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

       In this paper, a fixed point theorem of nonexpansive mapping is established to study the existence and sufficient conditions for the controllability of nonlinear fractional control systems in reflexive Banach spaces. The result so obtained have been modified and developed in arbitrary space having Opial’s condition by using fixed point theorem deals with nonexpansive mapping defined on a set has normal structure. An application is provided to show the effectiveness of the obtained result.

Background: Varicose vein (VV) is a common problem that mostly occurs in legs. This medical condition can influence the quality of life and working condition of nurses. Aim of the study: To estimate the prevalence of lower limbs varicosity and its associated risk factors among nurses. Methods: This a cross-sectional descriptive study was carried out among 100 nurses working Baghdad Teaching Hospital, Surgical Specialties Hospital, and Al- Kidney Teaching Hospital, Baghdad, Iraq from January 1st to May 10th, 2022. The participants were recruited in the study using systematic random sampling. The Occupational Sitting and Physical Activity and Aberdeen Varicose Vein Questionnaires were used for data gathering. Results: The prevalence o

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

Two nanocomposite corrosion inhibitors were synthesized from Aloe vera extract: one incorporating sodium thiosulfate and the other silver nitrate. Both nanocomposites were subjected to structural characterization using atomic force microscopy (AFM), which revealed distinct morphological features. The sodium thiosulfate-based nanocomposite exhibited uniform and well-dispersed nanoparticles with an average size of 47.51 nm, suggesting a stable and homogeneous distribution. In contrast, the silver nitrate-based nanocomposite displayed slightly larger particles with an average diameter of 58.34 nm, indicating a tendency toward moderate aggregation. The corrosion inhibition performance of these nanocomposites for carbon steel (CS1137) was invest

This research aims to explain the effect of the imported inflation (which moves through the raise of global prices to Iraqi economy) over local prices, besides, the recognition the most important channels of imported inflation moving, its causes, effects, ways and policies that reduce the negative effects. To achieve the research aim, the deductive approach was adopted through using descriptive method to describe and determine phenomenon. The most important conclusion is that the research found out that there are two channels to transmission imported inflation in world. The first channel is the direct channel (prices) and the second channel is the indirect (income). The most important recommendation is to create sovereign fund (O

Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id