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

Background: Although the new treatment methods developed in recent years are aiming to minimize the need for cooperation of the patients; however, the latter still important factor the treatment. The aim of the study was to evaluate the cooperation level of Class III maloc-clusion patients with orthodontic treatment. Materials and methods: This study followed a cross-sectional style; the targeted population was patients with Class III malocclusion who were treated with three different types of orthopaedic appliances. Four questionnaires were delivered to the patient, patient’s parents, and orthodontists. Statistical analyses of the study were performed with SPSS 20.0 software. Descriptive analyses were presented using fre-quency, percenta

The history of the arts is closely connected with the history of humankind, since it is impossible to separate our scientific and artistic advances’. Therefore, the current research focuses on the close bond between art and other disciplines. The connection of the arts to the sciences is unequivocal and undisputed; the contributions of artists to the various scientific domains are clear. If one scrutinises the ability of artists to participate in building societies, one will find that the arts have penetrated deeply into a range of products and inventions, starting with the pencil and ending with the missile. The artist’s contributions play a part in the minutest of details across all fields of industry: production, craftsmanship, me

This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d

Rutting in asphalt mixtures is a very common type of distress. It occurs due to the heavy load applied and slow movement of traffic. Rutting needs to be predicted to avoid major deformation to the pavement. A simple linear viscous method is used in this paper to predict the rutting in asphalt mixtures by using a multi-layer linear computer programme (BISAR). The material properties were derived from the Repeated Load Axial Test (RLAT) and represented by a strain-dependent axial viscosity. The axial viscosity was used in an incremental multi-layer linear viscous analysis to calculate the deformation rate during each increment, and therefore the overall development of rutting. The method has been applied for six mixtures and at different tem