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arXiv 2020年

作者： Anzt, Hartwig Bach, Felix Druskat, Stephan Löffler, Frank Loewe, Axel Renard, Bernhard Y. Seemann, Gunnar Struck, Alexander Achhammer, Elke Aggarwal, Piush Appel, Franziska Bader, Michael Brusch, Lutz Busse, Christian Chourdakis, Gerasimos Dabrowski, Piotr W. Ebert, Peter Flemisch, Bernd Friedl, Sven Fritzsch, Bernadette Funk, Maximilian D. Gast, Volker Goth, Florian Grad, Jean-Noël Hermann, Sibylle Hohmann, Florian Janosch, Stephan Kutra, Dominik Linxweiler, Jan Muth, Thilo Peters-Kottig, Wolfgang Rack, Fabian Raters, Fabian H.C. Rave, Stephan Reina, Guido Reißig, Malte Ropinski, Timo Schaarschmidt, Joerg Seibold, Heidi Thiele, Jan P. Uekerman, Benjamin Unger, Stefan Weeber, Rudolf Germany Innovative Computing Lab University of Tennessee KnoxvilleTN United States Department of English Studies Friedrich Schiller University Jena Germany Germany Department of Computer Science Humboldt-Universität zu Berlin Germany Heinz Nixdorf Chair for Distributed Information Systems Friedrich Schiller University Jena Germany Michael Stifel Center Jena Germany Center for Computation and Technology Louisiana State University Baton Rouge United States Germany Robert Koch Institute Berlin Germany Hasso Plattner Institute Faculty of Digital Engineering University of Potsdam Germany Institute for Experimental Cardiovascular Medicine University Heart Centre Freiburg Bad Krozingen Germany Faculty of Medicine University of Freiburg Freiburg Germany Matters of Activity. Image Space Material. Cluster of Excellence at Humboldt-Universität zu Berlin Germany Technische Universität München Germany Language Technology Lab Universität Duisburg-Essen Germany Germany Department of Informatics Technical University of Munich Germany Technische Universität Dresden Germany Deutsches Krebsforschungszentrum Heidelberg Germany Scientific Computing in Computer Science Technical University Munich Germany School of Computing Communication and Business Hochschule für Technik und Wirtschaft Berlin Germany Center for Bioinformatics Saar Saarland Informatics Campus Germany Institute for Modelling Hydraulic and Environmental Systems University of Stuttgart Germany Berlin Institute of Health Germany Scientific Computing Alfred Wegener Institute Helmholtz Center for Polar and Marine Research Bremerhaven Germany Max-Planck-Gesellschaft e.V. Institut für Theoretische Physik und Astrophysik Universität Würzburg Germany Institut für Computerphysik University of Stuttgart Germany University Library University of Stuttgart Germany Universität Bremen Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany European Molecular Biology Laboratory Heidelb

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of sustainable research software practices. In particular, we recommend strategies and measures to create an environment for sustainable research software, with the ultimate goal to ensure that software-driven research is valid, reproducible and sustainable, and that software is recognized as a first class citizen in research. This paper is the outcome of two workshops run in Germany in 2019, at deRSE19 - the first International Conference of Research Software Engineers in Germany - and a dedicated DFG-supported follow-up workshop in Berlin. Copyright © 2020, The Authors. All rights reserved.

关键词： Software design

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Double exponential smoothing: An alternative to Kalman filter-based predictive tracking

Double exponential smoothing: An alternative to Kalman filte...

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9th EUROGRAPHICS Workshop on Virtual Environments, EGVE 2003

作者： LaViola Jr., Joseph J. Brown University Technology Center for Advanced Scientific Computing and Visualization PO Box 1910 Providence RI 02912 United States

ISBN: (纸本)1581136862

We present novel algorithms for predictive tracking of user position and orientation based on double exponential smoothing. These algorithms, when compared against Kalman and extended Kalman filter-based predictors with derivative free measurement models, run approximately 135 times faster with equivalent prediction performance and simpler implementations. This paper describes these algorithms in detail along with the Kalman and extended Kalman Filter predictors tested against. In addition, we describe the details of a predictor experiment and present empirical results supporting the validity of our claims that these predictors are faster, easier to implement, and perform equivalently to the Kalman and extended Kalman filtering predictors. © 2003 The Eurographics Association.

关键词： Extended Kalman filters

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A testbed for studying and choosing predictive tracking algorithms in virtual environments

A testbed for studying and choosing predictive tracking algo...

