Proceedings of ASEAN-Australian Engineering Congress (AAEC2022) : engineering solutions in the age of digital disruption

Proceedings of ASEAN-Australian Engineering Congress (AAEC2022) : engineering solutions in the age of digital disruption / Chung Siung Choo, Basil T. Wong, Khairul Hafiz Bin Sharkawi, Daniel Kong, editors.

This book presents the proceedings of the ASEAN-Australian Engineering Congress (AAEC2022), held as a virtual event, 1315 July 2022 with the theme Engineering Solutions in the Age of Digital Disruption. The book presents selected papers covering scientific research in the field of Engineering Comput...

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Bibliographic Details
Corporate Author: ASEAN-Australian Engineering Congress Online
Other Authors: Choo, Chung Siung (Editor), Wong, B. T. (Basil T.) (Editor), Sharkawi, Khairul Hafiz Bin (Editor), Kong, Daniel (Editor)
Format: eBook
Language:English
Published: Singapore : Springer, 2023.
Series:Lecture notes in electrical engineering ; v. 1072.
Subjects:
Engineering > Data processing > Congresses.
Industry 4.0 > Congresses.
Engineering > Data processing.
Industry 4.0.
proceedings (reports)
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Description
Summary:This book presents the proceedings of the ASEAN-Australian Engineering Congress (AAEC2022), held as a virtual event, 1315 July 2022 with the theme Engineering Solutions in the Age of Digital Disruption. The book presents selected papers covering scientific research in the field of Engineering Computing, Network, Communication and Cybersecurity, Artificial Intelligence & Machine Learning, Materials Science & Manufacturing, Automation and Sensors, Smart Energy & Cities, Simulation & Optimisation and other Industry 4.0 related Technologies. The book appeals to researchers, academics, scientists, students, engineers and practitioners who are interested in the latest developments and applications related to addressing the Fourth Industrial Revolution (IR4.0).
Physical Description:1 online resource (342 pages) : illustrations (black and white, and color).
Bibliography:References -- Cough Sound Disease Detection with Artificial Intelligence -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Data Analysis of Fly Ash Geopolymer Compressive Strength Using Machine Learning Method -- 1 Introduction -- 2 Methodology -- 2.1 Sample Preparation -- 2.2 Compressive Strength Test -- 2.3 Neural Network -- 3 Result and Discussion -- 3.1 Compressive Strength -- 3.2 Neural Network -- 4 Conclusion -- 5 Recommendations -- References
ISBN:9789819955473
9819955475
Source of Description, Etc. Note:Print version record.

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