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Big Data and Cognitive Computing, Volume 3, Issue 4

2019 December - 4 articles

Cover Story: In science and engineering, using edge-embedded software, it is necessary to demonstrate the validity of results. The aim of this study is to guarantee the validity of the sampled-time filter and time domain as fundamental elements of autonomous edge software. This requires an update on the law of a sampled-time filter to be invoked once per every control cycle. It is very simple; however, it is not trivial with regard to reliability. The proposed domain specific language implemented by popular programming language modern C++ shows that it is possible to validate edge software using only the language itself without any auxiliary toolchains. View this paper
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Articles (4)

  • Article
  • Open Access
15 Citations
6,594 Views
14 Pages

Text classification is a process of classifying textual contents to a set of predefined classes and categories. As enormous numbers of documents and contextual contents are introduced every day on the Internet, it becomes essential to use text classi...

  • Article
  • Open Access
5,709 Views
18 Pages

In science and engineering using edge-embedded software, it is necessary to demonstrate the validity of results; therefore, the software responsible for operating an edge system is required to guarantee its own validity. The aim of this study is to g...

  • Article
  • Open Access
23 Citations
8,943 Views
12 Pages

Agent-based modelling is a successful technique in many different fields of science. As a bottom-up method, it is able to simulate complex behaviour based on simple rules and show results at both micro and macro scales. However, developing agent-base...

  • Article
  • Open Access
41 Citations
10,028 Views
20 Pages

Big Data and Energy Poverty Alleviation

  • Hossein Hassani,
  • Mohammad Reza Yeganegi,
  • Christina Beneki,
  • Stephan Unger and
  • Mohammad Moradghaffari

The focus of this paper is to bring to light the vital issue of energy poverty alleviation and how big data could improve the data collection quality and mechanism. It also explains the vicious circle of low productivity, health risk, environmental p...

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Big Data Cogn. Comput. - ISSN 2504-2289