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9th EUROGRAPHICS Workshop on Virtual Environments, EGVE 2003

作者： LaViola Jr., Joseph J. Brown University Technology Center for Advanced Scientific Computing and Visualization PO Box 1910 Providence RI 02912 United States

ISBN: (纸本)1581136862

We present a testbed for comparing predictive tracking algorithms that allows virtual environment system developers to make better choices about which predictors to use in their environments and aids researchers in determining how predictors work across various virtual environment configurations. Our testbed saves the virtual environment developer and researcher both time and effort with the important task of reducing dynamic tracking error and masking latency. The testbed consists of three components: a prediction algorithm library, a motion data repository, and a graphical testing application which provides users with the ability to test different predictive tracking algorithms across a variety of user motion sequences. The testbed provides enough generality for testing across different algorithmic and system parameters such as sampling rate, prediction time, and noise variance. The paper describes the contents of the predictor library and how to extend it, the types of motion data sets collected thus far, the motion data preparation methodology, and the graphical testing application's functionality and architecture. A simple testing scenario showing output from the testbed is also presented. © 2003 The Eurographics Association.

关键词： Testbeds

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A testbed for studying and choosing predictive tracking algorithms in virtual environments 03

A testbed for studying and choosing predictive tracking algo...

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Proceedings of the workshop on Virtual environments 2003

作者： Joseph J. LaViola Brown University Technology Center for Advanced Scientific Computing and Visualization Providence RI

ISBN: (纸本)9781581136869

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Double exponential smoothing: an alternative to Kalman filter-based predictive tracking 03

Double exponential smoothing: an alternative to Kalman filte...

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Proceedings of the workshop on Virtual environments 2003

作者： Joseph J. LaViola Brown University Technology Center for Advanced Scientific Computing and Visualization Providence RI

ISBN: (纸本)9781581136869

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An experiment comparing double exponential smoothing and Kalman filter-based predictive tracking algorithms

An experiment comparing double exponential smoothing and Kal...

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IEEE Annual International Symposium Virtual Reality

作者： J.J. LaViola Advanced Scientific Computing and Visualization Brown University Technology Center Providence RI USA

We present an experiment comparing double exponential smoothing and Kalman filter-based predictive tracking algorithms with derivative free measurement models. Our results show that the double exponential smoothers run approximately 135 times faster with equivalent prediction performance. The paper briefly describes the algorithms used in the experiment and discusses the results.

关键词： Smoothing methods Kalman filters Prediction algorithms Equations Vectors Predictive models Quaternions Interpolation scientific computing visualization

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A comparison of unscented and extended Kalman filtering for estimating quaternion motion

A comparison of unscented and extended Kalman filtering for ...

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American Control Conference (ACC)

作者： J.J. LaViola For Advanced Scientific Computing and Visualization Brown University Technology Center Providence RI USA

The unscented Kalman filter is a superior alternative to the extended Kalman filter for a variety of estimation and control problems. However, its effectiveness for improving human motion tracking for virtual reality applications in the presence of noisy data has been unexplored. In this paper, we present an empirical study comparing the performance of unscented and extended Kalman filtering for improving human head and hand tracking. Specifically, we examine human head and hand orientation motion signals, represented with quaternions, which are critical for correct viewing perspectives in virtual reality. Our experimental results and analysis indicate that unscented Kalman filtering performs equivalently with extended Kalman filtering. However, the additional computational overhead of the unscented Kalman filter and quasi-linear nature of the quaternion dynamics lead to the conclusion that the extended Kalman filter is a better choice for estimating quaternion motion in virtual reality applications.

关键词： Kalman filters Filtering Motion estimation Quaternions Virtual reality Humans Tracking Head Application software Jacobian matrices

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Pop through button devices for VE navigation and interaction

Pop through button devices for VE navigation and interaction

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IEEE Annual International Symposium Virtual Reality

作者： R.C. Zeleznik J.J. LaViola D. Acevedo Feliz D.F. Keefe Advanced Scientific Computing and Visualization Brown University Technology Center Providence RI USA

ISBN: (纸本)0769514928

Presents a novel class of virtual reality input devices that combine pop-through buttons with 6-DOF trackers. Compared to similar devices that use conventional buttons, pop-through devices double the number of potential discrete interaction modes, since each button has two activation states corresponding to light and firm pressure. This additional state per button provides a foundation to address a range of shortcomings with conventional virtual environment (VE) input devices that includes reducing the physical dexterity required to perform interactions, reducing the cognitive complexity of some compound tasks and enabling the design of less obtrusive devices without sacrificing expressive power. Specifically, we present two novel input devices: the FingerSleeve was designed to be minimally obtrusive physically, whereas the TriggerGun was designed to be physically similar to, yet more functional than a conventional hand-held trigger device. Further, we present a set of novel navigation and interaction techniques that leverage the capabilities of our pop-through button devices to improve interaction quality and provide insight into harnessing the potential of pop-through buttons for other tasks. Finally, we discuss how we incorporated one of our devices into a real application.

关键词： Navigation Fingers Electronic switching systems scientific computing visualization Virtual environment Virtual reality

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