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  • Open Access


    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

    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


    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

    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


    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

    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


    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

    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: 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

    Abstract This article has no abstract. More >

  • Open Access


    Improving the Segmentation of Arabic Handwriting Using Ligature Detection Technique

    Husam Ahmad Al Hamad*, Mohammad Shehab*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2015-2034, 2024, DOI:10.32604/cmc.2024.048527

    Abstract Recognizing handwritten characters remains a critical and formidable challenge within the realm of computer vision. Although considerable strides have been made in enhancing English handwritten character recognition through various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexity arises from the diverse array of writing styles among individuals, coupled with the various shapes that a single character can take when positioned differently within document images, rendering the task more perplexing. In this study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locate the local minima of the vertical… More >

  • Open Access


    KurdSet: A Kurdish Handwritten Characters Recognition Dataset Using Convolutional Neural Network

    Sardar Hasen Ali*, Maiwan Bahjat Abdulrazzaq

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 429-448, 2024, DOI:10.32604/cmc.2024.048356

    Abstract Handwritten character recognition (HCR) involves identifying characters in images, documents, and various sources such as forms surveys, questionnaires, and signatures, and transforming them into a machine-readable format for subsequent processing. Successfully recognizing complex and intricately shaped handwritten characters remains a significant obstacle. The use of convolutional neural network (CNN) in recent developments has notably advanced HCR, leveraging the ability to extract discriminative features from extensive sets of raw data. Because of the absence of pre-existing datasets in the Kurdish language, we created a Kurdish handwritten dataset called (KurdSet). The dataset consists of Kurdish characters, digits,… More >

  • Open Access


    Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

    Ibrahim M. Alwayle1, Hala J. Alshahrani2, Saud S. Alotaibi3, Khaled M. Alalayah1, Amira Sayed A. Aziz4, Khadija M. Alaidarous1, Ibrahim Abdulrab Ahmed5, Manar Ahmed Hamza6,*

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 153-168, 2023, DOI:10.32604/iasc.2023.034718

    Abstract Abstractive text summarization is crucial to produce summaries of natural language with basic concepts from large text documents. Despite the achievement of English language-related abstractive text summarization models, the models that support Arabic language text summarization are fewer in number. Recent abstractive Arabic summarization models encounter different issues that need to be resolved. Syntax inconsistency is a crucial issue resulting in the low-accuracy summary. A new technique has achieved remarkable outcomes by adding topic awareness in the text summarization process that guides the module by imitating human awareness. The current research article presents Abstractive Arabic… More >

  • Open Access


    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.1, pp. 97-114, 2024, DOI:10.32604/csse.2023.034520

    Abstract Computational linguistics is the scientific and engineering discipline related to comprehending written and spoken language from a computational perspective and building artefacts that effectively process and produce language, either in bulk or in a dialogue setting. This paper develops a Chaotic Bird Swarm Optimization with deep ensemble learning based Arabic poem classification and dictarization (CBSOEDL-APCD) technique. The presented CBSOEDL-APCD technique involves the classification and dictarization of Arabic text into Arabic poetries and prose. Primarily, the CBSOEDL-APCD technique carries out data pre-processing to convert it into a useful format. Besides, the ensemble deep learning (EDL) model More >

  • Open Access


    Multi-Versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis on Arabic Corpus

    Mesfer Al Duhayyim1,*, Badriyya B. Al-onazi2, Jaber S. Alzahrani3, Hussain Alshahrani4, Mohamed Ahmed Elfaki4, Abdullah Mohamed5, Ishfaq Yaseen6, Gouse Pasha Mohammed6, Mohammed Rizwanullah6, Abu Sarwar Zamani6

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3049-3065, 2023, DOI:10.32604/csse.2023.033836

    Abstract Sentiment analysis (SA) of the Arabic language becomes important despite scarce annotated corpora and confined sources. Arabic affect Analysis has become an active research zone nowadays. But still, the Arabic language lags behind adequate language sources for enabling the SA tasks. Thus, Arabic still faces challenges in natural language processing (NLP) tasks because of its structure complexities, history, and distinct cultures. It has gained lesser effort than the other languages. This paper developed a Multi-versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis (MVODRL-AA) on Arabic Corpus. The presented MVODRL-AA model majorly concentrates on identifying… More >

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