Land Use & Public Transport Accessibility Index (LUPTAI) tool : the development and pilot application of LUPTAI for the Gold Coast

LUPTAI is a decision-aiding tool to enable local and state governments to optimise land use and transport integration. In contrast to mobility between land uses (typically via road), accessibility represents opportunity and choice to reach common land use destinations by public transport and/or walking. LUPTAI uses a GIS-based methodology to quantify and map accessibility to common land use destinations by walking and/or public transport. The tool can be applied to small or large study areas. It can be applied to the current situation in a study area or to future scenarios (such as scenarios involving changes to public transport services, public transport corridors or stations, population density or land use). The tool has been piloted on the Gold Coast and the results are encouraging. This paper outlines the GIS-based methodology and the findings related to this pilot study. The paper demonstrates benefits and possible application of LUPTAI to other urbanised local government areas in Queensland. It also discusses how this accessibility indexing approach could be developed into a decision-support tool to assist local and state government agencies in a range of transport and land-use planning activities.

Performing composition : developing a computer assisted composition system through live coding performance

This thesis maps the author's journey from a music composition practice to a composition and performance practice. The work involves the development of a software library for the purpose of encapsulating compositional ideas in software, and realising these ideas in performance through a live coding computer music practice. The thesis examines what artistic practice emerges through live coding and software development, and does this permit a blurring between the activities of music composition and performance. The role that software design plays in affecting musical outcomes is considered to gain an insight into how software development contributes to artistic development. The relationship between music composition and performance is also examined to identify the means by which engaging in live coding and software development can bring these activities together. The thesis, situated within the discourse of practice led research, documents a journey which uses the experience of software development and performance as a means to guide the direction of the research. The journey serves as an experiment for the author in engaging an hitherto unfamiliar musical practice, and as a roadmap for others seeking to modify or broaden their artistic practice.

QUT speaker identity verification system for EVALITA 2009

This document outlines the system submitted by the Speech and Audio Research Laboratory at the Queensland University of Technology (QUT) for the Speaker Identity Verication: Application task of EVALITA 2009. This submission consisted of a score-level fusion of three component systems, a joint-factor GMM system and two SVM systems using GLDS and GMM supervector kernels. Development and evaluation results are presented, demonstrating the effectiveness of this fused system approach.

Full scale fire tests of a new light gauge steel floor-ceiling system

Cold-formed steel members can be assembled in various combinations to provide cost-efficient and safe light gauge floor systems for buildings. Such Light gauge Steel Framing (LSF) systems are widely accepted in industrial and commercial building construction. An example application is in floor-ceiling systems. Light gauge steel floor-ceiling systems must be designed to serve as fire compartment boundaries and provide adequate fire resistance. Fire-rated floor-ceiling assemblies formed with new materials and construction methodologies have been increasingly used in buildings. However, limited research has been undertaken in the past and hence a thorough understanding of their fire resistance behaviour is not available. Recently a new composite floor-ceiling system has been developed to provide higher fire rating under standard fire conditions. But its increased fire rating could not be determined using the currently available design methods. Therefore a research project was carried out to investigate its structural and fire resistance behaviour under standard fire conditions. In this research project full scale experimental tests of the new LSF floor system based on a composite ceiling unit were undertaken using a gas furnace at the Queensland University of Technology. Both the conventional and the new steel floor-ceiling systems were tested under structural and fire loads. Full scale fire tests provided a good understanding of the fire behaviour of the LSF floor-ceiling systems and confirmed the superior performance of the new composite system. This paper presents the details of this research into the structural and fire behaviour of light gauge steel floor systems protected by the new composite panel, and the results.

State of the arts and innovation : before and after the review of the national innovation system

This article examines the relationship between the arts and national innovation policy in Australia, pivoting around the Venturous Australia report released in September 2008 as part of the Review of the National Innovation System (RNIS). This came at a time of optimism that the arts sector would be included in Australia’s federal innovation policy. However, despite the report’s broad vision for innovation and specific commentary on the arts, the more ambitious hopes of arts sector advocates remained unfulfilled. This article examines the entwining discourses of creativity and innovation which emerged globally and in Australia prior to the RNIS, before analysing Venturous Australia in terms of the arts and the ongoing science-and-technology bias to innovation policy. It ends by considering why sector-led policy research and lobbying has to date proved unsuccessful and then suggests what public policy development is now needed.

Airborne vision-based collision-detection system

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of vision sensors (as opposed to radar and TCAS). This paper describes the development and evaluation of a real-time vision-based collision detection system suitable for fixed-wing aerial robotics. Using two fixed-wing UAVs to recreate various collision-course scenarios, we were able to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. This type of image data is extremely scarce and was invaluable in evaluating the detection performance of two candidate target detection approaches. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We overcame the challenge of achieving real-time computational speeds by exploiting the parallel processing architectures of graphics processing units found on commercially-off-the-shelf graphics devices. Our chosen GPU device suitable for integration onto UAV platforms can be expected to handle real-time processing of 1024 by 768 pixel image frames at a rate of approximately 30Hz. Flight trials using manned Cessna aircraft where all processing is performed onboard will be conducted in the near future, followed by further experiments with fully autonomous UAV platforms.

