CdO:NiO/Si solar cell film was fabricated via deposition of CdO:NiO in different concentrations 1%, 3%, and 5% for NiO thin films in R.T and 723K, on n-type silicon substrate with approximately 200 nm thickness using pulse laser deposition. CdO:NiO/n-Si solar cell photovoltaic properties were examined under 60 mW/cm2 intensity illumination. The highest efficiency of the solar cell is 2.4% when the NiO concentration is 0.05 at 723K.

In this experimental study, the use of stone powder as a stabilizer to the clayey soil studied. Tests of Atterberg limits, compaction, fall cone (FCT), Laboratory vane shear (LVT), and expansion index (EI) were carried out on soil-stone powder mixtures with fixed ratios of stone powder (0%, 5%, 10%, 15%, and 20%) by the dry weight. Results indicated that the undrained shear strength obtained from FCT and LVT increased at all the admixture ratios, and the expansion index reduced with the increase of the stone powder.

The effect of annealing on the structural and optical properties of Antimony trisulfide (Sb2S3) is investigated. Sb2S3 powder is vaporized on clean glass substrates at room temperature under high vacuum pressure to form thin films. The structural research was done with the aid of X-ray diffraction (XRD) and atomic force microscopy (AFM). The amorphous to the polycrystalline transformation of these thin films was shown by X-ray diffraction analysis after thermal annealing. These films' morphology is explained. The absorption coefficient and optical energy gap of the investigated films are calculated using transmission spectra. Both samples have strong absorption in the visible spectrum, according to UV-visible absorption spectra. The optical

Background: This study aimed to evaluate the effect addition of polyester fibers on the some mechanical properties of heat cured acrylic resin (implant strength, flexural strength and hardness) Materials and methods: Ninety specimens were used in the study. Thirty specimens were used for impact strength measurements (80mm X 10mm X 4mm) length, width and thickness respectively. The specimens divided into three test groups (n=10), first group formed from heat cure acrylic resin without fiber reinforcement. Second group was formed from heat cure acrylic resin was reinforced with 2 mm length polyester fiber and third group was formed from heat cure acrylic resin reinforced with 4mm length polyester fiber, impact strength measured by impact test

Blockchain represents a new promising technology with a huge economic impact resulting from its uses in various fields such as digital currency and banking; malware represents a serious threat to users, and there are many differences in the effectiveness of antivirus software used to deal with the problem of malware. This chapter has developed a coefficient for measuring the effectiveness of antivirus software. This chapter evaluates the effectiveness of antivirus software by conducting tests on a group of protection programs using a folder containing an amount of data. These programs are applied to combat viruses contained in this folder. The study revealed that the effectiveness of antivirus software is as follows: AVG scored 0%,

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

This work dealt with separation of naphthenic hydrocarbons from non-naphthenic hydrocarbons and in particular concerns an improved process for increasing the naphthenes concentration in naphtha, The separation was examined using adsorption by Y and  B zeolite in a fixed bed process. The concentration of naphthenes in the influent and effluent streams was determined using PONA classification. The effect of different operating variables such as feed flow rate (2- 4 L/hr); bed length (50 - 80 cm) on the adsorption capacity of Y and  zeolite was studied. Increasing the bed length lead to increase the naphthenes concentration, and increasing the flow rate lead to decrease in the concentration of naphthenes, It was found that the decrease

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