Preferred Language
Articles
/
bsj-7427
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
...Show More Authors

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).

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
...Show More Authors

View Publication Preview PDF
Scopus (36)
Crossref (24)
Scopus Clarivate Crossref
Publication Date
Tue Jul 01 2014
Journal Name
Ieee Transactions On Circuits And Systems I: Regular Papers
Crosstalk-Aware Multiple Error Detection Scheme Based on Two-Dimensional Parities for Energy Efficient Network on Chip
...Show More Authors

Achieving reliable operation under the influence of deep-submicrometer noise sources including crosstalk noise at low voltage operation is a major challenge for network on chip links. In this paper, we propose a coding scheme that simultaneously addresses crosstalk effects on signal delay and detects up to seven random errors through wire duplication and simple parity checks calculated over the rows and columns of the two-dimensional data. This high error detection capability enables the reduction of operating voltage on the wire leading to energy saving. The results show that the proposed scheme reduces the energy consumption up to 53% as compared to other schemes at iso-reliability performance despite the increase in the overhead number o

... Show More
View Publication
Scopus (25)
Crossref (19)
Scopus Clarivate Crossref
Publication Date
Wed Dec 28 2022
Journal Name
Al–bahith Al–a'alami
Topics and political frameworks for the news of the Iraqi Ministry of Foreign Affairs on its website: an analytical study
...Show More Authors

This is a descriptive study that used the survey method, it’s aimed to identify the topics and frameworks of diplomatic and political issues covered by the news of the website of the Iraqi Ministry of Foreign Affairs, through the content analysis method applied on a sample selected in a systematic random manner for news published in the year 2021. The sample included (191) news equivalent to (20%) of the total study population of (942). The study reached some results, the most important of which were as follows: The political issue, in its general sense, grabbed the most prominent attention among the various issues and events focused on by Iraqi diplomacy: "international cooperation", "bilateral cooperation", and then "regional politic

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
...Show More Authors

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

... Show More
View Publication Preview PDF
Scopus (21)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Scientific Development For Studies And Research
The Role of E-Learning in teaching the Arabic language to non- native speakers
...Show More Authors

After the information revolution that occurred in the Western world, and the developments in all fields, especially in the field of education and e-learning, from an integrated system based on the effective employment of information and communication technology in the teaching and learning processes through an environment rich in computer and Internet applications, the community and the learner were able to access information sources and learning at any time and place, in a way that achieves mutual interaction between the elements of the system and the surrounding environment. After the occurrence of the phenomenon of Covid 19, it led to a major interruption in all educational systems that had never happened before, and the disrupt

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection
...Show More Authors

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust EA wit

... Show More
View Publication
Scopus (2)
Scopus Crossref
Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
...Show More Authors

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
Mental motivation among students of Arabic language departments and its relationship to their attitudes towards the profession
...Show More Authors

The aim of the research is to know the level of mental motivation among students of the Arabic language departments in the Faculties of Education in the universities of Baghdad Governorate and its relationship to their attitudes towards the profession, and the level of orientation towards the profession among students of the Arabic language departments in the Faculties of Education. And the correlational relationship between mental motivation and career orientation among students of Arabic language departments in the Faculties of Education, and the current research is determined by students of Arabic language departments in the Faculties of Education and the universities (Education Ibn Rushd-  University of Baghdad, Education- &nbsp

... Show More
View Publication Preview PDF
Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
...Show More Authors

View Publication
Scopus (16)
Crossref (4)
Scopus Crossref
Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network
...Show More Authors

The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w

... Show More
View Publication Preview PDF
Crossref