Urban informatics, ubiquitous computing and social media for healthy cities

The increasing ubiquity of digital technology, internet services and location-aware applications in our everyday lives allows for a seamless transitioning between the visible and the invisible infrastructure of cities: road systems, building complexes, information and communication technology, and people networks create a buzzing environment that is alive and exciting. Driven by curiosity, initiative and interdisciplinary exchange, the Urban Informatics Research Lab at Queensland University of Technology (QUT), Brisbane, Australia, is an emerging cluster of people interested in research and development at the intersection of people, place and technology with a focus on cities, locative media and mobile technology. This paper introduces urban informatics as a transdisciplinary practice across people, place and technology that can aid local governments, urban designers and planners in creating responsive and inclusive urban spaces and nurturing healthy cities. Three challenges are being discussed. First, people, and the challenge of creativity explores the opportunities and challenges of urban informatics that can lead to the design and development of new tools, methods and applications fostering participation, the democratisation of knowledge, and new creative practices. Second, technology, and the challenge of innovation examines how urban informatics can be applied to support user-led innovation with a view to promote entrepreneurial ideas and creative industries. Third, place, and the challenge of engagement discusses the potential to establish places within cities that are dedicated to place-based applications of urban informatics with a view to deliver community and civic engagement strategies.

A Python package for Bayesian estimation using Markov Chain Monte Carlo

Markov chain Monte Carlo (MCMC) estimation provides a solution to the complex integration problems that are faced in the Bayesian analysis of statistical problems. The implementation of MCMC algorithms is, however, code intensive and time consuming. We have developed a Python package, which is called PyMCMC, that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood of coding error, as well as aid in the minimisation of repetitive code. PyMCMC contains classes for Gibbs, Metropolis Hastings, independent Metropolis Hastings, random walk Metropolis Hastings, orientational bias Monte Carlo and slice samplers as well as specific modules for common models such as a module for Bayesian regression analysis. PyMCMC is straightforward to optimise, taking advantage of the Python libraries Numpy and Scipy, as well as being readily extensible with C or Fortran.

Marginalised students and insider knowledge

One of the claims made for valuing the voices of marginalised students is that an insider perspective can be revealed on student issues and the ways in which education policies and systems impact on them. This chapter examines the ways in which participants in an Australian ‘students-as-researchers’ (SaR) project were able to raise knowledge of and address, to some extent, long-standing issues of racism in their schools. The SaR project has operated in more than thirty schools for periods of one to five years. Based on a participatory action research model, groups of secondary school students from schools serving socio-economically disadvantaged communities have worked with nominated teachers and university researchers to identify and research local issues relating to low academic outcomes and to develop and enact responses to the identified concerns. The voices of marginalised students quoted in this chapter illustrate that important insider knowledge can be revealed through the SaR process. Where student views have been acknowledged and acted on by the schools, significant change to student-teacher relationships and school culture has been achieved; the participants have been personally empowered and academic improvements across the schools have been noted. For such change to occur, however, a culture of mutual respect must be created in which teachers and school administrators value students’ views and are open to the possibility of unfavourable criticism.

An exploration of young students' ability to generalise function tasks

The Early Years Generalising Project involves Australian students, Years 1-4 (age 5-9), and explores how the students grasp and express generalisations. This paper focuses on the data collected from clinical interviews with Year 3 and 4 cohorts in an investigative study focusing on the identifications, prediction and justification of function rules. It reports on students' attempts to generalise from function machine contexts, describing the various ways students express generalisation and highlighting the different levels of justification given by students. Finally, we conjecture that there are a set of stages in the expression and justification of generalisations that assist students to reach generality within tasks.

Drink driving after the first offence: Characteristics of offenders who continue to drink and drive

Drink driving remains a significant problem on Australian roads, with about a quarter to a third of fatal crashes involving drivers or riders who have a BAC of 0.05 or greater. Last available data in the state of Queensland (2003) of the major factors involved in road fatalities and injuries indicated that alcohol and drugs were noted as one of the contributing factors in 38% of fatalities and 11% of all crashes, making it the highest single contributing factor to road fatalities. Until this point, there has been little information about first time offenders as a group, but it is known that offenders typically are not first time drink drivers but rather ‘first time apprehended’, in that most have engaged in drink driving in the years leading to the first offence. This paper follows 89 first time drink driving offenders who were interviewed at the time of court mention and followed up around 6 months following the court hearing. Of the offenders, 27% reported to have driven over the limit in the time between initial contact and follow up. The paper demonstrates the characteristics and offending patterns of first offenders who engaged in drink driving following conviction and those who didn’t, providing suggestions on how to target those at high risk for the behaviour and subsequent offending.

