• Architectural research
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• v.10 no.2
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• pp.21-26
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• 2008

The number of measured degrees of freedom for detecting the damage of any structures is usually less than the number of model degrees of freedom. It is necessary to expand the measured data to full set of model degrees of freedom for updating modal data. This study presents the expansion methods to estimate all static displacements and dynamic modal data of finite element model from the measured data. The static and dynamic methods are derived by minimizing the variation of the potential energy and the Gauss's function, respectively. The applications illustrate the validity of the proposed methods. It is observed that the numerical results obtained by the static approach correspond with the Guyan condensation method and the derived static and dynamic approaches provide the fundamental idea for damage detection.

• Journal of Power Electronics
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• v.13 no.2
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• pp.304-312
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• 2013

The most common power quality problems in distribution systems are related to unbalanced voltage sags. Voltage sags must be detected quickly and corrected in a minimum amount of time. One of the most widely used methods for sag detection is based on the d-q transformation. This method has the disadvantage of missing the detection of unbalanced faults, because this method uses a voltage sag level signal obtained from the average of 3 phases for sag detection. In this paper, an adaptive filter sag detection method is proposed for Dynamic Voltage Restorers (DVR) under unbalanced fault conditions. The proposed DVR controller is able to detect balanced, unbalanced and single phase voltage sags. A novel reference voltage generation method is also presented. To validate the proposed control methods, a 3-phase DSP controlling a DVR prototype with a power rating of 1.5-kVA has been developed. Finally, experimental results are presented to verify the performance of the proposed control methods.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.243-260
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• 2018

Detection of damages in fibre reinforced plastic (FRP) composite structures is important from the safety and serviceability point of view. Usually, damage is realized as a local reduction of stiffness and if dynamic responses of the structure are sensitive enough to such changes in stiffness, then a well posed inverse problem can provide an efficient solution to the damage detection problem. Usually, such inverse problems are solved within the framework of pattern recognition. Support Vector Machine (SVM) Algorithm is one such methodology, which minimizes the weighted differences between the experimentally observed dynamic responses and those computed using the finite element model- by optimizing appropriately chosen parameters, such as stiffness. A damage detection strategy is hereby proposed using SVM which perform stepwise by first locating and then determining the severity of the damage. The SVM algorithm uses simulations of only a limited number of damage scenarios and trains the algorithm in such a way so as to detect damages at unknown locations by recognizing the pattern of changes in dynamic responses. A rectangular fiber reinforced plastic composite plate has been investigated both numerically and experimentally to observe the efficiency of the SVM algorithm for damage detection. Experimentally determined modal responses, such as natural frequencies and mode shapes are used as observable parameters. The results are encouraging since a high percentage of damage cases have been successfully determined using the proposed algorithm.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.963-968
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• 2007

In this paper introduce Standard 3D object(Bounding-Volume). In 3D game very efficient control algorithm Using collision detection which controls the convenient of a game based on Standard 3D object specially collision-detection. This algorithm is designed LOD(Level-of-Detail) using Dynamic-Hierarchies of collision detection efficiency improvement in 3D object.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.141-148
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• 2003

Customer retention is a common concern for many industries and a critical issue for the survival in today's greatly compressed marketplace. Current customer retention models only focus on detection of potential defectors based on the likelihood of defection by using demographic and customer profile information. In this paper, we propose a dynamic procedure for defection detection and prevention using past and current customer behavior by utilizing SOM and Markov chain. The basic idea originates from the observation that a customer has a tendency to change his behavior (i.e. trim-out his usage volumes) before his eventual withdrawal. This gradual pulling out process offers the company the opportunity to detect the defection signals. With this approach, we have two significant benefits compared with existing defection detection studies. First, our procedure can predict when the potential defectors could withdraw and this feature helps to give marketing managers ample lead-time for preparing defection prevention plans. The second benefit is that our approach can provide a procedure for not only defection detection but also defection prevention, which could suggest the desirable behavior state for the next period so as to lower the likelihood of defection. We applied our dynamic procedure for defection detection and prevention to the online gaming industry. Our suggested procedure could predict potential defectors without deterioration of prediction accuracy compared to that of the MLP neural network and DT.

• Journal of Environmental Science International
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• v.19 no.12
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• pp.1447-1454
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• 2010

In this study, the detection limits of lower fatty acids in air were investigated by using Dynamic SPME(Solid Phase Micro-Extraction), i.e. improved Head Space - SPME method(HS-SPME). This Dynamic SPME, called SPDE(Solid Phase Dynamic Extraction), is the analytical method for volatile compounds in air with the extraction by using a stainless steel needle of which inner surface is coated with adsorption material and following the gas chromatographic analysis by inserting the needle into a injection port of GC and subsequently, desorption of the volatile compounds into a gas-chromatographic column. Extraction was carried out by passing the sample air through the needle with a suction pump which has been used for a detection tube. The result of measurement for the 6 lower fatty acids showed that the detection limits ranged from 0.10 ppm to 0.44 ppm and the linear correlation coefficients were over 0.99. Relative standard deviations obtained from 5 analytical repetition of a ca. 1.6 ppm standard mixture were in the range of 1.87%~2.47%. This method has been shown to be a adequate for the measuring C2~C5 fatty acids in air in the concentrations of over several hundreds ppb.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.651-656
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• 2010

This paper proposes a new dynamic PCA algorithm to recognize types of electric poles, which is necessary for a mobile robot moving along the neutral line for inspecting high-voltage facilities. Since the mobile robot needs to pass over the electric poles and grasp the neutral wire again for the next region inspection, the detection of the electric pole type is a critical factor for the successful passing-over the electric pole. The CCD camera installed on the mobile robot captures the image of the electric pole while it is approaching to the electric pole. Applying the dynamic PCA algorithm to the CCD image, the electric pole type has been classified to provide the stable grasping operation for the mobile robot. The new dynamic PCA algorithm replaces the reference image in real time to improve the robustness of the PCA algorithm, adjusts the brightness to get the clear images, and applies the Laplacian edge detection algorithm to increase the recognition rate of electric pole type. Through the real experiments, the effectiveness of this proposed dynamic PCA algorithm method using Laplacian edge detecting method has been demonstrated, which improves the recognition rate about 20% comparing to the conventional PCA algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.1-9
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• 2010

Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.258-261
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• 2012

In this paper, I propose a new asset allocation framework to cope with the dynamic nature of the financial market. The investment performance can be much improved by protecting the capital from the market crashes, and such crashes can be pre-identified with high probabilities by regime detection analysis via a specialized unsupervised machine learning technique.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.919-922
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• 1998

A content-base search method is required for video which has an unformatted and huge size of data. The index techniue is necessary for the content-based search of the video data. The first step of the video indexing is a cut detection. We propose a dynamic threshold method which change a threshold value during the cut detection process. We demonstrate that the proposed method is more efficient than the existing methods.