Android operating system, since its first start, is growing very fast and takes a large space in smart devices market. It is built and developed on Linux and designed basically for touch screen devices such as, mobiles, tablets, etc. Mobile devices are markedly complicated and feature-rich; therefore they are prone to reliability of software and performance problems. Because of the small resources, smart devices, such as CPU, RAM, suffer from problems. One of these problems is Software Aging (SA). SA is recognized in long running OSs as a shortage in resources, performance retreating, and finally failure. SA is looked at from two sides, namely the poor response time of application which represents the end user side and the shortage in me

Background: Occult Hepatitis B virus infection (OBI) among blood donors is an important medical concern.
Objectives: This study was done to detect the presence of occult hepatitis B virus infections among blood donors with negative hepatitis B surface antigen and positive total anti-hepatitis B core antibodies in Hawler Major Blood Bank in Hawler city/Kurdistan Region of Iraq.
Methods: A total number of 12,185 blood donors in Hawler Major Blood Bank were screened for HBsAg and total anti-HBcAb using ELISA technique, and then positive results were retested by confirmatory technique by Chemiluminescence assay. All HBsAg-/HBcAb+ were selected as the study group; HBV DNA was tested among HBsAg-/HBcAb+ by conventional PCR and Real time-

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Background: Since declaring coronavirus disease 19 as a pandemic by the World Health Organization, a great concern was directed toward pregnant women and their fetuses. Despite the substantial impact of COVID-19 disease on pregnancy, there is a scarcity of national researches discussing this important issue.          

Objectives: To study the relationship between peripheral blood abnormalities and COVID-19 in pregnant women.

Patients and methods: A case control study was conducted in the labour wards of Baghdad Teaching Hospital in the Medical complex / Baghdad /Iraq during the period from 1^st of February till 31^st of July, 2021. Fifty pregna

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

Abstract

This research aims to assess the practice of physical activities by people with intellectual disabilities and its challenges during the Coronavirus (COVID-19) pandemic from their families' point of view. The research sample consisted of (87) individuals from families with intellectual disabilities in the Makkah region. The sample was selected by the simple random method where the researcher used the descriptive analytical approach. A questionnaire of (32) items was used as the research tool to collect data. The findings of the study showed that the assessment level of practicing physical activities by people with intellectual disabilities was low. The public facilities dimension ranked first with a moder