7,367 research outputs found

    Aerospace medicine and biology: A continuing bibliography with indexes

    Get PDF
    This bibliography lists 138 reports, articles, and other documents introduced into the NASA scientific and technical information system in Jun. 1980

    Human in the AI loop via xAI and Active Learning for Visual Inspection

    Get PDF
    Industrial revolutions have historically disrupted manufacturing by introducing automation into production. Increasing automation reshapes the role of the human worker. Advances in robotics and artificial intelligence open new frontiers of human-machine collaboration. Such collaboration can be realized considering two sub-fields of artificial intelligence: active learning and explainable artificial intelligence. Active learning aims to devise strategies that help obtain data that allows machine learning algorithms to learn better. On the other hand, explainable artificial intelligence aims to make the machine learning models intelligible to the human person. The present work first describes Industry 5.0, human-machine collaboration, and state-of-the-art regarding quality inspection, emphasizing visual inspection. Then it outlines how human-machine collaboration could be realized and enhanced in visual inspection. Finally, some of the results obtained in the EU H2020 STAR project regarding visual inspection are shared, considering artificial intelligence, human digital twins, and cybersecurity

    Human in the AI loop via xAI and Active Learning for Visual Inspection

    Get PDF
    Industrial revolutions have historically disrupted manufacturing by introducing automation into production. Increasing automation reshapes the role of the human worker. Advances in robotics and artificial intelligence open new frontiers of human-machine collaboration. Such collaboration can be realized considering two sub-fields of artificial intelligence: active learning and explainable artificial intelligence. Active learning aims to devise strategies that help obtain data that allows machine learning algorithms to learn better. On the other hand, explainable artificial intelligence aims to make the machine learning models intelligible to the human person. The present work first describes Industry 5.0, human-machine collaboration, and state-of-the-art regarding quality inspection, emphasizing visual inspection. Then it outlines how human-machine collaboration could be realized and enhanced in visual inspection. Finally, some of the results obtained in the EU H2020 STAR project regarding visual inspection are shared, considering artificial intelligence, human digital twins, and cybersecurity

    Advanced Wind Turbine Drivetrain Concepts: Workshop Report, June 29-30, 2010

    Full text link
    This report presents key findings from the Department of Energy's Advanced Drivetrain Workshop, held on June 29-30, 2010 in Broomfield, Colorado, to assess different advanced drivetrain technologies, their relative potential to improve the state-of-the-art in wind turbine drivetrains, and the scope of research and development needed for their commercialization in wind turbine applications
    corecore