30,024 research outputs found

    MUSE CSP: An Extension to the Constraint Satisfaction Problem

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    This paper describes an extension to the constraint satisfaction problem (CSP) called MUSE CSP (MUltiply SEgmented Constraint Satisfaction Problem). This extension is especially useful for those problems which segment into multiple sets of partially shared variables. Such problems arise naturally in signal processing applications including computer vision, speech processing, and handwriting recognition. For these applications, it is often difficult to segment the data in only one way given the low-level information utilized by the segmentation algorithms. MUSE CSP can be used to compactly represent several similar instances of the constraint satisfaction problem. If multiple instances of a CSP have some common variables which have the same domains and constraints, then they can be combined into a single instance of a MUSE CSP, reducing the work required to apply the constraints. We introduce the concepts of MUSE node consistency, MUSE arc consistency, and MUSE path consistency. We then demonstrate how MUSE CSP can be used to compactly represent lexically ambiguous sentences and the multiple sentence hypotheses that are often generated by speech recognition algorithms so that grammar constraints can be used to provide parses for all syntactically correct sentences. Algorithms for MUSE arc and path consistency are provided. Finally, we discuss how to create a MUSE CSP from a set of CSPs which are labeled to indicate when the same variable is shared by more than a single CSP.Comment: See http://www.jair.org/ for any accompanying file

    Far-infrared observations of Sagittarius B2: Reconsideration of source structure

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    New moderate-angular-resolution far-infrared observations of the Sagittarius B2 star-forming region are presented, discussed, and compared with recent radio molecular and continuum observations of this source. In contrast to previous analyses, its far-infrared spectrum is interpreted as the result of a massive frigid cloud overlying a more-or-less normal infrared source, a natural explanation for the object's previously-noted pecularities. The characteristics derived for the obscuring cloud are similar to those found for the W51 MAIN object. Both sources have high sub-millimeter surface brightness, a high ratio of sub-millimeter to far-infrared flux, and numerous regions of molecular maser emission

    Study of properties of high-field superconductors at elevated temperatures Final technical report, 27 Apr. - 26 Aug. 1966

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    Properties of high field superconductors at high temperatures - magnetization experiments on niobium and niobium compound

    Study of properties of high field superconductors, ac field induced flux jumps Technical summary report, 21 Jun. 1965 - 26 Apr. 1966

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    Magnetization experiments in superimposed dc and audiofrequency ac magnetic fields on cold worked NbTi alloy samples - ac field induced flux jump

    A Hybrid Modelling Framework for Real-time Decision-support for Urgent and Emergency Healthcare

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    In healthcare, opportunities to use real-time data to support quick and effective decision-making are expanding rapidly, as data increases in volume, velocity and variety. In parallel, the need for short-term decision-support to improve system resilience is increasingly relevant, with the recent COVID-19 crisis underlining the pressure that our healthcare services are under to deliver safe, effective, quality care in the face of rapidly-shifting parameters. A real-time hybrid model (HM) which combines real-time data, predictions, and simulation, has the potential to support short-term decision-making in healthcare. Considering decision-making as a consequence of situation awareness focuses the HM on what information is needed where, when, how, and by whom with a view toward sustained implementation. However the articulation between real-time decision-support tools and a sociotechnical approach to their development and implementation is currently lacking in the literature. Having identified the need for a conceptual framework to support the development of real-time HMs for short-term decision-support, this research proposed and tested the Integrated Hybrid Analytics Framework (IHAF) through an examination of the stages of a Design Science methodology and insights from the literature examining decision-making in dynamic, sociotechnical systems, data analytics, and simulation. Informed by IHAF, a HM was developed using real-time Emergency Department data, time-series forecasting, and discrete-event simulation. The application started with patient questionnaires to support problem definition and to act as a formative evaluation, and was subsequently evaluated using staff interviews. Evaluation of the application found multiple examples where the objectives of people or sub-systems are not aligned, resulting in inefficiencies and other quality problems, which are characteristic of complex adaptive sociotechnical systems. Synthesis of the literature, the formative evaluation, and the final evaluation found significant themes which can act as antecedents or evaluation criteria for future real-time HM studies in sociotechnical systems, in particular in healthcare. The generic utility of IHAF is emphasised for supporting future applications in similar domains
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