The effect of autonomy transparency in human-robot interactions : a preliminary study on operator cognitive workload and situation awareness in multiple heterogeneous UAV management

The autonomous capabilities in collaborative unmanned aircraft systems are growing rapidly. Without appropriate transparency, the effectiveness of the future multiple Unmanned Aerial Vehicle (UAV) management paradigm will be significantly limited by the human agent’s cognitive abilities; where the operator’s CognitiveWorkload (CW) and Situation Awareness (SA) will present as disproportionate. This proposes a challenge in evaluating the impact of robot autonomous capability feedback, allowing the human agent greater transparency into the robot’s autonomous status - in a supervisory role. This paper presents; the motivation, aim, related works, experiment theory, methodology, results and discussions, and the future work succeeding this preliminary study. The results in this paper illustrates that, with a greater transparency of a UAV’s autonomous capability, an overall improvement in the subjects’ cognitive abilities was evident, that is, with a confidence of 95%, the test subjects’ mean CW was demonstrated to have a statistically significant reduction, while their mean SA was demonstrated to have a significant increase.

Cost-effective biodiversity restoration with uncertain growth in forest habitat quality

This paper develops a dynamic model for cost-effective selection of sites for restoring biodiversity when habitat quality develops over time and is uncertain. A safety-first decision criterion is used for ensuring a minimum level of habitats, and this is formulated in a chance-constrained programming framework. The theoretical results show; (i) inclusion of quality growth reduces overall cost for achieving a future biodiversity target from relatively early establishment of habitats, but (ii) consideration of uncertainty in growth increases total cost and delays establishment, and (iii) cost-effective trading of habitat requires exchange rate between sites that varies over time. An empirical application to the red listed umbrella species - white-backed woodpecker - shows that the total cost of achieving habitat targets specified in the Swedish recovery plan is doubled if the target is to be achieved with high reliability, and that equilibrating price on a habitat trading market differs considerably between different quality growth combinations. © 2013 Elsevier GmbH.

Cost-effective suppression and eradication of invasive predators

Introduced predators can have pronounced effects on naïve prey species; thus, predator control is often essential for conservation of threatened native species. Complete eradication of the predator, although desirable, may be elusive in budget-limited situations, whereas predator suppression is more feasible and may still achieve conservation goals. We used a stochastic predator-prey model based on a Lotka-Volterra system to investigate the cost-effectiveness of predator control to achieve prey conservation. We compared five control strategies: immediate eradication, removal of a constant number of predators (fixed-number control), removal of a constant proportion of predators (fixed-rate control), removal of predators that exceed a predetermined threshold (upper-trigger harvest), and removal of predators whenever their population falls below a lower predetermined threshold (lower-trigger harvest). We looked at the performance of these strategies when managers could always remove the full number of predators targeted by each strategy, subject to budget availability. Under this assumption immediate eradication reduced the threat to the prey population the most. We then examined the effect of reduced management success in meeting removal targets, assuming removal is more difficult at low predator densities. In this case there was a pronounced reduction in performance of the immediate eradication, fixed-number, and lower-trigger strategies. Although immediate eradication still yielded the highest expected minimum prey population size, upper-trigger harvest yielded the lowest probability of prey extinction and the greatest return on investment (as measured by improvement in expected minimum population size per amount spent). Upper-trigger harvest was relatively successful because it operated when predator density was highest, which is when predator removal targets can be more easily met and the effect of predators on the prey is most damaging. This suggests that controlling predators only when they are most abundant is the "best" strategy when financial resources are limited and eradication is unlikely. © 2008 Society for Conservation Biology.

Resource allocation in two species systems: Is it worth acknowledging species interactions?

It is becoming increasingly popular to consider species interactions when managing ecological foodwebs. Such an approach is useful in determining how management can affect multiple species, with either beneficial or detrimental consequences. Identifying such actions is particularly valuable in the context of conservation decision making as funding is severely limited. This paper outlines a new approach that simplifies the resource allocation problem in a two species system for a range of species interactions: independent, mutualism, predator-prey, and competitive exclusion. We assume that both species are endangered and we do not account for decisions over time. We find that optimal funding allocation is to the conservation of the species with the highest marginal gain in expected probability of survival and that, across all except mutualist interaction types, optimal conservation funding allocation differs between species. Loss in efficiency from ignoring species interactions was most severe in predator-prey systems. The funding problem we address, where an ecosystem includes multiple threatened species, will only become more commonplace as increasing numbers of species worldwide become threatened. © 2011 Elsevier B.V.

Live from the Sydney Opera House: Remote musical interactions for teacher professional development

A significant challenge for the implementation of the Australian Curriculum: The Arts is the professional development of primary school teachers in all parts of the country. During 2012, the Sydney Symphony Orchestra (SSO) conducted a remote music professional development workshop as part of the Sydney Opera House’s Digital Education Program for teachers in New South Wales using the Department of Education’s Connected Classroom system which allows live synchronous interaction between facilitators and participants in multiple sites. In this article, we analyse observational and videotape data collected during this live professional development event to consider the opportunities and challenges presented by this type of professional learning experience in the arts. In particular, consideration is given to the impact of a remote musical interaction on embodied learning and aesthetic experience. We draw on actor-network theory to consider the ways in which a remote professional development experience differs to one in which all participants are present in the same space. Finally, we conclude that although there are significant differences in the type of learning that occurs in a remote music interaction, the online space provides a legitimate and potentially transforming experience for primary school teachers.

