797 research outputs found

    New gamma/hadron separation parameters for a neural network for HAWC

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    The High-Altitude Water Cherenkov experiment (HAWC) observatory is located 4100 meters above sea level. HAWC is able to detect secondary particles from extensive air showers (EAS) initiated in the interaction of a primary particle (either a gamma or a charged cosmic ray) with the upper atmosphere. Because an overwhelming majority of EAS events are triggered by cosmic rays, background noise suppression plays an important role in the data analysis process of the HAWC observatory. Currently, HAWC uses cuts on two parameters (whose values depend on the spatial distribution and luminosity of an event) to separate gamma-ray events from background hadronic showers. In this work, a search for additional gamma-hadron separation parameters was conducted to improve the efficiency of the HAWC background suppression technique. The best-performing parameters were integrated to a feed-foward Multilayer Perceptron Neural Network (MLP-NN), along with the traditional parameters. Various iterations of MLP-NN's were trained on Monte Carlo data, and tested on Crab data. Preliminary results show that the addition of new parameters can improve the significance of the point source at high-energies (~ TeV), at the expense of slightly worse performance in conventional low-energy bins (~ GeV). Further work is underway to improve the efficiency of the neural network at low energies.Comment: Presented at the 35th International Cosmic Ray Conference (ICRC2017), Bexco, Busan, Korea. See arXiv:1708.02572 for all HAWC contribution

    Alien Registration- Bourbeau, Gratia E. (Greenville, Piscataquis County)

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    https://digitalmaine.com/alien_docs/10043/thumbnail.jp

    Desirable attributes of theories, models, and frameworks for implementation strategy design in healthcare: a scoping review protocol [version 1; peer review: 1 approved, 2 approved with reservations]

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    Background: Implementation strategies can facilitate the adoption of evidence-based practices and policies. A wide range of theoretical approaches—theories, models, and frameworks—can be used to inform implementation strategy design in different ways (e.g., guiding barrier and enabler assessment to implementing evidence-based interventions). While selection criteria and attributes of theoretical approaches for use in implementation strategy design have been studied, they have never been synthesized. Furthermore, theoretical approaches have never been classified according to desirable criteria and attributes for use in implementation strategy design. This scoping review aims to a) identify the literature reporting on the selection of theoretical approaches for informing implementation strategy design in healthcare and b) understand the suggested use of these approaches in implementation strategy design. Methods: The Joanna Briggs Institute methodological guidelines will be used to conduct this scoping review. A search of three bibliographical databases (MEDLINE, Embase, CINAHL) will be conducted for peer-reviewed discussion, methods, protocol, or review papers. Data will be managed using the Covidence software. Two review team members will independently perform screening, full text review and data extraction. Results: Results will include a list of selection criteria and attributes of theoretical approaches for use in research on implementation strategy design. Descriptive data regarding selection criteria and attributes will be synthesized graphically and in table format. Data regarding the suggested use of theoretical approaches in implementation strategy design will be presented narratively. Conclusions: Results will be used to classify existing theoretical approaches according to the attributes and selection criteria identified in this scoping review. Envisioned next steps include an online tool that will be created to assist researchers in selecting theories, models, and frameworks for implementation strategy design
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