Two ligand ortho-amino phenyl thio benzyl (L1) and 1,3 bis (ortho - amino phenyl thio ) acetone (L2) and their complexes have been prepared and characterized . The L1 ligand is lossing phenyl group on complexcation and forming 1,2 bis (ortho - amino phenyl thio ) ethane L3 and this tetrahedrally coordinated to the metal ion ( M+2 = Ni , Cu , Cd ) and octahedrally coordinated with mercury and cobalt ions , while the ligand L2 is behave as tridentate ligand forming octahedrally around chrome metal ion . Structural , diagnosis were established by i.r , Uv- visible , conductivity elemental analysis and (mass spectra , H nmr spectra for( L1 , L2 ) .

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

Theligand4-[5-(2-hydoxy-phenyl)- [1,3,4- thiadiazole-2- ylimino methyl]-1,5-dimethyl -2-phenyl-1,2-dihydro-pyrazol-3-one [HL1] is prepared and characterized. It is reacted with poly(vinyl chloride) (PVC) in THF to form the PVC-L compounds ,PVC-L interacted with ions of transition metals to form PVC-L-MII complexes .All prepared compounds are characterized by FTIR spectroscopy, u.v-visible spectroscopy, C.H.N.S. analysis and some of them by 1HNMR

New substituted coumarins derivatives were synthesized by using nitration reaction to produce different nitro coumarin isomers which were separated from these isomers by using different solvent, and the reduction of nitro compounds was done to give corresponding amino coumarins. Temperature and reaction time of reaction were very important factors in determining the most productive nitro isotopes. A low temperature for three hours was sufficient to give a high product of a compound 6-nitro coumarin while increasing the temperature for a period of twenty-four hours that gave a high product of 8-nitro-coumarin. The synthesized compounds were confirmed by FT-IR,1 H-NMR, and13 C-NMR spectroscopy and all final compounds were tested for their ant

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

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord