Thin films of microcrystalline and nanocrystalline -silicon carbide and silicon, where deposited on glass substrate with substrate temperature ranging from 350-400C, with deposition rate 0.5nm per pulse, by laser induced chemical vapor deposition. The deposition induced by TEACO2 laser. The reactant gases (SiH4 and C2H4) photo decompose throughout collision associated multiple photon dissociate. Such inhomogeneous film structure containing crystalline silicon, silicon carbide and amorphous silicon carbide matrix, give rise to a new type of material nanocrystalline silicon carbide in which the optical transmittance is governed by amorphous SiC phase while nanocrystalline grain are responsible for the conduction processes. This new m

The paper reports the influence of annealing temperature under vacuum for one hour on the some structural and electrical properties of p-type CdTe thin films were grown at room temperature under high vacuum by using thermal evaporation technique with a mean thickness about 600nm. X-ray diffraction analysis confirms the formation of CdTe cubic phase at all annealing temperature. From investigated the electrical properties of CdTe thin films, the electrical conductivity, the majority carrier concentration, and the Hall mobility were found increase with increasing annealing temperatures.

The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six differen

The work include synthesis of nanocomposites (X / S / Ag) based on blend from Xanthan gum / sodium alginate polymers (X / S) with different loading of synthesized silver nanoparticales (0.01, 0.03 and 0.05 wt%) were added to the blend. The silver nanoparticles were prepared by reduction method and were characterized and analyzed using X-ray diffraction (XRD) and Atomic force microscope (AFM). XRD study showed the presence nanoparticle of silver with crystalline nature and face-centered cubic (FCC) structure and an average size of nanoparticles ranging from 32 to 37 nm. The surface study was performed using AFM which showed a fairly uniform shape to the nanocomposites and a spherical nature for the silver nanoparticles. The nanocomposite exh

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This paper proposes improving the structure of the 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. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work

<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi