Abstract

The current research aims to identify the attitudes towards the Covid-19 vaccine and the Locus of Control (internal, external) among university students, to identify the significance of the difference in attitudes towards the Covid-19 vaccine, the significance of the difference in the Locus of Control (internal, external) according to the gender variable (male, female), and to identify the significance of the difference in students’ attitudes towards Covid-19 vaccine according to the Locus of Control (internal, external). To achieve the objective of the research, the researcher developed two scales, a scale of (20) items to identify the attitudes toward a covid-19 vaccine, and a scale of the locus of c

Abstract

This study identified the developing of a range of students' geography learning skills and the change in their attitudes toward fieldwork as a consequence of leaning experiences that occurred within a field trip. The sample of the study consisted of (27) students within a special topic course enrolled in Geography Department at Umm Al-Qura University in Saudi Arabia in semester 2, 2018. A range of students' geography learning skills were measured by the skills questionnaire that consisted of 12 geography skills after completing field work. Changes in students' at

Abstract:

     The research aims to shed light on the Corona pandemic and its repercussions on the global economy in general, and on the activities of Iraqi economic units in particular. It also aims to show the impact of the auditor’s reporting on the effects of the Corona pandemic on economic units and its reflection on the quality of his reporting. To achieve the objectives of the research, the researcher prepared a questionnaire according to the five-point Likert scale and took into account in its preparation compatibility with the characteristics of the study community, and that the target community for this questionnaire are the economic units listed in the Iraq Stock Exchange that have complet

Emergency contraceptives (ECs) are indicated for preventing the chance of unintended pregnancy that follows unprotected sexual intercourse in cases of incorrectly used regular contraceptives and in sexual assault. It is considered a safe choice to prevent pregnancy than abortion which is considered life threating. The aim of this study was to assess knowledge, attitude, and practices (KAP) of community pharmacists towards emergency contraceptives and their association with sociodemographic variables. This study was a cross sectional study conducted between August and September 2021 on a convenient sample of community pharmacists from Iraq. The survey tool was an online, self-administered questionnaire, in English language and a paper-bas

Factor analysis is distinguished by its ability to shorten and arrange many variables in a small number of linear components. In this research, we will study the essential variables that affect the Coronavirus disease 2019 (COVID-19), which is supposed to contribute to the diagnosis of each patient group based on linear measurements of the disease and determine the method of treatment with application data for (600) patients registered in General AL-KARAMA Hospital in Baghdad from 1/4/2020 to 15/7/2020. The explanation of the variances from the total variance of each factor separately was obtained with six elements, which together explained 69.266% of the measure's variability. The most important variable are cough, idleness, fever, headach

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings