Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

In this paper, some series of new complexes of Mn(II), Co(II), Ni (II) Cu(II) and Hg(II) are prepared from the Schiff bases (L1,L2). (L1) derived from 4-aminoantipyrine and O-phenylene dia mine then (L2) derived from (L1) and 2-benzoyl benzoic acid. Structural features are obtained from their elemental microanalyses, molar conductance, IR, UV–Vis, 1H, 13CNMR spectra and magnetic susceptibility. The magnetic susceptibility and UV–Vis, IR spectral data of the ligand (L1) complexes get square–planar and tetrahedral geometries and the complexes oflig and (L2) get an octahedral geometry. Antimicrobial examinations show good results in the sharing complexes.

In this paper, some series of new complexes of Mn(II), Co(II), Ni (II) Cu(II) and Hg(II) are prepared from the Schiff bases (L1,L2). (L1) derived from 4-aminoantipyrine and O-phenylene dia mine then (L2) derived from (L1) and 2-benzoyl benzoic acid. Structural features are obtained from their elemental microanalyses, molar conductance, IR, UV–Vis, 1H, 13CNMR spectra and magnetic susceptibility. The magnetic susceptibility and UV–Vis, IR spectral data of the ligand (L1) complexes get square–planar and tetrahedral geometries and the complexes oflig and (L2) get an octahedral geometry. Antimicrobial examinations show good results in the sharing complexes.

The problem of the study and its significance:

           Due to the increasing pressures of life continually, and constant quest behind materialism necessary and frustrations that confront us daily in general, the greater the emergence of a number of cases of disease organic roots psychological causing them because of severity of a lack of response to conventional treatments (drugs), and this is creating in patients a number of emotional disorders resulting from concern the risk of disease

     That is interested psychologists and doctors searchin

Three hundred samples of washing water of vegetables were collected from women aged ( 15- 6o) years from different area in Baghdad governorate and its suburbs include two rural area ( Jaddria in Baghdad university and Al –Wagif in Rashdia) and two urbane area (Mansoure and Escan) . The samples were examined by precipitation method and then by staining method ( Lugols –Iodine stain) . The percentage of infection of intestinal parasites 36.3% include 15.3% for urban area and 57.3% in rural area and a significant difference was found between those groups . .The results showed also increased in the prevalence of parasitic infection in group age (15 -30) year .Also the results showed only 109 sample infected with eight specie

A series of laboratory model tests has been carried out to investigate the using of pomegranate sticks mat as reinforcement to increase the bearing capacity of footing on loose sand. The influence of depth and length of pomegranate sticks layer was examined. In the present research single layer of pomegranate sticks reinforcement was used to strengthen the loose sand stratum beneath the strip footing. The dimensions of the used foundation were 4*20 cm. The reinforcement layer has been embedded at depth 2, 4 and 8 cm under surcharge stresses . Reinforcing layer with length of 8 and 16 cm were used. The final model test results indicated that the inclusion of pomegranate sticks reinforcement is very effective in improvement the loading cap