Regulating roles of the use of the balanced scorecard in shaping corporate identities

The literature on corporate identity management suggests that managing corporate identity is a strategically complex task embracing the shaping of a range of dimensions of organisational life. The performance measurement literature and its applications likewise now also emphasise organisational ability to incorporate various dimensions considering both financial and non-financial performance measures when assessing success. The inclusion of these soft non-financial measures challenges organisations to quantify intangible aspects of performance such as corporate identity, transforming unmeasurables into measurables. This paper explores the regulatory roles of the use of the balanced scorecard in shaping key dimensions of corporate identities in a public sector shared service provider in Australia. This case study employs qualitative interviews of senior managers and employees, secondary data and participant observation. The findings suggest that the use of the balanced scorecard has potential to support identity construction, as an organisational symbol, a communication tool of vision, and as strategy, through creating conversations that self-regulate behaviour. The development of an integrated performance measurement system, the balanced scorecard, becomes an expression of a desired corporate identity, and the performance measures and continuous process provide the resource for interpreting actual corporate identities. Through this process of understanding and mobilising the interaction, it may be possible to create a less obtrusive and more subtle way to control “what an organisation is”. This case study also suggests that the theoretical and practical fusion of the disciplinary knowledge around corporate identities and performance measurement systems could make a contribution to understanding and shaping corporate identities.

The Smart Skies Project

Smart Skies is an international research project exploring the development and demonstration of future aviation technologies which facilitate the more efficient utilisation of airspace for both manned and unmanned aircraft. These technologies include autonomous vision-based collision avoidance systems, autonomous airspace separation management systems and a mobile ground-based radar system to support non-segregated UAS operations within the NAS. This presentation will provide an introduction to the key programs of research, detail results from recent flight trial activities and will outline future directions for the project.

Automatic Detection of Marine Mammal from Aerial Imagery

The following technical report describes the approach and algorithm used to detect marine mammals from aerial imagery taken from manned/unmanned platform. The aim is to automate the process of counting the population of dugongs and other mammals. We have developed and algorithm that automatically presents to a user a number of possible candidates of these mammals. We tested the algorithm in two distinct datasets taken from different altitudes. Analysis and discussion is presented in regards with the complexity of the input datasets, the detection performance.

Evaluation of separation management algorithms in Class G airspace

Use of Unmanned Aerial Vehicles (UAVs) in support of government applications has already seen significant growth and the potential for use of UAVs in commercial applications is expected to rapidly expand in the near future. However, the issue remains on how such automated or operator-controlled aircraft can be safely integrated into current airspace. If the goal of integration is to be realized, issues regarding safe separation in densely populated airspace must be investigated. This paper investigates automated separation management concepts in uncontrolled airspace that may help prepare for an expected growth of UAVs in Class G airspace. Not only are such investigations helpful for the UAV integration issue, the automated separation management concepts investigated by the authors can also be useful for the development of new or improved Air Traffic Control services in remote regions without any existing infrastructure. The paper will also provide an overview of the Smart Skies program and discuss the corresponding Smart Skies research and development effort to evaluate aircraft separation management algorithms using simulations involving realworld data communication channels, and verified against actual flight trials. This paper presents results from a unique flight test concept that uses real-time flight test data from Australia over existing commercial communication channels to a control center in Seattle for real-time separation management of actual and simulated aircraft. The paper also assesses the performance of an automated aircraft separation manager.

ARCS collaboration tools

The Australian Research Collaboration Service (ARCS) has been supporting a wide range of Collaboration Services and Tools which have been allowing researchers, groups and research communities to share ideas and collaborate across organisational boundaries.----- This talk will give an introduction to a number of exciting technologies which are now available. Focus will be on two main areas of Video Collaboration Tools, allowing researchers to talk face-to-face and share data in real-time, and Web Collaboration Tools, allowing researchers to share information and ideas with other like-minded researchers irrespective of distance or organisational structure. A number of examples will also be shown of how these technologies have been used with in various research communities.----- A brief introduction will be given to a number of services which ARCS is now operating and/or supporting such as:--- * EVO – A video conferencing application, which is particularly suited to desktop or low bandwidth applications.--- * AccessGrid – An open source video conferencing and collaboration tool kit, which is great for room to room meetings.--- * Sakai – An online collaboration and learning environment, support teaching and learning, ad hoc group collaboration, support for portfolios and research collaboration.--- * Plone – A ready-to-run content management system, that provides you with a system for managing web content that is ideal for project groups, communities, web sites, extranets and intranets.--- * Wikis – A way to easily create, edit, and link pages together, to create collaborative websites.

ARCS collaboration tools and support workshop

Registration fees for this workshop are being met by ARCS. There is no cost to attend; however space is limited.----- The Australian Research Collaboration Service (ARCS) has been supporting a wide range of Collaboration Services and Tools which have been allowing researchers, groups and research communities to share ideas and collaborate across organisational boundaries.----- This workshop will give an introduction into a number of web based and real-time collaboration tools and services which researchers may find useful for day-to-day collaboration with members of a research team located within an institution or across institutions. Attendees will be shown how a number of these tools work with strong emphasis placed on how these tools can help facilitate communication and collaboration. Attendees will have the opportunity to try out a number of examples themselves, and interact with the workshop staff to discuss how their own use cases could benefit from the tools and services which can be provided.----- Outline: A hands on introduction will be given to a number of services which ARCS is now operating and/or supporting such as:--- * EVO – A video conferencing environment, which is particularly suited to desktop or low bandwidth applications.--- * AccessGrid – An open source video conferencing and collaboration tool kit, which is great for room to room meetings.--- * Sakai – An online collaboration and learning environment, support teaching and learning, ad hoc group collaboration, support for portfolios and research collaboration.--- * Plone and Drupal – A ready-to-run content management system, that provides you with a system for managing web content that is ideal for project groups, communities, web sites, extranets and intranets.--- * Wikis – A way to easily create, edit, and link pages together, to create collaborative websites.

Test architecture for prototyping automated dynamic airspace control

The automation of various aspects of air traffic management has many wide-reaching benefits including: reducing the workload for Air Traffic Controllers; increasing the flexibility of operations (both civil and military) within the airspace system through facilitating automated dynamic changes to en-route flight plans; ensuring safe aircraft separation for a complex mix of airspace users within a highly complex and dynamic airspace management system architecture. These benefits accumulate to increase the efficiency and flexibility of airspace use(1). Such functions are critical for the anticipated increase in volume of manned and unmanned aircraft traffic. One significant challenge facing the advancement of airspace automation lies in convincing air traffic regulatory authorities that the level of safety achievable through the use of automation concepts is comparable to, or exceeds, the accepted safety performance of the current system.

Relative entropy rate based multiple hidden Markov Model Approximation

This paper proposes a novel relative entropy rate (RER) based approach for multiple HMM (MHMM) approximation of a class of discrete-time uncertain processes. Under different uncertainty assumptions, the model design problem is posed either as a min-max optimisation problem or stochastic minimisation problem on the RER between joint laws describing the state and output processes (rather than the more usual RER between output processes). A suitable filter is proposed for which performance results are established which bound conditional mean estimation performance and show that estimation performance improves as the RER is reduced. These filter consistency and convergence bounds are the first results characterising multiple HMM approximation performance and suggest that joint RER concepts provide a useful model selection criteria. The proposed model design process and MHMM filter are demonstrated on an important image processing dim-target detection problem.

Automating human thought processes for a UAV forced landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

