• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.998-1013
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• 2013

Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

• 전자공학회논문지CI
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• 제44권1호
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• pp.94-101
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• 2007

스트리밍 비디오 서비스는 최근 이종망으로 구성되는 무선망에서 중요한 어플리케이션으로 자리잡을 것으로 예상된다. 그러나 군집성있는 패킷 손실에 의해서 서비스의 충분한 품질이 보장되지 않는다. 무선망에서 패킷 손실에 대한 효율적인 해결책은 수신단에서 적절한 에러 은닉 기술을 사용하는 방법일 것이다. 그러나 대부분의 에러 은닉 기술은 손실 블록에 인접한 이웃 블록들이 군집성 패킷 손실에 의해 이미 손실되었기 때문에 효율적으로 손실된 블록열들을 복원하기 어렵다. 이를 해결하기 위해 손실된 MB에서의 움직임 선형 특성을 이용하는 bidirectional motion vector tracking (BMVT)가 이전에 제안되었었다. 본 논문에서는 BMVT 에러 은닉 기술을 향상시킨 채널 적응형 잉여 코딩 방식이 소개되어진다.

• 한국항행학회논문지
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• 제14권2호
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• pp.206-212
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• 2010

본 논문에서는 유비쿼터스 환경에서 로봇의 응용서비스를 제공하는데 필요한 네트워크로서 로보틱 지그비 네트워크의 개념을 소개하고 이를 이용한 응용 시나리오를 제시한다. 제시한 응용시나리오의 기본이 되는 네트워크 연결 및 데이터 전송에 관한 실험을 수행하였다. 이 실험 결과를 통해 앞으로 Robotic Zigbee Network를 이용한 위치인식 오차율을 최소화하는 로봇의 위치추정 및 추적 알고리즘 개발의 기반을 마련한다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1996년도 추계학술대회 논문집
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• pp.225-229
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• 1996

In this study, in order to develop outdoor insulating materials, SIN(simultaneous interpenetrating polymer network) was introduced to Epoxy resin and the environment resistance was investigated. The single network structure specimen(E series) formed of Epoxy resin alone and simultaneous interpenetrating polymer network specimen (EM series) in which epoxy resin was taken as the first network and methyl methacrylate resin as the second network were manufactured. Ten kinds of specimens were manufacture by filler (SiO$_2$) content. SEM were utilized in order to confirm their network structure changes, and AC voltage dielectric strength was measured. Also, UV-test and tracking test were carried out investigate the environment resistance characteristic. Therefore the variations of network structure were happened as a result of SEM test, and it was confirmed that simultaneous interpenetrating polymer network specimens were more excellent than single network structure specimens.

• 한국항행학회논문지
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• 제26권6호
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• pp.522-527
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• 2022

객체추적은 이전시간에서 추정한 위치와 현재 관측 데이터를 바탕으로 객체의 위치를 연속적으로 추적하는 신호처리 분야이다. 이 논문에서는 3개의 RNN을 서브모듈로 가지는 적응형 스케일조절 신경망을 이용해 입력 데이터의 스케일을 스스로 조절하여 추적할 수 있는 신경망을 제안한다. 객체 추적 성능을 평가하기 위해 객체가 조각별 등가속운동을 하는 1차원 객체 운동 모델에서 제안하는 시스템, 칼만 필터와 최대우도기법의 추적 성능을 비교한다. 그 결과 제안하는 알고리듬의 성능이 평균제곱근오차 기준으로 최대우도기법과 칼만필터보다 다양한 상황에서 전반적으로 우수하며 관측잡음이 커질수록 성능격차가 더 커지는 것을 보인다.

• 한국멀티미디어학회논문지
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• 제20권7호
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• pp.986-993
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• 2017

Object Tracking is a technique for tracking moving objects over time in a video image. Using object tracking technique, many research are conducted such a detecting dangerous situation and recognizing the movement of nearby objects in a smart car. However, it still remains a challenging task such as occlusion, deformation, background clutter, illumination variation, etc. In this paper, we propose a novel deep visual object tracking method that can be operated in robust to many challenging task. For the robust visual object tracking, we proposed a Convolutional Neural Network(CNN) which shares weight of the convolutional layers. Input of the CNN is a three; first frame object image, object image in a previous frame, and current search frame containing the object movement. Also we propose a method to consider the motion of the object when determining the current search area to search for the location of the object. Extensive experimental results on a authorized resource database showed that the proposed method outperformed than the conventional methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.641-643
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• 2000

CATV Network Management system of Korea is used for mainly monitor forward broadcasting signal because of the difficulty of tracking, measuring and control reverse path nosie. Thereby Purpose of this Structure is removing return Path noise of CATV Network for maintaining two way Netowrk Service of the Highest quality.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.85-88
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• 2000

In this paper, the ultra precision positioning system for piezoelectric actuator using hysteresis compensation has been developed. Piezoelectric actuators exhibit limited accuracy in tracking control due to their hysteresis nonlinearity. The main purpose of the proposed controller is to compensate the hysteresis nonlinearity of the piezoelectric actuator. The controller is composed of a PD, hysteresis compensation and neural network part in parallel manner, at first, the excellent tracking performance of the neural network controller was verified by experiments and was compared with the classical PD controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권4호
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• pp.294-300
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• 2009

The neural network with radial basis function is introduced for position tracking control of AC servo drive with the existence of system uncertainties. An adaptive robust term is applied to overcome the external disturbances. The proposed controller is implemented on a high performance digital signal processing DSP TMS320C6713-300. The stability and the convergence of the system are proved by Lyapunov theory. The validity and robustness of the controller are verified through simulation and experimental results

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.