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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
Wed Oct 25 2023
Journal Name
College Of Islamic Sciences
The good and bad words in Surah Ibrahim, peace be upon him
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In the name of God, the Most Gracious, the Most Merciful

Praise be to God who revived Balu. And the good word brought hard hearts after removing from them what had almost killed them of ignorance, injustice, hatred, hostility, estrangement, and irritation... So God replaced for them what was best with what was best in terms of knowledge and fairness, and what was corrupt, love, and altruism. So the example of a believer and a good word is like a tree with good roots and branches. Then I pray and greet the one who watered it from the pure and inexhaustible spring of Islam, our Master Muhammad, so that the valleys flowed in their capacity, and the crops grew, then they became thicker and became even, and their good fruits in behavi

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Publication Date
Fri Oct 02 2009
Journal Name
Noise And Health
Expert system to predict effects of noise pollution on operators of power plant using neuro-fuzzy approach
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Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems

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Publication Date
Fri Jan 25 2019
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics Vol
Predicate the Ability of Extracorporeal Shock Wave Lithotripsy (ESWL) to treat the Kidney Stones by used Combined Classifier
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Extracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone. Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment. The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on. Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or tousing another remedy technique. In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classi

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Sun May 01 2016
Journal Name
Iraqi Journal Of Science
Efficient text in image hiding method based on LSB method principle
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The steganography (text in image hiding) methods still considered important issues to the researchers at the present time. The steganography methods were varied in its hiding styles from a simple to complex techniques that are resistant to potential attacks. In current research the attack on the host's secret text problem didn’t considered, but an improved text hiding within the image have highly confidential was proposed and implemented companied with a strong password method, so as to ensure no change will be made in the pixel values of the host image after text hiding. The phrase “highly confidential” denoted to the low suspicious it has been performed may be found in the covered image. The Experimental results show that the covere

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Publication Date
Tue Mar 01 2022
Journal Name
Sustainable Studies
Description of the word formation system in contemporary Russian
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This paper deals with the description of the system of formation and derivation of words in the Russian language. In this work, we will present recent trends in the study of the Russian language that deal with vocabulary formation. The lexical system of the Russian language is associated with a common (or opposite) meaning; similar (or opposite) in stylistic characteristics; united by a common type of word formation; related to a common descent and belonging to a vocabulary of much or little use, etc. The results of the most prominent linguists and specialists who dealt with this topic will be presented, in addition to presenting their different views on word formation. The words of the Russian language consist of mor vimat that participate

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Publication Date
Fri Jun 30 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory
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Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

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Publication Date
Sun Jan 02 2022
Journal Name
Journal Of The College Of Languages (jcl)
Lexical Characteristics of the Translation of the Russian Newspapers: "Komsomolskaya Pravda" as Example: Лексические особенности перевода газетных заголовков (На материале газеты «Комсомольская правда»)
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      The present study discusses the semantic characteristics of the Russian newspapers journalistic headlines (The Russian newspaper "Komsomolskaya Pravda" as Example"). The study traces the characteristics of the Russian newspaper headlines, its relevance to grammar, syntax, lexical items and style. These characteristics in Russian will be investigated and compared to their Arabic correspondents in the process of translation. The study also specifies the meanings and the functions of the newspaper headlines in the light of modern linguistics stressing the grammatical, lexical and stylistic aspects of headlines translation from Russian into Arabic.

       J

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Publication Date
Sun Jan 02 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Role Of Historical Memory In Promoting The Concept Of Belonging To The Homeland In A Novel "Mazurka For Two Dead Men" Of The Spanish Novelist Camilo Jose Cela: El Papel De La Memoria Histórica En El Apoyo Del Concepto De Pertenencia A La Patria , En La Novela “Mazurca Para Dos Muertos”, De Camilo José Cela
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       The present study discusses the significant role of the historical memory in all the Spanish society aspects of life. When a novelist takes the role and puts on the mask of one of the novel’s protagonists or hidden characters, his memory of the events becomes the keywords of accessing the close-knit fabric of society and sheds lights on deteriorating social conceptions in  a backwards social reality that rejects all new progressive ideas and  modernity. Through concentrating on the society flawing aspects and employing everything of his stored memory, the author uses sarcasm to criticize and change such old deteriorating reality conceptions.   

   &nbs

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Wear Parameters in AISI 4340 Steel
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Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

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