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

This work studies the role of serum apelin-36 and Glutathione S-transferases (GST) activity in association with the hormonal, metabolic profiles and their link to the risk of cardiovascular disease (CVD) in healthy and patients' ladies with polycystic ovary syndrome (PCOS). A total of fifty-four (PCOS) patients and thirty-one healthy woman as a control have been studied. The PCOS patients were subdivided on the basis of body-mass-index (BMI), into 2-subgroups (the first group was obese-PCOS with BMI ≥ 30 and the second group was non-obese PCOS MBI<30). Fasting-insulin-levels and Lipid-profile, Homeostatic-model assessment-of-insulin-resistance (HOMA-IR), follicle-stimulating-hormone (FSH), luteinizing-hormone (LH), testosterone and

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

     Vitiligo is a common depigmenting skin disorder classified as an autoimmune ailment. It is linked to immune mechanisms, oxidative stress, and disturbances in the cellular environment. Among the factors contributing to histological changes, proteolytic enzymes such as collagenase stand out, due to their role in degrading components of the extracellular matrix. Prolidase is a key enzyme in collagen metabolism, involved in the breakdown of proline-rich peptides. Objective: This study aims to investigate the mechanism of collagen decline in Iraqi vitiligo patients, prolidase activity and basic homeostasis to understand their roles in disease progression. This study was conducted as a cross-sectional comparative study, and 150 p

أستهدفت الدراسة اختبار أثر التوجه السوقي والتزام العاملين على أداء المنظمة المسوقة لخدمات النقل الجوي. حيث تم اختيار شركة الخطوط الجوية الملكية الأردنية كمجال تطبيقي.وقد اعتمدت الدراسة في قياس المتغيرات على مقاييس مختبرة وقد تأكد صحتها وثباتها لقياس المتغيرات في البيئة الحالية.  وقد بينت نتائج التحليل الإحصائي الذي استخدمت فيه أساليب إحصائية مختلفة بالاستعانة ببرنامج SPSS))

This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

Abstract
The research hypothesizes is that the external Environment
has the responsibility concerning decisions making and behavioral
upon industrial firms. It is, Furthermore, an attempt to review the
problem of closures of private industrial firms in the country, during
the period (1976-1985), i.e. prior to and during the Iraqian- Iranian
war.
The behavioral approach of industrial geography has been
adopted as a theoretical background and the statistical test has
been practiced for the applied purposes.
As result, the research comes out with suggestions,
depending upon previous trials in the field of direction and
formulation of the of the private industrial sector. The chief point
among th

This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r

Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in