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Augmented Intelligence and Intelligent Tutoring Systems
This book constitutes the refereed proceedings of the 19th International Conference on Augmented Intelligence and Intelligent Tutoring Systems, ITS 2023, held in Corfu, Greece, during June 2-5, 2023. The 41 full papers and 19 short papers presented in this book were carefully reviewed and selected from 84 submissions. The papers are divided into the following topical sections: augmented intelligence in tutoring systems; augmented intelligence in healthcare informatics; augmented intelligence in games, serious games and virtual reality; neural networks and data mining; augmented intelligence and metaverse; security, privacy and ethics in augmented intelligence; and applied natural language processing.
Interior Modelling of Massive Stars in Multiple Systems
This thesis by Cole Johnston brings novel insights into the inner workings of young massive stars. By bridging the observational fields of binary stars and asteroseismology this thesis uses state of the art statistical techniques to scrutinise theories of modern stellar astrophysics. Developing upon the commonly used isochrone fitting methodology, the author introduces the idea of isochrone cloud fitting in order to account for the full breadth of physics observed in stars. The author combines this methodology with gravity mode asteroseismic analysis to asses the level of chemical mixing deep within the stellar core in order to determine the star‘s age and core mass. Wrapped into a robust statistical framework to account for correlations, this methodology is employed to analyse individual stars, multiple systems, and clusters alike to demonstrate that chemical mixing has dramatic impact on stellar structure and evolution.
Gravitational Wave Astrophysics
This book offers review chapters written by invited speakers of the 3rd Session of the Sant Cugat Forum on Astrophysics - Gravitational Waves Astrophysics. All chapters have been peer reviewed. The book goes beyond normal conference proceedings in that it provides a wide panorama of the astrophysics of gravitational waves and serves as a reference work for researchers in the field.
High-Precision Studies of Compact Variable Stars
This book, which is a reworked and updated version of Steven Bloemen’s original PhD thesis, reports on several high-precision studies of compact variable stars. Its strength lies in the large variety of observational, theoretical and instrumentation techniques that are presented and used and paves the way towards new and detailed asteroseismic applications of single and binary subdwarf stars. Close binary stars are studied using high cadence spectroscopic datasets collected with state of the art electron multiplying CCDs and analysed using Doppler tomography visualization techniques. The work touches upon instrumentation, presenting the calibration of a new fast, multi-colour camera instal...
Modelling Transitions
Modelling Transitions shows what computational, formal and data-driven approaches can and could mean for sustainability transitions research, presenting the state-of-the-art and exploring what lies beyond. Featuring contributions from many well-known authors, this book presents the various benefits of modelling for transitions research. More than just taking stock, it also critically examines what modelling of transformative change means and could mean for transitions research and for other disciplines that study societal changes. This includes identifying a variety of approaches currently not part of the portfolios of transitions modellers. Far from only singing praise, critical methodological and philosophical introspection are key aspects of this important book. This book speaks to modellers and non-modellers alike who value the development of robust knowledge on transitions to sustainability, including colleagues in congenial fields. Be they students, researchers or practitioners, everyone interested in transitions should find this book relevant as reference, resource and guide.
Knowledge Guided Machine Learning
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and d...
The Falck Family
Falck is Teutonic for falcon. The Falck family originated in Hesse Darmstadt. Johann Georg Falck (1793-1878) is the earliest known ancestor of the Falck family. His son, Philip Falck (1818-1889) was the first to come to America. In 1847 he married Catherine Hangen in Wisconsin and they were the parents of eleven children, all of whom were born and died in Wisconsin. Descendants live in Wisconsin and other north-central states.
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