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.

Parallel attentive visual tracking

The research reported here addresses the problem of detecting and tracking independently moving objects from a moving observer in real-time, using corners as object tokens. Corners are detected using the Harris corner detector, and local image-plane constraints are employed to solve the correspondence problem. The approach relaxes the restrictive static-world assumption conventionally made, and is therefore capable of tracking independently moving and deformable objects. Tracking is performed without the use of any 3-dimensional motion model. The technique is novel in that, unlike traditional feature-tracking algorithms where feature detection and tracking is carried out over the entire image-plane, here it is restricted to those areas most likely to contain-meaningful image structure. Two distinct types of instantiation regions are identified, these being the “focus-of-expansion” region and “border” regions of the image-plane. The size and location of these regions are defined from a combination of odometry information and a limited knowledge of the operating scenario. The algorithms developed have been tested on real image sequences taken from typical driving scenarios. Implementation of the algorithm using T800 Transputers has shown that near-linear speedups are achievable, and that real-time operation is possible (half-video rate has been achieved using 30 processing elements).

Shortest path and vehicle trajectory aided map-matching for low frequency GPS data

Map-matching algorithms that utilise road segment connectivity along with other data (i.e.position, speed and heading) in the process of map-matching are normally suitable for high frequency (1 Hz or higher) positioning data from GPS. While applying such map-matching algorithms to low frequency data (such as data from a fleet of private cars, buses or light duty vehicles or smartphones), the performance of these algorithms reduces to in the region of 70% in terms of correct link identification, especially in urban and sub-urban road networks. This level of performance may be insufficient for some real-time Intelligent Transport System (ITS) applications and services such as estimating link travel time and speed from low frequency GPS data. Therefore, this paper develops a new weight-based shortest path and vehicle trajectory aided map-matching (stMM) algorithm that enhances the map-matching of low frequency positioning data on a road map. The well-known A* search algorithm is employed to derive the shortest path between two points while taking into account both link connectivity and turn restrictions at junctions. In the developed stMM algorithm, two additional weights related to the shortest path and vehicle trajectory are considered: one shortest path-based weight is related to the distance along the shortest path and the distance along the vehicle trajectory, while the other is associated with the heading difference of the vehicle trajectory. The developed stMM algorithm is tested using a series of real-world datasets of varying frequencies (i.e. 1 s, 5 s, 30 s, 60 s sampling intervals). A high-accuracy integrated navigation system (a high-grade inertial navigation system and a carrier-phase GPS receiver) is used to measure the accuracy of the developed algorithm. The results suggest that the algorithm identifies 98.9% of the links correctly for every 30 s GPS data. Omitting the information from the shortest path and vehicle trajectory, the accuracy of the algorithm reduces to about 73% in terms of correct link identification. The algorithm can process on average 50 positioning fixes per second making it suitable for real-time ITS applications and services.

Growing food in the city : Design ideations for urban residential gardeners

Urban agriculture refers to the production of food in urban and peri-urban spaces. It can contribute positively to health and food security of a city, while also reducing ‘food miles.’ It takes on many forms, from the large and organised community garden, to the small and discrete backyard or balcony. This study focuses on small-scale food production in the form of residential gardening for home or personal use. We explore opportunities to support people’s engagement in urban agriculture via human-computer interaction design. This research presents the findings and HCI design insights from our study of residential gardeners in Brisbane, Australia. By exploring their understanding of gardening practice with a human-centred design approach, we present six key themes, highlighting opportunities and challenges relating to available time and space; the process of learning and experimentation; and the role of existing online platforms to support gardening practice. Finally we discuss the overarching theme of shared knowledge, and how HCI could improve community engagement and gardening practice.

Coastal development, coral reefs and marine life in Asia: Tourism's double-edged sword

A large proportion of the world's population, including those of Asian countries, live in close proximity to the coastline. Coastlines are being developed at a £aster rate than ever before and there is now a growing body of literature to show that such activities are affecting the quality of coastal ecosystems and its wildlife (see, for example, Jennings, 2004; Siler et al., 2014; Duke eta!., 2007). This in turn is impacting negatively on the fishing and the tourism industries, amongst others. Millions of people depend on these sectors for their livelihoods and, unsustainable development can only make the plight of those who rely on these resources worse. The tourism industry in the coastal regions is particularly at risk since the industry relies heavily on coastal ecosystems to attract visitors. This chapter discusses the strong links that exist between coastal development, tourism, marine ecosystems and its wildlife, drawing attention to two well-known species widely used in tourism, namely whales and sea turtles, and discussing their conservation in relation to tourism. The chapter is divided into six sections. The second section examines why it is important to strike a balance between coastal development and protecting ecosystems. In this section, we discuss the ma.ior identified causes of coastal ecosystem degradation from the published literature, and the third section focuses attention on tourism development in the Asian region, which is one of the major reasons for coastal degradation. A diagrammatic approach is used to illustrate that planning of coastal tourism development which takes into account environmental impacts could result in economic benefits to the areas and regions concerned. The negative impacts on tourism when coastal ecosystems are damaged are discussed in section four. Section five shows the economic benefits resulting from sea turtle and whale watching-based tourism in Australia, and section six examines tourism as a conservation tool. In this section, the differing experiences of sea turtle tourism in Sri Lanka and Australia are discussed based on our published work. The final section concludes.

