The research objectives, to build a measure of the level of tactical performance of volleyball players applying for the Iraqi Premier League for the 2018-2019 season. The nature of the research problem, then the researchers determined the research sample in the deliberate manner of the players of the Iraqi clubs for the Premier League (B, A). The researchers adopted the entire community as a sample for the research, and the number (156) players distributed over (13) clubs and divided the sample into (12)players an exploratory experiment player representing (the police club) and (100) player representing the construction sample and after a maximum period of two months has passed since applying the scale to the construction sample the researc

Abstract

In this work, the plasma parameters (electron temperature (T_e), electron density( n_e), plasma frequency (f_p) and Debye length (λ_D)) have been studied by using the spectrometer that collect the spectrum of Laser produce CdTe_(X):S_(1-X) plasma at X=0.5 with different energies. The results of electron temperature for CdTe range 0.758-0.768 eV also the electron density 3.648 10¹⁸ – 4.560 10¹⁸ cm^-3  have been measured under vacuum reaching 2.5 10^-2 mbar .Optical properties of CdTe:S were determined through the optical transmission method using ultraviolet visible spectrophotometer within the r

The process of evaluating and measuring tax performance is critical to support the tax collection process. The comparison of the amount of revenue collection with what is expected and the process of measuring tax performance continuously by the tax administration leads to increase the collection of tax, determine the size of deviations and stand and know the reasons and take the necessary measures to address them to get a better result in the future. According to the different tasks assigned to them, criteria and indicators for measuring the tax performance vary from one organization to another. These are indicators or criteria that measure tax revenue (i.e., amounts). One of the research's main findings was to raise the tax collection leve

Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i

The aims of this research is to investigate : The nature of academic specialization of the officials of Baghdad University Presidency , Level of job performance of the officials of Baghdad University Presidency through job performance appraisal form per year , Differences in the levels of job performance of the officials of Baghdad university presidency , according to the variables (sex , academic specialization , the current work , the duration between the date of graduation and the date of appointment , service duration) , The relationship of academic specialization of the officials of Baghdad university presidencywith their job performance . The researcher has followed the analytical descriptive mode to achieve the aims of this resear

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod