The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the shuffled audio to yield the cipher audio. The experimental results prove that the proposed method surpassed the other techniques by encrypting two types of audio files, as mono and stereo audio files with large sizes up to 122 MB, different sample rates 22,050, 44,100, 48,000, and 96,000 for WAV and 44,100 sample rates for MP3 of size 11 MB. The results show high Mean Square Error (MSE), low Signal-to-Noise Ratio (SNR), spectral distortion, 100% Number of Sample Change Rate (NSCR), high Percent Residual Deviation (PRD), low Correlation Coefficient (CC), large key space 2616, high sensitivity to a slight change in the secret key and that it can counter several attacks, namely brute force attack, statistical attack, differential attack, and noise attack.
In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de
... Show MoreIn this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo
... Show MoreIn this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.
So, this study aimed at testing the system performance at poor s
... Show MoreThis paper is devoted to an inverse problem of determining discontinuous space-wise dependent heat source in a linear parabolic equation from the measurements at the final moment. In the existing literature, a considerably accurate solution to the inverse problems with an unknown space-wise dependent heat source is impossible without introducing any type of regularization method but here we have to determine the unknown discontinuous space-wise dependent heat source accurately using the Haar wavelet collocation method (HWCM) without applying the regularization technique. This HWCM is based on finite-difference and Haar wavelets approximation to the inverse problem. In contrast to othe
3D‐printed scaffolds loaded with healing directed agents could be employed for better treatment outcome in regenerative dentistry. The aim of this study was to fabricate and characterize simple 3D‐printed poly lactic acid (PLA) scaffolds coated with nanoHydroxyapatite (nHA), Naringin (NAR), or their combination, and testing their morphological, chemical, mechanical, antibacterial, biocompatible and bioactive properties. Methodology: Two variants pore sizes, 300 and 700 μm, of 3D‐printed PLA disc scaffolds measuring (10 × 1 mm) were fabricated. These scaffolds were dip‐coated with nHA, NAR, or both (nHA/NAR). Field emission scanning electron microscopy (FeSEM), energy‐dispersive X‐ray spectroscopy (EDX), Fourier transfo
... Show MoreMedia studies have focused mostly on the issue of the mental image because the image that is formed in the mind has become not only a photo of a human being and having kept for himself. This image has an outside influence which may sometimes up to the formation of the fate of others and it sometimes includes individuals and groups together.
This study comes in the context of identifying the image of Iraqi political parties among Iraqi university students and the nature of the view that students have in their minds about these parties.
Chapter one includes the problem of the research, the importance of the study, the goals and method used. Chapter two is divided into two sections: section one deals with the concept of the mental i