Futsal and blind football are group games of a competitive nature due to their excitement, excitement, fun, and aesthetic goals with charming artistic touches. This explains the public's passion for these two games, whether healthy people or blind people play them, to expand their vision and knowledge. About these two games, a historical approach is presented about their origins, development, and how they became globally recognized competitive sports with unified rules and world championships at various levels. Studying the origin and global spread of both futsal and blind football and identifying the most prominent developments in the rules and tools for futsal and blind football. The most important findings were that both futsal and footb

This study was conducted to detect the relationship between organic content in the sediment of Rivers Tigris and Diyala, at two locations south of Baghdad, with some environmental factors and the benthic invertebrates and values of diversity indices. Monthly samples collected from the area for the period November 2007 to October 2008. Results showed differences in the physical and chemical characteristics of the two sites, Where the annual average in Tigris and Diyala were respectively for: water temperature (19, 20) C°, pH (8, 8), dissolved oxygen (4, 8) mg / l , Biochemical oxygen Demand BOD5 (3,44 ) mg/l, TDS (632,1585) mg / l, TSS (42, 44) mg / l, turbidity (28,74) NTU, and total hardness as CaCO3 (485,823) mg / l ,Sulfat

Nosocomial infections (NIs) are hospital-acquired associated infections, and also contracted due to the infections or toxins that exist in some location, like hospital. Therefore in our study, 4 Lactic acid bacteria (LAB) isolates were obtained from dairy product (Lactobacillus brevis, L. acidophilus, Lactococcus raffinolactis and Lactococcus lactis) and were tested for Bacteriocin production to select Lactococcus lactis among them. Cell free supernatant (CFS), Lipid and partial purification of protein La. Lactis had high inhibitory effect against test pathogens (E. coli, Bacillus cereus, Staphylococcus aureus and Streptococcus). 30 isolates that diagnosed by Vitec, were isol

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p