Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

Examining the profile and experiences of older sub-acute patients who present to public hospital emergency departments in South East Queensland: A mixed methods approach

There is a scarcity of research that informs Interface Health Service (IHS) development. This research applied a mixed methods approach to profile older emergency department patients and patterns of health service use and to explore their ED experiences in public hospital EDs in South-East Queensland. IHS was under-utilised by older people with complex co-morbidities. Lack of communication and need identification were factors that undermined the effectiveness of IHS in reaching this cohort which highlighted a need for change.

Haemodialysis work environment contributors to job satisfaction and stress: A sequential mixed methods study

Background: Haemodialysis nurses form long term relationships with patients in a technologically complex work environment. Previous studies have highlighted that haemodialysis nurses face stressors related to the nature of their work and also their work environments leading to reported high levels of burnout. Using Kanters (1997) Structural Empowerment Theory as a guiding framework, the aim of this study was to explore the factors contributing to satisfaction with the work environment, job satisfaction, job stress and burnout in haemodialysis nurses. Methods: Using a sequential mixed-methods design, the first phase involved an on-line survey comprising demographic and work characteristics, Brisbane Practice Environment Measure (B-PEM), Index of Work Satisfaction(IWS), Nursing Stress Scale (NSS) and the Maslach Burnout Inventory (MBI). The second phase involved conducting eight semi-structured interviews with data thematically analyzed. Results: From the 417 nurses surveyed the majority were female (90.9 %), aged over 41 years of age (74.3 %), and 47.4 % had worked in haemodialysis for more than 10 years. Overall the work environment was perceived positively and there was a moderate level of job satisfaction. However levels of stress and emotional exhaustion (burnout) were high. Two themes, ability to care and feeling successful as a nurse, provided clarity to the level of job satisfaction found in phase 1. While two further themes, patients as quasi-family and intense working teams, explained why working as a haemodialysis nurse was both satisfying and stressful. Conclusions: Nurse managers can use these results to identify issues being experienced by haemodialysis nurses working in the unit they are supervising.

Analysing commercial catch and effort data from a penaeid trawl fishery: A comparison of linear models, mixed models, and generalised estimating equations approaches

Statistical methods are often used to analyse commercial catch and effort data to provide standardised fishing effort and/or a relative index of fish abundance for input into stock assessment models. Achieving reliable results has proved difficult in Australia's Northern Prawn Fishery (NPF), due to a combination of such factors as the biological characteristics of the animals, some aspects of the fleet dynamics, and the changes in fishing technology. For this set of data, we compared four modelling approaches (linear models, mixed models, generalised estimating equations, and generalised linear models) with respect to the outcomes of the standardised fishing effort or the relative index of abundance. We also varied the number and form of vessel covariates in the models. Within a subset of data from this fishery, modelling correlation structures did not alter the conclusions from simpler statistical models. The random-effects models also yielded similar results. This is because the estimators are all consistent even if the correlation structure is mis-specified, and the data set is very large. However, the standard errors from different models differed, suggesting that different methods have different statistical efficiency. We suggest that there is value in modelling the variance function and the correlation structure, to make valid and efficient statistical inferences and gain insight into the data. We found that fishing power was separable from the indices of prawn abundance only when we offset the impact of vessel characteristics at assumed values from external sources. This may be due to the large degree of confounding within the data, and the extreme temporal changes in certain aspects of individual vessels, the fleet and the fleet dynamics.

Motivation or demotivation of health workers providing maternal health services in rural areas in Vietnam: findings from a mixed-methods study

Background Motivation is an important driver for health professionals to maintain professional competencies, continue in a workforce and contribute to work tasks. While there is some research about motivation in health workers in low to middle income countries, maternal morbidity and mortality remains high in many low and middle income countries and this can be improved by improving the quality of maternal services and the training and skills maintenance of maternal health workers. This study examines the impact of motivation on maintenance of professional competence among maternal health workers in Vietnam using mixed methods. Methods The study consisted of a survey using a self-administered questionnaire of 240 health workers in 5 districts across two Vietnamese provinces and in-depth interviews with 43 health workers and health managers at the commune, district and provincial level to explore external factors that influenced motivation. The questionnaire includes a 23 item motivation instrument based on Kenyan health context, modified for Vietnamese language and culture. Results The 240 responses represented an estimated 95% of the target sample. Multivariate analysis showed that three factors contributed to the motivation of health workers: access to training (β = -0.14, p=0.03), ability to perform key tasks (β = 0.22, p=0.001), and shift schedule (β = -0.13, p=0.05). Motivation was higher in health workers self-identifying as competent or enabled to provide more care activities. Motivation was lower in those who worked more frequent night shifts and those who had received training in the last 12 months. The interviews identified that the latter was because they felt the training was irrelevant to them, and in some cases, they do not have opportunity to practice their learnt skills. The qualitative data also showed other factors relating to service context and organisational management practices contributed to motivation. Conclusions The study demonstrates the importance of understanding the motivations of health workers and the factors that contribute to this and may contribute to more effective management of the health workforce in low and middle income countries.

