Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

This paper studies the effects of stiffeners on shear lag in steel box girders with stiffened flanges. A three-dimensional linear finite element analysis using STAAD.Pro V8i program has been employed to evaluate and determine the actual top flange stress distribution and effective width in steel box girders. The steel plates of the flanges and webs have been modeled by four-node isoparametric shell elements, while the stiffeners have been modeled as beam elements. Different numbers (4, 8, and 15) for the steel stiffeners have been used in this study to establish their effects on the shear lag and longitudinal stresses in the flange. Using stiffeners reduced the magnitude of the top flange longitudinal stresses about 40%, but did

Due to the broad range uses of chromium for industrial purposes, besides its carcinogenic effect, an efficient, cost effective removal method should be obtained. In this study, cow bones as a cheap raw material were utilized to produce active carbon (CBAC) by physiochemical activation, which was characterized using: SEM to investigate surface morphology and BET to estimate the specific surface area. The best surface area of CBAC was 595.9 m²/gm which was prepared at 600 ^ᵒC activation temperature and impregnation ratio of 1:1.5. CBAC was used in aqueous chromium ions adsorption. The investigated factors and their ranges are: initial concentration (10-50 mg/L), adsorption time (30-300 min), temperature (20-50

Electronic properties including (bond length, energy gap, HOMO, LUMO and density of state) as well as spectroscopic properties such like infrared, Raman scattering, force constant, reduced mass and longitu- dinal optical mode as a function of frequency are based on size and concentration of the molecular and nanostructures of aluminum nitride ALN, boron nitride BN and AlxB7-XN7 as nanotubes has calculated using Ab –initio approximation method dependent on density functional theory and generalized gradient approximation. The geometrical structure are calculated by using Gauss view 05 as a complementary program. Shows the energy gap of ALN, BN and AlxB7-XN7 as a function of the total number of atoms , start from smallest molecule to reached

This research deals with the most important indicators used to measure the phenomenon of financial depth, beyond the traditional indicators, which are called quantitative indicators, which is shown to be inadequate to show the facts accurately, but it may come in the results of a counterfactual, although reliable in econometric studies done in this regard.

Therefore, this research has sought to put forward alternative indicators, is the structural indicators, and financial prices, and availability of financial instruments, and cost of transactions concluded, in order to measure the phenomenon of financial depth.

After using and analyzing data collected from countries the research

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet