Task modeling for collaborative authoring

Motivation ?Task analysis for designing modern collaborative work needs a more fine grained approach. Especially in a complex task domain, like collaborative scientific authoring, when there is a single overall goal that can only be accomplished only by collaboration between multiple roles, each requiring its own expertise. We analyzed and re-considered roles, activities, and objects for design for complex collaboration contexts. Our main focus is on a generic approach to design for multiple roles and subtasks in a domain with a shared overall goal, which requires a detailed approach. Collaborative authoring is our current example. This research is incremental: an existing task analysis approach (GTA) is reconsidered by applying it to a case of complex collaboration. Our analysis shows that designing for collaboration indeed requires a refined approach to task modeling: GTA, in future, will need to consider tasks at the lowest level that can be delegated or mandates. These tasks need to be analyzed and redesigned in more in detail, along with the relevant task object.

Plasma nanoscience : from nano-solids in plasmas to nano-plasmas in solids

The unique plasma-specific features and physical phenomena in the organization of nanoscale soild-state systems in a broad range of elemental composition, structure, and dimensionality are critically reviewed. These effects lead to the possibility to localize and control energy and matter at nanoscales and to produce self-organized nano-solids with highly unusual and superior properties. A unifying conceptual framework based on the control of production, transport, and self-organization of precursor species is introduced and a variety of plasma-specific non-equilibrium and kinetics-driven phenomena across the many temporal and spatial scales is explained. When the plasma is localized to micrometer and nanometer dimensions, new emergent phenomena arise. The examples range from semiconducting quantum dots and nanowires, chirality control of single-walled carbon nanotubes, ultra-fine manipulation of graphenes, nano-diamond, and organic matter to nano-plasma effects and nano-plasmas of different states of matter. © 2013 Taylor and Francis Group, LLC.

Influence of the diesel fuel sulfur content on the formation of nanoparticles

In recent years fine and ultra fine particles emitted from internal combustion engines have attracted an increasing level of attention. This attention has arisen from epidemiological studies conducted by a number of research groups and pointing to the health effects resulting from inhalation of fine particles. Previous studies on the influence of fuel sulfur level on diesel vehicle emissions were mainly concentrated on particle mass emissions. This study aims at investigating the influence of the reduction of diesel fuel sulfur level on the emission and formation of nanoparticles

Dispersion of zero valent iron nanoparticles onto bentonites and the decolourization of orange II

Nano Zero valent iron (Fe0) were reported as an effective material for azo dye removal, however, similar to other nano-materials, ultra-fine powder has a strong tendency to agglomerate into larger particles, resulting in an adverse effect on both effective surface area and catalyst performance. Here we report nano sized Fe0 particles dispersed onto the surface of natural bentonites. X-ray diffraction was used to study the sample phases. Scanning electron microscopy and transmission electron microscopy were applied to study the morphology and morphological changes. Spherical individual Fe0 particles were observed after dispersion onto bentonites, and these samples were used for orange II (OII) decolourization with wide working pH range. Higher reactivity is attributed to good dispersion of Fe0 particles on clay minerals’ surface. This study is significant for providing novel modified clay based catalyst materials for the decolourization of azo dye contaminants from wastewater.

A policy model for access control using building information models

Building information models have created a paradigm shift in how buildings are built and managed by providing a dynamic repository for building data that is useful in many new operational scenarios. This change has also created an opportunity to use building information models as an integral part of security operations and especially as a tool to facilitate fine-grained access control to building spaces in smart buildings and critical infrastructure environments. In this paper, we identify the requirements for a security policy model for such an access control system and discuss why the existing policy models are not suitable for this application. We propose a new policy language extension to XACML, with BIM specific data types and functions based on the IFC specification, which we call BIM-XACML.

