In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Cervical ectropion is considered to be a physiologic condition caused by columnar epithelium migration from the cervical canal into the vaginal portion of the cervix and usually there is no treatement for clinically asymptomatic cervical ectropion . Treatment can be achieved by thermal cauterization (Electrocautery), Cryosurgery or laser vaporization. Aim of the study: To study the effectiveness of CO2 laser (10600nm) in treatment of symptomatic cervical ectropion . Setting: The study was carried out at Laser Medicine Research Clinic at the Institute of Laser for Postgraduate Studies, University of Baghdad between the first of August 2013 to the end of October 2013. Patients and Methods: Ten female Patients with age range between 25-48 y

In this research the researcher had the concept of uncertainty in terms of types and theories of treatment and measurement as it was taken up are three types of indeterminacy and volatility and inconsistency

The study focused on the treatment of real oilfield produced water from the East Baghdad field affiliated to the Midland Oil Company (Iraq) using an oil skimming process followed by a coagulation/flocculation process for zero liquid discharge system applications. Belt type oil skimmer was utilized for evaluating the process efficiency with various operating conditions such as temperature (17-40 °C) and time (0.5-2.5 hr.). Polyaluminum chloride (PAC) coagulant and polyacrylamide (PAM) flocculant was used to investigate the performance of the coagulation/flocculation process with PAC dosage (5-90 ppm) and pH (5-10) as operating conditions. In the skimming process, the oil content, COD, turbidity, and TSS decreased with an increase in tempera

One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried