In this study lattice parameters, band structure, and optical characteristics of pure and V-doped ZnO are examined by employing (USP) and (GGA) with the assistance of First-principles calculation (FPC) derived from (DFT). The measurements are performed in the supercell geometry that were optimized. GGA+U, the geometrical structures of all models, are utilized to compute the amount of energy after optimizing all parameters in the models. The volume of the doped system grows as the content of the dopant V is increased. Pure and V-doped ZnO are investigated for band structure and energy bandgaps using the Monkhorst–Pack scheme's k-point sampling techniques in the Brillouin zone (G-A-H-K-G-M-L-H). In the presence of high V content, the bandgap energy decreases from 3.331 to 2.043 eV as seen by the band diagram. PDOS diagram was utilized to get the insight of the electronic structure of the atoms and the amount to which all energy bands contribute to a particular orbit of the atoms. As the V content grew, so did the PDOS for all of the states. The manipulation of bandgaps was carried out in a way that narrowing the bandgaps occurs, resulting in a redshift of the absorption spectrum in the IR region. At lower photon energies, the imaginary and real parts dielectric functions have increased. The effectiveness of V atoms on transmissivity especially in the low energy region of the V-doped ZnO perovskite has been verified compared to the other theoretical results.
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
... Show MoreLow bearing capacity of weak soil under shallow footings represents one of construction problems.
Kaolin with water content converges to liquid limit used to represent the weak soil under shallow
footing prototype. On the other hand, fly ash, which can be defined as undesirable industrial waste
material, was used to improve the bearing capacity of the soft soil considered in this research. The soft
soil was prepared in steel box (36×36×25) cm and shallow square footing prototype (6×6) cm were
used .Group of physical and chemical tests were conducted on kaolin and fly ash. The soft soil was
improved by a bed of compacted fly ash placed under the footing with dimensions equal to that of
footing but with different de
Melanoides tuberculata (O. F. Müller, 1774), a freshwater snail native to eastern Mediterranean, eastern Africa, southeast Asia, southern Asia, India, and Malaysia, it is an effective invader and is now nearly globally distributed. This snail has been studied with interest because of its rapidly distributed, and because of being can serve as compatible intermediate host for many of trematodes in the world. We have summarized information from many articles in order to highlight the most important aspects of this invader snail life.
Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different
... Show MoreThis study synthesized nanocomposite photocatalyst materials from a mixture of Cu2O nanoparticles, ZnO nanoparticles, and graphene oxide (GO) through coprecipitation and hydrothermal methods. This study aims to determine the optimum composition of Cu2O/ZnO/GO nanocomposites in degrading methylene blue. The nanocomposite was synthesized in two steps: 1 the synthesis of Cu2O and ZnO nanoparticles through the coprecipitation method and the preparation of GO through the modified Hummer method. 2 The preparation of Cu2O and ZnO nanoparticles mixtures with GO through the hydrothermal method to form Cu2O/ZnO/GO nanocomposites. The adsorption-photocatalysis process of methylene blue
... Show MoreThe study aims to build a model that revolves around the main question of the role of strategic agility (SA) in enhancing organizational excellence (OE). For the purpose of achieving OE and to determine the extent of interest and knowledge of managers at the Midwest Refineries Company (MRC) on the theoretical and practical implications, and on the performance foundations of these two vital variables with the aim of continuous improvement. A questionnaire was used and distributed to a random sample of 54 managers in this important energy production company. The study followed the descriptive analytical approach to answer the questions raised. The study model and dimensions were built according to reference models, most notably the mo
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