An efficient and robust system for multi-person event detection in real world indoor surveillance scenes

Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

Creative occupations as knowledge practices : innovation and precarity in the creative economy

The ARC Centre of Excellence in Creative Industries and Innovation (herewith CCI) was established with two simple policy objectives. One was to assess anecdotal and boosterish claims about the growth rates of the creative industries, and hence, to measure the size of the creative industries contribution to gross domestic product (GDP). The other was to ascertain the contribution of the creative industries to employment. Preliminary research detailed in Cunningham and Higgs (2009) showed that the existing industrial classifications did not incorporate the terminology of the creative industries, nor did they disaggregate new categories of digital work such as video games. However, we discovered that occupational codes provide a much more fine-grained account of work that would enable us to disaggregate and track economic activity that corresponded to creative industries terminology. Thus was born one major centrepiece of CCI research – the tracking of national occupational codes in pursuit of measuring creative industries policy outcomes. This paper commences with some description of empirical work that investigates creative occupations; however, the real point is to suggest that this type of detailed, occupation-based empirical work has important theoretical potential that has not yet been fully expended (though see Cunningham 2013; Hearn and Bridgstock 2014; Bakhshi, Freeman and Higgs 2013; Hartley and Potts 2014).

Evaluation of features for leaf classification in challenging conditions

Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

Fred’s Flow (Canada) and Murphy Well (Australia) : thick komatiitic lava flows with contrasting compositions, emplacement mechanisms and water contents

Two Archaean komatiitic flows, Fred’s Flow in Canada and the Murphy Well Flow in Australia, have similar thicknesses (120 and 160 m) but very different compositions and internal structures. Their contrasting differentiation profiles are keys to determine the cooling and crystallization mechanisms that operated during the eruption of Archaean ultramafic lavas. Fred’s Flow is the type example of a thick komatiitic basalt flow. It is strongly differentiated and consists of a succession of layers with contrasting textures and compositions. The layering is readily explained by the accumulation of olivine and pyroxene in a lower cumulate layer and by evolution of the liquid composition during downward growth of spinifex-textured rocks within the upper crust. The magmas that erupted to form Fred’s Flow had variable compositions, ranging from 12 to 20 wt% MgO, and phenocryst contents from 0 to 20 vol%. The flow was emplaced by two pulses. A first ~20-m-thick pulse was followed by another more voluminous but less magnesian pulse that inflated the flow to its present 120 m thickness. Following the second pulse, the flow crystallized in a closed system and differentiated into cumulates containing 30–38 wt% MgO and a residual gabbroic layer with only 6 wt% MgO. The Murphy Well Flow, in contrast, has a remarkably uniform composition throughout. It comprises a 20-m-thick upper layer of fine-grained dendritic olivine and 2–5 vol% amygdales, a 110–120 m intermediate layer of olivine porphyry and a 20–30 m basal layer of olivine orthocumulate. Throughout the flow, MgO contents vary little, from only 30 to 33 wt%, except for the slightly more magnesian basal layer (38–40 wt%). The uniform composition of the flow and dendritic olivine habits in the upper 20 m point to rapid cooling of a highly magnesian liquid with a composition like that of the bulk of the flow. Under equilibrium conditions, this liquid should have crystallized olivine with the composition Fo94.9, but the most magnesian composition measured by electron microprobe in samples from the flow is Fo92.9. To explain these features, we propose that the parental liquid contained around 32 wt% MgO and 3 wt% H2O. This liquid degassed during the eruption, creating a supercooled liquid that solidified quickly and crystallized olivine with non-equilibrium textures and compositions.

Developing young students’ meta-representational competence through integrated mathematics and science investigations

This paper describes students’ developing meta-representational competence, drawn from the second phase of a longitudinal study, Transforming Children’s Mathematical and Scientific Development. A group of 21 highly able Grade 1 students was engaged in mathematics/science investigations as part of a data modelling program. A pedagogical approach focused on students’ interpretation of categorical and continuous data was implemented through researcher-directed weekly sessions over a 2-year period. Fine-grained analysis of the developmental features and explanations of their graphs showed that explicit pedagogical attention to conceptual differences between categorical and continuous data was critical to development of inferential reasoning.

Portal-based support for mental health research

This paper describes experiences with the use of the Globus toolkit and related technologies for development of a secure portal that allows nationally-distributed Australian researchers to share data and application programs. The portal allows researchers to access infrastructure that will be used to enhance understanding of the causes of schizophrenia and advance its treatment, and aims to provide access to a resource that can expand into the world’s largest on-line collaborative mental health research facility. Since access to patient data is controlled by local ethics approvals, the portal must transparently both provide and deny access to patient data in accordance with the fine-grained access permissions afforded individual researchers. Interestingly, the access protocols are able to provide researchers with hints about currently inaccessible data that may be of interest to them, providing them the impetus to gain further access permissions.

