This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

    This paper defines a method for sputtering high strength, extremely conductive silver mirrors on glass substrates at temperatures ranging from 20^o to 22^o C. The silver coated layer thicknesses in this work ranges from 7.5 to 16.1 nm using sputtering time from 10 to 30 min at power 25 W, 13.7 to 29.2 nm for time 10 to 30 min at 50 W, 15.7 to 26.4 nm for time 10 to 30 min at 75 W and 13.8 to 31.1 nm for time 10 to 30 min at 100 W. The optimum values of pressure and electrode gape for plasma sputtering system are 0.1 mbar and 5 cm respectively. The effect of DC sputtering power, sputtering duration or (sputtering time), and thickness on optical properties was investigated using an ultraviolet-visible spectrophot

In this work, silicon nitride (Si₃N₄) thin films were deposited on metallic substrates (aluminium and titanium sheets) by the DC reactive sputtering technique using two different silicon targets (n-type and p-type Si wafers) as well as two Ar:N₂ gas mixing ratios (50:50 and 70:30). The electrical conductivity of the metallic (aluminium and titanium) substrates was measured before and after the deposition of silicon nitride thin films on both surfaces of the substrates. The results obtained from this work showed that the deposited films, in general, reduced the electrical conductivity of the substrates, and the thin films prepared from n-type silicon targets using a 50:50 mixing ratio and deposited on both

The electrical properties of the AlNiCo thin films with thickness (1000oA) deposited on glass substrates using Ion – Beam sputtering (IBS) technique under vacuum <10-6 torr have been studied . Also it studied the effect of annealing temperature from this films , It is found that the effective energy decrease with increase of temperature and the conductivity decrease with increase temperature 323oK but after this degree the conductivity increasing .

 In this work, we are Study the effect of annealing temperature on the structure of a-Ge films doped with Sb and the electrical properties of a-Ge:Sb/c-Si heterojunction fabricated by deposition of a-Ge:Sb film on c-Si by using thermal evaporation. Electrical properties of aGe:Sb/c-Si heterojunction include I-V characteristics in dark at different annealing temperatures and C-V characteristics and with the C-V characteristics suggest that the fabricated heterojunction was abrupt type, built in potential determined by extrapolation from 1/C2-V curve and show that the built - inpotential (Vbi) for the Ge:Sb/Si system increases with the increase of annealing temperatures

Leishmaniasis is a disease caused by a protozoan parasite of the genus Leishmania. It is transmitted by the bite of sandfly (Subfamily Phlebotominae). Limited drugs are available for the treatment of leishmaniasis, and the general drug (pentostam) have many side effect on patients. Therefore, there is an urgent need for another drugs for the treatment of leishmaniasis.
This study aimed to develop new type of antileishmanial agents instead of classical drug (pentostam) and investigated the effectiveness of silver nanoparticles (Ag NPs) on Leishmania tropica parasites in both phases promastigote and amastigote in comparision to pentostam in in vitro condition.
This study showed the effects of Ag NPs in comparision to pentostam with d

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe