• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.591-597
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• 2003

In this paper, a best-basis selection algorithm that improves the performance of the coding gains and the computational complexity is proposed. The proposed algorithm limits the computational complexity according to the resolved threshold value and decomposes the parent subbands by using the top-down tree search and the relative energy between the parent subbands and the child subbands. For the experiments of the proposed algorithm, the bit-rates, the peak signal-to-noise ratio (PSNR), and the reconstructed images are presented by using the Quad-tree coder. The result of the proposed algorithm is compared to that of DWT algorithm using the Quad-tree coder for a set of standard test images. In addition, the result of the proposed algorithm is compared to that of JPEG-2000 algorithm and that of S+P algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.905-916
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• 2008

In this paper, we propose a new method which estimates and encrypts significant component of digital hologram using discrete wavelet packet transform (DWPT). After analyzing the characteristics of digital hologram in spatial and frequency domain, the required information for ciphering digital hologram was extracted. Based on this information an ciphering method was proposed with wavelet transform and packetization of subbands. The proposed algorithm can encrypt digital hologram in various robust from selecting transform-level and energy threshold. From analyzing the encryption effect numerically and visually, the optimized parameter for encryption is presented. Without additional analyzing process, one can encrypt efficiently digital hologram using the proposed parameter. Although only 0.032% among total data is encrypted, the reconstructed object dose not identified. The paketization information of subbands and the cipher key can be used for the entire secret key.

• Structural Engineering and Mechanics
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• v.76 no.5
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• pp.591-598
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• 2020

Ultrasonic waves provide a non-destructive and sensitive way to monitor the concrete hydration. However, limited works are reported to monitor the evolution of the mechanical parameter at early ages. In this study, modified piezoelectric aggregates are embedded inside a concrete beam to excite and receive primary waves. A hydration index, namely, the variation of ultrasonic waveform (VUW) is developed to characterize the variation of the transmitted waves during the hydration process. The recorded hydration indices are compared with the compressive strength measured by destructive test at different ages. The results show that the VUW is closer to the compressive strength than the other two traditional hydration indices, ultrasonic velocity and wave packet energy. The proposed VUW provides a simple and accurate way to monitor the concrete hydration at early ages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.603-611
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• 2013

In this paper, we propose a new method which estimates and encrypts significant component of digital image such as digital cinema using discrete wavelet packet transform (DWPT). After analyzing the characteristics of images in spatial and frequency domain, the required information for ciphering an image was extracted. Based on this information an ciphering method was proposed with wavelet transform and packetization of subbands. The proposed algorithm can encrypt images in various robust from selecting transform-level and energy threshold. From analyzing the encryption effect numerically and visually, the optimized parameter for encryption is presented. Without additional analyzing process, one can encrypt efficiently digital image using the proposed parameter. Although only 0.18% among total data is encrypted, the reconstructed image dose not identified. The paketization information of subbands and the cipher key can be used for the entire secret key.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.374-387
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• 2012

In this paper, we implement a new hardware for finding the significant coefficients of a digital hologram and ciphering them using discrete wavelet packet transform (DWPT). Discrete wavelet transform (DWT) and packetization of subbands is used, and the adopted ciphering technique can encrypt the subbands with various robustness based on the level of the wavelet transform and the threshold of subband energy. The hologram encryption consists of two parts; the first is to process DWPT, and the second is to encrypt the coefficients. We propose a lifting based hardware architecture for fast DWPT and block ciphering system with multi-mode for the various types of encryption. The unit cell which calculates the repeated arithmetic with the same structure is proposed and then it is expanded to the lifting kernel hardware. The block ciphering system is configured with three block cipher, AES, SEED and 3DES and encrypt and decrypt data with minimal latency time(minimum 128 clocks, maximum 256 clock) in real time. The information of a digital hologram can be hided by encrypting 0.032% data of all. The implemented hardware used about 200K gates in $0.25{\mu}m$ CMOS library and was stably operated with 165MHz clock frequency in timing simulation.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1955-1962
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• 2017

