In this paper the concept of (m, n)- fully stable Banach Algebra-module relative to ideal (F − (m, n) − S − B − A-module relative to ideal) is introducing, we study some properties of F − (m, n) − S − B − A-module relative to ideal and another characterization is given

(phen) (L(M [formula general a with complexes ligand-mixed new of series A methods analyses different by characterised and synthesised been have ,ligand arysecond as phenanthroline1,10- = phen and ligand primary as dithiocarbamate-1-azolebenzoimid-H-1)sulfinyl)methyl)yl-”-2pyriden)trifluroethoxy2,2,2- “(-4-methyl3-(((2-Sodium = L,ZnIIandCdII,CuII,NiII,CoII= M where,Cl)]phen)(L(Pd [Cland]2)O2H( ligands to metal ,moments magnetic and ,elementalanalysis ,spectrum mass ,surementsmea conductivity ,analysis thermal ,spectroscopy Vis-UV ,IR-FT ,NMR-C,13 H1 such dithiocarbamate the with formed coordination anisobidentate that showed spectra IRFT The.)phen:dithiocarbamate:M) (1:1:1(be to found been has complexes all in ratio nitrogen th

Mixed ligand of Co and Ni (II) complexes were prepared from [5-(p-nitrophenyl)-4/-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide](TRZ.DTC) as primary ligand and 2,2'-bipyridyl (bipy) as a co-ligand with metal salts. These complexes were analytically and spectroscopically characterized in solid state by elemental analyses, flame atomic absorption, magnetic susceptibility and molar conductance measurements, as well as by UV–Vis and FTIR spectroscopy. Infrared, ultra violet spectra reveal a bidentate coordination of the two ligands with metal ions 1:1:1 mole ratio. Room temperature magnetic moments and solid reflectance spectra data indicate paramagnetic complexes with five-coordinate square pyramidal geometry for nickel (II) comple

Resource estimation is an essential part of reservoir evaluation and development planning which highly affects the decision-making process. The available conventional logs for 30 wells in Nasiriyah oilfield were used in this study to model the petrophysical properties of the reservoir and produce a 3D static geological reservoir model that mimics petrophysical properties distribution to estimate the stock tank oil originally in place (STOOIP) for Mishrif reservoir by volumetric method. Computer processed porosity and water saturation and a structural 2D map were utilized to construct the model which was discretized by 537840 grid blocks. These properties were distributed in 3D Space using sequential Gaussian simulation and the variation in

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha