Journal of Theoretical and Applied Information Technology is a peer-reviewed electronic research papers & review papers journal with aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of IT (Informaiton Technology

This study was conducted to investigate the presence of Staphylococcus aureus in the red and white meat available in local markets. They were selected ten samples of red and white meat randomly (Iraq, Saudi Arabia, Turkey, and Brazil) from different markets in Baghdad, and the results of reading the nutrition facts of media indication card showed that all models confirm to the Iraqi standard quality in terms of scanning all data of the media indication card, except for the birds of Bayader, where the date of expire & production date of the product was not mentioned. Also, the results of the study showed that there is no Staphylococcus aureus in local red and white meat as well as imported.

This work aims to introduce the concepts of left and right derivations in an AT-algebra and discuss some interesting theorems of these concepts. Also, a fuzzy derivation of an AT-subalgebra, a fuzzy right (left) derivation ideal, a fuzzy derivation of AT-subalgebra, and a fuzzy right (left) derivation ideal are studied. Finally, a level derivation of AT-algebras is defined and some propositions are achieved.

      The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc :  COVID-19 patients ( without vaccine ) , Gp₁: COVID-19 patients took one dose of Pfizer Biontech, Gp₂ : COVID-19 patients took two doses of Pfizer Biontech, Ga₁ : patients took one dose of AstraZeneca Oxford vaccine , Ga₂: patients took two doses of AstraZeneca Oxford vaccine , Gs₁ : patients took one dose of Sinopharm vaccine and Gs₂:

Ecological risk assessment of mercury contaminant has a means to analyze the ecological risk aspect of ecosystem using the potential impact of mercury pollution in soil, water and organism. The ecological risk assessment in a coastal area can be shown by mangrove zonation, clustering and interpolation of mercury accumulation. This research aims to analyze ecological risk assessment of potential mercury (including bioaccumulation and translocation) using indicators of species distribution, clustering, zonation and interpolation of mercury accumulation. The results showed that the Segara Anakan had a high risk of mercury pollution, using indicators like as the potential of mercury contaminant in water body was 0137±0.0137 ppm, substrate a

This research aims to shed light on the necessity of establishing an information security management system through which banking security risks are managed in the light of the ISO (IEC 27001) standard, through which bank departments seek to demonstrate the management of their security systems and their controls in accordance with the specifications of the standard to obtain an internationally recognized security certificate And the need for senior management in banks to an independent person with scientific and practical qualification and who has accredited certificates in the field of information technology for the purpose of helping them to verify the level of compatibility between the policies and procedures applied and the p

In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

Background: Endometrial Cancer (EC) is the malignant tumor originating from endometrium cell (lining of the uterus). EC incidence and mortality have increased in recent years. Routinely used methods for EC diagnosis and treatment are histopathological tissue culture after surgery and postoperative radiotherapy, however there is still not enough efficient treatment for recurrence or progression of this disease. So, there is a critical need for further EC identification by new biological ways for the prognostic diagnosis of it. Objective: This study aimed to look for ways by which could help in diagnosis of EC before the hysterectomy. Materials and Methods: 55 patients with EC and 57 healthy women were involved in this study (up to 45 years)