The aim of the research is the knowing of the academic Scientific Journals of the colleges of University of Baghdad , through searching in the University of Baghdad website and the websites of colleges and thus studying the presentation of these journals in those website , and this is done by surfing the main pages of the websites for the colleges included in the research , and by analyzing the research made a menu for all the academic Scientific Journals for all institutes of the University of Baghdad , which simplifies the way for the researchers to publish these researches in the specific journals for their specialties .

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

In this paper, a compression system with high synthetic architect is introduced, it is based on wavelet transform, polynomial representation and quadtree coding. The bio-orthogonal (tap 9/7) wavelet transform is used to decompose the image signal, and 2D polynomial representation is utilized to prune the existing high scale variation of image signal. Quantization with quadtree coding are followed by shift coding are applied to compress the detail band and the residue part of approximation subband. The test results indicate that the introduced system is simple and fast and it leads to better compression gain in comparison with the case of using first order polynomial approximation.

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

     The study is designed to identify intestinal parasitic infections examined at Al-Aziziyah Hospital in Wasit Governorate in Iraq. In this study, a total of (460) internal and external patients were monitored for intestinal parasitic infections. All stool samples were analyzed by the direct method (microscopic exam.) to discover the trophozoite stages and cyst stages for intestinal protozoan parasites. The most incidence parasites in different sex, area residence and different age groups. Out of (460) patient sample were infected with 217 at a percentage of (47.17%), 101(46.5%) were for males and 116 (53.5%) were for females. It was found that the numbers and percentages of a single (one

Eimeriosis is a major problem affecting ruminants worldwide. The disease is primarily caused by Eimeria species, which are specialized for each host and grow in the small and large intestine of animals. The losses due to subclinical infections (especially weight loss) and clinical disease (diarrhea) make the species of this genus a very significant economic concern. Therefore, this study was conducted in some areas of Wasit Province. A total of 180 fecal samples from goats, of both sexes and covering different age groups and months, were collected. All fecal samples were examined microscopically, and 75 positive fecal samples were taken for molecular examination and further analyzed using conventional PCR, sequencing and phylogeneti

2-(2-amino-5-nitro-phenylazo) -phenol was ready by grouping the diazonium salt of 2-aminophenol with 4-nitroaniline.Thegeometry of azo ligand(HL)was resolved on the origin of (C.H.N) analysis, 1H and 13CNMR spectra, infrared spectra and UV–vis electronic absorption spectra. Dealing with the azo ligand produced with Nd+3,Cd+3,Dy+3 and Er+3at aqueous ethanol for a 1:2 metal: ligand rate, and in perfect ph. The formation for compounds have been described by utilizing flame atomic absorption,(C.H.N) Analyses, conductivity, infrared spectra and UV–vis spectral procedures. Nature in the produced compounds have been studied obey the ratio of mole and continuous variance manners, Beer's law yielded up a concentration rate (1×10-4 - 3×10-4M) .

6-(2-benzathiazolyl azo),-3,5-dimethylphenol was formed by grouping the 2- benzothiazole diazonium chloride with 3,5-dimethylphenol. Azo ligand(L) was resolved on the origin by 1H and 13CNMR, FTIR and UV-V is spectral analysis. Complexation of tridentate ligand (L) with Co2+, Ni2+, Cu2+ and Zn2+ in aqueous of ethyl alcohol with a 1:2 metal:ligand, and at ideal pH.. The formation of metal chelates are assigned using flame atomic, absorption, FTIR, and UV-Vis spectral analysis, other than conductivity and magnetic estates. The nature of the metal chelates were carried out by mole ratio and continuous, variation mechanism, Beer's law, followed the rate (0.0001 - 3×0.0001 M) concentration., High molar, absorptivity, for the complex solutions w