A multi-hypothesis topological SLAM approach for loop closing on edge-ordered graphs

We present a method for topological SLAM that specifically targets loop closing for edge-ordered graphs. Instead of using a heuristic approach to accept or reject loop closing, we propose a probabilistically grounded multi-hypothesis technique that relies on the incremental construction of a map/state hypothesis tree. Loop closing is introduced automatically within the tree expansion, and likely hypotheses are chosen based on their posterior probability after a sequence of sensor measurements. Careful pruning of the hypothesis tree keeps the growing number of hypotheses under control and a recursive formulation reduces storage and computational costs. Experiments are used to validate the approach.

Efficient goal directed navigation using RatSLAM

RatSLAM is a system for vision based Simultaneous Localization and Mapping (SLAM) that has been shown to be capable of building stable representations of real world environments. In this paper we describe a method for using RatSLAM representations as the basis for navigation to designated goal locations. The method uses a new component, goal memory, to learn the temporal gradient between places. Paths are recalled or inferred from the goal memory by following the temporal gradient from the robot’s current position to the goal location. Experimental results have been gathered in a combined office and laboratory environment using a Pioneer robot. The experiments show that the robot can perform vision based SLAM on-line and in real time, and then use those representations immediately to navigate directly to designated goal locations.

Shadowlands (Directed by Caroline Heim)

The controversial love affair of CS Lewis, Oxford scholar and writer of the Narnia Chronicles, is set in a constellation of music, sculpture and mime. CS Lewis’s intriguing relationship with poet Joy Davidman moves, inspires and confronts us with the big questions. Beauty contrasts with the ephemeral land of the shadows. Crossbow’s adaption of William Nicholson’s soulful and witty play explores the joy and the grief of “experience: that most brutal of teachers.” Showcasing the abilities of Brisbane and Sydney actors, the company that brought you The Miracle Worker and Anne of the Thousand Days, will quicken your senses and stir your heart with Shadowlands. All performances have a tactile tour of the stage 20 minutes before the start time of the show. Special signed performance for hearing impaired patrons Thur 5 Aug 2pm

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Self-directed student work groups using blended learning

This paper provides a description of an innovative teaching approach designed to facilitate student work groups using a blended learning approach that incorporates both traditional face-to-face teaching methods and an online student work group facility. The teaching approach is designed to accommodate a large introductory human resource management subject positioned within an undergraduate business degree.

Parallel ABM for electricity distribution grids : a case study

This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

Bacterial kinetics-controlled shape-directed biosynthesis of silver nanoplates using Morganella psychrotolerans

We show for the first time that by controlling the growth kinetics of Morganella psychrotolerans, a silver-resistant psychrophilic bacterium, the shape anisotropy of silver nanoparticles can be achieved. This is particularly important considering that there has been no report that demonstrates a control over shape of Ag nanoparticles by controlling the growth kinetics of bacteria during biological synthesis. Additionally, we have for the first time performed electrochemistry experiments on bacterial cells after exposing them to Ag(+) ions, which provide significant new insights about mechanistic aspects of Ag reduction by bacteria. The possibility to achieve nanoparticle shape control by using a "green" biosynthesis approach is expected to open up new exciting avenues for eco-friendly, large-scale, and economically viable shape-controlled synthesis of nanomaterials.

Hairpin RNAs derived from RNA polymerase II and polymerase III promoter-directed transgenes are processed differently in plants

RNA polymerase III (Pol III) as well as Pol II (35S) promoters are able to drive hairpin RNA (hpRNA) expression and induce target gene silencing in plants. siRNAs of 21 nt are the predominant species in a 35S Pol II line, whereas 24- and/or 22-nucleotide (nt) siRNAs are produced by a Pol III line. The 35S line accumulated the loop of the hpRNA, in contrast to full-length hpRNA in the Pol III line. These suggest that Pol II and Pol III-transcribed hpRNAs are processed by different pathways. One Pol III transgene produced only 24-nt siRNAs but silenced the target gene efficiently, indicating that the 24-nt siRNAs can direct mRNA degradation; specific cleavage was confirmed by 59 rapid amplification of cDNA ends (RACE). Both Pol II- and Pol III-directed hpRNA transgenes induced cytosine methylation in the target DNA. The extent of methylation is not correlated with the level of 21-nt siRNAs, suggesting that they are not effective inducers of DNA methylation. The promoter of a U6 transgene was significantly methylated, whereas the promoter of the endogenous U6 gene was almost free of cytosine methylation, suggesting that endogenous sequences are more resistant to de novo DNA methylation than are transgene constructs. Published by Cold Spring Harbor Laboratory Press. Copyright © 2008 RNA Society.

Expression of Caenorhabditis elegans RNA-directed RNA polymerase in transgenic Drosophila melanogaster does not affect morphological development

Drosophila melanogaster, along with all insects and the vertebrates, lacks an RdRp gene. We created transgenic strains of Drosophila melanogaster in which the rrf-1 or ego-1 RdRp genes from C. elegans were placed under the control of the yeast GAL4 upstream activation sequence. Activation of the gene was performed by crossing these lines to flies carrying the GAL4 transgene under the control of various Drosophila enhancers. RT-PCR confirmed the successful expression of each RdRp gene. The resulting phenotypes indicated that introduction of the RdRp genes had no effect on D. melanogaster morphological development. © 2010 Springer Science+Business Media B.V.

The nature and correlates of young women's peer-directed protective behavioral strategies

Objective Recently, a number of studies have identified self-employed Protective Behavioral Strategies (PBS) as effective in decreasing the level of alcohol-related harm among young people. However, much of the published research has ignored important gender differences, such as women's increased tendency to rely on PBS that are social in nature. To further the understanding of women's PBS, the current study sought to investigate the nature and correlates of the strategies young women employ to keep their friends safe when drinking (i.e., peer-directed PBS). Method A scale measuring peer-directed PBS was developed and administered in conjunction with existing measures of alcohol consumption, personal PBS, and peer attachment. Participants consisted of 422 women aged 18–30 years, recruited among psychology students and the general public. Results Exploratory factor analysis revealed two clusters of peer-directed PBS; those that were aimed at reducing intoxication among one's friends and those that were designed to minimize alcohol-related harms. Further analysis found a positive relationship between women's tendency to implement personal and peer-directed PBS and that risky drinkers were less likely to engage in personal or peer-directed PBS (either type). Conclusion Findings indicate that personal and peer-directed PBS are related behaviors that are less frequently adopted by risky drinkers.