Macquarie University, Sydney Macquarie University ResearchOnline

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Date: 2019
Language: eng
Resource Type: Thesis MRes
Identifier: http://hdl.handle.net/1959.14/1270556
Description: Empirical thesis.
Full Text: Full Text
Authors: Bohan, Elise
Date: 2018
Language: eng
Resource Type: Thesis PhD
Identifier: http://hdl.handle.net/1959.14/1268521
Description: Theoretical thesis.
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Date: 2016
Language: eng
Resource Type: journal article
Identifier: http://hdl.handle.net/1959.14/1074359
Description: Evolution has transformed life through key innovations in information storage and replication, including RNA, DNA, multicellularity, and culture and language. We argue that the carbon-based biosphere ... More
Reviewed: Reviewed
Date: 2013
Language: eng
Resource Type: journal article
Identifier: http://hdl.handle.net/1959.14/278768
Description: Objective: We describe how ehealth communication programs can be improved by using artificial intelligence (AI) to increase immediacy. Methods: We analyzed major deficiencies in ehealth communication ... More
Reviewed: Reviewed
Date: 2013
Language: eng
Resource Type: book
Identifier: http://hdl.handle.net/1959.14/210737
Description: This book constitutes the refereed post-proceedings of the First International Workshop on Cognitive Agents for Virtual Environments, CAVE 2012, held at AAMAS 2012, in Valencia, Spain, in June 2012. T ... More
Date: 2013
Language: eng
Resource Type: journal article
Identifier: http://hdl.handle.net/1959.14/278769
Description: Objective: This paper describes how design science theory and methods and use of artificial intelligence (AI) components can improve the effectiveness of health communication. Methods: We identified k ... More
Reviewed: Reviewed
Authors: Aydin, Ali Orhan
Date: 2011
Language: eng
Resource Type: Thesis PhD
Identifier: http://hdl.handle.net/1959.14/133670
Description: Thesis (PhD)--Macquarie University, Faculty of Science, Dept. of Computing, 2011.
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Date: 2006
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/349256
Description: This work addresses the application of a machine-learning approach to classify ATC trajectory segments from recorded opportunity traffic. It is based on the mode probabilities estimated by an IMM trac ... More
Reviewed: Reviewed
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