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Go to Editorial ManagerThe use of image communication has increased in recent years. In this approach, the encryption process is performed by hiding the processing steps of the wavelet transform. The attacker cannot obtain the original image unless processing steps are known. In this paper, the performance of three different hidden wavelet-based schemes are applied. First, hiding filter types encryption scheme (HFT), second, hiding wavelet packet tree encryption scheme (HWPT), lastly, by combining the previous two methods (HFTWPT). Several experiments are given to illustrate the performance of the proposed schemes.
The use of image communication has increased in recent years. In this approach, the encryption process is performed by hiding the processing steps of the wavelet transform. The attacker cannot obtain the original image unless processing steps are known. In this paper, the performance of three different hidden wavelet-based schemes are applied. First, hiding filter types encryption scheme (HFT), second, hiding wavelet packet tree encryption scheme (HWPT), lastly, by combining the previous two methods (HFTWPT). Several experiments are given to illustrate the performance of the proposed schemes.
The discovery and identification of damages in engineering structures is very important in the field of engineering maintenance, as it is a great challenge in presenting new methods in measuring vibrations and discovering damages with the development in the field of automation and high accuracy in discovering damages. In this study, natural frequencies and mode shapes of transverse vibration for damage detection in structures are investigated. The study is performed for various crack depth and crack location. And suggested a new technique based on Continuous Wavelet Transform (CWT) and Convolution Neural Network (CNN). The comparison will be done by simulating the oscillations of a cantilever steel beam with and without defect as a numerical case. The proposed new technique proved to outperform classical methods and has achieved a100% accuracy in the identification of defect position for the data studied.
This paper introduces a radial distribution feeder protection scheme based on certain features extraction from current signals measurement at the substation. The features are captured using the discrete wavelet transform (DWT). Two digital signals processing methods are used to introduce those features to the 1) fault detection 2) identification and 3) localization schemes; the first one is the energy method and the second one is the root mean square method. For the purpose of fault type identification, two systems are tested and compared, a Fuzzy Inference System (FIS) and Artificial Neural Network (ANN). Fault location scheme is then built based on ANNs. An effort is made to reduce the computational burden and the speed of detection provided by the fault detection and identification schemes. Since the short circuit faults are the most likely types of faults that can occur in power systems, the ten types of these faults taking into account different fault resistances are simulated in MATLAB environment and the protection scheme is built based on the idea of over current. The power quality disturbances such as switching transient events on the feeder is also taken into account in order to build a reliable and secure protection scheme.
In this paper, image deblwring and denoising are presented. The used images were blurred either with Gaussian or motion blur and corrupted either by Gaussian noise or by salt & pepper noise. In our algorithm, a discrete wavelet transform is used to dJvide the image into two parts. This partition will help in increasing the manipulation speed of images that are of the big sizes. Therefore, the first part represents the approximation coefficients, that a blur is reduced b,y using the modified fixed-phase iterative algorithm. While the second part represents the detail coefficients, that a noise is removed by using the BayesShrink wavelet thresholding method.