Mapping a suburb with a single camera using a biologically inspired SLAM system

This paper describes a biologically inspired approach to vision-only simultaneous localization and mapping (SLAM) on ground-based platforms. The core SLAM system, dubbed RatSLAM, is based on computational models of the rodent hippocampus, and is coupled with a lightweight vision system that provides odometry and appearance information. RatSLAM builds a map in an online manner, driving loop closure and relocalization through sequences of familiar visual scenes. Visual ambiguity is managed by maintaining multiple competing vehicle pose estimates, while cumulative errors in odometry are corrected after loop closure by a map correction algorithm. We demonstrate the mapping performance of the system on a 66 km car journey through a complex suburban road network. Using only a web camera operating at 10 Hz, RatSLAM generates a coherent map of the entire environment at real-time speed, correctly closing more than 51 loops of up to 5 km in length.

Persistent navigation and mapping using a biologically inspired SLAM system

The challenge of persistent navigation and mapping is to develop an autonomous robot system that can simultaneously localize, map and navigate over the lifetime of the robot with little or no human intervention. Most solutions to the simultaneous localization and mapping (SLAM) problem aim to produce highly accurate maps of areas that are assumed to be static. In contrast, solutions for persistent navigation and mapping must produce reliable goal-directed navigation outcomes in an environment that is assumed to be in constant flux. We investigate the persistent navigation and mapping problem in the context of an autonomous robot that performs mock deliveries in a working office environment over a two-week period. The solution was based on the biologically inspired visual SLAM system, RatSLAM. RatSLAM performed SLAM continuously while interacting with global and local navigation systems, and a task selection module that selected between exploration, delivery, and recharging modes. The robot performed 1,143 delivery tasks to 11 different locations with only one delivery failure (from which it recovered), traveled a total distance of more than 40 km over 37 hours of active operation, and recharged autonomously a total of 23 times.

Helicopter automation using a low-cost sensing system

This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.

Helicopter automation using a low-cost sensing system

This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.

A global vision system for a robot soccer team

This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system achieves a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.

Effect of representation size and visual ambiguity on RatSLAM system performance

RatSLAM is a vision-based SLAM system based on extended models of the rodent hippocampus. RatSLAM creates environment representations that can be processed by the experience mapping algorithm to produce maps suitable for goal recall. The experience mapping algorithm also allows RatSLAM to map environments many times larger than could be achieved with a one to one correspondence between the map and environment, by reusing the RatSLAM maps to represent multiple sections of the environment. This paper describes experiments investigating the effects of the environment-representation size ratio and visual ambiguity on mapping and goal navigation performance. The experiments demonstrate that system performance is weakly dependent on either parameter in isolation, but strongly dependent on their joint values.

Featureless vehicle-based visual SLAM with a consumer camera

The Simultaneous Localisation And Mapping (SLAM) problem is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision-only approaches. We present an alternative approach to the leading existing techniques, which extracts approximate rotational and translation velocity information from a vehicle-mounted consumer camera, without tracking landmarks. When coupled with an existing SLAM system, the vision module is able to map a 45 metre long indoor loop and a 1.6 km long outdoor road loop, without any parameter or system adjustment between tests. The work serves as a promising pilot study into ground-based vision-only SLAM, with minimal geometric interpretation of the environment.

The implementation of a novel, bio-inspired, robotic security system

The implementation of a robotic security solution generally requires one algorithm to route the robot around the environment and another algorithm to perform anomaly detection. Solutions to the routing problem require the robot to have a good estimate of its own pose. We present a novel security system that uses metrics generated by the localisation algorithm to perform adaptive anomaly detection. The localisation algorithm is a vision-based SLAM solution called RatSLAM, based on mechanisms within the hippocampus. The anomaly detection algorithm is based on the mechanisms used by the immune system to identify threats to the body. The system is explored using data gathered within an unmodified office environment. It is shown that the algorithm successfully reacts to the presence of people and objects in areas where they are not usually present and is tolerised against the presence of people in environments that are usually dynamic.

Red clover (Trifolium pratense) isoflavones and serum homocysteine in premenopausal women : a pilot study

Background: There is limited information on the effect of isoflavones on homocysteine concentrations, a risk factor for a number of chronic diseases. Methods: Twenty-three premenopausal women participated in a double-blind, randomized, parallel study for four menstrual cycles. Subjects consumed either placebo or purified red clover (Trifolium pratense) isoflavone (86mg/day) tablets. Blood samples were collected weekly during cycles 1, 3, and 4 for determination of serum folate and total homocysteine concentrations. Dietary intake was monitored monthly. Results: Concentrations of folate and homocysteine in serum did not change significantly in either group, and there were no significant differences observed between the follicular and luteal phases of the menstrual cycle. The participants' dietary records indicated that nutrient intake was constant, and compliance was confirmed by analysis of urinary isoflavone concentrations and tablet counts in returned containers. Conclusions: These results suggest that in the absence of any dietary modification, supplementation with purified isoflavones that are predominantly methoxylated has no effect on serum homocysteine or folate in premenopausal women.