The Dielectric properties of EP/TiO2 and MgO nanocomposite at
a frequency range of (102-106 Hz) were studied. The composite were
prepared with the state volume ratio (0, 0.05, 0.1) for EP/TiO2 and
MgO respectively. The impedance, dielectric constant and dielectric
loss were found decrease with frequency increase.

Abstract

 Nano-crystalline ZSM-5 zeolite was synthesized by hydrothermal method using chelating agent and two gel compositions:Compositionɪ:Al₂O₃:86SiO₂:5.5TPA:12.7Na₂O:3.4Trien:3320H₂O.Compositionɪɪ:Al₂O₃:68SiO₂:5.4TPA:10Na₂O:2.6Trien:2626H₂O.Study of hydrothermal reaction factors on characteristics of nano- sized zsm-5 has been carried on ,among them are crystallization temperature, crystallization time and concentration of template ( TPAOH ) solution. Synthesis was accomplished in PTFE lined autoclave ( reactor ) . The product were characterized by X-ray diffraction ( XRD ),Atomic force microsc

ِabstract:In this research we prepared nanofibers by electrospinning from poly (Vinyl Alcohol) /TiO2. The spectrum of the solution (Emission) was studied and found to be at 772 nm, several process parameters were such as concentration of TiO2 , and the effect of distance from nozzle tip to the grounded collector (gap distance). The result of the lower concentration of, the smaller the diameter of nanofiber is. Increasing the gap distance will affect nanofibers diameter.

In this research we prepared nanofibers by electrospinning from
poly (Vinyl Alcohol) /TiO2. The spectrum of the solution (Emission)
was studied and found to be at 772 nm, several process parameters
were such as concentration of TiO2 , and the effect of distance from
nozzle tip to the grounded collector (gap distance). The result of the
lower concentration of, the smaller the diameter of nanofiber is.
Increasing the gap distance will affect nanofibers diameter

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua