One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

Evaluation of the Antibacterial Efficacy of Electrolyzed Oxidizing Water as an Irrigant against Enterococcus faecalis (An In vitro Study), Noor A Khait*, Muna Saleem Kalaf

This study aimed at identifying how children express the emerging coronavirus in general and according to their age groups (4-13 years) by analyzing 91 of their drawings published online, using the descriptive content analytical approach. The results showed that children's artistic expression of the virus came according to the concepts and ideas they carried about the virus for the age groups of (4-7 years) and (7-9 years), while it came according to visual perception for age groups (9-11 years), and from (11-13) years. Also, most children were aware about the presence of the virus and its widespread around the world, but (99%) of them do not realize the seriousness of the virus. It was confirmed that between (25-34%) of children were su

Background: There is a significant molecular response to imatinib given at standard doses in individuals with chronic myeloid leukemia (CML) whose ABCB1 polymorphisms are present. Objective: To investigate the impact of the polymorphism in the ABCB1 gene rs1128503 on the effectiveness of nilotinib or imatinib therapy. Methods: From May 2022 until the end of January 2023, the current study was carried out in a single research institution, the National Center of Hematology, Baghdad Teaching Hospital at Medical City, Iraq. 76 people with chronic phase myeloid leukemia (CML-CP), who had previously received a diagnosis using the European Leukemia Net (ELN) criteria, enrolled in the trial. The PCR product was delivered to Macrogen Corpora