Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

Activities of daily living in children with developmental coordination disorder: Performance, learning, and participation

Background Children with developmental coordination disorder (DCD) face evident motor difficulties in daily functioning. Little is known, however, about their difficulties in specific activities of daily living (ADL). Objective The purposes of this study were: (1) to investigate differences between children with DCD and their peers with typical development for ADL performance, learning, and participation, and (2) to explore the predictive values of these aspects. Design. This was a cross-sectional study. Methods In both a clinical sample of children diagnosed with DCD (n=25 [21 male, 4 female], age range=5-8 years) and a group of peers with typical development (25 matched controls), the children’s parents completed the DCDDaily-Q. Differences in scores between the groups were investigated using t tests for performance and participation and Pearson chi-square analysis for learning. Multiple regression analyses were performed to explore the predictive values of performance, learning, and participation. Results Compared with their peers, children with DCD showed poor performance of ADL and less frequent participation in some ADL. Children with DCD demonstrated heterogeneous patterns of performance (poor in 10%-80% of the items) and learning (delayed in 0%-100% of the items). In the DCD group, delays in learning of ADL were a predictor for poor performance of ADL, and poor performance of ADL was a predictor for less frequent participation in ADL compared with the control group. Limitations A limited number of children with DCD were addressed in this study. Conclusions This study highlights the impact of DCD on children’s daily lives and the need for tailored intervention.

Digital videos in financial accounting: A sociocognitive approach to learning

Understanding the important concepts necessary to undertake the preparation of consolidated financial statements has proven challenging for many accounting undergraduate students. As a result, the development of multimedia modelling concepts such as acquisition analysis, business combination valuation entries, reacquisition entries and intragroup transactions were embedded within an e-learning environment. The principle of modelling, derived from social cognitive theory, was applied to the design of the multimedia. A study was conducted to gauge the effectiveness of the approach and consider student perceptions with regard to learning through this approach. Quantitative data were collected from accounting undergraduate students (n= 464) enrolled across three different cohorts including international campuses (n=386), an Australian campus (n=49) and a distance education cohort (n=29). Analyses were undertaken to show significant differences between these cohorts. This research paper presents findings that indicate a positive and significant association between the number of times the videos were accessed, and the assignment score (p<0.05) was evident, suggesting that students that referred to the videos relatively frequently were able to utilise the knowledge gained from the videos to assist them in completing the assignment.

Analysis of turbulent confined highly swirling flow

We report here a CFD model of highly swirling flow in a quarl burner using three versions of the k-epsilon model. Results for the recirculating zone, the bounding shear layer and the downstream flow are presented. We discuss, with suitable qualifications, how the model predictions can inform our understanding of this class of flows.

Critical Discourse Analysis research methods for the English classroom

Critical Discourse Analysis (CDA) is an approach to analysing the discourses that operate in social contexts, such as classrooms in schools, and their material effects on people, such as teachers and learners. CDA offers a range of ways of engaging with the relationship between texts in context and the power they exercise. In this article, I overview key approaches and provide detail of Fairclough’s (1992, 2003) textually-oriented, linguistic method of CDA, with an example from my own research. I offer a challenge for English teachers, as researchers, to ‘make strange’ the familiar world of their classroom work, and in so doing, identify possibilities for productive change.

The social tasks of learning to become a physical education teacher: Considering the HPE subject department as a community of practice

Initial teacher education (ITE) students participate in various workplaces within schools and in doing so, form understandings about the numerous, and at times competing, expectations of teachers’ work. Through these experiences they form understandings about themselves as health and physical education (HPE) teachers. This paper examines the ways communities of practice within HPE subject department offices function as sites of workplace learning for student teachers. In particular this research focused on how ITE students negotiate tacit and contradictory expectations as well as social tasks during the practicum and the ways in which their understandings are mediated through participation in the workspace. Qualitative methods of survey and semi-structured interview were used to collect data on a cohort of student teachers during and following their major (10 week) practicum experience. Analysis was informed by theories of communities of practice (Wenger, 1998), workplace learning (Billett, 2001), and social task systems (Doyle, 1977). It was evident that considerable effort, attention, and energy was expended on various interrelated social tasks aimed at building positive relationships with their supervisor and other HPE teachers at the school. The social dynamics were highly nuanced and required a game-like approach. In our view the complexity that student teachers must negotiate in striving for an excellent evaluation warrants specific attention in physical education teacher education (PETE) programs. This study raises questions regarding our responsibilities in sending student teachers into contexts that might even be described as toxic. We offer some suggestions for how PETE might better support students going into practicum contexts that might be regarded as problematic workplaces.

With the best of intentions: A critical discourse analysis of HPE curriculum materials

Much of physical education curriculum in the developed world and specifically in Australia tends to be guided in principle by syllabus documents that represent, in varying degrees, some form of government education priorities. Through the use of critical discourse analysis we analyze one such syllabus example (an official syllabus document of one of the Australian States) to explore the relationships between the emancipatory/social justice expectations presented in the rubric of and introduction to the official syllabus document, and the language details of learning outcomes that indicate how the expectations might be satisfied. Given the complexity and multilevel pathways of message systems/ideologies we question the efficacy of such documents oriented around social justice principles to genuinely deliver more radical agendas which promote social change and encourage a preparedness to engage in social action leading to a betterment of society.

