The coordination ability of the azo-Schiff base 2-[1,5-Dimethyl-3-[2-(5-methyl-1H-indol-3-yl)-ethyl imino]-2-phenyl-2,3-dihydro-1H-pyrazol-4-ylazo]-5- hydroxy-benzoic acid has been proven in complexation reactions with Co(II), Ni(II), Cu(II), Pd(II) and Pt(II) ions. The free ligand (LH) and its complexes were characterized using elemental analysis, determination of metal concentration, magnetic susceptibility, molar conductivity, FTIR, Uv-Vis, (1H, 13C) NMR spectra, mass spectra and thermal analysis (TGA). The results confirmed the coordination of the ligand through the nitrogen of the azomethine, Azo group (Azo) and the carboxylate ion with the metal ions. The activation thermodynamic parameters, such as ΔE*, ΔH*, ΔS*, ΔG*and K are cal

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

     In this work, calcium ions were determined by the addition to the allyl chloride monomer resulting from bulk polymerization formation. To acquire the highest adsorption capacity, molar ratios of the template, monomer, and cross-linking agent, as well as solvents and multiple monomers were investigated. Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) were used to analyze the calcium ion polymer. The elution of calcium had a small effect on the surfaces of the three-dimensional network structure. Calcium (II) ions were successfully eluted using a mixture of methanol and acetic acid. The calcium adsorption capacities were 3.8145 and 9.01773 mol/g (Q_max), respectively. A Langmuir isot

   In this work, the(m-phenylenediamine) and (2-naphthol) have been used in the synthesis of tetradentate ligand [m-phenylenedi(azo-2-naphthol)][H2L] type (N2O2). The ligand was refluxed in the ethanol with the metal ions [Co(II), Cu(II) and Zn(II)] salts, using triethyleamine as a base in (2:2) molar ratio to give the binuclear  complexes. These complexes were characterised by (A.A), F.T.I.R, (U.V-Vis) spectroscopies, along with conductivity, chloride content and melting point measurement. These studies revealed an octahedral geometries for  Co(II), Cu(II) and Zn(II) complexes with the general structure [M2(L)2(H2O)4]. The ligand and its complexes exhibited biological activity against the Bacillus(G+) strain and the

  A new simple and sensitive spectrophotometric method for the determination of trace amount of Cu(II) in the ethanol solution have been developed. The method is based on the complexation of Cu(II) with ethyl cyano(2-methyl carboxylate phenyl azo acetate) (ECA) in basic medium of sodium hydroxide givining maximum absorbance at (λmax = 521 nm). Beer's law is obeyed over the concentration range (5-50) (μg / ml) with molar absorptivity of (3.1773 × 102 L mol-1 cm-1) and correlation coefficient (0.9989). The optimum conditions for the determination of Cu(II)-complex and have been studied and applied to determine Cu(II) in synthetic water sample using simple and standard addition methods.