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Future Internet, Volume 12, Issue 6

June 2020 - 15 articles

Cover Story: Soft sensors (SSs) are inferential models used in many industrial fields. They allow real-time estimation of hard-to-measure variables as a function of easy-to-measure variables obtained from on-line sensors. SSs are generally built from industries’ historical databases through data-driven approaches. A critical issue in SSs design concerns the selection of input variables, among those available in a candidate dataset, that can reach great numbers in an industrial environment. Such numbers of inputs would make the design computationally demanding and lead to poorly performing models. An input selection procedure is necessary. Most input selection approaches for SS design are addressed and classified in the paper, with their benefits and drawbacks outlined, to guide the designer through this step. View this paper.
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Articles (15)

  • Perspective
  • Open Access
5 Citations
4,998 Views
20 Pages

From close to scratch, the COVID-19 pandemic created the largest volunteer supercomputer on earth. Sadly, processing resources assigned to the corresponding Folding@home project cannot be shared with other volunteer computing projects efficiently. Co...

  • Review
  • Open Access
34 Citations
6,652 Views
24 Pages

Input Selection Methods for Soft Sensor Design: A Survey

  • Francesco Curreri,
  • Giacomo Fiumara and
  • Maria Gabriella Xibilia

Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historic...

  • Article
  • Open Access
17 Citations
4,981 Views
14 Pages

Benefitting from the rapid development of artificial intelligence (AI) and deep learning, the machine translation task based on neural networks has achieved impressive performance in many high-resource language pairs. However, the neural machine tran...

  • Review
  • Open Access
45 Citations
6,714 Views
25 Pages

Simulating Resource Management across the Cloud-to-Thing Continuum: A Survey and Future Directions

  • Malika Bendechache,
  • Sergej Svorobej,
  • Patricia Takako Endo and
  • Theo Lynn

In recent years, there has been significant advancement in resource management mechanisms for cloud computing infrastructure performance in terms of cost, quality of service (QoS) and energy consumption. The emergence of the Internet of Things has le...

  • Article
  • Open Access
123 Citations
19,515 Views
20 Pages

COVID-19 Epidemic as E-Learning Boost? Chronological Development and Effects at an Austrian University against the Background of the Concept of “E-Learning Readiness”

  • Martin Ebner,
  • Sandra Schön,
  • Clarissa Braun,
  • Markus Ebner,
  • Ypatios Grigoriadis,
  • Maria Haas,
  • Philipp Leitner and
  • Behnam Taraghi

The COVID-19 crisis influenced universities worldwide in early 2020. In Austria, all universities were closed in March 2020 as a preventive measure, and meetings with over 100 people were banned and a curfew was imposed. This development also had a m...

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Future Internet - ISSN 1999-5903Creative Common CC BY license