The precise identification of electrical model parameters of Li-Ion batteries is essential for efficient usage and better prediction of the battery performance. In this work, the model identification performance of two metaheuristic optimization algorithms is compared. The algorithms in comparison are the Marine Predator Algorithm (MPA) and the Partial Reinforcement Optimizer (PRO) to find the

This paper investigates two different blind watermarking systems in the frequency domain with the development of a Pseudo Random Number Generator (PRNG), based on a fractional-order chaotic system, for watermark encryption. The methodology is based on converting the cover image to the YCbCr color domain and applying two different techniques of frequency transforms, Discrete Cosine Transform (DCT)

Abstract: In the context of the three-phase hysteresis model (3PHL), a system of equations is established for a generalized thermoelastic medium under the influence of a magnetic field and an internal heat source. The problem is discussed using Eringen’s nonlocal elastic model. The exact expression of the physical quantity is obtained by normal mode analysis and illustrated graphically by

Stochastic computing is a relatively new approach to computing that has gained interest in recent years due to its potential for low-power and high-noise environments. It is a method of computing that uses probability to represent and manipulate data, therefore it has applications in areas such as signal processing, machine learning, and cryptography. Stochastic steganography involves hiding a

This paper introduces a planar antipodal meander line antenna fabricated using RO3003 substrate. The proposed antenna is designed to radiate in the end-fire direction, achieving a maximum measured gain of 10.43 dBi within its working bandwidth, which ranges from 2.24 GHz to 2.7 GHz, covering long-range WLAN/WiMAX applications. A systematic procedure is adopted in the design process to prove its

Secret Image Sharing (SIS) transfers an image to mutually suspicious receivers as n meaningless shares, where k or more shares must be present to recover the secret. This paper proposes a (k, n)-SIS system for any image type using polynomial interpolation based on Lagrange polynomials, where the generated shares are of size 1/k of the secret image size. A full encryption system, consisting of

Image enhancement is a vital process that serves as a tool for improving the quality of a lot of real-life applications. Fractional calculus can be utilized in enhancing images using fractional order kernels, adding more controllability to the system, due to the flexible choice of the fractional order parameter, which adds extra degrees of freedom. The proposed system merges two fractional order

Nowadays, Machine Learning is commonly integrated into most daily life applications in various fields. The K Nearest Neighbor (KNN), which is a robust Machine Learning algorithm, is traditionally used in classification tasks for its simplicity and training-less nature. Hardware accelerators such as FPGAs and ASICs are greatly needed to meet the increased requirements of performance for these

Biometric security has been developed in recent years with the emergence of cancellable biometric concepts. The idea of the cancellable biometric traits is concerned with creating encrypted or distorted traits of the original ones to protect them from hacking techniques. So, encrypted or distorted biometric traits are stored in databases instead of the original ones. This can be accomplished

Achieving robustness against adversarial attacks while maintaining high accuracy remains a critical challenge in neural networks. Parameter quantization is one of the main approaches used to compress deep neural networks to have less inference time and less storage memory size. However, quantization causes severe degradation in accuracy and consequently in model robustness. This work investigates