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  • Open Access

    ARTICLE

    Multifactorial Disease Detection Using Regressive Multi-Array Deep Neural Classifier

    D. Venugopal1, T. Jayasankar2,*, N. Krishnaraj3, S. Venkatraman4, N. B. Prakash5, G. R. Hemalakshmi5

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 27-38, 2021, DOI:10.32604/iasc.2021.015205

    Abstract Comprehensive evaluation of common complex diseases associated with common gene mutations is currently a hot area of human genome research into causative new developments. A multi-fractal analysis of the genome is performed by placing the entire DNA sequence into smaller fragments and using the chaotic game representation and systematic methods to calculate the general dimensional spectrum of each fragment. This is a time consuming process as it uses floating point to represent large data sets and requires processing time. The proposed Regressive Multi-Array Deep Neural Classifier (RMDNC) system is implemented to reduce the computation time, it is called a polymorphic… More >

  • Open Access

    ARTICLE

    Elderly Fall Detection Based on Improved SSD Algorithm

    Jiancheng Zou1, Na Zhu1,*, Bailin Ge1, Don Hong2

    Journal of New Media, Vol.3, No.1, pp. 1-10, 2021, DOI:10.32604/jnm.2021.017763

    Abstract We propose an improved a single-shot detector (SSD) algorithm to detect falls of the elderly. The VGG16 network part of the SSD network is replaced with the MobilenetV2 network. At the same time, we change the infrastructure of MobilenetV2 network, the three layers that were not downsampled at the end were removed, which can make the model structure simpler and faster to detect. The complete Intersection-over-Union (CIoU) loss function is introduced to get a good regression of the target borders that have different sizes and different proportions. We use Feature Pyramid Network (FPN) for upsampling, it can fuse low-level feature… More >

  • Open Access

    ARTICLE

    A Reliable NLP Scheme for English Text Watermarking Based on Contents Interrelationship

    Fahd N. Al-Wesabi1,2,*, Saleh Alzahrani3, Fuad Alyarimi3, Mohammed Abdul3, Nadhem Nemri3, Mohammed M. Almazah4

    Computer Systems Science and Engineering, Vol.37, No.3, pp. 297-311, 2021, DOI:10.32604/csse.2021.015915

    Abstract In this paper, a combined approach CAZWNLP (a combined approach of zero-watermarking and natural language processing) has been developed for the tampering detection of English text exchanged through the Internet. The third gram of alphanumeric of the Markov model has been used with text-watermarking technologies to improve the performance and accuracy of tampering detection issues which are limited by the existing works reviewed in the literature of this study. The third-grade level of the Markov model has been used in this method as natural language processing technology to analyze an English text and extract the textual characteristics of the given… More >

  • Open Access

    ARTICLE

    A Learning-based Static Malware Detection System with Integrated Feature

    Zhiguo Chen1,*, Xiaorui Zhang1,2, Sungryul Kim3

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 891-908, 2021, DOI:10.32604/iasc.2021.016933

    Abstract The rapid growth of malware poses a significant threat to the security of computer systems. Analysts now need to examine thousands of malware samples daily. It has become a challenging task to determine whether a program is a benign program or malware. Making accurate decisions about the program is crucial for anti-malware products. Precise malware detection techniques have become a popular issue in computer security. Traditional malware detection uses signature-based strategies, which are the most widespread method used in commercial anti-malware software. This method works well against known malware but cannot detect new malware. To overcome the deficiency of the… More >

  • Open Access

    ARTICLE

    Detection of COVID-19 Enhanced by a Deep Extreme Learning Machine

    Aaqib Inam1,*, Zhuli1, Ayesha Sarwar1, Salah-ud-din2, Ayesha Atta3, Iftikhar Naaseer4, Shahan Yamin Siddiqui5,6, Muhammad Adnan Khan7

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 701-712, 2021, DOI:10.32604/iasc.2021.014235

    Abstract The outbreak of coronavirus disease 2019 (COVID-19) has had a tremendous effect on daily life and a great impact on the economy of the world. More than 200 countries have been affected. The diagnosis of coronavirus is a major challenge for medical experts. Early detection is one of the most effective ways to reduce the mortality rate and increase the chance of successful treatment. At this point in time, no antiviral drugs have been approved for use, and clinically approved vaccines have only recently become available in some countries. Hybrid artificial intelligence computer-aided systems for the diagnosis of disease are… More >

  • Open Access

    ARTICLE

    Entropy-Based Watermarking Approach for Sensitive Tamper Detection of Arabic Text

    Fahd N. Al-Wesabi1,2,*

    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 >

  • Open Access

    ARTICLE

    On Network Designs with Coding Error Detection and Correction Application

    Mahmoud Higazy1,2,*, Taher A. Nofal1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3401-3418, 2021, DOI:10.32604/cmc.2021.015790

    Abstract The detection of error and its correction is an important area of mathematics that is vastly constructed in all communication systems. Furthermore, combinatorial design theory has several applications like detecting or correcting errors in communication systems. Network (graph) designs (GDs) are introduced as a generalization of the symmetric balanced incomplete block designs (BIBDs) that are utilized directly in the above mentioned application. The networks (graphs) have been represented by vectors whose entries are the labels of the vertices related to the lengths of edges linked to it. Here, a general method is proposed and applied to construct new networks designs.… 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

    CNN Ensemble Approach to Detect COVID-19 from Computed Tomography Chest Images

    Haikel Alhichri*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3581-3599, 2021, DOI:10.32604/cmc.2021.015399

    Abstract In January 2020, the World Health Organization declared a global health emergency concerning the spread of a new coronavirus disease, which was later named COVID-19. Early and fast diagnosis and isolation of COVID-19 patients have proven to be instrumental in limiting the spread of the disease. Computed tomography (CT) is a promising imaging method for fast diagnosis of COVID-19. In this study, we develop a unique preprocessing step to resize CT chest images to a fixed size (256 × 256 pixels) that preserves the aspect ratio and reduces image loss. Then, we present a deep learning (DL) method to classify… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Hookworm Detection in Wireless Capsule Endoscopic Image Using AdaBoost Classifier

    K. Lakshminarayanan1, N. Muthukumaran1, Y. Harold Robinson2, Vimal Shanmuganathan3, Seifedine Kadry4, Yunyoung Nam5,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3045-3055, 2021, DOI:10.32604/cmc.2021.014370

    Abstract Hookworm is an illness caused by an internal sponger called a roundworm. Inferable from deprived cleanliness in the developing nations, hookworm infection is a primary source of concern for both motherly and baby grimness. The current framework for hookworm detection is composed of hybrid convolutional neural networks; explicitly an edge extraction framework alongside a hookworm classification framework is developed. To consolidate the cylindrical zones obtained from the edge extraction framework and the trait map acquired into the hookworm scientific categorization framework, pooling layers are proposed. The hookworms display different profiles, widths, and bend directions. These challenges make it difficult for… More >

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