Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

        End Stage Renal Disease is a well-known global public health problem. Maintenance hemodialysis is considered a life-saving treatment for patients with such disease. This treatment method that requires patients to be adherent to hemodialysis attendance, dietary and fluid recommendations as well as adherence to prescribed medications to ensure success. The aim of the current study was to assess adherence, perception, and counseling among hemodialysis patients to different modalities of treatment (fluid restriction, dietary recommendations, medications, and hemodialysis schedules). A cross-sectional study carried out on hemodialysis patients who attended to the dialysis centers at al- Karama teachi

The present study investigated the total content of phenolic compounds, antioxidant and antimicrobial activities of water extracts oat (Avena sativa) and basil (Ocimum basilicum), medicinal plants. The Folin-ciocalteu reagent assay was used to estimate the total phenolic content of plants extract. The antioxidant capacity of the plants extract was tested by ferric reducing/antioxidant power Assay (FRAP) and ferric reducing scavenging activity using DPPH method, and the antimicrobial activity was measured against [Staphylococcus epidermidis; Staphylococcus aureus; Proteus spp.; Klebsiella spp.; Escherichia coli; Candida albicans] as tester strains. The total phenolic content of Avena sativa and Ocimum basilicum extracts revealed that the

Background: Placenta is a chief cause of maternal and perinatal mortality and significant factor in fetal growth retardation. It undergoes different variations in weight, volume, structure, shape and function continuously throughout the gestation tosupport the prenatal life. Cautious examination of placenta can give information which can be useful in the management of complications in mother and the newborn. Objective: The present work has been attempted towards determination of the morphological ( macroscopic and microscopic) parameters of human full-term placentae and their relation with different parity and age group of mothers. Patients and Methods: A whole of 40 placentae were recently collected.They were divided into four groups