Mathematics, programming, and STEM

Learning mathematics is a complex and dynamic process. In this paper, the authors adopt a semiotic framework (Yeh & Nason, 2004) and highlight programming as one of the main aspects of the semiosis or meaning-making for the learning of mathematics. During a 10-week teaching experiment, mathematical meaning-making was enriched when primary students wrote Logo programs to create 3D virtual worlds. The analysis of results found deep learning in mathematics, as well as in technology and engineering areas. This prompted a rethinking about the nature of learning mathematics and a need to employ and examine a more holistic learning approach for the learning in science, technology, engineering, and mathematics (STEM) areas.

Evaluation of an intervention for patients with alcohol-related injuries: results of a mixed methods study

Objective: To explore the effect of education and training on the delivery of alcohol screening and brief intervention and referral to high-risk patients in a hospital setting. Main outcome measures included; delivery of training; practice change in relation to staff performing alcohol screening, brief intervention and referrals. Methods: Observational study design using mixed methods set in a tertiary referral hospital. Pre-post assessment of medical records and semi-structured interviews with key informants. Results: Routine screening for substance misuse (9% pre / 71.4% post) and wellbeing concerns (6.6% pre / 15 % post) was more frequent following the introduction of resources and staff participation in educational workshops. There was no evidence of a concomitant increase in delivery of brief intervention or referrals to services. Implementation challenges, including time constraints and staff attitudes, and enablers such as collaboration and visible pathways, were identified. Conclusion: Rates of patient screening increased, however barriers to delivery of brief intervention and referrals remained. Implementation strategies targeting specific barriers and enablers to introducing interventions are both required to improve the application of secondary prevention for patients in acute settings. Implications: Educational training, formalised liaison between services, systematised early intervention protocols, and continuous quality improvement processes will progress service delivery in this area.

Implementing music therapy on an adolescent inpatient unit: A mixed-methods evaluation of acceptability, experience of participation and perceived impact

Objective: We aimed to assess the feasibility of delivering a music therapy program on adolescent psychiatric wards. Method: We undertook a mixed-methods evaluation of a pilot program. Various active and receptive techniques were employed in group music therapy sessions delivered as part of a structured clinical program. Data collected in interviews with participants and staff and feedback questionnaires were thematically and descriptively analysed and triangulated. Results: Data from 62 questionnaires returned by 43 patients who took part in 16 music therapy sessions, and seven staff, evidenced strong support for music therapy. Patients typically reported experiencing sessions as relaxing, comforting, uplifting, and empowering; >90% would participate by choice and use music therapeutically in the future. Staff endorsed music therapy as valuable therapeutically, reporting that patients engaged enthusiastically and identified sessions as improving their own moods and ward milieu. Conclusions: Integration of music therapy in inpatient treatment of adolescents is feasible and acceptable, and is valued by staff and patients as a complement to ‘talking therapies’. Participation is enjoyed and associated with outcomes including improvement in mood, expression of feelings and social engagement consistent with recovery.

A mixed-methods research approach to the review of competency standards for orthotist/prosthetists in Australia

