Toward making inroads in reducing the disparity of lung health in Australian Indigenous and New Zealand Maori children

Globally, Indigenous populations, which include Aboriginal and Torres Strait islanders in Australia and Māori people in New Zealand (NZ), have poorer health than their non-Indigenous counterparts. Indigenous peoples worldwide face substantial challenges in poverty, education, employment, housing and disconnection from ancestral lands. While addressing social determinants of health is a priority, solving clinical issues is equally important. Indeed, ignoring the latter until social issues improve risks further disparity as this may take generations. A systematic overview of interventions addressing social determinants of health found a striking lack of reliable evaluations.Where evidence was available, health improvement associated with interventions was modest or uncertain. 10 Thus advances in healthcare remain essential and these require the best evidence available in 11 preventing and managing common illnesses, including respiratory illnesses.

On secure outsourcing of cryptographic computations to cloud

For the past few years, research works on the topic of secure outsourcing of cryptographic computations has drawn significant attention from academics in security and cryptology disciplines as well as information security practitioners. One main reason for this interest is their application for resource constrained devices such as RFID tags. While there has been significant progress in this domain since Hohenberger and Lysyanskaya have provided formal security notions for secure computation delegation, there are some interesting challenges that need to be solved that can be useful towards a wider deployment of cryptographic protocols that enable secure outsourcing of cryptographic computations. This position paper brings out these challenging problems with RFID technology as the use case together with our ideas, where applicable, that can provide a direction towards solving the problems.

Finite volume methods for simulating anomalous transport

In this thesis a new approach for solving a certain class of anomalous diffusion equations was developed. The theory and algorithms arising from this work will pave the way for more efficient and more accurate solutions of these equations, with applications to science, health and industry. The method of finite volumes was applied to discretise the spatial derivatives, and this was shown to outperform existing methods in several key respects. The stability and convergence of the new method were rigorously established.

Design thinking frameworks as transformative cross-disciplinary pedagogy

Final report for the Australian Government Office for Learning and Teaching. "This seed project ‘Design thinking frameworks as transformative cross-disciplinary pedagogy’ aimed to examine the way design thinking strategies are used across disciplines to scaffold the development of student attributes in the domain of problem solving and creativity in order to enhance the nation’s capacity for innovation. Generic graduate attributes associated with innovation, creativity and problem solving are considered to be amongst the most important of all targeted attributes (Bradley Review of Higher Education, 2009). The project also aimed to gather data on how academics across disciplines conceptualised design thinking methodologies and strategies. Insights into how design thinking strategies could be embedded at the subject level to improve student outcomes were of particular interest in this regard. A related aim was the investigation of how design thinking strategies could be used by academics when designing new and innovative subjects and courses." Case Study 3: QUT Community Engaged Learning Lab Design Thinking/Design Led Innovation Workshop by Natalie Wright Context "The author, from the discipline area of Interior Design in the QUT School of Design, Faculty of Creative Industries, is a contributing academic and tutor for The Community Engaged Learning Lab, which was initiated at Queensland University of Technology in 2012. The Lab facilitates university-wide service-learning experiences and engages students, academics, and key community organisations in interdisciplinary action research projects to support student learning and to explore complex and ongoing problems nominated by the community partners. In Week 3, Semester One 2013, with the assistance of co-lead Dr Cara Wrigley, Senior Lecturer in Design led Innovation, a Masters of Architecture research student and nine participating industry-embedded Masters of Research (Design led Innovation) facilitators, a Design Thinking/Design led Innovation workshop was conducted for the Community Engaged Learning Lab students, and action research outcomes published at 2013 Tsinghua International Design Management Symposium, December 2013 in Shenzhen, China (Morehen, Wright, & Wrigley, 2013)."

Antisocial personality disorder and therapeutic justice court programs

It has become commonplace for courts to supervise an offender as part of the sentencing process. Many of them have Anti Social Personality Disorder (ASPD). The focus of this article is how the work of specialist and/or problem solving courts can be informed by the insights of the psychology profession into the best practice in the treatment and management of people with ASPD. It is a legitimate purpose of legal work to consider and improve the well-being of the participants in the legal process. Programs designed specifically to deal with those with ASPD could be incorporated into existing Drug Courts, or implemented separately by courts to aid with reforming offenders with ASPD and in managing the re-entry of offenders into the community as part of their sentence. For the success of this initiative on the part of the court, ASPD will need to be specifically diagnosed and treated. Close co-operation between courts and psychologists is required to improve the effectiveness of court programs to treat people with ASPD and to evaluate their success.

Coverage algorithms for an under-actuated car-like vehicle in an uncertain environment

A coverage algorithm is an algorithm that deploys a strategy as to how to cover all points in terms of a given area using some set of sensors. In the past decades a lot of research has gone into development of coverage algorithms. Initially, the focus was coverage of structured and semi-structured indoor areas, but with time and development of better sensors and introduction of GPS, the focus has turned to outdoor coverage. Due to the unstructured nature of an outdoor environment, covering an outdoor area with all its obstacles and simultaneously performing reliable localization is a difficult task. In this paper, two path planning algorithms suitable for solving outdoor coverage tasks are introduced. The algorithms take into account the kinematic constraints of an under-actuated car-like vehicle, minimize trajectory curvatures, and dynamically avoid detected obstacles in the vicinity, all in real-time. We demonstrate the performance of the coverage algorithm in the field by achieving 95% coverage using an autonomous tractor mower without the aid of any absolute localization system or constraints on the physical boundaries of the area.

