Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (6)
  • Open Access


    Towards Cache-Assisted Hierarchical Detection for Real-Time Health Data Monitoring in IoHT

    Muhammad Tahir1,2,*, Mingchu Li1,2, Irfan Khan1,2, Salman A. Al Qahtani3, Rubia Fatima4, Javed Ali Khan5, Muhammad Shahid Anwar6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2529-2544, 2023, DOI:10.32604/cmc.2023.042403

    Abstract Real-time health data monitoring is pivotal for bolstering road services’ safety, intelligence, and efficiency within the Internet of Health Things (IoHT) framework. Yet, delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems. We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this. This strategy is devised to streamline the data retrieval path, subsequently diminishing network strain. Crafting an adept cache processing scheme poses its own set of challenges, especially given the transient nature of monitoring data and the imperative for swift data transmission,… More >

  • Open Access


    Secured Health Data Transmission Using Lagrange Interpolation and Artificial Neural Network

    S. Vidhya1,*, V. Kalaivani2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2673-2692, 2023, DOI:10.32604/csse.2023.027724

    Abstract In recent decades, the cloud computing contributes a prominent role in health care sector as the patient health records are transferred and collected using cloud computing services. The doctors have switched to cloud computing as it provides multiple advantageous measures including wide storage space and easy availability without any limitations. This necessitates the medical field to be redesigned by cloud technology to preserve information about patient’s critical diseases, electrocardiogram (ECG) reports, and payment details. The proposed work utilizes a hybrid cloud pattern to share Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) resources over the private… More >

  • Open Access


    Health Data Availability Protection: Delta-XOR-Relay Data Update in Erasure-Coded Cloud Storage Systems

    Yifei Xiao, Shijie Zhou*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 169-185, 2023, DOI:10.32604/cmes.2022.021795

    Abstract To achieve the high availability of health data in erasure-coded cloud storage systems, the data update performance in erasure coding should be continuously optimized. However, the data update performance is often bottlenecked by the constrained cross-rack bandwidth. Various techniques have been proposed in the literature to improve network bandwidth efficiency, including delta transmission, relay, and batch update. These techniques were largely proposed individually previously, and in this work, we seek to use them jointly. To mitigate the cross-rack update traffic, we propose DXR-DU which builds on four valuable techniques: (i) delta transmission, (ii) XOR-based data More >

  • Open Access


    Health Data Deduplication Using Window Chunking-Signature Encryption in Cloud

    G. Neelamegam*, P. Marikkannu

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1079-1093, 2023, DOI:10.32604/iasc.2023.031283

    Abstract Due to the development of technology in medicine, millions of health-related data such as scanning the images are generated. It is a great challenge to store the data and handle a massive volume of data. Healthcare data is stored in the cloud-fog storage environments. This cloud-Fog based health model allows the users to get health-related data from different sources, and duplicated information is also available in the background. Therefore, it requires an additional storage area, increase in data acquisition time, and insecure data replication in the environment. This paper is proposed to eliminate the de-duplication… More >

  • Open Access


    Cuckoo Optimized Convolution Support Vector Machine for Big Health Data Processing

    Eatedal Alabdulkreem1, Jaber S. Alzahrani2, Majdy M. Eltahir3, Abdullah Mohamed4, Manar Ahmed Hamza5,*, Abdelwahed Motwakel5, Mohamed I. Eldesouki6, Mohammed Rizwanullah5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3039-3055, 2022, DOI:10.32604/cmc.2022.029835

    Abstract Big health data collection and storing for further analysis is a challenging task because this knowledge is big and has many features. Several cloud-based IoT health providers have been described in the literature previously. Furthermore, there are a number of issues related to time consumed and overall network performance when it comes to big data information. In the existing method, less performed optimization algorithms were used for optimizing the data. In the proposed method, the Chaotic Cuckoo Optimization algorithm was used for feature selection, and Convolutional Support Vector Machine (CSVM) was used. The research presents… More >

  • Open Access


    Deep Neural Artificial Intelligence for IoT Based Tele Health Data Analytics

    Nithya Rekha Sivakumar1,*, Ahmed Zohair Ibrahim2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4467-4483, 2022, DOI:10.32604/cmc.2022.019041


    Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances. It makes an effort to get the better of issues of health service delivery involving time factor, space and laborious terrains, validating cost-efficiency and finer ingress in both developed and developing countries. Tele health has been categorized into either real-time electronic communication, or store-and-forward communication. In recent years, a third-class has been perceived as remote healthcare monitoring or tele health, presuming data obtained via Internet of Things (IOT). Although, tele health data analytics and machine learning have been researched

    More >

Displaying 1-10 on page 1 of 6. Per Page