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.

Design of experiments for bivariate binary responses modelled by Copula functions

Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.

Oral intake and serum levels of ascorbic acid in continuous ambulatory peritoneal dialysis patients

Oral intake of ascorbic acid is essential for optimum health in human beings. Continuous ambulatory peritoneal dialysis (CAPD) patients have an increased need for ascorbic acid, because of increased loss through dialysate, reduced intake owing to nausea and loss of appetite, and increased oxidative stress. However, optimum intake is still controversial. We studied 50 clinically stable patients to determine the relationship between oral ascorbic acid intake and serum ascorbic acid (SAA) level. Total oral intake ranged from 28 mg daily to 412 mg daily. Only one patient had an oral intake of ascorbic acid below 60 mg per day. The SAA levels ranged from 1 mg/L to 36.17 mg/L. Although a strong correlation existed between intake and SAA (p < 0.001, R2 = 0.47), the variation in SAA at any given intake level was wide. Of the studied patients, 62% had an SAA < 8.7 mg/L, 40% had an SAA < 5.1 mg/L (below the level in a healthy population), and 12% had a level below 2 mg/L (scorbutic). None of the patients demonstrated clinical manifestations of scurvy. Our results show that, in CAPD patients, ascorbic acid deficiency can be reliably detected only with SAA measurements, and oral intake may influence SAA level. To maintain ascorbic acid in the normal range for healthy adults, daily oral intake needs to be increased above the U.S. recommended dietary allowance to 80-140 mg.

Evaluating multivariate volatility forecasts : how effective are statistical and economic loss functions?

Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.

Continuous and pedagogically sound assessment : A new economy of power relations in Australian Law schools

In recent decades, assessment practices within Australian law schools have moved from the overwhelming use of end-of-year closed-book examinations to an increase in the use of a wider range of techniques. This shift is often characterised as providing a ‘better’ learning environment for students, contributing more positively to their own ‘personal development’ within higher education, or, considered along the lines of critical legal thought, as ‘liberating’ them from the ‘conservatising’ and ‘indoctrinating’ effects of the power relations that operate in law schools. This paper seeks to render problematic such liberal-progressive narratives about these changes to law school assessment practices. It will do so by utilising the work of French historian and philosopher Michel Foucault on power, arguing that the current range of assessment techniques demonstrates a shift in the ‘economy’ of power relations within the law school. Rather than ‘liberating’ students from relations of power, these practices actually extend the power relations through which students are governed. This analysis is intended to inform legal education research and assessment practice by providing a far more nuanced conceptual framework than one that seeks to ‘free’ law students from these ‘repressive’ practices, or hopes to ‘objectively’ contribute to their ‘personal development’.

Continuous innovation in SMEs : how design innovation shapes business performance through doing more with less

Firms face the challenge to survive and thrive in an increasingly competitive global market, developing strategies to continuously innovate, often having to do more with less. Increasing awareness of the benefits of stimulating continuous innovation in small and medium enterprises has led to the development and implementation of design innovation programs, with many western countries investing in design innovation programs for better firm performance. This paper investigates how firms respond to a design innovation program and engage in continuous innovation, doing more business with a focused less diverse strategy. Early findings from a study of companies engaged in a design innovation program indicate that applying design principles to all aspects of their business has delivered better business performance and better positioning in global markets.

Accelerated leap methods for simulating discrete stochastic chemical kinetics

Biologists are increasingly conscious of the critical role that noise plays in cellular functions such as genetic regulation, often in connection with fluctuations in small numbers of key regulatory molecules. This has inspired the development of models that capture this fundamentally discrete and stochastic nature of cellular biology - most notably the Gillespie stochastic simulation algorithm (SSA). The SSA simulates a temporally homogeneous, discrete-state, continuous-time Markov process, and of course the corresponding probabilities and numbers of each molecular species must all remain positive. While accurately serving this purpose, the SSA can be computationally inefficient due to very small time stepping so faster approximations such as the Poisson and Binomial τ-leap methods have been suggested. This work places these leap methods in the context of numerical methods for the solution of stochastic differential equations (SDEs) driven by Poisson noise. This allows analogues of Euler-Maruyuma, Milstein and even higher order methods to be developed through the Itô-Taylor expansions as well as similar derivative-free Runge-Kutta approaches. Numerical results demonstrate that these novel methods compare favourably with existing techniques for simulating biochemical reactions by more accurately capturing crucial properties such as the mean and variance than existing methods.

A continuous time model for election timing

We consider a continuous time model for election timing in a Majoritarian Parliamentary System where the government maintains a constitutional right to call an early election. Our model is based on the two-party-preferred data that measure the popularity of the government and the opposition over time. We describe the poll process by a Stochastic Differential Equation (SDE) and use a martingale approach to derive a Partial Differential Equation (PDE) for the government’s expected remaining life in office. A comparison is made between a three-year and a four-year maximum term and we also provide the exercise boundary for calling an election. Impacts on changes in parameters in the SDE, the probability of winning the election and maximum terms on the call exercise boundaries are discussed and analysed. An application of our model to the Australian Federal Election for House of Representatives is also given.

Neuropsychological development in children with early and continuously treated phenylketonuria : association with biochemical markers

PKU is a genetically inherited inborn error of metabolism caused by a deficiency of the enzyme phenylalanine hydroxylase. The failure of this enzyme causes incomplete metabolism of protein ingested in the diet, specifically the conversion of one amino acid, phenylalanine, to tyrosine, which is a precursor to the neurotransmitter dopamine. Rising levels of phenylalanine is toxic to the developing brain, disrupting the formation of white matter tracts. The impact of tyrosine deficiency is not as well understood, but is hypothesized to lead to a low dopamine environment for the developing brain. Detection in the newborn period and continuous treatment (a low protein phe-restricted diet supplemented with phenylalanine-free protein formulas) has resulted in children with early and continuously treated PKU now developing normal I.Q. However, deficits in executive function (EF) are common, leading to a rate of Attention Deficit Hyperactivity Disorder (ADHD) up to five times the norm. EF worsens with exposure to higher phenylalanine levels, however recent research has demonstrated that a high phenylalanine to tyrosine ratio (phenylalanine:tyrosine ratio), which is hypothesised to lead to poorer dopamine function, has a more negative impact on EF than phenylalanine levels alone. Research and treatment of PKU is currently phenylalanine-focused, with little investigation of the impact of tyrosine on neuropsychological development. There is no current consensus as to the veracity of tyrosine monitoring or treatment in this population. Further, the research agenda in this population has demonstrated a primary focus on EF impairment alone, even though there may be additional neuropsychological skills compromised (e.g., mood, visuospatial deficits). The aim of this PhD research was to identify residual neuropsychological deficits in a cohort of children with early and continuously treated phenylketonuria, at two time points in development (early childhood and early adolescence), separated by eight years. In addition, this research sought to determine which biochemical markers were associated with neuropsychological impairments. A clinical practice survey was also undertaken to ascertain the current level of monitoring/treatment of tyrosine in this population. Thirteen children with early and continuously treated PKU were tested at mean age 5.9 years and again at mean age 13.95 years on several neuropsychological measures. Four children with hyperphenylalaninemia (a milder version of PKU) were also tested at both time points and provide a comparison group in analyses. Associations between neuropsychological function and biochemical markers were analysed. A between groups analysis in adolescence was also conducted (children with PKU compared to their siblings) on parent report measures of EF and mood. Minor EF impairments were evident in the PKU group by age 6 years and these persisted into adolescence. Life-long exposure to high phenylalanine:tyrosine ratio and/or low tyrosine independent of phenylalanine were significantly associated with EF impairments at both time points. Over half the children with PKU showed severe impairment on a visuospatial task, and this was associated only with concurrent levels of tyrosine in adolescence. Children with PKU also showed a statistically significant decline in a language comprehension task from 6 years to adolescence (going from normal to subnormal), this deficit was associated with lifetime levels of phenylalanine. In comparison, the four children with hyperphenylalaninemia demonstrated normal function at both time points, across all measures. No statistically significant differences were detected between children with PKU and their siblings on the parent report of EF and mood. However, depressive symptoms were significantly correlated with: EF; long term high phe:tyr exposure; and low tyrosine levels independent of phenylalanine. The practice survey of metabolic clinics from 12 countries indicated a high level of variability in terms of monitoring/treatment of tyrosine in this population. Whilst over 80% of clinics surveyed routinely monitored tyrosine levels in their child patients, 25% reported treatment strategies to increase tyrosine (and thereby lower the phenylalanine:tyrosine ratio) under a variety of patient presentation conditions. Overall, these studies have shown that EF impairments associated with PKU provide support for the dopamine-deficiency model. A language comprehension task showed a different trajectory, serving a timely reminder that non-EF functions also remain vulnerable in this population; and that normal function in childhood does not guarantee normal function by adolescence. Mood impairments were associated with EF impairments as well as long term measures of phenylalanine:tyrosine and/or tyrosine. The implications of this research for enhanced clinical guidelines are discussed given varied current practice.

A longitudinal study of corporate earnings guidance in Australia’s continuous disclosure environment

Since the introduction of a statutory‐backed continuous disclosure regime (CDR) in 1994, regulatory reforms have significantly increased litigation risk in Australia for failure to disclose material information or for false and misleading disclosure. However, there is almost no empirical research on the impact of the reforms on corporate disclosure behaviour. Motivated by the absence of research and using management earnings forecasts (MEFs) as a disclosure proxy, this study examines (1) why managers issue earnings forecasts, (2) what firm‐specific factors influence MEF characteristics, and (3) how MEF behaviour changes as litigation risk increases. Based on theories in information economics, a theoretical framework for MEF behaviour is formulated which includes antecedent influencing factors related to firms‟ internal and external environments. Applying this framework, hypotheses are developed and tested using multivariate models and a large sample of hand-collected MEFs (7,213) issued by top 500 ASX-listed companies over the 1994 to 2008 period. The results reveal strong support for the hypotheses. First, MEFs are issued to reduce information asymmetry, litigation risk and signal superior performance. Second, firms with better financial performance, smaller earnings changes, and lower operating uncertainty provide better quality MEFs. Third, forecast frequency and quality (accuracy, timeliness and precision) noticeably improve as litigation risk increases. However, managers appear to be still reluctant to disclose earnings forecasts when there are large earnings changes, and an asymmetric treatment of news type continues to prevail (a good news bias). Thus, the findings generally provide support for the effectiveness of the CDR regulatory reforms in improving disclosure behaviour and will be valuable to market participants and corporate regulators in understanding the implications of management forecasting decisions and areas for further improvement.