Threat of resource loss: The role of self-regulation in adaptive task performance

Changes at work are often accompanied with the threat of, or actual, resource loss. Through an experiment, we investigated the detrimental effect of the threat of resource loss on adaptive task performance. Self-regulation (i.e., task focus and emotion control) was hypothesized to buffer the negative relationship between the threat of resource loss and adaptive task performance. Adaptation was conceptualized as relearning after a change in task execution rules. Threat of resource loss was manipulated for 100 participants undertaking an air traffic control task. Using discontinuous growth curve modeling, 2 kinds of adaptation—transition adaptation and reacquisition adaptation—were differentiated. The results showed that individuals who experienced the threat of resource loss had a stronger drop in performance (less transition adaptation) and a subsequent slower recovery (less reacquisition adaptation) compared with the control group who experienced no threat. Emotion control (but not task focus) moderated the relationship between the threat of resource loss and transition adaptation. In this respect, individuals who felt threatened but regulated their emotions performed better immediately after the task change (but not later on) compared with those individuals who felt threatened and did not regulate their emotions as well. However, later on, relearning (reacquisition adaptation) under the threat of resource loss was facilitated when individuals concentrated on the task at hand.

Robust iris recognition using decision fusion and degradation modelling

This thesis investigates the use of fusion techniques and mathematical modelling to increase the robustness of iris recognition systems against iris image quality degradation, pupil size changes and partial occlusion. The proposed techniques improve recognition accuracy and enhance security. They can be further developed for better iris recognition in less constrained environments that do not require user cooperation. A framework to analyse the consistency of different regions of the iris is also developed. This can be applied to improve recognition systems using partial iris images, and cancelable biometric signatures or biometric based cryptography for privacy protection.

Conceptualising recognition of prior learning processes in the age of open learning

This chapter interrogates what recognition of prior learning (RPL) can and does mean in the higher education sector—a sector in the grip of the widening participation agenda and an open access age. The chapter discusses how open learning is making inroads into recognition processes and examines two studies in open learning recognition. A case study relating to e-portfolio-style RPL for entry into a Graduate Certificate in Policy and Governance at a metropolitan university in Queensland is described. In the first instance, candidates who do not possess a relevant Bachelor degree need to demonstrate skills in governmental policy work in order to be eligible to gain entry to a Graduate Certificate (at Australian Qualifications Framework Level 8) (Australian Qualifications Framework Council, 2013, p. 53). The chapter acknowledges the benefits and limitations of recognition in open learning and those of more traditional RPL, anticipating future developments in both (or their convergence).

Functional activation during the Rapid Visual Information Processing task in a middle aged cohort: An fMRI study

The Rapid Visual Information Processing (RVIP) task, a serial discrimination task where task performance believed to reflect sustained attention capabilities, is widely used in behavioural research and increasingly in neuroimaging studies. To date, functional neuroimaging research into the RVIP has been undertaken using block analyses, reflecting the sustained processing involved in the task, but not necessarily the transient processes associated with individual trial performance. Furthermore, this research has been limited to young cohorts. This study assessed the behavioural and functional magnetic resonance imaging (fMRI) outcomes of the RVIP task using both block and event-related analyses in a healthy middle aged cohort (mean age = 53.56 years, n = 16). The results show that the version of the RVIP used here is sensitive to changes in attentional demand processes with participants achieving a 43% accuracy hit rate in the experimental task compared with 96% accuracy in the control task. As shown by previous research, the block analysis revealed an increase in activation in a network of frontal, parietal, occipital and cerebellar regions. The event related analysis showed a similar network of activation, seemingly omitting regions involved in the processing of the task (as shown in the block analysis), such as occipital areas and the thalamus, providing an indication of a network of regions involved in correct trial performance. Frontal (superior and inferior frontal gryi), parietal (precuenus, inferior parietal lobe) and cerebellar regions were shown to be active in both the block and event-related analyses, suggesting their importance in sustained attention/vigilance. These networks and the differences between them are discussed in detail, as well as implications for future research in middle aged cohorts.

Unsupervised Domain Adaptation by Domain Invariant Projection

Domain-invariant representations are key to addressing the domain shift problem where the training and test exam- ples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be di- rectly suitable for such a comparison, since some of the fea- tures may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Domain Invariant Projection approach: An unsupervised domain adaptation method that overcomes this issue by extracting the information that is invariant across the source and tar- get domains. More specifically, we learn a projection of the data to a low-dimensional latent space where the distance between the empirical distributions of the source and target examples is minimized. We demonstrate the effectiveness of our approach on the task of visual object recognition and show that it outperforms state-of-the-art methods on a stan- dard domain adaptation benchmark dataset

Repeatable Condition-Invariant Visual Odometry for Sequence-Based Place Recognition

This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

Enhancing human action recognition with region proposals

Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.

The con-stitutional re-cognition (s)cam-pain: The campaign for the hidden recognition of first nations peoples' racial inferiority

The constitutional recognition campaign has received party-wide support and its efforts have been promoted by Prime Minister Tony Abbott as being something that would ‘complete our Constitution.’ The broader rhetoric surrounding this campaign suggests that it will result in a just, albeit delayed, recognition of indigenous peoples in the Australian legal system. However, beneath the surface of this seemingly benevolent gesture, is a reaffirmation of the colonial subordination and erasure of the several hundred original nations’ peoples and ways of being.

Recognition and enforcement in cross-border insolvency law: A proposal for judicial gap-filling

This Article analyzes the recognition and enforcement of cross-border insolvency judgments from the United States, United Kingdom, and Australia to determine whether the UNCITRAL Model Law’s goal of modified universalism is currently being practiced, and subjects the Model Law to analysis through the lens of international relations theories to elaborate a way forward. We posit that courts could use the express language of the Model Law text to confer recognition and enforcement of foreign insolvency judgments. The adoption of our proposal will reduce costs, maximize recovery for creditors, and ensure predictability for all parties.

Overparenting and homework: The student’s task, but everyone’s responsibility

A high level of parental involvement is widely considered to be essential for optimal child and adolescent development and wellbeing, including academic success. However, recent consideration has been given to the idea that extremely high levels of parental involvement (often called ‘overparenting’ or ‘helicopter parenting’) might not be beneficial. This study used a newly created overparenting measure, the Locke Parenting Scale (LPS), to investigate the association of overparenting and children’s homework. Eight hundred and sixty-six parents completed online questionnaires about their parenting beliefs and intentions, and their attitudes associated with their child’s homework. Parents with higher LPS scores tended to take more personal responsibility for the completion of their child’s homework than did other parents, and ascribed greater responsibility for homework completion to their child’s teacher. However, increased perceived responsibility by parents and teachers was not accompanied by a commensurate reduction in what they perceived was the child’s responsibility. Future research should examine whether extreme parental attitudes and reported behaviours translate to validated changes in actual homework support.

Data distribution and task scheduling for distributed computing of all-to-all comparison problems

This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

Patients with physical debility undergoing subacute physical rehabilitation following an acute hospital admission demonstrated improvement in cognitive functional task independence

Background: Hospitalised older adults often experience a decline in physical functioning and mobility in the lead up to (or during) an acute hospital admission. During acute illness and hospitalisation, older adults may also experience a decline or fluctuation in their cognitive functioning. Previous studies have demonstrated that patients with or without reduced cognitive functioning on admission to subacute inpatient rehabilitation have considerable potential to improve their physical functioning and quality of life.

Robust automatic face clustering in news video

Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.

Can teacher collaboration overcome barriers to interdisciplinary learning in a disciplinary university? A case study using climate change

A teacher network was formed at an Australian university in order to better promote interdisciplinary student learning on the complex social-environmental problem of climate change. Rather than leaving it to students to piece together disciplinary responses, eight teaching academics collaborated on the task of exposing students to different types of knowledge in a way that was more than the summing of disciplinary parts. With a part-time network facilitator providing cohesion, network members were able to teach into each other’s classes, and share material and student activities across a range of units that included business, zoology, marine science, geography and education. Participants reported that the most positive aspects of the project were the collegiality and support for teaching innovation provided by peers. However, participants also reported being time-poor and overworked. Maintaining the collaboration beyond the initial one year project proved difficult because without funding for the network facilitator, participants were unable to dedicate the time required to meet and collaborate on shared activities. In order to strengthen teacher collaboration in a university whose administrative structures are predominantly discipline-based, there is need for recognition of the benefits of interdisciplinary learning to be matched by recognition of the need for financial and other resources to support collaborative teaching initiatives.

Turing and the Trans-Pacific Partnership: Intellectual Property, Public Health, and Access to Essential Medicines

A recent controversy in the United States over drug pricing by Turing Pharmaceuticals AG has raised larger issues in respect of intellectual property, access to medicines, and the Trans-Pacific Partnership (TPP). In August 2015, Turing Pharmaceuticals AG – a private biopharmaceutical company with offices in New York, the United States, and Zug, Switzerland - acquired the exclusive marketing rights to Daraprim in the United States from Impax Laboratories Incorporated. Martin Shkreli, Turing’s Founder and Chief Executive Officer, maintained: “The acquisition of Daraprim and our toxoplasmosis research program are significant steps along Turing’s path of bringing novel medications to patients with serious disorders, some of whom often go undiagnosed and untreated.” He emphasised: “We intend to invest in the development of new drug candidates that we hope will yield an even better clinical profile, and also plan to launch an educational effort to help raise awareness and improve diagnosis for patients with toxoplasmosis.” In September 2015, there was much public controversy over the decision of Martin Shkreli to raise the price of a 62 year old drug, Daraprim, from $US13.50 to $US750 a pill. The drug is particularly useful in respect to the treatment and prevention of malaria, and in the treatment of infections in individuals with HIV/AIDS. Daraprim is listed on the World Health Organization’s (WHO) List of Essential Medicines. In the face of much criticism, Martin Shkreli has said that he will reduce the price of Daraprim. He observed: “We've agreed to lower the price on Daraprim to a point that is more affordable and is able to allow the company to make a profit, but a very small profit.” He maintained: “We think these changes will be welcomed.” However, he has been vague and ambiguous about the nature of the commitment. Notably, the lobby group, Pharmaceutical Research and Manufacturers of America (PhARMA), disassociated itself from the claims of Turing Pharmaceuticals. The group said: “PhRMA members have a long history of drug discovery and innovation that has led to increased longevity and improved lives for millions of patients.” The group noted: “Turing Pharmaceutical is not a member of PhRMA and we do not embrace either their recent actions or the conduct of their CEO.” The biotechnology peak body Biotechnology Industry Organization also sought to distance itself from Turing Pharmaceuticals. A hot topic: United States political debate about access to affordable medicines This controversy over Daraprim is unusual – given the age of drug concerned. Daraprim is not subject to patent protection. Nonetheless, there remains a monopoly in respect of the marketplace. Drug pricing is not an isolated problem. There have been many concerns about drug pricing – particularly in respect of essential medicines for HIV/AIDS, tuberculosis, and malaria. This recent controversy is part of a larger debate about access to affordable medicines. The dispute raises larger issues about healthcare, consumer rights, competition policy, and trade. The Daraprim controversy has provided impetus for law reform in the US. US Presidential Candidate Hillary Clinton commented: “Price gouging like this in this specialty drug market is outrageous.” In response to her comments, the Nasdaq Biotechnology Index fell sharply. Hillary Clinton has announced a prescription drug reform plan to protect consumers and promote innovation – while putting an end to profiteering. On her campaign site, she has emphasised that “affordable healthcare is a basic human right.” Her rival progressive candidate, Bernie Sanders, was also concerned about the price hike. He wrote a letter to Martin Shkreli, complaining about the price increase for the drug Daraprim. Sanders said: “The enormous, overnight price increase for Daraprim is just the latest in a long list of skyrocketing price increases for certain critical medications.” He has pushed for reforms to intellectual property to make medicines affordable. The TPP and intellectual property The Daraprim controversy and political debate raises further issues about the design of the TPP. The dispute highlights the dangers of extending the rights of pharmaceutical drug companies under intellectual property, investor-state dispute settlement, and drug administration. Recently, the civil society group Knowledge Ecology International published a leaked draft of the Intellectual Property Chapter of the TPP. Knowledge Ecology International Director, James Love, was concerned the text revealed that the US “continues to be the most aggressive supporter of expanded intellectual property rights for drug companies.” He was concerned that “the proposals contained in the TPP will harm consumers and in some cases block innovation.” James Love feared: “In countless ways, the Obama Administration has sought to expand and extend drug monopolies and raise drug prices.” He maintained: “The astonishing collection of proposals pandering to big drug companies make more difficult the task of ensuring access to drugs for the treatment of cancer and other diseases and conditions.” Love called for a different approach to intellectual property and trade: “Rather than focusing on more intellectual property rights for drug companies, and a death-inducing spiral of higher prices and access barriers, the trade agreement could seek new norms to expand the funding of medical research and development (R&D) as a public good, an area where the US has an admirable track record, such as the public funding of research at the National Institutes of Health (NIH) and other federal agencies.” In addition, there has been much concern about the Investment Chapter of the TPP. The investor-state dispute settlement regime would enable foreign investors to challenge government policy making, which affected their investments. In the context of healthcare, there is a worry that pharmaceutical drug companies will deploy their investor rights to challenge public health measures – such as, for instance, initiatives to curb drug pricing and profiteering. Such concerns are not merely theoretical. Eli Lilly has brought an investor action against the Canadian Government over the rejection of its drug patents under the investor-state dispute settlement regime of the North American Free Trade Agreement (NAFTA). The Health Annex to the TPP also raises worries that pharmaceutical drug companies will able to object to regulatory procedures in respect of healthcare. It is disappointing that the TPP – in the leaks that we have seen – has only limited recognition of the importance of access to essential medicines. There is a need to ensure that there are proper safeguards to provide access to essential medicines – particularly in respect of HIV/AIDs, malaria, and tuberculosis. Moreover, there must be protection against drug profiteering and price gouging in any trade agreement. There should be strong measures against the abuse of intellectual property rights. The dispute over Turing Pharmaceuticals AG and Daraprim is an important cautionary warning in respect of some of the dangers present in the secret negotiations in respect of the TPP. There is a need to preserve consumer rights, competition policy, and public health in trade negotiations over an agreement covering the Pacific Rim.