Sixteen new complexes with the general formula [M(L)2(H2O)2] were prepared resulting from the reaction of the two new Schiff base ligands, which are: - L1= (E)-5-((2-hydroxybenzylidene)amino)-2-phenyl-2,4-dihydro-3H-pyrazol-3-one) L2 = (E)-5-((2-hydroxy-3-methoxybenzylidene)amino)-2-phenylpyrazolidin-3-one) With divalent metal ions (manganese, cobalt, nickel, copper, zinc, cadmium, mercury) and (tetravalent platinum). Ligands was derived from the reaction of the amine (5-amino-2-phenyl-2,4-dihydro-3H-pyrazol-3-one) with Salicylaldehyde and ortho-vanillin, which is linked to the metal ions via the nitrogen atoms are the isomethene group and the oxygen is the hydroxide group of the pyrazoline ring. The two prepared ligands are distinguished by their ability to dissolve in organic solvents such as alcohols, ether, acetone, chloroform, carbon tetrachloride and ethanol, and their inability to dissolve in water. The prepared compounds were characterized using infrared spectroscopy and spectroscopy nuclear magnetic resonance, ultraviolet spectroscopy, micro-analysis of elements (C.H.N), atomic absorption analysis, electrical conductivity of solutions of complexes at a concentration of 1×10-3 , the magnetic susceptibility of the complexes was measured, and the effect of the solvent on the prepared compounds was studied, and from the results of the measurements, the octahedral geometric structure of the prepared complexes was proposed.. The inhibitory ability of the prepared compounds was tested against two types of selected bacteria, Staphylococcus aureus and Escherichia coli, and a type of fungus, Candida. The results showed that the ability of the metal complexes to inhibit is higher than the ligand.
The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
Blockchain has garnered the most attention as the most important new technology that supports recent digital transactions via e-government. The most critical challenge for public e-government systems is reducing bureaucracy and increasing the efficiency and performance of administrative processes in these systems since blockchain technology can play a role in a decentralized environment and execute a high level of security transactions and transparency. So, the main objectives of this work are to survey different proposed models for e-government system architecture based on blockchain technology implementation and how these models are validated. This work studies and analyzes some research trends focused on blockchain
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We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
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XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.
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Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai
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