Contents IJPAM: Volume 116, No. 3 (2017)

       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

Total Quality Assurance Concept have appeared in Higher Education Institutions as a result of the continuous criticism for the lower quality of the outputs of these institutions and their inappropriacy to the needs of the job market. The faculty, i.e. teaching staff member, is one of the most important output for his/her responsibility to achieve the stated goals in higher education. This represents a problem that may influence the construction of society which has to limit his tasks, responsibilities, and competencies that should be found in a faculty, and evaluating his teaching profession in light of the prerequisites of the century to become an input to achieve quality assurance in Higher Education. Therefore, the present study aims

In the present time, radioactive contamination is considered one of the most dangerous types of environmental pollution. It usually takes place because of a leakage of radioactive materials to one of the environment natural components, such as, water, air, and soil. Iraq is considered one of the most contaminated environments in the world; this is closely associated with the wars Iraq had suffered from; especially, in 1991 and 2003. Considering the importance of the radioactive contamination and its different health impacts on the population, the current paper is interested in studying this type of environmental contamination and its impact on the birth defects depending on the data available in the annual reports issued by the Iraqi min

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

Background: Hyperlipidemia is an elevated fat (lipids), mostly cholesterol and triglycerides, in the blood. These lipids usually bind to proteins to remain circulated so-called lipoprotein. Aims of the study: To determine taste detection threshold and estimate the trace elements (zinc) in serum and saliva of those patients and compare all of these with healthy control subjects. Methods: Eighty subjects were incorporated in this study, thy were divided into two groups: forty patients on simvastatin treatment age between (35-60) years, and forty healthy control of age range between (35-60) years. Saliva was collected by non-stimulated technique within 10 minutes. Serum was obtained from each subject. Zinc was estimated in serum and saliva