The subject of indication is one of many subjects that the Arabic language interest in and we decide that this research which we called (Indication of the abstract and Augmented Tri verbs) in one of Al-Quran Suras which is Al-moulk to dive in the secrets and knowledge of its meanings and knowledge of its structure in terms of abstraction and increase, And the investigation of our ancient scholars of linguistics and interpreters in its meanings. The verbss were classified according to the structure in which they were presented. The research includes two sections followed by the conclusion of the research, sources and its references. The first section (the indication of the abstract Tri verbs) in the sura is divided into four branches in which a group of actions carried multiple connotations, and the second topic was about the Augmented Tri verbs included two types of verbs the first: the Tri verbs, which are augmented by one letter, the other which are augmented by two letters.
Among the results reached is the diversity of verbs in the sura between the abstract and Augmented Tri verbs by one letter and two letters, and the absence of Quadrant verbs, and Augmented verb gave more meaning than the abstract verb, and that is because the increase in letters leads to an increase in meaning.as we have observed the accuracy of the use of the Koran language vocabulary commensurate with the meaning of words and bringing the meaning to the listener as we have reached a difference in the significance of the actions of scientists through the Comparison between two sets the language and the interpretation books. We collect most views that have been said in the Indication of these verbs.
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This work aim to prepare Ag/R6G/PMMA nanocomposite thin
films by In-situ plasma polymerization and study the changes in the
optical properties of fluorophore due to the presence of Ag
nanoparticles structures in the vicinity of the R6G laser dye. The
concentrations of R6G dye/MMA used are: 10-4M solutions were
prepared by dissolving the required quantity of the R6G dye in
MMAMonomer. Then Silver nanoparticles with 50 average particles
size were mixed with MMAmonomer with concentration of 0.3, 0.5,
0.7wt% to get R6G silver/MMA in liquid phase. The films were
deposited on glass substrates by dielectric barrier discharge plasma
jet. The Ag/R6G/PMMA nanocomposite thin films were
characterization by UV-Visible
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia
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This study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su
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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
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