ORCID Profile
0000-0001-6278-4793
Current Organisation
RMIT University
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Software Engineering | Simulation And Modelling | Artificial Intelligence and Image Processing | Information Storage, Retrieval And Management | Neural Networks, Genetic Alogrithms And Fuzzy Logic | Computer Software | Information Systems | Art History | Image Processing | Central Nervous System | Information Systems Organisation | Neurosciences | Art Theory and Criticism | Historical Studies not elsewhere classified | Pattern Recognition | Database Management | Visual Cultures
Information processing services | Technological and organisational innovation | Application tools and system utilities | Application packages | Understanding Australia's Past | Nervous system and disorders | The Creative Arts (incl. Graphics and Craft) | Studies in human society | Integrated (ecosystem) assessment and management | Biological sciences | Scientific instrumentation | Computer software and services not elsewhere classified | Property and business services | Preventive medicine | Heritage not elsewhere classified | Other |
Publisher: IGI Global
Date: 2010
DOI: 10.4018/978-1-61692-834-6.CH040
Abstract: Green ICT Practices fall in two different extremes of either only recommendations to reduce the resource usage such as electricity, or high level strategic management techniques such as Green Balanced Scorecard. The one extreme is very micro level operational approach and the other extreme is just paper strategies without a roadmap for total sustainability. This chapter proposes the enterprise architecture framework and mathematical model providing dynamic model for total sustainability. A brief description of currently popular Green ICT Metrics in practice is presented, together with a discussion of architectural frameworks providing three different architecture layers and a roadmap to achieve desirable “total sustainability indicator (TSI™) - a measurement framework based on mathematical models and game theory.
Publisher: Springer International Publishing
Date: 2016
Publisher: IEEE
Date: 12-2015
Publisher: Springer Berlin Heidelberg
Date: 1992
Publisher: IEEE
Date: 11-2018
Publisher: IEEE
Date: 10-2006
DOI: 10.1109/EDOC.2006.10
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2019
Publisher: Elsevier BV
Date: 06-2003
Publisher: IEEE
Date: 09-2015
Publisher: Open Publishing Association
Date: 02-04-2014
DOI: 10.4204/EPTCS.147.1
Publisher: IEEE Comput. Soc. Press
Date: 1995
Publisher: IEEE
Date: 09-2009
Publisher: ACM
Date: 28-09-2015
Publisher: Springer International Publishing
Date: 2016
Publisher: Elsevier BV
Date: 07-2017
Publisher: IEEE
Date: 08-2007
Publisher: IEEE
Date: 2005
DOI: 10.1109/EDOC.2005.31
Publisher: IGI Global
Date: 2010
DOI: 10.4018/978-1-61692-834-6.CH011
Abstract: Increasing resource consumption by business organizations is impacting the environment and resulting in changes to climatic patterns. The use of Information Technology (IT) and related systems are further contributing to sustainability issues and challenges within business. Hence it becomes imperative for enterprises to formulate their IT Strategies with green approaches in mind so as to reduce the environmental impact of their IT usage. This chapter discusses the issues and challenges in formulating such strategies with particular emphasis on architecture based approaches to green initiatives. A six step methodology for Green IT strategies for business is also recommended.
Publisher: Springer International Publishing
Date: 2015
Publisher: Elsevier BV
Date: 2017
Publisher: IEEE Comput. Soc
Date: 2001
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: MDPI AG
Date: 08-06-2018
DOI: 10.20944/PREPRINTS201806.0138.V1
Abstract: Trends such as Industrial Internet of Things (IIoT) and Industry 4.0 have increased the need to use powerfull network technologies in industrial automation. The growing communication in industrial automation is harnessing the productivity and efficiency of manufacturing and process automation with minimum human intervention. Due to the ongoing evolution of industrial networks from Fieldbus technologies to Ethernet, the new opportunity has emerged to integrate the Software Defined Networking (SDN) technique. In this paper, we provide a brief overview of SDN in the domain of industrial automation. We propose a network architecture called Software Defined Industrial Automation Network (SDIAN), with the objective of improving network scalability and efficiency. To match the specific considerations and requirements of having a deterministic system in an industrial network, we propose two solutions for flow creation: Pro-active Flow Installation Scheme (PFIS) and Hybrid Flow-Installation Scheme (HFIS). We analytically quantify the proposed solutions in alleviating the overhead incurred from the flow setup cost. The analytical model is verified through monte carlo simulations. We also evaluate the SDIAN architecture and analyze the network performance of the modified topology using an emulator called Mininet. We further list and motivate SDIAN features and in particular report on an experimental food processing plant demonstration featuring Raspberry PIs (RPIs) instead of traditional Programmable Logic Controllers (PLCs). Our demonstration exemplifies the characteristics of SDIAN.
Publisher: IEEE
Date: 2005
Publisher: ACM
Date: 11-09-2017
Publisher: IGI Global
Date: 2016
Abstract: A method preserving cyber-physical systems to operate safely in a joint physical space is presented. It comprises the model-based development of the control software and simulators for the continuous physical environment as well as proving the models for spatial and real-time properties. The corresponding toolchain is based on the model-based engineering tool Reactive Blocks and the spatial model checker BeSpaceD. The real-time constraints to be kept by the controller are proven using the model checker UPPAAL.
Publisher: IEEE
Date: 09-2015
Publisher: IEEE
Date: 11-2017
Publisher: ACM
Date: 07-09-2015
Publisher: IEEE
Date: 2009
DOI: 10.1109/SEAA.2009.59
Publisher: The Company of Biologists
Date: 07-2007
DOI: 10.1242/JEB.004853
Abstract: By directional training, young domestic chickens have been shown to use a magnetic compass the same method has now been used to analyse the functional characteristics and the physical principles underlying the chickens' magnetic compass. Tests in magnetic fields with different intensities revealed a functional window around the intensity of the local geomagnetic field, with this window extending further towards lower than higher intensities. Testing chickens under monochromatic 465 nm blue and 645 nm red light suggested a wavelength dependence, with orientation possible under blue but not under red light. Exposing chickens to an oscillating field of 1.566 MHz led to disorientation, identifying an underlying radical pair mechanism. Local anesthesia of the upper beak, where iron-rich structures have been described as potential magnetoreceptors, did not affect the performance, suggesting that these receptors are not involved in compass orientation. These findings show obvious parallels to the magnetic compass described for European robins,indicating that chickens and small passerines use the same type of magnetic compass mechanism. This suggests that the avian magnetic compass may have evolved in the common ancestor of all present-day birds to facilitate orientation within the home range.
Publisher: ACM
Date: 07-09-2015
Publisher: IEEE
Date: 2007
Publisher: IEEE
Date: 2005
DOI: 10.1109/QSIC.2005.64
Publisher: IEEE
Date: 07-2017
Publisher: IEEE
Date: 05-2019
Publisher: MDPI AG
Date: 06-08-2018
DOI: 10.3390/JSAN7030033
Abstract: Trends such as the Industrial Internet of Things and Industry 4.0 have increased the need to use new and innovative network technologies in industrial automation. The growth of industrial automation communications is an outcome of the shift to harness the productivity and efficiency of manufacturing and process automation with a minimum of human intervention. Due to the ongoing evolution of industrial networks from Fieldbus technologies to Ethernet, a new opportunity has emerged to harness the benefits of Software Defined Networking (SDN). In this paper, we provide a brief overview of SDN in the industrial automation domain and propose a network architecture called the Software Defined Industrial Automation Network (SDIAN), with the objective of improving network scalability and efficiency. To match the specific considerations and requirements of having a deterministic system in an industrial network, we propose two solutions for flow creation: the Pro-active Flow Installation Scheme and the Hybrid Flow Installation Scheme. We analytically quantify the proposed solutions that alleviate the overhead incurred from the flow setup. The analytical model is verified using Monte Carlo simulations. We also evaluate the SDIAN architecture and analyze the network performance of the modified topology using the Mininet emulator. We further list and motivate SDIAN features and report on an experimental food processing plant demonstration featuring Raspberry Pi as a software-defined controller instead of traditional proprietary Programmable Logic Controllers. Our demonstration exemplifies the characteristics of SDIAN.
Publisher: IEEE
Date: 04-2007
DOI: 10.1109/ASWEC.2007.6
Publisher: Elsevier BV
Date: 2016
Publisher: ACM
Date: 20-06-2011
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2019
Publisher: IEEE
Date: 09-2014
Publisher: Elsevier BV
Date: 03-2003
Publisher: IEEE
Date: 08-2010
Publisher: IEEE
Date: 07-2015
Publisher: IEEE
Date: 06-2006
Publisher: Springer International Publishing
Date: 2016
Publisher: IEEE Comput. Soc
Date: 2000
Publisher: IEEE
Date: 2003
Publisher: Elsevier BV
Date: 04-1991
Publisher: Springer International Publishing
Date: 2021
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Elsevier BV
Date: 2015
Publisher: IEEE
Date: 12-2016
Publisher: IGI Global
Date: 2015
DOI: 10.4018/978-1-4666-8122-4.CH011
Abstract: One of the main challenges for large-scale computer clouds dealing with massive real-time data is in coping with the rate at which unprocessed data is being accumulated. Transforming big data into valuable information requires a fundamental re-think of the way in which future data management models will need to be developed on the Internet. Unlike the existing relational schemes, pattern-matching approaches can analyze data in similar ways to which our brain links information. Such interactions when implemented in voluminous data clouds can assist in finding overarching relations in complex and highly distributed data sets. In this chapter, a different perspective of data recognition is considered. Rather than looking at conventional approaches, such as statistical computations and deterministic learning schemes, this chapter focuses on distributed processing approach for scalable data recognition and processing.
Publisher: IEEE Comput. Soc
Date: 1998
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1989
DOI: 10.1109/52.16907
Publisher: IEEE
Date: 2005
Publisher: IEEE Comput. Soc
Date: 1999
Publisher: ACM
Date: 17-06-2013
Publisher: IEEE
Date: 2005
Publisher: Elsevier BV
Date: 03-2003
Publisher: IEEE Comput. Soc
Date: 2000
Publisher: ACM
Date: 28-09-2015
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE Comput. Soc. Press
Date: 1996
Publisher: Springer Berlin Heidelberg
Date: 1999
Publisher: IEEE
Date: 25-08-2015
Publisher: World Scientific Pub Co Pte Lt
Date: 12-2006
DOI: 10.1142/S0218843006001517
Abstract: Understanding nonfunctional aspects of system behavior is an essential component of practical software development and maintenance. Many nonfunctional system properties, such as reliability and availability, involve time and probabilities. In this paper, we present a framework for runtime verification and prediction of timed and probabilistic nonfunctional properties of component-based architectures, built using the Meta-Object Facility and the Distributed Management Task Force's Common Information Model (CIM) standard. We describe a Microsoft .NET-based implementation of our framework. We define a language for describing timed probabilistic behavior based on Probabilistic Computational Tree Logic (PCTL). We provide a formal semantics for this language in terms of observed application execution traces. The semantics is interesting in that it permits checking of required timing behavior both over the overall average of traces and also over local "trends" in traces. The latter aspect of the semantics is achieved by incorporating exponential smoothing prediction techniques into the truth function for statements of our language. The semantics is generic over the aspects of an application that are represented by states and state transitions. This enables the language to be used to describe a wide range of nonfunctional properties for runtime verification and prediction purposes. We explain how statements of our language are used to define precise contracts for system monitoring, through relating the semantics to an extended CIM monitoring infrastructure.
Publisher: Springer International Publishing
Date: 2018
Publisher: ACM
Date: 14-05-2016
Publisher: IEEE
Date: 05-2015
DOI: 10.1109/MISE.2015.8
Publisher: IEEE
Date: 12-2015
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2017
Publisher: Springer International Publishing
Date: 2016
Publisher: IEEE
Date: 2009
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 2003
Start Date: 05-2007
End Date: 12-2010
Amount: $480,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 11-2007
End Date: 12-2008
Amount: $160,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 11-2005
End Date: 12-2007
Amount: $100,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 10-2004
End Date: 06-2007
Amount: $239,776.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2003
End Date: 06-2009
Amount: $5,208,295.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2012
End Date: 12-2013
Amount: $240,000.00
Funder: Australian Research Council
View Funded Activity