Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

     This work includes the synthesis of new ester compounds containing two 1,3,4-oxadiazole rings, 15a-c and 16a-c. This was done over seven steps, starting with p-acetamido-phenol 1 and 2-mercaptobenzoimidazole 2. The structure of the products was determined using FT-IR, 1H NMR, and mass spectroscopy. The evaluation of the antimicrobial activities of some prepared compounds was achieved against four types of bacteria (two types of gram-positive bacteria; Staphylococcus aureus and Bacillus subtilis, and two types of gram-negative bacteria, Pseudomonas aeruginosa and E. Coli), as well as against one types of fungus (C. albino). The results show moderate activit against the study bacteria, and the theoretical analysis of the toxi

The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits

Many new heterocyclic compounds including 4-thiazolidinones containing indole with triazole units were described. The new Schiff bases [VII] a, b and [VIII] a, b synthesized by condensation acid hydrazides [II],[VI] with different (aromatic) aldehydes in absolute ethanol. The refluxing equimolar amounts of the Schiff bases ([VII] a, b,[VIII] a, b) with thioglycolic acid in benzene led to get thiazolidin-4-ones derivatives ([IX] a, b and [X] ad). Finally, the new derivatives [XI] ac run out via the reacted compound [IX] a with different n-alkyl bromide (methyl bromide, ethyl bromide, and butyl bromide)

 Three of imide intermediate products  were synthesized by reacting of phthalic anhydride with glycine (2a), and tetrachloro phthalic anhydride with glycine , (S)-2-[(tert-Butoxycarbonyl)amino]-3-aminopropionic acid ( 2b,c)  respectively   in  dry toluene  with azeotropic removal of water using Dean- stark apparatus then carboxyl functional group activated by refluxing with  thionyl chloride, the resulted acid chloride (3a-c) were reacted with different amine (5-flourouracil, 4-chloroaniline, 4-bromoaniline, 2-amino thiazole, and pyrrolidine) (4a-e) , the   resulted products consider as