Alumina thin films have significant applications in the areas of optoelectronics, optics, electrical insulators, sensors and tribology. The novel aspect of this work is that the homogeneous alumina thin films were prepared in several stages to generate a plasma jet. In this paper, aluminium nanoparticles suspended in vinyl alcohol were prepared using exploding wire plasma. TEM analysis was used to determine the size and shape of particles in aluminium and vinyl alcohol suspensions; the TEM images showed that the particle size is 17.2 nm. Aluminium/poly vinyl alcohol (Al/PVA) thin films were prepared using this suspension on quartz substrate by plasma jet technique at room temperature with an argon gas flow rate of 1 L/min. The Al/PVA thin films were thermally converted to alumina films, where they were annealed at different temperatures (700, 800, or 900°C). X-ray diffraction (XRD), atomic force microscopy (AFM), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR) techniques were used to characterise these thin films before and after annealing process. The diffraction patterns of the prepared thin films before subjecting them to the annealing process indicated the presence of peaks belonging to aluminium and PVA; however, the diffraction patterns and FTIR spectra obtained for these films after the annealing process showed peaks indicating the formation of alumina films of different phases. AFM and SEM investigations proved that the formed particles for all prepared films before and after the annealing process were similar in size and almost spherical; the diameter of the particles was on the order of a few nanometres. To control the properties of prepared thin films, the plasma which was used to produce thin films is diagnosed spectrophotometrically. The generated plasma was diagnosed using optical emission spectroscopy to estimate the electron temperature Te; the electron temperature was 1.925 eV.
The study aimed to design a test of pre-writing skills for public kindergartens in Baghdad city. The test consisted of (25) items applied on a sample of (150) kindergarteners to identify these skills as well as to identify the significant difference between male and female children and if there is a difference between pre-school children and kindergarteners. The results showed the presence of pre-writing skills with a high degree in kindergarten children. The differences were clear in these skills between male and female children and those in pre-school than those in kindergartens. The researcher suggested a number of recommendations and proposals.
Today in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,
... Show MoreDue to the continuous development in society and the multiplicity of customers' desires and their keeping pace with this development and their search for the quality and durability of the commodity that provides them with the best performance and that meets their needs and desires, all this has led to the consideration of quality as one of the competitive advantages that many industrial companies compete for and which are of interest to customers and are looking for. The research problem showed that the Diyala State Company for Electrical Industries relies on some simple methods and personal experience to monitor the quality of products and does not adopt scientific methods and modern programs. The aim of this research is to desi
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
... Show MoreThis research takes up address the practical side by taking case studies for construction projects that include the various Iraqi governorates, as it includes conducting a field survey to identify the impact of parametric costs on construction projects and compare them with what was reached during the analysis and the extent of their validity and accuracy, as well as adopting the approach of personal interviews to know the reality of the state of construction projects. The results showed, after comparing field data and its measurement in construction projects for the sectors (public and private), the correlation between the expected and actual cost change was (97.8%), and this means that the data can be adopted in the re
... Show MoreA new efficient Two Derivative Runge-Kutta method (TDRK) of order five is developed for the numerical solution of the special first order ordinary differential equations (ODEs). The new method is derived using the property of First Same As Last (FSAL). We analyzed the stability of our method. The numerical results are presented to illustrate the efficiency of the new method in comparison with some well-known RK methods.
In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
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