• Journal of the Korea Computer Graphics Society
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• v.5 no.2
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• pp.33-41
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• 1999

This paper presents a new algorithm about motion adjustment for dynamic balance. It adjusts an unbalanced motion to an balanced motion while preserving the nuance of original motion. We solve dynamic balancing problem using the zero moment point (ZMP) which is often used for controlling the balance of biped robot. Our algorithm is consists of four steps. First, it fits joint angle data to spline curves for reducing noise. Second, the algorithm analyzes the ZMP trajectory so that it can detects the dynamically-unbalanced duration. Third, the algorithm project the ZMP trajectory into the supporting area if the trajectory deviates from the area. Finally, the algorithm produces the balanced motion that satisfies the new ZMP trajectory. In this step, the constrained optimization method is used so that the new motion keeps the original motion characteristics as much as possible. We make several experiments in order to prove that our algorithm is useful to add physical realism to a kinematically edited motion.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.165-175
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• 2000

In recent years, it becomes a very important issue to consider the mechanical systems such as high-speed vehicles and railway trains moving on elastic beam structures. In this paper, a general approach, which can predict the dynamic behavior of constrained mechanical system and elastic beam structure, is proposed. Also, various supporting conditions of a foundation support are considered for the elastic beam structures. The elastic structure is assumed to be a nonuniform and linear Bernoulli-Euler beam with proportional damping effect. Combined Differential-Algebraic Equations of motion are derived using multibody dynamics theory and Finite Element Method. The proposed equations of motion can be solved numerically using generalizd coordinate partitioning method and Predictor-Corrector algorithm, which is an implicit multi-step integration method.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.1
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• pp.37-42
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• 2003

Active control of flexural vibrations of smart laminated composite beams has been carried out using piezoceramic sensor/actuator and viscoelastic material. The beams with passive constrained layer damping have been analyzed by formulating the equations of motion through the use of extended Hamilton's principle. The dynamic characteristics such as damping ratio and modal damping of the beam are calculated for various fiber orientations by means of iterative complex eigensolution method. This paper addresses a design strategy of laminated composite under flexural vibrations to design structure with maximum possible damping capacity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1333-1337
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• 2000

The flexural vibration of laminated composite beams with active and passive constrained-layer damping has been investigated to design structure with maximum possible damping capacity. The equations of motion are derived for flexural vibrations of symmetrical, multi-layer laminated beams. The damping ratio and modal damping of the first bending mode are calculated by means of iterative complex eigensolution method. This paper addresses a design strategy of laminated composite under flexural vibrations with active control.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.183-188
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• 1994

A passivity-based adaptive controller for robots executing fine motion tasks is proposed. The robot dynamics is modelled such that it is subject to holonomic constraints and hence it can be treated as a particular case of constrained motion tasks. Energy-motivated stability analysis is used to conclude the asymptotic stability. Remarks regarding the structure of the controller are given. A computer simulations study is presented and a robust constraint stabilization algorithm is also proposed.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.567-572
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• 2004

In this research, a stable walking pattern generation method for a biped robot is presented. A biped robot is considered as constrained multibody system by several kinematic joints. The proposed method is based on the optimized polynomial approximation of the trunk motion along the moving direction. Foot motions can be designed according to the ground condition and walking speed. To minimize the deviation from the desired ZMP, the trunk motion is generated by the fifth order polynomial approximation. Walking simulation for a virtual biped robot is performed to demonstrate the effectiveness and validity of the proposed method. The method can be applied to the biped robot for stable walking pattern generation.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.4
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• pp.54-63
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• 2002

In recent years, mechanical systems such as high speed vehicles and railway trains moving on elastic beam structures have become a very important issue to consider. In this paper, a general approach, which can predict the dynamic behavior of a constrained mechanical system moving on a flexible beam structure, is proposed. Various supporting conditions for the foundation support are considered for the elastic beam structure. The elastic structure is assumed to be a non-uniform and linear Bernoulli-Euler beam with a proportional damping effect. Combined differential-algebraic equation of motion is derived using the multi-body dynamics theory and the finite element method. The proposed equations of motion can be solved numerically using the generalized coordinate partitioning method and predictor-corrector algorithm, which is an implicit multi-step integration method.

• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1073-1080
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• 2020

360-degree video streaming technologies have been widely developed to provide immersive virtual reality (VR) experiences. However, high computational power and bandwidth are required to transmit and render high-quality 360-degree video through a head-mounted display (HMD). One way to overcome this problem is by transmitting high-quality viewport areas. This paper therefore proposes a motion-constrained tile set (MCTS)-based tile extractor for versatile video coding (VVC). The proposed extractor extracts high-quality viewport tiles, which are simulcasted with low-quality whole video to respond to unexpected movements by the user. The experimental results demonstrate a savings of 24.81% in the bjøntegaard delta rate (BD-rate) saving for the luma peak signal-to-noise ratio (PSNR) compared to the rate obtained using a VVC anchor without tiled streaming.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1053-1063
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• 2019

Recently, tile-based streaming that transmits one 360 video in several tiles, is actively being studied in order to transmit these 360 video more efficiently. In this paper, for the transmission of high-definition 360 video corresponding to user's viewport in tile-based streaming scenarios, a system of assigning the quality of tiles at each tile by applying the saliency map generated by existing network models is proposed. As a result of usage of Motion-Constrained Tile Set (MCTS) technique to encode each tile independently, the user's viewport was rendered and tested based on Salient360! dataset, streaming 360 video based on the proposed system results in gain to 23% of the user's viewport compared to using the existing high-efficiency video coding (HEVC).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5530-5546
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• 2016

Automatic analysis and understanding of human activities is a challenging task in computer vision, especially for the surveillance scenarios which typically contains crowds, complex motions and occlusions. To address these issues, a Bag-of-words representation of videos is developed by leveraging information including crowd positions, motion directions and velocities. We infer the crowd activity in a motion field using Category Constrained Correlated Topic Model (CC-CTM) with latent topics. We represent each video by a mixture of learned motion patterns, and predict the associated activity by training a SVM classifier. The experiment dataset we constructed are from Crowd_PETS09 bench dataset and UCF_Crowds dataset, including 2000 documents. Experimental results demonstrate that accuracy reaches 90%, and the proposed approach outperforms the state-of-the-arts by a large margin.