998 resultados para progress ratio


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Computational Fluid Dynamics (CFD) simulations are widely used in mechanical engineering. Although achieving a high level of confidence in numerical modelling is of crucial importance in the field of turbomachinery, verification and validation of CFD simulations are very tricky especially for complex flows encountered in radial turbines. Comprehensive studies of radial machines are available in the literature. Unfortunately, none of them include enough detailed geometric data to be properly reproduced and so cannot be considered for academic research and validation purposes. As a consequence, design improvements of such configurations are difficult. Moreover, it seems that well-developed analyses of radial turbines are used in commercial software but are not available in the open literature especially at high pressure ratios. It is the purpose of this paper to provide a fully open set of data to reproduce the exact geometry of the high pressure ratio single stage radial-inflow turbine used in the Sundstrand Power Systems T-100 Multipurpose Small Power Unit. First, preliminary one-dimensional meanline design and analysis are performed using the commercial software RITAL from Concepts-NREC in order to establish a complete reference test case available for turbomachinery code validation. The proposed design of the existing turbine is then carefully and successfully checked against the geometrical and experimental data partially published in the literature. Then, three-dimensional Reynolds-Averaged Navier-Stokes simulations are conducted by means of the Axcent-PushButton CFDR CFD software. The effect of the tip clearance gap is investigated in detail for a wide range of operating conditions. The results confirm that the 3D geometry is correctly reproduced. It also reveals that the turbine is shocked while designed to give a high-subsonic flow and highlight the importance of the diffuser.

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This paper proposes the use of Bayesian approaches with the cross likelihood ratio (CLR) as a criterion for speaker clustering within a speaker diarization system, using eigenvoice modeling techniques. The CLR has previously been shown to be an effective decision criterion for speaker clustering using Gaussian mixture models. Recently, eigenvoice modeling has become an increasingly popular technique, due to its ability to adequately represent a speaker based on sparse training data, as well as to provide an improved capture of differences in speaker characteristics. The integration of eigenvoice modeling into the CLR framework to capitalize on the advantage of both techniques has also been shown to be beneficial for the speaker clustering task. Building on that success, this paper proposes the use of Bayesian methods to compute the conditional probabilities in computing the CLR, thus effectively combining the eigenvoice-CLR framework with the advantages of a Bayesian approach to the diarization problem. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 33.5% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

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Content analysis of text offers a method for exploring experiences which usually remain unquestioned and unexamined. In this paper the authors analyse a set of patient progress notes by re-framing them as a narrative account of a significant event in the experience of a patient, her family and attending health care workers. Examination of these notes provides insights into aspects of clinical practice which are usually dealt with at a taken-for-granted level. An interpretation of previously unexamined therapeutic practices within the social and political context of institutional health care is offered.

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Sintered bars of YBa2Cu3O7-x obtained by slip-casting are investigated for drying and sintering behaviour. High J(cm) values (approximate to 10(6) A/cm(2) at 77K) are obtained, although J(ct) values are low (approximate to 10(2) A/cm(2) at 77K). Microstructural characterisation is undertaken on selected samples which demonstrate significant differences in physical density and critical current density.

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Scientific and programmatic progress toward the development of a cosmic dust collection facility (CDCF) for the proposed space station is documented. Topics addressed include: trajectory sensor concepts; trajectory accuracy and orbital evolution; CDCF pointing direction; development of capture devices; analytical techniques; programmatic progress; flight opportunities; and facility development.

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Large Igneous Provinces are exceptional intraplate igneous events throughout Earth’s history. Their significance and potential global impact is related to the total volume of magma intruded and released during these geologically brief events (peak eruptions are often within 1-5 Myrs duration) where millions to tens of millions of cubic kilometers of magma are produced. In some cases, at least 1% of the Earth’s surface has been directly covered in volcanic rock, being equivalent to the size of small continents with comparable crustal thicknesses. Large Igneous Provinces are thus important, albeit episodic episodes of new crust addition. However, most magmatism is basaltic so that contributions to crustal growth will not always be picked up in zircon geochronology studies that better trace major episodes of extension-related silicic magmatism and the silicic Large Igneous Provinces. Much headway has been made on our understanding of these anomalous igneous events over the last 25 years, driving many new ideas and models. This includes their: 1) global spatial and temporal distribution, with a long-term average of one event approximately every 20 Myrs, but a clear clustering of events at times of supercontinent break-up – Large Igneous Provinces are thus an integral part of the Wilson cycle and are becoming an increasingly important tool in reconnecting dispersed continental fragments; 2) compositional diversity that in part reflects their crustal setting of ocean basins, and continental interiors and margins where in the latter setting, LIP magmatism can be silicicdominant; 3) mineral and energy resources with major PGE and precious metal resources being hosted in these provinces, as well as magmatism impacting on the hydrocarbon potential of volcanic basins and rifted margins through enhancing source rock maturation, providing fluid migration pathways, and trap formation; 4) biospheric, hydrospheric and atmospheric impacts, with Large Igneous Provinces now widely regarded as a key trigger mechanism for mass extinctions, although the exact kill mechanism(s) are still being resolved; 5) role in mantle geodynamics and thermal evolution of the Earth, by potentially recording the transport of material from the lower mantle or core-mantle boundary to the Earth's surface and being a fundamental component in whole mantle convection models; and 6) recognition on the inner planets where the lack of plate tectonics and erosional processes and planetary antiquity means that the very earliest record of LIP events during planetary evolution may be better preserved than on Earth.

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One of the primary desired capabilities of any future air traffic separation management system is the ability to provide early conflict detection and resolution effectively and efficiently. In this paper, we consider the risk of conflict as a primary measurement to be used for early conflict detection. This paper focuses on developing a novel approach to assess the impact of different measurement uncertainty models on the estimated risk of conflict. The measurement uncertainty model can be used to represent different sensor accuracy and sensor choices. Our study demonstrates the value of modelling measurement uncertainty in the conflict risk estimation problem and presents techniques providing a means of assessing sensor requirements to achieve desired conflict detection performance.

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Video presented as part of Smart Services CRC Participants conferences. This video shows an example of the latest version of our middleware linking the YAWL workflow engine to Open Simulator. We have created a simple example of an accident victim being brought into a Hospital to be processed. The preliminary interface to the YAWL accident treatment workflow is shown as a worklist on the left of the image. The tasks are presented to the avatar via this interface, in a similar manner as done in web based workflow systems. Objects in the simulator are instrumented with a knowledge base, that enables the validation of actions within the world, to make sure that tasks are carried out correctly.

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Although Design Science Research (DSR) is now an accepted approach to research in the Information Systems (IS) discipline, consensus on the methodology of DSR has yet to be achieved. Lack of a comprehensive and detailed methodology for Design Science Research (DSR) in the Information System (IS) discipline is a main issue. Prior research (the parent-study) aimed to remedy this situation and resulted in the DSR-Roadmap (Alturki et al., 2011a). Continuing empirical validation and revision of the DSR-Roadmap strives towards a methodology with appropriate levels of detail, integration, and completeness for novice researchers to efficiently and effectively conduct and report DSR in IS. The sub-study reported herein contributes to this larger, ongoing effort. This paper reports results from a formative evaluation effort of the DSR-Roadmap conducted using focus group analysis. Generally, participants endorsed the utility and intuitiveness of the DSR-Roadmap, while also suggesting valuable refinements. Both parent-study and sub-study make methodological contributions. The parent-study is the first attempt of utilizing DSR to develop a research methodology showing an example of how to use DSR in research methodology construction. The sub-study demonstrates the value of the focus group method in DSR for formative product evaluation.

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Many who have taken a tax course in the last few years will be aware of the plight of Ms Symone Anstis. Her story is a simple one. The year is 2006 and Ms Anstis, an undergraduate student is undertaking a teaching degree at the Australian Catholic University. To support herself she works at Katies earning $14,946, and receives Youth Allowance of $3,622. In her tax return for that year Ms Anstis claims $920 for ‘self-education expenses’ comprising travel, supplies, student administration fees, depreciation on her computer, textbooks and stationery. These expenses totalling $1,170 are correctly reduced by the non-deductible first $250, per s 82A of the Income Tax Assessment Act (1997) (Cth) (ITAA97). Ms Anstis claims a deduction for ‘self-education expenses’ on the basis that a condition of receiving Youth Allowance is the enrolment and satisfactory progress in an acceptable course of study. Generally, a deduction is allowed where a loss or outgoing is incurred in gaining or producing assessable income and that loss or outgoing is not of a private or domestic nature. Ms Anstis claims the expenses are incurred to meet the requirements of maintaining Youth Allowance so the nexus is satisfied. On assessment, the Commissioner of Taxation disallows the deduction claimed on the basis that ‘self-education expenses’ are only deductible if they have a relevant connection to the taxpayer’s current income-earning activities or they are likely to lead to an increase in a taxpayer’s income from his or her current income-earning activities in the future.

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Classifier selection is a problem encountered by multi-biometric systems that aim to improve performance through fusion of decisions. A particular decision fusion architecture that combines multiple instances (n classifiers) and multiple samples (m attempts at each classifier) has been proposed in previous work to achieve controlled trade-off between false alarms and false rejects. Although analysis on text-dependent speaker verification has demonstrated better performance for fusion of decisions with favourable dependence compared to statistically independent decisions, the performance is not always optimal. Given a pool of instances, best performance with this architecture is obtained for certain combination of instances. Heuristic rules and diversity measures have been commonly used for classifier selection but it is shown that optimal performance is achieved for the `best combination performance' rule. As the search complexity for this rule increases exponentially with the addition of classifiers, a measure - the sequential error ratio (SER) - is proposed in this work that is specifically adapted to the characteristics of sequential fusion architecture. The proposed measure can be used to select a classifier that is most likely to produce a correct decision at each stage. Error rates for fusion of text-dependent HMM based speaker models using SER are compared with other classifier selection methodologies. SER is shown to achieve near optimal performance for sequential fusion of multiple instances with or without the use of multiple samples. The methodology applies to multiple speech utterances for telephone or internet based access control and to other systems such as multiple finger print and multiple handwriting sample based identity verification systems.

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Dr Wyatt’s study investigated the complex relationship between vitamin D and melanoma, specifically if vitamin D status is associated with more aggressive melanomas. Exposure to solar ultraviolet radiation is the principal risk factor for melanoma and also the main source of vitamin D. This research found that insufficient vitamin D at time of melanoma diagnosis is significantly associated with poorer prognosis (as defined by tumour thickness). These results will contribute to a more refined public health message concerning melanoma and vitamin D, particularly in Queensland, which has the highest global incidence of melanoma, but vitamin D deficiency is not uncommon.

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This study reports the synthesis of extremely high aspect ratios (>3000) organic semiconductor nanowires of Ag–tetracyanoquinodimethane (AgTCNQ) on the surface of a flexible Ag fabric for the first time. These one-dimensional (1D) hybrid Ag/AgTCNQ nanostructures are attained by a facile, solution-based spontaneous reaction involving immersion of Ag fabrics in an acetonitrile solution of TCNQ. Further, it is discovered that these AgTCNQ nanowires show outstanding antibacterial performance against both Gram negative and Gram positive bacteria, which outperforms that of pristine Ag. The outcomes of this study also reflect upon a fundamentally important aspect that the antimicrobial performance of Ag-based nanomaterials may not necessarily be solely due to the amount of Ag+ ions leached from these nanomaterials, but that the nanomaterial itself may also play a direct role in the antimicrobial action. Notably, the applications of metal-organic semiconducting charge transfer complexes of metal-7,7,8,8-tetracyanoquinodimethane (TCNQ) have been predominantly restricted to electronic applications, except from our recent reports on their (photo)catalytic potential and the current case on antimicrobial prospects. This report on growth of these metal-TCNQ complexes on a fabric not only widens the window of these interesting materials for new biological applications, it also opens the possibilities for developing large-area flexible electronic devices by growing a range of metal-organic semiconducting materials directly on a fabric surface.

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Enterprise social networks are organizationally bounded online platforms for users to interact with another and maintain interpersonal relationships. The allure of these technologies is often seen in intra-organizational communication, collaboration and innovation. How these technologies actually support organizational innovation efforts remains unclear. A specific challenge is whether digital content on these platforms converts to actual innovation development efforts. In this study we set out to examine innovation-centric content flows on enterprise social networking platforms, and advance a conceptual model that seeks to explain which innovation conveyed in the digital content will traverse from the digital platform into regular processes. We describe important constructs of our model and offer strategies for the operationalization of the constructs. We conclude with an outlook to our ongoing empirical study that will explore and validate the key propositions of our model, and we sketch some potential implications for industry and academia.