Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

Most drugs undergo some metabolism in the liver before excretion by the kidneys or bile. Thus, it is not surprising that liver injury may be provoked due to its exposure to various drugs and compounds. Drug-induced cholestatic liver injury may occur particularly under conditions of increased drug concentrations, genetic alterations in expression of enzymes or transporters. Additionally, the drug-induced cholestasis can be caused by direct toxic effects of drugs or their metabolites on different hepatic cell types or through an immune-mediated process. Amoxicillin/ clavulanic acid, an antibiotic that is therapeutically utilized for the treatment of a number of bacterial infections. Omega-3 fatty acids are unsaturated fatty acids that have ro

The effect of mental and physical health on the feelings of subject welfare is known as health-related quality of life. The chronic obstructive pulmonary disease is a common respiratory diseases. Assessment of health-related quality of life is considered important in such chronic disease. The objective of the current study was to measure health-related quality of life in a sample of chronic obstructive pulmonary  patients in AL- Diwanyia city/Iraq. This study was carried out on 150 already diagnosed COPD patients who attended to the Center of Respiratory Diseases/AL-Diwaniyah Teaching Hospital during September  2019 to January 2020. The Arabic version of St George’s Respiratory Questionnaire was used to asses

The heavy metals Cd, Cu, Fe, pb, and Zn were determined in dissolved and particulate phases of the water,in addition to exchangeable and residual phases of the sediment and in the selected organs of the fish Cyprinus carpio collected from the Euphrates River near Al-Nassiriya city center south of Iraq during the summer period / 2009 .Also sediment texture and total organic carbon(TOC) were measured. Analysis emploing a flam Atomic Absorption Spectrophotometers . The mean regional concentrations of the heavy metals in dissolved (µg/l) and particulate phases (µg/gm) dry weight were Cd (0.15,16.13) ,Cu (0.59,24.48) ,Fe (726,909.4) ,Pb (0.20, 49.95) and Zn (2.5,35.62) respectively,and those for exchangeable and residual phases of the

Objectives: The study aims to: (1) assess the prevalence of phantom vibration and ringing syndrome among
nurses, (2) determine the level of job-related stress among those nurses who are working at teaching hospitals in
Al- Nasiriyah city, and (3) identify the association between job-related stress and experience of phantom
vibration and ringing syndrome.
Methodology: : A descriptive design, cross-sectional study was used for the present study was carried out
from 4th December, 2017 to the 4th April, 2018 in order to determine the association of Phantom
Vibration and Ringing Syndrome with Job - Related Stress among nurses at Teaching Hospitals in AlNasiriyah
City , on a purposive (non-probability) sample was used in t