Abstract:In this research we prepared nanofibers by electrospinning from poly (Vinyl Alcohol) / TiO2. The spectrum of the solution (Emission) was studied at 772 nm. Several process parameter were Investigated as concentration of PVA, the effect of distance from nozzle tip to the grounded collector (gap distance), and final the effect of high voltage. We find the optimum condition to prepare a narrow nanofibers is at concentration of PVA 16gm, the fiber has 20nm diameter.

In this research we prepared nanofibers by electrospinning
from poly (Vinyl Alcohol) / TiO2. The spectrum of the solution
(Emission) was studied at 772 nm. Several process parameter were
Investigated as concentration of PVA, the effect of distance from
nozzle tip to the grounded collector (gap distance), and final the
effect of high voltage. We find the optimum condition to prepare a
narrow nanofibers is at concentration of PVA 16gm, the fiber has
20nm diameter

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

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.

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

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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

Pulsed laser deposition (PLD) technique was applied to prepared Chromium oxide (Cr₂O₃) nanostructure doped with Titanium oxide (TiO₂) thin films at different concentration ratios 3,5,7 and 9 wt % of TiO₂. The effect of TiO₂ dopant on the average size of crystallite of the synthesized nanostructures was examined by X-ray diffraction. The morphological properties were discussed using atomic force microscopy(AFM). Observed optical band gap value ranged from 2.68 eV to 2.55 eV by ultraviolet visible(UV-Vis.) absorption spectroscopy with longer wave length shifted  in comparison with that of the bulk Cr₂O₃ ~3eV. This indicated that the synthesized samples a

Thin films of Zinc Selenide ZnSe have been prepared by using thermal evaporation in vacuum technique (10-5Torr) with thickness (1000, 2700, 4000) A0 and change electrode material and deposited on glass substrates with temperature (373K) and study some electrical properties at this temperature . The graphs shows linear relation between current and voltage and the results have shown increases in the value of current and electrical conductivity with increase thickness and change electrode material from Aluminum to Copper

The goal of this investigation is to prepare zinc oxide (ZnO) nano-thin films by pulsed laser deposition (PLD) technique through Q-switching double frequency Nd:YAG laser (532 nm) wavelength, pulse frequency 6 Hz, and 300 mJ energy under vacuum conditions (10-3 torr) at room temperature. (ZnO) nano-thin films were deposited on glass substrates with different thickness of 300, 600 and 900 nm. ZnO films, were then annealed in air at a temperature of 500 °C for one hour. The results were compared with the researchers' previous theoretical study. The XRD analysis of ZnO nano-thin films indicated a hexagonal multi-crystalline wurtzite structure with preferential growth lines (100), (002), (101) for ZnO nano-thin films with different thi