Sociopathic attitudes to road safety

Injuries and deaths due to unsafe driving practices are a substantial health and socioeconomic burden to the community. Young socially disadvantaged males who are involved in a lifestyle of risky behaviour, crime and motor vehicle accidents seem unaffected by educational campaigns to improve safer driving. The aim is to develop a driving and social behavioural profile that may explain the lack of effectiveness of road safety advertising and suggest ways to refine educational strategies to reduce the risky lifestyle and associated harms among those most vulnerable, the 15-25 year olds. The procedure involved a quantitative and qualitative analysis through questionnaires, surveys and focus groups involving a comparison of populations (n = 668) by age, gender and socioeconomic status in three discrete Australian sites. Information gathered included issues related to road safety awareness, knowledge of advertising, personal and peer group attitudes as well as driving and life style history. The results indicate that within the community a highly visible profile of strong anti-social road safety activities by an educationally and economically disadvantaged sub-culture exists and this group seem impervious to road safety advertising and education initiatives. As the overall unsafe driving and risky antisocial behaviour is significant among 15-25 year olds within the community the solution is seen to be community based. A long-term (five to ten year) program has been posited; promoting community partnerships through consultative and local action committees at all levels creating locally designed formal and informal educational and mutual support programs.

Women, drinking and aggression on a night out: Do girls just wanna have fun?

Alcohol misuse and violence is a major public safety concern. Although the extent and nature of alcohol-related violence has been examined there is a paucity of research surrounding the ongoing construction and re-construction of gender identity and its relationship to aggression and alcohol consumption. A social constructionist perspective was used to explore women’s perceptions and experiences of drinking alcohol and incidents of public violence and aggression. Two methods were used. Firstly, an exploratory study consisting of three in-depth interviews and three focus groups to examine the ideas women constructed in relation to their experiences; and further, an online survey to explore self-reported drinking patterns among men and women. The main themes emerging from the qualitative material were ‘planned drinking to excess’ (incorporating the rituals of a ‘pre-drink’ routine), and perceptions of appropriate feminine behaviour (particularly in relation to excessive drinking and alcohol related aggression in and around licensed venues). The survey data indicated that men continue to consume more alcohol and at higher levels than women, while women’s involvement in aggressive incidents on a night out being similar to that of men. Both genders considered that women’s involvement in aggressive incidents in and around licensed venues as ‘unfeminine’. Understanding drinking as a socially constructed activity adds to our understanding of the meaning of drinking for women, and in particular, young women. This perspective may allow more focussed initiatives to address the social and health related harms associated with drinking in and around licensed venues.

Feature-based visual odometry and featureless place recognition for SLAM in 2.5D environments

In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

Projecting Computational Sense of Self: A Study of Transition in a Chronic Illness Online Community

We report on analysis of discussions in an online community of people with chronic illness using socio-cognitively motivated, automatically produced semantic spaces. The analysis aims to further the emerging theory of "transition" (how people can learn to incorporate the consequences of illness into their lives). An automatically derived representation of sense of self for individuals is created in the semantic space by the analysis of the email utterances of the community members. The movement over time of the sense of self is visualised, via projection, with respect to axes of "ordinariness" and "extra-ordinariness". Qualitative evaluation shows that the visualisation is paralleled by the transitions of people during the course of their illness. The research aims to progress tools for analysis of textual data to promote greater use of tacit knowledge as found in online virtual communities. We hope it also encourages further interest in representation of sense-of-self.

Controlling cell-material interactions with polymer nanocomposites by use of surface modifying additives

Polymer nanocomposites (NC) are fabricated by incorporating well dispersed nanoscale particles within a polymer matrix. This study focuses on elastomeric polyurethane (PU) based nanocomposites, containing organically modified silicates (OMS), as bioactive materials. Nanocomposites incorporating chlorhexidine diacetate as an organic modifier (OM) were demonstrated to be antibacterial with a dose dependence related to both the silicate loading and the loading of OM. When the non-antibacterial OM dodecylamine was used, both cell and platelet adhesion were decreased on the nanocomposite surface. These results suggest that OM is released from the polymer and can impact on cell behaviour at the interface. Nanocomposites have potential use as bioactive materials in a range of biomedical applications.