The Habitual Rhythms of Becoming-Involved: Insights into Participation Experiences in Urban Spaces by Children with Diverse Mobility

This chapter reports on a study that reveals the essence of participation in urban spaces by ten children who live with various physical conditions: Muscular Dystrophy, Cerebral Palsy, and Autoimmune Rheumatic Diseases. These conditions affect muscle and movement differently resulting in diverse ways in which children move through space (personal mobility). The children at the time of the research were 9-12 years of age residing in South-east Queensland, Australia. The approach and methods selected for this study, interpretive phenomenological inquiry and grounded theory, were chosen for their capacity to capture the complexity and multiple interactions of the child’s urban living. The confronting and poignant accounts by children and their families of their experiences produced a new way of understanding the concept of participation, as a ‘journey of becoming involved.’ Their accounts of performing everyday routines (e.g. leaving home, getting in and out of the car, and entering places) in urban spaces (neighbourhood streets, schools, open spaces, shopping centres, and hospitals) revealed differences in the way settings were experienced. These differences were associated with the interplay between the body, space and context. Where interplays were problematic, explicit decisions about children’s involvement were made. These decisions were described in terms of ‘avoid going’, ‘pick and choose’, ‘discontinue’, ‘accept’, or ‘contest.’ What these decisions mean is some spaces are avoided, some journeys are discontinued, and some barriers encountered in journeys are normalised as everyday experiences, i.e. ‘tolerable discrimination’. These actions resulted in experiences of non-participation or partial–tokenistic participation. The key substantive contribution of the research lies in the identification of points in children’s journeys that shape participation experience. These points identify where future interventions in policy, programming and design can be made to make real and sustaining changes to lives of children and their families in geographies crucial to urban living.

Simultaneous localization and planning on multiple map hypotheses

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

When to pull the plug and when to take the plunge : timing strategic decisions about new ventures

It is not uncommon for firms to explore a new venture under the belief it will generate profits, only to find out later that although costs accumulated, profits did not materialize. To manage the high level of uncertainty involved in this process, new ventures are generally designed as vehicles of exploration (Wu, 2012) that allow for a staged investment of resources, starting with small initial investments that can be scaled up or discontinued as uncertainty is resolved over time (Folta, 1998; Li and Chi, 2013). As such, new ventures provide firms a vehicle by which they can probe an uncertain future (Brown and Eisenhardt, 1997) without fully committing early on to an irreversible course of action (Folta, Johnson, and O’Brien, 2006). Our focus in the present paper is on the timing of strategic decisions that firms make regarding their exploration ventures. Prior research in the fields of entrepreneurship, real options reasoning, and decision speed has demonstrated a link between the timing of making decisions and performance (Baum and Wally, 2003; Eisenhardt, 1989; Judge and Miller, 1991). The antecedents to the timing of decisions, however, are less understood and pose an interesting dilemma.

The topography of multiple drug use among adolescent Australians : findings from the National Drug Strategy Household Survey

Introduction and aims: Despite evidence that many Australian adolescents have considerable experience with various drug types, little is known about the extent to which adolescents use multiple substances. The aim of this study was to examine the degree of clustering of drug types within individuals, and the extent to which demographic and psychosocial predictors are related to cluster membership. Design and method: A sample of 1402 adolescents aged 12-17. years were extracted from the Australian 2007 National Drug Strategy Household Survey. Extracted data included lifetime use of 10 substances, gender, psychological distress, physical health, perceived peer substance use, socioeconomic disadvantage, and regionality. Latent class analysis was used to determine clusters, and multinomial logistic regression employed to examine predictors of cluster membership. Result: There were 3 latent classes. The great majority (79.6%) of adolescents used alcohol only, 18.3% were limited range multidrug users (encompassing alcohol, tobacco, and marijuana), and 2% were extended range multidrug users. Perceived peer drug use and psychological distress predicted limited and extended multiple drug use. Psychological distress was a more significant predictor of extended multidrug use compared to limited multidrug use. Discussion and conclusion: In the Australian school-based prevention setting, a very strong focus on alcohol use and the linkages between alcohol, tobacco and marijuana are warranted. Psychological distress may be an important target for screening and early intervention for adolescents who use multiple drugs.

