Emergent task-specific object semantics through distributed experience networks

Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.

Tracking the Brisbane residential property market : Post GFC

Prior to the GFC, Brisbane and Perth were experiencing the highest increases in median residential house prices, compared to the other major Australian cities, due to strong demand for both owner occupied and investment residential property. In both these cities, a major driver of this demand and subsequent increases in residential property prices was the strong resources sector. With the onset of the GFC in 2008, the resources and construction sectors in Queensland contracted significantly and this had both direct and indirect impacts on the Brisbane residential property market. However, this impact was not consistent across Brisbane residential property sectors. The affect on houses and units differed, as did the impact based on geographic location and suburb value. This paper tracks Brisbane residential property sales listings, sales and returns over the period February 2009 to July 2010 and provides an analysis of the residential market for 24 Brisbane suburbs. These suburbs cover main residential areas of Brisbane and are based on an equal number of low, medium and high socioeconomic areas of Brisbane. This assessment of socio-economic status for the suburbs is based on both median household income and median house price. The analysis will cover both free standing residential property and residential units/townhouses/villas. The results will show how each of these residential property sub markets have performed following the GFC.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Toward automated power line corridor monitoring using advanced aircraft control and multisource feature fusion

The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

Performance control of distributed generation using digital estimation of signal parameters

The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.

Temporal tracking of mineralization and transcriptional developments of shell formation during the early life history of pearl oyster Pinctada maxima

Molluscan larval ontogeny is a highly conserved process comprising three principal developmental stages. A characteristic unique to each of these stages is shell design, termed prodissoconch I, prodissoconch II and dissoconch. These shells vary in morphology, mineralogy and microstructure. The discrete temporal transitions in shell biomineralization between these larval stages are utilized in this study to investigate transcriptional involvement in several distinct biomineralization events. Scanning electron microscopy and X-ray diffraction analysis of P. maxima larvae and juveniles collected throughout post-embryonic ontogenesis, document the mineralogy and microstructure of each shelled stage as well as establishing a timeline for transitions in biomineralization. P. maxima larval samples most representative of these biomineralization distinctions and transitions were analyzed for differential gene expression on the microarray platform PmaxArray 1.0. A number of transcripts are reported as differentially expressed in correlation to the mineralization events of P. maxima larval ontogeny. Some of those isolated are known shell matrix genes while others are novel; these are discussed in relation to potential shell formation roles. This interdisciplinary investigation has linked the shell developments of P. maxima larval ontogeny with corresponding gene expression profiles, furthering the elucidation of shell biomineralization.

Tracking employees' twists and turns : describing a mixed methods approach to assessing change in the psychological contract

The psychological contract is a key analytical device utilised by both academics and practitioners to conceptualise and explore the dynamics of the employment relationship. However, despite the recognised import of the construct, some authors suggest that its empirical investigation has fallen into a 'methodological rut' [Conway & Briner, 2005, p. 89] and is neglecting to assess key tenets of the concept, such as its temporal and dynamic nature. This paper describes the research design of a longitudinal, mixed methods study which draws upon the strengths of both qualitative and quantitative modes of inquiry in order to explore the development of, and changes in, the psychological contract. Underpinned by a critical realist philosophy, the paper seeks to offer a research design suitable for exploring the process of change not only within the psychological contract domain, but also for similar constructs in the human resource management and broader organisational behaviour fields.

Towards automatic object segmentation with sequential multiple views

Object segmentation is one of the fundamental steps for a number of robotic applications such as manipulation, object detection, and obstacle avoidance. This paper proposes a visual method for incorporating colour and depth information from sequential multiview stereo images to segment objects of interest from complex and cluttered environments. Rather than segmenting objects using information from a single frame in the sequence, we incorporate information from neighbouring views to increase the reliability of the information and improve the overall segmentation result. Specifically, dense depth information of a scene is computed using multiple view stereo. Depths from neighbouring views are reprojected into the reference frame to be segmented compensating for imperfect depth computations for individual frames. The multiple depth layers are then combined with color information from the reference frame to create a Markov random field to model the segmentation problem. Finally, graphcut optimisation is employed to infer pixels belonging to the object to be segmented. The segmentation accuracy is evaluated over images from an outdoor video sequence demonstrating the viability for automatic object segmentation for mobile robots using monocular cameras as a primary sensor.

