Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You only look once”) neural network algorithm, which is an efficient real-time object identification algorithm, an intelligent system was developed in this thesis to distinguish which faces are wearing a mask and who is not wearing a wrong mask. The proposed system was developed based on data preparation, preprocessing, and adding a multi-layer neural network, followed by extracting the detection algorithm to improve the accuracy of the system. Two global data sets were used to train and test the proposed system and worked on it in three models, where the first contains the AIZOO data set, the second contains the MoLa RGB CovSurv data set, and the third model contains a combined data set for the two in order to provide cases that are difficult to identify and the accuracy results that were obtained. obtained from the merging datasets showed that the face mask (0.953) and the face recognition system were the most accurate in detecting them (0.916).
Brachycerous Dipteran species on alfalfa plant Medicago sativa surveyed in several regions of Iraq from March to November 2012. The study was registered 14 species belonging to nine genera and four families. The results showed that Limnophra quaterna, Atherigona laevigata and Atherigona theodori as new records to Iraq and new pests of alfalfa.
The study of properties of space of entire functions of several complex variables was initiated by Kamthan [4] using the topological properties of the space. We have introduced in this paper the sub-space of space of entire functions of several complex variables which is studied by Kamthan.
In the current study, different concentrations of miltefosine drug, which is the first effective and safe oral treatment for visceral leishmaniasis, was evaluated against L. donovani promastigotes in comparison with pentosam drug. Direct counting microscopic assay was used to find 50% inhibitory concentration (IC50) of miltefosine and pentostam against L. donovani promastigotes. The IC50 of miltefosine drug was 45.42μg/ml, 46.76μg/ml and 36.68μg/ml after 24 hr, 48hr and 72hr respectively, In comparison with IC 50 of pentostam drug was 75.39 μg/ml after 72hr. There were significant differences (P˂0.05) between IC50 values of miltefosine and pentostam drugs from first day to third day.
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The main object of this paper is to study the representations of monomial groups and characters technique for representations of monomial groups. We refer to monomial groups by M-groups. Moreover we investigate the relation of monomial groups and solvable groups. Many applications have been given the symbol G e.g. group of order 297 is an M-group and solvable. For any group G, the factor group G/G? (G? is the derived subgroup of G) is an M-group in particular if G = Sn, SL(4,R).
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