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  • Open Access

    ARTICLE

    An Expert System to Detect Political Arabic Articles Orientation Using CatBoost Classifier Boosted by Multi-Level Features

    Saad M. Darwish1,*, Abdul Rahman M. Sabri2, Dhafar Hamed Abd2, Adel A. Elzoghabi1

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1595-1624, 2024, DOI:10.32604/csse.2024.054615 - 22 November 2024

    Abstract The number of blogs and other forms of opinionated online content has increased dramatically in recent years. Many fields, including academia and national security, place an emphasis on automated political article orientation detection. Political articles (especially in the Arab world) are different from other articles due to their subjectivity, in which the author’s beliefs and political affiliation might have a significant influence on a political article. With categories representing the main political ideologies, this problem may be thought of as a subset of the text categorization (classification). In general, the performance of machine learning models… More >

  • Open Access

    ARTICLE

    Arabic Dialect Identification in Social Media: A Comparative Study of Deep Learning and Transformer Approaches

    Enas Yahya Alqulaity1, Wael M.S. Yafooz1,*, Abdullah Alourani2, Ayman Jaradat3

    Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 907-928, 2024, DOI:10.32604/iasc.2024.055470 - 31 October 2024

    Abstract Arabic dialect identification is essential in Natural Language Processing (NLP) and forms a critical component of applications such as machine translation, sentiment analysis, and cross-language text generation. The difficulties in differentiating between Arabic dialects have garnered more attention in the last 10 years, particularly in social media. These difficulties result from the overlapping vocabulary of the dialects, the fluidity of online language use, and the difficulties in telling apart dialects that are closely related. Managing dialects with limited resources and adjusting to the ever-changing linguistic trends on social media platforms present additional challenges. A strong… More >

  • Open Access

    ARTICLE

    Enhancing Arabic Cyberbullying Detection with End-to-End Transformer Model

    Mohamed A. Mahdi1, Suliman Mohamed Fati2,*, Mohamed A.G. Hazber1, Shahanawaj Ahamad3, Sawsan A. Saad4

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1651-1671, 2024, DOI:10.32604/cmes.2024.052291 - 27 September 2024

    Abstract Cyberbullying, a critical concern for digital safety, necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces. To tackle this challenge, our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers (BERT) base model (cased), originally pretrained in English. This model is uniquely adapted to recognize the intricate nuances of Arabic online communication, a key aspect often overlooked in conventional cyberbullying detection methods. Our model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media (SM) tweets showing a notable… More >

  • Open Access

    ARTICLE

    Fireworks Optimization with Deep Learning-Based Arabic Handwritten Characters Recognition Model

    Abdelwahed Motwakel1,*, Badriyya B. Al-onazi2, Jaber S. Alzahrani3, Ayman Yafoz4, Mahmoud Othman5, Abu Sarwar Zamani1, Ishfaq Yaseen1, Amgad Atta Abdelmageed1

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1387-1403, 2024, DOI:10.32604/csse.2023.033902 - 13 September 2024

    Abstract Handwritten character recognition becomes one of the challenging research matters. More studies were presented for recognizing letters of various languages. The availability of Arabic handwritten characters databases was confined. Almost a quarter of a billion people worldwide write and speak Arabic. More historical books and files indicate a vital data set for many Arab nations written in Arabic. Recently, Arabic handwritten character recognition (AHCR) has grabbed the attention and has become a difficult topic for pattern recognition and computer vision (CV). Therefore, this study develops fireworks optimization with the deep learning-based AHCR (FWODL-AHCR) technique. The… More >

  • Open Access

    ARTICLE

    Advanced Nanocomposite Arabic Gum Polyacrylic Acid Hydrogels for Flexible Supercapacitors

    Borhan Albiss*, Asala Saleh

    Journal of Renewable Materials, Vol.12, No.7, pp. 1219-1236, 2024, DOI:10.32604/jrm.2024.050685 - 21 August 2024

    Abstract In this work, the fabrication and characterization of the nanocomposite hydrogel, as a solid electrode in electrochemical cell and gel electrolyte material using Indium titanium oxide/polyethylene terephthalate (ITO/PET) flexible substrate for double-layer supercapacitors have been reported. The nanocomposite hydrogel composed of Arabic gum (AG), Acrylic acid (AA), reduced graphene oxide (RGO), and silver nanoparticles (AgNPs) was fabricated via a physical cross-linked polymerization reaction, in which the ascorbic acid was used as a reducing agent to generate AgNPs and to convert Graphene oxide (GO) to RGO during the polymerization reaction. The morphology and structural characteristics of… More > Graphic Abstract

    Advanced Nanocomposite Arabic Gum Polyacrylic Acid Hydrogels for Flexible Supercapacitors

  • Open Access

    ARTICLE

    A Machine Learning Approach to Cyberbullying Detection in Arabic Tweets

    Dhiaa Musleh1, Atta Rahman1,*, Mohammed Abbas Alkherallah1, Menhal Kamel Al-Bohassan1, Mustafa Mohammed Alawami1, Hayder Ali Alsebaa1, Jawad Ali Alnemer1, Ghazi Fayez Al-Mutairi1, May Issa Aldossary2, Dalal A. Aldowaihi1, Fahd Alhaidari3

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1033-1054, 2024, DOI:10.32604/cmc.2024.048003 - 18 July 2024

    Abstract With the rapid growth of internet usage, a new situation has been created that enables practicing bullying. Cyberbullying has increased over the past decade, and it has the same adverse effects as face-to-face bullying, like anger, sadness, anxiety, and fear. With the anonymity people get on the internet, they tend to be more aggressive and express their emotions freely without considering the effects, which can be a reason for the increase in cyberbullying and it is the main motive behind the current study. This study presents a thorough background of cyberbullying and the techniques used… More >

  • Open Access

    ARTICLE

    Chaotic Elephant Herd Optimization with Machine Learning for Arabic Hate Speech Detection

    Badriyya B. Al-onazi1, Jaber S. Alzahrani2, Najm Alotaibi3, Hussain Alshahrani4, Mohamed Ahmed Elfaki4, Radwa Marzouk5, Heba Mohsen6, Abdelwahed Motwakel7,*

    Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 567-583, 2024, DOI:10.32604/iasc.2023.033835 - 11 July 2024

    Abstract In recent years, the usage of social networking sites has considerably increased in the Arab world. It has empowered individuals to express their opinions, especially in politics. Furthermore, various organizations that operate in the Arab countries have embraced social media in their day-to-day business activities at different scales. This is attributed to business owners’ understanding of social media’s importance for business development. However, the Arabic morphology is too complicated to understand due to the availability of nearly 10,000 roots and more than 900 patterns that act as the basis for verbs and nouns. Hate speech… More >

  • Open Access

    ARTICLE

    Optimised CNN Architectures for Handwritten Arabic Character Recognition

    Salah Alghyaline*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4905-4924, 2024, DOI:10.32604/cmc.2024.052016 - 20 June 2024

    Abstract Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles. Arabic is morphologically rich, and its characters have a high similarity. The Arabic language includes 28 characters. Each character has up to four shapes according to its location in the word (at the beginning, middle, end, and isolated). This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters. The proposed architectures were derived from the popular CNN architectures, such as VGG, ResNet, and Inception, to make them applicable to recognizing character-size images. The experimental results on three More >

  • Open Access

    REVIEW

    Coffee Leaf Rust (Hemileia vastatrix) Disease in Coffee Plants and Perspectives by the Disease Control

    Alexis Salazar-Navarro1, Victor Ruiz-Valdiviezo2, Jose Joya-Dávila3, Daniel Gonzalez-Mendoza1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 923-949, 2024, DOI:10.32604/phyton.2024.049612 - 28 May 2024

    Abstract Coffee Leaf Rust (CLR) is caused by Hemileia vastatrix in Coffea spp. It is one of the most dangerous phytopathogens for coffee plantations in terms of coffee productivity and coffee cup quality. In this review, we resume the problem of CLR in Mexico and the pathogenesis of H. vastatrix. The review abord plant-pathogen interactions which lead a compatible or incompatible interactions and result in CLR disease or resistance, respectively. The review abord Coffea spp. defense response pathways involved in H. vastatrix pathogenicity. Additionally, current measures to control H. vastatrix proliferation and germination were aborded focused on phytosanitary actions, and biological More >

  • Open Access

    CORRECTION

    Correction: Computational Linguistics Based Arabic Poem Classification and Dictarization Model

    Manar Ahmed Hamza1,*, Hala J. Alshahrani2, Najm Alotaibi3, Mohamed K. Nour4, Mahmoud Othman5, Gouse Pasha Mohammed1, Mohammed Rizwanullah1, Mohamed I. Eldesouki6

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 869-870, 2024, DOI:10.32604/csse.2024.053660 - 20 May 2024

    Abstract This article has no abstract. More >

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