In pursuit of becoming a senior coach: The learning culture for Australian Football League coaches

- Background and Purpose Given the turbulent and highly contested environment in which professional coaches work, a prime concern to coach developers is how coaches learn their craft. Understanding the learning and development of senior coaches (SCs) and assistant coaches (ACs) in the Australian Football League (AFL – the peak organisation for Australian Rules Football) is important to better develop the next generation of performance coaches. Hence the focus of this research was to examine the learning of SC and AC in the AFL. Fundamental to this research was an understanding that the AFL and each club within the league be regarded as learning organisations and workplaces with their own learning cultures where learning takes place. The purpose of this paper was to examine the learning culture for AFL coaches. - Method Five SCs, 6 ACs, and 5 administrators (4 of whom were former coaches) at 11 of the 16 AFL clubs were recruited for the research project. First, demographic data were collected for each participant (e.g. age, playing and coaching experience, development and coach development activities). Second, all participants were involved in one semi-structured interview of between 45 and 90 minutes duration. An interpretative (hierarchical content) analysis of the interview data was conducted to identify key emergent themes. - Results Learning was central to AFL coaches becoming a SC. Nevertheless, coaches reported a sense of isolation and a lack of support in developing their craft within their particular learning culture. These coaches developed a unique dynamic social network (DSN) that involved episodic contact with a number of respected confidantes often from diverse fields (used here in the Bourdieuian sense) in developing their coaching craft. Although there were some opportunities in their workplace, much of their learning was unmediated by others, underscoring the importance of their agentic engagement in limited workplace affordances. - Conclusion The variety of people accessed for the purposes of learning (often beyond the immediate workplace) and the long time taken to establish networks of supporters meant that a new way of describing the social networks of AFL coaches was needed; DSN. However, despite the acknowledged utility of learning from others, all coaches reported some sense of isolation in their learning. The sense of isolation brought about by professional volatility in high-performance Australian Football offers an alternative view on Hodkinson, Biesta and James' attempt in overcoming dualisms in learning.

The application of learning analytics to improve learning: Questions from the academy

Since 2007, close collaboration between the Learning and Teaching Unit’s Academic Quality and Standards team and the Department of Reporting and Analysis’ Business Objects team resulted in a generational approach to reporting where QUT established a place of trust. This place of trust is where data owners are confident in date storage, data integrity, reported and shared. While the role of the Department of Reporting and Analysis focused on the data warehouse, data security and publication of reports, the Academic Quality and Standards team focused on the application of learning analytics to solve academic research questions and improve student learning. Addressing questions such as: • Are all students who leave course ABC academically challenged? • Do the students who leave course XYZ stay within the faculty, university or leave? • When students withdraw from a unit do they stay enrolled on full or part load or leave? • If students enter through a particular pathway, what is their experience in comparison to other pathways? • With five years historic reporting, can a two-year predictive forecast provide any insight? In answering these questions, the Academic Quality and Standards team then developed prototype data visualisation through curriculum conversations with academic staff. Where these enquiries were applicable more broadly this information would be brought into the standardised reporting for the benefit of the whole institution. At QUT an annual report to the executive committees allows all stakeholders to record the performance and outcomes of all courses in a snapshot in time or use this live report at any point during the year. This approach to learning analytics was awarded the Awarded 2014 ATEM/Campus Review Best Practice Awards in Tertiary Education Management for The Unipromo Award for Excellence in Information Technology Management.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

Learning experiences in a giant interactive environment: Insights from The Cube

In November 2012, Queensland University of Technology in Australia launched a giant interactive learning environment known as The Cube. This article reports a phenomenographic investigation into visitors’ different experiences of learning in The Cube. At present very little is known about people’s learning experience in spaces featuring large interactive screens. We observed many visitors to The Cube and interviewed 26 people. Our analysis identified critical variation across the visitors’ experience of learning in The Cube. The findings are discussed as the learning strategy (in terms of Absorption, Exploration, Isolation and Collaboration); and the content learned (in terms of Technology, Skills and Topics). Other findings presented here are dimensions of the learning strategy and the content learned, with differing perspectives on each dimension. These outcomes provide early insights into the potential of giant interactive environments to enhance learning approaches and guide the design of innovative learning spaces in higher education.

Ageing and learning as conceptualized by senior adults in two cultures: Hong Kong and Australia

This paper is about a study aimed to understand what successful ageing and later life learning mean to older adults in two cultures: Hong Kong and Australia. Findings from the study were reported in this paper to shed light on: (1) the meaning of ageing and learning as conceptualized by elders in Hong Kong and Australia; (2) the reasons for participation in later life learning, as well as, barriers for non-participation; (3) their learning interests and instructional preferences, and finally (4) the correlation between learning and successful ageing, and between learning and other well-being variables, including health, happiness and satisfaction of elders in Hong Kong and Australia. Two large samples of elders from Hong Kong (n=519) and Queensland, Australia (n=421) participated in the study. Within group analysis of the data from the two locations indicated that there are more similarities, rather than differences, between elders in Hong Kong and Australia with respect to background characteristics, meanings of ageing and learning, reasons for participation, barriers for non-participation, learning interests and instructional preferences.