Linear and nonlinear optical properties of epoxy/ Al2O3 nanocomposites system were studied for epoxy neat and (0.5, 1.5, 3, and 5) % Al2O3 nanocomposites.The band gap of epoxy and its nanocomposites was obtained at these weight ratios. Nonlinear optical properties experiments were performed using Q-switched Nd:YAG laser z-scan system.These experiments were carried out for different parameters: wavelengths (1064 nm and 532 nm), laser intensities (0.530, 0.679, and 0.772) GW/cm2 and weight ratio of Al2O3 nanocomposites. The results showed that the band gaps were decreased with increasing the weight ratio of nanoalumina except at 5wt% and the nonlinear refractive index coefficient is directly proportional to the incident intensities while o

This contribution aims to investigate volume-dependent thermal and mechanical properties of the two most studied phases of molybdenum nitride (c-MoN and h-MoN) by means of the quasi-harmonic approximation approach (QHA) via first-principles calculations up to their melting point and a pressure of 12 GPa. Lattice constants, band gaps, and bulk modulus at 0 K match corresponding experimental measurements well. Calculated Bader’s charges indicate that Mo–N bonds exhibit a more ionic nature in the cubic MoN phase. Based on estimated Gibbs free energies, the cubic phase presents thermodynamic stability higher than that detected for hexagonl, with no phase transition observed in the selected T–P conditions as detected experimentall

The alloys of CdSe1-xTex compound have been prepared from their elements successfully with high purity (99.9999%) which mixed stoichiometry ratio (x=0.0, 0.25, 0.5, 0.75 and 1.0) of (Cd, Se and Te) elements. Films of CdSe1-xTex alloys for different values of composition with thickness(0.5?m) have been prepared by thermal evaporation method at cleaned glass substrates which heated at (473K) under very low pressure (4×10-5mbar) at rate of deposition (3A?/s), after that thin films have been heat treated under low pressure (10-2mbar) at (523K) for two hours. The optical studies revealed that the absorption coefficient (?) is fairly high. It is found that the electronic transitions in the fundamental absorption edge tend to be allowed direct tr

Studied the optical properties of the membranes CdS thin containing different ratios of ions cadmium to sulfur attended models manner spraying chemical gases on the rules of the glass temperature preparation (350c) were calculated energy gap allowed direct these membranes as observed decrease in the value of the energy gap at reducing the proportion ofsulfur ions as absorption coefficient was calculated

Non thermal argon plasma needle at atmospheric pressure was constructed. The experimental set up was based on simple and low cost electric components that generate electrical field sufficiently high at the electrodes to ionize various gases which flow at atmospheric pressure. A high AC power supply was used with 9.6kV peak to peak and 33kHz frequency. The plasma was generated using two electrodes. The voltage and current discharge waveform were measured. The temperature of Ar gas plasma jet at different gas flow rate and distances from the plasma electrode was also recorded. It was found that the temperature increased with increasing frequency to reach the maximum value at 15 kHz, and that the current leading the voltage, which demonstra

Polyaniline polymer has been prepared by chemical oxidation
polymerization method in laboratory successfully. The PANI and
(PVA+PVP) as a polymer blends in different percentage (30%, 50%,
70%) from Polyaniline was prepared. The sample was studies as
optical properties by UV-vis spectrophotometer at (400-700) nm.
The result of optical energy gap was 2.23 eV for pure (PVA+ PVP)
and with additive was increasing with increasing PANI concentration
to become (2.49 for 30% to 2.52 for 70%) PANI. The goal of this
project is prepare triple blend polymer and study the effect when add
conductive polymer (Polyaniline) on the optical properties and
calculate optical constant as energy gap, refractive index, dielectric

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a