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

The research's aim is to place two teaching methods ( total and analytical method) and to know which one of them is better than the other in teaching the counter-attack with Epee. The researchers have used the experimental method for being considered suitable to solve the problem of the research. The sample of the research includes third –stage female students of college of physical education and sport sciences / Baghdad University in the subject of fencing, their number amounted 60 female students. It has been used SPSS for processing the results. They have concluded that the two groups of the research and the two methods (( total and analytical) have learnt the counter- attack of the two over mentioned groups. they have recommended to c

During the study the current selection seven stations in the Zab River bottom and the Tigris River took samples a month to study the signs of bacterial contamination study coliform and colon fecal Almsobhaat and Almsobhaat Bazah and the total number of bacteria and bacterial gangrene gas causing Knkeran as well as a study to isolate and diagnose some races and types of bacterial pathogens in water or intensityusing the traditional system and the system of intestinal bacteria

Abstract: non-alcoholic fatty liver disease (NAFLD) is one of the widespread chronic liver diseases; it is ranging from simple fat buildup in the liver (steatosis) to non-alcoholic steatohepatitis (NASH) presence of inflammation and hepatocyte injury.                                                                                                                                        &nb

To investigate the effects of losartan and enalapril on serum uric acid in hypertensive patients with metabolic syndrome, one hundred and twenty six newly diagnosed mild hypertensive patients, having markers of metabolic syndrome included  in the study. The patients were divided into two groups. Group 1 (60 patients) was given losartan (50 mg/ day) and group 2 (66 patients)  enalapril (20 mg/ day) for a duration of 2 months. A control group of seventy apparently healthy individuals were included. Metabolic syndrome was diagnosed according to diagnostic criteria of metabolic syndrome related to the American National Cholesterol Education Program-Adult Treatment Panel III. Serum uric acid levels were measured bef

Ten isolates of Klebsiella pneumoniae, seven isolates of Pseudomonas aeruginosa and nine isolates of Staphylococcus aureus, were obtained from 100 urine samples collected from Baghdad hospitals. All isolates were identified biochemically and confirmed by using VITEK 2 and were then tested for their susceptibility towards 6 antibiotics and for phenolic extracts of Thymus vulgaris and Cinnamomum cassia. All bacteria were greatly affected by T. vulgaris, especially K. pneumoniae. Viable count was performed, it was noted that the number of bacterial cells reduced from 1×108 CFU to 1.2× 103, 2×105 and 1.8×106CFU of K. pneumoniae, P. aeruginosa and S. aureus respectively. While C. cassiahad a slight effect on them. K. pneumoniae isola