Is group more cost effective than individual cognitive behaviour therapy? The evidence is not solid yet

This paper critically evaluates the empirical evidence of 36 studies regarding the comparative cost-effectiveness of group and individual cognitive behaviour therapy (CBT) as a whole, and also for specific mental disorders (e.g. depression, anxiety, substance abuse) or populations (e.g. children). Methods of calculating costs, as well as methods of comparing treatment outcomes were appraised and criticized. Overall, the evidence that group CBT is more cost-effective than individual CBT is mixed, with group CBT appearing to be more cost effective in treating depression and children, but less cost effective in treating drugs and alcohol dependence, anxiety and social phobias. In addition, methodological weaknesses in the studies assessed are noted. There is a need to improve cost calculation methodology, as well as more solid and a greater number of empirical cost-effectiveness studies before a firm conclusion can be reached that group CBT is more cost effective then individual CBT.

The culture of young women's drinking: Implications for developing effective policing strategies. Report to National Drug Strategy Law Enforcement Committee

Alcohol-related mortality and morbidity represents a substantial financial burden on communities across the world. Adolescence and young adulthood is a peak period for heavy episodic alcohol consumption, with over a third of all people aged 14-19 years having been at risk of acute alcoholrelated harm at least once in the previous 12 months (Australian Institute of Health and Welfare [AIHW], 2011). Excessive alcohol consumption has long been seen as a male problem; however, a gradual shift towards a social acceptance of female drunkenness has narrowed the gap in drinking quantity and style between men and women (Grucza, Bucholz, Rice, & Bierut, 2008). The presented data point to the vulnerability of women to the consequences of acute alcohol intoxication and indicate that alcohol-related offending by women is on the rise. Taken together, these findings reveal that alcohol-related harms and aggression for young women are becoming more prevalent and problematic. This report addressed these issues from a policing perspective...

Key beliefs of hospital nurses’ hand-hygiene behaviour: Protecting your peers and needing effective reminders

Issues addressed: Hand hygiene in hospitals is vital to limit the spread of infections. This study aimed to identify key beliefs underlying hospital nurses’ hand-hygiene decisions to consolidate strategies that encourage compliance. Methods: Informed by a theory of planned behaviour belief framework, nurses from 50 Australian hospitals (n = 797) responded to how likely behavioural beliefs (advantages and disadvantages), normative beliefs (important referents) and control beliefs (barriers) impacted on their hand-hygiene decisions following the introduction of a national ‘5 moments for hand hygiene’ initiative. Two weeks after completing the survey, they reported their hand-hygiene adherence. Stepwise regression analyses identified key beliefs that determined nurses’ hand-hygiene behaviour. Results: Reducing the chance of infection for co-workers influenced nurses’ hygiene behaviour, with lack of time and forgetfulness identified as barriers. Conclusions: Future efforts to improve hand hygiene should highlight the potential impact on colleagues and consider strategies to combat time constraints, as well as implementing workplace reminders to prompt greater hand-hygiene compliance. So what? Rather than emphasising the health of self and patients in efforts to encourage hand-hygiene practices, a focus on peer protection should be adopted and more effective workplace reminders should be implemented to combat forgetting.

Achievement unlocked: Investigating the design of effective gamification experiences for mobile applications and devices

This thesis investigates the design of motivating and engaging software experiences. In particular it examines the use of video game elements in non-game contexts, known as gamification, and how to effectively design gamification experiences for smartphone applications. The original contribution of this thesis is a novel framework for designing gamification, derived from an iterative process of evaluating gamified prototypes. The outcomes of this research can help us to better understand the impact of gamification in today's society and how it can be used to design more effective software.

Investigating a model of mentoring for effective teaching

This paper investigates a five-factor model of mentoring for effective teaching. A survey was administered to 218 student teachers after student teaching to provide insights into their mentoring experience. Results indicated the five factors, namely, personal attributes, system requirements, pedagogical knowledge, modeling, and feedback, had Cronbach alpha scores of .93, .81, .95, .91, and .91, respectively with mean scale scores ranging from 4.20 to 4.60 (p< .001). Items associated with each factor were analyzed; the lowest percentage response was reviewing lesson plans (71%) and the highest percentage was modeling effective teaching practices (96%). Triangulated data from the survey results suggested that the practices implemented by the mentor teachers were perceived to have supported the student teachers’ development during student teaching. Implications of this study suggest that actively engaging mentor teachers who apply the principles outlined by the five factor areas will serve to ensure highly effective support for the development of student teachers.

Centroid training to achieve effective text classification

Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

Development of a cost-effective and flexible vibration DAQ system for long-term continuous structural health monitoring

In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

Effective removal of zinc (II) from aqueous solutions by tricalcium aluminate (C3A)

Recently, studies have identified high zinc levels in various environmental resources, and excessive intake of zinc has long been considered to be harmful to human health. The aim of this research was to investigate the effectiveness of tricalcium aluminate (C3A) as a removal agent of zinc from aqueous solution. Inductively coupled plasma-atomic emission spectrometer (ICP-AES), X-ray diffraction (XRD) and scanning electron microscopy (SEM) have been used to characterize such removal behavior. The effects of various factors such as pH influence, temperature and contact time were investigated. The adsorption capacity of C3A for Zn2+ was computed to be up to 13.73 mmol g−1, and the highest zinc removal capacity was obtained when the initial pH of Zn(NO3)2 solution was between 6.0 and 7.0, with temperature around 308 K. The XRD analysis showed that the resultant products were ZnAl-LDHs. Combined with the analysis of solution component, it was proved the existence of both precipitation and cation exchange in the removal process. From the experimental results, it was clear that C3A could be potentially used as a cost-effective material for the removal of zinc in aqueous environment.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.