Dr. Arman Arefi
Scientific researcher
Department: System Process Engineering
Telefon: +49 331 5699-905
E-Mail: AArefi@atb-potsdam.de
Online:
Mitarbeit in Forschungsprogrammen
Arbeitsgebiete
Our mission in the Drying Technology research group is to converge Digital Twins and Drying Technology. For this purpose, our research activities are focused on I) Investigation of potential non-invasive sensors to monitor drying process, II) Mathematical modeling of drying process, III) Machine learning algorithms to mimic the drying process, and IV) Dynamic optimization of the process.
Veröffentlichungen
- Arefi, A.; Sturm, B.; Babor, M.; Horf, M.; Hoffmann, T.; Höhne, M.; Friedrich, K.; Schroedter, L.; Venus, J.; Olszewska-Widdrat, A. (2024): Digital model of biochemical reactions in lactic acid bacterial fermentation of simple glucose and biowaste substrates. Heliyon. (19): p. 1-13. Online: https://doi.org/10.1016/j.heliyon.2024.e38791
- Arefi, A.; Sturm, B.; Hoffmann, T. (2024): Explainability of deep convolutional neural networks when it comes to NIR spectral data: a case study of starch content estimation in potato tubers. LWT-Food Science and Technology. : p. 0. Online: https://doi.org/10.1016/j.foodcont.2024.110979
- Nurkhoeriyati, T.; Arefi, A.; Kulig, B.; Sturm, B.; Hensel, O. (2023): Non-destructive monitoring of quality attributes kinetics during the drying process: A case study of celeriac slices and the model generalisation in selected commodities. Food Chemistry. (136379): p. 136379. Online: https://doi.org/10.1016/j.foodchem.2023.136379
- Arefi, A.; Sturm, B.; Hensel, O.; Raut, S. (2023): NIR monochrome imaging for monitoring of apple drying process: Light-emitting diode and band-pass filter imaging techniques. Food Bioscience. (August 2023): p. 102898. Online: https://doi.org/10.1016/j.fbio.2023.102898