Resisting innovation talk in higher education teaching and learning

The exhortation to innovate is a pervasive one that occupies a central position across university mission statements, strategic plans, marketing literature and job titles. This paper locates a discourse of innovation within a history of Australian federal higher education policy, a history that may bear similarity with other national contexts. This paper names this discourse as an innovation talk that influences our teaching and learning practices, a discourse that can be reconfigured in a way that opens up the possibility for change. As such, this paper presents an analytical process used to resist taken-for-granted views of what constitutes valuable teaching practices. Suggestions for re-conceptualising how universities govern and support teaching and learning innovation are drawn from analysis of key federal policies that have influenced university practices in recent years.

Control and application of minimally-actuated underwater vehicles

Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats. With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.

Extending persistent monitoring by combining ocean models and Markov decision processes

Ocean processes are complex and have high variability in both time and space. Thus, ocean scientists must collect data over long time periods to obtain a synoptic view of ocean processes and resolve their spatiotemporal variability. One way to perform these persistent observations is to utilise an autonomous vehicle that can remain on deployment for long time periods. However, such vehicles are generally underactuated and slow moving. A challenge for persistent monitoring with these vehicles is dealing with currents while executing a prescribed path or mission. Here we present a path planning method for persistent monitoring that exploits ocean currents to increase navigational accuracy and reduce energy consumption.

Recognising the capacities of dynamic reconfiguration for the QoS assurance of running systems in concurrent and parallel environments

Recognizing the impact of reconfiguration on the QoS of running systems is especially necessary for choosing an appropriate approach to dealing with dynamic evolution of mission-critical or non-stop business systems. The rationale is that the impaired QoS caused by inappropriate use of dynamic approaches is unacceptable for such running systems. To predict in advance the impact, the challenge is two-fold. First, a unified benchmark is necessary to expose QoS problems of existing dynamic approaches. Second, an abstract representation is necessary to provide a basis for modeling and comparing the QoS of existing and new dynamic reconfiguration approaches. Our previous work [8] has successfully evaluated the QoS assurance capabilities of existing dynamic approaches and provided guidance of appropriate use of particular approaches. This paper reinvestigates our evaluations, extending them into concurrent and parallel environments by abstracting hardware and software conditions to design an evaluation context. We report the new evaluation results and conclude with updated impact analysis and guidance.

Embedding human expert cognition and real-time trajectory planning in autonomous UAS

This thesis presents a new approach to compute and optimize feasible three dimensional (3D) flight trajectories using aspects of Human Decision Making (HDM) strategies, for fixed wing Unmanned Aircraft (UA) operating in low altitude environments in the presence of real time planning deadlines. The underlying trajectory generation strategy involves the application of Manoeuvre Automaton (MA) theory to create sets of candidate flight manoeuvres which implicitly incorporate platform dynamic constraints. Feasible trajectories are formed through the concatenation of predefined flight manoeuvres in an optimized manner. During typical UAS operations, multiple objectives may exist, therefore the use of multi-objective optimization can potentially allow for convergence to a solution which better reflects overall mission requirements and HDM preferences. A GUI interface was developed to allow for knowledge capture from a human expert during simulated mission scenarios. The expert decision data captured is converted into value functions and corresponding criteria weightings using UTilite Additive (UTA) theory. The inclusion of preferences elicited from HDM decision data within an Automated Decision System (ADS) allows for the generation of trajectories which more closely represent the candidate HDM’s decision strategies. A novel Computationally Adaptive Trajectory Decision optimization System (CATDS) has been developed and implemented in simulation to dynamically manage, calculate and schedule system execution parameters to ensure that the trajectory solution search can generate a feasible solution, if one exists, within a given length of time. The inclusion of the CATDS potentially increases overall mission efficiency and may allow for the implementation of the system on different UAS platforms with varying onboard computational capabilities. These approaches have been demonstrated in simulation using a fixed wing UAS operating in low altitude environments with obstacles present.

An investigation on the accuracy of regional ocean models through field trials

Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

Multiuser virtual safety training system for tower crane dismantlement

Tower crane dismantling is one of the most dangerous activities in the construction industry. Tower crane erection and dismantlement causes 10–12% of the fatalities of all crane accidents. The nature of the task is such that off-the-job training is not practicable, and the knowledge and expertise needed has to be gained on the job. However, virtual trainers such as Microsoft Flight Simulator for airplane pilots and mission rehearsal exercise (MRE) for army personnel have been developed and are known to provide a highly successful means of overcoming the risks involved in such on-the-job learning and clearly have potential in construction situations. This paper describes the newly developed multiuser virtual safety training system (MVSTS) aimed at providing a similar learning environment for those involved in tower crane dismantlement. The proposed training system is developed by modifying an existing game engine. Within the close-to-reality virtual environment, trainees can participate in a virtual dismantling process. During the process, they learn the correct dismantling procedure and working location and to cooperate with other trainees by virtually dismantling the crane. The system allows the trainees to experience the complete procedure in a risk-free environment. A case study is provided to demonstrate how the system works and its practical application. The proposed system was evaluated by interviews with 30 construction experts with different backgrounds, divided into three groups according to their experience and trained by the traditional and virtual methods, respectively. The results indicate that the trainees of the proposed system generally learned better than those using the traditional method. The ratings also indicate that the system generally has great potential as a training platform.

Spot the differences in traditional and social entrepreneurial intention : highlighting the role of human and social capital

There is general agreement in the scientific community that entrepreneurship plays a central role in the growth and development of an economy in rapidly changing environments (Acs & Virgill 2010). In particular, when business activities are regarded as a vehicle for sustainable growth at large, that goes beyond mere economic returns of singular entities, encompassing also social problems and heavily relying on collaborative actions, then we more precisely fall into the domain of ‘social entrepreneurship’(Robinson et al. 2009). In the entrepreneurship literature, prior studies demonstrated the role of intentionality as the best predictor of planned behavior (Ajzen 1991), and assumed that the intention to start a business derives from the perception of desirability and feasibility and from a propensity to act upon an opportunity (Fishbein & Ajzen 1975). Recognizing that starting a business is an intentional act (Krueger et al. 2000) and entrepreneurship is a planned behaviour (Katz & Gartner 1988), models of entrepreneurial intentions have substantial implications for intentionality research in entrepreneurship. The purpose of this paper is to explore the emerging practice of social entrepreneurship by comparing the determinants of entrepreneurial intention in general versus those leading to startups with a social mission. Social entrepreneurial intentions clearly merit to be investigated given that the opportunity identification process is an intentional process not only typical of for profit start-ups, and yet there is a lack of research examining opportunity recognition in social entrepreneurship (Haugh 2005). The key argument is that intentionality in both traditional and social entrepreneurs during the decision-making process of new venture creation is influenced by an individual's perceptions toward opportunities (Fishbein & Ajzen 1975). Besides opportunity recognition, at least two other aspects can substantially influence intentionality: human and social capital (Davidsson, 2003). This paper is set to establish if and to what extent the social intentions of potential entrepreneurs, at the cognitive level, are influenced by opportunities recognition, human capital, and social capital. By applying established theoretical constructs, the paper draws comparisons between ‘for-profit’ and ‘social’ intentionality using two samples of students enrolled in Economy and Business Administration at the University G. d’Annunzio in Pescara, Italy. A questionnaire was submitted to 310 potential entrepreneurs to test the robustness of the model. The collected data were used to measure the theoretical constructs of the paper. Reliability of the multi-item scale for each dimension was measured using Cronbach alpha, and for all the dimensions measures of reliability are above 0.70. We empirically tested the model using structural equation modeling with AMOS. The results allow us to empirically contribute to the argument regarding the influence of human and social cognitive capital on social and non-social entrepreneurial intentions. Moreover, we highlight the importance for further researchers to look deeper into the determinants of traditional and social entrepreneurial intention so that governments can one day define better polices and regulations that promote sustainable businesses with a social imprint, rather than inhibit their formation and growth.

