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.

A capability framework visualisation for multiple heterogeneous UAVs : from a mission commander's perspective

There is an increased interested in Uninhabited Aerial Vehicle (UAV) operations and research into advanced methods for commanding and controlling multiple heterogeneous UAVs. Research into areas of supervisory control has rapidly increased. Past research has investigated various approaches of autonomous control and operator limitation to improve mission commanders' Situation Awareness (SA) and cognitive workload. The aim of this paper is to address this challenge through a visualisation framework of UAV information constructed from Information Abstraction (IA). This paper presents the concept and process of IA, and the visualisation framework (constructed using IA), the concept associated with the Level Of Detail (LOD) indexing method, the visualisation of an example of the framework. Experiments will test the hypothesis that, the operator will be able to achieve increased SA and reduced cognitive load with the proposed framework.

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.

The effect of screen size on mission commander's situation awareness

Situation awareness lost is a common factor leading to human error in the aviation industry. However, few studies have investigated the effect on situation awareness where the control interface is a touch-screen device that supports simultaneous multi-touch input and information output. This research aims to conduct an experiment to evaluate the difference in situation awareness on a large screen device, DiamondTouch (DT107), and a small screen device, iPad, both with multi-touch interactive functions. The Interface Operation and Situation Awareness Testing Simulator (IOSATS), is a simulator to test the three basis interface operations (Search Target, Information Reading, and Change Detection) by implementing a simplified search and rescue scenario. The result of this experiment will provide reliable data for future research for improving operator's situation awareness in the avionic domain.

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.

Mission drift or strategic shift? Group formation strategies within MEPs

Microenterprise development programs (MEPs) have been recognised as a valuable way to help the poor engage in micro-businesses (Green et al., 2006; Vargas, 2000), presenting a way out of poverty (Choudhury et al., 2008; Strier, 2010). Concerns have been raised however, that the benefits of MEPs often don’t reach the extremely poor (Jones et al., 2004; Midgley, 2008; Mosley and Hulme, 1998; Nawaz, 2010; Pritchett, 2006). Balancing reach of these programs with depth is a challenging task. Targeting as many poor people as possible often results in MEPs focusing on the upper or middle poor, overlooking the most challenging group. As such, MEPs have been criticised for mission drift – losing sight of the organisation’s core purpose; assisting those more likely to succeed.

The Icelander abroad: Hjalti Skeggjason’s Swedish mission

This chapter analyses the characterization of Hjalti Skeggjason in the medieval Icelandic text Heimskringla. It argues that Hjalti is developed as an exemplary character who is able to adapt to life at the Norwegian court while exerting his own influence on how that court functions.

Hybrid game evolutionary algorithm for mission path planning of aerial survey tasks

The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Pareto-optimal solutions.

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.

Design, simulation and analysis of a parallel hybrid electric propulsion system for unmanned aerial vehicles

Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This paper presents the development of a parallel Hybrid Electric Propulsion System (HEPS) on a small fixed-wing UAV incorporating an Ideal Operating Line (IOL) control strategy. A simulation model of an UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine were determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

Multidisciplinary design and flight testing of a remote gas/particle airborne sensor system

The main objective of this paper is to describe the development of a remote sensing airborne air sampling system for Unmanned Aerial Systems (UAS) and provide the capability for the detection of particle and gas concentrations in real time over remote locations. The design of the air sampling methodology started by defining system architecture, and then by selecting and integrating each subsystem. A multifunctional air sampling instrument, with capability for simultaneous measurement of particle and gas concentrations was modified and integrated with ARCAA’s Flamingo UAS platform and communications protocols. As result of the integration process, a system capable of both real time geo-location monitoring and indexed-link sampling was obtained. Wind tunnel tests were conducted in order to evaluate the performance of the air sampling instrument in controlled nonstationary conditions at the typical operational velocities of the UAS platform. Once the remote fully operative air sampling system was obtained, the problem of mission design was analyzed through the simulation of different scenarios. Furthermore, flight tests of the complete air sampling system were then conducted to check the dynamic characteristics of the UAS with the air sampling system and to prove its capability to perform an air sampling mission following a specific flight path.