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

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

Objective: The aim of the research is to prepare skilled mental exercises according to spatial and temporal perceptions and the awareness of the strength of young pole-vaulters, and to recognize the impact of these exercises on improving the indicators of electrical activity of working muscles and some special physical abilities and accomplishing this effectiveness Research methodology: The researcher used the experimental curriculum (one experimental group), and included the sample of research on (5) two joint jumpers in the Iraqi club championship, all from the center of talent in athletics, the sample is trained on the same curriculum prepared by the coach himself but accompanied by a mental training approach that Prepared by the

Background: Listeria monocytogenes, a member of the genus Listeria, is widely distributed in agricultural environments, such as soil, manure and water. The genus of Listeria bacteria is about 15-17 species. It is a pathogenic bacterium that can cause a rare but dangerous infection called listeriosis.

Objectives: Studying the rate of salads contaminated with Listeria bacteria. and Listeria monocytogenes according to International, Arabic and Iraqi specifications and finding the correlation between commitments of restaurants to standard health conditions with contamination with these bacteria

Methods: The study included

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

Titanium alloy (Ti-6Al-4V or Gr.23) was widely used as a dental alloy. In the current study, polymerization of eugenol (PE) on Gr.23 titanium alloys was conducted by an electrochemical process before and after being treated by Micro Arc Oxidation (MAO). The formed films were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). The corrosion behavior of Gr.23 alloy in an artificial saliva environment at a temperature range of 293–323 K has been studied and assessed by means of electrochemical polarization and impedance spectroscopy techniques. Three cases are taken into consideration; bare Gr.23, Gr.23 coated by PE, and Gr.23 coated by PE after MAO treatment. The maxi