Dynamic digital posters : making the most of collaborative learning spaces

Academic and professional staff at Queensland University of Technology (QUT) have been faced with the challenge of how to create engaging student experiences in collaborative learning spaces. In 2013 a new Bachelor of Science course was implemented focusing on inquiry-based, collaborative and active learning. Student groups in two of the first year units carried out a poster assessment task. This paper provides a preliminary evaluation of the assessment approach used, whereby students created dynamic digital posters to capitalise on the affordances of the learning space.

Subtropical futures : Victoria Park re-imagined

Brisbane, the capital of Queensland, in South-East Queensland is situated on the Brisbane River, one of the largest rivers (and floodplains) on the east coast of Australia. The river defines the city and gives it its name. The river has been a natural place to accommodate some population growth for the city with high-density development that capitalises on the natural amenity, cycleways and a string of parks and the flatter land. The major floods of 2011 and the scare of 2013, has seen a more malevolent quality of the river and shift of thinking on its role within the city. The floods have made council, for the first time, acquire prime development sites near the river, with proposals for high density development and made them parks, at great cost. The pressure for population growth in Brisbane remains. 140,000 new dwellings are required by 2031. Brownfield sites are less plentiful and there is interest to rethink of some of the other strategic locations in the city away from the river on higher ground and steeper slopes. Some of these places are currently open spaces. Victoria Park Golf Course sits on a high ridge line and a very strategic part of the city just north of the city centre is one of the few remaining golf courses close to the centre of an Australian capital city. While it is a public course and a valuable community asset, it has been compromised by the recently completed northern busway with two bus stations constructed on its edges. It is bounded on the west and north-east by two major community facilities, the Queensland University of Technology (QUT) to the west and RBW Hospital at its northern end. In a city in need of urban consolidation, perhaps it is time to review the future of the golf course. This question has been investigated as a conjecture in the Master of Architecture program at the QUT. The project has been to re-imagine Victoria Park as a new city parkland and a place that makes an urban connection from the QUT to the hospital. This new urban precinct is be a medium to high-density transit oriented development that capitalises on the bus way stations and the proximity of the university and hospital. The precinct will frame/define/interact with the new major urban park for the city. A key question being addressed is how the design can embody and define principles of a subtropical urbanism. Students are identifying the appropriate street and block structure, density and built form to be accommodated on blocks that define and activate a rich sequence of streets and public spaces. The paper will present a critical overview of the project work that provides a lens to how future professionals may respond to these issue that will be the focus of their professional lives.

Towards Vision-Based Pose- and Condition-Invariant Place Recognition along Routes

Vision-based place recognition involves recognising familiar places despite changes in environmental conditions or camera viewpoint (pose). Existing training-free methods exhibit excellent invariance to either of these challenges, but not both simultaneously. In this paper, we present a technique for condition-invariant place recognition across large lateral platform pose variance for vehicles or robots travelling along routes. Our approach combines sideways facing cameras with a new multi-scale image comparison technique that generates synthetic views for input into the condition-invariant Sequence Matching Across Route Traversals (SMART) algorithm. We evaluate the system’s performance on multi-lane roads in two different environments across day-night cycles. In the extreme case of day-night place recognition across the entire width of a four-lane-plus-median-strip highway, we demonstrate performance of up to 44% recall at 100% precision, where current state-of-the-art fails.

FluMum : a prospective cohort study of mother-infant pairs assessing the effectiveness of maternal influenza vaccination in prevention of influenza in early infancy

INTRODUCTION Influenza vaccination in pregnancy is recommended for all women in Australia, particularly those who will be in their second or third trimester during the influenza season. However, there has been no systematic monitoring of influenza vaccine uptake among pregnant women in Australia. Evidence is emerging of benefit to the infant with respect to preventing influenza infection in the first 6 months of life. The FluMum study aims to systematically monitor influenza vaccine uptake during pregnancy in Australia and determine the effectiveness of maternal vaccination in preventing laboratory-confirmed influenza in their offspring up to 6 months of age. METHODS AND ANALYSIS A prospective cohort study of 10 106 mother-infant pairs recruited between 38 weeks gestation and 55 days postdelivery in six Australian capital cities. Detailed maternal and infant information is collected at enrolment, including influenza illness and vaccination history with a follow-up data collection time point at infant age 6 months. The primary outcome is laboratory-confirmed influenza in the infant. Case ascertainment occurs through searches of Australian notifiable diseases data sets once the infant turns 6 months of age (with parental consent). The primary analysis involves calculating vaccine effectiveness against laboratory-confirmed influenza by comparing the incidence of influenza in infants of vaccinated mothers to the incidence in infants of unvaccinated mothers. Secondary analyses include annual and pooled estimates of the proportion of mothers vaccinated during pregnancy, the effectiveness of maternal vaccination in preventing hospitalisation for acute respiratory illness and modelling to assess the determinants of vaccination. ETHICS AND DISSEMINATION The study was approved by all institutional Human Research Ethics Committees responsible for participating sites. Study findings will be published in peer review journals and presented at national and international conferences. TRIAL REGISTRATION NUMBER The study is registered with the Australia and New Zealand Clinical Trials Registry (ANZCTR) number: 12612000175875.

