Enhancing the teaching and learning of mathematical visual images

The literacy demands of mathematics are very different to those in other subjects (Gough, 2007; O'Halloran, 2005; Quinnell, 2011; Rubenstein, 2007) and much has been written on the challenges that literacy in mathematics poses to learners (Abedi and Lord, 2001; Lowrie and Diezmann, 2007, 2009; Rubenstein, 2007). In particular, a diverse selection of visuals typifies the field of mathematics (Carter, Hipwell and Quinnell, 2012), placing unique literacy demands on learners. Such visuals include varied tables, graphs, diagrams and other representations, all of which are used to communicate information.

BP-XACML: An authorisation policy language for business processes

XACML has become the defacto standard for enterprise- wide, policy-based access control. It is a structured, extensible language that can express and enforce complex access control policies. There have been several efforts to extend XACML to support specific authorisation models, such as the OASIS RBAC profile to support Role Based Access Control. A number of proposals for authorisation models that support business processes and workflow systems have also appeared in the literature. However, there is no published work describing an extension to allow XACML to be used as a policy language with these models. This paper analyses the specific requirements of a policy language to express and enforce business process authorisation policies. It then introduces BP-XACML, a new profile that extends the RBAC profile for XACML so it can support business process authorisation policies. In particular, BP-XACML supports the notion of tasks, and constraints at the level of a task instance, which are important requirements in enforcing business process authorisation policies.

How everyday language can and will boost effective information retrieval

Typing 2 or 3 keywords into a browser has become an easy and efficient way to find information. Yet, typing even short queries becomes tedious on ever shrinking (virtual) keyboards. Meanwhile, speech processing is maturing rapidly, facilitating everyday language input. Also, wearable technology can inform users proactively by listening in on their conversations or processing their social media interactions. Given these developments, everyday language may soon become the new input of choice. We present an information retrieval (IR) algorithm specifically designed to accept everyday language. It integrates two paradigms of information retrieval, previously studied in isolation; one directed mainly at the surface structure of language, the other primarily at the underlying meaning. The integration was achieved by a Markov machine that encodes meaning by its transition graph, and surface structure by the language it generates. A rigorous evaluation of the approach showed, first, that it can compete with the quality of existing language models, second, that it is more effective the more verbose the input, and third, as a consequence, that it is promising for an imminent transition from keyword input, where the onus is on the user to formulate concise queries, to a modality where users can express more freely, more informal, and more natural their need for information in everyday language.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

Enhanced student learning in accounting utilising web-based technology, peer-review feedback and reflective practices: A learning community approach to assessment

Higher education is becoming a major driver of economic competitiveness in an increasingly knowledge-driven global economy. Maintaining the competitive edge has seen an increase in public accountability of higher education institutions through the mechanism of ranking universities based on the quality of their teaching and learning outcomes. As a result, assessment processes are under scrutiny, creating tensions between standardisation and measurability and the development of creative and reflective learners. These tensions are further highlighted in the context of large undergraduate subjects, learner diversity and time-poor academics and students. Research suggests that high level and complex learning is best developed when assessment, combined with effective feedback practices, involves students as partners in these processes. This article reports on a four-phase, cross-institution and cross-discipline project designed to embed peer-review processes as part of the assessment in two large, undergraduate accounting classes. Using a social constructivist view of learning, which emphasises the role of both teacher and learner in the development of complex cognitive understandings, we undertook an iterative process of peer review. Successive phases built upon students’ feedback and achievements and input from language/learning and curriculum experts to improve the teaching and learning outcomes.

Problems with the coronial determination of ‘suicide’

After over 100 years of constant dissatisfaction with the accuracy of suicide data, this paper suggests that the problem may actually lie with the category of suicide itself. In almost all previous research, ‘suicide’ is taken to be a self-evidently valid category of death, not an object of study in its own right. Instead, the focus in this paper is upon the presupposition that how a social fact like suicide is counted depends upon norms for its governmental regulation, leading to a reciprocal relationship between social norms and statistical norms. Since this relationship is centred almost entirely in the coroner’s office, this paper examines governmental, definitional and categorisational issues relating to how coroners reach findings of suicide. The intention of this paper is to contribute to international debates over how suicide can best be conceptualised and adjudged.

An exploratory study of the current assessment practices for improving the learning of English as a foreign language (EFL) in two Vietnamese universities

This case study investigated EFL assessment practices at one public and one private university to explore the support of assessment for English language learning (ELL) within the Vietnamese sociocultural context. Findings demonstrated the potential of assessment to engage students in learning; enhance their understanding of the learning objectives; and facilitate their learning reflection. Findings also identified strong influences of contextual factors such as teachers' language assessment literacy, high-stakes testing and institutional administrative policies on the practices of assessment for ELL. This study contributes to research on Assessment for Learning and EFL education at tertiary level in Vietnam and other similar sociocultural contexts.

Bayesian computational methods for spatial analysis of images

This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

Futile treatment in hospital: Doctors’ intergroup language

Treatment that will not provide significant net benefit at the end of a person’s life (called futile treatment) is considered by many people to represent a major problem in the health sector, as it can waste resources and raise significant ethical issues. Medical treatment at the end of life involves a complex negotiation that implicates intergroup communication between health professionals, patients, and families, as well as between groups of health professionals. This study, framed by intergroup language theory, analyzed data from a larger project on futile treatment, in order to examine the intergroup language associated with futile treatment. Hospital doctors (N = 96) were interviewed about their understanding of treatment given to adult patients at the end of life that they considered futile. We conducted a discourse analysis on doctors’ descriptions of futile treatment provided by themselves and their in-group and out-group colleagues. Results pointed to an intergroup context, with patients, families, and colleagues as out-groups. In their descriptions, doctors justified their own decisions using the language of logic, ethics, and respect. Patients and families, however, were characterized in terms of wishing and wanting, as were outgroup colleagues. In addition, out-group doctors were described in strongly negative intergroup language.

Habitus realisation: Negotiating identities through Chinese looks and Chinese language

The increasing linguistic and cultural diversity of our contemporary world points to the salience of maintaining and developing Heritage Language of ethnic minority groups. The mutually constitutive effect between Heritage Language learning and ethnic identity construction has been well documented in the literature. Classical social psychological work often quantitatively structures this phenomenon in a predictable linear relationship. In contrast, poststructural scholarship draws on qualitative approaches to claim the malleable and multiple dynamics behind the phenomenon. The two schools oppose but complement each other. Nevertheless, both schools struggle to capture the detailed and nuanced construction of ethnic identity through Heritage Language learning. Different from the extant research, we make an attempt to ethno-methodologically unearth the nuisances and predicaments embedded in the reflexive, subtle, and multi-layered identity constructions through nuanced, inter-nested language practices. Drawing on data from the qualitative phase of a large project, we highlight some small but powerful moments abstracted from the interview accounts of five Chinese Australian young people. Firstly, we zoom in on the life politics behind the ‘seen but unnoticed’ stereotype that looking Chinese means being able to speak Chinese. Secondly, we speculate the power relations between the speaker and the listener through the momentary and inadvertent breaches of the taken-for-granted stereotype. Next, we unveil how learning Chinese has become an accountably rational priority for these young Chinese Australians. Finally, we argue that the normalised stereotype becomes visible and hence stable when it is breached – a practical accomplishment that we term ‘habitus realisation’.

Perubahan bahasa dalam perspektif Pre neogrammarian dan Neogrammarian dan Pengajaran bahasa dalam konteks EFL (Pre-Neogrammarian and Neogrammarians’ language change and English language pedagogy in EFL contexts)

This article describes different perspectives in response to language change, and aligns the perspectives of language change to English language pedagogy in non-English speaking contexts. The Pre-Neogrammarian and Neo-grammarian linguists that believe the change leads to respectively language decay or language existence will be outlined. This article suggests that the theories derived from both perspectives can be applied to any language. Once there is cultural contact between languages, the dominant language tends to suppress the non-dominant language. Hence, besides focusing on changes that happen in English and the effects of the changes into this language, this article also considers that other language—in this case EFL teachers’ “local language”—experiences an adverse change as the result of the speakers’ interaction with English. Then, this article also describes how the changes might lead to EFL teachers’ adaptation in their practice and cause teachers’ dilemmas.

Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture

We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

Fluid registration of diffusion tensor images using information theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

Active fibers: Matching deformable tract templates to diffusion tensor images

Reliable quantitative analysis of white matter connectivity in the brain is an open problem in neuroimaging, with common solutions requiring tools for fiber tracking, tractography segmentation and estimation of intersubject correspondence. This paper proposes a novel, template matching approach to the problem. In the proposed method, a deformable fiber-bundle model is aligned directly with the subject tensor field, skipping the fiber tracking step. Furthermore, the use of a common template eliminates the need for tractography segmentation and defines intersubject shape correspondence. The method is validated using phantom DTI data and applications are presented, including automatic fiber-bundle reconstruction and tract-based morphometry. © 2009 Elsevier Inc. All rights reserved.