Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Pseudomonas aeruginosa is emerging opportunistic clinical pathogens. Clinical isolates of P. aeruginosaresist wide spectrum of antibiotics and form biofilm. The comparison study between clinical and environmental of P. aeruginosa in terms of biofilm formation and antibiotic resistance is very scanty. Thus, in current study microtiter plate technique was used to measure the biofilm formation by several clinical and environmental isolates. Moreover, the antibiotic susceptibility of these bacteria was evaluated by VITIK 2 techniques. The relationship between the antibiotic susceptibility and biofilm formation was evaluated for clinical and environmental isolates. Clinical and environm

Ball and Plate (B&P) system is a benchmark system in the control engineering field that has been used to verify many control methods. In this paper the design of a sliding mode . controller has been investigated and verified in real-time via implementation on a real ball and plate system hardware. The mathematical model has been derived and the necessary parameters have been measured. The sliding mode controller has been designed based on the obtained mathematical model. The resulting controller has been implemented using the Arduino Mega 2560 and a ball and plate system built completely from scratch. The Arduino has been programmed by the Arduino support target for Simulink. Three test signals has been used for verification purposes

Abstract
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thestudents in studing Arabic langnage text-books
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Copper (I) complex containing folic acid ligand was prepared and characterized on the basis of metal analyses, UV-VIS, FTIR spectroscopies and magnetic susceptibility. The density functional theory (DFT) as molecular modeling calculations was used to determine the donor atoms of folic acid ligand which appear clearly at oxygen atoms binding to hydrogen. Detection of donation sights is supported by theoretical parameters such as geometry, mulliken population, mulliken charge and HOMO-LUMO gap obtained by DFT calculations.

    Ni2O3 nanomaterial, a phase of nickel oxide, is synthesized by a simple chemical process. The pure raw materials used in the present process were nickel chloride hexahydrate NiCl2.6H2O and potassium hydroxide KOH by utilizing temperature at 250 oC for 2 hour.  The structural, morphological and optical properties of the synthesized specimens of Ni2O3 were investigated employing diverse techniques such as XRD, AFM, SEM and UV-Vis, respectively. The XRD technique confirms the presence of Ni2O3 nanomaterial with crystal size of 57.083 nm which indexing to the (2θ) of 31.82; this results revealed the Ni2O3 was a phase of nickel oxide with Nano structure. The synthesized Ni2O3 will be useful in manufacturng electrodes materials f

ABSTRACT: Polypyrrole and polypyrrole / silver nanocomposites were fabricated by in-situ polymerization employing Ammonium Persulphate as an oxidizing agent. Nanocomposites were synthesized by combining polypyrrole and silver nanoparticles in various weight percentages (0.1%, 0.5%, 3%, 5% and 7% wt.). Crystallographic data were collected using X-ray diffraction.  PPy particles were found to have an orthorhombic symmetry. In contrast, PPy/Ag nanocomposites were reported to have monoclinic structure. The crystallite size was determined by XRD using Scherrer equation and considered to be within 49 nm range. DC conductivity of pelletized samples was evaluated in the temperature range of 323.15k to 453.15k. The conductivity displayed an

Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection