Making sense of an everyday science text : linguistic, visual and spatial design

In this article, we take a close look at the literacy demands of one task from the ‘Marvellous Micro-organisms Stage 3 Life and Living’ Primary Connections unit (Australian Academy of Science, 2005). One lesson from the unit, ‘Exploring Bread’, (pp 4-8) asks students to ‘use bread labels to locate ingredient information and synthesise understanding of bread ingredients’. We draw upon a framework offered by the New London Group (2000), that of linguistic, visual and spatial design, to consider in more detail three bread wrappers and from there the complex literacies that students need to interrelate to undertake the required task. Our findings are that although bread wrappers are an example of an everyday science text, their linguistic, visual and spatial designs and their interrelationship are not trivial. We conclude by reinforcing the need for teachers of science to also consider how the complex design elements of everyday science texts and their interrelated literacies are made visible through instructional practice.

Making sense of working lives and working choices : the role of satirical cartoons

This study examined the tone and content of 107 political, satirical cartoons images published in the popular culture forum of mainstream newspapers. The cartoons illustrated the reform of the industrial relations system in Australia in 2005 and 2006. The images were conveyed in a moderate tone. That is, they were more about poking fun at and questioning authority and power, rather than simply describing the issues on one hand, or demonstrating any revolutionary fervor on the other. The cartoons’ content represented many of the concerns and issues being voiced by employer groups, government, opposition, unions and the media at the time. Themes likely to evoke a strong response from the readership included the importance of a collective response in voicing opposition to the legislation and enacting change, the risks to fundamental working conditions, the stealth and dogma associated with the rollout of the changes and the increasing disparity in wealth and power between employers and workers. The images were an important part of the wider discourse and a mechanism which helped place industrial relations squarely in the minds of working Australians.

Sense and sensibility by Jane Austen

It's the fact that it's Austen mentioned here that provokes a response. The broad cultural veneration of Jane Austen means that even those who have never read her work are likely to have a strong reaction to Emerson's famou quotation. It is worth considering Emerson's accustion befor teaching an Austen novel, as many of his assertions will be amde - albeit in different terms - byt twenty-first-century students.

Making sense of the resource-based view?

The Resource Based View (RBV) of strategic management has been criticized for relying on inconsistent assumptions of rationality, and mutually inconsistent underlying hypotheses. In this paper, I outline how these critiques can be addressed by re-building RBV on a sense-making foundation. The core notions from sense-making of bounded cognition, retrospective sense-making, incrementalism, loose coupling, causal maps and organizational paradigm are introduced. These are then used to propose a re-construction of key RBV constructs, extending some conceptual discussions, and providing for a conceptually consistent formulation. Implications for the use of RBV as a theory and future research are discussed.

Making sense of Australia's war memorials

War memorials are an important part of the Australian landscape and culture. This essay suggests five possible explanations for this: a) imperial loyalty, at least initially; b) the warrior cult; c) guilt at the loss of so many young people in a seemingly senseless fashion; d) the demise of formal religion, and; e) the insecure nature of Australian nationalism.

Spaces of hybridity : creating a sense of belonging through spatial awareness

When the colonisers first came to Australia there was an urgent desire to map, name and settle. This desire, in part, stemmed from a fear of the unknown. Once these tasks were completed it was thought that a sense of identity and belonging would automatically come. In Anglo-Australian geography the map of Australia was always perceived in relationship to the larger map of Europe and Britain. The quicker Australia could be mapped the quicker its connection with the ‘civilised’ world could be established. Official maps could be taken up in official history books and a detailed monumental history could begin. Australians would feel secure in where they were placed in the world. However, this was not the case and anxieties about identity and belonging remained. One of the biggest hurdles was the fear of the open spaces and not knowing how to move across the land. Attempts to transpose colonisers’ use of space onto the Australian landscape did not work and led to confusion. Using authors who are often perceived as writers of national fictions (Henry Lawson, Barbara Baynton, Patrick White, David Malouf and Peter Carey) I will reveal how writing about space becomes a way to create a sense of belonging. It is through spatial knowledge and its application that we begin to gain a sense of closeness and identity. I will also look at how one of the greatest fears for the colonisers was the Aboriginal spatial command of the country. Aborigines already had a strongly developed awareness of spatial belonging and their stories reveal this authority (seen in the work of Lorna Little, Mick McLean) Colonisers attempted to discredit this knowledge but the stories and the land continue to recognise its legitimacy. From its beginning Australian spaces have been spaces of hybridity and the more the colonisers attempted to force predetermined structures onto these spaces the more hybrid they became.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Towards the implementation of vision-based UAS sense-and-avoid

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 the sensors involved. This paper describes the development of detection algorithms and the evaluation of a real-time flight ready hardware implementation of a vision-based collision detection system suitable for fixed-wing small/medium size UAS. In particular, this paper demonstrates the use of Hidden Markov filter to track and estimate the elevation (β) and bearing (α) of the target, compares several candidate graphic processing hardware choices, and proposes an image based visual servoing approach to achieve collision avoidance

Examination of the latent structure of the psychological sense of school membership scale

Despite its widespread use, there has been limited examination of the underlying factor structure of the Psychological Sense of School Membership (PSSM) scale. The current study examined the psychometric properties of the PSSM to refine its utility for researchers and practitioners using a sample of 504 Australian high school students. Results from exploratory and confirmatory factor analyses indicated that the PSSM is a multidimensional instrument. Factor analysis procedures identified three factors representing related aspects of students’ perceptions of their school membership: caring relationships, acceptance, and rejection

Making sense of brain tumour: A qualitative investigation of personal and social processes of adjustment

This study investigated personal and social processes of adjustment at different stages of illness for individuals with brain tumour. A purposive sample of 18 participants with mixed tumour types (9 benign and 9 malignant) and 15 family caregivers was recruited from a neurosurgical practice and a brain tumour support service. In-depth semi-structured interviews focused on participants’ perceptions of their adjustment, including personal appraisals, coping and social support since their brain tumour diagnosis. Interview transcripts were analysed thematically using open, axial and selective coding techniques. The primary theme that emerged from the analysis entailed “key sense making appraisals”, which was closely related to the following secondary themes: (1) Interactions with those in the healthcare system, (2) reactions and support from the personal support network, and (3) a diversity of coping efforts. Adjustment to brain tumour involved a series of appraisals about the illness that were influenced by interactions with those in the healthcare system, reactions and support from people in their support network, and personal coping efforts. Overall, the findings indicate that adjustment to brain tumour is highly individualistic; however, some common personal and social processes are evident in how people make sense of and adapt to the illness over time. A preliminary framework of adjustment based on the present findings and its clinical relevance are discussed. In particular, it is important for health professionals to seek to understand and support individuals’ sense-making processes following diagnosis of brain tumour.