Objective(s): The aim of this study is to assess the impact of social phobia upon self-esteem of nursing
collegians.
Methodology: A Cross-sectional study is carried out at University of Baghdad, Karkuk, Thi-Qar, and Kufa,
colleges of nursing from Feb 8
th
, 2011 to Sep. 25th, 2011. A sample of all first class nursing collegians (N=330)
were selected from a probability sample of nursing colleges by dividing Iraq to three geographical areas (South,
North, and Middle Euphrates) in addition to Baghdad. The data were collected through the use of selfadministered
technique as a mean for data collection, by using a questionnaire that consists of three parts:
First part was the socio-demographic data form; the second o

Objectives of the study: The study aims to assess satisfy of the coronary artery patients for the care product from
the nurse and physician and to find out the relationship between patient satisfaction with the social and the
clinical characteristics of the patients.
Methodology: A descriptive design study conducted using the evaluation approach for the duration of June 3
rd
2012 to January 31, 2013. Non-probability sample of (60) patients who were visiting or admitted (inpatient or
outpatient) to the teaching hospital in Baquba with the diagnosis of coronary artery disease. A questionnaire have
been built and develop by the researcher based on review of literature and previous research, the form included of
(3) p

Objectives: ٨ descriptive study has been conducted in the premature baby unit in Al-Khansaa' and Al-Batool
hospitals for maternity and children in Mosul city to assess knowledge and practice of the nursing staff in the
caring of premature infants. A descriptive study has been conducted in the premature baby unit in Al-Khansaa'
and Al-Batool hospitals for maternity and children in Mosul city to assess knowledge and practice of the nursing
staff in the caring of premature infants.
Methodology: the data were collected by using knowledge assessment and practice measurement tool.
Results: the results of the study show that high percentages (about 40%) of the staff who work in the premature
baby units are of the young age

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

Background: Cardiopulmonary resuscitation (CPR) is a technique or procedure that combined chest compression and rescue breathing to maintain enough circulation that prevents brain damage until other essential steps are taken to control the main cause of cardiac and respiratory arrest. The health care personnel should be qualified in the performing of cardiopulmonary resuscitation (CPR) to improve the survival rate of the victims. Therefore; it is necessary to use new methods for learning [1]. Objectives: the study aims to compare the effectiveness of self-instructional teaching strategy and traditional teaching approach on student’s knowledge toward cardiopulmonary resuscitation. Methods: A randomized comparative trial (RCT) design was ca

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d