In this paper, the packing problem for complete ( 4)-arcs in is partially solved. The minimum and the maximum sizes of complete ( 4)-arcs in are obtained. The idea that has been used to do this classification is based on using the algorithm introduced in Section 3 in this paper. Also, this paper establishes the connection between the projective geometry in terms of a complete ( , 4)-arc in and the algebraic characteristics of a plane quartic curve over the field represented by the number of its rational points and inflexion points. In addition, some sizes of complete ( 6)-arcs in the projective plane of order thirteen are established, namely for = 53, 54, 55, 56.
In this study, synthesis of polymer Nanocomposites through the blending of prepared polymers with polyvinyl alcohol (a synthetic polymer) or chitosan (a natural polymer) then mixed with nano oxide silica by many steps. The new compound [I] was obtained via reaction of 3,3’-dimethoxybiphenyl-4,4’-diamine as starting material with malic anhydride in DMF then treatment with ammonium persulfate (NH4 )2 S2 O8 (as the initiator) in order to produce polymer [II]. Also, we prepared new polymers [III-V] by using the same starting material (3,3’-dimethoxybiphenyl-4,4’-diamine) with glutaric acid or adipic acid or isophthalic acid in DMF and pyridine. In this study, new polymer blending [VI-IX] and [X-XIII] were synthesized from a prepared pol
... Show MoreDuring 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
... Show MoreBy unusual method for separating two isomers of a substituted nitro-coumarin using a soxhlet extractor and in controlling temperature to get a selective nitration reaction, several new Schiff base coumarins were synthesized from nitro coumarins as starting material, which were reduced by Fe in glacial acetic acid to produce corresponding amino coumarin derivatives. Then the latter was reacted with different aromatic aldehydes to produce the desired Schiff bases derivatives. After characterization by Fourier transform infrared (FT-IR), Proton nuclear magnetic resonance (1HNMR) and Carbon-13 nuclear magnetic resonance (C-NMR), all these compounds were evaluated as potential Antimicrobial and Antioxidant Agents.
A new Azo‐Schiff base ligand L was prepared by reaction of m‐hydroxy benzoic acid with (Schiff base B) of 3‐[2‐(1H–indol‐3‐yl)‐ethylimino]‐1.5‐dimethyl‐2‐phenyl‐2,3‐dihydro‐1H‐pyrazol‐4‐ylamine. This synthesized ligand was used for complexation with different metal ions like Ni(II), Co(II), Pd(II) and Pt(IV) by using a molar ratio of ligand: metal as 1:1. Resulted compounds were characterized by NMR (1H and 13C), UV–vis spectroscopy, TGA, FT‐IR, MS, elemental analysis, magnetic moment and molar conductivity studies. The activation thermodynamic parameters, such as ΔE*, ΔH*, ΔS*, ΔG*and
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The present paper is very important for study of biodiversity of Iraq , to know how the
changes going and how the laughing dove S. senegalensis was a rare species in Iraq and now
is common and also the (baz) gosh hawk A. gentilis is common and the most famous 6rd of
pray in Iraq, till now missing from ornithologist and bird watcher to record it
The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.