• Steel and Composite Structures
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• v.19 no.1
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• pp.191-208
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• 2015

The sensitivity-based finite element model updating method has received increasing attention in damage detection of structures based on measured modal parameters. Finding an optimization technique with high efficiency and fast convergence is one of the key issues for model updating-based damage detection. A new simple and computationally efficient optimization algorithm is proposed and applied to damage detection by using finite element model updating. The proposed method combines the Gauss-Newton method with region truncation of each iterative step, in which not only the constraints are introduced instead of penalty functions, but also the searching steps are restricted in a controlled region. The developed algorithm is illustrated by a numerically simulated 25-bar truss structure, and the results have been compared and verified with those obtained from the trust region method. In order to investigate the reliability of the proposed method in damage detection of structures, the influence of the uncertainties coming from measured modal parameters on the statistical characteristics of detection result is investigated by Monte-Carlo simulation, and the probability of damage detection is estimated using the probabilistic method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1117-1122
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• 2017

Pedestrian detection is a very important and valuable part of artificial intelligence and computer vision. It can be used in various areas for example automatic drive, video analysis and others. Many works have been done for the pedestrian detection. The accuracy of pedestrian detection on multiple pedestrian image has reached high level. It is not easily get more progress now. This paper proposes a new structure based on the idea of HOG and convolutional filters to do the pedestrian detection in single pedestrian image. It can be a method to increase the accuracy depend on the high accuracy in single pedestrian detection. In this paper, we use Multiblock HOG and magnitude of the pixel as the feature and use convolutional filter to do the to extract the feature. And then use NEWFM to be the classifier for training and testing. We use single pedestrian image of the INRIA data set as the data set. The result shows that the Convolutional Multiblock HOG we proposed get better performance which is 0.015 miss rate at 10-4 false positive than the other detection methods for example HOGLBP which is 0.03 miss rate and ChnFtrs which is 0.075 miss rate.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.472-484
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• 2019

This paper proposes a time-domain sound event detection algorithm using DNN (Deep Neural Network). In this system, time domain sound waveform data which is not converted into the frequency domain is used as input to the DNN. The overall structure uses CRNN structure, and GLU, ResNet, and Squeeze-and-excitation blocks are applied. And proposed structure uses structure that considers features extracted from several layers together. In addition, under the assumption that it is practically difficult to obtain training data with strong labels, this study conducted training using a small number of weakly labeled training data and a large number of unlabeled training data. To efficiently use a small number of training data, the training data applied data augmentation methods such as time stretching, pitch change, DRC (dynamic range compression), and block mixing. Unlabeled data was supplemented with insufficient training data by attaching a pseudo-label. In the case of using the neural network and the data augmentation method proposed in this paper, the sound event detection performance is improved by about 6 %(based on the f-score), compared with the case where the neural network of the CRNN structure is used by training in the conventional method.

• Bulletin of the Korean Chemical Society
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• v.31 no.12
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• pp.3797-3799
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• 2010

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1865-1872
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• 1997

This paper proposes not only the thresholding problem which has been one of the major problems in the pre-existing edge detection method but also the removal of blurring effect occurred at the edge regions due to the smoothing process. The structure of a given image is assigned as one of the three predefined image structure classes by evaluating its toll membership value to each reference structure class:The structure of an image belongs to the structure class which has the least cost value with the image. Upon the structure class assigned, noise removal and edge extraction precesses are performed, e.g., the smoothing algorithm is applied to the image if its structure belongs to the pure noise region class; edge extraction while removing the noise is performed simultaneously if the edge structure class. The proposed method shows that preventing the blurring effect can be usually seen in the edge images and extracting the edges with no using thresholding value by the experiments.

• Smart Structures and Systems
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• v.4 no.3
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• pp.305-318
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• 2008

The development of a digital signal processor based prototype is described in relation to continuing efforts for realizing a fully self-contained active sensor system utilizing impedance-based structural health monitoring. The impedance method utilizes a piezoelectric material bonded to the structure under observation to act as both an actuator and sensor. By monitoring the electrical impedance of the piezoelectric material, insights into the health of the structured can be inferred. The active sensing system detailed in this paper interrogates a structure utilizing a self-sensing actuator and a low cost impedance method. Here, all the data processing, storage, and analysis is performed at the sensor location. A wireless transmitter is used to communicate the current status of the structure. With this new low cost, field deployable impedance analyzer, reliance on traditional expensive, bulky, and power consuming impedance analyzers is no longer necessary. A complete power analysis of the prototype is performed to determine the validity of power harvesting being utilized for self-containment of the hardware. Experimental validation of the prototype on a representative structure is also performed and compared to traditional methods of damage detection.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.333-342
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• 2003

The objective of this paper is to present an algorithm to locate and size damage in a beam structure. The method uses the changes in the modal strain energy distribution. A damage index, utilized to identify possible location and corresponding severity of local damage, is formulated and expressed in terms of modal displacements that can be obtained from mode shapes of the undamaged and the damaged structures. The possible damage locations in the structure arc determined by the application of damage indicator according to previously developed decision rules. The robustness and effectiveness of the method arc demonstrated using numerical examples of beam structures with simulated damage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1732-1743
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• 2000

In this paper a fixed-delay trellis search with decision feedback (FDTrS/DF) for high-density DVD systems (4.7-15GB) is proposed and implemented with FPGA. The proposed FDTrS/DF is derived by transforming the binary tree search structure into trellis search structure implying that FDTrS/DF performs better than the singnal detection techniques based on tree search structure such as FDTS/DF and SSD/DF. Advantages of FDTrS/DF are significant reductions in hardware complexity due to the unique structure of FDTrS composed of only one trellis stage requiring no traceback procedure usually implemented in the Viterbi detector. Also in this paper the PDFS/DF and SSD/DF orginally proposed for high-density magnetic recording systems are modified for the DVD system and compared with the proposed FDTrS/DF. In order to increase speed in the FPGA implementation the pipelining technique and absolute branch metric (instead of square branch metric) are applied. The proposed FDTrS/DF is shown to provide the best performance among various signal detection techniques such as PRML, DFE, FDTS/DF and SSD/DF even with a small hardware complexity.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.19-30
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• 2007

In this paper, we propose low-complexity implementation of orthogonal frequency division multiple access (OFDMA) timing delay detector with multiple receive antennas for broadband wireless access (BWA). First, in order to reduce the computational complexity, the detection structure which rotates the phase of the received ranging symbols is introduced. Second, we propose the detection structure with the N-point/M-interval fast Fourier transform structure and a frequency-domain average-power estimator for complexity reduction without sacrificing the system performance. Finally, simulation results for the proposed structures and complexity comparison of the existing structure with the proposed detectors are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.835-836
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• 2014

In this paper, we have designed the collimator of different sizes structure for the development of stereo radiation detector. And we conducted a study of the optimal structure of collimator using the results of the Gamma-ray irradiation test associated with the change of the incident angle. According to the results of the performance analysis, and showed the results of the optimal incident angle 2. Results of the paper are used as basic data for designing the structure of the detector efficiency for radiation detection.