ORCID Profile
0000-0002-0365-3192
Current Organisation
Ryan Watson Consulting Pty Ltd
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Publisher: MDPI AG
Date: 09-07-2020
DOI: 10.3390/SMARTCITIES3030034
Abstract: Australian governments at all three levels—local (council), state, and federal—are beginning to exploit the massive amounts of data they collect through sensors and recording systems. Their aim is to enable Australian communities to benefit from “smart city” initiatives by providing greater efficiencies in their operations and strategic planning. Increasing numbers of datasets are being made freely available to the public. These so-called big data are amenable to data science analysis techniques including machine learning. While there are many cases of data use at the federal and state level, local councils are not taking full advantage of their data for a variety of reasons. This paper reviews the status of open datasets of Australian local governments and reports progress being made in several student and other projects to develop open data web services using machine learning for smart cities.
Publisher: Elsevier BV
Date: 09-1986
Publisher: MDPI AG
Date: 12-01-2022
DOI: 10.3390/JSAN11010007
Abstract: Big data analytics can be used by smart cities to improve their citizens’ liveability, health, and wellbeing. Social surveys and also social media can be employed to engage with their communities, and these can require sophisticated analysis techniques. This research was focused on carrying out a sentiment analysis from social surveys. Data analysis techniques using RStudio and Python were applied to several open-source datasets, which included the 2018 Social Indicators Survey dataset published by the City of Melbourne (CoM) and the Casey Next short survey 2016 dataset published by the City of Casey (CoC). The qualitative nature of the CoC dataset responses could produce rich insights using sentiment analysis, unlike the quantitative CoM dataset. RStudio analysis created word cloud visualizations and bar charts for sentiment values. These were then used to inform social media analysis via the Twitter application programming interface. The R codes were all integrated within a Shiny application to create a set of user-friendly interactive web apps that generate sentiment analysis both from the historic survey data and more immediately from the Twitter feeds. The web apps were embedded within a website that provides a customisable solution to estimate sentiment for key issues. Global sentiment was also compared between the social media approach and the 2016 survey dataset analysis and showed some correlation, although there are caveats on the use of social media for sentiment analysis. Further refinement of the methodology is required to improve the social media app and to calibrate it against analysis of recent survey data.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2011
Publisher: Elsevier BV
Date: 12-1983
Publisher: Elsevier BV
Date: 11-1981
Publisher: World Scientific Pub Co Pte Lt
Date: 20-11-2011
DOI: 10.1142/S0217984911027546
Abstract: We report the results of our numerical investigation on the temperature dependence of the characteristics of the cylindrical gate-all-around Si nanowire field effect transistor ( Si -NW-FET). Assuming the effect of temperature on the energy band structure of Si just like the effect of strain, we simulate the transistor characteristics at various temperatures (50 K ≤ T ≤ 300 K ). In this investigation, we demonstrate the temperature dependence of the transistor sub-threshold swing and the threshold voltage are both linear functions of the temperature, represented by 61.5 × (T/300) + 63.4 (mV/decade) and 220–140 × (T/300-1) (mV). By calculating the I DS - T characteristics for V DS = 0.4 V and various V GS , we show that the temperature sensitivity of the drain current defined as the slope of the I DS - T plot, for a given V GS , is independent of the temperature and increases with V GS in a quadratic manner [- 150 × (V GS - 0.50) 2 + 8.5 (nA/K)]. Ultimately, the dependence of the transistor delay time on temperature will be presented.
Publisher: IEEE
Date: 05-2012
Publisher: MDPI AG
Date: 14-03-2017
Publisher: ACM
Date: 16-01-2021
Publisher: Elsevier BV
Date: 11-1982
Publisher: Elsevier BV
Date: 10-2020
Publisher: World Scientific Pub Co Pte Lt
Date: 16-07-2012
DOI: 10.1142/S0217984912501369
Abstract: We present a model to understand the effect of temperature on the electrical resistance of in idual semiconducting single wall carbon nanotubes (s-SWCNTs) of various diameters under various electric fields. The temperature dependence of the resistance of s-SWCNTs and metallic SWCNTs (m-SWCNTs) are compared. These results help us to understand the temperature dependence of the resistance of SWCNTs network. We experimentally examine the temperature dependence of the resistance of random networks of SWCNTs, prepared by dispersing CNTs in ethanol and drop-casting the solution on prefabricated metallic electrodes. Examining various s les with different electrode materials and spacings, we find that the dominant resistance in determination of the temperature dependence of resistance of the network is the resistance of in idual tubes, rather than the tube–tube resistance or tube–metal contact resistance. It is also found that the tube–tube resistance depends on the electrode spacing and it is more important for larger electrode spacings. By applying high electric field to burn the all-metallic paths of the SWCNTs network, the temperature dependence of the resistance of s-SWCNTs is also examined. We also investigate the effect of acid treatment of CNTs on the temperature dependence of the resistance of SWCNTs and also multi-wall CNTs (MWCNTs) networks.
Publisher: Elsevier BV
Date: 12-2012
Publisher: American Physical Society (APS)
Date: 10-1988
Publisher: Elsevier BV
Date: 06-2012
Publisher: American Physical Society (APS)
Date: 12-1986
Publisher: American Physical Society (APS)
Date: 06-1983
Publisher: ACM
Date: 31-01-2023
Publisher: The Optical Society
Date: 11-11-2011
DOI: 10.1364/OL.36.004368
Publisher: Inderscience Publishers
Date: 2014
Publisher: Elsevier BV
Date: 02-2011
Publisher: American Physical Society (APS)
Date: 02-1984
Publisher: Informa UK Limited
Date: 19-03-2020
Publisher: American Physical Society (APS)
Date: 07-1984
Publisher: IEEE
Date: 05-2012
Publisher: IGI Global
Date: 04-03-2022
DOI: 10.4018/978-1-7998-9312-7.CH002
Abstract: The internet of things (IoT) is a global ecosystem of networked “things.” It is the subject of much research worldwide, although it still has many challenges to overcome before it can achieve its full potential. Many papers have been written on the IoT and related areas including big data analytics, smart cities, and industrial IoT (IIoT). These challenges have mostly been seen as technical, although the IoT's business and societal challenges are also important. Most authors of research papers discuss the research challenges with which they are most familiar, but a framework which identifies and classifies all the challenges and cross-references the publications describing them in detail, is much needed. In this chapter, the authors extend their earlier IoT classification scheme to include more recent papers, and business and societal challenges as well as technical ones. The nature of the classification scheme and research challenges are described however, the other chapters of this book cover in more detail the in idual challenges and proposed strategies to mitigate them.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Peter Ryan.