This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database

Multi-carrier direct sequence code division multiple access (MC-DS-CDMA) has emerged recently as a promising candidate for the next generation broadband mobile networks. Multipath fading channels have a severe effect on the performance of wireless communication systems even those systems that exhibit efficient bandwidth, like orthogonal frequency division multiplexing (OFDM) and MC-DS-CDMA; there is always a need for developments in the realisation of these systems as well as efficient channel estimation and equalisation methods to enable these systems to reach their maximum performance. A novel MC-DS-CDMA transceiver based on the Radon-based OFDM, which was recently proposed as a new technique in the realisation of OFDM systems, will be us

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

Hybrid bilayer heterojunction Zinc Phthalocyanine (ZnPc) thin-film P-type is considered as a donor active layer as well as the Zinc Oxide (ZnO) thin film n-type is considered as an acceptor with (Electron Transport Layer). In this study, using the technique of Q-switching Nd-YAG Pulsed Laser Deposition (PLD) under vacuum condition 10-3 torr on two ITO (Indium Tin Oxide) and (AL) electrodes and aluminum, is used to construct the hydride bilayer photovoltaic solar cell heterojunction (PVSC). The electrical properties of hybrid heterojunction Al/ZnPc/ZnO/ITO thin film are studied. The results show that the voltage of open circuit (V_oc=0.567V), a short circuit (I_sc=36 ?A), and the fill factor (FF) of 0.443. In addition, the conversion

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m