The researchers reached many conclusions, the most important of which was the distinction of practitioners of sports activity with high degrees in the trait (social). At the same time, it was low in the trait (aggression –restraint-desisting) and non-practitioners were distinguished by sports activity with high degrees in the trait (aggression –restraint-desisting). In contrast, the degree was low in the trait (social), and there were significant differences in favor of practitioners of the activity of the athlete, Through the conclusions, the researchers recommend the need for university students to practice sports activities because of their positive impact on their health in general and on the deve

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

Abstract: The power and the size of the final spot of the laser beam reaching the target are very important requirements in most of the laser applications and fields such as medical, military, and scientific, so studying laser propagation in the atmosphere is a very important topic. The propagation of the laser beam through the atmosphere is subject to several attenuation processes that deplete the power and expand the beam. Through the simulation results of the free electron laser within the visible region of the electromagnetic spectrum (400-700nm), it was found that the attenuation increases with decreasing wavelength. Laser propagation in the presence of rain and snow leads to a very large l

The present study explores the solar-induced photocatalytic degradation of reactive red (RR) and reactive turquoise (RT) dyes in a single system using TiO2 immobilized in xanthan gum (TiO2/XG), synthesized using the sol–gel dip-coating technique for direct precipitation. SEM-EDX, XRD, FTIR, and UV–Vis were used to assess the characteristics of the resulting catalyst. Moreover, the effects of different operating parameters, specifically pH, dye concentration, TiO2/XG concentration, H2O2 concentration, and contact time, were also investigated in a batch photocatalytic reactor. The immobilized TiO2/XG catalyst showed a slight adsorption degradation efficiency and then improved the RR and RT dye degradation activity (92.5 and 90.8%

According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

Background: Pain is one of the most reported side effects of orthodontic treatment despite the advanced technology in orthodontics. Many analgesics have been introduced to control orthodontic pain including acetaminophen and selective and nonselective nonsteroidal anti-inflammatory drugs. The great concern about these drugs is their adverse effect on rate of teeth movement. Aims: The purpose of this study was to evaluate and compare the effect of acetaminophen, ibuprofen and etoricoxib on pain perception and their influence on the rate of teeth movement during leveling and alignment stage. Methods: Forty patients were evenly and randomly distributed in a blinded way to one of four groups: placebo (starch capsules), acetaminophen 500mg th

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise