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 behavior. A total of seven deep beam specimens with identical shear span-to-depth ratio, compressive strength of concrete, and amount of horizontal and vertical web reinforcement ratios have been tested under mid-span concentrated load applied monotonically until failure. The main variables studied were the effects of depth of the web openings and the prestressing location on deep beam performance. The test results showed that the enlargement in the size of web openings substantially reduces the element’s shear capacities while prestressing strands location above the web openings has more effect at increasing the element’s shear capacities. The numerical study considered three-dimensional finite element models that have been developed in Abaqus software to simulate and predict the performance of prestressed deep beams. The results of numerical simulations were in good agreement with the experimental ones.
Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po
This investigation presents an experimental and analytical study on the behavior of reinforced concrete deep beams before and after repair. The original beams were first loaded under two points load up to failure, then, repaired by epoxy resin and tested again. Three of the test beams contains shear reinforcement and the other two beams have no shear reinforcement. The main variable in these beams was the percentage of longitudinal steel reinforcement (0, 0.707, 1.061, and 1.414%). The main objective of this research is to investigate the possibility of restoring the full load carrying capacity of the reinforced concrete deep beam with and without shear reinforcement by using epoxy resin as the material of repair. All be
... Show MoreDiabetic 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
... Show MoreThis research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3
... Show MoreThis paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark
... Show MoreA phosphorus‐containing Schiff base was prepared from bis{3‐[2‐(4‐amino‐1,5‐dimethyl‐2‐phenylpyrazol‐3‐ylideneamino)ethyl]indol‐1‐ylmethyl}phosphinic acid and paraformaldehyde as a novel antibacterial compound. The reaction of the Schiff base ligand with VO(IV), Ni(II), Co(II), Cu(II), Zn(II), Cd(II), Hg(II), Pd(II) and Pt(IV) led to binuclear species of metal complexes, depending on the ratio of metal ion and ligand. The ligand and its complexes were investigated using elemental analysis, Fourier transform infrared, 1H NMR, 13C NMR, UV–visible and mass spectra, thermogravimetric analysis, conductivity measurements and thermal analysis. The results showed that the S
... Show MoreThe study of triples seeks to deal with the comprehensive nature of the Qur’an texts, and the choice fell on the trilogy of great torment, pain, and humiliation in the Noble Qur’an - an objective study, the title of this research, in which I tried to shed light on these terms, and the nuances between them, and in particular torment The eschatological terminology varied, which can be summed up in three terms, namely the great, the painful, and the offensive. The types of torment, the pain is the painful one that is described by the severity of pain and its horror, as for the humiliating punishment, it is that which humiliates the one who has fallen on it, and the diversity of torment is due to the diversity of sins.