Four mixed ligand complexes were prepared from 1,10-phenanthroline (Phen), 5-chlorosalicylic acid (CSA), and anthranilic acid (Anthra) dissolved in aqueous ethanol at a ratio of (1:1:1:1) M: Phen:CSA: Anthra, M(II)= Cu, Zn, Cd, and Hg. The prepared compounds were analyzed by flame atomic absorption, FT-IR, UV-Vis, and spectroscopic methods, as well as conductivity measurements and magnetic properties. After analyzing the prepared compounds using the acquired data, the complexes formed by mixing ligands were concluded to adopt an octahedral geometry. That study has been conducted to test the inhibitory effectiveness of the complexes (1,10-Phenanthroline (Phen),  5-Chlorosalicylic acid (CSA), Na[Cu(Phen)(CSA)(Anthra), Na[Zn(Phen)(CSA

The preparation and characterization of the Cu (II), Co(II), Ni(II), Zn(II), Cd(II), and Hg(II) metal complexes of heterocyclic azo ligand 2-[(4`-sulphamide phenyl) azo] -4,5-diphenyl imidazole (4-SuBAI) have been studied by elemental analysis, FT-IR and UV-Vis Spectroscopic, magnetic moment and molar conductance methods. The analytical data showed that all chelate complexes were prepared with (metal-ligand) ratio of (1:2). The general formula of these complexes was [ML2X2]. nH2O [were L=2-[(4`-sulphamide phenyl) azo]-4,5-diphenyl imidazole and X=Cl, and the octahedral geometry were suggested for these complexes .

Ortho amino hydrazobenzene (L) has been prepared from the reaction of ortho amino phenyl thiol with phenyl hyrazan in mole ratio(1:1). It has been characterized by elemental analysis (C, H, N), IR, UV–Vis. The complexes of the bivalent ions (Co, Ni, Cu, Zn, Pd, Cd, Hg and Pb) and the trivalent (Cr) have been prepared and characterized too. The structural have been established by elemental analysis(C,H,N), IR , UV – Vis spectra , conductivity measurements , atomic absorption and magnetic susceptibility . The complexes showed characteristic behaviour of octahedral geometry around the metal ion and the( N,N) ligand coordinated in bidentate modeexcept with pd showed square planer. ? ,kf , ?max for the complexes were estimated too . ? for Co

Four mixed ligand complexes were prepared from 1,10-phenanthroline (Phen), 5-chlorosalicylic acid (CSA), and anthranilic acid (Anthra) dissolved in aqueous ethanol at a ratio of (1:1:1:1) M: Phen:CSA: Anthra, M(II)= Cu, Zn, Cd, and Hg. The prepared compounds were analyzed by flame atomic absorption, FT-IR, UV-Vis, and spectroscopic methods, as well as conductivity measurements and magnetic properties. After analyzing the prepared compounds using the acquired data, the complexes formed by mixing ligands were concluded to adopt an octahedral geometry. That study has been conducted to test the inhibitory effectiveness of the complexes (1,10-Phenanthroline (Phen),  5-Chlorosalicylic acid (CSA), Na[Cu(Phen)(CSA)(Anthra), Na[Zn(Phen)(CSA)(Anthra

This paper deals with constructing mixed probability distribution from mixing exponential

In this paper, a new seven-parameter Mittag-Leffler function of a single com-plex variable is proposed as a generalization of the standard Mittag-Leffler function, certain generalizations of Mittag-Leffler function, hypergeometric function and confluent hypergeometric function. Certain essential analytic properties are mainly discussed, such as radius of convergence, order, type, differentiation, Mellin-Barnes integral representation and Euler transform in the complex plane. Its relation to Fox-Wright function and H-function is also developed.

The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods. 

The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),