517 research outputs found

    The Visual Language of Holograms

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    Hyperobject: homeland

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    This paper describes the conceptual underpinning, theoretical context and workflow of a haptic drawing hologram project, Hyperobject: Homeland which proposes that one’s homeland is emergent as life experience. The social context of this project is the current extensive use of holographic maps in tactical battle visualisation by the military. The Hyperobject: Homeland project proposes a shift in our perception of what a homeland might be in the age of the hyperobject. By inviting viewers to take up the same military point of view above a hologram it allows contemplation of a visualisation of homeland as a type of ‘common’

    A novel dynamic asset allocation system using Feature Saliency Hidden Markov models for smart beta investing

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    The financial crisis of 2008 generated interest in more transparent, rules-based strategies for portfolio construction, with Smart beta strategies emerging as a trend among institutional investors. While they perform well in the long run, these strategies often suffer from severe short-term drawdown (peak-to-trough decline) with fluctuating performance across cycles. To address cyclicality and underperformance, we build a dynamic asset allocation system using Hidden Markov Models (HMMs). We test our system across multiple combinations of smart beta strategies and the resulting portfolios show an improvement in risk-adjusted returns, especially on more return oriented portfolios (up to 50%\% in excess of market annually). In addition, we propose a novel smart beta allocation system based on the Feature Saliency HMM (FSHMM) algorithm that performs feature selection simultaneously with the training of the HMM, to improve regime identification. We evaluate our systematic trading system with real life assets using MSCI indices; further, the results (up to 60%\% in excess of market annually) show model performance improvement with respect to portfolios built using full feature HMMs

    A systematic review of speech recognition technology in health care

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    BACKGROUND To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. RESULTS The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. CONCLUSIONS SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns.Funding for this study was provided by the University of Western Sydney. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program. NICTA is also funded and supported by the Australian Capital Territory, the New South Wales, Queensland and Victorian Governments, the Australian National University, the University of New South Wales, the University of Melbourne, the University of Queensland, the University of Sydney, Griffith University, Queensland University of Technology, Monash University and other university partners

    COVID-19 School Closures: Professional and Personal Impacts on Building Principals

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    The COVID-19 pandemic has had a global impact resulting in an altered reality for educational systems around the world. The mandate by the governor of Washington State to close all school buildings produced immediate and significant impacts to the educational systems throughout the state, which resulted in professional and personal challenges for building leaders. The researchers, two school administrators at different levels in separate districts, had a unique “front row seat” to the challenges being faced by educators in the region and across the state. Based on this positionality and the current reality, the overarching question of this study focused on the professional and personal impacts to elementary and secondary public-school principals during the COVID-19 crisis to develop an understanding of these impacts on school leaders in Washington State, as well as the potential long-term effects. A survey of Washington State school administrators was conducted with a focus on the professional demands of the job during a crisis, social-emotional and physical well-being, the technological and learning challenges of remote learning, and the inequities associated with a virtual platform. The data analysis examined levels of job satisfaction pre- and post- the COVID-19 pandemic as well as the availability of support systems and coping mechanisms employed by administrators during the crisis. Recommendations for potential support systems in the time of crises and further research are based on the survey data and subsequent analyses

    A systematic review of speech recognition technology in health care

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    Background To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. Methods A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. Results The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. Conclusions SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns
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