Coordinated probabilistic optimal decision-making model for multi-area ATC with risk control

In the decision-making of multi-area ATC (Available Transfer Capacity) in electricity market environment, the existing resources of transmission network should be optimally dispatched and coordinately employed on the premise that the secure system operation is maintained and risk associated is controllable. The non-sequential Monte Carlo simulation is used to determine the ATC probability density distribution of specified areas under the influence of several uncertainty factors, based on which, a coordinated probabilistic optimal decision-making model with the maximal risk benefit as its objective is developed for multi-area ATC. The NSGA-II is applied to calculate the ATC of each area, which considers the risk cost caused by relevant uncertainty factors and the synchronous coordination among areas. The essential characteristics of the developed model and the employed algorithm are illustrated by the example of IEEE 118-bus test system. Simulative result shows that, the risk of multi-area ATC decision-making is influenced by the uncertainties in power system operation and the relative importance degrees of different areas.

Residential dissonance and mode choice

Residential dissonance refers to the mismatch in land-use patterns between individuals’ preferred residential neighbourhood type and the type of neighbourhood in which they currently reside. Current knowledge regarding the impact of residential dissonance is limited to short-term travel behaviours in urban vs. suburban, and rural vs. urban areas. Although the prevailing view is that dissonants adjust their orientation and lifestyle around their surrounding land use over time, empirical evidence is lacking to support this proposition. This research identifies both short-term mode choice behaviour and medium-term mode shift behaviour of dissonants in transit oriented development (TODs) vs. non-TOD areas in Brisbane, Australia. Natural groupings of neighbourhood profiles (e.g. residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility levels) of 3957 individuals were identified as living either in a TOD (510 individuals) or non-TOD (3447 individuals) areas in Brisbane using the TwoStep cluster analysis technique. Levels of dissonance were measured based on a factor analysis of 16 items representing the travel attitudes/preferences of individuals. Two multinomial logistic (MNL) regression models were estimated to understand mode choice behaviour of (1) TOD dissonants, and (2) non-TOD dissonants in 2009, controlling for socio-demographics and environmental characteristics. Two additional MNL regression models were estimated to investigate mode shift behaviour of (3) TOD dissonants, and (4) non-TOD dissonants between 2009 and 2011, also controlling for socio-demographic, changes in socio-demographic, and built environmental factors. The findings suggest that travel preference is relatively more influential in transport mode choice decisions compared with built environment features. Little behavioural evidence was found to support the adjustment of a dissonant orientation toward a particular land use feature and mode accessibility they represent (e.g. a modal shift to greater use of the car for non-TOD dissonants). TOD policies should focus on reducing the level of dissonance in TODs in order to enhance transit ridership.

Emergency Health Services (EHS) : demand and service delivery models. monograph 3 : patients’ reasons and perceptions

Executive Summary Emergency health is a critical component of Australia’s health system and emergency departments (EDs) are increasingly congested from growing demand and blocked access to inpatient beds. The Emergency Health Services Queensland (EHSQ) study aims to identify the factors driving increased demand for emergency health and to evaluate strategies which may safely reduce the future demand growth. This monograph addresses the perspectives of users of both ambulance services and EDs. The research reported here aimed to identify the perspectives of users of emergency health services, both ambulance services and public hospital Emergency Departments and to identify the factors that they took into consideration when exercising their choice of location for acute health care. A cross-sectional survey design was used involving a survey of patients or their carers presenting to the EDs of a stratified sample of eight hospitals. A specific purpose questionnaire was developed based on a novel theoretical model which had been derived from analysis of the literature (Monograph 1). Two survey versions were developed: one for adult patients (self-complete); and one for children (to be completed by parents/guardians). The questionnaires measured perceptions of social support, health status, illness severity, self-efficacy; beliefs and attitudes towards ED and ambulance services; reasons for using these services, and actions taken prior to the service request. The survey was conducted at a stratified sample of eight hospitals representing major cities (four), inner regional (two) and outer regional and remote (two). Due to practical limitations, data were collected for ambulance and ED users within hospital EDs, while patients were waiting for or under treatment. A sample size quota was determined for each ED based on their 2009/10 presentation volumes. The data collection was conducted by four members of the research team and a group of eight interviewers between March and May 2011 (corresponding to autumn season). Of the total of 1608 patients in all eight emergency departments the interviewers were able to approach 1361 (85%) patients and seek their consent to participate in the study. In total, 911 valid surveys were available for analysis (response rate= 67%). These studies demonstrate that patients elected to attend hospital EDs in a considered fashion after weighing up alternatives and there is no evidence of deliberate or ill-informed misuse. • Patients attending ED have high levels of social support and self-efficacy that speak to the considered and purposeful nature of the exercise of choice. • About one third of patients have new conditions while two thirds have chronic illnesses • More than half the attendees (53.1%) had consulted a healthcare professional prior to making the decision. • The decision to seek urgent care at an ED was mostly constructed around the patient’s perception of the urgency and severity of their illness, reinforced by a strong perception that the hospital ED was the correct location for them (better specialised staff, better care for my condition, other options not as suitable). • 33% of the respondent held private hospital insurance but nevertheless attended a public hospital ED. Similarly patients exercised considered and rational judgements in their choice to seek help from the ambulance service. • The decision to call for ambulance assistance was based on a strong perception about the severity of the illness (too severe to use other means of transport) and that other options were not considered appropriate. • The decision also appeared influenced by a perception that the ambulance provided appropriate access to the ED which was considered most appropriate for their particular condition (too severe to go elsewhere, all facilities in one spot, better specialised and better care). • In 43.8% of cases a health care professional advised use of the ambulance. • Only a small number of people perceived that ambulance should be freely available regardless of severity or appropriateness. These findings confirm a growing understanding that the choice of professional emergency health care services is not made lightly but rather made by reasonable people exercising a judgement which is influenced by public awareness of the risks of acute health and which is most often informed by health professionals. It is also made on the basis of a rational weighing up of alternatives and a deliberate and considered choice to seek assistance from a service which the patient perceived was most appropriate to their needs at that time. These findings add weight to dispensing with public perceptions that ED and ambulance congestion is a result of inappropriate choice by patients. The challenge for health services is to better understand the patient’s needs and to design and validate services that meet those needs. The failure of our health system to do so should not be grounds for blaming the patient, claiming inappropriate patient choices.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

A probabilistic framework to monitor a multi-mode outdoor robot

This paper presents an approach to autonomously monitor the behavior of a robot endowed with several navigation and locomotion modes, adapted to the terrain to traverse. The mode selection process is done in two steps: the best suited mode is firstly selected on the basis of initial information or a qualitative map built on-line by the robot. Then, the motions of the robot are monitored by various processes that update mode transition probabilities in a Markov system. The paper focuses on this latter selection process: the overall approach is depicted, and preliminary experimental results are presented

Exact series solutions of reactive transport models with general initial conditions

Exact solutions of partial differential equation models describing the transport and decay of single and coupled multispecies problems can provide insight into the fate and transport of solutes in saturated aquifers. Most previous analytical solutions are based on integral transform techniques, meaning that the initial condition is restricted in the sense that the choice of initial condition has an important impact on whether or not the inverse transform can be calculated exactly. In this work we describe and implement a technique that produces exact solutions for single and multispecies reactive transport problems with more general, smooth initial conditions. We achieve this by using a different method to invert a Laplace transform which produces a power series solution. To demonstrate the utility of this technique, we apply it to two example problems with initial conditions that cannot be solved exactly using traditional transform techniques.

Fast re-parameterisation of Gaussian mixture models for robotics applications

Autonomous navigation and picture compilation tasks require robust feature descriptions or models. Given the non Gaussian nature of sensor observations, it will be shown that Gaussian mixture models provide a general probabilistic representation allowing analytical solutions to the update and prediction operations in the general Bayesian filtering problem. Each operation in the Bayesian filter for Gaussian mixture models multiplicatively increases the number of parameters in the representation leading to the need for a re-parameterisation step. A computationally efficient re-parameterisation step will be demonstrated resulting in a compact and accurate estimate of the true distribution.

Comparison of eight published static finite element models of the intact lumbar spine : predictive power of models improves when combined together

Finite element (FE) model studies have made important contributions to our understanding of functional biomechanics of the lumbar spine. However, if a model is used to answer clinical and biomechanical questions over a certain population, their inherently large inter-subject variability has to be considered. Current FE model studies, however, generally account only for a single distinct spinal geometry with one set of material properties. This raises questions concerning their predictive power, their range of results and on their agreement with in vitro and in vivo values. Eight well-established FE models of the lumbar spine (L1-5) of different research centres around the globe were subjected to pure and combined loading modes and compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges, and their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with published median in vitro values. However, the ranges of predictions were larger and exceeded those reported in vitro, especially for the facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with measured in vivo values. In light of high inter-subject variability, the generalization of results of a single model to a population remains a concern. This study demonstrated that the pooled median of individual model results, similar to a probabilistic approach, can be used as an improved predictive tool in order to estimate the response of the lumbar spine.

The game of clones and the Australia tax : divergent views about copyright business models and the willingness of Australian consumers to infringe

It is often said that Australia is a world leader in rates of copyright infringement for entertainment goods. In 2012, the hit television show, Game of Thrones, was the most downloaded television show over bitorrent, and estimates suggest that Australians accounted for a plurality of nearly 10% of the 3-4 million downloads each week. The season finale of 2013 was downloaded over a million times within 24 hours of its release, and again Australians were the largest block of illicit downloaders over BitTorrent, despite our relatively small population. This trend has led the former US Ambassador to Australia to implore Australians to stop 'stealing' digital content, and rightsholders to push for increasing sanctions on copyright infringers. The Australian Government is looking to respond by requiring Internet Service Providers to issue warnings and potentially punish consumers who are alleged by industry groups to have infringed copyright. This is the logical next step in deterring infringement, given that the operators of infringing networks (like The Pirate Bay, for example) are out of regulatory reach. This steady ratcheting up of the strength of copyright, however, comes at a significant cost to user privacy and autonomy, and while the decentralisation of enforcement reduces costs, it also reduces the due process safeguards provided by the judicial process. This article presents qualitative evidence that substantiates a common intuition: one of the major reasons that Australians seek out illicit downloads of content like Game of Thrones in such numbers is that it is more difficult to access legitimately in Australia. The geographically segmented way in which copyright is exploited at an international level has given rise to a ‘tyranny of digital distance’, where Australians have less access to copyright goods than consumers in other countries. Compared to consumers in the US and the EU, Australians pay more for digital goods, have less choice in distribution channels, are exposed to substantial delays in access, and are sometimes denied access completely. In this article we focus our analysis on premium film and television offerings, like Game of Thrones, and through semi-structured interviews, explore how choices in distribution impact on the willingness of Australian consumers to seek out infringing copies of copyright material. Game of Thrones provides an excellent case study through which to frame this analysis: it is both one of the least legally accessible television offerings and one of the most downloaded through filesharing networks of recent times. Our analysis shows that at the same time as rightsholder groups, particularly in the film and television industries, are lobbying for stronger laws to counter illicit distribution, the business practices of their member organisations are counter-productively increasing incentives for consumers to infringe. The lack of accessibility and high prices of copyright goods in Australia leads to substantial economic waste. The unmet consumer demand means that Australian consumers are harmed by lower access to information and entertainment goods than consumers in other jurisdictions. The higher rates of infringement that fulfils some of this unmet demand increases enforcement costs for copyright owners and imposes burdens either on our judicial system or on private entities – like ISPs – who may be tasked with enforcing the rights of third parties. Most worryingly, the lack of convenient and cheap legitimate digital distribution channels risks undermining public support for copyright law. Our research shows that consumers blame rightsholders for failing to meet market demand, and this encourages a social norm that infringing copyright, while illegal, is not morally wrongful. The implications are as simple as they are profound: Australia should not take steps to increase the strength of copyright law at this time. The interests of the public and those of rightsholders align better when there is effective competition in distribution channels and consumers can legitimately get access to content. While foreign rightsholders are seeking enhanced protection for their interests, increasing enforcement is likely to increase their ability to engage in lucrative geographical price-discrimination, particularly for premium content. This is only likely to increase the degree to which Australian consumers feel that their interests are not being met and, consequently, to further undermine the legitimacy of copyright law. If consumers are to respect copyright law, increasing sanctions for infringement without enhancing access and competition in legitimate distribution channels could be dangerously counter-productive. We suggest that rightsholders’ best strategy for addressing infringement in Australia at this time is to ensure that Australians can access copyright goods in a timely, affordable, convenient, and fair lawful manner.

