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).
I've led an end to the Palestinian presence in the Jordan to the occurrence of a major fault line in relations between Jordan and the Palestinian on the levels of all , and as a result sought King Hussein and the initiative of the U.S. to heal the rift that solution between Jordanians , Palestinians, and the regulation of relations between the two parties announced in March 1972 for the project and unitary featuring Jordan and Palestine in the Arab kingdom united with the two countries , but that the Palestine Liberation Organization and the Palestinian resistance factions rejected by asserting that it is has the right of self-determination of the Palestinian people and no one else , and rejected by the Arab states and ( Israel ) , and l
... Show MoreOsteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA usin
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreIn recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
... Show MoreThe research aims to identify the new reality of Iraq’s international relations through the news
coverage carried out by Al-Iraqiya TV since the size and nature of the coverage indicate the extent
to which these relations have reached. The research problem is summarized by the main question
(what is the size and nature of news coverage of Iraq’s international relations in the Iraqi News
Channel?).
This research is considered a descriptive research, as the researchers used the survey method and the
content analysis method through a partial confinement of the research community consisting of the
main news broadcast for one programmatic period. The content analysis form that was subjected to
evaluation was design
This research is intended to high light the uses of political content in foreign Arabic / speaking websites, such as “ CNN “ and” Euro News“, The research problem stems from the main question: What is the nature of the use of the websites in the political content provided through them? A set of sub-questions that give the research aspects and aims to achieve a set of objectives , including the identification of topics that included , the political content provided through , the sample sites during the time period for analysis and determine that the study uses descriptive research based on the discovery of the researcher, describing it accurately and defining the relations between the components.
The research conducted the des
Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p
... Show MoreThis research aims to evaluate the teaching methods used by intermediate Arabic language teachers. To achieve the goal, the researcher followed the descriptive-analytical approach. The research sample was limited to Arabic language teachers at intermediate school for the academic year (2017-2018) the researcher chose a random sample included (155) teachers which form a (40%) Of the original community at Baghdad/ Rusafa1th. The researcher has developed standards of teaching methods which are (7) standards with (39) paragraphs included three alternatives. The results showed the need to pay attention to the use of various modern teaching methods. Moreover, the researcher suggested making an evaluation of the teaching methods used by Arabic
... Show MoreDetection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200
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