Playing Monopoly(TM) with 1st year property economics students

Game playing contributes to the acquisition of required skills and competencies whilst supporting collaboration, communication and problem solving. This project introduced the board game Monopoly CityTM to tie theoretical class room learning with collaborative, play based problem solving.

Locally weighted learning methods for non-rigid robot control

This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.

Designing a digital experience for young children with developmental disabilities

This paper reports on the development of a playful digital experience, Anim-action, designed for young children with developmental disabilities. This experience was built using the Stomp platform, a technology designed specifically to meet the needs of people with intellectual disability through facilitating whole body interaction. We provide detail on how knowledge gained from key stakeholders informed the design of the application and describe the design guidelines used in the development process. A study involving 13 young children with developmental disabilities was conducted to evaluate the extent to which Anim-action facilitates cognitive, social and physical activity. Results demonstrated that Anim-action effectively supports cognitive and physical activity. In particular, it promoted autonomy and encouraged problem solving and motor planning. Conversely, there were limitations in the system’s ability to support social interaction, in particular, cooperation. Results have been analyzed to determine how design guidelines might be refined to address these limitations.

Learning through modelling in the primary years

Many nations are highlighting the need for a renaissance in the mathematical sciences as essential to the well-being of all citizens (e.g., Australian Academy of Science, 2006; 2010; The National Academies, 2009). Indeed, the first recommendation of The National Academies’ Rising Above the Storm (2007) was to vastly improve K–12 science and mathematics education. The subsequent report, Rising Above the Gathering Storm Two Years Later (2009), highlighted again the need to target mathematics and science from the earliest years of schooling: “It takes years or decades to build the capability to have a society that depends on science and technology . . . You need to generate the scientists and engineers, starting in elementary and middle school” (p. 9). Such pleas reflect the rapidly changing nature of problem solving and reasoning needed in today’s world, beyond the classroom. As The National Academies (2009) reported, “Today the problems are more complex than they were in the 1950s, and more global. They’ll require a new educated workforce, one that is more open, collaborative, and cross-disciplinary” (p. 19). The implications for the problem solving experiences we implement in schools are far-reaching. In this chapter, I consider problem solving and modelling in the primary school, beginning with the need to rethink the experiences we provide in the early years. I argue for a greater awareness of the learning potential of young children and the need to provide stimulating learning environments. I then focus on data modelling as a powerful means of advancing children’s statistical reasoning abilities, which they increasingly need as they navigate their data-drenched world.

A semi-alternating direction method for a 2-D fractional FitzHugh–Nagumo monodomain model on an approximate irregular domain

A FitzHugh-Nagumo monodomain model has been used to describe the propagation of the electrical potential in heterogeneous cardiac tissue. In this paper, we consider a two-dimensional fractional FitzHugh-Nagumo monodomain model on an irregular domain. The model consists of a coupled Riesz space fractional nonlinear reaction-diffusion model and an ordinary differential equation, describing the ionic fluxes as a function of the membrane potential. Secondly, we use a decoupling technique and focus on solving the Riesz space fractional nonlinear reaction-diffusion model. A novel spatially second-order accurate semi-implicit alternating direction method (SIADM) for this model on an approximate irregular domain is proposed. Thirdly, stability and convergence of the SIADM are proved. Finally, some numerical examples are given to support our theoretical analysis and these numerical techniques are employed to simulate a two-dimensional fractional Fitzhugh-Nagumo model on both an approximate circular and an approximate irregular domain.

High order unconditionally stable difference schemes for the Riesz space-fractional telegraph equation

In this paper, a class of unconditionally stable difference schemes based on the Pad´e approximation is presented for the Riesz space-fractional telegraph equation. Firstly, we introduce a new variable to transform the original dfferential equation to an equivalent differential equation system. Then, we apply a second order fractional central difference scheme to discretise the Riesz space-fractional operator. Finally, we use (1, 1), (2, 2) and (3, 3) Pad´e approximations to give a fully discrete difference scheme for the resulting linear system of ordinary differential equations. Matrix analysis is used to show the unconditional stability of the proposed algorithms. Two examples with known exact solutions are chosen to assess the proposed difference schemes. Numerical results demonstrate that these schemes provide accurate and efficient methods for solving a space-fractional hyperbolic equation.

A framework for identification of similarities between multiple algorithms

This thesis in software engineering presents a novel automated framework to identify similar operations utilized by multiple algorithms for solving related computing problems. It provides a new effective solution to perform multi-application based algorithm analysis, employing fundamentally light-weight static analysis techniques compared to the state-of-art approaches. Significant performance improvements are achieved across the objective algorithms through enhancing the efficiency of the identified similar operations, targeting discrete application domains.

Decision boundary setting and classifier combination for text classification

This thesis presents a promising boundary setting method for solving challenging issues in text classification to produce an effective text classifier. A classifier must identify boundary between classes optimally. However, after the features are selected, the boundary is still unclear with regard to mixed positive and negative documents. A classifier combination method to boost effectiveness of the classification model is also presented. The experiments carried out in the study demonstrate that the proposed classifier is promising.

Template-based circuit understanding

When verifying or reverse-engineering digital circuits, one often wants to identify and understand small components in a larger system. A possible approach is to show that the sub-circuit under investigation is functionally equivalent to a reference implementation. In many cases, this task is difficult as one may not have full information about the mapping between input and output of the two circuits, or because the equivalence depends on settings of control inputs. We propose a template-based approach that automates this process. It extracts a functional description for a low-level combinational circuit by showing it to be equivalent to a reference implementation, while synthesizing an appropriate mapping of input and output signals and setting of control signals. The method relies on solving an exists/forall problem using an SMT solver, and on a pruning technique based on signature computation.