This study aims to clarify areas of using information technology in accounting and its impact on the profession of auditors by reviewing the concept, types, areas and the importance of information technology and its implications on the audit profession as well as to clarify the extent of contribution of information technology in  developing of procedures of the audit profession and what its requirement, also this study aims to enhance the theoretical side by identifying the views of a sample of auditors in  Arab countries selected (Iraq, Syria, Jordan), for the extent of using of information technology in their work and level of their perception for the importance of that

Abstract:

     This study aims to identify the level of patients’ satisfaction among a sample of hospitalized patients in the targeted hospital (Al-Kindy Teaching Hospital, and Al-Yarmook Teaching Hospital). Moreover, this study highlights the reality of services for patients, especially in the targeted governmental teaching hospitals. The Patient Satisfaction with Nursing Care (PSNCS) has been measured in these hospitals through the revised scale by Tang et al, (2013).This scale includes four major domains; Health Information (5 items), Influencing Support (4 items), Decision Control (4 items), Specialized Technical Competence (7 items). The method of surveying patients’ opinions about the degree

There is a global shortage of health care providers needed to address all levels of primary and specialty care.  The recent COVID-19 pandemic also highlights the importance and added value of health professionals with specialty training in infectious diseases.  In the United States, advanced practice providers (APPs) are being engaged to meet the expanding demand for generalist and specialist patient care.  The history and development of advanced practice registered nurses (APRNs) and physician assistants (PAs), are discussed as collaborative healthcare providers to promote better understanding of the ways they can be incorporated into a healthcare system.  An example of how APPs are utilized to provide both inpatient and outpatient

المستودع الرقمي العراقي. مركز المعلومات الرقمية التابع لمكتبة العتبة العباسية المقدسة

field of modern and contemporary Yemeni history, accomplished at Ibn Rushd College of Education, University of Baghdad. It was determined according to a time frame in the years 1989, which is the date of completion of the first master’s thesis in the field of modern and contemporary Yemeni history, which deals with the subject of “Iraqi-Yemeni relations 1932- 1962”, and the year 2020, which is the year of completion of a master’s thesis on the position of Iraqi public opinion on the Egyptian military intervention in Yemen (1962-1970). The study determined the nature of these studies, whether they were in the form of master’s theses or doctoral dissertations, or research and studies published in issues of the refereed scien

In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τ_i ) which  has

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K