• Smart Structures and Systems
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• v.8 no.3
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• pp.253-274
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• 2011

In this paper, the harmonic displacement response of a damaged square plate with all-over part-through damage parallel to one edge is utilized as the input signal function in wavelet analysis. The method requires the properties of the damaged plate, i.e., no information about the original undamaged structure is required. The location of damage is identified by sudden changes in the spatial variation of transformed response. The incurred damage causes a change in the stiffness or mass of the plate. This causes a localized singularity which can be identified by a wavelet analysis of the displacement response. In this study via numerical examples shown by using harmonic response is more versatile and effective compared with the static deflection response, specially in the presence of noise. In the light of the obtained results, suggestions for future work are presented and discussed.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.67-72
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• 1996

Wavelets are localized in space and in frequency. This localization properties result from the multiresolution analysis of wavelets. The wavelet transform can be used to detect singularity of dynamic systems after the signal is de-noised. We applied the wavelet transform decomposition and do-noising procedures to the Hanaro dynamics consisting of 39 nonlinear differential equation plus Gaussian noise. The numerical tests demonstrate that the wavelet transform de-noising is effective for detection of the abrupt reactivity change and computationally efficient. Thus this wavelet theory could be profitably utilized in a real-time system for automatic event recognition (e.g., reactor condition monitoring).

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1157-1159
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• 1987

A syntactic and semantic approach is used to make type classification based on feature points(whorl, delta, core) and the shape of flow line around feature points. The image is divided into 30 by 30 subregions which are represented in the average direction and 4-tuple direction component. Next the relaxation process with singularity detection and convergency checking is performed. A set of semantic languages is used to describe the major flow line around the extracted feature points. LR(1) parser and feature transfer function are used to recognize the coded flow patterns. The 72 fingerprint impressions is used to test the proposed approach and the rate of the classification is about 93 percentages.

• Structural Engineering and Mechanics
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• v.24 no.6
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• pp.665-682
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• 2006

A vibration-based nondestructive damage evaluation technique for a curved thin beam is introduced. The proposed method is capable of detecting, locating, and sizing structural damage simultaneously by using a few of the lower natural frequencies and their corresponding mode shapes before and after a small damage event. The proposed approach utilizes modal flexibilities reconstructed from measured modal parameters. A rigorous system of equations governing damage and curvature of modal flexibility is derived in the context of elasticity. To solve the resulting system of governing equations, an efficient pseudo-inverse technique is introduced. The direct inspection of the resulting solutions provides the location and severity of damage in a curved thin beam. This study confirms that there is a strong linear relationship between the curvature of modal flexibility and flexural damage in the selected class of structures. Several numerical case studies are provided to justify the performance of the proposed approach. The proposed method introduces a way to avoid the singularity and mode selection problems from earlier attempts.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.172-181
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• 2005

The latest attack type against network traffic appeared by worm and bot that are advanced in DDoS. It is difficult to detect them because they are diversified, intelligent, concealed and automated. The exisiting traffic analysis method using SNMP has a vulnerable problem; it considers normal P2P and other application program to be harmful traffic. It also has limitation that does not analyze advanced programs such as worm and bot to harmful traffic. Therefore, we analyzed harmful traffic out Protocol and Port analysis. We also classified traffic by protocol, well-known port, P2P port, existing attack port, and specification port, apply singularity weight to detect, and analyze attack availability. As a result of simulation, it is proved that it can effectively detect P2P application, worm, bot, and DDoS attack.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.39-47
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• 2010

A research of image-based articulated pose estimation has some problems such as detection of human feature, precise pose estimation, and real-time performance. In particular, various methods are currently presented for recovering many joints of human body. We propose the novel numerical inverse kinematics improved with the UKF(unscented Kalman filter) in order to estimate the human pose in real-time. An existing numerical inverse kinematics is required many iterations for solving the optimal estimation and has some problems such as the singularity of jacobian matrix and a local minima. To solve these problems, we combine the UKF as a tool for optimal state estimation with the numerical inverse kinematics. Combining the solution of the numerical inverse kinematics with the sampling based UKF provides the stability and rapid convergence to optimal estimate. In order to estimate the human pose, we extract the interesting human body using both background subtraction and skin color detection algorithm. We localize its 3D position with the camera geometry. Next, through we use the UKF based numerical inverse kinematics, we generate the intermediate joints that are not detect from the images. Proposed method complements the defect of numerical inverse kinematics such as a computational complexity and an accuracy of estimation.