Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two non-parametric transforms, namely, the rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

Fast Friends

Two works were included in the curated exhibition "Fast Friends" at the Nona Gallery, at the Brisbane Institute of Art. This exhibition was the the second of three exhibitions. This project curated by Jill Barker was collectively entitled "Pace" and was supported by an Arts Queensland grant. The premise for the exhibition and for the work creatied for the exhibiton is as follows. For fast friends the pieces will be works that consist of more than one part. In the way that a friendship consists of more than one person. You could say that the location of a friendship lies somewhere between the friends - so in each of the artworks in fast friends, the 'centre' of the work - if it can be said to have a centre - will be in the relationship between the parts.

On the probability density function of the product of Rayleigh distributed random variables

In this paper we investigate the distribution of the product of Rayleigh distributed random variables. Considering the Mellin-Barnes inversion formula and using the saddle point approach we obtain an upper bound for the product distribution. The accuracy of this tail-approximation increases as the number of random variables in the product increase.

Fast scanning electron microscope (FSEM)

High magnification and large depth of field with a temporal resolution of less than 100 microseconds are possible using the present invention which combines a linear electron beam produced by a tungsten filament from an SX-40A Scanning Electron Microscope (SEM), a magnetic deflection coil with lower inductance resulting from reducing the number of turns of the saddle-coil wires, while increasing the diameter of the wires, a fast scintillator, photomultiplier tube, photomultiplier tube base, and signal amplifiers and a high speed data acquisition system which allows for a scan rate of 381 frames per second and 256.times.128 pixel density in the SEM image at a data acquisition rate of 25 MHz. The data acquisition and scan position are fully coordinated. A digitizer and a digital waveform generator which generates the sweep signals to the scan coils run off the same clock to acquire the signal in real-time.

Efficient solution of two-sided nonlinear space-fractional diffusion equations using fast Poisson preconditioners

We develop a fast Poisson preconditioner for the efficient numerical solution of a class of two-sided nonlinear space fractional diffusion equations in one and two dimensions using the method of lines. Using the shifted Gr¨unwald finite difference formulas to approximate the two-sided(i.e. the left and right Riemann-Liouville) fractional derivatives, the resulting semi-discrete nonlinear systems have dense Jacobian matrices owing to the non-local property of fractional derivatives. We employ a modern initial value problem solver utilising backward differentiation formulas and Jacobian-free Newton-Krylov methods to solve these systems. For efficient performance of the Jacobianfree Newton-Krylov method it is essential to apply an effective preconditioner to accelerate the convergence of the linear iterative solver. The key contribution of our work is to generalise the fast Poisson preconditioner, widely used for integer-order diffusion equations, so that it applies to the two-sided space fractional diffusion equation. A number of numerical experiments are presented to demonstrate the effectiveness of the preconditioner and the overall solution strategy.

Fast exact nearest neighbour matching in high dimensions using d-D Sort

Data structures such as k-D trees and hierarchical k-means trees perform very well in approximate k nearest neighbour matching, but are only marginally more effective than linear search when performing exact matching in high-dimensional image descriptor data. This paper presents several improvements to linear search that allows it to outperform existing methods and recommends two approaches to exact matching. The first method reduces the number of operations by evaluating the distance measure in order of significance of the query dimensions and terminating when the partial distance exceeds the search threshold. This method does not require preprocessing and significantly outperforms existing methods. The second method improves query speed further by presorting the data using a data structure called d-D sort. The order information is used as a priority queue to reduce the time taken to find the exact match and to restrict the range of data searched. Construction of the d-D sort structure is very simple to implement, does not require any parameter tuning, and requires significantly less time than the best-performing tree structure, and data can be added to the structure relatively efficiently.

Accuracy and functional variability in elite and developing fast bowlers

Objectives The relationship between performance variability and accuracy in cricket fast bowlers of different skill levels under three different task conditions was investigated. Bowlers of different skill levels were examined to observe if they could adapt movement patterns to maintain performance accuracy on a bowling skills test. Design 8 national, 12 emerging and 12 junior pace bowlers completed an adapted version of the Cricket Australia bowling skills test, in which they performed 30 trials involving short (n = 10), good (n = 10), and full (n = 10) length deliveries. Methods Bowling accuracy was recorded by digitising ball position relative to the centre of a target. Performance measures were mean radial error (accuracy), variable error (consistency), centroid error (bias), bowling score and ball speed. Radial error changes across the duration of the skills test were used to record accuracy adjustment in subsequent deliveries. Results Elite fast bowlers performed better in speed, accuracy, and test scores than developing athletes. Bowlers who were less variable were also more accurate across all delivery lengths. National and emerging bowlers were able to adapt subsequent performance trials within the same bowling session for short length deliveries. Conclusions Accuracy and adaptive variability were key components of elite performance in fast bowling which improved with skill level. In this study, only national elite bowlers showed requisite levels of adaptive variability to bowl a range of lengths to different pitch locations.

Numerical methods of the variable-order Rayleigh-Stokes problem for a heated generalized second grade fluid with fractional derivative

Rayleigh–Stokes problems have in recent years received much attention due to their importance in physics. In this article, we focus on the variable-order Rayleigh–Stokes problem for a heated generalized second grade fluid with fractional derivative. Implicit and explicit numerical methods are developed to solve the problem. The convergence, stability of the numerical methods and solvability of the implicit numerical method are discussed via Fourier analysis. Moreover, a numerical example is given and the results support the effectiveness of the theoretical analysis.

