• The Transactions of The Korean Institute of Electrical Engineers
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• 제58권11호
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• pp.2192-2199
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• 2009

This paper proposes a novel tracking algorithm for efficiency improvement of photovoltaic(PV) system using sensor method. PV system of sensor method is exactly impossible to track a sun position when insolation is low or rapidly changed by the clouds and fogs. Also, in this case, tracking device is occurred energy consumption by unnecessary operating. This statement of reason, real power of PV system is not increased than fixed PV system in specified location. Therefore, this paper proposes a novel tracking algorithm considered insolation for efficiency improvement of PV system using sensor method. And this paper analyzes the generation volume and proves the validity of proposed algorithm as compared with the conventional PV tracking system using sensor method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• 제67권4호
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• pp.227-232
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• 2018

In this paper, we propose a faster object detection and tracking method using Deep Learning, UAV(unmanned aerial vehicle), Kalman filter and YOLO(You Only Look Once)v3 algorithms. The performance of the object tracking system is decided by the performance and the accuracy of object detecting and tracking algorithms. So we applied to the YOLOv3 algorithm which is the best detection algorithm now at our proposed detecting system and also used the Kalman Filter algorithm that uses a variable detection area as the tracking system. In the experiment result, we could find the proposed system is an excellent result more than a fixed area detection system.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제59권4호
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• pp.779-787
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• 2010

In this paper, We introduce electrical tracking generated from surface activity associated with flow of leakage current on insulator under wet and contaminated conditions and design electrical tracking pattern recognition system by using LabVIEW. We measure the leaking current of contaminated wire by using LabVIEW software and the NI-c-DAQ 9172 and NI-9239 hardware. As pattern recognition algorithm and optimization algorithm for electrical tracking system, neural networks, Radial Basis Function Neural Networks(RBFNNs) and particle swarm optimization are exploited. The designed electrical tracking recognition system consists of two parts such as the hardware part of electrical tracking generator, the NI-c-DAQ 9172 and NI-9239 hardware and the software part of LabVIEW block diagram, LabVIEW front panel and pattern recognition-related application software. The electrical tracking system decides whether electrical tracking generate or not on electrical wire.

• The KIPS Transactions:PartB
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• 제12B권3호
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• pp.273-282
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• 2005

Real-time Object tracking is an important field in developing vision applications such as surveillance systems and vision based navigation. mean-shift algerian and Condensation algorithm are widely used in robust object tracking systems. Since the mean-shift algorithm is easy to implement and is effective in object tracking computation, it is widely used, especially in real-time tracking systems. One of the drawbacks is that it always converges to a local maximum which may not be a global maximum. Therefore, in a cluttered environment, the Mean-shift algorithm does not perform well. On the other hand, since it uses multiple hypotheses, the Condensation algorithm is useful in tracking in a cluttered background. Since it requires a complex object model and many hypotheses, it contains a high computational complexity. Therefore, it is not easy to apply a Condensation algorithm in real-time systems. In this paper, by combining the merits of the Condensation algorithm and the mean-shift algorithm we propose a new model which is suitable for real-time tracking. Although it uses only a few hypotheses, the proposed method use a high-likelihood hypotheses using mean-shift algorithm. As a result, we can obtain a better result than either the result produced by the Condensation algorithm or the result produced by the mean-shift algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• 제7권4호
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• pp.5-12
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• 2004

The tracking algorithm based on the interacting multiple model(IMM) requires a considerable number of sub-models for the various maneuvering targets in order to have a good performance. But it is not feasible to use the nm algorithm in the real system because of the computational burden. Therefore, we need an algorithm which requires less computing resources while maintaining a good performance. In this paper, we propose a fuzzy interacting multiple model algorithm(FIMMA) for the tracking of maneuvering targets, which uses a minimal number of sub-models by considering the maneuvering properties and adjusts the mode transition probabilities by using the mode probability as a fuzzy input. In order to verify the performance of FIMMA, the developed algorithm is applied to the tracking of i borne targets. Simulation results show that the FIMMA is very effective in the tracking of maneuvering targets.

• Journal of Korea Society of Digital Industry and Information Management
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• 제13권3호
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• pp.27-33
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• 2017

In this paper presents the MPPT tracking algorithm using angle control of flexible PV in BIPV. The proposed algorithm is based on MPPT tracking algorithm for curtain wall using flexible PV. It is an algorithm to find optimal power generation condition by controlling the angle of flexible PV using the air layer of window. The angle of flexible PV tests the power generation by separating the center of flexible PV into the interior angle in the interior direction and the external angle in the center of flexible PV. When the angle of flexible PV was used as interior angle, the generation amount was increased by 15.79% and increased by 8.45% compared with the external angle. MPPT tracking is performed on the generation amount of the interior angle which has the most power after comparing the generation amount according to the bending shape of the flexible PV. This algorithm can be the most efficient method for the curtain wall using flexible PV because the bending pattern with the greatest amount of power generation may be different because the environment of the building applying the curtain wall is different.

• International journal of advanced smart convergence
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• 제4권2호
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• pp.20-28
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• 2015

In this paper, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame with posture variation and camera view point adaptation by employing the non-adaptive random projections that preserve the structure of the image feature space of objects. The existing online tracking algorithms update models with features from recent video frames and the numerous issues remain to be addressed despite on the improvement in tracking. The data-dependent adaptive appearance models often encounter the drift problems because the online algorithms does not get the required amount of data for online learning. So, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame.

• The Journal of the Korea institute of electronic communication sciences
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• 제18권6호
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• pp.1109-1116
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• 2023

Object tracking is used to track a goal in a video sequence by using coordinate information provided as annotation in the first frame of the video. In this paper, we propose a tracking algorithm that combines deep features and region inference modules to improve object tracking accuracy. In order to obtain sufficient object information, a convolution neural network was designed with a Siamese network structure. For object region inference, the region proposal network and overlapping confidence module were applied and used for tracking. The performance of the proposed tracking algorithm was evaluated using the Object Tracking Benchmark dataset, and it achieved 69.1% in the Success index and 89.3% in the Precision Metrics.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 한국조명전기설비학회 2009년도 추계학술대회 논문집
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• pp.375-378
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• 2009

This paper proposes active tracking algorithm to improve efficiency of PV system. Active tracking algorithm tracks sun position using sensor method and program method with insolation condition. Also, in this case that insolation is very low, tracking system is controlled by environment mode to reduce the power loss. Proposed algorithm is applied the PV system and analyzes the generation value. And this algorithm proves the validity of this pater through the experimental result.

• Journal of the Korea Institute of Military Science and Technology
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• 제5권3호
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• pp.62-76
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• 2002

This paper describes the design of a Coordinates Tracking algorithm for EOTS and its error analysis. EOTS stabilizes the image sensors such as FLIR, CCD TV camera, LRF/LD, and so on, tracks targets automatically, and provides navigation capability for vehicles. The Coordinates Tracking algorithm calculates the azimuth and the elevation angle of EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which is generated by a Radar or an operator. In the error analysis in this paper, the unexpected behaviors of EOTS that is due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. This algorithm is verified and the error analysis is confirmed through simulations. The application of this algorithm to EOTS will improve the operational capability by reducing the time which is required to find the target and support especially the flight in a night time flight and the poor weather condition.