Background: Separation and deboning of artificial teeth from denture bases present a major clinical and labortory problem which affect both the patient and the dentist. The optimal bond strength of artificial teeth with denture base reinforced with nanofillers and flexible denture bases and the effect of thermo cycling should be evaluated. This study was conducted to evaluate and compare the shear bond strength of artificial teeth (acrylic and porcelain) with denture bases reinforced by 5% Zirconium oxide nanofillers and flexible bases under the effect of different surface treatments and thermo cycling and comparing the results with conventional water bath cured denture bases. Material and methods: Two types of artificial teeth; acrylic and

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

 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

Abstract 

In the present study, composites were prepared by Hand lay-up molding. The composites constituents were epoxy resin as a matrix, 6% volume fractions of glass fibers (G.F) as reinforcement and 3%, 6% volume fractions of preparation natural material (Rice Husk Ash, Carrot Powder, and Sawdust) as filler. Studied the erosion wear behavior and coating by natural wastes (Rice Husk Ash) with epoxy resin after erosion. The results showed the non – reinforced epoxy have lower resistance erosion than natural based material composites and the specimen (Epoxy+6%glass fiber+6%RHA) has higher resistance erosion than composites reinforced with carrot powder and sawdust  at 30cm , angle 60

سمير خلف فياض * و محسن طالب د.نوال عزت عبد اللطيف*, مجلة الهندسة والتكنولوجيا, 2010

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

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st