225 resultados para benchmark


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The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation in cloud computing. From the computational point of view, the mappers/reducers placement problem is a generalization of the classical bin packing problem, which is NP-complete. Thus, in this paper we propose a new heuristic algorithm for the mappers/reducers placement problem in cloud computing and evaluate it by comparing with other several heuristics on solution quality and computation time by solving a set of test problems with various characteristics. The computational results show that our heuristic algorithm is much more efficient than the other heuristics. Also, we verify the effectiveness of our heuristic algorithm by comparing the mapper/reducer placement for a benchmark problem generated by our heuristic algorithm with a conventional mapper/reducer placement. The comparison results show that the computation using our mapper/reducer placement is much cheaper while still satisfying the computation deadline.

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Parametric roll is a critical phenomenon for ships, whose onset may cause roll oscillations up to +-40 degrees, leading to very dangerous situations and possibly capsizing. Container ships have been shown to be particularly prone to parametric roll resonance when they are sailing in moderate to heavy head seas. A Matlab/Simulink parametric roll benchmark model for a large container ship has been implemented and validated against a wide set of experimental data. The model is a part of a Matlab/Simulink Toolbox (MSS, 2007). The benchmark implements a 3rd-order nonlinear model where the dynamics of roll is strongly coupled with the heave and pitch dynamics. The implemented model has shown good accuracy in predicting the container ship motions, both in the vertical plane and in the transversal one. Parametric roll has been reproduced for all the data sets in which it happened, and the model provides realistic results which are in good agreement with the model tank experiments.

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Introduction Due to their high spatial resolution diodes are often used for small field relative output factor measurements. However, a field size specific correction factor [1] is required and corrects for diode detector over-response at small field sizes. A recent Monte Carlo based study has shown that it is possible to design a diode detector that produces measured relative output factors that are equivalent to those in water. This is accomplished by introducing an air gap at the upstream end of the diode [2]. The aim of this study was to physically construct this diode by placing an ‘air cap’ on the end of a commercially available diode (the PTW 60016 electron diode). The output factors subsequently measured with the new diode design were compared to current benchmark small field output factor measurements. Methods A water-tight ‘cap’ was constructed so that it could be placed over the upstream end of the diode. The cap was able to be offset from the end of the diode, thus creating an air gap. The air gap width was the same as the diode width (7 mm) and the thickness of the air gap could be varied. Output factor measurements were made using square field sizes of side length from 5 to 50 mm, using a 6 MV photon beam. The set of output factor measurements were repeated with the air gap thickness set to 0, 0.5, 1.0 and 1.5 mm. The optimal air gap thickness was found in a similar manner to that proposed by Charles et al. [2]. An IBA stereotactic field diode, corrected using Monte Carlo calculated kq,clin,kq,msr values [3] was used as the gold standard. Results The optimal air thickness required for the PTW 60016 electron diode was 1.0 mm. This was close to the Monte Carlo predicted value of 1.15 mm2. The sensitivity of the new diode design was independent of field size (kq,clin,kq,msr = 1.000 at all field sizes) to within 1 %. Discussion and conclusions The work of Charles et al. [2] has been proven experimentally. An existing commercial diode has been converted into a correction-less small field diode by the simple addition of an ‘air cap’. The method of applying a cap to create the new diode leads to the diode being dual purpose, as without the cap it is still an unmodified electron diode.

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There have now been two decades of rhetoric on the need for culturally and contextually appropriate perspectives in international education. However, the extent to which courses, provision and pedagogy have truly reflected differences in cultural characteristics and learning preferences is still open to question. Little attention has been paid to these matters in quality assurance frameworks. This chapter discusses these issues and draws upon Hofstede’s cultural dimensions framework and studies into Asian pedagogy and uses of educational technology. It proposes a benchmark and performance indicators for assuring cultural, contextual, educational and technological appropriateness in the provision of transnational distance education in Asia by Australian universities.

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Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

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Research Background Young people’s avid use of mobile technologies in daily life has led to an increase in the design and research on mHealth (mobile health) interventions targeting young people. ‘Music eScape’ is a mobile based mood regulation app that uses an innovative approach to promoting young people’s wellbeing using music. Research Question The design, research, development and evaluation of ‘Music eScape’ addressed a number of research questions from across the fields of Psychology and Interactive and Visual Design. The specific design research question addressed was: How can interaction and visual design be utilized to promote and enable young people to effectively regulate their mood using music and how can the new design further promote their experience of empowerment, control and agency over actively directing their mood journey? Research Contribution Innovation and New Knowledge Through its unique visual interface design and interactivity, the application presents a novel approach to promoting young people’s wellbeing using music and a specific function that allows users to ‘draw’ their mood journey in order to generate a playlist. The mobile app is the first to contain a function that enables users to plan their mood journey and exercise a sense of agency, intentional choice and control over the mood shift and by extension, their wellbeing. The feature ‘drawing’ interface was designed by Oksana Zelenko using participatory design research and Russell’s circumplex model of affect (1980) to inform the key visual design concept and underpinning interaction design. Research Significance The significance of the design research component within the larger interdisciplinary practices that have informed ‘Music eScape’ (e.g. field of psychology, reported through journal articles and other related outcomes), is the unique visual and interactive presentation of participant data and music therapy research within the app interface and interaction design which improves and increases young people’s engagement with the health messages it contains. The industry quality standard is further demonstrated by the launch on Apple iTunes. This demonstrates the application meets the high professional requirements for national release and meets international standards. The app also creates a new benchmark for the quality of health apps on the market as it marks the industry release of a trialled evidence-based mHealth intervention co-designed with young people.

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The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

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The political and bureaucratic discourse surrounding non-profit sector reform is centred on streamlining the regulatory framework. Phrases such as 'one-stop shop','reducing red tape' and 'duplicative, burdensome and unclear requirements' fill press releases, government reports and discussion papers. In this chapter, I examine quantitative measures of the current regulatory compliance burden facing non-profit organisations in Australia as a benchmark for measuring progress over the coming years. I focus on regulatory compliance estimates for four key stages of non-profit enterprise activity non-profit enterprise start-up and registrations; fundraising;grant paperwork; and regulation proportionate to the size of the non-profit enterprise.

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Settlements and communities in the Great Barrier Reef (GBR) are highly vulnerable to climate change and face an uncertain social, economic and environmental future. The concept of community resilience is gaining momentum as stakeholders and institutions seek to better understand the social, economic and governance factors which affect community capacity to adapt in the face of climate change. This paper defines a framework to benchmark community resilience and applies it to a case study in the Wet Tropics in tropical Queensland within the GBR catchment. It finds that rural, indigenous and some urban populations are highly vulnerable and sensitive to climate change, particularly in terms of economic vitality, community knowledge, aspirations and capacity for adaptation. Without early and substantive action, this could result in declining social and economic wellbeing and natural resource health. Capacity to manage the possible shocks associated with the impacts of climate change and extreme climatic events is emerging and needs to be carefully fostered and further developed to achieve broader community resilience outcomes. Better information about what actions, policies and arrangements build community resilience and mobilise adaptive capacity in the face of climate change is needed.

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This paper presents the results of a full-scale research project undertaken to assess scour losses/gains for modular tray green roof specimens placed on a mock-up building, and identify important factors to consider for wind design criteria. Visual assessment of the experimental results showed that usage of vegetation, parapet height, wind direction, and test duration were the predominant factors affecting scour resistance of the growth media in tested specimens. Statistical analysis results indicated that the differences in soil losses measured among Phase 2’s test trials were more significant than those in Phase 1. This was attributed to the lack of parapet, cornering wind conditions, and longer test duration found in Phase 2. Findings presented in this paper constitute a benchmark for future research to improve the knowledge gap that exists in green roof wind design.

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This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.

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This paper develops and presents a fully coupled non-linear finite element procedure to treat the response of piles to ground shocks induced by underground explosions. The Arbitrary Lagrange Euler coupling formulation with proper state material parameters and equations are used in the study. Pile responses in four different soil types, viz, saturated soil, partially saturated soil and loose and dense dry soils are investigated and the results compared. Numerical results are validated by comparing with those from a standard design manual. Blast wave propagation in soils, horizontal pile deformations and damages in the pile are presented. The pile damage presented through plastic strain diagrams will enable the vulnerability assessment of the piles under the blast scenarios considered. The numerical results indicate that the blast performance of the piles embedded in saturated soil and loose dry soil are more severe than those in piles embedded in partially saturated soil and dense dry soil. Present findings should serve as a benchmark reference for future analysis and design.

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There is substantial attention worldwide to the quality of secondary school teaching in STEM in Education. This paper reports on the use of Outcome Mapping (OM) as an approach to guide and monitor change in teacher practice and a visual tool, shaped as a Star, to benchmark and monitor this behaviour. OM and the visual tool were employed to guide and document three secondary teachers’ behaviour as they planned, implemented and assessed a science unit in the new Australian standards-referenced curriculum. Five key outcome markers in the teachers’ behaviour were identified together with progress markers — cumulative qualitative indicators — leading to these outcomes. The use of a Star to benchmark and track teachers’ behaviours was particularly useful because it showed teacher behaviour on multiple dimensions simultaneously at various points in time. It also highlighted priorities in need of further attention and provided a pathway to achievement. Hence, OM and the Star representation provide both theoretical and pragmatic approaches to enhancing quality in STEM teaching.

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Firstly, on behalf of the secretariat that has coordinated these meetings every two years since 1985, our thanks to the organising committee here at the University of Economics in Cracow, Poland, for hosting this conference. I was asked to offer comment on the research agenda. There are many famous names to refer to. Two Australian colleagues here today are Peter Dowling and Helen De Cieri, longtime stalwarts of the field of IHRM. I acknowledge their contributions over many years, along with Randy Schuler and Denise Welch, and Dennis Briscoe. Other names such as Rosalie Tung, Pawan Bhudwhar, Michael Morley, Paul Sparrow and Wayne Cascio are known to us all. Their books have become classics. One example is the 700 page benchmark 2012 work by Chris Brewster and Wolfgang Mayrhofer, Handbook of Research on Comparative Human Resource Management (Brewster & Mayrhofer, 2012). More recently, in a book published by Cambridge University press in 2014, Mustafa Özbilgin, Dimitria Groutsis and William Harvey offer students a very accessible overview of the basics in IHRM (Ozbilgin, Groutsis, & Harvey, 2014). As for a research agenda, there are excellent literature reviews to which I would refer you, such as those by people who over the years have been frequent participants at this conference (Tarique & Schuler, 2010), (Farndale, Scullion, & Sparrow, 2010), and (Scullion & Collings, 2011).

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Graphene has received great interest from researchers all over the world owing to its unique properties. Much of the excitement surrounding graphene is due to its remarkable properties and inherent quantum effects. These effects and properties make it a desirable material for the fabrication of new devices. Graphene has a plethora of potential uses including gas and molecular sensors, electronics, spintronics and optics [1-7]. Interestingly, some of these properties have been known about since before the material was even isolated due to a considerable amount of theoretical work and simulations. The material was to some extent a condensed matter modelers "toy" as it was used as a benchmark 2D material Graphene had been used for a long time as the fundamental building block of many other carbon structures...