The nuclear structure of ³⁸Ar, ⁵⁹Co, ¹²⁴Sn, ¹⁴⁶Nd, ¹⁵³Eu and ²⁰³Tl target nuclei used in technology for nuclear batteries have been investigation, in order that, these nuclei are very interesting for radioisotope thermo-electric generator (RTG) space studies and for betavoltaic battery microelectronic systems. The single particle radial density distribution, the corresponding root mean square radii (rms), neutron skin thicknesses and binding energies have been investigated within the framework of Hartree-Fock Approximation with Skyrme interaction. The bremsstrahlung spectrums produced by absorption of beta particles in betavoltaic process and backscattered p

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

In this study, polymeric coating was developed by incorporating nano graphene in the polymer blend with applications to oil storage tanks. The oil storage tanks samples were brought from the oil Pipeline Company / Doura refinery in Baghdad. The coating polymer was formed with a blend (epoxy resin and repcoat ZR). The proportion of mixing the mixture was 3:1:1 epoxy resin 21.06 gm: repcoat ZR 10.53 gm: hardener 10.53 gm. The blend/graphene was prepared using in stui-polymerization method with different weight percentage 1, 3, 5, and 7 wt % added to blend. The resulting solution was put in a glass tube on a magnetic stirrer for one hour at a temperature of 40 ^°C. The result of contact angle and wate

The research aims to develop alternatives to transportation at the entrance to the Educational City (University of Baghdad) during the morning and evening peaks, which result from of the traffic congestion at the entrances to the educational city (the University of Baghdad), and affects the emotional, functional, and social performance of the whole city, and leads to hotbeds of confluence and congestion at the entrances in the morning and evening peaks. This movement was measured on the ground for pedestrians and vehicles. Some criteria were adopted to determine the density of road length to the area and density of roads for the number of users and the rate of the area served by roads. The research reviews the experiences of some

The research studied and analyzed the hybrid parallel-series systems of asymmetrical components by applying different experiments of simulations used to estimate the reliability function of those systems through the use of the maximum likelihood method as well as the Bayes standard method via both symmetrical and asymmetrical loss functions following Rayleigh distribution and Informative Prior distribution. The simulation experiments included different sizes of samples and default parameters which were then compared with one another depending on Square Error averages. Following that was the application of Bayes standard method by the Entropy Loss function that proved successful throughout the experimental side in finding the reliability fun

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi