Gebhard, Christian Alexander (2022)
4th International Conference Business Meets Technology 2022.
.
DOI: 10.4995/BMT2022.2022.15328
Gebhard, Christian Alexander ; Baudracco-Kastner, Monica (2022)
4th International Conference Business Meets Technology 2022..
DOI: 10.4995/BMT2022.2022.15324
Bölz, Annika; Gaisser, Sibylle (2022)
BMT 2022 – 4th International Conference Business Meets Technology 2022
Valencia (Spain). July 7-9, 2022.
DOI: 10.4995/BMT2022.2022.16007
Hain, Christopher; Gaisser, Sibylle (2022)
Business Meets Technology. 4th International Conference of the University of Applied Sciences Ansbach (7th to 9th July 2022) 2023.
DOI: 10.4995/BMT2022.2022.16007
The non-conventional yeast Yarrowia lipolytica is attracting increasing attention due to its potential to produce large amounts of organic acids from hydrophobic substrates. Due to the steadily increasing demand for citric acid in the industrial sector, the aim of this scientific work was to develop a predictive model of the citric acid productivity of the strain Yarrowia lipolytica DSM3286. As a basis for this, the optical density, pH, cell number and citric acid were determined in 18 identical mixtures.
The citric acid concentration (mean values of the measured concentration over time) follows a linear increase. Based on this, the mathematical calculation operation of linear regression was selected for modeling the prediction model in Python. The following coefficients were determined for the variables used in the learning algorithm:
• time: 6,104 * 10-4
• OD: -1,224 * 10-1
• pH value: -4,043 * 10-1
• Cell count: 1,749 * 10-8
In final validation of the program, a result accuracy of 86.5% was obtained. The result obtained in the present scientific work shows that by means of simple linear regression, over a cultivation period of 13 days, a prediction of the citric acid productivity of strain Yarrowia lipolytica DSM3286 is possible.
Kröckel, Pavlina; Piazza, Alexander; Wessel, Pascal (2022)
4th International Conference Business Meets Technology 2022 2022, S. 220-231.
DOI: 10.4995/BMT2022.2022.15631
Technology in football is increasingly used for decision making. Adoption, especially in Germany, has been slow. However, the benefits of data analytics for pre-, and post-match analysis have motivated decision makers to pay attention to the data science trend. Nowadays, football clubs from the third leagues or even amateur clubs are using technology to help them gain a competitive edge. Fan experience, both online and offline (home infront of the TV or at the stadium) is driving the next innovation stage in football. The study presented here is focused on testing and evaluation a facial recognition software on images from football coaches, just a few seconds after an important situation during the match has taken place (e.g., win, goal scored). We demonstrated that, in fact, emotion recognition software captures unexpected emotional reactions from coaches which could then be used to calculate interesting statistics and increase fan engagement and entertainment.
Paglia, Chiara; Stiehl, Annika; Uhl, Christian (2022)
CONTROLO 2022. Lecture Notes in Electrical Engineering, Vol 930, Springer, Cham, S. 205-213.
DOI: 10.1007/978-3-031-10047-5_18
Romberger, Philipp; Warmuth, Monika; Uhl, Christian; Hüper, Knut (2022)
CONTROLO 2022. Lecture Notes in Electrical Engineering, Vol 930. Springer, Cham, S. 385-394.
DOI: 10.1007/978-3-031-10047-5_34
Fehr, Stefanie (2022)
DGRI DreiLänderTreffen vom 30.06.-02.07.22.
Garg, Ritam (2022)
4th International Conference Business Meets Technology 2022.
DOI: 10.4995/BMT2022.2022.15543
Fehr, Stefanie (2022)
Vortrag auf dem DGRI-Drei-Länder-Treffen, Karlsruhe, 30.06. - 02.07.2022.
Fehr, Stefanie (2022)
Zeitschrift für Datenschutz 06/2022, S. 256-260.
Hänel, Svenja; Ahlers, Michael; Martin, Annette (2022)
Tagungsband 16. ThGOT Thementage Grenz- und Oberflächentechnik und 13. Biomaterial-Kolloquium 14. - 15. Juni 2022, INNOVENT e.V. ISBN 978-3-00-063254-9.
Wissler, J.; Häfner, Philipp; Aberle, A.; Loerler, N.; Mamdouh, D.; Szwajgier, D.; Reimann, Hans-Achim (2022)
Wissler, J.; Häfner, Philipp; Aberle, A.; Loerler, N.; Mamdouh, D.; Szwajgier, D....
21st International European Light Microscopy Initiative Meeting, ELMI2022, 7.-10.06.2022, Turku, Finland.
Häfner, Philipp; Ketterle, A.; Reimann, Hans-Achim (2022)
2. Posterpreis. 16. ThGOT und 13. Biomaterial-Kolloquium 2022. Innovent e.V..
Warmuth, Monika; Romberger, Philipp; Hüper, Knut; Uhl, Christian (2022)
ITISE 2022, 27. - 30.06.2022, Gran Canaria, Spanien.
Händel, Marion; Martschinke, Sabine (2022)
Vortrag im Rahmen der Ringvorlesung "Digitalität – Bildung – Ethik" der FAU Erlangen-Nürnberg, Juni 2022.
Schmid , Elena ; Mehlin, Vanessa ; Henne, Sophie ; Schacht, Sigurd (2022)
2022 IEEE 28th International Conference on Engineering, Technology and Innovation (ICE/ITMC) & 31st International Association For Management of Technology (IAMOT) Joint Conference.
DOI: 10.1109/ICE/ITMC-IAMOT55089.2022.10033236
In a current research project at a German university, a digital study assistant based on conversational AI is being developed. In this research project, four main application areas of the digital assistant are planned: communicator, for answering questions, conversation, and mentoring; a planner, for performing time and task management and course planning; a motivator, for actively managing learning success with gamification elements; and an analyzer, for processing necessary information about the student's study progress. In order to identify different application examples and possibilities for these four areas of the digital study assistant, the aim of this paper is to conduct a literature review. In addition to application examples and possibilities, implementation goals and the improvement of study results through such applications were researched.
Durst, Carolin; Hähnlein, Johannes (2022)
https://www.rkw-kompetenzzentrum.de/das-rkw/presse/eepa/ und https://gruendungsberatung.hs-ansbach.de/gruendungstag/.
Gomez-Barrero, Marta; Busch, Christoph (2022)
IEEE Access 2022 (10), S. 67573-67589.
DOI: 10.1109/ACCESS.2022.3184301
Blettner, Daniela; Gollisch, Simon (2022)
Management Research Review.
DOI: 10.1108/MRR-11-2021-0807
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