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

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

The aim of this research was to study the concentrations of Uranium in the phosphorus fertilizers using Nuclear track detector (CR-39). Our present investigation is based on the study of 10 types samples for different kinds of phosphorus fertilizers which were available in the local market Some of them were Iraqi made and the others from different countries like, (Iran, Italy, Holland, Lebanon and Jordan) .. The result obtained shows that the Uranium concentration in phosphorus fertilizers samples varies from (3.59ppm) to(2.59ppm). Based on the radioactive concentration of Uranium in the samples all the results obtained between(3.59ppm) in the Iraqi super phosphate to (2.59ppm) in the mixture Iraqi phosphate fertilizer are withi

The effect of high energy radiation on the energy gap of compound semiconductor Silicon Carbide (SiC) are viewed. Emphasis is placed on those effects which can be interpreted in terms of energy levels. The goal is to develop semiconductors operating at high temperature with low energy gaps by induced permanent damage in SiC irradiated by gamma source. TEACO2 laser used for producing SiC thin films. Spectrophotometer lambda - UV, Visible instrument is used to determine energy gap (Eg). Co-60, Cs-137, and Sr-90 are used to irradiate SiC samples for different time of irradiation. Possible interpretation of the changing in Eg values as the time of irradiation change is discussed

Abstract: Colloidal gold nanoparticles (ringworm Palm or in the form of paper willow) have been prepared from HAuCl4 containing aqueous solution by hot chemical reduction method. The colloidal gold nanoparticles were characterized by SEM, EDX, and UV-VIS absorption spectroscopy. It was found that the variation of reduction time from boiling point affects the size of the nanoparticles and also in chemical reduction approach the size of nanoparticles can be controlled by varying the amount of variation the volume of reductant material with respect to the volume of HAuCL4.

Non-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important role in d

   Cranberry (Vaccinium macrocarpon) is a North American natural fruit. consumed as food and used for health promotion and prevention of various diseases. Aim. The present study was designed to evaluate the protective effect of cranberry fruit extract on nephrotoxicity induced by cisplatin in mice by measuring selected oxidative stress markers. Methods. Twenty-eight male albino mice were used in this study. The animals were divided into 4 groups as follows: Group I [Negative Control]/orally-administered normal saline for 7 successive days; Group II [Orally-administered cranberry fruit extract alone (200 mg/kg) for 7 successive days; Group III/Mice IP injection with cisplatin (12mg/kg) on day 7 and; Group IV [Orally-administered cr

Power switches require snubbing networks for driving single – phase industrial heaters. Designing these networks, for controlling the maximum allowable rate of rise of anode current (di/dt) and excessive anode – cathode voltage rise (dv/dt) of power switching devices as thyristors and Triacs, is usually achieved using conventional methods like Time Constant Method (TCM), resonance Method (RM), and Runge-Kutta Method (RKM). In this paper an alternative design methodology using Fuzzy Logic Method (FLM) is proposed for designing the snubber network to control the voltage and current changes. Results of FLM, with fewer rules requirements, show the close similarity with those of conventional design methods in such a network of a Triac drivin

The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

   Adsorption of lead ions from wastewater by native agricultural waste, precisely tea waste. After the activation and carbonization of tea waste, there was a substantial improvement in surface area and other physical characteristics which include density, bulk density, and porosity. FTIR analysis indicates that the functional groups in tea waste adsorbent are aromatic and carboxylic. It can be concluded that the tea waste could be a good sorbent for the removal of Lead ions from wastewater. Different dosages of the adsorbents were used in the batch studies. A random series of experiments indicated a removal degree efficiency of lead reaching (95 %) at 5 ppm optimum concentration, with adsorbents R² =97.75% for tea. Three mo