Visible-light photodetectors constructed Fe2O3 were manufactured effectively concluded chemical precipitation technique, films deposited on glass substrate and Si wafer below diverse dopant (0,2,4,6)% of Cl, enhancement in intensity with X-ray diffraction analysis was showed through favored orientation along the (110) plane, the optical measurement presented direct allowed with reduced band gap energies thru variation doping ratio , current–voltage characteristics Fe2O3 /p-Si heterojunction revealed respectable correcting performance in dark, amplified by way of intensity of incident light, moreover good photodetector properties with enhancement in responsivity occurred at wavelength between 400 nm and 470 nm.

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

Recently, many materials have shown that they can be used as alternatives to chemicals materials in order to be used to improve the properties of drilling fluids. Some of these materials are banana peels and corn cobs which both are considered environmentally- friendly materials. The results of the X-ray diffraction examination have proved that the main components of these materials are cellulose and hemicellulose, which contribute greatly to the increasing of the effectiveness of these two materials. Due to their distinct composition, these two materials have improved the rheological properties (plastic viscosity and yield point) and reduced the filtration of the drilling fluids to a large extent. The addition rates used for each o

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

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

In drilling fluid program, selecting the drilling fluid that will reduce the lost time is the first objective, and will be economical regardless of its cost. The amount and type of solids in drilling fluid is the primary control of the rheological and filtration properties. Palygorskite clay (attapulgite) is an active solid that has the ability to reactive with its environment and form a gel structure within a fluid and due to its stability in the presence of brines and electrolytes this type of clay is preferred for use. The aim of this study is to improve properties of Iraqi palygorskite (PAL) by adding different chemical additives such as caustic soda NaOH and soda ash Na₂CO₃ with a different con

Background: Poly (methylmethacrylate) is the most widely used material in denture fabrication. The characteristics of acrylic resin which support microorganism development can threaten the oral health of denture users. This study was assigned to prepareand incorporate Ag-Zn zeolite powder into heat cured denture base material as antimicrobial material and to investigate its effect on some properties of heat cured acrylic denture base materials. Materials and methods: Sliver –zinc zeolite was prepared by ion exchange method and characterized then incorporated into poly (methylmethacrylate) powder in0.5% by weight. Specimens were constructed and divided into 6 groups according to the using tests; each group was subdivided into 2 groups