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

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

Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,

Several recent approaches focused on the developing of traditional systems to measure the costs to meet the new environmental requirements, including Attributes Based Costing (ABCII). It is method of accounting is based on measuring the costs according to the Attributes that the product is designed on this basis and according to achievement levels of all the Attribute of the product attributes. This research provides the knowledge foundations of this approach and its role in the market-oriented compared to the Activity based costing as shown in steps to be followed to apply for this Approach. The research problem in the attempt to reach the most accurate Approach in the measurement of the cost of products from th

This study presents a transient thermo-mechanical finite element framework for high-speed end milling of AISI 4340 steel. The model couples moving heat sources, rate- and temperature-dependent plasticity, and adaptive mesh refinement (AMR) triggered by temperature gradient, plastic strain rate, and contact pressure. It is integrated with a design of experiments/response surface methodology using cutting speed (VC), feed per tooth (fZ), radial depth of cut/width of cut (ae), axial depth of cut (ap), and coolant mode. Responses include peak interface temperature per tooth (Tpeak), predicted surface residual stress (?_xx^"surf" ), and depth of compressive residual stress layer (dcomp). Experiments provide X-ray diffraction-based surfac

Objectives: Successful endodontic treatment outcome requires effective shaping and cleaning of root canals. This study aims to evaluate the smear layer removal after continuous chelation (CC) ) NaOCL\HEDP( and sequential chelation (SC) )NaOCL\EDTA( and their influence on the push-out bond strength (POBS) of Bio-C sealer. Materials and Methods: Palatal roots of the maxillary first molar (n=72) were divided into four groups (n=18) as follows: 3% NaOCL, SC: 3% NaOCL followed by 17% EDTA, CC: 3% NaOCL \9% HEDP and Distilled water. Thirty-two roots (n=8/group) were split longitudinally for smear layer evaluation using SEM. Forty roots were obturated with Guttapercha and Bio-C sealer using a single cone technique. Thre

Abstract: Objectives: To investigate the effect of temperature elevation on the bonding strength of resin cement to the zirconia ceramic using fractional CO2 laser. Background: Fractional CO2 laser is an effective surface treatment of zirconia ceramic, as it increases the bonding strength of zirconia to resin cement. Methods: Thirty sintered zirconia discs (10 mm diameter, 2 mm thickness) were prepared and divided to three groups (N=10) and five diffident pulse durations were used in each group (0.1, 0.5, 1, 5 and 10 ms). Group A was treated with 10 W power setting, group B with 20 W and group C with 30 W. During laser irradiation, temperature elevation measurement was recorded for each specimen. Luting cement was bonded to the treated z

Objective(s): The world of dentistry is constantly evolving, and with the advent of 3D printing technology, the possibilities are endless. However, little is known about the effects of adding ZrO2 NPs to the denture base resin of 3D additive manufacturing technique.Aim of this study is to evaluate the behavior of resin which is used to 3D printing of denture base with the addition of ZrO2 NPs on denture adaptation property and diametral compression strength.Methods: 60 samples were printed, 30 disks for diametral compressive test and 30 denture base for denture adaptation test. Three groups per test (n=10). The control group for each test included unreinforced 3Dprinted denture base resin, and the other groups were  reinforced with (2&