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  • Open Access

    ARTICLE

    Machine Learning Based Analysis of Real-Time Geographical of RS Spatio-Temporal Data

    Rami Sameer Ahmad Al Kloub*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5151-5165, 2022, DOI:10.32604/cmc.2022.024309 - 14 January 2022

    Abstract Flood disasters can be reliably monitored using remote sensing photos with great spatiotemporal resolution. However, satellite revisit periods and extreme weather limit the use of high spatial resolution images. As a result, this research provides a method for combining Landsat and MODIS pictures to produce high spatiotemporal imagery for flood disaster monitoring. Using the spatial and temporal adaptive reflectance fusion model (STARFM), the spatial and temporal reflectance unmixing model (STRUM), and three prominent algorithms of flexible spatiotemporal data fusion (FSDAF), Landsat fusion images are created by fusing MODIS and Landsat images. Then, to extract flood… More >

  • Open Access

    ARTICLE

    Wi-Fi Positioning Dataset with Multiusers and Multidevices Considering Spatio-Temporal Variations

    Imran Ashraf, Sadia Din, Soojung Hur, Yongwan Park*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5213-5232, 2022, DOI:10.32604/cmc.2022.018707 - 11 October 2021

    Abstract Precise information on indoor positioning provides a foundation for position-related customer services. Despite the emergence of several indoor positioning technologies such as ultrawideband, infrared, radio frequency identification, Bluetooth beacons, pedestrian dead reckoning, and magnetic field, Wi-Fi is one of the most widely used technologies. Predominantly, Wi-Fi fingerprinting is the most popular method and has been researched over the past two decades. Wi-Fi positioning faces three core problems: device heterogeneity, robustness to signal changes caused by human mobility, and device attitude, i.e., varying orientations. The existing methods do not cover these aspects owing to the unavailability More >

  • Open Access

    ARTICLE

    Case Study: Spark GPU-Enabled Framework to Control COVID-19 Spread Using Cell-Phone Spatio-Temporal Data

    Hussein Shahata Abdallah1, *, Mohamed H. Khafagy1, Fatma A. Omara2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1303-1320, 2020, DOI:10.32604/cmc.2020.011313 - 20 August 2020

    Abstract Nowadays, the world is fighting a dangerous form of Coronavirus that represents an emerging pandemic. Since its early appearance in China Wuhan city, many countries undertook several strict regulations including lockdowns and social distancing measures. Unfortunately, these procedures have badly impacted the world economy. Detecting and isolating positive/probable virus infected cases using a tree tracking mechanism constitutes a backbone for containing and resisting such fast spreading disease. For helping this hard effort, this research presents an innovative case study based on big data processing techniques to build a complete tracking system able to identify the… More >

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