Fahd N. Al-Wesabi^1,2,*, Huda G. Iskandar^2,3, Saleh Alzahrani⁴, Abdelzahir Abdelmaboud⁴, Mohammed Abdul⁴, Nadhem Nemri⁴, Mohammad Medani⁴, Mohammed Y. Alghamdi⁵

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3789-3806, 2021, DOI:10.32604/cmc.2021.017674

Abstract In this article, a high-sensitive approach for detecting tampering attacks on transmitted Arabic-text over the Internet (HFDATAI) is proposed by integrating digital watermarking and hidden Markov model as a strategy for soft computing. The HFDATAI solution technically integrates and senses the watermark without modifying the original text. The alphanumeric mechanism order in the first stage focused on the Markov model key secret is incorporated into an automated, null-watermarking approach to enhance the proposed approach’s efficiency, accuracy, and intensity. The first-level order and alphanumeric Markov model technique have been used as a strategy for soft computing… More >

Saleem Ibraheem Saleem^*, Adnan Mohsin Abdulazeez

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3353-3372, 2021, DOI:10.32604/cmc.2021.016342

Abstract Writer identification (WI) based on handwritten text structures is typically focused on digital characteristics, with letters/strokes representing the information acquired from the current research in the integration of individual writing habits/styles. Previous studies have indicated that a word’s attributes contribute to greater recognition than the attributes of a character or stroke. As a result of the complexity of Arabic handwriting, segmenting and separating letters and strokes from a script poses a challenge in addition to WI schemes. In this work, we propose new texture features for WI based on text. The histogram of oriented gradient… More >

Saleem Ibraheem Saleem^1,*, Adnan Mohsin Abdulazeez¹, Zeynep Orman²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2727-2754, 2021, DOI:10.32604/cmc.2021.016447

Abstract The writer identification (WI) of handwritten Arabic text is now of great concern to intelligence agencies following the recent attacks perpetrated by known Middle East terrorist organizations. It is also a useful instrument for the digitalization and attribution of old text to other authors of historic studies, including old national and religious archives. In this study, we proposed a new affective segmentation model by modifying an artificial neural network model and making it suitable for the binarization stage based on blocks. This modified method is combined with a new effective rotation model to achieve an… More >

Ra’ed M. Al-Khatib^1,*, Taha Zerrouki², Mohammed M. Abu Shquier³, Amar Balla⁴, Asef Al-Khateeb⁵

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1255-1269, 2021, DOI:10.32604/cmc.2021.016155

Abstract This paper introduces a new enhanced Arabic stemming algorithm for solving the information retrieval problem, especially in medical documents. Our proposed algorithm is a light stemming algorithm for extracting stems and roots from the input data. One of the main challenges facing the light stemming algorithm is cutting off the input word, to extract the initial segments. When initiating the light stemmer with strong initial segments, the final extracting stems and roots will be more accurate. Therefore, a new enhanced segmentation based on deploying the Direct Acyclic Graph (DAG) model is utilized. In addition to More >

Norah Alsaaran^*, Maha Alrabiah

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 471-485, 2021, DOI:10.32604/cmc.2021.016054

Abstract Named Entity Recognition (NER) is one of the fundamental tasks in Natural Language Processing (NLP), which aims to locate, extract, and classify named entities into a predefined category such as person, organization and location. Most of the earlier research for identifying named entities relied on using handcrafted features and very large knowledge resources, which is time consuming and not adequate for resource-scarce languages such as Arabic. Recently, deep learning achieved state-of-the-art performance on many NLP tasks including NER without requiring hand-crafted features. In addition, transfer learning has also proven its efficiency in several NLP tasks… More >

Adnan A. Hnaif^1,*, Emran Kanan², Tarek Kanan¹

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 107-119, 2021, DOI:10.32604/iasc.2021.015939

Abstract In recent years, the use of social media has rapidly increased and developed significant influence on its users. In the study of the behavior, reactions, approval, and interactions of social media users, detecting the polarity (positive, negative, neutral) of news posts is of considerable importance. This proposed research aims to collect data from Arabic social media pages, with the posts comprising the main unit in the dataset, and to build a corpus of manually-processed data for training and testing. Applying Natural Language Processing to the data is crucial for the computer to understand and easily manipulate More >

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… 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… 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… 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… More >