The future of outsourcing in the Asia-Pacific region: Implications for research and practice—panel report from PACIS 2014

This paper summarizes a panel discussion held at the 18th Pacific Asia Conference on Information Systems (PACIS) in Chengdu, China, 2014, with the same title. The panel discussed the future of outsourcing in the Asia-Pacific region (specifically the importance of outsourcing, new trends, and issues in outsourcing). This paper provides directions for future research that surpasses regional specificity (i.e., the Asia-Pacific region), and contributes to research interests on outsourcing in general.

Paralog-specific kinase inhibition of FGFR4: Adding to the arsenal of anti-FGFR agents

In this issue of Cancer Discovery, Hagel and colleagues report the design and the in vitro and in vivo activity of a novel, irreversible, paralog-specific kinase inhibitor of FGFR4, BLU9931. This compound binds covalently to a cysteine residue in the hinge region of FGFR4 but not in FGFR1-3. BLU9931 induces tumor shrinkage in hepatocellular carcinoma models that express a functioning ligand/receptor complex consisting of FGF19/FGFR4/KLB and adds to a growing list of anti-FGFR4 agents.

MRI reveals individual level deformities in the growing scoliotic spine that clinically are masked by the Cobb angle

Clinically, the Cobb angle method measures the overall scoliotic curve in the coronal plane but does not measure individual vertebra and disc wedging. The contributions of the vertebrae and discs in the growing scoliotic spine were measured using sequential MRI scans to investigate coronal plane deformity progression with growth. Sequential MRI data showed complex patterns of deformity progression. Changes to the wedging of individual vertebrae and discs may occur in patients who have no increase in overall Cobb angle measure; the Cobb method alone may be insufficient to capture the complex mechanisms of deformity progression.

Medical imaging and Biomechanical analysis of scoliosis progression in the growing adolescent spine

Progression of spinal deformity in children was studied with Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) to identify how gravity affects the deformity and to determine the full three-dimensional character of the deformity. The CT study showed that gravity is significant in deformity progression in some patients which has implications for clinical patient management. The world first MRI study showed that the standard clinical measure used to define the extent of the deformity is inadequate and further use of three-dimensional MRI should be considered by spinal surgeons.

Measuring the regional availability of biomass for biofuels and the potential for microalgae

Biomass is an important energy resource for producing bioenergy and growing the global economy whilst minimising greenhouse gas emissions. Many countries, like Australia have a huge amount of biomass with the potential for bioenergy, but non-edible feedstock resources are significantly under-exploited. Hence it is essential to map the availability of these feedstocks to identify the most appropriate bioenergy solution for each region and develop supply chains for biorefineries. Using Australia as a case study,we present the spatial availability and opportunities for second and third generation feedstocks. Considerations included current land use, the presence of existing biomass industries and climatic conditions. Detailed information on the regional availability of biomass was collected from government statistics, technical reports and energy assessments as well as from academic literature. Second generation biofuels have the largest opportunity in New South Wales, Queensland and Victoria (NSW, QLD and VIC) and the regions with the highest potential for microalgae are Western Australia and Northern Territory (WA, NT), based on land use opportunity cost and climate. The approach can be used in other countries with a similar climate. More research is needed to overcome key technical and economic hurdles.

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.

Anti-tumour effects of antibodies targeting the extracellular cysteine-rich region of the receptor tyrosine kinase EphB4

EphB4 is a membrane-bound receptor tyrosine kinase (RTK) commonly over-produced by many epithelial cancers but with low to no expression in most normal adult tissues. EphB4 over-production promotes ligand-independent signaling pathways that increase cancer cell viability and stimulate migration and invasion. Several studies have shown that normal ligand-dependent signaling is tumour suppressive and therefore novel therapeutics which block the tumour promoting ligand-independent signaling and/or stimulate tumour suppressive ligand-dependent signaling will find application in the treatment of cancer. An EphB4-specific polyclonal antibody, targeting a region of 200 amino acids in the extracellular portion of EphB4, showed potent in vitro anti-cancer effects measured by an increase in apoptosis and a decrease in anchorage independent growth. Peptide exclusion was used to identify the epitope targeted by this antibody within the cysteine-rich region of the EphB4 protein, a sequence defined as a potential ligand interacting interface. Addition of antibody to cancer cells resulted in phosphorylation and subsequent degradation of the EphB4 protein, suggesting a mechanism that is ligand mimetic and tumour suppressive. A monoclonal antibody which specifically targets this identified extracellular epitope of EphB4 significantly reduced breast cancer xenograft growth in vivo confirming that EphB4 is a useful target for ligand-mimicking antibody-based anti-cancer therapies.

Growing food in the city: A study across interaction design and urban agriculture

The thesis offers the foundation of a design pattern language for urban gardening, as well as a prototype mobile storytelling platform through which urban gardeners can share gardening experiences. This study examined three urban agriculture communities – a city farm, a permaculture movement, and residential gardeners – in order to better understand some of the challenges in their food growing practices. The city is increasingly being rediscovered by gardeners, food activists, and local governments as an under-utilised opportunity space for land cultivation and local food production, and the findings of this research were analysed with a view to consider interactive technology and design interventions in response.

Growing more sustainable communities

According to the Green Building Council of Australia, some 85 per cent of the Australian population is now concentrated in cities, and the nation’s population is expected to rise by 60 per cent by 2050. Clearly, the coming decade will see a greater emphasis not only on environmental impacts, but also the social impacts of our expanding urban areas.

A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.