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  • Open Access


    Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’ Response Against COVID Variants

    Hassam Tahir1, Muhammad Shahbaz Khan1, Fawad Ahmed2, Abdullah M. Albarrak3, Sultan Noman Qasem3, Jawad Ahmad4,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3517-3535, 2023, DOI:10.32604/cmc.2023.035410

    Abstract The COVID-19 outbreak began in December 2019 and was declared a global health emergency by the World Health Organization. The four most dominating variants are Beta, Gamma, Delta, and Omicron. After the administration of vaccine doses, an eminent decline in new cases has been observed. The COVID-19 vaccine induces neutralizing antibodies and T-cells in our bodies. However, strong variants like Delta and Omicron tend to escape these neutralizing antibodies elicited by COVID-19 vaccination. Therefore, it is indispensable to study, analyze and most importantly, predict the response of SARS-CoV-2-derived t-cell epitopes against Covid variants in vaccinated… More >

  • Open Access


    Data-Driven Probabilistic System for Batsman Performance Prediction in a Cricket Match

    Fawad Nasim1,2,*, Muhammad Adnan Yousaf1, Sohail Masood1,2, Arfan Jaffar1,2, Muhammad Rashid3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2865-2877, 2023, DOI:10.32604/iasc.2023.034258

    Abstract Batsmen are the backbone of any cricket team and their selection is very critical to the team’s success. A good batsman not only scores run but also provides stability to the team’s innings. The most important factor in selecting a batsman is their ability to score runs. It is a generally accepted notion that the future performance of a batsman can be predicted by observing and analyzing their past record. This hypothesis is based on the fact that a player’s batting average is generally considered to be a good indicator of their future performance. We… More >

  • Open Access


    An Efficient Long Short-Term Memory Model for Digital Cross-Language Summarization

    Y. C. A. Padmanabha Reddy1, Shyam Sunder Reddy Kasireddy2, Nageswara Rao Sirisala3, Ramu Kuchipudi4, Purnachand Kollapudi5,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6389-6409, 2023, DOI:10.32604/cmc.2023.034072

    Abstract The rise of social networking enables the development of multilingual Internet-accessible digital documents in several languages. The digital document needs to be evaluated physically through the Cross-Language Text Summarization (CLTS) involved in the disparate and generation of the source documents. Cross-language document processing is involved in the generation of documents from disparate language sources toward targeted documents. The digital documents need to be processed with the contextual semantic data with the decoding scheme. This paper presented a multilingual cross-language processing of the documents with the abstractive and summarising of the documents. The proposed model is More >

  • Open Access


    Challenges and Limitations in Speech Recognition Technology: A Critical Review of Speech Signal Processing Algorithms, Tools and Systems

    Sneha Basak1, Himanshi Agrawal1, Shreya Jena1, Shilpa Gite2,*, Mrinal Bachute2, Biswajeet Pradhan3,4,5,*, Mazen Assiri4

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2022.021755

    Abstract Speech recognition systems have become a unique human-computer interaction (HCI) family. Speech is one of the most naturally developed human abilities; speech signal processing opens up a transparent and hand-free computation experience. This paper aims to present a retrospective yet modern approach to the world of speech recognition systems. The development journey of ASR (Automatic Speech Recognition) has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper. A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented, along with a brief discussion of various More >

  • Open Access


    Customer Segment Prediction on Retail Transactional Data Using K-Means and Markov Model

    A. S. Harish*, C. Malathy

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 589-600, 2023, DOI:10.32604/iasc.2023.032030

    Abstract Retailing is a dynamic business domain where commodities and goods are sold in small quantities directly to the customers. It deals with the end user customers of a supply-chain network and therefore has to accommodate the needs and desires of a large group of customers over varied utilities. The volume and volatility of the business makes it one of the prospective fields for analytical study and data modeling. This is also why customer segmentation drives a key role in multiple retail business decisions such as marketing budgeting, customer targeting, customized offers, value proposition etc. The… More >

  • Open Access


    Damage and Deterioration Model of Basalt Fiber/Magnesium Oxychloride Composites Based on GM(1, 1)-Markov in the Salt Spray Corrosion Environment

