The researchers have discovered weaknesses in the rotational phase of the 100-meter freestyle event, including a lack of proper movement direction and control of biomechanical variables necessary for swimmers to achieve high rotational accuracy, which leads to outperforming competitors. The objective of this study was to investigate the effect of using a laser device on improving the performance of the rotational phase among swimmers on the Iraqi national team. The experimental approach was conducted on a sample of 6 swimmers, representing 100% of the target population. The researchers concluded that the utilization of a proposed laser device in the rotational phase resulted in positive differences in biomechanical variables, contri

Focusing of Gaussian laser beam through nonlinear media can induce spatial self- phase modulation which forms a far field intensity pattern of concentric rings. The nonlinear refractive index change of material depends on the number of pattern rings. In this paper, a formation of tunable nonlinear refractive index change of hybrid functionalized carbon nanotubes/silver nanoparticles acetone suspensions (F-MWCNTs/Ag-NPs) at weight mixing ratio of 1:3 and volume fraction of 6x10-6 , 9x10-6 , and 18x10-6 using laser beam at wavelength of 473nm was investigated experimentally. The results showed that tunable nonlinear refractive indices were obtained and increasing of incident laser power density led to increase the nonlinear refractive inde

Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

The study aims to identify the degree of implementation of the coronavirus prevention standards (covid-19) in the kingdom of Saudi Arabia and compare it with the families of intellectual disabilities. The study population consisted of all families residing in the Kingdom of Saudi Arabia. To achieve the objectives of the research, the analytical descriptive approach was employed. The study sample consisted of (372) families, among them (84) families with intellectual disabilities, and (288) families without intellectual disabilities. They were chosen from the Saudi community according to what is available for collection in a simple random way, using the standard criteria for the prevention of coronavirus (Covid- 19) Prepared by the resear

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

Jumping ability is a fundamental variable in many sports, as its execution requires an integration of muscular strength Q1 and certain biomechanical variables. This is particularly evident in gymnastics jumping events and jump shots in ball games, both of which rely on a high level of vertical resistance. Vertical resistance serves as an indicator of an athlete’s ability to overcome their body weight while counteracting gravitational force to achieve optimal performance. As such, it is considered one of the key factors in movements that demand explosive power and speed. The researchers believe that despite the significant relationship between vertical resistance, speed-strength of the arms and legs, and certain biomechanical varia

Three-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and construc

 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot