The graduate attributes we've overlooked : enhancing graduate employability through career management skills

Recent shifts in education and labour market policy have resulted in universities being placed under increasing pressure to produce employable graduates. However, contention exists regarding exactly what constitutes employability and which graduate attributes are required to foster employability in tertiary students. This paper argues that in the context of a rapidly changing information- and knowledge-intensive economy, employability involves far more than possession of the generic skills listed by graduate employers as attractive. Rather, for optimal economic and social outcomes, graduates must be able to proactively navigate the world of work and self-manage the career building process. A model of desirable graduate attributes that acknowledges the importance of self-management and career building skills to lifelong career management and enhanced employability is presented. Some important considerations for the implementation of effective university career management programs are then outlined.

Open standards-based system integration for asset management decision support

Over the last decade, system integration has grown in popularity as it allows organisations to streamline business processes. Traditionally, system integration has been conducted through point-to-point solutions – as a new integration scenario requirement arises, a custom solution is built between the relevant systems. Bus-based solutions are now preferred, whereby all systems communicate via an intermediary system such as an enterprise service bus, using a common data exchange model. This research investigates the use of a common data exchange model based on open standards, specifically MIMOSA OSA-EAI, for asset management system integration. A case study is conducted that involves the integration of processes between a SCADA, maintenance decision support and work management system. A diverse number of software platforms are employed in developing the final solution, all tied together through MIMOSA OSA-EAI-based XML web services. The lessons learned from the exercise are presented throughout the paper.

Power management and power flow control with back-to-back converters in a utility connected microgrid

This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

Abandoned object detection using multi-layer motion detection

Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.

Object tracking using multiple motion modalities

This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of multiple modes within the object detection stage. Consequently, different categories of objects, within motion or stationary, can be effectively detected utilising either optical flow, static foreground or active foreground information. The proposed system is evaluated using the ETISEO database and evaluation metrics and compared to a baseline system utilising a single mode foreground segmentation technique. Results demonstrate a significant improvement in tracking results can be made through the incorporation of the additional motion information.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Inertial motion capture and live performance (with a focus on dance)

3D Motion capture is a fast evolving field and recent inertial technology may expand the artistic possibilities for its use in live performance. Inertial motion capture has three attributes that make it suitable for use with live performance; it is portable, easy to use and can operate in real-time. Using four projects, this paper discusses the suitability of inertial motion capture to live performance with a particular emphasis on dance. Dance is an artistic application of human movement and motion capture is the means to record human movement as digital data. As such, dance is clearly a field in which the use of real-time motion capture is likely to become more common, particularly as projected visual effects including real-time video are already often used in dance performances. Understandably, animation generated in real-time using motion capture is not as extensive or as clean as the highly mediated animation used in movies and games, but the quality is still impressive and the ‘liveness’ of the animation has compensating features that offer new ways of communicating with an audience.

Unmanned Aerial Vehicles UAVs attitude, height, motion estimation and control using visual systems

This paper presents an implementation of an aircraft pose and motion estimator using visual systems as the principal sensor for controlling an Unmanned Aerial Vehicle (UAV) or as a redundant system for an Inertial Measure Unit (IMU) and gyros sensors. First, we explore the applications of the unified theory for central catadioptric cameras for attitude and heading estimation, explaining how the skyline is projected on the catadioptric image and how it is segmented and used to calculate the UAV’s attitude. Then we use appearance images to obtain a visual compass, and we calculate the relative rotation and heading of the aerial vehicle. Additionally, we show the use of a stereo system to calculate the aircraft height and to measure the UAV’s motion. Finally, we present a visual tracking system based on Fuzzy controllers working in both a UAV and a camera pan and tilt platform. Every part is tested using the UAV COLIBRI platform to validate the different approaches, which include comparison of the estimated data with the inertial values measured onboard the helicopter platform and the validation of the tracking schemes on real flights.

Accurate silhouette segmentation using motion detection and graph cuts

Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.

Evaluation of aerial remote sensing techniques for vegetation management in power line corridors

The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

Examining the role of human resource management in continuous improvement

The objective of this paper is to take a first step in developing a theoretical framework describing the role of HRM in successful CI, based on the current literature from both fields. To this end, elements from the CI Maturity Model and a framework depicting the role of HRM in innovation serve as a foundation for examining how specific bundles of HRM practices utilised during different phases of the CI implementation process may contribute to sustained organisational and enhanced operational performance. The primary contribution of this paper is theoretical; however, the framework has practical value in that it suggests important relationships between HRM practices and behaviours necessary for successful CI. A preliminary test of the framework in an empirical setting is summarised at the conclusion of this paper, where a number of possible research avenues are also suggested.

The intra-aortic balloon pump in heart failure management : implications for nursing practice

Management of acute heart failure is an important consideration in critical care. Mechanical support of the failing heart is crucial for improving health outcomes. The most common Australasian application of intraaortic balloon counterpulsation (IABP) is in the setting of cardiogenic shock. High end users of IABP (>37/annum) demonstrate significantly lower mortality for cardiogenic shock managed with IABP (p <0.001) in contrast to hospitals which employ limited IABP (<4/annum). This underscores the importance of proficiency in managing patient receiving IABP support. Nurses play a crucial role in carding for patients with acute heart failure. This paper summarises care considerations for management of the IABP.