Mixed ligands of 2-benzoyl Thiobenzimiazole (L1) with 1,10-phenanthroline (L2) complexes of Cr(III) , Ni(II) and Cu(II) ions were prepared. The ligand and the complexes were isolated and characterized in solid state by using FT-IR, UV-Vis spectroscopy, 1H, 13C-NMR, flame atomic absorption, elemental micro analysis C.H.N.S, magnetic susceptibility , melting points and conductivity measurements. 2-Benzoyl thiobenzimiazole behaves as bidenetate through oxygen atom of carbonyl group and nitrogen atom of imine group. From the analyses Octahedral geometry was suggested for all prepared complexes. A theoretical treatment of ligands and their metal complexes in gas phase were studied using HyperChem-8 program, moreover, ligands in gas phase

Determination of the proportion of selected metal elements (Fe, Mn, Co, Cu, Cr, Ni, Mo, Pb, Cd ) using a flame absorption spectroscopy device and the spectroscopy of Graphite furnace, and Phenols so as Free Radical (NO3-, NO2-) using ultraviolet spectroscopy device in the industrial wastewater of Al-Dura (A) and AlNajaf (B) refinery before and after entering the treatment units, taking into consideration the sampling time Varying (more than separated) and setting the temperature during the drawing of the model and conducting a statistical study of the results reached

In this study, poly4-(nicotinamido)-4-oxo-2-butenoic acid (PNOE) was prepared by the electro polymerization of 4-(nicotinamido)-4-oxo-2-butenoic acid (NOE) monomer on a 316 stainless steel (St.St) which acts as an anticorrosion coating.  Fourier transforms infrared (FTIR), atomic force microscopy (AFM), scanning electron microscopy (SEM), and cyclic voltammetry were used to diagnose the structure and the properties of the prepared polymer layer. The corrosion behavior of the uncoated and coated 316  St.St were evaluated by using an electro chemical polarization technique in 0.2 M hydrochloric acid  solution as a corrosive medium at a temperature range of 293 to 323 K. Nano materials, such as nano ZnO and graphene were added in di

Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t