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  • Open Access

    ARTICLE

    An Optimized English Text Watermarking Method Based on Natural Language Processing Techniques

    Fahd N. Al-Wesabi1,2,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1519-1536, 2021, DOI:10.32604/cmc.2021.018202

    Abstract In this paper, the text analysis-based approach RTADZWA (Reliable Text Analysis and Digital Zero-Watermarking Approach) has been proposed for transferring and receiving authentic English text via the internet. Second level order of alphanumeric mechanism of hidden Markov model has been used in RTADZWA approach as a natural language processing to analyze the English text and extracts the features of the interrelationship between contexts of the text and utilizes the extracted features as watermark information and then validates it later with attacked English text to detect any tampering occurred on it. Text analysis and text zero-watermarking techniques have been integrated by… More >

  • Open Access

    ARTICLE

    A Markov Model for Subway Composite Energy Prediction

    Xiaokan Wang1,2,*, Qiong Wang1, Liang Shuang3, Chao Chen4

    Computer Systems Science and Engineering, Vol.39, No.2, pp. 237-250, 2021, DOI:10.32604/csse.2021.015945

    Abstract Electric vehicles such as trains must match their electric power supply and demand, such as by using a composite energy storage system composed of lithium batteries and supercapacitors. In this paper, a predictive control strategy based on a Markov model is proposed for a composite energy storage system in an urban rail train. The model predicts the state of the train and a dynamic programming algorithm is employed to solve the optimization problem in a forecast time domain. Real-time online control of power allocation in the composite energy storage system can be achieved. Using standard train operating conditions for simulation,… More >

  • Open Access

    ARTICLE

    Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack

    Fahd N. Al-Wesabi1,2,*, Huda G. Iskandar2,3, 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 to analyze the text of… More >

  • Open Access

    ARTICLE

    Text Analysis-Based Watermarking Approach for Tampering Detection of English Text

    Fahd N. Al-Wesabi1,2,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3701-3719, 2021, DOI:10.32604/cmc.2021.015785

    Abstract Due to the rapid increase in the exchange of text information via internet networks, the security and the reliability of digital content have become a major research issue. The main challenges faced by researchers are authentication, integrity verification, and tampering detection of the digital contents. In this paper, text zero-watermarking and text feature-based approach is proposed to improve the tampering detection accuracy of English text contents. The proposed approach embeds and detects the watermark logically without altering the original English text document. Based on hidden Markov model (HMM), the fourth level order of the word mechanism is used to analyze… More >

  • Open Access

    ARTICLE

    State-Based Offloading Model for Improving Response Rate of IoT Services

    K. Sakthidasan1, Bhekisipho Twala2, S. Yuvaraj3, K. Vijayan3,*, S. Praveenkumar3, Prashant Mani4, C. Bharatiraja3

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3721-3735, 2021, DOI:10.32604/cmc.2021.014321

    Abstract The Internet of Things (IoT) is a heterogeneous information sharing and access platform that provides services in a pervasive manner. Task and computation offloading in the IoT helps to improve the response rate and the availability of resources. Task offloading in a service-centric IoT environment mitigates the complexity in response delivery and request processing. In this paper, the state-based task offloading method (STOM) is introduced with a view to maximize the service response rate and reduce the response time of the varying request densities. The proposed method is designed using the Markov decision-making model to improve the rate of requests… More >

  • Open Access

    ARTICLE

    Improving Language Translation Using the Hidden Markov Model

    Yunpeng Chang1, Xiaoliang Wang1,*, Meihua Xue1, Yuzhen Liu1, Frank Jiang2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3921-3931, 2021, DOI:10.32604/cmc.2021.012304

    Abstract Translation software has become an important tool for communication between different languages. People’s requirements for translation are higher and higher, mainly reflected in people’s desire for barrier free cultural exchange. With a large corpus, the performance of statistical machine translation based on words and phrases is limited due to the small size of modeling units. Previous statistical methods rely primarily on the size of corpus and number of its statistical results to avoid ambiguity in translation, ignoring context. To support the ongoing improvement of translation methods built upon deep learning, we propose a translation algorithm based on the Hidden Markov… More >

  • Open Access

    ARTICLE

    Proposing a High-Robust Approach for Detecting the Tampering Attacks on English Text Transmitted via Internet

    Fahd N. Al-Wesabi1,*, Huda G. Iskandar2, Mohammad Alamgeer3, Mokhtar M. Ghilan2

    Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1267-1283, 2020, DOI:10.32604/iasc.2020.013782

    Abstract In this paper, a robust approach INLPETWA (an Intelligent Natural Language Processing and English Text Watermarking Approach) is proposed to tampering detection of English text by integrating zero text watermarking and hidden Markov model as a soft computing and natural language processing techniques. In the INLPETWA approach, embedding and detecting the watermark key logically conducted without altering the plain text. Second-gram and word mechanism of hidden Markov model is used as a natural text analysis technique to extracts English text features and use them as a watermark key and embed them logically and validates them during detection process to detect… More >

  • Open Access

    ARTICLE

    An Accurate Persian Part-of-Speech Tagger

    Morteza Okhovvat1,∗, Mohsen Sharifi2,†, Behrouz Minaei Bidgoli2,‡

    Computer Systems Science and Engineering, Vol.35, No.6, pp. 423-430, 2020, DOI:10.32604/csse.2020.35.423

    Abstract The processing of any natural language requires that the grammatical properties of every word in that language are tagged by a part of speech (POS) tagger. To present a more accurate POS tagger for the Persian language, we propose an improved and accurate tagger called IAoM that supports properties of text to speech systems such as Lexical Stress Search, Homograph words Disambiguation, Break Phrase Detection, and main aspects of Persian morphology. IAoM uses Maximum Likelihood Estimation (MLE) to determine the tags of unknown words. In addition, it uses a few defined rules for the sake of achieving high accuracy. For… More >

  • Open Access

    ARTICLE

    A Phoneme-Based Approach for Eliminating Out-of-vocabulary Problem Turkish Speech Recognition Using Hidden Markov Model

    Erdem Yavuz1,∗, Vedat Topuz2

    Computer Systems Science and Engineering, Vol.33, No.6, pp. 429-445, 2018, DOI:10.32604/csse.2018.33.429

    Abstract Since Turkish is a morphologically productive language, it is almost impossible for a word-based recognition system to be realized to completely model Turkish language. Due to the fact that it is difficult for the system to recognize words not introduced to it in a word-based recognition system, recognition success rate drops considerably caused by out-of-vocabulary words. In this study, a speaker-dependent, phoneme-based word recognition system has been designed and implemented for Turkish Language to overcome the problem. An algorithm for finding phoneme-boundaries has been devised in order to segment the word into its phonemes. After the segmentation of words into… More >

  • Open Access

    ARTICLE

    Intelligent Speech Communication Using Double Humanoid Robots

    Li-Hong Juang1,*, Yi-Hua Zhao2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 291-301, 2020, DOI:10.31209/2020.100000164

    Abstract Speech recognition is one of the most convenient forms of human beings engaging in the exchanging of information. In this research, we want to make robots understand human language and communicate with each other through the human language, and to realize man–machine interactive and humanoid– robot interactive. Therefore, this research mainly studies NAO robots’ speech recognition and humanoid communication between double -humanoid robots. This paper introduces the future direction and application prospect of speech recognition as well as its basic method and knowledge of speech recognition fields. This research also proposes the application of the most advanced method—establishment of the… More >

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