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

High-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods,

This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d

The purpose of this research is to a treatment the impact of Views outliers to the estimators of a distributed arrival and service to the theory of queues and estimate the distribution parameters depending on the robust estimators, and when he was outliers greatest impact in the process of estimating the both distributions mentioned parameters, it was necessary to use way to test that does these data contain abnormal values ​​or not? it was used the method ( Tukey ) for this purpose and is of the most popular ways to discover the outliers , it shows that there are views abnormal (outliers ) in the estimators of each of the distributional arrival and service, which have a significant impact on the calculation of these estimato

Abstract Background: Multidrug-resistant bacteria (MDR) often contaminate hospital environment and cause serious illnesses. Quorum Sensing (QS) regulates a variety of downstream cellular processes, including antibiotics resistance mechanisms and biofilm formation, and causes harm to the host. This study investigates antibacterial susceptibility and biofilm formation of pathogenic bacteria in hospital environment. Methods: Hundred bacterial isolates were collected from various environments in the Medical City hospital. The antimicrobial susceptibility technique was evaluated through disk diffusion method. Next, biofilms formation was detected by the microliter plate assay. Finally, PCR was used to analyze the frequency of QS system gene

Pulsed-laser deposition (PLD) technique was used to prepare thin films from cerium oxide (CeO2) doped with erbium and indium oxides. In order to characterize the morphology and sensing features, these films were deposited on glass and/or single silicon substrates, respectively, with erbium and indium oxides. The morphological investigation conducted using atomic force microscope has shown an increase in the non-regularity of particle diameter with increasing doping ratios of both oxides. The maximum particle diameter of 61.45nm was obtained for 9% Eu2O3-doped CeO2. The surface roughness value of Eu2O3-doped ceria was higher than those of In2O3-doped ceria. The gas sensing measurements were done at

This assay rapidly detects chlorpromazine hydrochloride using its ability to reduce gold ions to form nanoparticles. Its low cost, resilience to interferences and short analysis time could facilitate environmental monitoring and biomedical analysis.