Fahd N. Al-Wesabi^1,2,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3635-3648, 2021, DOI:10.32604/cmc.2021.015865

Abstract The digital text media is the most common media transferred via the internet for various purposes and is very sensitive to transfer online with the possibility to be tampered illegally by the tampering attacks. Therefore, improving the security and authenticity of the text when it is transferred via the internet has become one of the most difficult challenges that researchers face today. Arabic text is more sensitive than other languages due to Harakat’s existence in Arabic diacritics such as Kasra, and Damma in which making basic changes such as modifying diacritic arrangements can lead to change the text meaning. In… More >

Ali A.R. Alkhafaji^1,*, Nilam Nur Amir Sjarif¹, M.A Shahidan¹, Nurulhuda Firdaus Mohd Azmi¹, Haslina Md Sarkan¹, Suriayati Chuprat¹, Osamah Ibrahim Khalaf², Ehab Nabiel Al-Khanak³

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3865-3885, 2021, DOI:10.32604/cmc.2021.015803

Abstract The most sensitive Arabic text available online is the digital Holy Quran. This sacred Islamic religious book is recited by all Muslims worldwide including non-Arabs as part of their worship needs. Thus, it should be protected from any kind of tampering to keep its invaluable meaning intact. Different characteristics of Arabic letters like the vowels (), Kashida (extended letters), and other symbols in the Holy Quran must be secured from alterations. The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR) and Embedding Ratio (ER).… More >

Fatmah Baothman^*, Sarah Alssagaff, Bayan Ashmeel

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 519-531, 2021, DOI:10.32604/iasc.2021.014828

Abstract The National Center for Education Statistics study reported that 80% of students change their major or institution at least once before getting a degree, which requires a course equivalency process. This error-prone process varies among disciplines, institutions, regions, and countries and requires effort and time. Therefore, this study aims to overcome these issues by developing a decision support tool called TiMELY for automatic Arabic text recognition using artificial intelligence techniques. The developed tool can process a complete document analysis for several course descriptions in multiple file formats, such as Word, Text, Pages, JPEG, GIF, and JPG. We applied a comparative… More >

Fahd N. Al-Wesabi¹, Abdelzahir Abdelmaboud^2,*, Adnan A. Zain³, Mohammed M. Almazah⁴, Ammar Zahary⁵

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 483-498, 2021, DOI:10.32604/iasc.2021.014322

Abstract Text information depends primarily on natural languages processing. Improving the security and usability of text information shared through the public internet has therefore been the most demanding problem facing researchers. In contact and knowledge sharing through the Internet, the authentication of content and the identification of digital content are becoming a key problem. Therefore, in this paper, a fragile approach of zero-watermarking based on natural language processing has been developed for authentication of content and prevention of misuse of Arabic texts distributed over the Internet. According to the proposed approach, watermark embedding, and identification was technically carried out such that… More >

Abderrahmane Saidi^*, Abdelmouneim Moulay Lakhdar, Mohammed Beladgham

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2875-2889, 2021, DOI:10.32604/cmc.2021.013744

Abstract Handwriting recognition is one of the most significant problems in pattern recognition, many studies have been proposed to improve this recognition of handwritten text for different languages. Yet, Fewer studies have been done for the Arabic language and the processing of its texts remains a particularly distinctive problem due to the variability of writing styles and the nature of Arabic scripts compared to other scripts. The present paper suggests a feature extraction technique for offline Arabic handwriting recognition. A handwriting recognition system for Arabic words using a few important structural features and based on a Radial Basis Function (RBF) neural… More >

Fahd N. Al-Wesabi^1,2,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 195-211, 2021, DOI:10.32604/cmc.2020.012088

Abstract In this paper, a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text contents. The proposed approach known as Second order of Alphanumeric Mechanism of Markov model and Zero-Watermarking Approach (SAMMZWA). Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed approach. The SAMMZWA approach embeds and detects the watermark logically without altering the original text document. The extracted… More >

Amin Alqudah^1,2, Hussein R. Al-Zoubi², Mahmood A. Al-Khassaweneh^2,3, Mohammed Al-Qodah¹

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 493-505, 2018, DOI:10.31209/2018.100000005

Abstract Handwritten numeral recognition is one of the most popular fields of research in automation because it is used in many applications. Indeed, automation has continually received substantial attention from researchers. Therefore, great efforts have been made to devise accurate recognition methods with high recognition ratios. In this paper, we propose a method for integrating the correlation coefficient with a Self-Organizing Maps (SOM)-based technique to recognize offline handwritten Arabic decimal digits. The simulation results show very high recognition rates compared with the rates achieved by other existing methods. More >

Mamouni El Mamoun^1,*, Zennaki Mahmoud¹, Sadouni Kaddour¹

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 995-1008, 2019, DOI:10.32604/cmc.2019.08081

Abstract Using Support Vector Machine (SVM) requires the selection of several parameters such as multi-class strategy type (one-against-all or one-against-one), the regularization parameter C, kernel function and their parameters. The choice of these parameters has a great influence on the performance of the final classifier. This paper considers the grid search method and the particle swarm optimization (PSO) technique that have allowed to quickly select and scan a large space of SVM parameters. A comparative study of the SVM models is also presented to examine the convergence speed and the results of each model. SVM is applied to handwritten Arabic characters… More >

Mahmoud MOUSTAFA^1,2, Saad ALAMRI¹, Hoida ZAKI², Naglaa LOUTFY², Tarek TAHA³, Ali SHATI¹, Mohamed ALKAHTANI¹, Sajda SIDDIQI¹

BIOCELL, Vol.43, No.2, pp. 81-88, 2019, DOI:10.32604/biocell.2019.06231

Abstract The present research reports of quick and marked changes induced by plant extract of Euryops arabicus in the gene expression of 49-kDa apyrases, cytoskeletal proteins, ATPases, ADPase and amount of amino acid of pea (Pisum sativum L. var. Alaska). Pellets of cytoskeletals proteins (27000 xg) were probed with anti-apyrase antibody, biotinylated anti-rat, actin and alpha and beta-tubulin for Western blotting. ATPase and ADPase activities were determined based on the hydrolytic efficacy of adenine triphosphate and adenine diphosphate. By 72 hours, the abundance of apyrases, cytoskeletal proteins and amount of amino acid in pellets of 27000 xg of germinated pea seeds… More >

Maha Al-Yahya^{1, *}

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 421-433, 2019, DOI:10.32604/cmc.2019.06209

Abstract The purpose of this study is to evaluate the performance of five supervised machine learning methods for the task of automated genre identification of classical Arabic texts using text most frequent words as features. We design an experiment for comparing five machine-learning methods for the genre identification task for classical Arabic text. We set the data and the stylometric features and vary the classification method to evaluate the performance of each method. Of the five machine learning methods tested, we can conclude that Support Vector Machine (SVM) are generally the most effective. The contribution of this work lies in the… More >