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

(Sepak takraw) is a game that mixes football and volleyball, it is played on a court similar to a badminton court, in which players have the right to play the ball with any part of the body except the arm and hand. The object of the game is to return the ball to the opponent's court and score a point. Since it is a newly emerging game, all aspects related to it must be studied and covered in order to reach the highest levels, and it is known that each game or sporting activity has its own physical and motor capabilities, which is important to determine the level of technical performance, as the game's abilities contribute to mastering the skills. The importance of research in determining standard levels of physical and motor abilities for y

Balance is considered one of the most important components of physical activity in individual and team sports because it allows proper motor response and performance accuracy. The problem of the research lies in the lack of model for motor balance tests in the field of sports that require different positions and movements for classifying, selecting, diagnosing, and comparing athletes. The importance of the research lies in designing a test for motor balance as a reference for specialists in the field of sports and sport sciences. The subjects were first year College of physical education and sport sciences students / Baghdad University 2016 – 2017. The data was collected and treated using proper statistical operations. The researchers con

Background: The isthmus is a difficult area in the root canal complex to manage. The research aimed to evaluate the efficiency of three different obturation techniques (lateral condensation, EandQ (thermoplasticized gutta percha system) and Soft Core (thermoplasticized core carrier gutta percha system)) to obturate the isthmus area of roots prepared by two different instrumentation techniques (rotary ProTaper universal and ProTaper Next systems). Material and method: Sixty freshly extracted teeth were randomly divided into two main groups (A and B) of 30 teeth each. Group A was prepared by rotary ProTaper Universal whereas group B was prepared by ProTaper Next system. Each main group was then randomly subdivided into three subgroups of 10 t

To decrease the dependency of producing high octane number gasoline on the catalytic processes in petroleum refineries and to increase the gasoline pool, the effect of adding a suggested formula of composite blending octane number enhancer to motor gasoline composed of a mixture of oxygenated materials (ethanol and ether) and aromatic materials (toluene and xylene) was investigated by design of experiments made by Mini Tab 15 statistical software. The original gasoline before addition of the octane number blending enhancer has a value of (79) research octane number (RON). The design of experiments which study the optimum volumetric percentages of the four variables, ethanol, toluene, and ether and xylene materials leads

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve