Friedrich Leisch
University of Natural Resources and Life Sciences, Vienna
230 Papers
917 Citations
Friedrich Leisch is an academic researcher from University of Natural Resources and Life Sciences, Vienna. The author has contributed to research in topics: Market segmentation & Computer science. The author has an hindex of 49, co-authored 219 publications. Previous affiliations of Friedrich Leisch include Vienna University of Technology & University of Erlangen-Nuremberg.
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Papers
Tourist segments' justifications for behaving in an environmentally unsustainable way.
TL;DR: In this paper, a finite mixture model with concomitant variables is used to analyse 2785 survey responses to investigate the existence of tourist segment sharing justification patterns, and three segments are identified.
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Pesticide Use and Associated Greenhouse Gas Emissions in Sugar Beet, Apples, and Viticulture in Austria from 2000 to 2019
TL;DR: In this paper , the authors analyzed trends in insecticide, fungicide, and herbicide use and calculated production-related GHG emissions, and the share of pesticide-related versus fertilizer-related emissions in three agricultural crops with different pesticide intensities: sugar beets, apples and grapevines.
On the Edge: Statistics & Computing: Reproducible Statistical Research
TL;DR: A number of issues common to both statistical research and collaboration that impact the verification, understanding, and subsequent application of novel statistical procedures are discussed.
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Prediction of the Quantity and Purity of an Antibody Capture Process in Real Time.
Nicole Walch,Theresa Scharl,Edit Felföldi,Dominik Georg Sauer,Michael Melcher,Friedrich Leisch,Astrid Dürauer,Alois Jungbauer +7 more
TL;DR: An online monitoring system for downstream processes is developed, which is based on an array of online detectors based on prediction models solely based on online signals providing real-time predictions that allow online pooling decisions replacing time- and labor-intensive laboratory measurements.
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Real-time monitoring and model-based prediction of purity and quantity during a chromatographic capture of fibroblast growth factor 2.
Dominik Georg Sauer,Michael Melcher,Magdalena Mosor,Nicole Walch,Matthias Berkemeyer,Theresa Scharl-Hirsch,Friedrich Leisch,Alois Jungbauer,Astrid Dürauer +8 more
TL;DR: In this study, a chromatographic workstation was equipped with additional online sensors, such as multi‐angle light scattering, refractive index, attenuated total reflection Fourier‐transform infrared, and fluorescence spectroscopy, to predict quantity, host cell proteins, and double‐stranded DNA content simultaneously.
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