Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (3)
  • Open Access

    ARTICLE

    Machine Learning-Driven Classification for Enhanced Rule Proposal Framework

    B. Gomathi1,*, R. Manimegalai1, Srivatsan Santhanam2, Atreya Biswas3

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1749-1765, 2024, DOI:10.32604/csse.2024.056659 - 22 November 2024

    Abstract In enterprise operations, maintaining manual rules for enterprise processes can be expensive, time-consuming, and dependent on specialized domain knowledge in that enterprise domain. Recently, rule-generation has been automated in enterprises, particularly through Machine Learning, to streamline routine tasks. Typically, these machine models are black boxes where the reasons for the decisions are not always transparent, and the end users need to verify the model proposals as a part of the user acceptance testing to trust it. In such scenarios, rules excel over Machine Learning models as the end-users can verify the rules and have more… More >

  • Open Access

    ARTICLE

    Early Detection of Heartbeat from Multimodal Data Using RPA Learning with KDNN-SAE

    A. K. S. Saranya1,*, T. Jaya2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 545-562, 2023, DOI:10.32604/csse.2023.029975 - 16 August 2022

    Abstract Heartbeat detection stays central to cardiovascular an electrocardiogram (ECG) is used to help with disease diagnosis and management. Existing Convolutional Neural Network (CNN)-based methods suffer from the less generalization problem thus; the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed. In contrast, this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders (KDNN-SAE) that computes the disease before the exact heart rate by combining features from multiple ECG Signals. Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error… More >

  • Open Access

    ARTICLE

    Analyzing and Enabling the Harmonious Coexistence of Heterogeneous Industrial Wireless Networks

    Bilal Khan1, Danish Shehzad1, Numan Shafi1, Ga-Young Kim2,*, Muhammad Umar Aftab1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1671-1690, 2022, DOI:10.32604/cmc.2022.024918 - 18 May 2022

    Abstract Nowadays multiple wireless communication systems operate in industrial environments side by side. In such an environment performance of one wireless network can be degraded by the collocated hostile wireless network having higher transmission power or higher carrier sensing threshold. Unlike the previous research works which considered IEEE 802.15.4 for the Industrial Wireless communication systems (iWCS) this paper examines the coexistence of IEEE 802.11 based iWCS used for delay-stringent communication in process automation and gWLAN (general-purpose WLAN) used for non-real time communication. In this paper, we present a Markov chain-based performance model that described the transmission… More >

Displaying 1-10 on page 1 of 3. Per Page