Fencing is characterized by rapid and sudden changes that require speed in decision-making and motor responses. In addition, it requires high sensorimotor awareness and strong coordination between leg, arm, and eye movements. In the current study, the researchers used cognitive coordination response speed exercises and physical and skill exercises in order to develop performance in the time counterattack. The aim of the study is to identify the effect of cognitive coordination response speed exercises on the performance of the time counterattack of female foil fencers. An experimental method was used on the female fencing team players at the College of Physical Education and Sports Sciences for Women/University of Baghdad in the spo

In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 p

Central banks around the world typically use various financial indicators to evaluate performance. In Iraq, the indicators used by central banks to evaluate the performance of banks are of great importance to ensure that the banks operating within the Iraqi banking system comply with the regulatory and legal requirements issued by the Central Bank of Iraq or the Ministry of Finance. Given the need to study the profitability indicator to ensure its ability to evaluate the performance of specialized banks in Iraq, these banks carry out their banking activities and businesses through capital funded by the government. The use of profitability indicators in evaluating the performance of specialized banks provides information about the profitabil

The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm³.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

     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

Introduction and Aim: Klebsiella pneumoniae is a Gram-negative bacterium responsible for a wide range of infections, including respiratory tract infections (RTIs). This research was aimed to study the antibacterial and antibiofilm effect of AgNPs produced by Gram positive and negative bacteria on RTIs associated with K. pneumoniae. Materials and Methods: The biofilm formation of K. pneumoniae was determined by tube method qualitatively from select bacterial species characterized by UV-Visible spectroscopy. The antibacterial susceptibility of the bacteria AgNPs was tested for their antibacterial and antibiofilm activity on a clinical isolate of K. pneumoniae. Results: K. pneumoniae isolated from RTIs were strong biofilm producers. The ant

Cyclophosphamide is chemotherapeutic agent that utilized for the treatment of different malignancies; however its’ used associated with numerous adverse effects. Vitamin B2 and vitamin B12 suggested having myeloprotective effect. This work is designed to investigate the myeloprotective effect of both vitamins against cyclophosphamide induced myelosuppression. One hundred adult rats of both sexes were used in this study. The animals were randomly enrolled into ten groups of 10 rats each. Group I: Control group. Group II: Cyclophosphamide-treated. Group III and Group IV Orally-administered vitamin B2 (10, and 40 mg/kg/day), respectively alone for 7 days. Group V: