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.

A novel algorithm based on honey bee mating optimization for distribution harmonic state estimation including distributed generators

This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics 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. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

Taxonomic analysis of marine phytoplankton

Samples of sea water contain phytoplankton taxa in varying amounts, and marine scientists are interested in the relative abundance of each taxa. Their relative biomass can be ascertained indirectly by measuring the quantity of various pigments using high performance liquid chromatography. However, the conversion from pigment to taxa is mathematically non trivial as it is a positive matrix factorisation problem where both matrices are unknown beyond the level of initial estimates. The prior information on the pigment to taxa conversion matrix is used to give the problem a unique solution. An iteration of two non-negative least squares algorithms gives satisfactory results. Some sample analysis of data indicates prospects for this type of analysis. An alternative more computationally intensive approach using Bayesian methods is discussed.

A Satellite Selection Algorithm for Achieving High Reliability of Ambiguity Resolution with GPS and Beidou Constellations

Reliability of carrier phase ambiguity resolution (AR) of an integer least-squares (ILS) problem depends on ambiguity success rate (ASR), which in practice can be well approximated by the success probability of integer bootstrapping solutions. With the current GPS constellation, sufficiently high ASR of geometry-based model can only be achievable at certain percentage of time. As a result, high reliability of AR cannot be assured by the single constellation. In the event of dual constellations system (DCS), for example, GPS and Beidou, which provide more satellites in view, users can expect significant performance benefits such as AR reliability and high precision positioning solutions. Simply using all the satellites in view for AR and positioning is a straightforward solution, but does not necessarily lead to high reliability as it is hoped. The paper presents an alternative approach that selects a subset of the visible satellites to achieve a higher reliability performance of the AR solutions in a multi-GNSS environment, instead of using all the satellites. Traditionally, satellite selection algorithms are mostly based on the position dilution of precision (PDOP) in order to meet accuracy requirements. In this contribution, some reliability criteria are introduced for GNSS satellite selection, and a novel satellite selection algorithm for reliable ambiguity resolution (SARA) is developed. The SARA algorithm allows receivers to select a subset of satellites for achieving high ASR such as above 0.99. Numerical results from a simulated dual constellation cases show that with the SARA procedure, the percentages of ASR values in excess of 0.99 and the percentages of ratio-test values passing the threshold 3 are both higher than those directly using all satellites in view, particularly in the case of dual-constellation, the percentages of ASRs (>0.99) and ratio-test values (>3) could be as high as 98.0 and 98.5 % respectively, compared to 18.1 and 25.0 % without satellite selection process. It is also worth noting that the implementation of SARA is simple and the computation time is low, which can be applied in most real-time data processing applications.

Parameter estimation of thrust models of uninhabited airborne systems

This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.

Multi-shot person re-identification via relational stein divergence

Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

Audit fees and asset securitization risks

The thesis investigates “where were the auditors in asset securitizations”, a criticism of the audit profession before and after the onset of the global financial crisis (GFC). Asset securitizations increase audit complexity and audit risks, which are expected to increase audit fees. Using US bank holding company data from 2003 to 2009, this study examines the association between asset securitization risks and audit fees, and its changes during the global financial crisis. The main test is based on an ordinary least squares (OLS) model, which is adapted from the Fields et al. (2004) bank audit fee model. I employ a principal components analysis to address high correlations among asset securitization risks. Individual securitization risks are also separately tested. A suite of sensitivity tests indicate the results are robust. These include model alterations, sample variations, further controls in the tests, and correcting for the securitizer self-selection problem. A partial least squares (PLS) path modelling methodology is introduced as a separate test, which allows for high intercorrelations, self-selection correction, and sequential order hypotheses in one simultaneous model. The PLS results are consistent with the main results. The study finds significant and positive associations between securitization risks and audit fees. After the commencement of the global financial crisis in 2007, there was an increased focus on the role of audits on asset securitization risks resulting from bank failures; therefore I expect that auditors would become more sensitive to bank asset securitization risks after the commencement of the crisis. I find that auditors appear to focus on different aspects of asset securitization risks during the crisis and that auditors appear to charge a GFC premium for banks. Overall, the results support the view that auditors consider asset securitization risks and market changes, and adjust their audit effort and risk considerations accordingly.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling technique in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling methodology in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

Psychological capital as moderator of organizational change demands on nursing stress

Healthcare organizations in all OECD countries have continued to undergo change. These changes have been found to have a negative effect on work engagement of nursing staff. While the extent to which nursing staff dealt with these changes has been documented in the literature, little is known of how they utilized their personal resources to deal with the consequences of these changes. This study will address this gap by integrating the Job Demands-Resources theoretical perspective with Positive Psychology, in particular, psychological capital (PsyCap). PsyCap is operationalized as a source of personal resources. Data were collected from 401 nurses from Australia and analyses were undertaken using Partial Least Squares modelling and moderation analysis. Two types of changes on the nursing work were identified. There was an increase in changes to the work environment of nursing. These changes, included increasing administrative workload and the amount of work, resulted in more job demands and job resources. On the other hand, another type of changes relate to reduction to training and management support, which resulted in less job demands. Nurses with more job demands utilized more job resources to address these increasing demands. We found PsyCap to be a crucial source of personal resources that has a moderating effect on the negative effects of job demands and role stress. PsyCap and job resources were both critical in enhancing the work engagement of nurses, as they encountered changes to nursing work. These findings provided empirical support for a positive psychological perspective of understanding nursing engagement.

Urban growth in the Kathmandu Valley: The transformation of public space

Traditional towns of the Kathmandu Valley boast a fine provision of public spaces in their neighbourhoods. Historically, a hierarchy of public space has been distributed over the entire town with each neighbourhood centered around more or less spacious public squares. However, rapid growth of these towns over the past decades has resulted in haphazard development of new urban areas with little provision of public space. Recent studies indicate that the loss of public space is a major consequence of the uncontrolled urban growth of the Kathmandu Valley and its new neighbourhoods. This paper reviews the current urban growth of the Kathmandu Valley and its impact on the development of public space in new neighbourhoods. The preliminary analysis of the case study of three new neighbourhoods shows that the formation and utilization of neighbourhood public space exhibit fundamental differences from those found in the traditional city cores. The following key issues are identified in this paper: a) Governance and regulations have been a challenge to regulate rapid urban growth; b) The current pattern of neighbourhood formation is found to be different from that of traditional neighbourhoods due to the changes with rapid urban development; c) Public spaces have been compromised in both planned and unplanned new neighbourhoods in terms of their quantity and quality; d) The changing provision of public space has contributed to its changing use and meaning; and e) The changing demographic composition, changing society and life style have had direct impact on the declining use of public space. Moreover, the management of public spaces remains a big challenge due to their changing nature and the changing governance. The current transformation public space does not appear to be conducive, and has led to adversely changing social environment of the new neighbourhoods.

Form-based planning and liveable urban environments

This review article discusses form-based planning an din details analise the following books: Stepehn Marshall (2012) Urban Coding and Planning (Routledge, New York, USA, 272pp. pISBN 1135689202). Emily Talen (2012) City Rules: How Regulations Affects Urban Form (Island Press, Washington DC, USA, 254 pp. ISBN 9781597266925). Richard Tomlinson (2012) Australia’s Unintended Cities: the Impact of Housing on Urban Development (CSIRO Publishing, Collingwood, Australia, 194pp. ISBN 9780643103771). The history of the city has been written and rewritten many times: the seminal works of Benevolo (1980) and Mumford (1989) reconstruct how settlements, particularly their urban form, have changed over centuries. Rowe and Koetter (1978), Kostof (1991, 1992), Krier (2003), and Rossi and Eisenmann (1982) address instead the components that shape the urban environment: the architect can aggregate and manipulate squares, streets, parks and public buildings to control urban design. Generally these studies aim to reveal the secret of the traditional city in contraposition to the contemporary townscape characterized by planning and zoning, which are generally regarded as problematic and sterile (Woodward, 2013). The ‘secret rules’ that have shaped our cities have a bearing on the relationship of spaces, mixed uses, public environments and walkability (Walters, 2011)...

Adaptive estimation of HMM transition probabilities

This paper presents new schemes for recursive estimation of the state transition probabilities for hidden Markov models (HMM's) via extended least squares (ELS) and recursive state prediction error (RSPE) methods. Local convergence analysis for the proposed RSPE algorithm is shown using the ordinary differential equation (ODE) approach developed for the more familiar recursive output prediction error (RPE) methods. The presented scheme converges and is relatively well conditioned compared with the ...