Mainstreaming sustainability into pre-service teacher edcuation in Australia

There is a growing interest in and support for education for sustainability in Australian schools. Australian Government schemes such as the Australian Sustainable Schools Initiative (AuSSI), along with strategies such as Educating for a Sustainable Future: A National Environmental Education Statement for Australian Schools(NEES(Australian Government and Curriculum Corporation (2005) and Living Sustainably: The Australian Government’s National Action Plan for Education for Sustainability (Australian Government 2009), recognise the need and offer support for education for sustainability in Australian schools. The number of schools that have engaged with AuSSI indicates that this interest also exists within Australian schools. Despite this, recent research indicates that pre-service teacher education institutions and programs are not doing all they can to prepare teachers for teaching education for sustainability or for working within sustainable schools. The education of school teachers plays a vital role in achieving changes in teaching and learning in schools. Indeed, the professional development of teachers in education for sustainability has been identified as ‘the priority of priorities’. Much has been written about the need to ‘reorient teacher education towards sustainability’. Teacher education is seen as a key strategy that is yet to be effectively utilised to embed education for sustainability in schools. Mainstreaming sustainability in Australian schools will not be achieved without the preparation of teachers for this task. The Mainstreaming Sustainability model piloted in this study seeks to engage a range of stakeholder organisations and key agents of change within a system to all work simultaneously to bring about a change, such as the mainstreaming of sustainability. The model is premised on the understanding that sustainability will be mainstreamed within teacher education if there is engagement with key agents of change across the wider teacher education system and if the key agents of change are ‘deeply’ involved in making the change. The model thus seeks to marry broad engagement across a system with the active participation of stakeholders within that system. Such a systemic approach is a way of bringing together diverse viewpoints to make sense of an issue and harness that shared interpretation to define boundaries, roles and relationships leading to a better defined problem that can be acted upon more effectively. Like action research, the systemic approach is also concerned with modelling change and seeking plausible solutions through collaboration between stakeholders. This is important in ensuring that outcomes are useful to the researchers/stakeholders and the system being researched as it creates partnerships and commitments to the outcomes by stakeholder participants. The study reported on here examines whether the ‘Mainstreaming Sustainability’ model might be effective as a means to mainstream sustainability in pre-service teacher education. This model, developed in an earlier study, was piloted in the Queensland teacher education system in order to examine its effectiveness in creating organisational and systemic change. The pilot project in Queensland achieved a number of outcomes. The project: • provided useful insights into the effectiveness of the Mainstreaming Sustainability model in bringing about change while also building research capacity within the system • developed capacities within the teacher education community: o developing competencies in education for sustainability o establishing more effective interactions between decision-makers and other stakeholders o establishing a community of inquiry • changed teaching and learning approaches used in participating teacher education institutions through: o curriculum and resource development o the adoption of education for sustainability teaching and learning processes o the development of institutional policies • improved networks within the teacher education system through: o identifying key agents of change within the system o developing new, and building on existing, partnerships between schools, teacher education institutions and government agencies • engaged relevant stakeholders such as government agencies and non-government organisations to understand and support the change Our findings indicate that the Mainstreaming Sustainability model is able to facilitate organisational and systemic change – over time – if: • the individuals involved have the conceptual and personal capacities needed to facilitate change, that is, to be a key agent of change • stakeholders are engaged as participants in the process of change, not simply as ‘interested parties’ • there is a good understanding of systemic change and the opportunities for leveraging change within systems. In particular, in seeking to mainstream sustainability in pre-service teacher education in Queensland it has become clear that one needs to build capacity for change within participants such as knowledge of education for sustainability, conceptual skills in systemic thinking, action research and organisational change, and leadership skills. It is also of vital importance that key agents of change – those individuals who are ‘hubs’ within a system and can leverage for change across a wide range of the system – are identified and engaged with as early as possible. Key agents of change can only be correctly identified, however, if the project leaders and known participants have clearly identified the boundary to their system as this enables the system, sub-system and environment of the system to be understood. Through mapping the system a range of key organisations and stakeholders will be identified, including government and nongovernment organisations, teacher education students, teacher education academics, and so on. On this basis, key agents of change within the system and sub-system can be identified and invited to assist in working for change. A final insight is that it is important to have time – and if necessary the funding to ‘buy time’ – in seeking to bring about system-wide change. Seeking to bring about system-wide change is an ambitious project, one that requires a great deal of effort and time. These insights provide some considerations for those seeking to utilise the Mainstreaming Sustainability model to bring about change within and across a pre-service teacher education system.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

Fast reconstruction of aerodynamic shapes using evolutionary algorithms and virtual Nash strategies in a CFD design environment

This paper compares the performances of two different optimisation techniques for solving inverse problems; the first one deals with the Hierarchical Asynchronous Parallel Evolutionary Algorithms software (HAPEA) and the second is implemented with a game strategy named Nash-EA. The HAPEA software is based on a hierarchical topology and asynchronous parallel computation. The Nash-EA methodology is introduced as a distributed virtual game and consists of splitting the wing design variables - aerofoil sections - supervised by players optimising their own strategy. The HAPEA and Nash-EA software methodologies are applied to a single objective aerodynamic ONERA M6 wing reconstruction. Numerical results from the two approaches are compared in terms of the quality of model and computational expense and demonstrate the superiority of the distributed Nash-EA methodology in a parallel environment for a similar design quality.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.