@inproceedings{SchulteEggert2021,
  author    = {Schulte, Maximilian and Eggert, Mathias},
  title     = {Predicting hourly bitcoin prices based on long short-term memory neural networks},
  series = {Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021},
  booktitle = {Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021},
  pages     = {16 Seiten},
  year      = {2021},
  abstract  = {Bitcoin is a cryptocurrency and is considered a high-risk asset class whose price changes are difficult to predict. Current research focusses on daily price movements with a limited number of predictors. The paper at hand aims at identifying measurable indicators for Bitcoin price movement s and the development of a suitable forecasting model for hourly changes. The paper provides three research contributions. First, a set of significant indicators for predicting the Bitcoin price is identified. Second, the results of a trained Long Short-term Memory (LSTM) neural network that predicts price changes on an hourly basis is presented and compared with other algorithms. Third, the results foster discussions of the applicability of neural nets for stock price predictions. In total, 47 input features for a period of over 10 months could be retrieved to train a neural net that predicts the Bitcoin price movements with an error rate of 3.52 \%.},
  language  = {en}
}
@inproceedings{FunkeBeckmannKeinzetal.2021,
  author    = {Funke, Harald and Beckmann, Nils and Keinz, Jan and Horikawa, Atsushi},
  title     = {30 years of dry low NOx micromix combustor research for hydrogen-rich fuels: an overview of past and present activities},
  series = {Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition, September 21-25, 2020, Virtual, Online. Vol.: 4B: Combustion, Fuels, and Emissions},
  booktitle = {Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition, September 21-25, 2020, Virtual, Online. Vol.: 4B: Combustion, Fuels, and Emissions},
  publisher = {American Society of Mechanical Engineers (ASME)},
  isbn      = {978-0-7918-8413-3},
  doi       = {10.1115/GT2020-16328},
  pages     = {14 Seiten},
  year      = {2021},
  language  = {en}
}
@article{AyedKustererFunkeetal.2017,
  author    = {Ayed, Anis Haj and Kusterer, Karsten and Funke, Harald and Keinz, Jan and Bohn, D.},
  title     = {CFD based exploration of the dry-low-NOx hydrogen micromix combustion technology at increased energy densities},
  series = {Propulsion and Power Research},
  volume    = {6},
  journal   = {Propulsion and Power Research},
  number    = {1},
  publisher = {Elsevier},
  address   = {Amsterdam},
  isbn      = {2212-540X},
  doi       = {10.1016/j.jppr.2017.01.005},
  pages     = {15 -- 24},
  year      = {2017},
  language  = {en}
}
@inproceedings{AyedStrieganKustereretal.2017,
  author    = {Ayed, Anis Haj and Striegan, Constantin J. D. and Kusterer, Karsten and Funke, Harald and Kazari, M. and Horikawa, Atsushi and Okada, Kunio},
  title     = {Automated design space exploration of the hydrogen fueled "Micromix" combustor technology},
  pages     = {1 -- 8},
  year      = {2017},
  abstract  = {Combined with the use of renewable energy sources for its production, Hydrogen represents a possible alternative gas turbine fuel for future low emission power generation. Due to its different physical properties compared to other fuels such as natural gas, well established gas turbine combustion systems cannot be directly applied for Dry Low NOx (DLN) Hydrogen combustion. This makes the development of new combustion technologies an essential and challenging task for the future of hydrogen fueled gas turbines. The newly developed and successfully tested "DLN Micromix" combustion technology offers a great potential to burn hydrogen in gas turbines at very low NOx emissions. Aiming to further develop an existing burner design in terms of increased energy density, a redesign is required in order to stabilise the flames at higher mass flows and to maintain low emission levels. For this purpose, a systematic design exploration has been carried out with the support of CFD and optimisation tools to identify the interactions of geometrical and design parameters on the combustor performance. Aerodynamic effects as well as flame and emission formation are observed and understood time- and cost-efficiently. Correlations between single geometric values, the pressure drop of the burner and NOx production have been identified as a result. This numeric methodology helps to reduce the effort of manufacturing and testing to few designs for single validation campaigns, in order to confirm the flame stability and NOx emissions in a wider operating condition field.},
  language  = {en}
}
@inproceedings{HeuermannHarzheimMuehmel2021,
  author    = {Heuermann, Holger and Harzheim, Thomas and M{\"u}hmel, Marc},
  title     = {A maritime harmonic radar search and rescue system using passive and active tags},
  series = {2020 17th European Radar Conference (EuRAD)},
  booktitle = {2020 17th European Radar Conference (EuRAD)},
  publisher = {IEEE},
  isbn      = {978-2-87487-061-3},
  doi       = {10.1109/EuRAD48048.2021.00030},
  pages     = {73 -- 76},
  year      = {2021},
  language  = {en}
}
@article{EngemannDuKallweitetal.2020,
  author    = {Engemann, Heiko and Du, Shengzhi and Kallweit, Stephan and C{\"o}nen, Patrick and Dawar, Harshal},
  title     = {OMNIVIL - an autonomous mobile manipulator for flexible production},
  series = {Sensors},
  volume    = {20},
  journal   = {Sensors},
  number    = {24, art. no. 7249},
  publisher = {MDPI},
  address   = {Basel},
  isbn      = {1424-8220},
  doi       = {10.3390/s20247249},
  pages     = {1 -- 30},
  year      = {2020},
  language  = {en}
}
@inproceedings{MistlerButenwegAnthoine2004,
  author    = {Mistler, M. and Butenweg, Christoph and Anthoine, A.},
  title     = {Evaluation of the failure criterion for masonry by homogenisation},
  series = {Proceedings of the Seventh International Conference on Computational Structures Technology : [Lisbon, Portugal, 7 - 9 September 2004] / ed. by B. H. V. Topping and C.A. Mota Soares},
  booktitle = {Proceedings of the Seventh International Conference on Computational Structures Technology : [Lisbon, Portugal, 7 - 9 September 2004] / ed. by B. H. V. Topping and C.A. Mota Soares},
  publisher = {Civil-Comp Press},
  address   = {Stirling},
  organization    = {International Conference on Computational Structures Technology <7, 2004, Lissabon>},
  isbn      = {0-948749-95-4},
  doi       = {10.4203/ccp.79.201},
  pages     = {16 Seiten},
  year      = {2004},
  language  = {en}
}
@article{JablonskiMuenstermannNorketal.2021,
  author    = {Jablonski, Melanie and M{\"u}nstermann, Felix and Nork, Jasmina and Molinnus, Denise and Muschallik, Lukas and Bongaerts, Johannes and Wagner, Torsten and Keusgen, Michael and Siegert, Petra and Sch{\"o}ning, Michael Josef},
  title     = {Capacitive field-effect biosensor applied for the detection of acetoin in alcoholic beverages and fermentation broths},
  series = {physica status solidi (a) applications and materials science},
  volume    = {218},
  journal   = {physica status solidi (a) applications and materials science},
  number    = {13},
  publisher = {Wiley-VCH},
  address   = {Weinheim},
  issn      = {1862-6319},
  doi       = {10.1002/pssa.202000765},
  pages     = {7 Seiten},
  year      = {2021},
  abstract  = {An acetoin biosensor based on a capacitive electrolyte-insulator-semiconductor (EIS) structure modified with the enzyme acetoin reductase, also known as butane-2,3-diol dehydrogenase (Bacillus clausii DSM 8716ᵀ), is applied for acetoin detection in beer, red wine, and fermentation broth samples for the first time. The EIS sensor consists of an Al/p-Si/SiO₂/Ta₂O₅ layer structure with immobilized acetoin reductase on top of the Ta₂O₅ transducer layer by means of crosslinking via glutaraldehyde. The unmodified and enzyme-modified sensors are electrochemically characterized by means of leakage current, capacitance-voltage, and constant capacitance methods, respectively.},
  language  = {en}
}
@incollection{EngemannDuKallweitetal.2020,
  author    = {Engemann, Heiko and Du, Shengzhi and Kallweit, Stephan and Ning, Chuanfang and Anwar, Saqib},
  title     = {AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation},
  series = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020},
  booktitle = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020},
  publisher = {IOS Press},
  address   = {Amsterdam},
  isbn      = {978-1-64368-137-5},
  doi       = {10.3233/FAIA200770},
  pages     = {89 -- 97},
  year      = {2020},
  abstract  = {We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.},
  language  = {en}
}
@phdthesis{Bronder2020,
  author    = {Bronder, Thomas},
  title     = {Label-free detection of tuberculosis DNA with capacitive field-effect biosensors},
  publisher = {Philipps-Universit{\"a}t Marburg},
  address   = {Marburg},
  doi       = {10.17192/z2021.0056},
  pages     = {X, 162 S},
  year      = {2020},
  language  = {en}
}