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

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

In the present work a modification was made on three equations to represent the
experiment data which results for Iraqi petroleum and natural asphalt. The equations
have been developed for estimating the chemical composition and physical properties
of asphalt cement at different temperature and aging time. The standard deviations of
all equations were calculated.
The modified correlation related to the aging time and temperature with penetration
index and durability index of aged petroleum and natural asphalts were developed.
The first equation represents the relationship between the durability index with aging
time and temperature.

log_e(DI)=a₁+0.0123(2log_e T

Copper oxide nanoparticles (CuO NPs) were synthesized by two methods. The first was chemical method by using copper nitrate Cu (NO3)2 and NaOH, while the second was green method by using Eucalyptus camaldulensis leaves extract and Cu (NO3)2. These methods easily give a large scale production of CuO nanoparticles. X-ray diffraction pattern (XRD) reveals single phase monoclinic structure. The average crystalline size of CuO NPs was measured and used by Scherrer equation which found 44.06nm from chemical method, while the average crystalline size was found from green method was 27.2nm. The morphology analysis using atomic force microscopy showed that the grain size for CuO NPs was synthesized by chemical and green methods were 77.70 and 89.24

PVC/Kaolinite composites were prepared by the melt intercalation method. Mechanical properties, thermal properties, flammability and water absorption percentage of prepared samples were tested. Mechanical characteristic such as tensile strength, elongation at break; hardness and impact strength (charpy type) were measured for all samples. It was found that the tensile strength and elongation at break of PVC composites decreased with increasing kaolinite loading. Also, the hardness of the composites increases with increase in filler content .The impact strength of the composites at the beginning increases at lower kaolinite loadings is due to the lack of kaolin adhesion to the matrix. However, at higher kaolin loadings. This severe agglom

This research studies the effect of adding micro, nano and hybrid by ratio (1:1) of (Al2O3,TiO2) to epoxy resin on thermal conductivity before and after immersion in HCl acid for (14 day) with normality (0.3 N) at weight fraction (0.02, 0.04, 0.06, 0.08) and thickness (6mm). The results of thermal conductivity reveled that epoxy reinforced by (Al2O3) and mixture (TiO2+Al2O3) increases with increasing the weight fraction, but the thermal conductivity (k) a values for micro and Nano (TiO2) decrease with increasing the weight fraction of reinforced, while the immersion in acidic solution (HCl) that the (k) values after immersion more than the value in before immersion.

The need for wireless sensing technology has rapidly increased recently, specifically the usage of electromagnetic waves which becoming more required as a source of information. Silicon carbide (SiC) Nano particles has been used in this study, the material under test (MUT) was exposed directly to a microwave field to examine the electromagnetic behavior. The permittivity and permeability were investigated with different filler materials to approach best and optimal electromagnetic absorbing characteristics to assist engineers to monitor structure-based composite for defects evaluation that may occur during operation conditions or through manufacturing process. XRD, FESEM and both complex permittivity and permeability were measured f

Single Walled Carbon nanotubes (SWCNTs), as nano-needle structures, are good candidates as nanocarrier delivery systems that carry drug to the site of action. They are good due to their unique pharmaceutical properties. Teniposide is an anticancer drug, which is widely used, but it has a problem of low solubility. In this study, to improve the properties of carbon nanotubes, pre-functionalization of carbon nanotubes via carboxylation with strong acids has been performed and then functionalized through attaching them to the polymer and copolymer. Concurrently, a proper polymer-copolymer combination has been selected by the UV-Visible spectrometer at 880nm. It is selected based on the qualitative dispersibility analysis, the visual observa