The paradox of transparency : short-termism and the institutionalisation of Australian capital markets

As the ultimate corporate decision-makers, directors have an impact on the investment time horizons of the corporations they govern. How they make investment decisions has been profoundly influenced by the expansion of the investment chain and the increasing concentration of share ownership in institutional hands. By examining agency in light of legal theory, we highlight that the board is in fact sui generis and not an agent of shareholders. Consequently, transparency can lead to directors being 'captured' by institutional investor objectives and timeframes, potentially to the detriment of the corporation as a whole. The counter-intuitive conclusion is that transparency may, under certain conditions, undermine good corporate governance and lead to excessive short-termism.

Transforming Queensland VET : Challenges and Opportunities (Volume 1)

The volume is a collection of papers that address issues associated with change in the delivery of VET programs in Queensland, foreshadowed by the release of The Queensland Skill Plan in 2006. Issues that relate to the implementation of the Actions identified in the Queensland Skills Plan are the focus of the collection. In particular, the incorporation of Information Communication Technologies (ICTs) and e-learning approaches in the delivery of training packages is a key topic, how such change can be managed in the delivery of training programs, as well as broader professional development issues for VET practitioners. Change at an organisational level is the focus of two papers. Lyn Ambrose uses ideas from Diffusion of Innovations Theory to consider how the adoption eLearning in a TAFE community can be addressed. The paper by Susan Todhunter also discusses the organisational challenges in change initiatives in TAFE Institutes. Specific issues related to in the professional development of VET teachers are the focus of the papers by Mary Campbell, Sharon Altena, and Judy Gronold. Mary Campbell discusses the importance of building staff capabilities within the TAFE system and how this might be managed. Sharon Altena considers how professional development programs are currently delivered and how new approaches to professional development for TAFE teachers are needed to ensure changes can be sustained in teaching practice. The paper by Judy Gronold takes up a specific challenge for VET practitioners in the Queensland Skills Plan. She addresses issues related to embedding employability skills into training delivery in order to address industries’ need for flexible, multi-skilled productive workers. Mark Driver discusses the issues resulting from increased number of mature-aged learners in VET programs and how this change in the demographic profile of students presents challenges to the VET system. In the paper by David McKee, implications in the incorporation of ICTs into trade training are discussed and the need for effective change management strategies to ensure a smooth transition to new ways of delivering trade training. Finally, in the paper by David Roberts, the potential of Problem-Based Learning (PBL) approaches in VET training and the role of ICTs within such approaches are discussed. David uses horticulture training as an example to discuss the issues in implementing PBL effectively in VET programs. These papers were completed by the authors as a part of their postgraduate studies at QUT. The views reported are those of the authors and should not be attributed to the Queensland Department of Education, Training and the Arts.

Unstructured strategic decision-making processes : CRE decision-making in the Italian consulting industry

This thesis aims at developing a better understanding of unstructured strategic decision making processes and the conditions for achieving successful decision outcomes. Specifically it focuses on the processes used to make CRE (Corporate Real Estate) decisions. The starting point for this thesis is that our knowledge of such processes is incomplete. A comprehensive study of the most recent CRE literature together with Behavioural Organization Theory has provided a research framework for the exploration of CRE recommended =best practice‘, and of how organizational variables impact on and shape these practices. To reveal the fundamental differences between CRE decision-making in practice and the prescriptive =best practice‘ advocated in the CRE literature, a study of seven Italian management consulting firms was undertaken addressing the aspects of content and process of decisions. This thesis makes its primary contribution by identifying the importance and difficulty of finding the right balance between problem complexity, process richness and cohesion to ensure a decision-making process that is sufficiently rich and yet quick enough to deliver a prompt outcome. While doing so, this research also provides more empirical evidence to some of the most established theories of decision-making while reinterpreting their mono-dimensional arguments in a multi-dimensional model of successful decision-making.

Rover autonomous integrity monitoring of GNSS RTK positioning solutions with multi-constellations

This paper studies receiver autonomous integrity monitoring (RAIM) algorithms and performance benefits of RTK solutions with multiple-constellations. The proposed method is generally known as Multi-constellation RAIM -McRAIM. The McRAIM algorithms take advantage of the ambiguity invariant character to assist fast identification of multiple satellite faults in the context of multiple constellations, and then detect faulty satellites in the follow-up ambiguity search and position estimation processes. The concept of Virtual Galileo Constellation (VGC) is used to generate useful data sets of dual-constellations for performance analysis. Experimental results from a 24-h data set demonstrate that with GPS&VGC constellations, McRAIM can significantly enhance the detection and exclusion probabilities of two simultaneous faulty satellites in RTK solutions.

Cross voltage control with inner hysteresis current control for multi-output boost converter

Multi-output boost (MOB) converter is a novel DC-DC converter unlike the regular boost converter, has the ability to share its total output voltage and to have different series output voltage from a given duty cycle for low and high power applications. In this paper, discrete voltage control with inner hysteresis current control loop has been proposed to keep the simplicity of the control law for the double-output MOB converter, which can be implemented by a combination of analogue and logical ICs or simple microcontroller to constrain the output voltages of MOB converter at their reference voltages against variation in load or input voltage. The salient features of the proposed control strategy are simplicity of implementation and ease to extend to multiple outputs in the MOB converter. Simulation and experimental results are presented to show the validity of control strategy.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

Multi-output DC-DC converters based on diode-clamped converters configuration : topology and control strategy

This paper presents a new DC-DC Multi-Output Boost (MOB) converter which can share its total output between different series of output voltages for low and high power applications. This configuration can be utilised instead of several single output power supplies. This is a compatible topology for a diode-clamed inverter in the grid connection systems, where boosting low rectified output-voltage and series DC link capacitors is required. To verify the proposed topology, steady state and dynamic analysis of a MOB converter are examined. A simple control strategy has been proposed to demonstrate the performance of the proposed topology for a double-output boost converter. The topology and its control strategy can easily be extended to offer multiple outputs. Simulation and experimental results are presented to show the validity of the control strategy for the proposed converter.

Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

Robust real time multi-layer foreground segmentation

Many surveillance applications (object tracking, abandoned object detection) rely on detecting changes in a scene. Foreground segmentation is an effective way to extract the foreground from the scene, but these techniques cannot discriminate between objects that have temporarily stopped and those that are moving. We propose a series of modifications to an existing foreground segmentation system\cite{Butler2003} so that the foreground is further segmented into two or more layers. This yields an active layer of objects currently in motion and a passive layer of objects that have temporarily ceased motion which can itself be decomposed into multiple static layers. We also propose a variable threshold to cope with variable illumination, a feedback mechanism that allows an external process (i.e. surveillance system) to alter the motion detectors state, and a lighting compensation process and a shadow detector to reduce errors caused by lighting inconsistencies. The technique is demonstrated using outdoor surveillance footage, and is shown to be able to effectively deal with real world lighting conditions and overlapping objects.

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.

Multi-sensor tracking using a scalable condensation filter

Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.