The power-energy performance of supercapacitors is usually visualized by the Ragone plot of (gravimetric or volumetric) energy density vs power density. The energy is commonly computed from E = CV2/2, and the power from P = E/Δt, which assume RCbased models. In this study, we investigate the energy-power profiles of two commercial supercapacitors discharged with three different types of loads: (i)

This paper demonstrates the possibility of extracting the single-dispersion and double-dispersion Cole-bio-impedance model parameters using oscillators (sinusoidal or relaxation). The method is based on replacing selected components in the oscillator structure with the biological sample under test and then using the Flower Pollination optimization Algorithm (FPA) to solve a set of nonlinear

This paper introduces a heuristic solver based on neural networks and deep learning for the knapsack problem. The solver is inspired by mechanisms and strategies used by both algorithmic solvers and humans. The neural model of the solver is based on introducing several biases in the architecture. We introduce a stored memory of vectors that holds up items representations and their relationship to

Committing robotics with artificial intelligence becomes mandatory collaboration with distinct environments. Omnidirectional Wheeled (Omni-WD) mobile robots are one of the robots that interact with humans in various circumstances, where it is important to function effectively and accurately. In this paper, the distinction of a 3WD-Omni model and control using machine vision is demonstrated. The

With recently increasing the environmental problems and expected energy crisis, it is necessary to synthesis a low-cost, efficient, and UV-light responsive photocatalyst for contaminants’ degradation. The nanostructured spinel ferrite Mn0.5Zn0.5-xMgxFe2O4 NPs (x = 0.0, 0.125, 0.25, 0.375 and 0.50) were synthesized via the sol-gel method. The crystallite size was lied in nano regime ranging from 21

Surface plasmon resonance (SPR) sensors are increasingly in demand due to their high sensitivity, better accuracy, and improved detection limit. Such performance parameters make these sensors suitable for biological and medical field’s applications. During the last decade, prism coupling-based SPR sensors had been a preferred choice among the designer and developers across the globe. This article

Convolutional Neural Networks (CNNs) for Artificial Intelligence (AI) algorithms have been widely used in many applications especially for image recognition. However, the growth in CNN-based image recognition applications raised challenge in executing millions of Multiply and Accumulate (MAC) operations in the state-of-The-Art CNNs. Therefore, GPUs, FPGAs, and ASICs are the feasible solutions for

This manuscript investigates the synchronization between a novel integer order hyperchaotic system and a fractional order hyperchaotic system. The controllers are constructed using the technique of tracking controller and the stability theory of the linear fractional order system. Chaotic analysis of the introduced novel integer order hyperchaotic system is also investigated. The Lyapunov exponent

It is feasible and safe to use unmanned aerial vehicle (UAV) as the data collection platform of the Internet of things (IoT). In order to save the energy loss of the platform and make the UAV perform the collection work effectively, it is necessary to optimize the deployment of UAV. The objective problem is to minimize the sum of the lost energy of UAV and the loss of data transmission of Internet

A novel non-uniform Kramers–Kronig Transform algorithm for bioimpedance phase extraction is proposed and tested in this work. The algorithm error is studied and compared with a previously proposed phase extraction technique, also based on the Kramers–Kronig transform. Results using simulated datasets and experimental datasets confirm the excellent performance of the algorithm. © 2020, European