Early mathematical learning: Number processing skills and executive function at 5 and 8 years of age

This research investigated differences and associations in performance in number processing and executive function for children attending primary school in a large Australian metropolitan city. In a cross-sectional study, performance of 25 children in the first full-time year of school, (Prep; mean age = 5.5 years) and 21 children in Year 3 (mean age = 8.5 years) completed three number processing tasks and three executive function tasks. Year 3 children consistently outperformed the Prep year children on measures of accuracy and reaction time, on the tasks of number comparison, calculation, shifting, and inhibition but not on number line estimation. The components of executive function (shifting, inhibition, and working memory) showed different patterns of correlation to performance on number processing tasks across the early years of school. Findings could be used to enhance teachers’ understanding about the role of the cognitive processes employed by children in numeracy learning, and so inform teachers’ classroom practices.

Prototyping the self-authored video interview : Challenges and opportunities

Self-authored video- where participants are in control of the creation of their own footage- is a means of creating innovative design material and including all members of a family in design activities. This paper describes our adaptation to this process called Self Authored Video Interviews (SAVIs) that we created and prototyped to better understand how families engage with situated technology in the home. We find the methodology produces unique insights into family dynamics in the home, uncovering assumptions and tensions unlikely to be discovered using more conventional methods. The paper outlines a number of challenges and opportunities associated with the methodology, specifically, maximising the value of the insights gathered by appealing to children to champion the cause, and how to counter perceptions of the lingering presence of researchers.

Collaborative data exploration interfaces - From participatory sensing to participatory sensemaking

As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.

Thinking like Disney: Supporting the Disney method using ambient feedback based on group performance

The Disney method is a collaborative creativity technique that uses three roles - dreamer, realist and critic - to facilitate the consideration of different perspectives on a topic. Especially for novices it is important to obtain guidance in applying this method. One way is providing groups with a trained moderator. However, feedback about the group’s behavior might interrupt the flow of the idea finding process. We built and evaluated a system that provides ambient feedback to a group about the distribution of their statements among the three roles. Our preliminary field study indicates that groups supported by the system contribute more and roles are used in a more balanced way while the visualization does not disrupt the group work.

Export of radioactive cesium from agricultural fields under simulated rainfall in Fukushima

In this study, we investigated the impact of rainfall on runoff, soil erosion and consequently on the discharge of radioactive cesium in agricultural fields in Fukushima prefecture using a rainfall simulator. Simulated heavy rainfalls (50 mm h-1) generated significant runoff and soil erosion. The average concentration of radioactive cesium (the sum of 134Cs and 137Cs) in the runoff sediments was [similar]3500 Bq kg-1 dry soil, more than double the concentrations measured in the field soils which should be considered in studies using the 137Cs loss to estimate long-term soil erosion. However, the estimated mass of cesium discharged through one runoff event was less than 2% of the cesium inventory in the field. This suggested that cesium discharge via soil erosion is not a significant factor in reducing the radioactivity of contaminated soils in Fukushima prefecture. However, the eroded sediment carrying radioactive cesium will deposit into the river systems and potentially pose a radioactivity risk for aquatic living organisms.

Introduction to "International Perspectives on Business Innovation and Disruption in the Creative Industries Film, Video and Photography"

The creative industries are particularly fecund empirical fields for investigating the processes of business innovation and disruption. The creative industries are some of the fastest growing sectors in many economies (European Commission, 2001; OECD, 2006; United States Census Bureau, 2010) and thus are worthy of study in their own right. Additionally, the study of the creative industries affords insights into how we understand the current economic transformation towards knowledge- based economies more broadly. The transformation toward knowledge- based economies has been foreshadowed by the transformation of creative industries such as publishing, film, video, photography, music and so on...

Identifying relevant information for emergency services from twitter in response to natural disaster

This project proposes a framework that identifies high‐value disaster-based information from social media to facilitate key decision-making processes during natural disasters. At present it is very difficult to differentiate between information that has a high degree of disaster relevance and information that has a low degree of disaster relevance. By digitally harvesting and categorising social media conversation streams automatically, this framework identifies highly disaster-relevant information that can be used by emergency services for intelligence gathering and decision-making.

Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms

There is an increased interest in measuring the amount of greenhouse gases produced by farming practices . This paper describes an integrated solar powered Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system for greenhouse gas emissions in agricultural lands. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the unmanned aerial system (UAS)as well as a data management platform to store, analyze and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications at a relatively low operational cost. In particular, agricultural environments are increasingly subject to emissions mitigation policies. Accurate measurements of CH4 and CO2 with its temporal and spatial variability can provide farm managers key information to plan agricultural practices. A video of the bench and flight test performed can be seen in the following link: https://www.youtube.com/watch?v=Bwas7stYIxQ

Narrative as a tool for critical reflective practice in the creative industries

This paper explores the efficacy of narrative in reflective practice across a range of creative disciplines. As practitioners within the creative industries the authors internalise experience and re-contextualise it as stories, designs, music videos, fiction and non-fiction films and dance. They are uniquely placed to examine narrative in critical reflection through the prism of their creative practice and in so doing offer insights into reconceptualising professional practice. The authors demonstrate how engagement with and reflection on and in their stories enables wider reflection. Their purpose in reflection is not just to learn from mistakes but to develop an epistemology of practice that enables them to apply rigorous academic inquiry to articulate their tacit professional knowledge and establish new methods for dealing with uncertainty in creative practice research.

You're hot, then you're cold: Creative industries policy making in Australia

Much compelling evidence has emerged over the last two decades demonstrating the importance of Australia’s creative industries. In 2014, the Australian Bureau of Statistics confirmed that culture is ‘big business’ in this country. Yet despite this, interest by policy makers at all levels of government has been intermittent, at best. This chapter gives a brief history of policy development, and offers a number of reasons for why policy and politics have not focussed more resolutely on Australia’s creative economy. It finishes with a discussion of Australia’s ‘unfinished agenda’, one which demands attention not only by government, but also industry and higher education, if we are to properly meet both the challenges and opportunities before us.

Relationships between user experience and intuitiveness of visual and physical interactions

This paper investigates the effects of experience on the intuitiveness of physical and visual interactions performed by airport security screeners. Using portable eye tracking glasses, 40 security screeners were observed in the field as they performed search, examination and interface interactions during airport security x-ray screening. Data from semi structured interviews was used to further explore the nature of visual and physical interactions. Results show there are positive relationships between experience and the intuitiveness of visual and physical interactions performed by security screeners. As experience is gained, security screeners are found to perform search, examination and interface interactions more intuitively. In addition to experience, results suggest that intuitiveness is affected by the nature and modality of activities performed. This inference was made based on the dominant processing styles associated with search and examination activities. The paper concludes by discussing the implications that this research has for the design of visual and physical interfaces. We recommend designing interfaces that build on users’ already established intuitive processes, and that reduce the cognitive load incurred during transitions between visual and physical interactions.

Image processing and classification procedure for the analysis of Australian frog vocalisations

Frog species have been declining worldwide at unprecedented rates in the past decades. There are many reasons for this decline including pollution, habitat loss, and invasive species [1]. To preserve, protect, and restore frog biodiversity, it is important to monitor and assess frog species. In this paper, a novel method using image processing techniques for analyzing Australian frog vocalisations is proposed. An FFT is applied to audio data to produce a spectrogram. Then, acoustic events are detected and isolated into corresponding segments through image processing techniques applied to the spectrogram. For each segment, spectral peak tracks are extracted with selected seeds and a region growing technique is utilised to obtain the contour of each frog vocalisation. Based on spectral peak tracks and the contour of each frog vocalisation, six feature sets are extracted. Principal component analysis reduces each feature set down to six principal components which are tested for classification performance with a k-nearest neighbor classifier. This experiment tests the proposed method of classification on fourteen frog species which are geographically well distributed throughout Queensland, Australia. The experimental results show that the best average classification accuracy for the fourteen frog species can be up to 87%.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

Questionnaire design for airport passenger experience survey

Assessing airport service performance requires understanding of a complete set of passenger experiences covering all activities from departures to arrivals. Weight-based indicator models allow passengers to express their priority on certain evaluation criteria (airport domains) and their service attributes over the others. The application of multilevel regression analysis in questionnaire design is expected to overcome limitations of traditional questionnaires, which require application of all indicators with equal weight. The development of a Taxonomy of Passenger Activities (TOPA), which captures all passenger processing and discretionary activities, has provided a novel perspective in understanding passenger experience in various airport domains. Based on further literature reviews on various service attributes at airport passenger terminals, this paper constitutes questionnaire design to employ a weighting method for all activities from the time passengers enter an airport domain at the departure terminal until leaving the arrival terminal (i.e. seven airport domains for departure, four airport domains during transit, and seven airport domains for arrival). The procedure of multilevel regression analysis is aimed not only at identifying the ranking of each evaluation criterion from the most important to the least important but also to explain the relationship between service attributes in each airport domain and overall service performance.