Uncertainty analysis of pollutant build-up modelling based on a Bayesian Weighted Least Squares approach

Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.

The probability archive : from essence to uncertainty in the mediation of knowledge

This volume puts together the works of a group of distinguished scholars and active researchers in the field of media and communication studies to reflect upon the past, present, and future of new media research. The chapters examine the implications of new media technologies on everyday life, existing social institutions, and the society at large at various levels of analysis. Macro-level analyses of changing techno-social formation – such as discussions of the rise of surveillance society and the "fifth estate" – are combined with studies on concrete and specific new media phenomena, such as the rise of Pro-Am collaboration and "fan labor" online. In the process, prominent concepts in the field of new media studies, such as social capital, displacement, and convergence, are critically examined, while new theoretical perspectives are proposed and explicated. Reflecting the inter-disciplinary nature of the field of new media studies and communication research in general, the chapters interrogate into the problematic through a range of theoretical and methodological approaches. The book should offer students and researchers who are interested in the social impact of new media both critical reviews of the existing literature and inspirations for developing new research questions.

Approaches to access control under uncertainty

The ultimate goal of an access control system is to allocate each user the precise level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting. On one hand employees need enough access to the organisation’s resources in order to perform their jobs and on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally, through carelessness or being socially engineered to give access to an adversary. This thesis investigates issues of existing approaches to access control in allocating optimal level of access to users and proposes solutions in the form of new access control models. These issues are most evident when uncertainty surrounding users’ access needs, incentive to misuse and accountability are considered, hence the title of the thesis. We first analyse access control in environments where the administrator is unable to identify the users who may need access to resources. To resolve this uncertainty an administrative model with delegation support is proposed. Further, a detailed technical enforcement mechanism is introduced to ensure delegated resources cannot be misused. Then we explicitly consider that users are self-interested and capable of misusing resources if they choose to. We propose a novel game theoretic access control model to reason about and influence the factors that may affect users’ incentive to misuse. Next we study access control in environments where neither users’ access needs can be predicted nor they can be held accountable for misuse. It is shown that by allocating budget to users, a virtual currency through which they can pay for the resources they deem necessary, the need for a precise pre-allocation of permissions can be relaxed. The budget also imposes an upper-bound on users’ ability to misuse. A generalised budget allocation function is proposed and it is shown that given the context information the optimal level of budget for users can always be numerically determined. Finally, Role Based Access Control (RBAC) model is analysed under the explicit assumption of administrators’ uncertainty about self-interested users’ access needs and their incentives to misuse. A novel Budget-oriented Role Based Access Control (B-RBAC) model is proposed. The new model introduces the notion of users’ behaviour into RBAC and provides means to influence users’ incentives. It is shown how RBAC policy can be used to individualise the cost of access to resources and also to determine users’ budget. The implementation overheads of B-RBAC is examined and several low-cost sub-models are proposed.

Yutori Kyoiku and the uncertainty of recent neo-liberal reforms in Japanese higher education

This paper draws upon the current situation within Japanese Higher Education. In particular the paper focuses on educational reforms and how they relate to the notions of Yutori Kyoiku which constituted a major attempt by Japanese education to develop individual student capacity. A clear subtext of the recent neo-liberal reform agenda is a desire to incorporated free-market ideals into the Japanese educational system. This paper raises several important problems connected to the reforms such as the decrease in classroom hours, changes to the contents of textbooks and a growing discrepancy in academic skills between students in different localities. These education reforms have impacted on notions of Yutori Kyoiku through the continuation of nationally standardized testing and changes directed at controlling the practices of classroom teachers. While acknowledging the current Japanese cabinet’s (DP) education policy has been inherited from an earlier LDP government, the paper points to similarities between the current reforms and the iconic Meiji era reforms of the late 1800s.

Asset specificity and behavioral uncertainty as moderators of the sales growth-employment growth relationship in emerging ventures

New venture growth is a central topic in entrepreneurship research. Although sales growth is emerging as the most commonly used measure of growth for emerging ventures, employment growth has also been used frequently. However, empirical research demonstrates that there are only very low to moderately sized correlations between the two (Delmar et aL, 2003; Weinzimmer, et al., 1998). In addition) sales growth and employment growth respond differently to a wide variety of criteria (Baum et al., 2001; Delmar et al., 2003). In this study we use transaction cost economics (Williamson, 1996) as a theoretical base to examine transaction cost influences on the addition of new employees as emerging ventures experience sales growth. \\le theorize that transaction cost economics variables will moderate the relationship between sales growth and employment growth. W'e develop and test hypotheses related to asset specificity, behavioral uncertainty, and the influence of resource munificence on the strength of the sales growth/ employment growth relationship. Asset specificity is theorized to be a positive moderator of the relationship between sales growth and employment growth. When the behavioral uncertainty associated with adding new employees is greater than that of outsourcing or subcontracting, it is hypothesized to be a negative moderator of the sales growth/employment growth relationship. We also hypothesize that resource scarcity will strengthen those relationships.

Project management under uncertainty

Morris' (1986) analysis of the factors affecting project success and failure is considered in relation to the psychology of judgement under uncertainty. A model is proposed whereby project managers may identify the specific circumstances in which human decision-making is prone to systematic error, and hence may apply a number of de-biasing techniques.

Robust scale initialization for long-range stereo visual odometry

Achieving a robust, accurately scaled pose estimate in long-range stereo presents significant challenges. For large scene depths, triangulation from a single stereo pair is inadequate and noisy. Additionally, vibration and flexible rigs in airborne applications mean accurate calibrations are often compromised. This paper presents a technique for accurately initializing a long-range stereo VO algorithm at large scene depth, with accurate scale, without explicitly computing structure from rigidly fixed camera pairs. By performing a monocular pose estimate over a window of frames from a single camera, followed by adding the secondary camera frames in a modified bundle adjustment, an accurate, metrically scaled pose estimate can be found. To achieve this the scale of the stereo pair is included in the optimization as an additional parameter. Results are presented both on simulated and field gathered data from a fixed-wing UAV flying at significant altitude, where the epipolar geometry is inaccurate due to structural deformation and triangulation from a single pair is insufficient. Comparisons are made with more conventional VO techniques where the scale is not explicitly optimized, and demonstrated over repeated trials to indicate robustness.

Averting uncertainty : a practical guide to physical activity research in Australian schools

Preventative health has become central to contemporary health care, identifying youth physical activity as a key factor in determining health and functioning. Schools offer a unique research setting due to distinctive methodological circumstances. However, school-based researchers face several obstacles in their endeavour to complete successful research investigations; often confronted with complex research designs and methodological procedures that are not easily amenable to school contexts. The purpose of this paper is to provide a practical guide for teachers (both teacher educators and teaching practitioners) seeking to conduct physical activity-based research in Australian school settings, as well as discuss research practices. The research enabling process has been divided into six phases: preparation; design; outcome measures; procedures; participants; and feedback. Careful planning and consideration must be undertaken prior to the commencement of, and during the research process, due to the complex nature of school settings and research processes that exist in the Australian context.

Essays on technology adoption under uncertainty, globalization and economic growth

This thesis examines how the initial institutional and technological aspects of the economy and the reforms that alter these aspects influence long run growth and development. These issues are addressed in the framework of stochastic endogenous growth models and an empirical framework. The thesis is able to explain why developing nations exhibit diverse growth and inequality patterns. Consequently, the thesis raises a number of policy implications regarding how these nations can improve their economic outcomes.

Error and uncertainty of adult age estimation of the pubic symphysis in an Australian sub-population using computed tomography

After attending this presentation, attendees will gain awareness of: (1) the error and uncertainty associated with the application of the Suchey-Brooks (S-B) method of age estimation of the pubic symphysis to a contemporary Australian population; (2) the implications of sexual dimorphism and bilateral asymmetry of the pubic symphysis through preliminary geometric morphometric assessment; and (3) the value of three-dimensional (3D) autopsy data acquisition for creating forensic anthropological standards. This presentation will impact the forensic science community by demonstrating that, in the absence of demographically sound skeletal collections, post-mortem autopsy data provides an exciting platform for the construction of large contemporary ‘virtual osteological libraries’ for which forensic anthropological research can be conducted on Australian individuals. More specifically, this study assesses the applicability and accuracy of the S-B method to a contemporary adult population in Queensland, Australia, and using a geometric morphometric approach, provides an insight to the age-related degeneration of the pubic symphysis. Despite the prominent use of the Suchey-Brooks (1990) method of age estimation in forensic anthropological practice, it is subject to intrinsic limitations, with reports of differential inter-population error rates between geographical locations1-4. Australian forensic anthropology is constrained by a paucity of population specific standards due to a lack of repositories of documented skeletons. Consequently, in Australian casework proceedings, standards constructed from predominately American reference samples are applied to establish a biological profile. In the global era of terrorism and natural disasters, more specific population standards are required to improve the efficiency of medico-legal death investigation in Queensland. The sample comprises multi-slice computed tomography (MSCT) scans of the pubic symphysis (slice thickness: 0.5mm, overlap: 0.1mm) on 195 individuals of caucasian ethnicity aged 15-70 years. Volume rendering reconstruction of the symphyseal surface was conducted in Amira® (v.4.1) and quantitative analyses in Rapidform® XOS. The sample was divided into ten-year age sub-sets (eg. 15-24) with a final sub-set of 65-70 years. Error with respect to the method’s assigned means were analysed on the basis of bias (directionality of error), inaccuracy (magnitude of error) and percentage correct classification of left and right symphyseal surfaces. Morphometric variables including surface area, circumference, maximum height and width of the symphyseal surface and micro-architectural assessment of cortical and trabecular bone composition were quantified using novel automated engineering software capabilities. The results of this study demonstrated correct age classification utilizing the mean and standard deviations of each phase of the S-B method of 80.02% and 86.18% in Australian males and females, respectively. Application of the S-B method resulted in positive biases and mean inaccuracies of 7.24 (±6.56) years for individuals less than 55 years of age, compared to negative biases and mean inaccuracies of 5.89 (±3.90) years for individuals greater than 55 years of age. Statistically significant differences between chronological and S-B mean age were demonstrated in 83.33% and 50% of the six age subsets in males and females, respectively. Asymmetry of the pubic symphysis was a frequent phenomenon with 53.33% of the Queensland population exhibiting statistically significant (χ2 - p<0.01) differential phase classification of left and right surfaces of the same individual. Directionality was found in bilateral asymmetry, with the right symphyseal faces being slightly older on average and providing more accurate estimates using the S-B method5. Morphometric analysis verified these findings, with the left surface exhibiting significantly greater circumference and surface area than the right (p<0.05). Morphometric analysis demonstrated an increase in maximum height and width of the surface with age, with most significant changes (p<0.05) occurring between the 25-34 and 55-64 year age subsets. These differences may be attributed to hormonal components linked to menopause in females and a reduction in testosterone in males. Micro-architectural analysis demonstrated degradation of cortical composition with age, with differential bone resorption between the medial, ventral and dorsal surfaces of the pubic symphysis. This study recommends that the S-B method be applied with caution in medico-legal death investigations of unknown skeletal remains in Queensland. Age estimation will always be accompanied by error; therefore this study demonstrates the potential for quantitative morphometric modelling of age related changes of the pubic symphysis as a tool for methodological refinement, providing a rigor and robust assessment to remove the subjectivity associated with current pelvic aging methods.

Perceptions of land-use uncertainty in Queensland's resource-based regions

Some of Queensland's regions are experiencing rapid changes related to the recent and growing capacity to more effectively exploit significant energy sources. These changes have triggered land-use conflicts between the mining sector and other economic sectors, mainly agriculture. These conflicts fuel existing uncertainty surrounding the current and future economic, social and environmental impacts of extractive industries. This paper explores the concept of uncertainty as it applies to planning for resource-based regions through a scoping analysis of regional stakeholders' perceptions of land-use uncertainty. It then investigates solutions to alleviate such an issue.

Redistribution and technology adoption under uncertainty : a political economy perspective

We examine the role of politico-economic influences on macroeconomic performance within the framework of an endogenous growth model with costly technology adoption and uncertainty. The model is aimed at understanding the diversity in growth and inequality experiences across countries. Agents adopt either of two risky technologies, one of which is only available through financial intermediaries, who are able to alleviate some of this risk. The entry cost of financial intermediation depends on the proportion of government revenue that is allocated towards cost-reducing financial development expenditure, and agents vote on this proportion. The results show that agents at the top and bottom ends of the distribution prefer alternative means of re-distribution, thereby effectively blocking the allocation of resources towards cost-reducing financial development expenditure. Thus political factors have a role in delaying financial and capital deepening and economic development. Furthermore, the model provides a political-economy perspective on the Kuznets curve; uncertainty interacts with the political economy mechanism to produce transitional inequality patterns that, depending on initial conditions, can unearth the Kuznets-curve experience. Finally, the political outcomes are inefficient relative to policies aimed at maximizing the collective welfare of agents in the economy.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

A Bayesian regression approach to assess uncertainty in pollutant wash-off modelling

Due to knowledge gaps in relation to urban stormwater quality processes, an in-depth understanding of model uncertainty can enhance decision making. Uncertainty in stormwater quality models can originate from a range of sources such as the complexity of urban rainfall-runoff-stormwater pollutant processes and the paucity of observed data. Unfortunately, studies relating to epistemic uncertainty, which arises from the simplification of reality are limited and often deemed mostly unquantifiable. This paper presents a statistical modelling framework for ascertaining epistemic uncertainty associated with pollutant wash-off under a regression modelling paradigm using Ordinary Least Squares Regression (OLSR) and Weighted Least Squares Regression (WLSR) methods with a Bayesian/Gibbs sampling statistical approach. The study results confirmed that WLSR assuming probability distributed data provides more realistic uncertainty estimates of the observed and predicted wash-off values compared to OLSR modelling. It was also noted that the Bayesian/Gibbs sampling approach is superior compared to the most commonly adopted classical statistical and deterministic approaches commonly used in water quality modelling. The study outcomes confirmed that the predication error associated with wash-off replication is relatively higher due to limited data availability. The uncertainty analysis also highlighted the variability of the wash-off modelling coefficient k as a function of complex physical processes, which is primarily influenced by surface characteristics and rainfall intensity.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).