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Open AccessMeeting Report

Report of the 2017 IEEE Cyber Science and Technology Congress

1
Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH 44115, USA
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Faculty of Computer and Information Science, Hosei University, 2 Chome-17-1 Fujimi, Chiyoda, Tokyo 102-8160, Japan
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Department of Electrical and Computer Engineering, The University of Auckland, Auckland 1010, New Zealand
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Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA
*
Author to whom correspondence should be addressed.
Appl. Sci. 2017, 7(12), 1299; https://doi.org/10.3390/app7121299
Received: 4 December 2017 / Revised: 12 December 2017 / Accepted: 12 December 2017 / Published: 14 December 2017
(This article belongs to the Special Issue Cyber Science 2017)
The modern digitized world has led to the emergence of a new paradigm on global information networks and infrastructures known as Cyberspace and the studies of Cybernetics, which bring seamless integration of physical, social and mental spaces. Cyberspace is becoming an integral part of our daily life from learning and entertainment to business and cultural activities. As expected, this whole concept of Cybernetics brings new challenges that need to be tackled. The 2017 IEEE Cyber Science and Technology Congress (CyberSciTech 2017) provided a forum for researchers to report their research findings and exchange ideas. The congress took place in Orlando, Florida, USA during 6–10 November 2017. Not counting poster papers, the congress accepted over fifty papers that are divided into nine sessions. In this report, we provide an overview of the research contributions of the papers in CyberSciTech 2017. View Full-Text
Keywords: Cybernetics; Cyberspace; Cyber Science; smart environment; smart healthcare; internet of things; machine learning; knowledge discovery; network security Cybernetics; Cyberspace; Cyber Science; smart environment; smart healthcare; internet of things; machine learning; knowledge discovery; network security
MDPI and ACS Style

Zhao, W.; Ma, J.; Wang, K.I.-K.; Wang, J. Report of the 2017 IEEE Cyber Science and Technology Congress. Appl. Sci. 2017, 7, 1299.

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