Methods to achieve net environmental gain in the course of development in Queensland

To achieve best environmental management practice in Queensland, effort needs to be extended into the private sector. A Regional Landscape Strategy compiled for any substantial new proposal must identify the most promising technique(s) (from an available tool kit of 13) by which a developer (of any type) is more likely to sustain on-site resources while assisting government deliver its future plans in any region of the State. Offsetting may prove to be one of the most effective of these tools. However, policy must address‘offset land mitigation’, whereby the necessary financial incentives are introduced. Practicable methods by which offset sites can be selected, and measurement of their consequent environmental benefit, have now been devised and tested to assist this process.

A Modified inverse integer Cholesky decorrelation method and the performance on ambiguity resolution

One of the research focuses in the integer least squares problem is the decorrelation technique to reduce the number of integer parameter search candidates and improve the efficiency of the integer parameter search method. It remains as a challenging issue for determining carrier phase ambiguities and plays a critical role in the future of GNSS high precise positioning area. Currently, there are three main decorrelation techniques being employed: the integer Gaussian decorrelation, the Lenstra–Lenstra–Lovász (LLL) algorithm and the inverse integer Cholesky decorrelation (IICD) method. Although the performance of these three state-of-the-art methods have been proved and demonstrated, there is still a potential for further improvements. To measure the performance of decorrelation techniques, the condition number is usually used as the criterion. Additionally, the number of grid points in the search space can be directly utilized as a performance measure as it denotes the size of search space. However, a smaller initial volume of the search ellipsoid does not always represent a smaller number of candidates. This research has proposed a modified inverse integer Cholesky decorrelation (MIICD) method which improves the decorrelation performance over the other three techniques. The decorrelation performance of these methods was evaluated based on the condition number of the decorrelation matrix, the number of search candidates and the initial volume of search space. Additionally, the success rate of decorrelated ambiguities was calculated for all different methods to investigate the performance of ambiguity validation. The performance of different decorrelation methods was tested and compared using both simulation and real data. The simulation experiment scenarios employ the isotropic probabilistic model using a predetermined eigenvalue and without any geometry or weighting system constraints. MIICD method outperformed other three methods with conditioning improvements over LAMBDA method by 78.33% and 81.67% without and with eigenvalue constraint respectively. The real data experiment scenarios involve both the single constellation system case and dual constellations system case. Experimental results demonstrate that by comparing with LAMBDA, MIICD method can significantly improve the efficiency of reducing the condition number by 78.65% and 97.78% in the case of single constellation and dual constellations respectively. It also shows improvements in the number of search candidate points by 98.92% and 100% in single constellation case and dual constellations case.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Grounding action in visuo-haptic space using experience networks

Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.

Inclusion of PMU current phasor measurements in a power system state estimator

Three different methods of inclusion of current measurements by phasor measurement units (PMUs) in a power sysetm state estimator is investigated. A comprehensive formulation of the hybrid state estimator incorporating conventional, as well as PMU measurements, is presented for each of the three methods. The behaviour of the elements because of the current measurements in the measurement Jacobian matrix is examined for any possible ill-conditioning of the state estimator gain matrix. The performance of the state estimators are compared in terms of the convergence properties and the varian in the estimated states. The IEEE 14-bus and IEEE 300-bus systems are used as test beds for the study.

Valuation methods for resident funded retirement villages in Australia : a practitioner's perspective

Designed for independent living, retirement villages provide either detached or semi-detached residential dwellings with car parking and small private yards. Retirement village developments usually include a mix of independent living units (ILUs) and serviced apartments (SAs) with community facilities providing a shared congregational area for village activities and socialising. Retirement Village assets differ from traditional residential assets due to their operation in accordance with statutory legislation. In Australia, each State and Territory has its own Retirement Village Act and Regulations. In essence, the village operator provides the land and buildings to the residents who pay an amount on entry for the right of occupation. On departure from the units an agreed proportion of either the original purchase price or the sale price is paid to the outgoing resident. The market value of the operator’s interest in the Retirement Village is therefore based upon the estimated future income from Deferred Management Fees and Capital Gain upon roll-over receivable by the operator in accordance with the respective residency agreements. Given the lumpiness of these payments, there is general acceptance that the most appropriate approach to valuation is through Discounted Cash Flow (DCF) analysis. There is however inconsistency between valuers across Australia in how they undertake their DCF analysis, leading to differences in reported values and subsequent confusion among users of valuation services. To give guidance to valuers and enhance confidence from users of valuation services this paper investigates the five major elements of discounted cash flow methodology, namely cash flows, escalation factors, holding period, terminal value and discount rate. Whilst there is dissatisfaction with the financial structuring of the DMF in residency agreements, as long as there are future financial returns receivable by the Village owner/operator, then DCF will continue to be the most appropriate valuation methodology for resident funded retirement villages.

Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.

Compensation for compulsory acquisition of a licensed car parking space

The Acquisition of Land Act 1967 (Qld) (‘the Act’) deals with the acquisition of land by the State for public purposes and provides for compensation. The issue that arose for determination in Sorrento Medical Service Pty Ltd v Chief Executive, Dept of Main Roads [2007] QCA 73 was whether the appellant was entitled to claim compensation under the Act in respect of land resumed by the Main Roads Department over which the appellant had an exclusive contractual licence for car parking spaces for use in association with a medical centre leased by the appellant. At first instance, it was held by the Land Court that the appellant was not entitled to compensation for the resumption of the car parking spaces. The basis for this decision by the Land Court was that a right to compensation only exists where resumption has taken some proprietary interest of the claimant in the land. Following an appeal to the Land Appeal Court being dismissed, the appellant instituted the present appeal to the Queensland Court of Appeal (McMurdo P, Holmes JA and Chesterman J).

State convergence in the initialisation of stream ciphers

An initialisation process is a key component in modern stream cipher design. A well-designed initialisation process should ensure that each key-IV pair generates a different key stream. In this paper, we analyse two ciphers, A5/1 and Mixer, for which this does not happen due to state convergence. We show how the state convergence problem occurs and estimate the effective key-space in each case.

Gifted young adolescents : voices of self

Despite the challenges that giftedness can add to self-formation during early adolescence, gifted young adolescents seldom are asked about their lives outside of counselling and educational contexts. The study considers the complexities that face gifted young adolescents in the process of self-discovery and self-representation, thereby building a case for seeking their own viewpoints. A guiding assumption for the study was that gifted young adolescents may respond positively to the opportunity to share their own perspectives and their own versions of “who they are”. The theoretical underpinnings for this study drew from Dialogical Self Theory. The study resides within an interactive view of self as a dynamic construction rather than a static state, where “who we are” is formed in everyday exchanges with self and others. Self-making as a process among gifted young adolescents is presented as an interactive network of “I” voices interpreted to reflect internal and external dialogue. In this way, self is understood within dialogical concepts of voices as multiple expressions. The study invited twelve gifted young adolescents to write freely about themselves over a six month period in an email journal project. Participants were recruited online and by word-of-mouth and they were able to negotiate their own levels of involvement. Access to the lives of individual young adolescents was sought in an out-of-school setting using narrative methods of personal writing in the form of journals sent as emails to the researcher. The role of the researcher was to act as a supportive listener who responded to participant-led emails and thereby facilitated the process of authoring that occurred across the data-gathering phase. The listening process involved responses that were affirming and designed to build trust. Data in the form of email texts were analysed using a close listening method that uncovered patterns of voices that were explicitly or subtly expressed by participants. The interpretation of voices highlighted the tensions and contradictions involved in the process of participants forming a “self” that emerged as multiple “I” voices. There were three key findings of the study. First, the gifted young adolescent participants each constructed a self around four key voices of Author, Achiever, Resistor/Co-operator and Self-Innovator. These voices were dialogical selfconstructions that showed multiplicity as a normal way of being. Second, the selfmaking processes of the gifted young adolescent participants were guided by a hierarchy of voices that were directed through self-awareness. Third, authoring in association with a responsive adult listener emerged as a dialogic space for promoting self-awareness and a language of self-expression among gifted young adolescents. The findings of the study contribute to knowledge about gifted young adolescents by presenting their own versions of “who” they are, perspectives that might differ from mainstream perceptions. Participants were shown to have highly diverse, complex and individual expressions that have implications for how well they are understood and supported by others. The use of email journals helped to create a synergy for self-disclosure and a safe space for self-expression where participants’ abilities to be themselves were encouraged. Increased self-awareness and selfknowledge among gifted young adolescents is vital to their self-formation and their management of self and others’ expectations. This study makes an original contribution to the field of self-study by highlighting the processes and complexities of young adolescents’ self-constructions. Through the innovative use of narrative methods and an inter-disciplinary approach, the voices of gifted young adolescents were privileged. At a practical level, the study can inform educators, policy-makers, parents and all those who seek to contribute to the well-being of gifted young adolescents.

School system as axiological medium : the state's primary macro-proposing context and its expanding moral role in Australia

This paper analyses the Australian Values Education Program (VEP) within the framework of late-classical political economy. using analytical methods from systemic functional linguistics and critical discourse analysis, we demonstrate that the VEP is an unwitting restatement of the principles of ideology as developed by the likes of Destutt de Tracy and the Young Hegelians. We conclude that the sudden shock of globalisation and the post-national cultures this has entailed is in many ways similar to the shock of formal nationalism that emerged in the late-Seventeenth and early- Eighteenth centuries. The overall result of the VEP for the Australian school system is a massive procedural burden that is unlikely to produce the results at which the program is aimed.

Numerical methods for second-order stochastic differential equations

We seek numerical methods for second‐order stochastic differential equations that reproduce the stationary density accurately for all values of damping. A complete analysis is possible for scalar linear second‐order equations (damped harmonic oscillators with additive noise), where the statistics are Gaussian and can be calculated exactly in the continuous‐time and discrete‐time cases. A matrix equation is given for the stationary variances and correlation for methods using one Gaussian random variable per timestep. The only Runge–Kutta method with a nonsingular tableau matrix that gives the exact steady state density for all values of damping is the implicit midpoint rule. Numerical experiments, comparing the implicit midpoint rule with Heun and leapfrog methods on nonlinear equations with additive or multiplicative noise, produce behavior similar to the linear case.