• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.210-212
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• 2009

In object tracking based on the particle filter algorithm controlling the proper distribution of the samples is essential to accurately track the target. If the samples are spread too wide compared to the target size, the tracking accuracy may degrade as some samples can be caught by background clutters that is similar to the target. On the other hands if the samples are spread too narrow, the particle filter may fail to track the abrupt motion of the target. To solve this problem we propose an improved particle filter that adopts "re-weighting" technique at the observe step. We estimate the distribution of the weights of the current samples by its mean and variance. Then the samples are re-weighted so that the appropriate distribution of the samples in proportional to the target scale is obtained at the next select step. The proposed tracking method can avoid convergence to local mean and improve the accuracy of the estimated target state.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.1
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• pp.43-52
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• 2014

This paper presents a tracking system using images captured from a camera on a moving platform. A camera on an unmanned flying vehicle generally moves and shakes due to external factors such as wind and the ego-motion of the machine itself. This makes it difficult to track a target properly, and sometimes the target cannot be kept in view of the camera. To deal with this problem, we propose a new system for stable tracking of a target under such conditions. The tracking system includes target tracking and 3-axis camera motion compensation. At the same time, we consider the simulation of the motion of flying vehicles for efficient and safe testing. With 3-axis motion compensation, our experimental results show that robustness and stability are improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1711-1725
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• 2014

Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of measurements and targets. In this paper, to reduce the computational cost of the data association process, we propose a novel multi-target tracking method that excludes particle samples in the overlapped predictive region between the target to track and marginal targets. Moreover, to resolve the occlusion problem, we define an occlusion mode with the normal dynamic mode. When the targets are occluded, the mode is switched to the occlusion mode and the samples are propagated by Gaussian noise without the sampling process of the particle filter. Experimental results demonstrate the robustness of the proposed multi-target tracking method even in occlusion.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.637-644
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• 2006

Acceleration time history used in the seismic analysis of nuclear porter plant structure should envelop a target power spectral density (PSD) function in addition to design response spectrum. Current regulation guide defines the target PSD function only for the U.S. URC RG 1.60 Design Response Spectrum. This paper proposes a technical scheme to obtain the target PSD function compatible with generally defined design response spectrum. The scheme includes the methodology for design-spectrum compatible motion history in order to minimize the variation of the derived target PSD function. The PSD calculation procedure follows simple and practical methods allowed within regulation. Effectiveness of the proposed scheme is identified through an example problem. The design response spectrum In the example is based on U.S. NRC RG 1.60 but amplifies the spectral acceleration amplitudes above 9Hz. The target PSD function with little variation can be constructed with the reduced time history ensemble.

• Journal of the military operations research society of Korea
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• v.36 no.3
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• pp.29-42
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• 2010

In this study, the weapon-target assignment problem arising in military application of operations research is considered. We reformulated the problem in order to simplify the solution methods based on genetic algorithms and heuristics. Since the problem is well known as NP-complete and cannot be solved in polynomial time, such solution methods have been widely used to obtain good solutions. Two chromosome representations--target number representation and permutation representation--in genetic algorithm are compared. In addition, a construction heuristic and three improving heuristics are developed. Several experiments under the condition of transitivity rules in weapon's kill probability have been accomplished. It shows that the construction heuristic and exchange-based improving heuristic guarantees good solutions within a second and the performance of construction heuristic is sensitive to transitivity rules.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.497-502
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• 2002

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, a DNA coding-based interacting multiple model (DNA coding-based W) method is proposed. The proposed method can overcome the mathematical limits of conventional methods by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive IMM algorithm and the GA-based IMM method in computer simulations.

• Korean Journal of Health Education and Promotion
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• v.17 no.1
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• pp.171-184
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• 2000

In present paper, author proposed an effective health education strategy for local health department, which was revised from the PATCH of CDC. The author suggested that an health department should follow several steps to have an effective health promotion programs in their community. First step would be community mobilization that encourage key persons and major organizations and agencies to participate in the program. The second step is collecting demographic and vital statistics in the community or for a target audience as well as social, psychological and behavioral data. Based on the data analysis, the next step is to choose a target audience and health problem(s) for the target audience in question. The fourth step is the development of health education strategy for the target audience and the health problem. The fourth step also includes selecting a proper communication channel and educational materials as well as pre- and post-testing. The final step is implementing health education programs and evaluating the process, outcome and impact of the program. Korean Institute for Health and Social Affairs(KIHASA) has developed a model for health education programs used in local health department. KIHASA can provide technical assistance and health education materials to assist local health departments in Korea.

• Proceedings of The Korean Society of Health Promotion Conference
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• 1999.07a
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• pp.73-92
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• 1999

In present paper, author proposed an effective health education strategy for local health department, which was revised from the PATCH of CDC. The author suggested that an health department should follow several steps to have an effective health promotion programs in their community. First step would be community mobilization that encourage key persons and major organizations and agencies to participate in the program. The second step is collecting demographic and vital statistics in the community or for a target audience as well as social, psychological and behavioral data. Based on the data analysis, the next step is to choose a target audience and health problem(s) for the target audience in question. The fourth step is the development of health education strategy for the target audience and the health problem. The fourth step also includes selecting a proper communication channel and educational materials as well as pre- and post-testing. The final step is implementing health education programs and evaluating the process, outcome and impact of the program. Korean Institute for Health and Social Affairs(KIHASA) has developed a model for health education programs used in local health department. KIHASA can provide technical assistance and health education materials to assist local health departments in Korea.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.185-191
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• 2019

During the modern battlefields of multi-batches flight formation attack situation, it is an essential task for a commander to make a proper fire distribution of air defense missile launch platforms for threat targets with effectively and quickly. Pan et al. try to solve this problem using genetic algorithm, but they are fails. This paper gets the initial feasible solution using high threat target first destroying strategy only use 75% available fire of each missile launch platform. Then, the assigned missile is moving to another target in the case of decreasing total threat. As a result of experiment, while the proposed algorithm is polynomial-time complexity greedy algorithm but this can be improve the solution than genetic algorithm.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.164-172
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• 2013

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.