• Smart Structures and Systems
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• v.6 no.9
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• pp.991-1005
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• 2010

The key to detecting damage to civil engineering structures is to find an effective damage indicator. The damage indicator should promptly reveal the location of the damage and accurately identify the state of the structure. We propose to use the distance measures of low-order AR models as a novel damage indicator. The AR model has been applied to parameterize dynamical responses, typically the acceleration response. The premise of this approach is that the distance between the models, fitting the dynamical responses from damaged and undamaged structures, may be correlated with the information about the damage, including its location and severity. Distance measures have been widely used in speech recognition. However, they have rarely been applied to civil engineering structures. This research attempts to improve on the distance measures that have been studied so far. The effect of varying the data length, number of parameters, and other factors was carefully studied.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.85-95
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• 1998

In this paper, a new watermarking method for a copy protectionof images is proposed. The proposed method adaptively embeds a watermark in the frequency domain of images using human visual system model. For this purpose, the Just Noticeable Differences(JNDs) of each frequency coeffeicient value of a luminance plane is first found using Watson and Solomon's visual system model. An invisible maximum watermark value with is different in every position according to the characteristics of images is determined usig JND and Minkowski metric. A low frequency domain is divided into two sets based on a PN-sequence to protect thewatermark from the attack. The watermarks are added to one set of coefficients and detecting a watermark, the difference between the mean values of absolute coefficient values of both sets is calculated. The embedded watermark is tested using statistical hypothesis based on test static dertermined by the ean difference. To demonstrate the perfromance of the proposed method, the new watermarking method is applied to a high frequency image and low frequency images. Experimenatal results show the watermark is invisible and robust to JPEGlossy compression and noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.134-138
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• 2002

The human faces do not have distinct features unlike other general objects. In general the features of eyes, nose and mouth which are first recognized when human being see the face are defined. These features have different characteristics depending on different human face. In this paper, We propose a face recognition algorithm using the hidden Markov model(HMM). In the preprocessing stage, we find edges of a face using the locally adaptive threshold scheme and extract features based on generic knowledge of a face, then construct a database with extracted features. In training stage, we generate HMM parameters for each person by using the forward-backward algorithm. In the recognition stage, we apply probability values calculated by the HMM to input data. Then the input face is recognized by the euclidean distance of face feature vector and the cross-correlation between the input image and the database image. Computer simulation shows that the proposed HMM algorithm gives higher recognition rate compared with conventional face recognition algorithms.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.111-115
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• 1997

ZnO varistors are widely used as surge arresters in power system based on their excellent nonlinearity. The property of power loss of ZnO varistors is related to the thermal stability and their life-spans of ZnO surge arresters. The power losses of ZnO varistors under different temperatures and applied voltages were measured, and the properties of power losses were analyzed. The Artificial Neural Network (ANN) was used to simulate the power losses properties of ZnO varistors which is an adaptive nonlinear dynamic system, and the results calculated by ANN simulating model were in good agreement with the tested ones.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1217-1219
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• 1998

For the improvement of an adaptive SPAR(Single-Phase Auto-Reclosure) and novel protection schemes, it is important to simulate arc faults. But, it is difficult to reproduce the real arc behaviour, i.e. the extinction phenomenon exactly by computer simulations due to extremely random behavior of secondary arc. This paper proposes a new computer modeling techniques for the primary and the secondary arc separately, which can be implemented with EMTP MODELS routine, and the performance of the proposed model is simulated on a typical 154 [kV] korean transmission line system.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.191-196
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• 2005

In this study, to describe vehicle-track-bridge dynamic interaction phenomena with 1/4 vehicle model, nonlinear Hertzian contact spring and nonlinear contact damper are introduced. In this approach external loads acting on 1/4 vehicle model are self weight of vehicle and geometry information of running surface. The constraint equation on contact surface is implemented by Penalty method. Also, to improve the numerical stability and to maintain accuracy of solution, the artificial damper and the reaction from constraint violation are introduced. A nonlinear time integration method, in this study, Newmark method is adopted for both equations of vehicles and structure. And to reduce the error caused by inadequate time step size, adaptive time-stepping technique is partially introduced. As the nonlinear Hertzian contact spring has no resistance to tensile force, the bouncing phenomena of wheelset can be described. Thus, it is expected that more versatile dynamic interaction phenomena can be described by this approach and it can be applied to various railway dynamic problems.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1081-1087
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• 2006

Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.839-842
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• 2000

A new and modified neural network model Is proposed for CT image reconstruction from four projection directions only. The model uses the Resilient Back-Propagation (Rprop) algorithm, which is derived from the original Back-Propagation, for adaptation of its weights. In addition to the error in projection directions of the image being reconstructed, the proposed network makes use of errors in pixels between an image which passed the median filter and the reconstructed one. Improved reconstruction was obtained, and the proposed method was found to be very effective in CT image reconstruction when the given number of projection directions is very limited.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.9
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• pp.97-106
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• 1996

In this paper, we propose a face recognition algorithm using the hidden markov model and neural networks (HMM-NN). In the preprocessing stage, we find edges of a face using the locally adaptive threshold (LAT) scheme and extract features based on generic knowledge of a face, then construct a database with extracted features. In the training stage, we generate HMM parameters for each person by using the forward-backward algorithm. In the recognition stage, we apply probability vlaues calculated by the HMM to subsequent neural networks (NN) as input data. Computer simulation shows that the proposed HMM-NN algorithm gives higher recognition rate compared with conventional face recognition algorithms.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.231-236
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• 2015

In this paper, the technical analysis and characteristics of screen content coding (SCC) based on High efficiency video coding (HEVC) are presented. For SCC, which is increasingly used these days, HEVC SCC standardization has been proceeded. Technologies such as intra block copy (IBC), palette coding, and adaptive color transform are developed and adopted to the HEVC SCC standard. This paper examines IBC and palette coding that significantly impacts RD performance of SCC for screen content. The HEVC SCC reference model (SCM) 4.0 was used to comparatively analyze the coding performance of HEVC SCC based on the HEVC range extension (RExt) model for screen content.