In this work, a single pile is physically modeled and embedded in an upper liquefiable loose sand layer overlying a non-liquefiable dense layer. A laminar soil container is adopted to simulate the coupled static-dynamic loading pile response during earthquake motions: Ali Algharbi, Halabjah, El-Centro, and Kobe earthquakes. During seismic events with combined loading, the rotation along the pile, the lateral and vertical displacements at the pile head as well as the pore pressure ratio in loose sandy soil were assessed. According to the experimental findings, combined loading that ranged from 50 to 100% of axial load would alter the pile reaction by reducing the pile head peak ground acceleration, rotation of the pile, and lateral displacem

This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

This research concentrate on cultivated Iraqi Agave attenuata dried leaves and roots, because of little studies on this plant especially on the root that lead to the eager of study and comparison of phytochemical constituents between leaves and root. Extraction of bioactive constituents was carried out using several solvents with increasing polarity (n-hexane, ethyl acetate and methanol) by soxhlet apparatus. Steroidal saponins in Agave genus is well documented in many species, lightening the minds in this research on extraction method which is specific for steroidal saponins. Phytochemical screening was done by GC/MS for n-hexane fraction, qualitative and quantitative estimation of several bioactive constituents (caffe