Refactoring Service Interface to Support Artefact-centric Service interaction

The growth of APIs and Web services on the Internet, especially through larger enterprise systems increasingly being leveraged for Cloud and software-as-a-service opportunities, poses challenges for improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operations having multiple data entities and parameter sets, supporting varying requests, and reflecting versioning across different system releases, compared to fine-grained operations of contemporary interfaces. We propose a technique to support the refactoring of service interfaces by deriving business entities and their relationships. In this paper, we focus on the behavioural aspects of service interfaces, aiming to discover the sequential dependencies of operations (otherwise known as protocol extraction) based on the entities and relationships derived. Specifically, we propose heuristics according to these relationships, and in turn, deriving permissible orders in which operations are invoked. As a result of this, service operations can be refactored on business entity CRUD lines, with explicit behavioural protocols as part of an interface definition. This supports flexible service discovery, composition and integration. A prototypical implementation and analysis of existing Web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms proposed through the paper.

'I wonder what you know...': Teachers designing requests for factual information

The early years are significant in optimising children’s educational, emotional and social outcomes and have become a major international policy priority. Within Australia, policy levers have prioritised early childhood education, with a focus on program quality, as it is associated with lifelong success. Longitudinal studies have found that high quality teacher-child interactions are an essential element of high quality programs, and teacher questioning is one aspect of teacher-child interactions that has been attributed to affecting the quality of education, linking open ended questioning to higher cognitive achievement. Teachers, however, overwhelmingly ask more closed than open questions. In the classroom, like everyday interaction, questions in interaction require answers. They are used to request, offer, repair, challenge, seek agreement (Curl & Drew, 2008; Enfield, Stivers, & Levinson, 2010; Hayano, 2013; Schegloff, 2007). Teachers use questions to set agendas and manage lessons (McHoul, 1978; Mehan, 1979; Sacks, 1995), and to gauge students’ knowledge and understanding (Lerner, 1995; McHoul, 1978; Mehan, 1979). Drawing on data from the Australian Research Council project Interacting with Knowledge: Interacting with people: Web searching in early childhood, this paper focuses on an extended sequence of talk between a teacher with two students aged between 3.5 and 5 years in a preschool classroom. The episode, drawn from a corpus of over 200 hours of video recorded data, captures how the teacher and children undertake an online search for images of lady beetles and hairy caterpillars on the Web. Ethnomethodological and conversation analysis approaches examine how the teacher asks questions, which call on the children to display their factual knowledge about the search topic. The fine grained analysis shows how teachers design their interactions to prompt children’s displays of factual knowledge, and how the design of factual questions affect a student’s response in terms of what and how they respond. In focussing on how the teacher designs factual questions and how children respond to these questions it shows that question design can close down a student’s reply; or elicit a range of answers, from one word to extended more detailed responses. Understanding how the design of teachers’ questions can influence students’ responses has pedagogic implications and may support educators to make intentional decisions regarding their own questioning techniques.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

‘Just choose the easy option’: Students talk about alcohol use and social influence

Previous research into young people’s drinking behaviour has studied how social practices influence their actions and how they negotiate drinking-related identities. Here, adopting the perspective of discursive psychology we examine how, for young people, social influences are bound up with issues of drinking and of identity. We conducted 19 focus groups with undergraduate students in Australia aged between 18 and 24 years. Thematic analysis of participants’ accounts for why they drink or do not drink was used to identify passages of talk that referred to social influence, paying particular attention to terms such as ‘pressure’ and ‘choice’. These passages were then analysed in fine-grained detail, using discourse analysis, to study how participants accounted for social influence. Participants treated their behaviour as accountable and produced three forms of account that: (1) minimised the choice available to them, (2) explained drinking as culture and (3) described resisting peer pressure. They also negotiated gendered social dynamics related to drinking. These forms of account allowed the participants to avoid individual responsibility for drinking or not drinking. These findings demonstrate that the effects of social influence on young people’s drinking behaviour cannot be assumed, as social influence itself becomes negotiable within local contexts of talk about drinking.