The [2-hydroxy-1, 2-diphynel-ethanone oxime] was reacted with 1, 2-dichloroethan to give the new ligand [H2L]. this ligand was reacted with some metal ions (Co (II), Ni (II), Cu (II), Zn (II) and Cd (II) in methanol as a solvent to give a series of new (1: 1) complexes of the general formula [M (HL)] Cl,(where: M= Co (II), Ni (II), Cu (II), Zn (II) and Cd (II)) are isolated All compounds have been characterized by spectroscopic methods [IR, UV-Vis] atomic absorption. Chloride content along with conductivity measurements. From the above data the proposed molecular structure for (Co, Cu, Ni, Zn and Cd) complexes adopting a tetrahedral structure

The [2-hydroxy -1,2-diphynel-ethanone oxime] was reacted with 1,2- dichloroethan to give the new ligand [H2L].this ligand was reacted with some metal ions (Co(II),Ni(II),Cu(II),Zn(II) and Cd(II) in methanol as a solvent to give a series of new (1:1)complexes of the general formula [ M(HL)]Cl ,( where : M= Co(II),Ni(II),Cu(II),Zn(II) and Cd(II)) are isolated All compounds have been characterized by spectroscopic methods [ I.R , U.V -Vis ] atomic absorption . Chloride content along with conductivity measurements. From the above data the proposed molecular structure for (Co, Cu, Ni, Zn and Cd) complexes adopting a tetrahedral structure.

A new Schiff base ligand Bis-1,4-di[N-3-(2-hydroxy-1-amino)- acetophenonylidene] benzylidene [L] and its complexes with (Mn(II) ,Co(II) ,Ni(II and Cu(II)) were synthesized . The ligand was prepared in two steps. In the first step a solution of (terphthalaldehyde) in methanol reacts under reflux with (p-aminoacetophenone) to give an intermediate compound [1-[3-({4-[(3-Acetyl-phenylimino)-methyl]-benzylidene}-amino)-phenyl]- ethanone which reacts in the second step with (2-Amino-phenol) giving the mentioned ligand. The complexes were synthesized by addition the corresponding metal salt solution to the solution of the ligand in methanol under reflux in (1:1) metal to ligand ratio. On the basis of, molar conductance, I.R., UV-Vis, HPLC, chlorid

The ligand [Potassium (E)-(4-(((2-((1-(3-aminophenyl) ethylidene) amino)-4-oxo-1,4- dihydropteridin-6-yl) methyl) amino)benzoyl)-L-glutamate] was prepared from the condensation reaction of folic acid with (3-aminoacetophenone) through Schiff reaction to give a new Schiff base ligand [H2L]. The ligand [H2L] was characterized by elemental analysis CHN, atomic absorption (A.A), (FT-I.R.), (U.V.-Vis), TLC, E.S. mass (for spectroscopes), molar conductance, and melting point. The new Schiff base ligand [H2L], reacts with Mn(II), Co(II), Ni(II), Cu(II), Cr(III) and Cd(II) metal ions and (2-aminophenol), (metal : derivative ligand : 2-aminophenol) to give a series of new mixed complexes in the general formula:- K3[M2(HL)(HA)2], (where M=Mn(II) and

 The precursor [W] [2-(2-(naphthalen-5-yl) diazenyl)-4-amino-3-hydroxynaphthalene-1sulfonic acid] was synthesized from reaction of diazonium salt with 1-amino-2-naphtol-4sulfonic acid. Then the tridentate Schiff base ligand type ONO was synthesized from the reaction of the precursor with salicyaldehyde in 1:1 mole ratio to produce the ligand H2L [2-(2-(naphthalen5-yl) diazenyl)-4-(2-hydroxynaphthalen-3-yl)methyleneamino)-3-hydroxy salicyalene-1-sulfonic acid],the reaction achieved in methanol as a solvent under reflux. Spectroscopic methods IR, U.V, 1H,13C-NMR was used to characterize the ligand. Complexes of [CrIII, CoII, NiII and CdII] ions were also prepared through reaction of ligand with metal salts in 2:1 mole ratio at reflux,

In present work, new tetra-dentate ligand, titled 3,5-bis ((E)-5-Bromo-2-hydroxy benzylidene amino) benzoic acid (H₃L), was prepared via an acid-catalyzed condensation process. New four metallic ligand complexes with Co(II), Ni(II), Cu(II) and Zn(II) ions, were also prepared from the refluxing of equivalent moles. Ligand's structure and its complexes; were confirmed by numerous characterization methods, including Ultraviolet-Visible, Infrared, Mass Spectrometer, ¹H and ¹³C Nuclear Magnetic Resonance spectra, atomic absorption, magnetic moments, and molar conductivity measurements. The results of the spectroscopic analyzes proved that the prepared ligand acts as tetradentate bi-ionic ligand and it was bond

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

This research basically gives an introduction about the multiple intelligence
theory and its implication into the classroom. It presents a unit plan based upon the
MI theory followed by a report which explains the application of the plan by the
researcher on the first class student of computer department in college of sciences/
University of Al-Mustansiryia and the teacher's and the students' reaction to it.
The research starts with a short introduction about the MI theory is a great
theory that could help students to learn better in a relaxed learning situation. It is
presented by Howard Gardener first when he published his book "Frames of
Minds" in 1983 in which he describes how the brain has multiple intelligen

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca