83 resultados para fine grained ground mass


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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).

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Cyclic plastic deformation of subgrade and other engineered layers is generally not taken into account in the design of railway bridge transition zones, although the plastic deformation is the governing factor of frequent track deterioration. Actual stress behavior of fine grained subgrade/embankment layers under train traffic is, however, difficult to replicate using the conventional laboratory test apparatus and techniques. A new type of torsional simple shear apparatus, known as multi-ring shear apparatus, was therefore developed to evaluate the actual stress state and the corresponding cyclic plastic deformation characteristics of subgrade materials under moving wheel load conditions. Multi-ring shear test results has been validated using a theoretical model test results; the capability of the multi-ring shear apparatus for replicating the cyclic plastic deformation characteristics of subgrade under moving train wheel load conditions is thus established. This paper describes the effects of principal stress rotation (PSR) of the subgrade materials to the cyclic plastic deformation in a railroad and impacts of testing methods in evaluating the influence of principal stress rotation to the track deterioration of rail track.

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Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

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We present a novel framework and algorithms for the analysis of Web service interfaces to improve the efficiency of application integration in wide-spanning business networks. Our approach addresses the notorious issue of large and overloaded operational signatures, which are becoming increasingly prevalent on the Internet and being opened up for third-party service aggregation. Extending upon existing techniques used to refactor service interfaces based on derived artefacts of applications, namely business entities, we propose heuristics for deriving relations between business entities, and in turn, deriving permissible orders in which operations are invoked. As a result, service operations are refactored on business entity CRUD which then leads to behavioural protocols generated, thus supportive of fine-grained and flexible service discovery, composition and interaction. A prototypical implementation and analysis of web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms and open up further insights into service interface synthesis.

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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 opportuni- ties, poses challenges to improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operation 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.

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The current investigation reports on diesel particulate matter emissions, with special interest in fine particles from the combustion of two base fuels. The base fuels selected were diesel fuel and marine gas oil (MGO). The experiments were conducted with a four-stroke, six-cylinder, direct injection diesel engine. The results showed that the fine particle number emissions measured by both SMPS and ELPI were higher with MGO compared to diesel fuel. It was observed that the fine particle number emissions with the two base fuels were quantitatively different but qualitatively similar. The gravimetric (mass basis) measurement also showed higher total particulate matter (TPM) emissions with the MGO. The smoke emissions, which were part of TPM, were also higher for the MGO. No significant changes in the mass flow rate of fuel and the brake-specific fuel consumption (BSFC) were observed between the two base fuels.

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The cation\[Si,C,O](+) has been generated by 1) the electron ionisation (EI) of tetramethoxysilane and 2) chemical ionisation (CI) of a mixture of silane and carbon monoxide. Collisional activation (CA) experiments performed for mass-selected \[Si,C,O](+), generated by using both methods, indicate that the structure is not inserted OSiC+; however, a definitive structural assignment as Si+-CO, Si+-OC or some cyclic variant is impossible based on these results alone. Neutralisation-reionisation (+NR+) experiments for EI-generated \[Si,C,O](+) reveal a small peak corresponding to SiC+, but no detectable SiO+ signal, and thus establishes the existence of the Si+-CO isomer. CCSD(T)//B3LYP calculations employing a triple-zeta basis set have been used to explore the doublet and quartet potential-energy surfaces of the cation, as well as some important neutral states The results suggest that both Si+-CO and Si+ - OC isomers are feasible; however, the global minimum is (2)Pi SiCO+. Isomeric (2)Pi SiOC+ is 12.1 kcal mol(-1) less stable than (2)Pi SiCO+, and all quartet isomers are much higher in energy. The corresponding neutrals Si-CO and Si-OC are also feasible, but the lowest energy Si - OC isomer ((3)A") is bound by only 1.5 kcal mol(-1). We attribute most, if nor all, of the recovery signal in the +NR' experiment to SiCO+ survivor ions. The nature of the bonding in the lowest energy isomers of Si+ -(CO,OC) is interpreted with the aid of natural bond order analyses, and the ground stale bonding of SiCO+ is discussed in relation to classical analogues such as metal carbonyls and ketenes.