RPAS integration within an Australian ATM system : what equipment and which airspace

The Australian Civil Aviation Safety Authority (CASA) currently lists more than 100 separate entities or organisations which maintain a UAS Operator Certificate (UOC) [1]. Approved operations are overwhelmingly a permutation of aerial photography, surveillance, survey or spotting and predominantly, are restricted to Visual Line of Sight (VLOS) operations, below 400 feet, and not within 3 NM of an aerodrome. However, demand is increasing for a Remote Piloted Aerial System (RPAS) regulatory regime which facilitates more expansive operations, in particular unsegregated, Beyond Visual Line of Sight (BVLOS) operations. Despite this demand, there is national and international apprehension regarding the necessary levels of airworthiness and operational regulation required to maintain safety and minimise the risk associated with unsegregated operations. Fundamental to addressing these legitimate concerns will be the mechanisms that underpin safe separation and collision avoidance. Whilst a large body of research has been dedicated to investigating on-board, Sense and Avoid (SAA) technology necessary to meet this challenge, this paper focuses on the contribution of the NAS to separation assurance, and how it will support, as well as complicate RPAS integration. The paper collates and presents key, but historically disparate, threads of Australian RPAS and NAS related information, and distils it with a filter focused on minimising RPAS collision risk. Our ongoing effort is motivated by the need to better understand the separation assurance contribution provided by the NAS layers, in the first instance, and subsequently employ this information to identify scenarios where the coincident collision risk is demonstrably low, providing legitimate substantiation for concessions on equipage and airworthiness standards.

Protect or deter? : the expert panel on asylum seekers in Australia

In June 2012 Prime Minister Gillard appointed an Expert Panel on Asylum Seekers to provide advice on policy options 'to prevent asylum seekers rising their lives on dangerous boat journeys to Australia'. This article examines the establishment of that Committee against the backdrop of an increasing number of boat arrivals, of deaths at sea and the failure of Government policy responses to prevent them. It examines the recommendations of the Expert Panel and considers the punitive outcome of some of these recommendations including the 'no advantage' test. It evaluates Kevin Rudd's Regional Resettlement Arrangement with Papua New Guinea and concludes that Australian and regional initiatives need to focus on protection of asylum seekers, not deterrence or avoidance of international obligations

Small firms and health and safety harmonisation : potential regulatory effects of a dominant narrative

Small firms are popularly viewed as resistant to complying with regulation. Harmonisation of Australia’s state-based work health and safety regimes is a significant regulatory change. In this article, we consider the likely responses of small firms to work health and safety harmonisation and argue that a range of choices are open to small firm owner-managers. These choices are shaped by individuals’ world views and are influenced by elements in the firms’ context. A significant element is the public narrative of work health and safety harmonisation, which can be understood by using discourse and sense-making concepts. Our analysis of small firm owner-manager choices takes into account small firms’ embeddedness in their regulatory context and the influence on organisational decision-making of the narrative of work health and safety harmonisation. The dominant narrative is arguably silent on the benefits of the work health and safety regulatory change and therefore the response of small firms is likely to be avoidance or minimalism. Non-compliance could be the result due to poor awareness of opportunities arising from this regulatory change.

Community engagement for disaster resilience : flood risk management in Jakarta, Indonesia

Understanding dynamics of interactions between community groups and government agencies is crucial to improve community resilience for flood risk reduction through effective community engagement strategies. Overall, a variety of approaches are available, however they are limited in their application. Based on research of a case study in Kampung Melayu Village in Jakarta, further complexity in engaging community emerges in planning policy which requires the relocation of households living in floodplains. This complexity arises in decision-making processes due to barriers to communication. This obstacle highlights the need for a simplified approach for an effective flood risk management which will be further explored in this paper. Qualitative analyses will be undertaken following semi-structured interviews conducted with key actors within government agencies, non-governmental organisations (NGOs), and representatives of communities. The analyses involve investigation of barriers and constraints on community engagement in flood risk management, particularly relevant to collaboration mechanism, perception of risk, and technical literacy to flood risk. These analyses result in potential redirection of community consultation strategies to lead to a more effective collaboration among stakeholders in the decision-making processes. As a result, greater effectiveness in plan implementation of flood risk management potentially improves disaster resilience in the future.

Potentiation of the early visual response to learned danger signals in adults and adolescents

The reinforcing effects of aversive outcomes on avoidance behaviour are well established. However, their influence on perceptual processes is less well explored, especially during the transition from adolescence to adulthood. Using electroencephalography, we examined whether learning to actively or passively avoid harm can modulate early visual responses in adolescents and adults. The task included two avoidance conditions, active and passive, where two different warning stimuli predicted the imminent, but avoidable, presentation of an aversive tone. To avoid the aversive outcome, participants had to learn to emit an action (active avoidance) for one of the warning stimuli and omit an action for the other (passive avoidance). Both adults and adolescents performed the task with a high degree of accuracy. For both adolescents and adults, increased N170 event-related potential amplitudes were found for both the active and the passive warning stimuli compared with control conditions. Moreover, the potentiation of the N170 to the warning stimuli was stable and long lasting. Developmental differences were also observed; adolescents showed greater potentiation of the N170 component to danger signals. These findings demonstrate, for the first time, that learned danger signals in an instrumental avoidance task can influence early visual sensory processes in both adults and adolescents.

Looming aircraft threats : shape-based passive ranging of aircraft from monocular vision

This paper proposes new techniques for aircraft shape estimation, passive ranging, and shape-adaptive hidden Markov model filtering which are suitable for a monocular vision-based non-cooperative collision avoidance system. Vision-based passive ranging is an important missing technology that could play a significant role in resolving the sense-and-avoid problem in un-manned aerial vehicles (UAVs); a barrier hindering the wider adoption of UAVs for civilian applications. The feasibility of the pro- posed shape estimation, passive ranging and shape-adaptive filtering techniques is evaluated on flight test data.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Visual predictive control of spiral motion

This paper deals with constrained image-based visual servoing of circular and conical spiral motion about an unknown object approximating a single image point feature. Effective visual control of such trajectories has many applications for small unmanned aerial vehicles, including surveillance and inspection, forced landing (homing), and collision avoidance. A spherical camera model is used to derive a novel visual-predictive controller (VPC) using stability-based design methods for general nonlinear model-predictive control. In particular, a quasi-infinite horizon visual-predictive control scheme is derived. A terminal region, which is used as a constraint in the controller structure, can be used to guide appropriate reference image features for spiral tracking with respect to nominal stability and feasibility. Robustness properties are also discussed with respect to parameter uncertainty and additive noise. A comparison with competing visual-predictive control schemes is made, and some experimental results using a small quad rotor platform are given.

Differential effects of refractive blur on day and night-time driving performance

Purpose To investigate the effect of different levels of refractive blur on real-world driving performance measured under day and nighttime conditions. Methods Participants included 12 visually normal, young adults (mean age = 25.8 ± 5.2 years) who drove an instrumented research vehicle around a 4 km closed road circuit with three different levels of binocular spherical refractive blur (+0.50 diopter sphere [DS], +1.00 DS, +2.00 DS) compared with a baseline condition. The subjects wore optimal spherocylinder correction and the additional blur lenses were mounted in modified full-field goggles; the order of testing of the blur conditions was randomized. Driving performance was assessed in two different sessions under day and nighttime conditions and included measures of road signs recognized, hazard detection and avoidance, gap detection, lane-keeping, sign recognition distance, speed, and time to complete the course. Results Refractive blur and time of day had significant effects on driving performance (P < 0.05), where increasing blur and nighttime driving reduced performance on all driving tasks except gap judgment and lane keeping. There was also a significant interaction between blur and time of day (P < 0.05), such that the effects of blur were exacerbated under nighttime driving conditions; performance differences were evident even for +0.50 DS blur relative to baseline for some measures. Conclusions The effects of blur were greatest under nighttime conditions, even for levels of binocular refractive blur as low as +0.50 DS. These results emphasize the importance of accurate and up-to-date refractive correction of even low levels of refractive error when driving at night.

Association between Australian-Indian mothers' controlling feeding practices and children's appetite traits

This cross-sectional study examined the association between controlling feeding practices and children's appetite traits. The secondary aim studied the relationship between controlling feeding practices and two proxy indicators of diet quality. Participants were 203 Australian-Indian mothers with children aged 1-5 years. Controlling feeding practices (pressure to eat, restriction, monitoring) and children's appetite traits (. food approach traits: food responsiveness, enjoyment of food, desire to drink, emotional overeating; food avoidance traits: satiety responsiveness, slowness in eating, fussiness and emotional undereating) were measured using self-reported, previously validated scales/questionnaires. Children's daily frequency of consumption of core and non-core foods was estimated using a 49-item list of foods eaten (yes/no) in the previous 24 hours as an indicator of diet quality. Higher pressure to eat was associated with higher scores for satiety responsiveness, slowness in eating, fussiness and lower score for enjoyment of food. Higher restriction was related to higher scores for food responsiveness and emotional overeating. Higher monitoring was inversely associated with fussiness, slowness in eating, food responsiveness and emotional overeating and positively associated with enjoyment of food. Pressure to eat and monitoring were related to lower number of core and non-core foods consumed in the previous 24 hours, respectively. All associations remained significant after adjusting for maternal and child covariates (n = 152 due to missing data). In conclusion, pressure to eat was associated with higher food avoidance traits and lower consumption of core foods. Restrictive feeding practices were associated with higher food approach traits. In contrast, monitoring practices were related to lower food avoidance and food approach traits and lower non-core food consumption.

Shaping safe drinking cultures : evoking positive emotion to promote moderate-drinking behaviour

Social marketing by Western governments that use fear tactics and threatening information to promote anti-drinking messages has polarized ‘binge drinking’ and ‘moderate drinking’ through a continuum that implies benefits and harms for both individuals and society. With the goal of extending insights into social marketing approaches that promote safer drinking cultures in Australia, we discuss findings from a study that examines alcohol consumers' moderate-drinking intentions. By applying the theory of planned behaviour and emotions theory, we discuss survey results from a sample of alcohol consumers, which demonstrate that positively framed value propositions that evoke happiness and love are more influential in the processing of an alcohol moderation message for alcohol consumers. The key limitations of this study are the cross-sectional nature of the data and the focal-dependent variable being behavioural intentions rather than behaviours. Research insight into the stronger influence of positive emotions on processing an alcohol moderation message establishes an important avenue for future social marketing communications that moves beyond negative, avoidance appeals to promote behaviour change in drinkers. These research findings will benefit professionals involved in developing social change campaigns that promote and reinforce consumers' positive intentions, with messages about the benefits of controlled, moderate drinking.

Coverage algorithms for an under-actuated car-like vehicle in an uncertain environment

A coverage algorithm is an algorithm that deploys a strategy as to how to cover all points in terms of a given area using some set of sensors. In the past decades a lot of research has gone into development of coverage algorithms. Initially, the focus was coverage of structured and semi-structured indoor areas, but with time and development of better sensors and introduction of GPS, the focus has turned to outdoor coverage. Due to the unstructured nature of an outdoor environment, covering an outdoor area with all its obstacles and simultaneously performing reliable localization is a difficult task. In this paper, two path planning algorithms suitable for solving outdoor coverage tasks are introduced. The algorithms take into account the kinematic constraints of an under-actuated car-like vehicle, minimize trajectory curvatures, and dynamically avoid detected obstacles in the vicinity, all in real-time. We demonstrate the performance of the coverage algorithm in the field by achieving 95% coverage using an autonomous tractor mower without the aid of any absolute localization system or constraints on the physical boundaries of the area.

The Role of the G20 in Taxation Regulation

This chapter explores the status of the current programs designed to address global tax avoidance, critiques the role that the G20 plays in the reform agenda, and considers the part that Australia will play in the process.

Teleoperation of a 7 DOF humanoid robot arm using human arm accelerations and EMG signals

We present our work on tele-operating a complex humanoid robot with the help of bio-signals collected from the operator. The frameworks (for robot vision, collision avoidance and machine learning), developed in our lab, allow for a safe interaction with the environment, when combined. This even works with noisy control signals, such as, the operator’s hand acceleration and their electromyography (EMG) signals. These bio-signals are used to execute equivalent actions (such as, reaching and grasping of objects) on the 7 DOF arm.

Measuring corruption in public construction projects in China

Corruption has been identified as the greatest obstacle to economic and social development. Public construction projects, in particular, face high corruption risk as public construction sector has been consecutively deemed as the most corrupt one. Despite considerable efforts have been undertaken to measure corruption at a nation level, few focus on the measurement of corruption in construction projects. This paper develops a fuzzy measurement model for the potential corruption in public construction projects in China. Through semi-structured interviews with 14 experts, followed by a questionnaire survey with 188 respondents, 24 measurement items of corruption were identified and further categorized into five constructs. The fuzzy set theory was then adopted to quantify each measurement item, construct and the overall corruption level. This model can facilitate in evaluating, revealing and monitoring corruption in public construction projects. Although this study focuses on measuring corruption in public construction projects in China, similar research methods can be applied in other countries around the world and thus contribute to the global body of knowledge of corruption.