In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

Due to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor i

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

The goal of the study is to discover the best model for forecasting the exchange rate of the US dollar against the Iraqi dinar by analyzing time series using the Box Jenkis approach, which is one of the most significant subjects in the statistical sciences employed in the analysis. The exchange rate of the dollar is considered one of the most important determinants of the relative level of the health of the country's economy. It is considered the most watched, analyzed and manipulated measure by the government. There are factors affecting in determining the exchange rate, the most important of which are the amount of money, interest rate and local inflation global balance of payments. The data for the research that represents the exchange r

In this work, functionally graded materials were synthesized by centrifugal technique at different
volume fractions 0.5, 1, 1.5, and 2% Vf with a rotation speed of 1200 rpm and a constant rotation time, T
= 6 min . The mechanical properties were characterized to study the graded and non-graded nanocomposites
and the pure epoxy material. The mechanical tests showed that graded and non-graded added alumina
(Al2O3) nanoparticles enhanced the effect more than pure epoxy. The maximum difference in impact strength
occurred at (FGM), which was loaded from the rich side of the nano-alumina where the maximum value was
at 1% Vf by 133.33% of the sample epoxy side. The flexural strength and Young modulus of the fu