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

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

      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

Metal and metal oxide NPs have shown to be perfectly synthesized by using plant extracts with high efficiency, low cost and low toxicity. Our goal was to synthesize ZnO NPs by using an extract of pomegranate seeds and investigate the anticorrosion, antimicrobial and antioxidant properties of the synthesized ZnO NPs. The results have shown that the use of pomegranate in the green synthesis of ZnO NPs gave a good yield, with a low cost and non-toxic approach. The electrophoretic deposition (EPD) was used to coat stainless steel (S.S) by synthesized ZnO NPs in an alcoholic solution at room temperature producing a good coating against corrosion. The corrosion properties were investigated in a saline solution and a temperature range of (293–32

Hypothesis Nanofluid flooding has been identified as a promising method for enhanced oil recovery (EOR) and improved Carbon geo-sequestration (CGS). However, it is unclear how nanoparticles (NPs) influence the CO2-brine interfacial tension (γ), which is a key parameter in pore-to reservoirs-scale fluid dynamics, and consequently project success. The effects of pressure, temperature, salinity, and NPs concentration on CO2-silica (hydrophilic or hydrophobic) nanofluid γ was thus systematically investigated to understand the influence of nanofluid flooding on CO2 geo-storage. Experiments Pendant drop method was used to measure CO2/nanofluid γ at carbon storage conditions using high pressure-high temperature optical cell. Findings CO2/nano

Many faces are exposed to degradation, discoloration, changes in humidity. The primary objective has improved some properties of hybrid nanocomposites materials that used for restoring of the function maxillofacial prosthesis and improving the esthetic. In the present research different lengths chopped and continuous of ultrahigh molecular weight polyethylene (UHMWPE) fiber was added at selected percentage (0.0, 0.2% and 1%) to polymer blend composite (95%SR /5%PMMA: 0.2% Pomegranate Peels Powder (PPP)) for developing the properties of silicone rubber used for the maxillofacial prosthesis applications. Some mechanical and physical properties were done on the all prepared samples. The results showed that all properties have improved when add

Silver nanoparticles (AgNPs) are of potential interest because of their effective antibacterial and antiviral activities. Capping agents are used for exhibiting a better antibacterial activity than uncapped Ag NPs. There are very few reports that have shown the usage of AgNPs for in-vivo antibacterial therapy. Citrate-capped silver nanoparticles were synthesized chemically by citrate reduction method; the size of Cit-AgNPs was determined by an atomic force microscope (AFM) and was between 15-90 nm. Acinetobacter baumannii (A. baumannii) isolates were the only sensitive species to Cit-AgNPs. MICs and MBC of Cit-AgNPs were determined by using A. baumannii. The results showed an additive effect of Cit-AgNPs. Four mice groups were infected with

In this study, synthesised new ligand: potassium 2,2'-(quinoxaline-2,3- diyl)bis(1-phenylhydrazinecarbodithioate) (L). The ligand synthesised by reacting N1,N2-dip-tolyloxalamide as the starting material with CS2 and KOH to add the CS2 group and then with phenylendiammine to achieve (L). The ligand used in the synthesis of complexes with (CoII, NiII and CdII). The new ligand and its complexes characterised by FT-IR, UV-Vis, 1H, 13C-NMR, Mass spectroscopy, and elemental analysis, in addition to the above techniques were using magnetic moment, atomic absorption, chloride content, and melting point to describe the metal complexes.

Objective(s): The aim of this study is to compare the impact strength of a heat cured denture-base acrylic resin
reinforced with metal wire and glass fibers.

Methodology: Forty five specimens were prepared from pink heat cure acrylic resin. Specimens were grouped into;
group-I (control group) which consists of 15 specimens with no reinforcement, group-II which consists of 15 specimens
reinforced with metal wire, and group-III consists of 15 specimens reinforced with glass fibers. Specimens were tested
by using charpy impact machine.

Results: The result showed that there was a highly significant difference in impact strength value among the testing
groups at (P < 0.001).

Conclusion: The impact str