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  • Open Access

    ARTICLE

    User Interaction Based Recommender System Using Machine Learning

    R. Sabitha1, S. Vaishnavi2,*, S. Karthik1, R. M. Bhavadharini3

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1037-1049, 2022, DOI:10.32604/iasc.2022.018985 - 22 September 2021

    Abstract In the present scenario of electronic commerce (E-Commerce), the in-depth knowledge of user interaction with resources has become a significant research concern that impacts more on analytical evaluations of recommender systems. For staying in aggressive E-Commerce, various products and services regarding distinctive requirements must be provided on time. Moreover, because of the large amount of product information available online, Recommender Systems (RS) are required to analyze the availability of consumers, which improves the decision-making of customers with detailed product knowledge and reduces time consumption. With that note, this paper derives a new model called User… More >

  • Open Access

    ARTICLE

    Symbol Detection Based on Back Tracking Search Algorithm in MIMO-NOMA Systems

    M. Nuri Seyman*

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 795-804, 2022, DOI:10.32604/csse.2022.019734 - 09 September 2021

    Abstract One of the most important methods used to cope with multipath fading effects, which cause the symbol to be received incorrectly in wireless communication systems, is the use of multiple transceiver antenna structures. By combining the multi-input multi-output (MIMO) antenna structure with non-orthogonal multiple access (NOMA), which is a new multiplexing method, the fading effects of the channels are not only reduced but also high data rate transmission is ensured. However, when the maximum likelihood (ML) algorithm that has high performance on coherent detection, is used as a symbol detector in MIMO NOMA systems, the… More >

  • Open Access

    ARTICLE

    Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

    Hanan A. Hosni Mahmoud*, Doaa S. Khafga, Amal H. Alharbi

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 805-821, 2022, DOI:10.32604/csse.2022.019633 - 09 September 2021

    Abstract Limbal Stem Cell Deficiency (LSCD) is an eye disease that can cause corneal opacity and vascularization. In its advanced stage it can lead to a degree of visual impairment. It involves the changing in the semispherical shape of the cornea to a drooping shape to downwards direction. LSCD is hard to be diagnosed at early stages. The color and texture of the cornea surface can provide significant information about the cornea affected by LSCD. Parameters such as shape and texture are very crucial to differentiate normal from LSCD cornea. Although several medical approaches exist, most… More >

  • Open Access

    ARTICLE

    Secure Data Sharing with Confidentiality, Integrity and Access Control in Cloud Environment

    V. Rajkumar1,*, M. Prakash2, V. Vennila3

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 779-793, 2022, DOI:10.32604/csse.2022.019622 - 09 September 2021

    Abstract Cloud storage is an incipient technology in today’s world. Lack of security in cloud environment is one of the primary challenges faced these days. This scenario poses new security issues and it forms the crux of the current work. The current study proposes Secure Interactional Proof System (SIPS) to address this challenge. This methodology has a few key essential components listed herewith to strengthen the security such as authentication, confidentiality, access control, integrity and the group of components such as AVK Scheme (Access List, Verifier and Key Generator). It is challenging for every user to… More >

  • Open Access

    ARTICLE

    Implementation of K-Means Algorithm and Dynamic Routing Protocol in VANET

    Manoj Sindhwani1, Charanjeet Singh1,*, Rajeshwar Singh2

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 455-467, 2022, DOI:10.32604/csse.2022.018498 - 09 September 2021

    Abstract With the growth of Vehicular Ad-hoc Networks, many services delivery is gaining more attention from the intelligent transportation system. However, mobility characteristics of vehicular networks cause frequent disconnection of routes, especially during the delivery of data. In both developed and developing countries, a lot of time is consumed due to traffic congestion. This has significant negative consequences, including driver stress due to increased time demand, decreased productivity for various personalized and commercial vehicles, and increased emissions of hazardous gases especially air polluting gases are impacting public health in highly populated areas. Clustering is one of… More >

  • Open Access

    ARTICLE

    Intelligent Identification and Resolution of Software Requirement Conflicts: Assessment and Evaluation

    Maysoon Aldekhail1, Marwah Almasri2,*

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 469-489, 2022, DOI:10.32604/csse.2022.018269 - 09 September 2021

    Abstract Considerable research has demonstrated how effective requirements engineering is critical for the success of software projects. Requirements engineering has been established and recognized as one of the most important aspects of software engineering as of late. It is noteworthy to mention that requirement consistency is a critical factor in project success, and conflicts in requirements lead to waste of cost, time, and effort. A considerable number of research studies have shown the risks and problems caused by working with requirements that are in conflict with other requirements. These risks include running overtime or over budget,… More >

  • Open Access

    ARTICLE

    Mammogram Learning System for Breast Cancer Diagnosis Using Deep Learning SVM

    G. Jayandhi1,*, J.S. Leena Jasmine2, S. Mary Joans2

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 491-503, 2022, DOI:10.32604/csse.2022.016376 - 09 September 2021

    Abstract The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces… More >

  • Open Access

    ARTICLE

    Secure Rotation Invariant Face Detection System for Authentication

    Amit Verma1, Mohammed Baljon2, Shailendra Mishra2,*, Iqbaldeep Kaur1, Ritika Saini1, Sharad Saxena3, Sanjay Kumar Sharma4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1955-1974, 2022, DOI:10.32604/cmc.2022.020084 - 07 September 2021

    Abstract Biometric applications widely use the face as a component for recognition and automatic detection. Face rotation is a variable component and makes face detection a complex and challenging task with varied angles and rotation. This problem has been investigated, and a novice algorithm, namely RIFDS (Rotation Invariant Face Detection System), has been devised. The objective of the paper is to implement a robust method for face detection taken at various angle. Further to achieve better results than known algorithms for face detection. In RIFDS Polar Harmonic Transforms (PHT) technique is combined with Multi-Block Local Binary… More >

  • Open Access

    ARTICLE

    Data Traffic Reduction with Compressed Sensing in an AIoT System

    Hye-Min Kwon1, Seng-Phil Hong2, Mingoo Kang1, Jeongwook Seo1,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1769-1780, 2022, DOI:10.32604/cmc.2022.020027 - 07 September 2021

    Abstract To provide Artificial Intelligence (AI) services such as object detection, Internet of Things (IoT) sensor devices should be able to send a large amount of data such as images and videos. However, this inevitably causes IoT networks to be severely overloaded. In this paper, therefore, we propose a novel oneM2M-compliant Artificial Intelligence of Things (AIoT) system for reducing overall data traffic and offering object detection. It consists of some IoT sensor devices with random sampling functions controlled by a compressed sensing (CS) rate, an IoT edge gateway with CS recovery and domain transform functions related… More >

  • Open Access

    ARTICLE

    Real-Time Network Intrusion Prevention System Using Incremental Feature Generation

    Yeongje Uhm1, Wooguil Pak2,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1631-1648, 2022, DOI:10.32604/cmc.2022.019667 - 07 September 2021

    Abstract Security measures are urgently required to mitigate the recent rapid increase in network security attacks. Although methods employing machine learning have been researched and developed to detect various network attacks effectively, these are passive approaches that cannot protect the network from attacks, but detect them after the end of the session. Since such passive approaches cannot provide fundamental security solutions, we propose an active approach that can prevent further damage by detecting and blocking attacks in real time before the session ends. The proposed technology uses a two-level classifier structure: the first-stage classifier supports real-time More >

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