• 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1759-1772
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• 1994

In this study, we re-examined the Tate's modified Bernoulli equation to study penetration phenomena for long rod projectile into single or multi-layered finite thickness plates. We used the force equlibrium equation at mushroomed nose/target interface instead of conventional pressure equation at the stagnation point. In our penetration model, we considered the velocity dependent $R_t$ value for semi-infinite target and considered only the back face effect for finite target. To compensate for $R_t$ value according to target's thickness and back face effect, we used the spherical cavity expansion theory for semi-infinite plate and used the cylindrical cavity expansion theory for finite plate. Also we developed the experimental technique using make screen to measure the penetration duration time at each layered plate. In 3-layered laminated RHA/mild steel/ A1 7039 plate, we observed that spall had occured around the back face of A1 7039 plate by the stress wave interaction. Through the comparison between theoretical and experimental data including Lambert's results, we conform that our study has good confidences.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.6
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• pp.545-556
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• 2016

JPDAF is a method of updating target's state estimation by using posterior probability that measurements are originated from existing target in multi-target tracking. In this paper, we propose a multi-target tracking algorithm for falling cluster bombs separated from a mother bomb based on JPDAS method which is obtained by applying fixed-interval smoothing technique to JPDAF. The performance of JPDAF and JPDAS multi-target tracking algorithm is compared by observing the average of the difference between targets' state estimations obtained from 100 independent executions of two algorithms and targets' true states. Based on this, results of simulations for a radar tracking problem that show proposed JPDAS has better tracking performance than JPDAF is presented.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.479-482
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• 2004

In this article we consider a single maneuvering target Tracking algorithm in the presence of missing measurements and high clutter environments for multi-sensor target tracking problem. The tracking algorithm is based on the Particle filtering method to predict and update target states. Proposed is the AMM-PF(Auxiliary Multiple Model Particle Filter)[2] method for maneuvering target tracking to improve performance in track estimate and maintenance with a high level of uncertainty. The algorithm we propose is compared to the Extended Kalman Filter(EKF). A simulation study is included.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2590-2606
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• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.728-733
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• 2008

Though multi-panel structures lined with a poroelastic material have been widely used to reduce sound transmission in various fields, most of the previous works to design them were conducted by repeated analyses or experiments based on initially given configurations or sequences. Therefore, it was difficult to obtain the optimal sequence of multi-panel structures lined with a poroelastic material yielding superior sound isolation capability. In this work, we propose a new design method to sequence a multi-panel structure lined with a poroelastic material having maximized sound transmission loss. Being formulated as a one-dimensional topology optimization problem for a given target frequency, the optimal sequencing of panel-poroelastic layers is systematically carried out in an iterative manner. In this method, a panel layer is expressed as a limiting case of a poroelastic layer to facilitate the optimization process. This means that main material properties of a poroelastic material are treated as Interpolated functions of design variables. The designed sequences of panel-poroelastic layers were shown to be significantly affected by the target frequencies; more panel layers were used at higher target frequencies. The sound transmission loss of the system was calculated by the transfer matrix derived from Biot's theory.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.828-831
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• 1997

One of the most important design factor for the image tracker is the speed of the data processing which allows real-time operation of the system and provides reasonably accurate performance at the same time. Use of powerful DSP alone does not guarantee to meet such requirement. In this paper, a simple efficient algorithm for real-time multi-target image tracking is suggested. The suggested method is based on a recursive centroiding technique and color table look-up. This method has been successfully implemented in a image processing system for Micro-Robot Soccer Tournament(MIROSOT). This tracker can track positions of a ball, 3 enemies, and 3 agents at the same time. The experimental results show that the processing time for each frame of image is less than 7ms, which is well within the 60Hz sampling interval for real-time operation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.1
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• pp.103-109
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• 2016

The performance of a multi-head, computerized combination scaling system to automatically identify a group of agricultural products having a total weight within the target range has been optimized to reduce the package cycle time of the merchandise. First, the structure of the scale was modified to enable faster measurement by enhancing the dynamic stability during the process. Second, the high frequency noise in the measured signal was eliminated by a high frequency filter to provide more accurate weight data. Finally, the algorithm to identify a group of products with a total weight within the target range was modified to enable a user to select an optimal number of scales. According to the experimental verifications, this modified system reduced the package cycle time significantly and also was accurate in measuring the total weight of the selected products.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.746-752
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• 2014

In a multi-camera measurement system, the determination of the external parameters is one of the vital tasks, referred to as the calibration of the system. In this paper, a new geometrical calibration method, which is based on the theory of the vanishing line, is proposed. Using a planar target with three equally spaced parallel lines, the normal vector of the target plane can be confirmed easily in every camera coordinate system of the measurement system. By moving the target into more than two different positions, the rotation matrix can be determined from related theory, i.e., the expression of the same vector in different coordinate systems. Moreover, the translation matrix can be derived from the known distance between the adjacent parallel lines. In this paper, the main factors effecting the calibration are analyzed. Simulations show that the proposed method achieves robustness and accuracy. Experimental results show that the calibration can reach 1.25 mm with the range about 0.5m. Furthermore, this calibration method also can be used for auto-calibration of the multi-camera mefasurement system as the feature of parallels exists widely.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1146-1152
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• 2002

This paper proposed a scheme for finding an optimal adaptive data association for multi-target between measurements and tracks. First, we assume the relationships between measurements as Mrkov Random Field. Also assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space, that may incorporate most of the important natural constraints. Through the experiments, we analyzed and compared this algorithm with other representative algorithms. The result is that it is stable, robust, fast enough for real timecomputation, as well as more accurate than other methods.