Real-time decision making by driverless city vehicles : a discrete event driven approach

This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

Making smart decisions : key steps towards a typology for emergency communication during natural hazards

Governments, authorities, and organisations dedicate significant resources to encourage communities to prepare for and respond to natural hazards such as cyclones, earthquakes, floods, and bushfires. However, recent events, media attention, and ongoing academic research continue to highlight cases of non-compliance including swift water rescues. Individuals who fail to comply with instructions issued during natural hazards significantly impede the emergency response because they divert resources to compliance-enforcement and risk the lives of emergency service workers who may be required to assist them. An initial investigation of the field suggests several assumptions or practices that influence emergency management policy, communication strategy, and community behaviours during natural hazards: 1) that community members will comply with instructions issued by governments and agencies that represent the most authoritative voice, 2) that communication campaigns are shaped by intuition rather than evidence-based approaches (Wood et al., 2012), and 3) that emergency communication is linear and directional. This extended abstract represents the first stage of a collaborative research project that integrates industry and cross-disciplinary perspectives to provide evidence-based approaches for emergency and risk communication during the response and recovery phases of a natural hazard. Specifically, this abstract focuses on the approach taken and key elements that will form the development of a typology of compliance-gaining messages during the response phase of natural hazards, which will be the focus of the conference presentation.

Making informed decisions on selecting promising Work Zone Safety Treatments

Lack of detailed and accurate safety records on incidents in Australian work zones prevents a thorough understanding of the relevant risks and hazards. Consequently it is difficult to select appropriate treatments for improving the safety of roadworkers and motorists alike. This paper presents a method for making informed decisions about safety treatments by 1) identifying safety issues and hazards in work zones, 2) understanding the attitudes and perceptions of both roadworkers and motorists, 3) reviewing the effectiveness of work zone safety treatments according to existing research, and 4) incorporating local expert opinion on the feasibility and usefulness of the safety treatments. Using data collected through semi-structured interviews with roadwork personnel and online surveys of Queensland drivers, critical safety issues were identified. The effectiveness of treatments for addressing the issues was understood through rigorous literature review and consultations with local road authorities. Promising work zone safety treatments include enforcement, portable rumble strips, perceptual measures to imply reduced lane width, automated or remotely-operated traffic lights, end of queue measures, and more visible and meaningful signage.

Theorizing the use of multiple conceptual models in combination

Conceptual modelling continues to be an important means for graphically capturing the requirements of an information system. Observations of modelling practice suggest that modellers often use multiple conceptual models in combination, because they articulate different aspects of real-world domains. Yet, the available empirical as well as theoretical research in this area has largely studied the use of single models, or single modelling grammars. We develop a Theory of Combined Ontological Coverage by extending an existing theory of ontological expressiveness of conceptual modelling grammars. Our new theory posits that multiple conceptual models are used to increase the maximum coverage of the real-world domain being modelled, whilst trying to minimize the ontological overlap between the models. We illustrate how the theory can be applied to analyse sets of conceptual models. We develop three propositions of the theory about evaluations of model combinations in terms of users’ selection, understandability and usefulness of conceptual models.

Population variation in biomonitoring data for persistent organic pollutants (POPs) : an examination of multiple population-based datasets for application to Australian pooled biomonitoring data

Background Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. Methods Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2′,4,4′ tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Results Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. Conclusions Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.

Making decisions about antibiotic use in the Australian primary healthcare sector

