• The KIPS Transactions:PartC
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• v.17C no.3
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• pp.281-290
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• 2010

In geographic forwarding algorithms, traditional route maintenance requires mobile nodes periodically exchange beacon messages with their neighbors. In beacon message based forwarding scheme, a longer interval reduces the number of beacons needed, but may result in significant location errors. Conversely, a shorter interval guarantees more accurate location information, but induces control overheads.Therefore, the fixed or dynamic interval scheme based forwarding schemes cannot adapt well to different mobility environments. Also, existing schemes result in the uncertainty of neighbor node's position in the forwarding table of mobile node. Therefore, this paper presents a self-adaptive location checking mechanism based proactive geo-routing algorithm for beacon-based geographic routing. Simulation results show that the proposed routing algorithm not only significantly increases the relay transmission rate but also guarantees the high end-to-end packet delivery in low and high mobility environments.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.2
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• pp.168-175
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• 2009

This paper proposes an enhanced algorithm for sensorless control of 45,000rpm/22kw type Permanent Magnetic Synchronous Motor (PMSM) with air-foil bearing. The proposed algorithm is based on iterative adaptive flux observer for sensorless control of the motor in wide speed range by on-line estimating angle and velocity of rotor. Simulation error between actual and estimated angle of rotor is analyzed to enhance characteristics of frequency response of conventional adaptive flux observer, which results in stable response in wide range of speed. Using the iteration number for stable phase-delay characteristics, the observer enhances the dynamic characteristics of the observer within current control period. The experiment results show the reliable performance of the proposed algorithm through starting to high speed operating range.

• Spatial Information Research
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• v.21 no.3
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• pp.11-19
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• 2013

Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.