Two-dimensional crystal has been achieved and controlled
with the aid of DC electric field applied between two electrodes at 5
millimeters separating distance between them. Sol-gel method has
been used to prepared nanosilica particle which used in this work as
well as TiO2 nanopaowder. The assembly of the silica particles is
due to the interaction between the electrical force, the particles
dipole, and the interaction between the particles themselves. When a
DC voltage is applied, the particles accumulated and crystallized on
the surface between the electrodes. The Light diffraction
demonstrates that the hexagonal crystal is always oriented with one
axis along the direction of the field. The particles disass

Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are Z_H (9.2-13.8) m, Z_d (4.3-8.1) m and Z_o (0.24-0.48) m.

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Computer-aided modeling and simulation software programs are essential tools
to predict how an optical communication component, link, or network will function
and perform. This paper aims to investigate the various effects on pulses
propagation in optical transmission systems utilizing the MATLAB program.
Dispersion and Attenuation effects are explored. The simulation of Gaussian pulses
propagation through single mode optical fiber, simplifies the design of optical
communication system and make the design process more efficient, less expensive,
and faster.

     The goal of this paper is to show the kinematic characteristics of gaseous stellar dynamics using scaling coefficient relationships (such as Tully-Fisher) in different spiral galaxies. We selected a sample of types of spiral morphology  (116 early, 150 intermediate, and 146 late) from previous literature work, and used statistical software (statistic-win-program) to find out the associations of multiple factors under investigation, such as the main kinematic properties of the gaseous-stellar (mass, luminosity, rotational speed, and baryons) in different types of spiral galaxies. We concluded that there is a robust positive connection between Log Vrot.max.) and Log Mstar(B-V), as well as between Log Vrot.max. and Log Mbar (

PM3 semiempirical method and Density Functional Theory (DFT) calculations of the type (B3LYP) and a Gaussian basis set (6-311G) were carried out for fullerene C60 molecule with its construction units (5radialene, 1,2,3-trimethylene indan, and corannulene), to evaluate the geometrical structure (bond lengths, symmetry, and energetic such as heat of formation ΔH0f, total energy Etot., dipole moment μ, EHOMO (highest occupied molecular orbital energy), ELUMO (lowest unoccupied molecular orbital energy), energy gap ΔEHOMO-LUMO), the distribution of electron density and vibration frequencies, all at their equilibrium geometries. Assignment of the vibrations modes was done according to the movement of the atoms as a result of DFT calculatio

PM3 semiempirical method and Density Functional Theory (DFT) calculations of the type (B3LYP) and a Gaussian basis set (6-311G) were carried out for fullerene C60 molecule with its construction units (5radialene, 1,2,3-trimethylene indan, and corannulene), to evaluate the geometrical structure (bond lengths, symmetry, and energetic such as heat of formation ΔH0f, total energy Etot., dipole moment μ, EHOMO (highest occupied molecular orbital energy), ELUMO (lowest unoccupied molecular orbital energy), energy gap ΔEHOMO-LUMO), the distribution of electron density and vibration frequencies, all at their equilibrium geometries. Assignment of the vibrations modes was done according to the movement of the atoms as a result of DFT calculatio

This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D