Aim: The requirement for an allied health workforce is expanding as the global burden of disease increases internationally. To safely meet the demand for an expanded workforce of orthotist/prosthetists in Australia, competency based standards, which are up-to-date and evidence-based, are required. The aims of this study were to determine the minimum level for entry into the orthotic/prosthetic profession; to develop entry level competency standards for the profession; and to validate the developed entry-level competency standards within the profession nationally, using an evidence-based approach. Methods: A mixed-methods research design was applied, using a three-step sequential exploratory design, where step 1 involved collecting and analyzing qualitative data from two focus groups; step 2 involved exploratory instrument development and testing, developing the draft competency standards; and step 3 involved quantitative data collection and analysis – a Delphi survey. In stage 1 (steps 1 and 2), the two focus groups – an expert and a recent graduate group of Australian orthotist/prosthetists – were led by an experienced facilitator, to identify gaps in the current competency standards and then to outline a key purpose, and work roles and tasks for the profession. The resulting domains and activities of the first draft of the competency standards were synthesized using thematic analysis. In stage 2 (step 3), the draft-competency standards were circulated to a purposive sample of the membership of the Australian Orthotic Prosthetic Association, using three rounds of Delphi survey. A project reference group of orthotist/prosthetists reviewed the results of both stages. Results: In stage 1, the expert (n = 10) and the new graduate (n = 8) groups separately identified work roles and tasks, which formed the initial draft of the competency standards. Further drafts were refined and performance criteria added by the project reference group, resulting in the final draft-competency standards. In stage 2, the final draft-competency standards were circulated to 56 members (n = 44 final round) of the Association, who agreed on the key purpose, 6 domains, 18 activities, and 68 performance criteria of the final competency standards. Conclusion: This study outlines a rigorous and evidence-based mixed-methods approach for developing and endorsing professional competency standards, which is representative of the views of the profession of orthotist/prosthetists.

Mixed reality stories: How creative writers integrate virtual and physical realities

Mixed reality stories (MRS) unfold simultaneously in the physical and the virtual world. Advancements in digital technologies, which are now able to capture more contextual information about our physical environments, are enabling novel ways of blending the two worlds. To explore the process of creating stories from this perspective, we conducted a study with creative writers, in which we asked them to write a MRS script for outdoor running. While we saw instances of intentional connections between physical and virtual worlds in their work, we also observed the use of ambiguity or even deliberate contradiction with available contextual information. In this paper we discuss how these approaches can be beneficial for MRS and propose directions for future work.

Being chased by zombies!: Understanding the experience of mixed reality quests

Both researchers and practitioners show increasing interest in exploring mixed reality games: games, where physical environments blend together with digital technologies. In this paper we have extended earlier work by bringing attention to the role of narrative in mixed reality games. For our case study we chose a mobile phone application Zombies Run!, which is designed to support actual running. This application contains a fictional story about a zombie apocalypse and provides runners with various quests (in the form of missions) to complete during their run. We investigated different aspects of participants' experience with the application and how it changed their running. Our findings show how the app changed running in three major ways. Firstly, it changed the way runs were organised. Secondly, it shook up established running routines. And lastly, it shaped the meanings associated with running.

Intuitive interaction in a mixed reality system

Tangible physical systems are more intuitive than Intangible virtual Systems. Mixed reality systems are considered as an alternative to virtual systems, bringing advantages of tangible systems into an interaction. However, past research has mainly focussed on technical aspects of incorporating pervasive-ness and immersive-ness in the virtual systems. This paper reports on an empirical study of intuitive Interaction in a Mixed Reality game system for children and the design aspects that could facilitate intuitive Interaction in such systems. A related samples Friedman’s test showed that the Mixed Reality game system demonstrated more intuitive interactions than non-intuitive Interactions. A linear regression analysis further established that the variation in intuitive Interaction in the Mixed Reality system could be statistically significantly explained primarily by physical affordances offered by the Mixed Reality system and to a lesser extent by the perceived affordances in the system. Design guidelines to develop intuitive Mixed Reality systems are discussed. These guidelines should allow designers to exploit the wonders of advances in technology and at the same time allow users to directly interact with the physical real world. This will allow users to access maximal physical affordances, which are primary contributors to intuitive interaction in Tangible and Mixed Reality systems.

Combining unsupervised and invigilated assessment of introductory programming

We compared student performance on large-scale take-home assignments and small-scale invigilated tests that require competency with exactly the same programming concepts. The purpose of the tests, which were carried out soon after the take home assignments were submitted, was to validate the students' assignments as individual work. We found widespread discrepancies between the marks achieved by students between the two types of tasks. Many students were able to achieve a much higher grade on the take-home assignments than the invigilated tests. We conclude that these paired assessments are an effective way to quickly identify students who are still struggling with programming concepts that we might otherwise assume they understand, given their ability to complete similar, yet more complicated, tasks in their own time. We classify these students as not yet being at the neo-Piagetian stage of concrete operational reasoning.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.