A large-scale computing infrastructure for design education

Most departmental computing infrastructure reflects the state of networking technology and available funds at the time of construction, which converge in a preconceived notion of homogeneity of network architecture and usage patterns. The DMAN (Digital Media Access Network) project, a large-scale server and network foundation for the Hong Kong Polytechnic University's School of Design was created as a platform that would support a highly complex academic environment while giving maximum freedom to students, faculty and researchers through simplicity and ease of use. As a centralized multi-user computation backbone, DMAN faces an extremely hetrogeneous user and application profile, exceeding implementation and maintenance challenges of typical enterprise, and even most academic server set-ups. This paper sumarizes the specification, implementation and application of the system while describing its significance for design education in a computational context.

Final report : enabling team collaboration with pervasive and mobile computing

This is the final report of research project 2002-057-C: Enabling Team Collaboration with Pervasive and Mobile Computing. The research project was carried out by the Australian Cooperative Research Centre for Construction Innovation and has two streams that consider the use of pervasive computing technologies in two different contexts. The first context was the on-site deployment of mobile computing devices, where as the second context was the use and development of intelligent rooms based on sensed environments and new human-computer interfaces (HCI) for collaboration in the design office. The two streams present a model of team collaboration that relies on continues communication to people and information to reduce information leakage. This report consists of five sections: (1) Introduction; (2) Research Project Background; (3) Project Implementation; (4) Case Studies and Outcomes; and (5) Conclusion and Recommendation. Introduction in Section 1 presents a brief description of the research project including general research objectives and structure. Section 2 introduces the background of the research and detailed information regarding project participants, objectives and significance, and also research methodology. Review of all research activities such as literature review and case studies are summarised in Project Implementation in Section 3. Following this, in Section 4 the report then focuses on analysing the case studies and presents their outcomes. Conclusion and recommendation of the research project are summarised in Section 5. Other information to support the content of the report such as research project schedule is provided in Appendices. The purpose of the final project report is to provide industry partners with detailed information on the project activities and methodology such as the implementation of pervasive computing technologies in the real contexts. The report summarises the outcomes of the case studies and provides necessary recommendation to industry partners of using new technologies to support better project collaboration.

Urban informatics

The increasing ubiquity of digital technology, internet ser-vices and social media in our everyday lives allows for a seamless transitioning between the visible and the invisible infrastructure of cities: road systems, building complexes, information and communication technology, and people networks create a buzzing environment that is alive and exciting. Driven by curiosity, initiative and interdiscipli-nary exchange, the Urban Informatics Research Lab at Queensland University of Technology (QUT), Brisbane, Australia, is an emerging cluster of people interested in research and development at the intersection of people, place and technology with a focus on cities, locative media and mobile technology. This paper seeks to define, for the first time, what we mean by ‘urban informatics’ and outline its significance as a field of study today. It describes the relevant background and trends in each of the areas of peo-ple, place and technology, and highlights the relevance of urban informatics to the concerns and evolving challenges of CSCW. We then position our work in academia juxta-posed with related research concentrations and labels, fol-lowed by a discussion of disciplinary influences. The paper concludes with an exposé of the three current research themes of the lab around augmented urban spaces, urban narratives, and environmental sustainability in order to illustrate specific cases and methods, and to draw out distinctions that our affiliation with the Creative Industries Faculty affords.

Urban informatics, ubiquitous computing and social media for healthy cities

The increasing ubiquity of digital technology, internet services and location-aware applications in our everyday lives allows for a seamless transitioning between the visible and the invisible infrastructure of cities: road systems, building complexes, information and communication technology, and people networks create a buzzing environment that is alive and exciting. Driven by curiosity, initiative and interdisciplinary exchange, the Urban Informatics Research Lab at Queensland University of Technology (QUT), Brisbane, Australia, is an emerging cluster of people interested in research and development at the intersection of people, place and technology with a focus on cities, locative media and mobile technology. This paper introduces urban informatics as a transdisciplinary practice across people, place and technology that can aid local governments, urban designers and planners in creating responsive and inclusive urban spaces and nurturing healthy cities. Three challenges are being discussed. First, people, and the challenge of creativity explores the opportunities and challenges of urban informatics that can lead to the design and development of new tools, methods and applications fostering participation, the democratisation of knowledge, and new creative practices. Second, technology, and the challenge of innovation examines how urban informatics can be applied to support user-led innovation with a view to promote entrepreneurial ideas and creative industries. Third, place, and the challenge of engagement discusses the potential to establish places within cities that are dedicated to place-based applications of urban informatics with a view to deliver community and civic engagement strategies.

ICT driven pedagogies and its impact on learning outcomes in high school mathematics

ICT (Information and Communication Technology) creates numerous opportunities for teachers to re-think their pedagogies. In subjects like mathematics which draws upon abstract concepts, ICT creates such an opportunity. Instead of a mimetic pedagogical approach, suitably designed activities with ICT can enable learners to engage more proactively with their learning. In this quasi-experimental designed study, ICT was used in teaching mathematics to a group of first year high school students (N=25) in Australia. The control group was taught predominantly through traditional pedagogies (N=22). Most of the variables that had previously impacted on the design of such studies were suitably controlled in this yearlong investigation. Quantitative and qualitative results showed that students who were taught by ICT driven pedagogies benefitted from the experience. Pre and post-test means showed that there was a difference between the treatment and control groups. Of greater significance was that the students (in the treatment group) believed that the technology enabled them to engage more with their learning.

User-driven quality of experience modelling for mobile video optimisation

The increasing demand for mobile video has attracted much attention from both industry and researchers. To satisfy users and to facilitate the usage of mobile video, providing optimal quality to the users is necessary. As a result, quality of experience (QoE) becomes an important focus in measuring the overall quality perceived by the end-users, from the aspects of both objective system performance and subjective experience. However, due to the complexity of user experience and diversity of resources (such as videos, networks and mobile devices), it is still challenging to develop QoE models for mobile video that can represent how user-perceived value varies with changing conditions. Previous QoE modelling research has two main limitations: aspects influencing QoE are insufficiently considered; and acceptability as the user value is seldom studied. Focusing on the QoE modelling issues, two aims are defined in this thesis: (i) investigating the key influencing factors of mobile video QoE; and (ii) establishing QoE prediction models based on the relationships between user acceptability and the influencing factors, in order to help provide optimal mobile video quality. To achieve the first goal, a comprehensive user study was conducted. It investigated the main impacts on user acceptance: video encoding parameters such as quantization parameter, spatial resolution, frame rate, and encoding bitrate; video content type; mobile device display resolution; and user profiles including gender, preference for video content, and prior viewing experience. Results from both quantitative and qualitative analysis revealed the significance of these factors, as well as how and why they influenced user acceptance of mobile video quality. Based on the results of the user study, statistical techniques were used to generate a set of QoE models that predict the subjective acceptability of mobile video quality by using a group of the measurable influencing factors, including encoding parameters and bitrate, content type, and mobile device display resolution. Applying the proposed QoE models into a mobile video delivery system, optimal decisions can be made for determining proper video coding parameters and for delivering most suitable quality to users. This would lead to consistent user experience on different mobile video content and efficient resource allocation. The findings in this research enhance the understanding of user experience in the field of mobile video, which will benefit mobile video design and research. This thesis presents a way of modelling QoE by emphasising user acceptability of mobile video quality, which provides a strong connection between technical parameters and user-desired quality. Managing QoE based on acceptability promises the potential for adapting to the resource limitations and achieving an optimal QoE in the provision of mobile video content.

A data mining driven risk profiling method for road asset management

Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.

A conceptualization of complexity in IS-driven organizational transformations

Organizational transformations reliant on successful ICT system developments (continue to) fail to deliver projected benefits even when contemporary governance models are applied rigorously. Modifications to traditional program, project and systems development management methods have produced little material improvement to successful transformation as they are unable to routinely address the complexity and uncertainty of dynamic alignment of IS investments and innovation. Complexity theory provides insight into why this phenomenon occurs and is used to develop a conceptualization of complexity in IS-driven organizational transformations. This research-in-progress aims to identify complexity formulations relevant to organizational transformation. Political/power based influences, interrelated business rules, socio-technical innovation, impacts on stakeholders and emergent behaviors are commonly considered as characterizing complexity while the proposed conceptualization accommodates these as connectivity, irreducibility, entropy and/or information gain in hierarchically approximation and scaling, number of states in a finite automata and/or dimension of attractor, and information and/or variety.

Performance-driven live migration of multiple virtual machines in datacenters

Live migration of multiple Virtual Machines (VMs) has become an indispensible management activity in datacenters for application performance, load balancing, server consolidation. While state-of-the-art live VM migration strategies focus on the improvement of the migration performance of a single VM, little attention has been given to the case of multiple VMs migration. Moreover, existing works on live VM migration ignore the inter-VM dependencies, and underlying network topology and its bandwidth. Different sequences of migration and different allocations of bandwidth result in different total migration times and total migration downtimes. This paper concentrates on developing a multiple VMs migration scheduling algorithm such that the performance of migration is maximized. We evaluate our proposed algorithm through simulation. The simulation results show that our proposed algorithm can migrate multiple VMs on any datacenter with minimum total migration time and total migration downtime.

eHealth-as-a-Service (eHaaS) : a data-driven decision making approach in Australian context

A commitment in 2010 by the Australian Federal Government to spend $466.7 million dollars on the implementation of personally controlled electronic health records (PCEHR) heralded a shift to a more effective and safer patient centric eHealth system. However, deployment of the PCEHR has met with much criticism, emphasised by poor adoption rates over the first 12 months of operation. An indifferent response by the public and healthcare providers largely sceptical of its utility and safety speaks to the complex sociotechnical drivers and obstacles inherent in the embedding of large (national) scale eHealth projects. With government efforts to inflate consumer and practitioner engagement numbers giving rise to further consumer disillusionment, broader utilitarian opportunities available with the PCEHR are at risk. This paper discusses the implications of establishing the PCEHR as the cornerstone of a holistic eHealth strategy for the aggregation of longitudinal patient information. A viewpoint is offered that the real value in patient data lies not just in the collection of data but in the integration of this information into clinical processes within the framework of a commoditised data-driven approach. Consideration is given to the eHealth-as-a-Service (eHaaS) construct as a disruptive next step for co-ordinated individualised healthcare in the Australian context.

Instance-driven TBox revision in DL-Lite

The development and maintenance of large and complex ontologies are often time-consuming and error-prone. Thus, automated ontology learning and revision have attracted intensive research interest. In data-centric applications where ontologies are designed or automatically learnt from the data, when new data instances are added that contradict to the ontology, it is often desirable to incrementally revise the ontology according to the added data. This problem can be intuitively formulated as the problem of revising a TBox by an ABox. In this paper we introduce a model-theoretic approach to such an ontology revision problem by using a novel alternative semantic characterisation of DL-Lite ontologies. We show some desired properties for our ontology revision. We have also developed an algorithm for reasoning with the ontology revision without computing the revision result. The algorithm is efficient as its computational complexity is in coNP in the worst case and in PTIME when the size of the new data is bounded.

High-performance computing for data analytics

One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.

GPU accelerated algorithms for computing matrix function vector products with applications to exponential integrators and fractional diffusion

The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.