Holding cost model for Greenfield Housing developments

Presentation provided to a PhD Colloquium between two Australian and one Malaysian University providing the opportunity to inform and critique progress of students concerning their selected topic. This presentation essentially involves "The conceptualisation, sensitivity and measurement of holding costs and other selected elements impacting housing affordability" as provided by Gary Owen Garner of QUT, with research objectives thus: 1. To establish the nature and composition of holding costs over time, as related to residential property in Australia, and internationally. 2. To examine the linkages that may exist between various planning instruments, the length of regulatory assessment periods, and housing affordability. 3. To develop a model that quantifies the impact of holding costs on housing affordability in Australia, with a particular focus on the consequences of extended assessment periods as a component of holding costs. Thus, provide clarification as to the impact of holding costs on overall housing affordability.

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.

Composite load model decomposition : induction motor contribution

In this thesis, a new technique has been developed for determining the composition of a collection of loads including induction motors. The application would be to provide a representation of the dynamic electrical load of Brisbane so that the ability of the power system to survive a given fault can be predicted. Most of the work on load modelling to date has been on post disturbance analysis, not on continuous on-line models for loads. The post disturbance methods are unsuitable for load modelling where the aim is to determine the control action or a safety margin for a specific disturbance. This thesis is based on on-line load models. Dr. Tania Parveen considers 10 induction motors with different power ratings, inertia and torque damping constants to validate the approach, and their composite models are developed with different percentage contributions for each motor. This thesis also shows how measurements of a composite load respond to normal power system variations and this information can be used to continuously decompose the load continuously and to characterize regarding the load into different sizes and amounts of motor loads.

Approach to developing a 3D conceptual hydrogeology model, in a system with multiple bore logs, Howard East, Darwin, using in-house software (GVS)

The Howard East rural area has experienced a rapid growth of small block subdivisions and horticulture over the last 40 years, which has been based on groundwater supply. Early bores in the area provide part of the water supply for Darwin City and are maintained and monitored by NT Power & Water Corporation. The Territory government (NRETAS) has established a monitoring network, and now 48 bores are monitored. However, in the area there are over 2700 private bores that are unregulated.Although NRETAS has both FDM and FEM simulations for the region, community support for potential regulation is sought. To improve stakeholder understanding of the resource QUT was retained by the TRaCKconsortium to develop a 3D visualisation of the groundwater system.

The applicability of biased estimation in model and model order selection

Biased estimation has the advantage of reducing the mean squared error (MSE) of an estimator. The question of interest is how biased estimation affects model selection. In this paper, we introduce biased estimation to a range of model selection criteria. Specifically, we analyze the performance of the minimum description length (MDL) criterion based on biased and unbiased estimation and compare it against modern model selection criteria such as Kay's conditional model order estimator (CME), the bootstrap and the more recently proposed hook-and-loop resampling based model selection. The advantages and limitations of the considered techniques are discussed. The results indicate that, in some cases, biased estimators can slightly improve the selection of the correct model. We also give an example for which the CME with an unbiased estimator fails, but could regain its power when a biased estimator is used.

Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Image synthesis based on a model of human vision

Modern computer graphics systems are able to construct renderings of such high quality that viewers are deceived into regarding the images as coming from a photographic source. Large amounts of computing resources are expended in this rendering process, using complex mathematical models of lighting and shading. However, psychophysical experiments have revealed that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these visually important regions contain low-level visual feature differences that attract the attention of the viewer. This thesis will present a new approach to image synthesis that exploits these experimental findings by modulating the spatial quality of image regions by their visual importance. Efficiency gains are therefore reaped, without sacrificing much of the perceived quality of the image. Two tasks must be undertaken to achieve this goal. Firstly, the design of an appropriate region-based model of visual importance, and secondly, the modification of progressive rendering techniques to effect an importance-based rendering approach. A rule-based fuzzy logic model is presented that computes, using spatial feature differences, the relative visual importance of regions in an image. This model improves upon previous work by incorporating threshold effects induced by global feature difference distributions and by using texture concentration measures. A modified approach to progressive ray-tracing is also presented. This new approach uses the visual importance model to guide the progressive refinement of an image. In addition, this concept of visual importance has been incorporated into supersampling, texture mapping and computer animation techniques. Experimental results are presented, illustrating the efficiency gains reaped from using this method of progressive rendering. This visual importance-based rendering approach is expected to have applications in the entertainment industry, where image fidelity may be sacrificed for efficiency purposes, as long as the overall visual impression of the scene is maintained. Different aspects of the approach should find many other applications in image compression, image retrieval, progressive data transmission and active robotic vision.

In-vehicle avatars to elicit social response and change driving behaviour

Social and psychological theories have provided a plethora of evidence showing that the physical difficulty to express appropriate social interactions between drivers expresses itself in aggression, selfish driving and anti-social behaviour. Therefore there is a need to improve interactions between drivers and allow clearer collective decision making between them. Personal characteristics and the driving situations play strong roles in driver’s aggression. Our approach is centered around the driving situation as opposed to focusing on personality characteristics. It examines aggression and manipulates contextual variables such as driver’s eye contact exchanges. This paper presents a new unobtrusive in-vehicle system that aims at communicating drivers’ intentions, elicit social responses and increasing mutual awareness. It uses eye gaze as a social cue to affect collective decision making with the view to contribute to safe driving. The authors used a driving simulator to design a case control experiment in which eye gaze movements are conveyed with an avatar. Participants were asked to drive through different types of intersections. An avatar representing the head of the other driver was displayed and driver behaviour was analysed. Significant eye gaze pattern difference where observed when an avatar was displayed. Drivers cautiously refer to the avatar when information is required on the intention of others (e.g. when they do not have the right of way). The majority of participants reported the perception of “being looked at”. The number of glances and time spent gazing at the avatar did not indicate an unsafe distraction by standards of in-vehicle device ergonomic design. Avatars were visually consulted primarily in less demanding driving situations, which underlines their non-distractive nature.

An administrative model for UCON

UCON is an emerging access control framework that lacks an administration model. In this paper we define the problem of administration and propose a novel administrative model. At the core of this model is the concept of attribute, which is also the central component of UCON. In our model, attributes are created by the assertions of subjects, which ascribe properties/rights to other subjects or objects. Through such a treatment of attributes, administration capabilities can be delegated from one subject to another and as a consequence UCON is improved in three aspects. First, immutable attributes that are currently considered as external to the model can be incorporated and thereby treated as mutable at- tributes. Second, the current arbitrary categorisation of users (as modifiers of attributes), to system and administrator can be removed. Attributes and objects are only modifiable by those who possess administration capability over them. Third, the delegation of administration over objects and properties that is not currently expressible in UCON is made possible.

A model for computer profiling

This paper discusses the use of models in automatic computer forensic analysis, and proposes and elaborates on a novel model for use in computer profiling, the computer profiling object model. The computer profiling object model is an information model which models a computer as objects with various attributes and inter-relationships. These together provide the information necessary for a human investigator or an automated reasoning engine to make judgements as to the probable usage and evidentiary value of a computer system. The computer profiling object model can be implemented so as to support automated analysis to provide an investigator with the information needed to decide whether manual analysis is required.

Enhancing in vivo vascularized bone formation by cobalt chloride-treated bone marrow stromal cells in a tissue engineered periosteum model

The periosteum plays an indispensable role in both bone formation and bone defect healing. In this study we constructed an artificial in vitro periosteum by incorporating osteogenic differentiated bone marrow stromal cells (BMSCs) and cobalt chloride (CoCl(2))-treated BMSCs. The engineered periostea were implanted both subcutaneously and into skull bone defects in SCID mice to investigate ectopic and orthotopic osteogenesis and vascularization. After two weeks in subcutaneous and four weeks in bone defect areas, the implanted constructs were assessed for ectopic and orthotopic osteogenesis and vascularization by micro-CT, histomorphometrical and immunohistochemical methods. The results showed that CoCl(2) pre-treated BMSCs induced higher degree of vascularization and enhanced osteogenesis within the implants in both ectopic and orthotopic areas. This study provided a novel approach using BMSCs sourced from the same patient for both osteogenic and pro-angiogenic purposes in constructing tissue engineered periosteum to enhance vascularized osteogenesis.

Towards a model of understanding strategic decision-making in micro-firms : exploring the Australian information technology sector

This study explores strategic decision-making (SDM) in micro-firms, an economically significant business subsector. As extant large- and small-firm literature currently proffers an incomplete characterization of SDM in very small enterprises, a multiple-case methodology was used to investigate how these firms make strategic decisions. Eleven Australian Information Technology service micro-firms participated in the study. Using an information-processing lens, the study uncovered patterns of SDM in micro-firms and derived a theoretical micro-firm SDM model. This research also identifies several implications for micro-firm management and directions for future research, contributing to the understanding of micro-firm SDM in both theory and practice.

The Revised Transactional Model (RTM) of occupational stress and coping : an improved process approach

Despite more than three decades of research, there is a limited understanding of the transactional processes of appraisal, stress and coping. This has led to calls for more focused research on the entire process that underlies these variables. To date, there remains a paucity of such research. The present study examined Lazarus and Folkman’s (1984) transactional model of stress and coping. One hundred and twenty nine Australian participants with full time employment (i.e. nurses and administration employees) were recruited. There were 49 male (age mean = 34, SD = 10.51) and 80 female (age mean = 36, SD = 10.31) participants. The analysis of three path models indicated that in addition to the original paths, which were found in Lazarus and Folkman’s transactional model (primary appraisal-->secondary appraisal-->stress-->coping), there were also direct links between primary appraisal and stress level time one and between stress level time one to stress level time two. This study has provided additional insights into the transactional process which will extend our understanding of how individuals appraise, cope and experience occupational stress.