Induction motors are a workhorse for the industry. The condition monitoring and fault analysis are the main concern for the engineers. The bearing is one of the vital segment of the induction machine and the condition of the whole machine is decided based on the condition of the bearing. In the present paper, the vibration signal of the bearing has been used for the analysis. The first line of action is to perform a statistical analysis of the vibration signal which gives trends in signal. To get the location of a fault in the bearing the second action is to develop an index based on Wavelet Packet Transform node energy named as Bearing Damage Index (BDI). Further, Teager-Kaiser Energy Operator (TKEO) has been calculated from higher index value to get the envelope and finally Power Spectral Density (PSD) has been applied to identify the fault frequencies. A performance index has also been developed to compare the usefulness of the proposed method with other existing methods. The result shows that the strong amplitude of fault characteristics and its side bands help to decide the type of fault present in the recorded signal obtained from the bearing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1096-1108
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• 1996

In this paper, we propose a temporal adaptive tranform 3D SBC coder with motion compensation, exploiting redundancy in the temporal domain. We propose a temporal adaptivity measure, by which the R-D optimal temporal transform can be chaosen. The base temporal subband frame is coded using H.261-like MC-DCT coder, while the higher temporal subband frames are coded using the 2D adaptive wavelet packet bases, considering the various energy distribution which results from the temporal variation. In encoding the subbands, we employ adaptive scanning methods, uniform step-size quantization with VLC, and coded/not-coded flag reduction technique using the quadtree structure. From the simulation results, the proposed adaptive 3D subband coder shows about 0.29~3.14 dB gain over the H.261 and the fixed 3D subband coder techniques.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.258-269
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• 2020

This paper proposes Snapping Shrimp Noise (SSN) detection and corrupted Orthogonal Frequency Division Multiplexing (OFDM) reconstruction methods to increase Bit Error Rate (BER) performance when OFDM transmitted signal is corrupted by impulsive SSNs in underwater acoustic communications. The proposed detection method utilizes multilayer wavelet packet decomposition for detecting impulsive and irregularly concentrated and SSN energy in specific frequency bands of SSN, and the proposed reconstruction scheme uses iterative decision directed-subcarrier reconstruction to recover corrupted OFDM signals using multiple carrier characteristics. Computer simulations were executed to show receiver operating characteristics curve for the detection performance and BER for the reconstruction. The practical ocean experiment of SAVEX 15 demonstrated that the proposed method exhibits a better detection performance compared with conventional detection method and improves BER by 250% and 1230% for uncoded and coded data, respectively, compared with the conventional reconstruction scheme.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.11
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• pp.1031-1040
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• 2014

In this paper, a new condition diagnosis algorithm for the lens injection molding process using various features extracted from cavity pressure, nozzle pressure and screw position signals is developed with the aid of probability neural network (PNN) method. A new feature extraction method is developed for identifying five (5), seven (7) and two (2) critical features from cavity pressure, nozzle pressure and screw position signals, respectively. The node energies extracted from cavity and nozzle pressure signals are also considered based on wavelet packet decomposition (WPD). The PNN method is introduced to build the condition diagnosis model by considering the extracted features and node energies. A series of the lens injection molding experiments are conducted to validate the model, and it is demonstrated that the proposed condition diagnosis model is useful with high diagnosis accuracy.

• Smart Structures and Systems
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• v.32 no.1
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• pp.61-81
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• 2023

This study presents an ensemble learning based Bayesian model updating approach for structural damage diagnosis. In the developed framework, the structure is initially decomposed into a set of substructures. The autoregressive moving average (ARMAX) model is established first for structural damage localization based structural motion equation. The wavelet packet decomposition is utilized to extract the damage-sensitive node energy in different frequency bands for constructing structural surrogate models. Four methods, including Kriging predictor (KRG), radial basis function neural network (RBFNN), support vector regression (SVR), and multivariate adaptive regression splines (MARS), are selected as candidate structural surrogate models. These models are then resampled by bootstrapping and combined to obtain an ensemble model by probabilistic ensemble. Meanwhile, the maximum entropy principal is adopted to search for new design points for sample space updating, yielding a more robust ensemble model. Through the iterations, a framework of surrogate ensemble learning based model updating with high model construction efficiency and accuracy is proposed. The specificities of the method are discussed and investigated in a case study.