The water catchment : fast forward to the past

The Water Catchment: fast forward to the past comprises two parts: a creative piece and an exegesis. The methodology is Creative Practice as Research; a process of critical reflection, where I observe how researching the exegesis, in my case analysing how the social reality of an era in which an author writes affects their writing of the protagonist's journey, and how this in turn shapes how I write the hero's pathway in the creative piece. The genre in which the protagonist's journey is charted and represented is dystopian young adult fiction; hence my creative piece, The Water Catchment, is a novel manuscript for a dystopian young adult fantasy. It is a speculative novel set in a possible future and poses (and answers) the question: What might happen if water becomes the most powerful commodity on earth? There are two communities, called 'worlds' to create a barrier and difference where physical ones are not in evidence. A battle ensues over unfair conditions and access to water. In the end the protagonist, Caitlyn, takes over leadership heralding a new era of co-operation and water management between the two worlds. The exegesis examines how the hero's pathway, the journey towards knowledge and resolution, is best explored in young adult literature through dystopian narratives. I explore how the dystopian worlds of Ursula Le Guin's first and last books of The Earthsea Quartet are foundational, and lay this examination over an analysis of both the hero's pathway within and the social contexts outside of the novels. Dystopian narratives constitute a liberating space for the adolescent protagonist between the reliance on adults in childhood and the world of adults. In young adult literature such narratives provide fertile ground to explore those aspects informing an adolescent's future.

Fast formulas for computing cryptographic pairings

The most powerful known primitive in public-key cryptography is undoubtedly elliptic curve pairings. Upon their introduction just over ten years ago the computation of pairings was far too slow for them to be considered a practical option. This resulted in a vast amount of research from many mathematicians and computer scientists around the globe aiming to improve this computation speed. From the use of modern results in algebraic and arithmetic geometry to the application of foundational number theory that dates back to the days of Gauss and Euler, cryptographic pairings have since experienced a great deal of improvement. As a result, what was an extremely expensive computation that took several minutes is now a high-speed operation that takes less than a millisecond. This thesis presents a range of optimisations to the state-of-the-art in cryptographic pairing computation. Both through extending prior techniques, and introducing several novel ideas of our own, our work has contributed to recordbreaking pairing implementations.

Mg-based nanocomposites with high capacity and fast kinetics for hydrogen storage

Magnesium and its alloys have shown a great potential in effective hydrogen storage due to their advantages of high volumetric/gravimetric hydrogen storage capacity and low cost. However, the use of these materials in fuel cells for automotive applications at the present time is limited by high hydrogenation temperature and sluggish sorption kinetics. This paper presents the recent results of design and development of magnesium-based nanocomposites demonstrating the catalytic effects of carbon nanotubes and transition metals on hydrogen adsorption in these materials. The results are promising for the application of magnesium materials for hydrogen storage, with significantly reduced absorption temperatures and enhanced ab/desorption kinetics. High level Density Functional Theory calculations support the analysis of the hydrogenation mechanisms by revealing the detailed atomic and molecular interactions that underpin the catalytic roles of incorporated carbon and titanium, providing clear guidance for further design and development of such materials with better hydrogen storage properties.

Acquisition of expertise in cricket fast bowling : perceptions of expert players and coaches

Objectives: Experiential knowledge of elite athletes and coaches was investigated to reveal insights on expertise acquisition in cricket fast bowling. Design: Twenty-one past or present elite cricket fast bowlers and coaches of national or international level were interviewed using an in-depth, open-ended, semi-structured approach. Methods: Participants were asked about specific factors which they believed were markers of fast bowling expertise potential. Of specific interest was the relative importance of each potential component of fast bowling expertise and how components interacted or developed over time. Results: The importance of intrinsic motivation early in development was highlighted, along with physical, psychological and technical attributes. Results supported a multiplicative and interactive complex systems model of talent development in fast bowling, in which component weightings were varied due to individual differences in potential experts. Dropout rates in potential experts were attributed to misconceived current talent identification programmes and coaching practices, early maturation and physical attributes, injuries and lack of key psychological attributes and skills. Conclusions: Data are consistent with a dynamical systems model of expertise acquisition in fast bowling, with numerous trajectories available for talent development. Further work is needed to relate experiential and theoretical knowledge on expertise in other sports.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

Quantitative genetic parameters for body traits at different ages in a cultured stock of giant freshwater prawn (Macrobrachium rosenbergii) selected for fast growth

The aim of the current study was to estimate heritabilities and correlations for body traits at different ages (Weeks 10 and 18 after stocking) in a giant freshwater prawn (Macrobrachium rosenbergii) population selected for fast growth rate in Vietnam. The dataset consisted of 4650 body records (2432 and 2218 records collected at Weeks 10 and 18, respectively) in the full pedigree comprising a total of 18 387 records. Variance and covariance components were estimated using restricted maximum likelihood fitting a multi-trait animal model. Estimates of heritability for body traits (bodyweight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) were moderate and ranged from 0.06 to 0.11 and from 0.11 to 0.22 at Weeks 10 and 18, respectively. Body-trait heritabilities estimated at Week 10 were not significantly lower than at Week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Our results suggested that selection for high growth rate in GFP can be undertaken successfully before full market size has been reached.