This research is presented experimental and numerical investigations of composite concrete-steel plate shear walls under axial loads to predicate the effect of both concrete compressive strength and aspect ratio of the wall on the axial capacity, lateral displacement and axial shortening of the walls. The experimental program includes casting and testing two groups of walls with various aspect ratios. The first group with aspect ratio H/L=1.667 and the second group with aspect ratio H/L=2. Each group consists of three composite concrete -steel plate wall with three targets of cube compressive strength of values 39, 54.75 and 63.3 MPa. The tests result obtained that the increase in concrete compressive strength results in increasing

In this research, the use of natural materials like wool and cannabis as intermediate reinforcement for prosthetic limbs due to their comfort, affordability, and local availability was discussed. As part of this study on below-the-knee (BK) prosthetic sockets, two sets of samples were made using a vacuum method. These sets were made of natural fiber-reinforced polymer composites with lamination 80:20: group (Y) had 4 perlon, 1 wool 4 perlon, and group (G) had 4 perlon, 1 cannabis 4 perlon. The two groups were compared with a socket made of polypropylene. Tensile testing was used to determine the mechanical characteristics of the socket materials. The Y group has a yield stress of 17 MPs, an ultimate strength of 18.75 MPa, and an elastic

Background: Poly (methyl methacrylate) has been widely utilized for fabrication of dentures for many years as it has good advantages but not achieved all demands of the mechanical properties such as low transverse strength, low impact strength, low surface hardness, high water solubility and high water sorption. Material and method: To provide bonding between ZrO2 nanoparticles and PMMA matrix, the ZrO2 Nano-fillers were surface-treated with a saline coupling agent. Plasma surface treatment of polyethylene (PE) fiber was done to change surface fiber by using DC- glow discharge system. For characterization of interring any functional groups, the (FTIR) spectrum were done .then the mechanical properties studied to choose the appropriate perc

This research presents an experimental investigation of the rehabilitation efficiency of the damaged hybrid reinforced concrete beams with openings in the shear region. The study investigates the difference in retrofitting ability of hybrid beams compared to traditional beams and the effect of two openings compared with one opening equalized to two holes in the area. Five RC beams classified into two groups, A and B, were primarily tested to full-failure under two-point loads. The first group (A) contained beams with normal weight concrete. The second group (hybrid) included beams with lightweight concrete for web and bottom flange, whereas the top flange was made from normal concrete. Two types of openings were considered in this s

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

         This study involves the design of 24 mixtures of fiber reinforced magnetic reactive powder concrete containing nano silica. Tap water was used for 12 of these mixtures, while magnetic water was used for the others. The nano silica (NS) with ratios (1, 1.5, 2, 2.5 and 3) % by weight of cement, were used for all the mixtures. The results have shown that the mixture containing 2.5% NS gives the highest compressive strength at age 7 days. Many different other tests were carried out, the results have shown that the carbon fiber reinforced magnetic reactive powder concrete containing 2.5% NS (CFRMRPCCNS) had higher compressive strength, modulus of rupture, splitting tension, str

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network