• Smart Media Journal
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• v.8 no.4
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• pp.53-57
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• 2019

In this paper, we propose a flex sensor-based data glove to track the movements of human fingers for virtual reality education. By putting flex sensors and utilizing an accelerometer, this data glove allows people to enjoy applications for virtual reality (VR) or augmented reality (AR). With the maximum and minimum values of the flex sensor at each finger joint, it determines an angle corresponding to the bending value of the flex sensor. It tracks the movements of fingers and hand gestures with respect to the angle values at finger joints. In order to prove the effectiveness of the proposed data glove, we implemented a VR classroom application.

• Journal of Oral Medicine and Pain
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• v.11 no.1
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• pp.19-27
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• 1986

Registration of the mandibular movement in patients with temporomandibular joint noise (clicking and/or crepitus) was performed using one of mandibular tracking devices(SAPHON VISI-TRAINER CII,Tokyo Shizai-sha Inc.,Japan). The obtained results were follows : 1. In many cases, the movement pattern of light emitting diode(LED) attached on the mandibular midline showed lateral deviation from a vertical reference line which was pronounced in association with TMJ noise during opening and closing. 2. In patients with unilateral TMJ noise the mandibular midline usually towards the side demonstrating TMJ noise during opening. 3. A distinct V-shaped discontinuity in the trace of velocity of mandibular movement was found at the point of the TMJ noise. 4. In patients with TMJ noise the velocity of mandibular movement at the point of the TMJ noise was decreased rapidly. 5. In several cases, TMJ noise could be eliminated by traning of Rocabado`s control of TMJ rotations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.23-33
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• 1994

In this paper, we propose a probabilistic model appropriate for the bearing estimator which uses cross-correlation method following a close investigation on real underwater acoustic bearing data. The well-known JPDA(Joint Probabilistic Data Association) filter is tuned to the underwater acoustic bearing estimation based on the result that the reliability of the bearing measurement is related to the amplitude of the cross-correlation peak. The proposed probabilistic model is shown to be adequate by presenting the results of the improved tracking performance of the modified filter for various real bearing data as well as artificially generated ones.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.173-179
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• 2002

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C50) fur robotic manipulators to achieve trajectory tracking angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved second stability analysis based on the indirect adaptive control theory. The proposed control scheme is simple in structure, fast in computation, an suitable fur implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by experimental results for a SCARA robot.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.29-34
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• 2010

This paper presents an intelligent learning controller for repetitive walking motion of biped walking robot. The proposed learning controller consists of an iterative learning controller and a direct learning controller. In the iterative learning controller, the PID feedback controller takes part in stabilizing the learning control system while the feedforward learning controller plays a role in compensating for the nonlinearity of uncertain biped walking robot. In the direct learning controller, the desired learning input for new joint trajectories with different time scales from the learned ones is generated directly based on the previous learned input profiles obtained from the iterative learning process. The effectiveness and tracking performance of the proposed learning controller to biped robotic motion is shown by mathematical analysis and computer simulation with 12 DOF biped walking robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.128-133
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• 2001

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C50) for robotic manipulators to achieve trajectory tracking angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved second stability analysis based on the indirect adaptive control theory. The proposed control scheme is simple in structure, fast in computation, an suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by experimental results for a SCARA robot.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.450-455
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• 1989

In this paper we investigate the application to the motion control of n-link robotic manipulators of recently developed stable factorization approach to tracking and disturbance rejection. Given control scheme consists of an approximate "Computed Torque" based upon a simplified model together with additional state feedback and feedforward compensation, and then, nonlinear control gain has more useful than constant control gain to guarantee robustness to parameter uncertainty and external disturbance. At this stage, we design high gain nonlinear state feedback controller and simulate this controller at the SCARA type robot manipulator of two joint.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• Speech Sciences
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• v.11 no.2
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• pp.227-235
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• 2004

In this paper, we proposed a new practical implementation method of the lattice transversal joint (LTJ) adaptive filter using speech codec's information. And it was applied to the adaptive echo cancellation problem to verify the efficiency of the proposed method. Realtime implementation of the LTJ adaptive filter is very difficult due to high computational complexity for the filter coefficients compensation. However, in case of using speech codec, complexity can be reduced since linear predictive coding (LPC) coefficients are updated each frame or sub-frame instead of every sample. Furthermore, LPC coefficients can be acquired from speech decoder and transformed to the reflection coefficients. Therefore, the computational complexity for updates of the reflection coefficients can be reduced. The effectiveness of the proposed LTJ adaptive filter was verified by the experiments about convergence and tracking performance of the adaptive echo canceller.

• Journal of Information Display
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• v.3 no.2
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.