In this study, an easy, low-cost, green, and environmentally
friendlier reagents have been used to prepare CdS QDs, in chemical
reaction method by mixed different ratio of CdO and sulfur in
paraffin liquid as solvent and oleic acid as the reacting media in
different concentration to get the optimum condition of the reaction
to formation CdS QDs. The results give an indication that the
behavior is at small concentration of 4ml of the oleic acid is best
concentration which give CdS QDs of small about to 9.23 nm with
nano fiber configuration.

A New Spectrophotometric Methods are improved for determination Metronidazole (MTZ) and Metronidazolebenzoate (MTZB) depending on1STand 2nd derivative spectrum of the two drugs by using ethanol as a solvent. Many techniques were proportionated with concentration (peak high to base line, peak to peak and peak area). The linearity of the methodsranged between(1-25µg.ml-1) is obtained. The results were precise and accurate throw RSD% were between (0.041-0.751%) and (0.0331-0.452%), Rec% values between (97.78, 101.87%) and (98.033-102.39%) while the LOD between (0.051-0.231 µg.ml-1) and (0.074-1.04 µg.ml-1) and LOQ between (0.170-0.770µg.ml-1) and (0.074-0.313 µg.ml-1) of (MTZ) and of (MTZB) respectively. These Methods were successfully ap

This paper reports a.c., d.c. conductivity and dielectric behavior of Ep-hybrid composite with12 Vol.% Kevlar-Carbon hybrid . D.C. conductivity measurements are conducted on the graded composites by using an electrometer over the temperature range from (293-413) K. It was shown then that conductivity increases by increasing number of Kevlar –Carbon fiber layers (Ep1, Ep2, Ep3), due to the high electrical conductivity of Carbon fiber. To identify the mechanism governing the conduction, the activation energies at low temperature region (LTR) and at high temperature region (HTR) have been calculated. The activation energy values for hybrid composite decrease with increasing number of fiber layers. The a.c. conductivity was measured over fr

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

Cipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

In this work, two graphene oxide (GO) samples were prepared using the Hummers method with graphite (g) and KMnO4 (g) ratios of 1:3 (GO3) and 1:6 (GO6). The effect of oxidation degree on the structural, electrical, and dielectric properties of the GO samples was investigated. The structures of the GO samples were studied using various techniques, including X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDXS). XRD analysis revealed an increase in the interlayer spacing and a decrease in the number of layers of the samples with increasing oxidant content. The two GO samples have giant permittivity values of ~105 in the low-frequency