The research objective was to study the amount of lost fluids, some blood components and mineral salts in volleyball players under hot weather conditions. The sample of the present study was composed of 12 volleyball players of Al-Sinaa Club (Baghdad, Iraq) in the 2022/2023 season. The variables analyzed in this study were: Heart rate before and after exercise, internal and external body temperature before and after exertion, potassium ion, sodium ion, calcium ion, and the amount of fluid lost (the player's weight) before and after the exercise. The tests were conducted at a temperature between 42-47 degrees Celsius. The maximum anaerobic exercise was performed with volleyball. The results showed that to play volleybal

The research objective was to study the amount of lost fluids, some blood components and mineral salts in volleyball players under hot weather conditions. The sample of the present study was composed of 12 volleyball players of Al-Sinaa Club (Baghdad, Iraq) in the 2022/2023 season. The variables analyzed in this study were: Heart rate before and after exercise, internal and external body temperature before and after exertion, potassium ion, sodium ion, calcium ion, and the amount of fluid lost (the player's weight) before and after the exercise. The tests were conducted at a temperature between 42-47 degrees Celsius. The maximum anaerobic exercise was performed with volleyball. The results showed that to play volleybal

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

 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

CuO-ZnO-Al2O3 catalyst was prepared in the ratios of 20:30:50 respectively, using the coprecipitation method of Cu, Zn and Al carbonates from their nitrate solutions dissolved in distilled water by adding sodium bicarbonate as precipitant.The catalyst was identified by XRD and quantitatively analysis to determine the percentages of its components using flame atomic absorption technique. Also the surface area was measured by BET method. The activity of this prepared catalyst was examined through the oxidation of ethanol to acetaldehyde which was evaluated by gas chromatography.

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

This study was aimed to investigat integrated system for in vitro growth of paulownia plants by assessing the efficacy of chlorine dioxide (ClO2) as an alternative to autoclave in sterilizing culture medium. Therefore, this study was devised to compare autoclave sterilization at three different times (5, 10, and 15) minutes and three different concentrations of ClO2 (0, 0.4, 0,8, 1) mg/L. The results showed that, compared with (0.4) mg/L concentration,  concentrations of (0.8 and 1) mg/L are more effective at sterilizing the culture medium. ClO2 sterilization improved individual single node growth more than autoclave sterilization. Since ClO2 is non-toxic, it could be used as a safe alternative to autoclave when propagating paulown

In this work we fabrication holographic optical element diffraction grating thickness 40?m and mirror90?m by using dichromated gelatin,to perform that we have to use the Nd-yaG laser doubling frequency of wavelenght (532)nm and its powers of (80)mWatt.we have studyed the thickness and concentration dichromat effect in mirror reflaction ,effect of angle of reconstruction beam in band width and diffraction efficiency ,study effect gelatin hardener of the diffraction efficiency.

Abstract

       The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he