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bsj-7427
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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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 Network (Text-CNN) and Long Short-Term Memory (LSTM) architecture to produce efficient hybrid model. Text-CNN is used to identify the relevant features, whereas the LSTM is applied to deal with the long-term dependency of sequence. The results showed that when trained individually, the proposed model outperformed both the Text-CNN and the LSTM. Accuracy was used as a measure of model quality, whereby the accuracy of the Hybrid Deep Neural Network is (0.914), while the accuracy of both Text-CNN and LSTM is (0.859) and (0.878), respectively. Moreover, the results of our proposed model are better compared to previous work that used the same dataset (AraNews dataset).

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Publication Date
Mon Nov 19 2018
Journal Name
Al–bahith Al–a'alami
Analytical Study of Cartoon picture AL-Mada Newspaper is a model
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The researcher studies and explains the content of some pictures that are published in al-Mada newspaper. The research is important as it deals with a topic that has a relation with visual culture and its role to transfer the press letter to the audience. The researcher finds that cartoonist exposed the security services through important people who have a major role in state policy and reveals the level of corruption and the weak treatments for this phenomenon and its reflection on the whole society and individuals. In addition to that, cartoonists try to encourage the public for going on the peaceful demonstrations since it is a good tool to make pressure on the government to punish the corrupts.

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Publication Date
Sun Feb 01 2015
Journal Name
Journal Of Engineering
Planning of Distribution Networks in Baghdad City
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Planning of electrical distribution networks is considered of highest priority at the present time in Iraq, due to the huge increase in electrical demand and expansions imposed on distribution networks as a result of the great and rapid urban development.

Distribution system planning simulates and studies the behavior of electrical distribution networks under different operating conditions. The study provide understanding of the existing system and to prepare a short term development plan or a long term plan used to guide system expansion and future investments needed for improved network performance.

The objective of this research is the planning of Al_Bayaa 11 kV distribution network in Baghdad city bas

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

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Publication Date
Sat Jan 01 2022
Journal Name
Graphene, Nanotubes And Quantum Dots-based Nanotechnology
Functionalized nanotubes
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Deep eutectic solvents (DESs) are considered as relativity green solvents in comparison with ionic liquids and organic solvents. DESs are used in nanotechnology applications due to their unique physiochemical properties, efficient dispersants and they can be easily prepared in high purity at low cost. Other advantages include their nontoxicity, no reactivity with water and being biodegradable. DESs have recently attracted much attention in various fields, especially in the field of nanotechnology in controlling the size, surface chemistry and morphology of the nanomaterials and in the processing of advanced functional nanomaterials. As a result, various studies have been undertaken to investigate the physicochemical characteristics of the c

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Publication Date
Sat Apr 04 2015
Journal Name
International Journal Of Advanced Technology In Engineering And Science
SYNTHESIS OF ZNO QUANTUM DOT BY SELF ASSEMBLY METHOD AND ZNO NANOROD BY HYDROTHERMAL METHOD
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In this work, ZnO quantum dots (Q.dots) and nanorods were prepared. ZnO quantum dots were prepared by self-assembly method of zinc acetate solution with KOH solution, while ZnO nanorods were prepared by hydrothermal method of zinc nitrate hexahydrate Zn (NO3)2.6H2O with hexamethy lenetetramin (HMT) C6H12N4. The optical , structural and spectroscopic properties of the product quantum dot were studied. The results show the dependence of the optical properties on the crystal dimension and the formation of the trap states in the energy band gap. The deep levels emission was studied for n-ZnO and p-ZnO. The preparation ZnO nanorods show semiconductor behavior of p-type, which is a difficult process by doping because native defects.

Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Effect of Variation of Degree of Saturation with depth on Soil–Concrete Pile Interface in Clayey Soil
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Bearing capacity of a concrete pile in fine grained cohesive soils is affected by the degree of saturation of the surrounding soil through the contribution of the matric suction. In addition, the embedded depth and the roughness of the concrete pile surface (expressed as British Pendulum Number BPN) also have their contribution to the shear strength of the concrete pile, consequently its bearing capacity. Herein, relationships among degree of saturation, pile depth, and surface roughness, were proposed as a mathematical model expressed as an equation where the shear strength of a pile can be predicted in terms of degree of saturation, depth, and BPN. Rel

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Taxonomy of Memory Usage in Swarm Intelligence-Based Metaheuristics
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Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Synthesis and Characterization of Gold Nanoparticles by Aluminum as a Reducing Agent
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             The synthesis of nanoparticles (GNPs) from the reduction of HAuCl4 .3H2O by aluminum metal was obtained in aqueous solution with the use of Arabic gum as a stabilizing agent. The GNPs were characterized by TEM, AFM and Zeta potential spectroscopy. The reduction process was monitored over time by measuring ultraviolet spectra at a range of λ 520-525 nm. Also the color changes from yellow to ruby red, shape and size of GNP was studied by TEM. Shape was spherical and the size of particles was (12-17.5) nm. The best results were obtained at pH 6.

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