A poroviscohyperelastic model for numerical analysis of mechanical behavior of single chondrocyte

The aim of this paper is to utilize a poroviscohyperelastic (PVHE) model which is developed based on the porohyperelastic (PHE) model to explore the mechanical deformation properties of single chondrocytes. Both creep and relaxation responses are investigated by using FEM models of micropipette aspiration and AFM experiments, respectively. The newly developed PVHE model is compared thoroughly with the SnHS and PHE models. It has been found that the PVHE can accurately capture both creep and stress relaxation behaviors of chondrocytes better than other two models. Hence, the PVHE is a promising model to investigate mechanical properties of single chondrocytes.

A case study of utilising concept knowledge in a topic specific document collection

The use of ‘topic’ concepts has shown improved search performance, given a query, by bringing together relevant documents which use different terms to describe a higher level concept. In this paper, we propose a method for discovering and utilizing concepts in indexing and search for a domain specific document collection being utilized in industry. This approach differs from others in that we only collect focused concepts to build the concept space and that instead of turning a user’s query into a concept based query, we experiment with different techniques of combining the original query with a concept query. We apply the proposed approach to a real-world document collection and the results show that in this scenario the use of concept knowledge at index and search can improve the relevancy of results.

Decision support for the efficient annotation of bioacoustic events

Acoustic sensors allow scientists to scale environmental monitoring over large spatiotemporal scales. The faunal vocalisations captured by these sensors can answer ecological questions, however, identifying these vocalisations within recorded audio is difficult: automatic recognition is currently intractable and manual recognition is slow and error prone. In this paper, a semi-automated approach to call recognition is presented. An automated decision support tool is tested that assists users in the manual annotation process. The respective strengths of human and computer analysis are used to complement one another. The tool recommends the species of an unknown vocalisation and thereby minimises the need for the memorization of a large corpus of vocalisations. In the case of a folksonomic tagging system, recommending species tags also minimises the proliferation of redundant tag categories. We describe two algorithms: (1) a “naïve” decision support tool (16%–64% sensitivity) with efficiency of O(n) but which becomes unscalable as more data is added and (2) a scalable alternative with 48% sensitivity and an efficiency ofO(log n). The improved algorithm was also tested in a HTML-based annotation prototype. The result of this work is a decision support tool for annotating faunal acoustic events that may be utilised by other bioacoustics projects.

Practical analysis of big acoustic sensor data for environmental monitoring

Monitoring the environment with acoustic sensors is an effective method for understanding changes in ecosystems. Through extensive monitoring, large-scale, ecologically relevant, datasets can be produced that can inform environmental policy. The collection of acoustic sensor data is a solved problem; the current challenge is the management and analysis of raw audio data to produce useful datasets for ecologists. This paper presents the applied research we use to analyze big acoustic datasets. Its core contribution is the presentation of practical large-scale acoustic data analysis methodologies. We describe details of the data workflows we use to provide both citizen scientists and researchers practical access to large volumes of ecoacoustic data. Finally, we propose a work in progress large-scale architecture for analysis driven by a hybrid cloud-and-local production-grade website.

Hardware design and implementation of a MAVLink interface for an FPGA-based autonomous UAV flight control system

This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

Schooling elsewhere: Rurality, inclusion and education

Over its history, the International Journal of Inclusive Education has had a strong record of naming, critiquing and redressing the ways in which particular social locations shape experiences of inclusion and exclusion in education. In this special issue, we continue this tradition taking as our focus those who live outside the metropolitan mainstream. To date, rural schools and the communities of which they are part have often been overlooked by researchers of inclusive education. This is not to suggest that the rural has been ignored entirely in research on inclusivity and schooling. For example, a number of studies have included rural case studies as part of broader research on subjects such as educational disadvantage and experiences of poverty (Horgan 2009), inclusivity and early childhood services (Penn 1997), constraints to inclusive educational practice (Shevlin, Winter, and Flynn 2013) and the efficacy of inclusivity training programmes for teachers (Strieker, Logan, and Kuhel 2012). Such work provides a critical reference point for this special issue as it has demon- strated that the educational landscape may be very differently experienced in the rural compared to the urban. Illustrative is Wikeley et al.’s (2009, 381) assertion that working class Irish youth living outside the urban sphere are ‘doubly disadvantaged’ in terms of accessing out-of-school activities and Milovanovic et al.’s (2014, 47) claim that for young children in the Western Balkans, there is a ‘dearth of pre-school provision in rural areas’. As well as highlighting cleavages of disadvantage as they exist between urban and rural schools, work in this journal has also revealed disadvantage that exists within rural schools. This scholarship has explored how particular social locations, such as disability, ethnicity, sexuality, gender and class intersect with rurality to produce very different educational biographies. For example, it may be class, as Holt (2012) found in her study of young rural women’s transition to a city university, or it may be gender, as Tuwor and Sossou (2008) posited in their work on the schooling of girls in West Africa.

Using the WWW to teach undergraduate nurses clinical communication

On-line learning is increasingly being used in nursing education. Nevertheless, there is still insufficient evidence to demonstrate: whether students respond positively when this form of learning is used to teach relatively practical or clinical subjects; whether it is effective; and whether it is fair to students with less access to, or familiarity with, computers and the internet. In 2003, an on-line Unit on clinical communication was developed for Australian undergraduate nurses in partnership between an Australian School of Nursing and the a Department of Clinical Psychology. Students were overwhelmingly positive in their evaluation of the Unit although some regretted the lack of face-to-face contact with tutors and peers. The best aspects of the Unit included the content and structure being perceived as interesting, fun and informative, the relevance of the material for them as nurses, flexibility to work independently, promotion of critical thinking and gaining an understanding of client issues. Neither their evaluation nor their final grades were related to students’ age or whether they preferred on-line or traditional learning. Students who had readily available computer access, however, had better final grades. Also, students’ grades were correlated with how often they accessed the Unit.

A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

When death is not a crime : challenges for police and policing

The over-representation of vulnerable populations within the criminal justice system, and the role of police in perpetuating this, has long been a topic of discussion in criminology. What is less discussed is the way in which non -criminal investigations by police, in areas like a death investigation, may perpetuate similar types of engagement with vulnerable populations. In Australia, as elsewhere, it is the police who are responsible for investigating both suspicious and violent deaths like homicide as well as non - suspicious, violent deaths like accidents and suicides. Police are also the agents tasked with investigating deaths which are neither violent nor suspicious but occur outside hospitals and other care facilities. This paper reports on how the police describe - or are described by others - their role in a non - suspicious death investigation, and the challenges that such investigations raise for police and policing.

Representing team behaviours from noisy data using player role

Due to their unobtrusive nature, vision-based approaches to tracking sports players have been preferred over wearable sensors as they do not require the players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retrieval, having noisy data (i.e. missing and false player detections) is problematic as it generates discontinuities in the input data stream. One method of circumventing this issue is to use an occupancy map, where the field is discretised into a series of zones and a count of player detections in each zone is obtained. A series of frames can then be concatenated to represent a set-play or example of team behaviour. A problem with this approach though is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a role representation to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labeled data.

Polly Pocket

Comprised of ten 3 minute and two 12 minutes animated episodes, featuring Polly Pockets and her friend in numerous adventures.

A three dimensional virtual medical imaging computed tomography suite: Innovation in education

Aims: The Medical Imaging Training Immersive Environment(MITIE) Computed Tomography(CT) system is an innovative virtual reality (VR) platform that allows students to practice a range of CT techniques. The aim of this pilot study was to harvest user feedback about the educational value of teh application and inform future pedagogical development. This presentation explores the use of this technology for skills training. Background: MITIE CT is a 3D VR environment that allows students to position a patient,and set CT technical parameters including IV contrast dose and dose rate. As with VR initiatives in other health disciplines the software mimics clinical practice as much as possible and uses 3D technology to enhance immersion and realism. The software is new and was developed by the Medical Imaging Course Team at a provider University with funding from a Health Workforce Australia 'Simulated Learning Environments' grant Methods: Current third year medical imaging students were provided with additional 1 hour MITIE laboratory tutorials and studnet feedback was collated with regard to educational value and performance. Ethical approval for the project was provided by the university ethics panel Results: This presentation provides qualitative analysis of student perceptions relating to satisfaction, usability and educational value. Students reported high levels of satisfaction and both feedback and assessment results confirmed the application's significance as a pre-clinical tool. There was a clear emerging theme that MITIE could be a useful learning tool that students could access to consolidate their clinical learning, either on campus or during their clinical placement. Conclusion: Student feedback indicates that MITIE CT has a valuable role to play in the clinial skills training for medical imaging students both in the academic and clinical environment. Future work will establish a framework for an appropriate supprting pedagogy that can cross the boundary between the two environments

Do-Rank: DCG optimization for learning-to-rank in tag-based item recommendation systems

Discounted Cumulative Gain (DCG) is a well-known ranking evaluation measure for models built with multiple relevance graded data. By handling tagging data used in recommendation systems as an ordinal relevance set of {negative,null,positive}, we propose to build a DCG based recommendation model. We present an efficient and novel learning-to-rank method by optimizing DCG for a recommendation model using the tagging data interpretation scheme. Evaluating the proposed method on real-world datasets, we demonstrate that the method is scalable and outperforms the benchmarking methods by generating a quality top-N item recommendation list.

Designing hubs for connected learning: social, spatial and technological insights from Coworking, Hackerspaces and Meetup groups

Connected learning, as a design approach, does not restrict learning to a dedicated learning space (school, university, etc.), but considers it to be an aggregation of individual experiences made through intrinsically motivated, active participation in and across various socio-cultural, every-day life environments. Urban places for meeting, interacting and connected learning with people from diverse backgrounds, cultures and areas of expertise are highly significant in the knowledge economy of our 21st century. However, little is yet known about best practices to design and curate such hubs that attract and support interest-driven and socially embedded learning experiences. The research study presented in this paper investigates design aspects that contribute to successful place-based spaces for connected learning. The paper reports findings from observations as well as interviews with users and managers of three different types of local, community-led learning environments, i.e., coworking spaces, hackerspaces, and meetup groups across Australia. The findings reveal social, spatial and technological interventions that these spaces apply to nourish a culture of connected learning, sharing and peer interaction. The discussion suggests a set of design implications for designers, managers and decision makers that have an interest in nourishing a connected learning culture among their user community.