This work involves the synthesis and characterization of  asymmetrical  pyromellitdiimide derivatives [VII]a-f  by four sequences steps reaction . One mole of pyromellitic dianhydride was reacted with one mole of various primary aromatic amines [2aminothiazole , 2-aminobenzothiazole , 5-(4-amino phenyl)-1,3,4-oxadiazole-2-thiol , 4-nitro aniline , 4-chloro aniline , 4-toludine] in excess of dry acetone to produce six compounds (Nsubstituted-pyromellitamic monoacid) [IV]a-f . These new compounds [IV]a-f  were converted to the  corresponding N- substituted- pyromellitmonoimide [V]a-f  when heating then at (8090) 0C in sodium acetate-acetic anhydride system .The compounds [V]d-f were allowed to react with one m

A variety of new phenolic Schiff bases derivatives have been synthesized starting from Terephthaladehyde compound, all proposed structures were supported by FTIR, 1H-NMR, 13C-NMR, Elemental analysis, some derivatives evaluated by Thermal analysis (TGA).

Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc

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A new series of bases of Schiff (H₂-H₄) derived from phthalic anhydrideweresynthesized. These Schiff bases were prepared by the reaction of different amines (tyrosine methyl ester, phenylalanine methyl ester, and isoniazid) with the phthalimide derived aldehyde with the aid of glacial acetic acid or triethylamine ascatalysts. All the synthesized compounds were characterized by (FT-IR and ¹HNMR) analyses and were in vitro evaluated for their antimicrobial activity against six various kinds of microorganisms. All the synthesized compounds had been screened for their antimicrobial activity against two Gram-positive bacteria “Staph. Aureus, and Bacillus subtilis

An attempt to synthesize the benzoimidazol derivatives from the reaction of o-phenylenediamine and benzoic acid derivatives in the presence of ethanol and various ketones under microwave irradiation, 1 , 5 - benzodiazepinum salt derivatives were obtained instead of them. Unexpected reaction was happened for synthesis a new series of benzodiazepinium salt derivatives in a selective yield . The reaction mechanism was also discussed. The new compounds were purified and identified their structures were elucidated using various physical techniques like; FT- IR spectra, micro elemental analysis (C.H.N) and 1H NMR spectra.

Coupling reaction of 2-amino benzoic acid with phenol gave the new bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, FT-IR and UV-Vis spectroscopic technique. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentr

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number