PMMA films of different thickness (0.006, 0.0105, 0.0206, 0.0385 and 0.056cm) were synthesized by casting process. The temperature and frequency dependence of dielectric constant and AC electrical conductivity measurements at various frequencies (10kHz-10MHz) and temperatures (293-373K) were carried out. Few anomalies in dielectric studies were observed near 313 and 373 K respectively. These points were related to glass transitions temperature. The variation of activation energy and conduction behavior was studied .From the AC conduction studies, it is confirmed that the mechanism responsible for the conduction process is hopping of carriers. The variations of the dielectric constant and loss as function of frequency at different tempera

 Indium doped CdTe polycrystalline films of thickness equals to 300nm were grown on corning glass substrates at temperature equals to 423K by thermal co-evaporation technique. The structural and electrical properties for these films were studied as a function of heat treatment (323,373,423)K. The x-ray analysis showed that all samples are polycrystalline and have the cubic zincblende structure with preferential orientation in the [111] direction, no diffraction peaks corresponding to metallic Cd, Te or other compounds were observed. It was found that the electrical resistivity drops and the carrier concentration increases when the CdTe film doped with 1.5% indium and treated at different annealing temperatures.

Chaotic systems have been proved to be useful and effective for cryptography. Through this work, a new Feistel cipher depend upon chaos systems and Feistel network structure with dynamic secret key size according to the message size have been proposed. Compared with the classical traditional ciphers like Feistel-based structure ciphers, Data Encryption Standards (DES), is the common example of Feistel-based ciphers, the process of confusion and diffusion, will contains the dynamical permutation choice boxes, dynamical substitution choice boxes, which will be generated once and hence, considered static,

            While using chaotic maps, in the suggested system, called

In present work examined the oxidation desulfurization in batch system for model fuels with 2250 ppm sulfur content using air as the oxidant and ZnO/AC composite prepared by thermal co-precipitation method. Different factors were studied such as composite loading 1, 1.5 and 2.5 g, temperature 25 ^oC, 30 ^oC and 40 ^oC and reaction time 30, 45 and 60 minutes. The optimum condition is obtained by using Tauguchi experiential design for oxidation desulfurization of model fuel. the highest percent sulfur removal is about 33 at optimum conditions. The kinetic and effect of internal mass transfer were studied for oxidation desulfurization of model fuel, also an empirical kinetic model was calculated for model fuels

  The morphological description and histological structure of Kidney in barn owl Tyto alba have been invesigated. The results of present study revealed that barn owl has pair of elongated solid kidney situated symmetrically on both sides of vertebral column. Each kidney consists of three lobes represented by carnial, middle and caudal lobes and all of then covered by a capsule of connective tissue.     Microscopical examination showed that the basic unit of kidney in barn owl represented by lobules which have conical shaped and each of them consists of cortex and medulla, and the cortex occupies more area than that of medulla. The results of the present study revealed that the glomerulus in barn owl represented b

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number