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

Soft pneumatic actuators grasping tasks is one of the essential rules in robot manipulation methods. The grasping forces can be adapted to handle delicate and hard objects without leaving any damages on the object surfaces. This paper investigates the influence of the inclination angle of the soft pneumatic actuator (SPA) on its gripping force at its end tip. A range of inclination angles for SPA

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

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

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

This paper represents modeling and control of an agricultural service skid steering mobile robot for the purposes of grass cutting using Proportional-Integral-Derivative (PID) controller and Fuzzy Logic techniques and feedback signals from sensors as IMU, encoders, and Machine Vision. The paper deals with the system modeling into two methods: The first is using Fuzzy modeling as a modeling tool

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)

Wind has a considerable effect on many water quality parameters. Some of the parameters are directly affected by the wind, while others are influenced by other physical water parameters like the velocity, temperature. etc. that are affected by wind and hence transfer their effect to water quality parameters. As the wind has an effect on water quality parameters, also covering waterways has a great

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