Charting the system : the integrated master schedule as a multi-level and poly-temporal boundary object in complex projects

This paper investigates the use of visual artifacts to represent a complex adaptive system (CAS). The integrated master schedule (IMS) is one of those visuals widely used in complex projects for scheduling, budgeting, and project management. In this paper, we discuss how the IMS outperforms the traditional timelines and acts as a ‘multi-level and poly-temporal boundary object’ that visually represents the CAS. We report the findings of a case study project on the way the IMS mapped interactions, interdependencies, constraints and fractal patterns in a complex project. Finally, we discuss how the IMS was utilised as a complex boundary object by eliciting commitment and development of shared mental models, and facilitating negotiation through the layers of multiple interpretations from stakeholders.

Using strategic movement to calibrate a neural compass : a spiking network for tracking head direction in rats and robots

The head direction (HD) system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular) inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that ‘grounding’ of modeled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology), and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

Tracking the defining moments of crisis process and practice

Crisis holds the potential for profound change in organizations and industries. The past 50 years of crisis management highlight key shifts in crisis practice, creating opportunities for multiple theories and research tracks. Defining crises such as Tylenol, Exxon Valdez, and September 11 terrorist attacks have influenced or challenged the principles of best practice of crisis communication in public relations. This study traces the development of crisis process and practice by identifying shifts in crisis research and models and mapping these against key management theories and practices. The findings define three crisis domains: crisis planning, building and testing predictive models, and mapping and measuring external environmental influences. These crisis domains mirror but lag the evolution of management theory, suggesting challenges for researchers to reshape the research agenda to close the gap and lead the next stage of development in the field of crisis communication for effective organizational outcomes.

An object oriented road asset information model

Preservation and enhancement of transportation infrastructure is critical to continuous economic development in Australia. Of particular importance are the road assets infrastructure, due to their high costs of setting up and their social and economic impact on the national economy. Continuous availability of road assets, however, is contingent upon their effective design, condition monitoring, maintenance, and renovation and upgrading. However, in order to achieve this data exchange, integration, and interoperability is required across municipal boundaries. On the other hand, there are no agreed reference frameworks that consistently describe road infrastructure assets. As a consequence, specifications and technical solutions being chosen to manage road assets do not provide adequate detail and quality of information to support asset lifecycle management processes and decisions taken are based on perception not reality. This paper presents a road asset information model, which works as reference framework to, link other kinds of information with asset information; integrate different data suppliers; and provide a foundation for service driven integrated information framework for community infrastructure and asset management.

Bringing the MIMOSA OSA-EAI into an object-orientated world

Despite being poised as a standard for data exchange for operation and maintenance data, the database heritage of the MIMOSA OSA-EAI is clearly evident from using a relational model at its core. The XML schema (XSD) definitions, which are used for communication between asset management systems, are based on the MIMOSA common relational information schema (CRIS), a relational model, and consequently, many database concepts permeate the communications layer. The adoption of a relational model leads to several deficiencies, and overlooks advances in object-oriented approach for an upcoming version of the specification, and the common conceptual object model (CCOM) sees a transition to fully utilising object-oriented features for the standard. Unified modelling language (UML) is used as a medium for documentation as well as facilitating XSD code generation. This paper details some of the decisions faced in developing the CCOM and provides a glimpse into the future of asset management and data exchange models.

The advancement of religion is still a valid charitable object in 2001

“The Relevance of Religion” is the title of a recent address delivered by The Honourable Chief Justice Murray Gleeson of the High Court of Australia.1 In making the point “about the continuing public importance of religion”, the Chief Justice referenced Lord Devlin’s contention that “no society has yet solved the problem of how to teach morality without religion”....