A case study of utilising concept knowledge in a topic specific document collection

The use of ‘topic’ concepts has shown improved search performance, given a query, by bringing together relevant documents which use different terms to describe a higher level concept. In this paper, we propose a method for discovering and utilizing concepts in indexing and search for a domain specific document collection being utilized in industry. This approach differs from others in that we only collect focused concepts to build the concept space and that instead of turning a user’s query into a concept based query, we experiment with different techniques of combining the original query with a concept query. We apply the proposed approach to a real-world document collection and the results show that in this scenario the use of concept knowledge at index and search can improve the relevancy of results.

Selection procedures for module discovery : exploring evolutionary algorithms for cognitive science

Evolutionary algorithms are playing an increasingly important role as search methods in cognitive science domains. In this study, methodological issues in the use of evolutionary algorithms were investigated via simulations in which procedures were systematically varied to modify the selection pressures on populations of evolving agents. Traditional roulette wheel, tournament, and variations of these selection algorithms were compared on the “needle-in-a-haystack” problem developed by Hinton and Nowlan in their 1987 study of the Baldwin effect. The task is an important one for cognitive science, as it demonstrates the power of learning as a local search technique in smoothing a fitness landscape that lacks gradient information. One aspect that has continued to foster interest in the problem is the observation of residual learning ability in simulated populations even after long periods of time. Effective evolutionary algorithms balance their search effort between broad exploration of the search space and in-depth exploitation of promising solutions already found. Issues discussed include the differential effects of rank and proportional selection, the tradeoff between migration of populations towards good solutions and maintenance of diversity, and the development of measures that illustrate how each selection algorithm affects the search process over generations. We show that both roulette wheel and tournament algorithms can be modified to appropriately balance search between exploration and exploitation, and effectively eliminate residual learning in this problem.

Language and literacy in mathematics: stepping stones or stumbling blocks in accelerating junior-secondary students

The authors have collaborated in the development and initial evaluation of a curriculum for mathematics acceleration. This paper reports upon the difficulties encountered with documenting student understanding using pen-and-paper assessment tasks. This leads to a discussion of the impact of students’ language and literacy on mathematical performance and the consequences for motivation and engagement as a result of simplifying the language in the tests, and extending student work to algebraic representations. In turn, implications are drawn for revisions to assessment used within the project and the language and literacy focus included within student learning experiences.

Use of genetic decompositions to scaffold the development of a structurally sequenced curriculum for mathematics acceleration

The authors have collaboratively used a graphical language to describe their shared knowledge of a small domain of mathematics, which has in turn scaffolded their re-development of a related curriculum for mathematics acceleration. This collaborative use of the graphical language is reported as a simple descriptive case study. This leads to an evaluation of the graphical language’s usefulness as a tool to support the articulation of the structure of mathematics knowledge. In turn, implications are drawn for how the graphical language may be utilised as the detail of the curriculum is further elaborated and communicated to teachers.

Unsupervised online learning of condition-invariant images for place recognition

This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.

Hardware design and implementation of a MAVLink interface for an FPGA-based autonomous UAV flight control system

This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

Temporal trends and bioavailability assessment of heavy metals in the sediments of Deception Bay, Queensland, Australia

Thirteen sites in Deception Bay, Queensland, Australia were sampled three times over a period of 7 months and assessed for contamination by a range of heavy metals, primarily As, Cd, Cr, Cu, Pb and Hg. Fraction analysis, enrichment factors and Principal Components Analysis-Absolute Principal Component Scores (PCA-APCS) analysis were conducted in order to identify the potential bioavailability of these elements of concern and their sources. Hg and Te were identified as the elements of highest enrichment in Deception Bay while marine sediments, shipping and antifouling agents were identified as the sources of the Weak acid Extractable Metals (WE-M), with antifouling agents showing long residence time for mercury contamination. This has significant implications for the future of monitoring and regulation of heavy metal contamination within Deception Bay.

Interpreting discovered patterns in terms of ontology concepts

Semantic Web offers many possibilities for future Web technologies. Therefore, it is a need to search for ways that can bring the huge amount of unstructured documents from current Web to Semantic Web automatically. One big challenge in searching for such ways is how to understand patterns by both humans and machine. To address this issue, we present an innovative model which interprets patterns to high level concepts. These concepts can explain the patterns' meanings in a human understandable way while improving the information filtering performance. The model is evaluated by comparing it against one state-of-the-art benchmark model using standard Reuters dataset. The results show that the proposed model is successful. The significance of this model is three fold. It gives a way to interpret text mining output, provides a technique to find concepts relevant to the whole set of patterns which is an essential feature to understand the topic, and to some extent overcomes information mismatch and overload problems of existing models. This model will be very useful for knowledge based applications.