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

By 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.

This study investigates the characterization and mechanical performance of Stone Mastic Asphalt (SMA) mixtures modified with two types of polymers: styrene–butadiene–styrene (SBS) and high-molecular-weight polyethylene (PE). Neat asphalt cement PG 64-16 was modified using a higher content of SBS and PE at concentrations of 6%, 7%, and 8% by weight of asphalt through the dry blending method to produce Highly Modified Asphalts (HiMA). The physical and rheological properties of the modified binders were evaluated using penetration, softening point, rotational viscosity, and dynamic shear rheometer (DSR) tests. Also, their phase compatibility and morphological changes were evaluated using the storage stability testing and scanning electron

This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

In the present work, the thermo-fluid characteristics of a heat exchanger formed of helical coiled tubes immersed in cold water are investigated experimentally. Two types of helical coiled tube are tested, a conventional vertical single helical coiled tube and a new triple vertical helical coiled tube in parallel connection called as meshed coils. The effect of hot water flow rates inside the tubes (ranges from 2.67 to 7.08 l/min), and its inlet temperatures (namely 50, 60, 70 and 80 °C) are investigated. The experimental results show that increasing the flow rate inside the meshed coils leads to decrease the temperature difference between inlet and outlet. An enhancement of heat transfer for meshed coils compared to single coil has been n

This paper suggests a novel optimal inverse Radial Basis Function (RBF) neural network model for the control of Twin Rotor Aerodynamic Systems (TRAS), such as Multi-Input–Multi-Output (MIMO) systems with high nonlinearity and coupling effects between channels. After analyzing and linearizing the dynamic model, TRAS is decoupled into two Single Input Single Output (SISO) systems, thereby creating vertical (pitch model) and horizontal (yaw model) systems. The relationship between the output angle of each subsystem and the input voltage is modeled using the inverse RBF neural network. The weights, biases, centers and widths of the Gaussian function are unknown parameters of the proposed inverse neural model, and they are obtained usi