One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

In this research, a novel thin film Si-GO10 and nanopowders Si-GO30 of silica-graphene oxide (GO) composite were prepared via the sol–gel method and deposited on glass substrates using spray pyrolysis. X-ray diffraction (XRD) results showed a relatively strong peak in the graphite layer that corresponds to the (002) plane. Transmission electron microscope (TEM) images showed that SiO2 nanoparticles were randomly distributed on the surface of GO plates, and the particle size in these nanopowders was below 50 nm. Field emission scanning electron microscopy (FESEM) analysis demonstrated that silica nanoparticles on the surface of GO plates exhibited almost spherical and rod-like nanoparticle shape, which in turn confirmed the formation of Si

In this research, a novel thin film Si-GO10 and nanopowders Si-GO30 of silica-graphene oxide (GO) composite were prepared via the sol–gel method and deposited on glass substrates using spray pyrolysis. X-ray diffraction (XRD) results showed a relatively strong peak in the graphite layer that corresponds to the (002) plane. Transmission electron microscope (TEM) images showed that SiO₂ nanoparticles were randomly distributed on the surface of GO plates, and the particle size in these nanopowders was below 50 nm. Field emission scanning electron microscopy (FESEM) analysis demonstrated that silica nanoparticles on the surface of GO plates exhibited almost spherical and rod-like nanoparticle shape, which in tur

This study employed the biosynthetic technique for creating vanadium nanoparticles (VNPs), which are affordable and user-friendly; VNPs was synthesized using vanadium sulfate (VOSO4.H2O) and a plant extract derived from Fumaria Strumii Opiz (E2) at a NaOH concentration of 0.1 M. This study aims to investigate the potential applications of utilizing an adsorbent for metal ions to achieve environmentally friendly production and assess its antibacterial activity and cytotoxicity. The reaction was conducted in an alkaline environment with a pH range of 8–12. The resulting product was subjected to various characterization techniques, including Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, x-ray diffraction (XRD), t

Zinc oxide nanoparticles sample is prepared by the precipitation method. This method involves using zinc nitrate and urea in aqueous solution, then (AgNO3) Solution with different concentrations is added. The obtained precipitated compound is structurally characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR). The average particle size of nanoparticles is around 28nm in pure, the average particle size reaches 26nm with adding AgNO3 (0.05g in100ml =0.002 M) (0.1g in100ml=0.0058M), AgNO3 (0.2g in 100ml=0.01M) was 25nm. The FTIR result shows the existence of -CO, -CO2, -OH, and -NO2- groups in sample and oxides (ZnO, Ag2O).and used an

A variety of oxides were examined as additives to a V2O5/Al2O3 catalyst in order to enhance the catalytic performance for the vapor phase oxidation of toluene to benzoic acid. It was found that the modification with MoO3 greatly promoted the little reaction leading to improve catalyst performance in terms of toluene conversion and benzoic acid selectivity. The effect of catalyst surface area, catalyst promoters, reaction temperature, O2/toluene, steam/toluene, space velocity, and catalyst composition to catalyst performance were examined in order to increase the benzoic acid selectivity and yield.