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).
Andalusian women enjoyed much historical news in the fluorescence of Andalusia, describing it as beautiful and good cohabitation, as the men were involved in conquests, including those who were wives of the caliphs, including scientists, singers, and adept writers Hassan and tongue, in addition to the acquisition of masters in slave markets in Cordoba, Seville and many cities, In addition, Andalusian women enjoy freedom in their relationship with men and have been reflected in the historical fluorescence of Andalusia, such as the book of the history of Ibn Abdul Malik bin Habib al-Alberi (d. And the collar of the dove repented in intimacy and thousands of Ibn Hazm al-Qurtubi (d. 456 AH / 1065 CE), the book of Hilla al-Sayra of Ibn al-Wel
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I have written my most important findings in my research are as follows:
The book forty nuclear is one of the writings of the nuclear imam "God's mercy" in which he had collected ahaadeeth from several different sections and diverse, has been described by scientists as the orbit of Islam are all valid conversations.
the duty to pay attention to the Sunnah of the Prophet from the linguistic point of view because it is very rich news and constructional evidence in all sections contained the forty nuclear talks on the news sentences in (30) places divided between the news request, as stated in (13)
home and primary news in (14) home and the news denial in (3) c
... Show MoreNewspaper headlines are described as compressed and ambiguous pieces of discourse that represent the bodies of the articles. Their main function is to provide the readers with an informative message they would have no prior idea about. Ifantidou (2009) claims that the function of a headline is to get the readers’ attention rather than providing information because it does not have to represent the whole of the article it refers to. This paper aims at examining this hypothesis in relation to scientific news headlines reported by a number of news agencies. The paper follows Halliday (1967) information structure theory by applying it on ten selected headlines; each two headlines represent one scientific discovery reported by different new
... Show MoreInformation processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (
... Show MoreThe study is dealing with an application reengineering process clean solar cells in the Ministry of electricity, as aimed at the possibility of the applicability and impact of re-engineering to achieve the level of performance of the Ministry's operations, with the application of the cleaning process solar cells, developed, improved and found a correlation, statistically significant effect between variable re-engineering and performance as well as the application of process reengineering clean solar cells:1- Before the re-engineering process the total time for cleaning up and solar cell 20 minutes and number of columns performed per day 24 columns and total columns750 which were completed per month that re
... Show MoreThe road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o
... Show MoreTranslation is a dynamic and living process that cannot be considered equal to the original text and requires the appropriate structure, language, thought and culture of the target language, and the translator's intellectual, linguistic and cultural influences inadvertently penetrate into the translated text. It causes heterogeneity of the destination text with the source text.
Admiral's theory is trying to help by providing components and suggested approaches to resolve these inconsistencies. In the meantime, in addition to the mission of putting words together, the translator must sometimes sit in the position of the reader and judge and evaluate the translated text in order to understand its shortcomings and try to correct it a
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
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