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

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

Removal of Congo red, Rhodamine B, and Dispers Blue dyes from water solution have been achieved using Flint Clay as an adsorbent. The adsorption was studied as a function of contact time, adsorbent dose, pH, and temperature under batch adsorption technique. The equilibrium data fit with Langmuir, Freundlich and Toth models of adsorption and the linear regression coefficient R2 was used to elucidate the best fitting isotherm model. Different thermodynamic parameters, namely Gibb’s free energy, enthalpy and entropy of the on-going adsorption process have also been evaluated. Batch technique has been employed for the kinetic measurements and the adsorption of the three dyes follows a second order rate kinetics. The kinetic investigations al

The remove of direct blue (DB71) anionic dye on flint clay in aqueous solution was investigated by using a batch system for various dye concentrations. The contact time, pH, adsorbent dose, and temperature was studied under batch adsorption technique. The data of adsorption equilibrium fit with isotherm Langmuar and Freiundlich ,when the correlation coefficient used to elucidate the best fitting isotherm model. The thermodynamic parameters such as, ?Hº ,?Sº and ?Gº. Thermodynamic analysis indicated that the sorption of the dyes onto Flint clay was endothermic and spontaneous.

The coordination ability of the azo-Schiff base 2-[1,5-Dimethyl-3-[2-(5-methyl-1H-indol-3-yl)-ethyl imino]-2-phenyl-2,3-dihydro-1H-pyrazol-4-ylazo]-5- hydroxy-benzoic acid has been proven in complexation reactions with Co(II), Ni(II), Cu(II), Pd(II) and Pt(II) ions. The free ligand (LH) and its complexes were characterized using elemental analysis, determination of metal concentration, magnetic susceptibility, molar conductivity, FTIR, Uv-Vis, (1H, 13C) NMR spectra, mass spectra and thermal analysis (TGA). The results confirmed the coordination of the ligand through the nitrogen of the azomethine, Azo group (Azo) and the carboxylate ion with the metal ions. The activation thermodynamic parameters, such as ΔE*, ΔH*, ΔS*, ΔG*and K are cal

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Activated carbon was Produced from coconut shell and was used for removing sulfate from industrial waste water in batch Processes. The influence of various parameter were studied such as pH (4.5 – 9.) , agitation time (0 – 120)min and adsorbent dose (2 – 10) gm.

The Langmuir and frandlich adsorption capacity models were been investigated where showed there are fitting with langmmuir model with squre regression value ( 0.76). The percent of removal of  sulfate (22% - 38%) at (PH=7) in the isotherm experiment increased  with adsorbent mass increasing. The maximum removal value of sulfate at  different pH experiments is (43%) at pH=7.

New technologies have risen into popularity causing the Liquid membrane techniques to evolve over other separation techniques due to its high selectivity and recovery, increased fluxes, and reduced investment and operating cost. This work focuses on extracting Methylene Blue (MB), a cationic dye using a simple BLM separation technique from its aqueous phase. It combines extraction and stripping in a single unit operation. The feed phase was an aqueous solution of MB, the solvent chosen was soybean oil for the liquid/organic membrane phase, and tri-octyl amine acted as a carrier. The strip phase was a hydrochloric acid solution for this study. A two-phase equilibrium study was done to choose the correct solvent, carrier,

Adsorption experiments were carried out using two different low-cost sorbent materials, date seeds and olive seeds. These sorbents used as a single phase (not as mixture) to remove cadmium ions from simulated wastewater by adsorption process. The equilibrium time was found at 2 hr. The experiments include different parameters such sorbent type and weight and contact time. It was found that both of olive seed and date seed have approximately the same adsorption capacity (qm) with 15.644 mg/g and 15.2112 mg/g, respectively. Equilibrium isotherms and kinetic studies have been carried out. Langmuir isotherm model better fits the experimental data compared with the Freundlich isotherm for olive seed, while Freundlich isotherm fits for date se