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 achieved lower computational complexity and number of layers, while being more reliable compared with other algorithms applied to recognize face masks. The findings reveal that the model's validation accuracy reaches 97.55% to 98.43% at different learning rates and different values of features vector in the dense layer, which represents a neural network layer that is connected deeply of the CNN proposed model training. Finally, the suggested model enhances recognition performance parameters such as precision, recall, and area under the curve (AUC).
In a survey of the crabronid fauna of Iraq during June to October 2022; 9species belonging to the genus
Density functional theory (DFT) calculations were used to evaluate the capability of Glutamine (Gln) and its derivative chemicals as inhibitors for the anti-corrosive behavior of iron. The current work is devoted to scrutinizing reactivity descriptors (both local and global) of Gln, two states of neutral and protonated. Also, the change of Gln upon the incorporation into dipeptides was investigated. Since the number of reaction centers has increased, an enhancement in dipeptides’ inhibitory effect was observed. Thus, the adsorption of small-scale peptides and glutamine amino acids on Fe surfaces (1 1 1) was performed, and characteristics such as adsorption energies and the configuration with the highest stability and lowest energy were ca
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New types of hydrodesulfurization (HDS) catalyst Re-Ni-Mo/ γ-Al2O3 was prepared and tested separately with two prepared conventional HDS catalysts (Ni-Mo/ γ-Al2O3 and Co-Mo//γ-Al2O3) by using a pilot plant hydrotreatment unit. Activities of three prepared hydrodesulfurization catalysts were examined in hydrodesulfurization (HDS) of atmospheric gas oil at different temperatures 275 to 350 °C and LHSV 1 to 4 h-1, the reactions conducted under constant pressure 40 bar and H2/HC ratio 500 ml/ml .Moreover, the hydrogenation of aromatic (HAD) in gas oil has been studied. HDS was much improved by adding promoter Re to the Ni-Mo/Al2O3
... Show MoreEverybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc
... Show MorePreparation and Identification of some new Pyrazolopyrin derivatives and their Polymerizations study
Several new derivatives of 1, 2, 4-triazoles linked to phthalimide moiety were synthesized through following multisteps. The first step involved preparation of 2, 2-diphthalimidyl ethanoic acid [2] via reaction of two moles of phthalimide with dichloroacetic acid. Treatment of the resulted imide with ethanol in the second step afforded 2, 2-diphthalimidyl ester [3] which inturn was introduced in reaction with hydrazine hydrate in the third step, producing the corresponding hydrazide derivative [4]. The synthesized hydazide was introduced in different synthetic paths including treatment with carbon disulfide in alkaline solution then with hydrazine hydrate to afford the new 1, 2, 4-triazole [10]. Reaction of compound [10] with different alde
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreThis study includes synthesis, characterization three series of the new derivatives via schiff bases for ampicillin which known as a high medicinal effectiveness. Series A include preparation schiff bases (A1-A6) by condensation of ampicillin with many substituted aldehyedes, while series B include preparation of six amines (B1-B6) is hydrazine hydrate derivatives by reaction schiff bases compounds which prepared in series A with hydrazine hydrate, then series C included for preparation of new six polymers C1-C6 by reaction of poly methyl methacrylate with amine compounds which prepared in series B. The synthesized polymers were identified by spectroscopic methods (FT-IR and 1 H-NMR) and measurement some of its physical characteristics.