We have designed, fabricated and studied the vertical axis wind turbine and its characterization. The system has been locally designed to pump water. It is considered as a one of the best options for low speed wind. The turbine has eight blades , each blade is 1.8m in length,  and the area dimension of the turbine 3.6 m² . were investigated  the  best characterization of the system at low wind speed are Power turbine  depends on the wind speed. It was 280 Watt at 6m/s and 160 watt at 5m/s  , and  the power after the turbine decreasing to factor  1/3. The system torque was 20 N.m , Power coefficient cap  0.29 , Tip speed ratio 0.46. It is suitable to be used in Iraq region , and low cost for get the wat

The properties of structural and optical of pure and doped nano titanium dioxide (TiO₂) films, prepared using chemical spray pyrolysis (CPS) technique, with different nanosize nickel oxide (NiO) concentrations in the range (3-9)wt% have been studied. X-Ray diffraction (XRD) technique where using to analysis the structure properties of the prepared thin films. The results revealed that the structure properties of TiO₂ have polycrystalline structure with anatase phase. The parameters, energy gap, extinction coefficient, refractive index, real and imaginary parts were studied using absorbance and transmittance measurements from a computerized ultraviolet visible spectrophotometer (Shimadzu UV-1601 PC) in the wavelength

This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

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

<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

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

           In this research, the preparation of a chemically activated carbon from date stones by using electric and microwave assisted K₂CO₃ activation was studied. The effect of radiation power, radiation time, and impregnation ratio on the yield and Iodine number on the activated carbons was investigated. The activated carbon characterizations were examined by its surface area, pore structure analysis, bulk density, moisture content, ash content, iodine number, FTIR, and scanning electron microscopy (SEM). The adsorption capacity was also studied by adsorption of fluoroquinolones antibiotics, CIP, NOR, and LEVO, by the prepared activated carbon.

In this study, titanium dioxide (TiO₂) nanoparticles incorporated with cement were synthesis by a simple casting method as a function concentration of TiO₂ (0.2, 0.4, 0.8, 1, and 2 wt%). The prepared samples were characterized using the technique of Field Emission Scanning Electron Microscope (FESEM) and UV-Visible spectrophotometer, which was used to measure the adsorption spectra. The observed photocatalytic efficiency of TiO₂ nanoparticles (NP) incorporated with cement was investigated by decomposing the dye methyl blue (MB) solution under sunlight irradiation. According to the slope, the value of the k constant at the best sample is 0.8wt%, k=0.8265 min^-1. FESEM image of the TiO₂

In this paper, nanofluid of TiO₂/water of concentrations of 0.002% and 0.004% volume was used. This nanofluid was flowing through heat exchanger of shell and concentric double tubes with counter current flow to the hot oil. The thermal conductivity of nanofluid is enhanced with increasing concentrations of the TiO₂, this increment was by 19% and 16.5% for 0.004% and 0.002% volume respectively relative to the base fluid (water). Also the heat transfer coefficient of the nanofluid is increased as Reynold's number and nanofluid concentrations increased too. The heat transfer coefficient is increased by 66% and 49% for 0.004% and 0.002% volume respectively relative to the base fluid. This study showed that the friction

   This research  studyies  wear  rate  of  composite  materials  by using Epoxy Resin and Polyurethane Rubber as a matrix  of weigt percentage (90:10) (Ep/Pu) and reinforced by PVC fibers and Aluminum fibers two dimension knitted mat with fractional volume(15 %), in different conditions like: lab conditions and after submerge the samples in water for different periods of time. . four kinds of materials were prepared: (Ep+pu), (Ep+Pu+PVC), (Ep+Pu+Al.F), (Ep+Pu+PVC+Al. F) .And the results have shown that the best wear resistance are for the hybrid composite material    (Ep + Pu+ PVC + Al. F) and wear rate of  all samples increased when it was submerged in water