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)

Industrial dyes are considered one of the main causes of increased water pollution of water. Many businesses, such as steel and paper, are located along riverbanks because they require large amounts of water in their manufacturing processes, and their wastes, which contain acids, alkalis, dyes, and other chemicals, are dumped and poured into rivers as effluents. For example, chemical enterprises

Indoor air pollution poses a substantial risk to human health and well-being, underscoring the crucial requirement for efficient monitoring systems. This paper introduces an advanced Air Pollution Monitoring System (APMS) tailored explicitly for indoor settings. The APMS integrates sensors and a user interface, ensuring the delivery of real-time and precise data concerning air quality parameters

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

Quantum Dots have shown a significant potential as a top candidate for infrared photodetection at higher temperatures. In the presented work, a theoretical model for estimating the coefficient of optical absorption of self-assembled truncated conical quantum dot is developed. This model considers both bound-to-continuum and bound-to-bound absorption mechanisms that increase the accuracy of the

In various areas of life, rechargeable lithium-ion batteries are the technology of choice. Equivalent circuit models are utilized extensively in characterizing and modeling energy storage systems. In real-time applications, several generic-based battery models are created to simulate the battery's charging and discharging behavior more accurately. In this work, we present two generic battery

Monte Carlo (MC) simulation is a widely adopted computational method that relies on random sampling, but it is susceptible to exhibiting patterns and biases due to the use of pseudo-random numbers. In contrast, Quasi-Monte Carlo (QMC) techniques employ low discrepancy sequences, resulting in more evenly distributed random numbers and the potential for more accurate and reliable simulation outcomes

Floating point representations are required in many applications due to their universality and ability to represent huge numbers accurately and in compact bit-width. Floating point arithmetic is complex, performance inefficient, and area-consuming compared to integer arithmetic operations. In this paper, hardware realization of area-efficient high-performance floating point arithmetic units for

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