Social innovation and social enterprise : evidence from Australia

‘Social innovation’ is a construct increasingly used to explain the practices, processes and actors through which sustained positive transformation occurs in the network society (Mulgan, G., Tucker, S., Ali, R., Sander, B. (2007). Social innovation: What it is, why it matters and how can it be accelerated. Oxford:Skoll Centre for Social Entrepreneurship; Phills, J. A., Deiglmeier, K., & Miller, D. T. Stanford Social Innovation Review, 6(4):34–43, 2008.). Social innovation has been defined as a “novel solution to a social problem that is more effective, efficient, sustainable, or just than existing solutions, and for which the value created accrues primarily to society as a whole rather than private individuals.” (Phills,J. A., Deiglmeier, K., & Miller, D. T. Stanford Social Innovation Review, 6 (4):34–43, 2008: 34.) Emergent ideas of social innovation challenge some traditional understandings of the nature and role of the Third Sector, as well as shining a light on those enterprises within the social economy that configure resources in novel ways. In this context, social enterprises – which provide a social or community benefit and trade to fulfil their mission – have attracted considerable policy attention as one source of social innovation within a wider field of action (see Leadbeater, C. (2007). ‘Social enterprise and social innovation: Strategies for the next 10 years’, Cabinet office,Office of the third sector http://www.charlesleadbeater.net/cms xstandard/social_enterprise_innovation.pdf. Last accessed 19/5/2011.). And yet, while social enterprise seems to have gained some symbolic traction in society, there is to date relatively limited evidence of its real world impacts.(Dart, R. Not for Profit Management and Leadership, 14(4):411–424, 2004.) In other words, we do not know much about the social innovation capabilities and effects of social enterprise. In this chapter, we consider the social innovation practices of social enterprise, drawing on Mulgan, G., Tucker, S., Ali, R., Sander, B. (2007). Social innovation: What it is, why it matters and how can it be accelerated. Oxford: Skoll Centre for Social Entrepreneurship: 5) three dimensions of social innovation: new combinations or hybrids of existing elements; cutting across organisational, sectoral and disciplinary boundaries; and leaving behind compelling new relationships. Based on a detailed survey of 365 Australian social enterprises, we examine their self-reported business and mission-related innovations, the ways in which they configure and access resources and the practices through which they diffuse innovation in support of their mission. We then consider how these findings inform our understanding of the social innovation capabilities and effects of social enterprise,and their implications for public policy development.

Key priorities for Australian infection control : summary of findings from the launch of the Centre for Research Excellence in Reducing Healthcare Associated Infections

The launch of the Centre of Research Excellence in Reducing Healthcare Associated Infection (CRE-RHAI) took place in Sydney on Friday 12 October 2012. The mission of the CRE-RHAI is to generate new knowledge about strategies to reduce healthcare associated infections and to provide data on the cost-effectiveness of infection control programs. As well as launching the CRE-RHAI, an important part of this event was a stakeholder Consultation Workshop, which brought together several experts in the Australian infection control community. The aims of this workshop were to establish the research and clinical priorities in Australian infection control, assess the importance of various multi-resistant organisms, and to gather information about decision making in infection control. We present here a summary and discussion of the responses we received.

An evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles with tactical and kinematic constraints

This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.

Fostering wellbeing of immigrants and refugees? Evaluating the outcomes of work integration social enterprise

Work integration social enterprises (WISE) seek to create employment and pathways to employment for those highly disadvantaged in the labour market. This chapter examines the effects of WISE on the wellbeing of immigrants and refugees experiencing multiple barriers to economic and social participation. Drawing on an evaluation of a programme that supports seven such enterprises in the Australian state of Victoria, the effects of involvement for individual participants and their communities are examined. The study finds that this social enterprise model affords unique local opportunities for economic and social participation for groups experiencing significant barriers to meaningful employment. These opportunities have a positive impact on individual and community-level wellbeing. However, the financial costs of the model are high relative to other employment programmes, which is consistent with international findings on intermediate labour market programmes. The productivity costs of WISE are also disproportionately high compared to private sector competitors in some industries. This raises considerable dilemmas for social enterprise operators seeking to produce social value and achieve business sustainability while bearing high productivity costs to fulfil their mission. Further, the evaluation illuminates an ongoing need to address the systemic and structural drivers of health and labour market inequalities that characterize socio-economic participation for immigrants and refugees.

SERS substrate for detection of explosives

A novel gold coated femtosecond laser nanostructured sapphire surface – an “optical nose” - based on surface-enhanced Raman spectroscopy (SERS) for detecting vapours of explosive substances was investigated. Four different nitroaromatic vapours at room temperature were tested. Sensor responses were unambiguous and showed response in the range of 0.05 – 15 uM at 25 °C. The laser fabricated substrate nanostructures produced up to an eight-fold increase in Raman signal over that observed on the unstructured portions of the substrate. This work demonstrates a simple sensing system that is compatible with commercial manufacturing practices to detect taggants in explosives which can undertake as part of an integrated security or investigative mission.

Key distribution mechanisms for wireless sensor networks : a survey

Advances in technology introduce new application areas for sensor networks. Foreseeable wide deployment of mission critical sensor networks creates concerns on security issues. Security of large scale densely deployed and infrastructure less wireless networks of resource limited sensor nodes requires efficient key distribution and management mechanisms. We consider distributed and hierarchical wireless sensor networks where unicast, multicast and broadcast type of communications can take place. We evaluate deterministic, probabilistic and hybrid type of key pre-distribution and dynamic key generation algorithms for distributing pair-wise, group-wise and network-wise keys.

Embedding human expert cognition into autonomous UAS trajectory planning

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.