Abstract:
This tribe had lived in Iraq since the first century A.D. Persia tried to
keep this tribe away from Iraq, but without result. The tribe managed to get
victory against Persia in the battle of Dhyqar.
When the Muslims had come to conquer Iraq, Rabi’a welcomed them
and takes part in that action.
That tribe helped the caliph Ali in the Jammal and Sifffen wars in order
to remain Iraq the center of the Islamic caliphates this tribe had felt very sad
and sorrowful when the caliphate become to the Umayyad . This tribe did not
give up, so this tribe did what could be done to help those who had revolted
against the Umayyad. Rabi’a did that in order to get ride of the Mudriat alsham,
and favored Rabi

The habitat type and food availability always influence the population size of many
organisms. Bird’s feeding pattern should be abstracted to complete avian community structure
data. The agronomy main research farm of Orissa University of Agriculture and Technology
is a well-managed multi-crop agro-ecosystem which provides a suitable ground for ecological
research. In a multi-crop farmland, the association of Barn Swallow Hirundo rustica Linnaeus,
1758, with the Indian mustard Brassica juncea (L.) Czernajew, 1859 crops have been
recorded for the first time while hovering only on this field. A flock of Barn swallows was
recorded in 32 field visits while flying continuously over the Indian mustard field after
flow

Abstract:
Bajila regarded as descending from Anmar Ibn Nizar. Al-Masudi accepts
Bajila and Khath”am as being of Nizar, and asserts that it was only out of the
enmity that they were said to be from the Yemen.
Al-Ya”qubi tries to harmonize this by assuming that Anmar married a
women of the Yemen and that his sons Bajila and Khath”am are thus
connected to the people of this region only through their mothers line.
Bajila embraced Islam in the period of the prophet. Omar 1 forced this
tribe to go to Iraq instead of Al-_Sham, and gave them the quarter of Al- Saw
ad. Then they prohibited from that quarter by given money as reward that
made them against omar1.
This tribe assisted the forth rightly guided ca

KE Sharquie, JR Al-Rawi, AA Noaimi, MM Jabir, Iraqi Postgraduate Medical Journal, 2009

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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As a result of the exacerbation of the problem of water pollution, research was directed towards studying the treatment using ceramic membranes, which proved to be highly effective in treating all water sources. The research aims to study the possibility of preparing a new type of ceramic membranes from Syrian zeolite that was not previously used in this field. In this research, ceramic membranes were prepared from Syrian raw zeolite in several stages. Zeolite sample was characterized, grinded, mixed with boric acid, pressed to form desks, treated thermally according to experiment program, finally coated with silver nanoparticles. Specifications of prepared membranes were determined according to reference methods, effectiveness of prepar

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve