Different injection material types were tried in the injection of soft clay, such as lime (L), silica fume (SF), and leycobond-h (LH). In this study, experiments were made to study the effect of injection on soft clay consolidation settlement. A sample of natural soft clayey soil was investigated in the laboratory and the sample was injected with each of the grout materials used, L, SF, L + SF, and L + SF + LH. A 20 cm3 of each slurry grout was conducted into the soil, which was compacted in California Bearing Ratio (CBR) mold and cured for 7 days, and then the sample was loaded to 80 N load by a circular steel footing 60 mm in diameter. The settlement was r
The summary of this study is to identify the relation ship between exposuing of the
public to foreign satellites and the degree of cultural of Iraqi public . the danger Iraqi public
exposure to foreign satellite specially some groups of the public are still own limited culture
and ideology without enough conscious to attitude of society . such people cun easily be
controlled by satellites , because these satellites may be the only cultural source for them
which may badly affect their behaviour . This study also aims to identify the level of Iraqi
people exposure to foreign satellites and the types and motivations of that exposure , then to
realize the relationship between exposing to foreign satellites and the cultur
This work investigates experimentally the effect of using a skirt with a square foundation of 100 mm width resting on dry gypseous soil (i.e., loose soil with 33% relative density), and subjected to an inclined load. Previous works did not study the use square skirted foundation rested on gypseous soil and subjected to inclined load. The investigated soil was brought from Tikrit city with 59% gypsum content. Standard physical and chemical tests on selected soil were carried out. Model laboratory tests were carried out to determine the effect of using a skirt with a square foundation on the load-settlement behavior of gypseous soil and subjected to inclined load with various Skirt depth (Ds) to foundation width (B) ratio
... Show MoreRetinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th
Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for