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

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

In this paper the method of singular value decomposition  is used to estimate the ridge parameter of ridge regression estimator which is an alternative to ordinary least squares estimator when the general linear regression model suffer from near multicollinearity.

Background: The bonded orthodontic retainer constructed from multistrand wire and composite is an efficient esthetic retainer, which can be maintained long-term. Clinical failures of bonded orthodontic retainers, most commonly at the wire/composite interface, have been reported. This in vitro investigation aimed to evaluate the tensile forces of selected multistrand wires and composite materials that are available for use in the construction of bonded fixed retainers. Materials and Methods: The study sample includes 120 wires with three types of retainer wires (3 braided strands\ Orthotechnology, 8 braided strands\ G&H Orthodontics, 6 coaxial strands\ Orthoclassic wires), two types of adhesive (flowable\ Orthotechnology, non flowable\ G&H O

Background: Mini implant stability is primarily related to local bone density; no studies have evaluated bone density related to mini implant placement for orthodontic anchorage between different age groups in the maxilla and the mandible. The present research aims to evaluate side, gender, age, and regional differences in bone density of the alveolar bone at various orthodontic implant sites. Materials and method: Fifty three individuals who were divided into two groups according to their age into: group I (ages 16-20 years) and group II (ages 21-29 years) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 102 points (51 in the maxilla

The topological indices of the "[(µ3-2, 5-dioxyocyclohexylidene)-bis ((2-hydrido)-nonacarbonyltriruthenium]” were studied within the quantum theory of atoms in the molecule (QTAIM), clusters are
analyzed using the density functional theory (DFT). The estimated topological variables accord with prior
descriptions of comparable transition metal complexes. The Quantum Theory of Atom, in molecules
investigation of the bridging core component, Ru3H2, revealed critical binding points (chemical bonding)
between Ru (1) and Ru (2) and Ru (3). Consequently, delocalization index for this non-bonding interaction
was calculated in the core of Ru3H2, the interaction is of the (5centre–5electron) class.

Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.

Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.

This study is conducted to verify the efficienecy of local Ninivite rock when used in the treatment of drinking water in plants operating currently in the country in order to develop the situation of these stations to cope with the increase in population. Also, this will limit the pollutian which are increasing in the country's rivers.

(Euphrates and Tigris). These rivers are the sources to feed all water treatment plants in the country. The idea is the develop or the modify these stations by replacing part of top layer of sand filters used in these stations with Ninivite rock to operate as filters composed of two medium. The efficiency of this rock is compared with other materials used successfully worldwide in this area, such a