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

A two-stage item recommendation method using probabilistic ranking with reconstructed tensor model

In a tag-based recommender system, the multi-dimensional correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods

In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.

Commuting mode choice in transit oriented development: Disentangling the effects of competitive neighbourhoods, travel attitudes, and self-selection

This research identifies the commuting mode choice behaviour of 3537 adults living in different types of transit oriented development (TOD) in Brisbane by disentangling the effects of their “evil twin” transit adjacent developments (TADs), and by also controlling for residential self-selection, travel attitudes and preferences, and socio-demographic effects. A TwoStep cluster analysis was conducted to identify the natural groupings of respondents’ living environment based on six built environment indicators. The analysis resulted in five types of neighbourhoods: urban TODs, activity centre TODs, potential TODs, TADs, and traditional suburbs. HABITAT survey data were used to derive the commute mode choice behaviour of people living in these neighbourhoods. In addition, statements reflecting both respondents’ travel attitudes and living preferences were also collected as part of the survey. Factor analyses were conducted based on these statements and these derived factors were then used to control for residential self-selection. Four binary logistic regression models were estimated, one for each of the travel modes used (e.g. public transport, active transport, less sustainable transport such as the car/taxi, and other), to differentiate between the commuting behaviour of people living in the five types of neighbourhoods. The findings verify that urban TODs enhance the use of public transport and reduce car usage. No significant difference was found in the commuting behaviour between respondents living in traditional suburbs and TADs. The results confirm the hypothesis that TADs are the “evil twin” of TODs. The data indicates that TADs and the mode choices of residents in these neighbourhoods is a missed transport policy opportunity. Further policy efforts are required for a successive transition of TADs into TODs in order to realise the full benefits of these. TOD policy should also be integrated with context specific TOD design principles.

Discussion of “Generalized estimating equations: Notes on the choice of the working correlation matrix”

Objective To discuss generalized estimating equations as an extension of generalized linear models by commenting on the paper of Ziegler and Vens "Generalized Estimating Equations. Notes on the Choice of the Working Correlation Matrix". Methods Inviting an international group of experts to comment on this paper. Results Several perspectives have been taken by the discussants. Econometricians have established parallels to the generalized method of moments (GMM). Statisticians discussed model assumptions and the aspect of missing data Applied statisticians; commented on practical aspects in data analysis. Conclusions In general, careful modeling correlation is encouraged when considering estimation efficiency and other implications, and a comparison of choosing instruments in GMM and generalized estimating equations, (GEE) would be worthwhile. Some theoretical drawbacks of GEE need to be further addressed and require careful analysis of data This particularly applies to the situation when data are missing at random.

Computation of confined swirling flow using RNG and k-epsilon turbulence models

In this work we numerically model isothermal turbulent swirling flow in a cylindrical burner. Three versions of the RNG k-epsilon model are assessed against performance of the standard k-epsilon model. Sensitivity of numerical predictions to grid refinement, differing convective differencing schemes and choice of (unknown) inlet dissipation rate, were closely scrutinised to ensure accuracy. Particular attention is paid to modelling the inlet conditions to within the range of uncertainty of the experimental data, as model predictions proved to be significantly sensitive to relatively small changes in upstream flow conditions. We also examine the characteristics of the swirl--induced recirculation zone predicted by the models over an extended range of inlet conditions. Our main findings are: - (i) the standard k-epsilon model performed best compared with experiment; - (ii) no one inlet specification can simultaneously optimize the performance of the models considered; - (iii) the RNG models predict both single-cell and double-cell IRZ characteristics, the latter both with and without additional internal stagnation points. The first finding indicates that the examined RNG modifications to the standard k-e model do not result in an improved eddy viscosity based model for the prediction of swirl flows. The second finding suggests that tuning established models for optimal performance in swirl flows a priori is not straightforward. The third finding indicates that the RNG based models exhibit a greater variety of structural behaviour, despite being of the same level of complexity as the standard k-e model. The plausibility of the predicted IRZ features are discussed in terms of known vortex breakdown phenomena.