design of attachments for dual arms of disaster responding heavy machine. The heavy machine handles a variety of tasks such as cutting, shredding, picking and moving in unstructured environment. Despite the need for rapid response, the heavy machine has difficulty in repeatedly replacing the attachment depending on the task. Thus, we propose a method to solve this physical and functional contradiction relation by using TRIZ separation principles. Above all, the existing equipment and the required working scenarios were surveyed and summarized in order to separate the attachments functionally for right-handed, left-handed and two-handed operation. Then, we proposed the design directions and conceptual design as following: multi function type attachment A, for precise operation and various operations; grab type attachment B, for grasping irregular objects and auxiliary device for both arms to handle bulky objects.

• 대한의용생체공학회:의공학회지
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• 제27권6호
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• pp.323-331
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• 2006

The purpose of this study was to investigate the effect of performing a cognitive task during treadmill walking on the stride rate variability. Ten university students(age $24.0{\pm}0.25$, height $172{\pm}3.1cm$, weight $66{\pm}5.3kg$) were participated in dual task experiments which consist of both walking alone and walking with a cognitive task. Two-back task was selected for the cognitive task since it did not have learning effect during the experimental procedure.3D motion analysis system was used to measure subject's position data by changing walking speed with 4.8, 5.6, 6.4, 6.8, and 7.2 km/hr. Stride rate was calculated by the time between heel contact and heel contact. Accuracy rate of a cognitive task during walking, coefficient of variance, allometric scaling methods and Fano factor were used to estimated the stride rate variability. As the walking speed increased, accuracy rate decreased and the logarithmic value of Fano factor increased which showed the statistical difference. Thus it can be concluded that the gait control mechanism is distracted by the secondary attention focus which is the cognitive task ie. two-back task. Further study is needed to clarify this by increasing the number of subject and experiment time.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 1999년도 춘계학술발표논문집 논문집
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• pp.35-38
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• 1999

• 로봇학회논문지
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• 제2권2호
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• pp.129-136
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• 2007

This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.

• 대한전기학회논문지:전력기술부문A
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• 제48권4호
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• pp.452-460
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• 1999

Sawing experiments using a two-arm system have been performed in this work. The two-arm system under consideration of two kinematically-nonidentical arms. A passive joint is inserted at the end-point of one robot in order to increase the mobility up to the motion degree required for sawing tasks. A hybrid control algorithm for control of the two-arm system is designed. We experimentally show that the performance of the velocity and force response are satisfactory, and that one additional passive joint not only prevents the system from unwanted yaw motion in the sawing task, but also allows an unwanted pitch motion to be notably reduced by an internal load control. To show the general applicability of the proposed algorithms, we perform experimentation under several different conditions for saw, such as three saw blades, two sawing speeds, and two vertical forces.

• Journal of Advanced Research in Ocean Engineering
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• 제3권3호
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

• Journal of Communications and Networks
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• 제7권1호
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• pp.76-86
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• 2005

Today's wireless access networks consist of several tiers that overlap each other. Provisioning of real time undisrupted communication to mobile users, anywhere and anytime through these heterogeneous overlay networks, is a challenging task. We extend the end-to-end approach for the handoff management in hybrid wireless data network by designing a fully mobile-controlled handoff for mobile devices equipped with dual mode interfaces. By handoff, we mean switching the communication between interfaces connected to different subnets. This mobile-controlled handoff scheme reduces the service disruption time during both horizontal and vertical handoffs and does not require any modification in the access networks. We exploit the IP diversity created by the dual interfaces in the overlapping area by simultaneously connecting to different subnets and networks. Power saving is achieved by activating both interfaces only during the handoff period. The performance evaluation of the handoff is carried out by a simple mathematical analysis. The analysis shows that with proper network engineering, exploiting the speed of mobile node and overlapping area between subnets can reduce service disruption and power consumption during handoff significantly. We believe that with more powerful network interfaces our proposal of dual interfaces can be realized.

• 한국컴퓨터정보학회논문지
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• 제29권6호
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• pp.1-12
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• 2024

최근 다양한 분야에서 딥러닝이 사용되면서, 더 빠르고 정확한 결과를 내는 딥러닝이 더욱 중요해졌다. 이를 위해서는 많은 양의 저장 공간이 필요하고, 대용량 연산을 진행해야 한다. 이에 따라 여러 연구는 빠르고 정확하게 연산 처리가 가능한 하드웨어 가속기를 이용한다. 하지만 하드웨어 가속기는 CPU와 하드웨어 사이를 이동하면서 병목현상이 발생하게 된다. 따라서 본 논문에서는 하드웨어 가속기의 병목현상을 효율적으로 줄일 수 있는 데이터 프리패치 전략을 제안한다. 데이터 프리패치 전략의 핵심 아이디어는 Matrix Multiplication Unit(MMU)가 연산을 진행하는 동안 다음 연산에 필요한 데이터를 예측하여 로컬 메모리로 올려 병목현상을 줄인다. 또한, 이 전략은 듀얼 버퍼를 이용하여 읽고 쓰는 두 가지 동작을 동시에 진행하여 처리율을 높인다. 이를 통해 데이터 전송의 지연시간 및 실행 시간을 감소시킨다. 시뮬레이션을 통해 듀얼 버퍼를 이용한 병렬 프로세싱과 데이터 프리패치를 이용한 메모리 간 병목현상을 최대한 감소시켜 하드웨어 가속기의 성능이 24% 향상함을 알 수 있다.

• 한국통신학회논문지
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• 제27권1C호
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• pp.103-111
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• 2002

IMT-2000에서 RNC의 Main Control Processor는 호 처리를 담당하는 부분으로, 고신뢰도와 실시간성이 요구되므로 결함 허용 시스템의 연구가 중요하다. 이를 위하여 본 연구에서는 태스크 기반 이중화 방안을 제안한다. 이 방안은 Active side의 태스크들이 메시지 단위로 동작하고, 동작 후 변경된 메모리 영역의 데이터를 Standby side에 전달하는 방식을 기본으로 하며, 절체 시 recovery를 위해 메시지를 logging하는 방식이다. 제안한 방식은 dual down 및 동기화 과정의 복잡성을 제거 할 뿐만 아니라, 태스크가 동기를 제어하므로 좀 더 정확한 동기화가 가능하다. 또한 효과적으로 태스크 기반 이중화를 수행하기 위한 결함 탐지 및 처리 방안을 제시한다. 이 방안은 결함 탐지 확률을 높이고 결함에 의하여 발생한 오류 데이터가 Standby side로 전송되는 것을 원천적으로 차단하는 것에 중점을 둔다.