    Jianqiao Yu1,*, Hongxia Qiao1,2, Theogene Hakuzweyezu1, Feifei Zhu1

    Journal of Renewable Materials, Vol.10, No.11, pp. 2973-2987, 2022, DOI:10.32604/jrm.2022.019620

    Abstract This study was designed to solve the problem of magnesium hazards due to potash extraction in the salt lake region. Using basalt fiber (BF) as the reinforcement material and magnesium oxychloride cement (MOC) as the gelling material, a BF/MOC composite material was prepared. Firstly, the effect of BF addition content on the basic mechanical properties of the composites was investigated. Then, through the salt spray corrosion test, the durability damage deterioration evaluation analysis was carried out from both macroscopic and microscopic aspects using mass change, relative dynamic modulus of elasticity (RDME) change, SEM analysis and… More >

  • Open Access


    Hybrid GrabCut Hidden Markov Model for Segmentation

    Soobia Saeed1,*, Afnizanfaizal Abdullah1, N. Z. Jhanjhi2, Mehmood Naqvi3, Mehedi Masud4, Mohammed A. AlZain5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 851-869, 2022, DOI:10.32604/cmc.2022.024085

    Abstract Diagnosing data or object detection in medical images is one of the important parts of image segmentation especially those data which is less effective to identify in MRI such as low-grade tumors or cerebral spinal fluid (CSF) leaks in the brain. The aim of the study is to address the problems associated with detecting the low-grade tumor and CSF in brain is difficult in magnetic resonance imaging (MRI) images and another problem also relates to efficiency and less execution time for segmentation of medical images. For tumor and CSF segmentation using trained light field database… More >

  • Open Access


    Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

    Mohammad Alamgeer1, Fahd N. Al-Wesabi2,3,*, Huda G. Iskandar3,4, Imran Khan5, Nadhem Nemri6, Mohammad Medani6, Mohammed Abdullah Al-Hagery7, Ali Mohammed Al-Sharafi3,8

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2497-2513, 2022, DOI:10.32604/cmc.2022.018591

    Abstract Content authentication, integrity verification, and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication technology. In this paper, a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking (SFASCDW) is proposed for content authentication and tampering detection of English text. A first-level order of alphanumeric mechanism, based on hidden Markov model, is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed approach. The researcher uses the first-level order and alphanumeric mechanism of Markov model as… More >

  • Open Access


    Securing Arabic Contents Algorithm for Smart Detecting of Illegal Tampering Attacks

    Mesfer Al Duhayyim1, Manal Abdullah Alohali2, Fahd N. Al-Wesabi3,4, Anwer Mustafa Hilal5,*, Mohammad Medani3, Manar Ahmed Hamza5

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2879-2894, 2022, DOI:10.32604/cmc.2022.019594

    Abstract The most common digital media exchanged via the Internet is in text form. The Arabic language is considered one of the most sensitive languages of content modification due to the presence of diacritics that can cause a change in the meaning. In this paper, an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the Internet. The core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking techniques. The watermark key will be generated by utilizing the extracted features of the text More >

  • Open Access


    Cross-Layer Hidden Markov Analysis for Intrusion Detection

    K. Venkatachalam1, P. Prabu2, B. Saravana Balaji3, Byeong-Gwon Kang4, Yunyoung Nam4,*, Mohamed Abouhawwash5,6

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3685-3700, 2022, DOI:10.32604/cmc.2022.019502

    Abstract Ad hoc mobile cloud computing networks are affected by various issues, like delay, energy consumption, flexibility, infrastructure, network lifetime, security, stability, data transition, and link accomplishment. Given the issues above, route failure is prevalent in ad hoc mobile cloud computing networks, which increases energy consumption and delay and reduces stability. These issues may affect several interconnected nodes in an ad hoc mobile cloud computing network. To address these weaknesses, which raise many concerns about privacy and security, this study formulated clustering-based storage and search optimization approaches using cross-layer analysis. The proposed approaches were formed by cross-layer analysis based… More >

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