<span lang="EN-US">Deep learning is currently playing an important role in image analysis and classification. Diseases in maize diminish productivity, which is a major cause of economic damages in the agricultural business throughout the world. Researchers have previously utilized hand-crafted characteristics to classify images and identify leaf illnesses in Maize plants. With the advancement of deep learning, researchers can now significantly enhance the accuracy of object classification and identification. Using the "Corn or Maize Leaf Disease Dataset" from the Kaggle website, four forms of maize leaf diseases were investigated: blight, common rust, gray leaf spot, and healthy. The pictures obtained from these corn leaf illnesses are categorized using four deep convolutional neural network (CNN) models that have been pre-trained (GoogleNet, AlexNet, ResNet50 and VGG16). Accuracy, precision, specificity, recall, F-score, and time are the six metrics used to assess the performance of any transfer learning (TL) model. MATLAB programming software is used to design and train the TL models. The accuracy of each item in the dataset has been checked. It has been determined that GoogleNet, AlexNet, VGG16, and ResNet50 each have an accuracy of 98.57%, 98.81%, 99.05%, and 99.36%, respectively.</span>
The inclination effect on the concrete column decrease confinement.• There are certain angles that we can adopt in the design of inclined columns to avoid reducing confinement. • The use of high strength concrete contributes greatly to avoiding the reduction of confinement in the inclined columns.The main objective of this paper is to study the confinement of the rectangular reinforced concrete short inclined columns. This paper was based on theoretical analysis using the MATLAB program according to Universal Codes, and variables that were carefully selected to be the most influential factor. The angle of the inclination (α) was taken as a major variable in the paper, in addition other variables which in turn affect directly on the behavior of inclined columns such as the percentage of reinforcing steel in the concrete section of the column (ρ), the compressive strength of the concrete (fʹc), yield strength of steel bars (fy) and effective depth ratio (γ). The results show that best ratio of reinforcing steel that improves the value of the confinement ranges from 0.4 -0.6 which leads to an increase in the confinement of (60 -100) %, and these rates increase with increasing α, and the increase in fʹc leads to a significant increase in the confinement, especially when HSC is used..On the other hand, decreasing fy leads to increase in confinement, and the value of the γ had a considerable effect on the confinement that was decreased by about 11% when γ equals 0.9, compared with the corresponding γ equals 0.6.
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