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

Background: Lateral sinus augmentation and simultaneous insertion of dental implants is a highlypredictable procedure and associated with high rate of implants success.Aims: To evaluate implant stability changes following maxillary sinus augmentation utilizing deproteinizedbovine bone alone or mixed with platelet-rich fibrin.Materials and Methods: A total of 34 lateral sinus augmentation procedures were performed and 50 dentalimplants simultaneously installed. The lateral sinus augmentation cases were allocated randomly into 3groups: Group A comprised 13 procedures and 21 dental implants utilizing solely deproteinized bovine bone.Group B involved 10 cases and 16 dental implants using deproteinized bovine bone mixed with leukocyteand

A computational investigation is carried out in the field of charged –particle optics with the aid of numerical analysis method using the personal computer. The work is concerned with the design of electron gun with space-charge effect. The Finite element method (FEM) used in the solution of Poison's equation for determine the axial potential distribution of the two-electrode immersion lens operated under zero magnification condition , and from the solution of the paraxial ray equation the optical properties such as the focal length , spherical and chromatic aberration coefficients are determined, also a calculation of the brightness and perveance for the lens. The electrodes geometry was determined in two and three dimensi

A total of 96 stool samples were collected from children with bloody diarrhea from two hospitals in Baghdad. All samples were surveyed and examined for the presence of the Escherichia coli O157:H7 and differentiate it from other Non -Sorbitol Fermenting Escherichia coli (NSF E. coli). The Bacterial isolates were identifed by using morphological diagnostic methods, Samples were cultured on liquid enrichment medium, incubated at 37C? for 24 hrs, and then cultured on Cefixime Tellurite -Sorbitol MacConkey Agar (CT- SMAC). 32 non-sorbitol fermenting bacterial isolates were obtained of which 11 were identified as Escherichia coli by using traditional biochemical tests and API20E diagnostic system without differentiation between

DBN Rashid, INTERNATIONAL JOURNAL OF DEVELOPMENT IN SOCIAL SCIENCE AND HUMANITIES, 2021

Double-layer micro-perforated panels (MPPs) have been studied extensively as sound absorption systems to increase the absorption performance of single-layer MPPs. However, existing proposed models indicate that there is still room for improvement regarding the frequency bands of absorption for the double-layer MPP. This study presents a double-layer MPP formed with two single MPPs with inhomogeneous perforation backed by multiple cavities of varying depths. The theoretical formulation is developed using the electrical equivalent circuit method to calculate the absorption coefficient under a normal incident sound. The simulation results show that the proposed model can produce absorption coefficient with wider absorption bandwidth compared w

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

The CuInSe2 (CIS) nanocrystals are synthesized by arrested precipitation from molecular precursors are added to a hot solvent with organic cap- ping ligands to control nanocrystal formation and growth. CIS thin films deposited onto glass substrate by spray - coating, then selenized in Ar- atmosphere to form CIS thin films. PVs were made with power conversion efficiencies of 0.631% as -deposited and 0.846% after selenization, for Mo coated, under AM 1.5 illumination. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CIS have the chalcopyrite structure as the major phase with a preferred orientation along (112) direction and the atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2

In this paper, the dynamic behaviour of the stage-structure prey-predator fractional-order derivative system is considered and discussed. In this model, the Crowley–Martin functional response describes the interaction between mature preys with a predator.  e existence, uniqueness, non-negativity, and the boundedness of solutions are proved. All possible equilibrium points of this system are investigated.  e su‰cient conditions of local stability of equilibrium points for the considered system are determined. Finally, numerical simulation results are carried out to con‹rm the theoretical results.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d