Introduction Australia is contributing to the global problem of antimicrobial resistance with one of the highest rates of antibiotic use amongst OECD countries. Data from the Australian primary healthcare sector suggests unnecessary antibiotics were prescribed for conditions that will resolve without it. If left unchecked, this will result in more resistant micro-organisms, against which antibiotics will be useless. There is a lack of understanding about what is influencing decisions to use antibiotics – what factors influences general practitioners (GPs) to prescribe antibiotics, consumers to seek antibiotics, and pharmacists to fill old antibiotic prescriptions? It is also not clear how these individuals trade-off between the possible benefits that antibiotics may provide in the immediate/short term, against the longer term societal risk of antimicrobial resistance. Method This project will investigate (a) what factors drive decisions to use antibiotics for GPs, pharmacists and consumers, and (b) how these individuals discount the future. Factors will be gleaned from published literature and from a qualitative phase using semi-structured interviews, to inform the development of Discrete Choice Experiments (DCEs). Three DCEs will be constructed – one for each group of interest – to allow investigation of which factors are more important in influencing (a) GPs to prescribe antibiotics, (b) consumers to seek antibiotics, and (c) pharmacists to fill legally valid but old or repeat prescriptions of antibiotics. Regression analysis will be conducted to understand the relative importance of these factors. A Time Trade Off exercise will be developed to investigate how these individuals discount the future, and whether GPs and pharmacists display the same extent of discounting the future, as consumers. Expected Results Findings from the DCEs will provide an insight into which factors are more important in driving decision making in antibiotic use for GPs, pharmacists and consumers. Findings from the Time Trade Off exercise will show what individuals are willing to trade for preserving the miracle of antibiotics. Conclusion The emergence of antibiotic resistance is inevitable. This research will expand on what is currently known about influencing desired behaviour change in antibiotic use, in the fight against antibiotic resistance. Real World Implications Research findings will contribute to existing national programs to bring about a reduction in inappropriate use of antibiotic in Australia. Specifically, influencing (1) how key messages and public health campaigns are crafted to increase health literacy, and (2) clinical education and empowerment of GPs and pharmacists to play a more responsive role as stewards of antibiotic use in the community.

Efficient multiple relay selection for cooperative communication using alamouti-coded virtual transmit antenna systems

An opportunistic relay selection scheme improving cooperative diversity is devised using the concept of a virtual SIMO-MISO antenna array. By incorporating multiple users as a virtual distributed antenna, not only helps combat fading but also provides significant advantage in terms of energy consumption. The proposed efficient multiple relay selection uses the concept of the distributed Alamouti scheme in a time varying environment to realize cooperative networking in wireless relay networks and provides the platform for outage, Diversiy-Multiplexing Tradeoff (DMT) and Bit-Error-Rate (BER) analysis to conclude that it is capable of achieving promising diversity gains by operating at much lower SNR when compared with conventional relay selection methods. It also has the added advantage of conserving energy for the relays that are reachable but not selected for the cooperative communication.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

The Catlin Seaview Survey – kilometre-scale seascape assessment, and monitoring of coral reef ecosystems

1.Marine ecosystems provide critically important goods and services to society, and hence their accelerated degradation underpins an urgent need to take rapid, ambitious and informed decisions regarding their conservation and management. 2.The capacity, however, to generate the detailed field data required to inform conservation planning at appropriate scales is limited by time and resource consuming methods for collecting and analysing field data at the large scales required. 3.The ‘Catlin Seaview Survey’, described here, introduces a novel framework for large-scale monitoring of coral reefs using high-definition underwater imagery collected using customized underwater vehicles in combination with computer vision and machine learning. This enables quantitative and geo-referenced outputs of coral reef features such as habitat types, benthic composition, and structural complexity (rugosity) to be generated across multiple kilometre-scale transects with a spatial resolution ranging from 2 to 6 m2. 4.The novel application of technology described here has enormous potential to contribute to our understanding of coral reefs and associated impacts by underpinning management decisions with kilometre-scale measurements of reef health. 5.Imagery datasets from an initial survey of 500 km of seascape are freely available through an online tool called the Catlin Global Reef Record. Outputs from the image analysis using the technologies described here will be updated on the online repository as work progresses on each dataset. 6.Case studies illustrate the utility of outputs as well as their potential to link to information from remote sensing. The potential implications of the innovative technologies on marine resource management and conservation are also discussed, along with the accuracy and efficiency of the methodologies deployed.

Heartbeat and economic decisions : observing mental stress among proposers and responders in the ultimatum bargaining game

The ultimatum bargaining game (UBG), a widely used method in experimental economics, clearly demonstrates that motives other than pure monetary reward play a role in human economic decision making. In this study, we explore the behaviour and physiological reactions of both responders and proposers in an ultimatum bargaining game using heart rate variability (HRV), a small and nonintrusive technology that allows observation of both sides of an interaction in a normal experimental economics laboratory environment. We find that low offers by a proposer cause signs of mental stress in both the proposer and the responder; that is, both exhibit high ratios of low to high frequency activity in the HRV spectrum.