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

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 and identification of ligand {3-((4-acetylphenyl)amino)-5,5-dimethylcyclohex2-en-1-one} (HL* ) by the treatment of 5,5-dimethylcyclohexane-1,3-dione with 4-aminoacetophenone under reflux. The ligand (HL* ) was identified via FTIR, Mass spectrum, elemental analysis (C.H.N.), 1H and 13C-NMR spectra, UV-Vis spectroscopy, TGA and melting point. The complexes were synthesized from ligand (HL* ) mixed with 3-aminophenol (A) and metal ion M(II), where M(II) = (Mn, Co, Ni, Cu, Zn and Cd) at alkaline medium to produce complexes of general formula [M(L* )(A)] with (1:1:1) molar ratio. These complexes were detected via FT-IR spectra, UV-Vis spectroscopy as well as elemental analysis (A.A) and melting point, conductivit

The Russian foreign policy of the post-cold-war era faced dilemmas in the light of the international and regional realities of the disintegration of the Soviet Union and the formation of a new unipolar international order led by the United States of America. Thus, Russian foreign policy-making was divided over the nature of the foreign policy to be followed. The achievement of the Russian goals, especially as the objectives of Russian foreign policy have been set within the framework of trying to regain the status and leading role, as well as the establishment of some fundamental changes to be consistent with the new international situation of the post-one The Russian Federation has adopted in the sphere of its foreign policy to the vari

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

Four Co(II), (C1); Ni(II), (C2); Cu(II), (C3) and Zn(II), (C4) chelates have been synthesized with 1-(4-((2-amino- 5‑methoxy)diazenyl)phenyl)ethanone ligand (L). The produced compounds have been identified by using spectral studies, elemental analysis (C.H.N.O), conductivity and magnetic properties. The produced metal chelates were studied using molar ratio as well as sequences contrast types. Rate of concentration (1 ×10􀀀 4 - 3 ×10􀀀 4 Mol/L) sequence Beer’s law. Compound solutions have been noticed height molar absorptivity. The free of ligand and metal chelates had been applied as disperse dyes on cotton fabrics. Furthermore, the antibacterial activity of the produced compounds against various bacteria had been investigated. F