449 research outputs found

    Analysing Scientific Collaborations of New Zealand Institutions using Scopus Bibliometric Data

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    Scientific collaborations are among the main enablers of development in small national science systems. Although analysing scientific collaborations is a well-established subject in scientometrics, evaluations of scientific collaborations within a country remain speculative with studies based on a limited number of fields or using data too inadequate to be representative of collaborations at a national level. This study represents a unique view on the collaborative aspect of scientific activities in New Zealand. We perform a quantitative study based on all Scopus publications in all subjects for more than 1500 New Zealand institutions over a period of 6 years to generate an extensive mapping of scientific collaboration at a national level. The comparative results reveal the level of collaboration between New Zealand institutions and business enterprises, government institutions, higher education providers, and private not for profit organisations in 2010-2015. Constructing a collaboration network of institutions, we observe a power-law distribution indicating that a small number of New Zealand institutions account for a large proportion of national collaborations. Network centrality concepts are deployed to identify the most central institutions of the country in terms of collaboration. We also provide comparative results on 15 universities and Crown research institutes based on 27 subject classifications.Comment: 10 pages, 15 figures, accepted author copy with link to research data, Analysing Scientific Collaborations of New Zealand Institutions using Scopus Bibliometric Data. In Proceedings of ACSW 2018: Australasian Computer Science Week 2018, January 29-February 2, 2018, Brisbane, QLD, Australi

    Comparing Computing Platforms for Deep Learning on a Humanoid Robot

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    The goal of this study is to test two different computing platforms with respect to their suitability for running deep networks as part of a humanoid robot software system. One of the platforms is the CPU-centered Intel NUC7i7BNH and the other is a NVIDIA Jetson TX2 system that puts more emphasis on GPU processing. The experiments addressed a number of benchmarking tasks including pedestrian detection using deep neural networks. Some of the results were unexpected but demonstrate that platforms exhibit both advantages and disadvantages when taking computational performance and electrical power requirements of such a system into account.Comment: 12 pages, 5 figure

    Survey on remnant data research: the artefacts recovered and the implications in a cyber security conscious world

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    The prevalence of remnant data in second hand storage media is well documented. Since 2004 there have been ten separate papers released through Edith Cowan University alone. Despite numerous government agencies providing advice on securing personal and corporate information, and news articles highlighting the need for data security, the availability of personal and confidential data on second hand storage devices is continuing, indicating a systemic laissez faire attitude to data security, even in our supposedly cyber security conscious world. The research continues, but there seems to be a lack of correlation of these studies to identify trends or common themes amongst the results. The fact that this type of research continues to be conducted highlights the deficiencies in the methods used to advertise warnings publicised by Government departments and industry experts. Major media organisations seem reluctant to broadcast these warnings, unless there is a bigger story behind the issue. This paper highlights the ongoing issues and provides insight to the factors contributing to this growing trend

    A universal ontology-based approach to data integration

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    One of the main problems in building data integration systems is that of semantic integration. It has been acknowledged that the problem would not exist if all systems were developed using the same global schema, but so far, such global schema has been considered unfeasible in practice. However, in our previous work, we have argued that given the current state-of-the-art, a global schema may be feasible now, and we have put forward a vision of a Universal Ontology (UO) that may be desirable, feasible, and viable. One of the reasons why the UO may be desirable is that it might solve the semantic integration problem. The objective of this paper is to show that indeed the UO could solve, or at least greatly alleviate, the semantic integration problem. We do so by presenting an approach to semantic integration based on the UO that requires much less effort than other approaches.Peer ReviewedPostprint (published version
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