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.

Autonomous aerial navigation and tracking of marine animals

In this paper, we describe the development of an independent and on-board visual servoing system which allows a computationally impoverished aerial vehicle to autonomously identify and track a moving surface target. Our image segmentation and target identification algorithms were developed with the specific task of monitoring whales at sea but could be adapted for other targets. Observing whales is important for many marine biology tasks and is currently performed manually from the shore or from boats. We also present hardware experiments which demonstrate the capabilities of our algorithms for object identification and tracking that enable a flying vehicle to track a moving target.

Individuals in a mass market environment: Australian bequest donors seek better communication from charities

Swelling social need and competing calls on government funds have heightened the philanthropic dollar’s value. Yet, Australia is not regarded as having a robust giving culture: while 86% of adults give, a mere 16% plan their giving with those who do donating four times as much as spontaneous givers (Giving Australia, 2005). Traditionally, the prime planned giving example is a charitable bequest, a revenue stream not prevalent here (Baker, 2007). In fact, Baker’s Victorian probate data shows under 5% of estates provide a charitable bequest and just over 1% of estate assets is bequeathed. The UK, in contrast, sources 30% and the US 10% of charitable income through bequests (NCVO, 2004; Sargeant, Wymer and Hilton,2006). Australian charities could boost bequest giving. Understanding the donor market, which has or may remember them in their will is critical. This paper reports donor perceptions of Australian charities’ bequest communication/ marketing. The data forms part of a wider study of Australian donors’ bequest attitudes and behaviour. Charities spend heavily on bequest promotion, from advertising to personal selling to public relations and promotion. Infrastructure funds are scarce so guidance on what works for donors is important. Guy and Patton (1988) made their classic call for a nonprofit marketing perspective and identify the need for charities to better understand the motivations and behaviour of their supporters. In similar vein, this study aims to improve the way nonprofits and givers interact; and ultimately, enhance the giving experience and thus multiply planned giving participation. Academically, it offers insights to Australian bequest motivations and attitudes not studied empirically before.

FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Their children's first educators : parents' views about child sexual abuse prevention education

In this descriptive focus group study, we investigated parents’ views about child sexual abuse prevention education at home and in schools. Focus groups were conducted with a sample of 30 Australian adults who identified as the parent or caregiver of a child/children aged 0–5 years. The study explored (1) parents’ knowledge about child sexual abuse prevention, (2) the child sexual abuse prevention messages they provided to their children and the topics they discussed, (3) their attitudes towards child sexual abuse prevention education in schools, and (4) their preferences for content. Data analysis provided seven key themes in these four areas: knowledge (the inadequacy of their own prevention education; and how important is stranger danger now?); messages (bodies, touching, and relationships; the role of protective adults; and parent–child communication); attitudes (voice and choice); and preferences (not the nitty gritty, just the basics). The findings may be useful in assisting school authorities and providers of child sexual abuse prevention programs to better understand parents’ contributions to child sexual abuse prevention education, and their perspectives in relation to provision of school-based prevention programs.

Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes

Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

Doing blog research

Blogs and other online platforms for personal writing such as LiveJournal have been of interest to researchers across the social sciences and humanities for a decade now. Although growth in the uptake of blogging has stalled somewhat since the heyday of blogs in the early 2000s, blogging continues to be a major genre of Internet-based communication. Indeed, at the same time that mass participation has moved on to Facebook, Twitter, and other more recent communication phenomena, what has been left behind by the wave of mass adoption is a slightly smaller but all the more solidly established blogosphere of engaged and committed participants. Blogs are now an accepted part of institutional, group, and personal communications strategies (Bruns and Jacobs, 2006); in style and substance, they are situated between the more static information provided by conventional Websites and Webpages and the continuous newsfeeds provided through Facebook and Twitter updates. Blogs provide a vehicle for authors (and their commenters) to think through given topics in the space of a few hundred to a few thousand words – expanding, perhaps, on shorter tweets, and possibly leading to the publication of more fully formed texts elsewhere. Additionally, they are also a very flexible medium: they readily provide the functionality to include images, audio, video, and other additional materials – as well as the fundamental tool of blogging, the hyperlink itself. Indeed, the role of the link in blogs and blog posts should not be underestimated. Whatever the genre and topic that individual bloggers engage in, for the most part blogging is used to provide timely updates and commentary – and it is typical for such material to link both to relevant posts made by other bloggers, and to previous posts by the present author, both to background material which provides readers with further information about the blogger’s current topic, and to news stories and articles which the blogger found interesting or worthy of critique. Especially where bloggers are part of a larger community of authors sharing similar interests or views (and such communities are often indicated by the presence of yet another type of link – in blogrolls, often in a sidebar on the blog site, which list the blogger’s friends or favourites), then, the reciprocal writing and linking of posts often constitutes an asynchronous, distributed conversation that unfolds over the course of days, weeks, and months. Research into blogs is interesting for a variety of reasons, therefore. For one, a qualitative analysis of one or several blogs can reveal the cognitive and communicative processes through which individual bloggers define their online identity, position themselves in relation to fellow bloggers, frame particular themes, topics and stories, and engage with one another’s points of view. It may also shed light on how such processes may differ across different communities of interest, perhaps in correlation with the different societal framing and valorisation of specific areas of interest, with the socioeconomic backgrounds of individual bloggers, or with other external or internal factors. Such qualitative research now looks back on a decade-long history (for key collections, see Gurak, et al., 2004; Bruns and Jacobs, 2006; also see Walker Rettberg, 2008) and has recently shifted also to specifically investigate how blogging practices differ across different cultures (Russell and Echchaibi, 2009). Other studies have also investigated the practices and motivations of bloggers in specific countries from a sociological perspective, through large-scale surveys (e.g. Schmidt, 2009). Blogs have also been directly employed within both K-12 and higher education, across many disciplines, as tools for reflexive learning and discussion (Burgess, 2006).

A comparative study of the number and mass of fine particles emitted with diesel fuel and marine gas oil (MGO)

The current investigation reports on diesel particulate matter emissions, with special interest in fine particles from the combustion of two base fuels. The base fuels selected were diesel fuel and marine gas oil (MGO). The experiments were conducted with a four-stroke, six-cylinder, direct injection diesel engine. The results showed that the fine particle number emissions measured by both SMPS and ELPI were higher with MGO compared to diesel fuel. It was observed that the fine particle number emissions with the two base fuels were quantitatively different but qualitatively similar. The gravimetric (mass basis) measurement also showed higher total particulate matter (TPM) emissions with the MGO. The smoke emissions, which were part of TPM, were also higher for the MGO. No significant changes in the mass flow rate of fuel and the brake-specific fuel consumption (BSFC) were observed between the two base fuels.

Evolutionary biology : mass survivals

The conclusion that the primary divergences of the modern groups of mammals occurred in the mid-Cretaceous requires fresh thinking about this facet of evolutionary history — especially in ecological terms.

Rapid prototyping framework for visual control of autonomous micro aerial vehicles

Rapid prototyping environments can speed up the research of visual control algorithms. We have designed and implemented a software framework for fast prototyping of visual control algorithms for Micro Aerial Vehicles (MAV). We have applied a combination of a proxy-based network communication architecture and a custom Application Programming Interface. This allows multiple experimental configurations, like drone swarms or distributed processing of a drone's video stream. Currently, the framework supports a low-cost MAV: the Parrot AR.Drone. Real tests have been performed on this platform and the results show comparatively low figures of the extra communication delay introduced by the framework, while adding new functionalities and flexibility to the selected drone. This implementation is open-source and can be downloaded from www.vision4uav.com/?q=VC4MAV-FW

Experimental validation of an unpowered unmanned aerial system : application to forced landing scenarios

The ability to perform autonomous emergency (forced) landings is one of the key technology enablers identified for UAS. This paper presents the flight test results of forced landings involving a UAS, in a controlled environment, and which was conducted to ascertain the performances of previously developed (and published) path planning and guidance algorithms. These novel 3-D nonlinear algorithms have been designed to control the vehicle in both the lateral and longitudinal planes of motion. These algorithms have hitherto been verified in simulation. A modified Boomerang 60 RC aircraft is used as the flight test platform, with associated onboard and ground support equipment sourced Off-the-Shelf or developed in-house at the Australian Research Centre for Aerospace Automation(ARCAA). HITL simulations were conducted prior to the flight tests and displayed good landing performance, however, due to certain identified interfacing errors, the flight results differed from that obtained in simulation. This paper details the lessons learnt and presents a plausible solution for the way forward.

Double diffusive magneto-convection fluid flow in a strong cross magnetic field with uniform surface heat and mass flux

In this study, magnetohydrodynamic natural convection boundary layer flow of an electrically conducting and viscous incompressible fluid along a heated vertical flat plate with uniform heat and mass flux in the presence of strong cross magnetic field has been investigated. For smooth integrations the boundary layer equations are transformed in to a convenient dimensionless form by using stream function formulation as well as the free variable formulation. The nonsimilar parabolic partial differential equations are integrated numerically for Pr ≪1 that is appropriate for liquid metals against the local Hartmann parameter ξ . Further, asymptotic solutions are obtained near the leading edge using regular perturbation method for smaller values of ξ . Solutions for values of ξ ≫ 1 are also obtained by employing the matched asymptotic technique. The results obtained for small, large and all ξ regimes are examined in terms of shear stress, τw, rate of heat transfer, qw, and rate of mass transfer, mw, for important physical parameter. Attention has been given to the influence of Schmidt number, Sc, buoyancy ratio parameter, N and local Hartmann parameter, ξ on velocity, temperature and concentration distributions and noted that velocity and temperature of the fluid achieve their asymptotic profiles for Sc ≥ 10:0.

‘They get fed up with playing.’ Parents’ views on play-based learning in the Preparatory Year

Within early childhood education two ideas are firmly held: play is the best way for children to learn and parents are partners in the child’s learning. While these ideas have been explored, limited research to date has investigated the confluence of the two - how parents of young children view the concept of play. This paper investigates parents’ views on play by analysing the views of small group of parents of Prep Year children in Queensland, Australia. The parents in this study held varying definitions of what constitutes play, and complex and contradictory notions of its value. Positive views of play were linked to learning without knowing it, engaging in hands-on activities, and preparation for Year One through a strong focus on academic progress. Some parents held that Prep was play-based, while others did not. The complexities and diversity of parental opinion in this study echo the ongoing commentary about how play ought to be defined. Moreover, the notion that adults may interpret play in different ways is also reflected here. The authors suggest that for early childhood educators these complexities require an ongoing engagement, debate and reconceptualisation of the place of play in light of broader curricular and socio-political agendas.

A mass spectrometric assay for the quantification of neuropeptide PYY in plasma

A multiple reaction monitoring mass spectrometric assay for the quantification of PYY in human plasma has been developed. A two stage sample preparation protocol was employed in which plasma containing the full length neuropeptide was first digested using trypsin, followed by solid-phase extraction to extract the digested peptide from the complex plasma matrix. The peptide extracts were analysed by LC-MS using multiple reaction monitoring to detect and quantify PYY. The method has been validated for plasma samples, yielding linear responses over the range 5–1,000 ng mL−1. The method is rapid, robust and specific for plasma PYY detection.