The present study aimed to identify the problems thatthe students of College of Education, for women in Iraqia university are suffering from and how to overcome them. thesample of the study contained of (392) student which forms (20%) of the basic sample which is  (2180) student, distributed on the six departments of the college they have been chosen randomly and the researcher has used the descriptive analytic method by applying one contains (67) items distributed on six fields,they are as follows: study skills field, academic field, curriculums field, students- teacher relationship field, examinations field, students family field,.

        The study has come with

Water resources would be differentiate in Morocco specially in Morocco  which appear as form of eyes ,rivers as dissolved water of mountain.

The human takes care of water either as rains to store and use in necessity trying to bring it to Maracas  by  helping from state

Teeth decay is one of the distinctive diseases which infects the children of generation .though it is not adeacly disease, it leads to huge problems , especially if it is infect children in their early childhood .There are many factors which lead to this disease , and to achieve the goal of this research in trying to stop the most important nutrition factors and others reasons that have relation with this disease .The practical application has been done for four months on children , who have been chosen randomly of the age ( 3-5 years) of both sexes , infected with teeth decay , from Baghdad city ( al karkh and al rusafa ) , the number of children reached to 90 child , divided into tow groups 45 male , and( 45 )female .Again they have be

The research is a vision of the future of industry in Iraq, so it is may be outside the ceiling of the capabilities of the Iraqi economy, and therefore it is exaggerated. Therefore, future plans must be applicable through the availability of capabilities. Everyone knows that the financial and administrative corruption and mismanagement of resources are the main cause of the inefficiency of the industrial sector, and the failure to exercise its real role in achieving economic development.; as well as the political situation and the dominance of parties and their insistence on addressing positions that have a strong relationship in managing the economic sector that has a significant impact on drawing the economic map in its current

The reaction oisolated and characterized by elemental analysis (C,H,N) , 1H-NMR, mass spectra and Fourier transform (Ft-IR). The reaction of the (L-AZD) with: [VO(II), Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II)], has been investigated and was isolated as tri nuclear cluster and characterized by: Ft-IR, U. v- Visible, electrical conductivity, magnetic susceptibilities at 25 Co, atomic absorption and molar ratio. Spectroscopic evidence showed that the binding of metal ions were through azide and carbonyl moieties resulting in a six- coordinating metal ions in [Cr (III), Mn (II), Co (II) and Ni (II)]. The Vo (II), Cu (II), Zn (II), Cd (II) and Hg (II) were coordinated through azide group only forming square pyramidal

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings