@inproceedings{SildatkeKarwanniKraftetal.2020,
  author    = {Sildatke, Michael and Karwanni, Hendrik and Kraft, Bodo and Schmidts, Oliver and Z{\"u}ndorf, Albert},
  title     = {Automated Software Quality Monitoring in Research Collaboration Projects},
  series = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops},
  booktitle = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops},
  publisher = {IEEE},
  address   = {New York, NY},
  doi       = {10.1145/3387940.3391478},
  pages     = {603 -- 610},
  year      = {2020},
  abstract  = {In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem. Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ. Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible. In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production. Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.},
  language  = {en}
}
@article{EngelmannPourshahidiShalabyetal.2022,
  author    = {Engelmann, Ulrich M. and Pourshahidi, Mohammad Ali and Shalaby, Ahmed and Krause, Hans-Joachim},
  title     = {Probing particle size dependency of frequency mixing magnetic detection with dynamic relaxation simulation},
  series = {Journal of Magnetism and Magnetic Materials},
  volume    = {563},
  journal   = {Journal of Magnetism and Magnetic Materials},
  number    = {In progress, Art. No. 169965},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0304-8853},
  doi       = {10.1016/j.jmmm.2022.169965},
  year      = {2022},
  abstract  = {Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles' magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.},
  language  = {en}
}
@article{AchtsnichtToedterNiehuesetal.2019,
  author    = {Achtsnicht, Stefan and T{\"o}dter, Julia and Niehues, Julia and Tel{\"o}ken, Matthias and Offenh{\"a}usser, Andreas and Krause, Hans-Joachim and Schr{\"o}per, Florian},
  title     = {3D printed modular immunofiltration columns for frequency mixing-based multiplex magnetic immunodetection},
  series = {Sensors},
  volume    = {19},
  journal   = {Sensors},
  number    = {1},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s19010148},
  pages     = {15 Seiten},
  year      = {2019},
  abstract  = {For performing point-of-care molecular diagnostics, magnetic immunoassays constitute a promising alternative to established enzyme-linked immunosorbent assays (ELISA) because they are fast, robust and sensitive. Simultaneous detection of multiple biomolecular targets from one body fluid sample is desired. The aim of this work is to show that multiplex magnetic immunodetection based on magnetic frequency mixing by means of modular immunofiltration columns prepared for different targets is feasible. By calculations of the magnetic response signal, the required spacing between the modules was determined. Immunofiltration columns were manufactured by 3D printing and antibody immobilization was performed in a batch approach. It was shown experimentally that two different target molecules in a sample solution could be individually detected in a single assaying step with magnetic measurements of the corresponding immobilization filters. The arrangement order of the filters and of a negative control did not influence the results. Thus, a simple and reliable approach to multi-target magnetic immunodetection was demonstrated.},
  language  = {en}
}
@misc{Buechel2022,
  type      = {Master Thesis},
  author    = {B{\"u}chel, Carolin},
  title     = {GYMLET : dein mobiles Freiluftstudio - Entwicklung eines serientauglichen Prototypen und einer Vermarktungsstrategie},
  publisher = {FH Aachen},
  address   = {Aachen},
  pages     = {93 Seiten},
  year      = {2022},
  abstract  = {Sportvereine verlieren zunehmend Mitglieder. Grund daf{\"u}r ist der wachsende Wunsch nach unabh{\"a}ngigen Trainingsm{\"o}glichkeiten. GYMLET bietet den Sportler:innen die M{\"o}glichkeit, ihre Fitness funktional, selbstorganisiert und unabh{\"a}ngig zu trainieren. Dabei kann durch den selbstbestimmten Trainingsort neben der k{\"o}rperlichen Fitness vor allem die Motivation zur sportlichen Aktivit{\"a}t und das Wohlbefinden gesteigert werden. Unterst{\"u}tzt wird das Trainingssystem durch eine App, welche den Sportler:innen neben Nutzungsm{\"o}glichkeiten als Coach und Trainingsplaner dient. Um diese Trainingsm{\"o}glichkeit an die Zielgruppe heranzutragen, ist eine Kampagnenstrategie aus zwei Phasen entstanden. In dieser sollen Postings und Clips {\"u}ber Instagram und Youtube ver{\"o}ffentlicht werden. Zus{\"a}tzlich werden Zeitschriften und m{\"o}gliche Kooperationen mit Therapeuten oder Freizeitunterk{\"u}nften zur Ver{\"o}ffentlichung der Kampagne genutzt.},
  language  = {de}
}
@article{HeuermannSadeghfam2009,
  author    = {Heuermann, Holger and Sadeghfam, Arash},
  title     = {Enhanced system architecture for rugged wide band data transmission / Sadeghfam, A. ; Heuermann, H.},
  series = {European Radar Conference, 2009 : EuRAD 2009 ; Sept. 30 - Oct. 2 2009, Rome, Italy ; part of the European Microwave Week (EuMW) / sponsored by EuMA, European Microwave Association},
  journal   = {European Radar Conference, 2009 : EuRAD 2009 ; Sept. 30 - Oct. 2 2009, Rome, Italy ; part of the European Microwave Week (EuMW) / sponsored by EuMA, European Microwave Association},
  publisher = {IEEE},
  address   = {Piscataway, NJ},
  isbn      = {978-2-87487-014-9},
  pages     = {347 -- 350},
  year      = {2009},
  language  = {en}
}
@book{KrauseUlkeMartinetal.2019,
  author    = {Krause, Thomas and Ulke, Bernd and Martin, Joachim and Lemke, J{\"o}rg and Sparla, Peter and Streit, Wilfried},
  title     = {{\"U}bungsaufgaben und Berechnungen f{\"u}r den Baubetrieb: Klausurvorbereitung mit ausf{\"u}hrlichen L{\"o}sungen},
  editor    = {Krause, Thomas and Ulke, Bernd},
  edition   = {3. Auflage},
  publisher = {Springer Vieweg},
  address   = {Wiesbaden},
  isbn      = {978-3-658-23126-2 (Print) 978-3-658-23127-9 (Online)},
  pages     = {XI, 347 Seiten ; Illustrationen},
  year      = {2019},
  language  = {de}
}
@article{TrappLammersEngudaretal.2023,
  author    = {Trapp, Svenja and Lammers, Tom and Engudar, Gokce and Hoehr, Cornelia and Denkova, Antonia G. and Paulßen, Elisabeth and de Kruijff, Robin M.},
  title     = {Membrane-based microfluidic solvent extraction of Ga-68 from aqueous Zn solutions: towards an automated cyclotron production loop},
  series = {EJNMMI Radiopharmacy and Chemistry},
  volume    = {2023},
  journal   = {EJNMMI Radiopharmacy and Chemistry},
  number    = {8, Article number: 9},
  publisher = {Springer Nature},
  issn      = {2365-421X},
  doi       = {10.1186/s41181-023-00195-2},
  pages     = {1 -- 14},
  year      = {2023},
  language  = {en}
}
@article{EngelmannShalabyShashaetal.2021,
  author    = {Engelmann, Ulrich M. and Shalaby, Ahmed and Shasha, Carolyn and Krishnan, Kannan M. and Krause, Hans-Joachim},
  title     = {Comparative modeling of frequency mixing measurements of magnetic nanoparticles using micromagnetic simulations and Langevin theory},
  series = {Nanomaterials},
  volume    = {11},
  journal   = {Nanomaterials},
  number    = {5},
  publisher = {MDPI},
  address   = {Basel},
  isbn      = {2079-4991},
  doi       = {10.3390/nano11051257},
  pages     = {1 -- 16},
  year      = {2021},
  abstract  = {Dual frequency magnetic excitation of magnetic nanoparticles (MNP) enables enhanced biosensing applications. This was studied from an experimental and theoretical perspective: nonlinear sum-frequency components of MNP exposed to dual-frequency magnetic excitation were measured as a function of static magnetic offset field. The Langevin model in thermodynamic equilibrium was fitted to the experimental data to derive parameters of the lognormal core size distribution. These parameters were subsequently used as inputs for micromagnetic Monte-Carlo (MC)-simulations. From the hysteresis loops obtained from MC-simulations, sum-frequency components were numerically demodulated and compared with both experiment and Langevin model predictions. From the latter, we derived that approximately 90\% of the frequency mixing magnetic response signal is generated by the largest 10\% of MNP. We therefore suggest that small particles do not contribute to the frequency mixing signal, which is supported by MC-simulation results. Both theoretical approaches describe the experimental signal shapes well, but with notable differences between experiment and micromagnetic simulations. These deviations could result from Brownian relaxations which are, albeit experimentally inhibited, included in MC-simulation, or (yet unconsidered) cluster-effects of MNP, or inaccurately derived input for MC-simulations, because the largest particles dominate the experimental signal but concurrently do not fulfill the precondition of thermodynamic equilibrium required by Langevin theory.},
  language  = {en}
}
@inproceedings{Kurz2008,
  author    = {Kurz, Melanie},
  title     = {On the benefit of moving images for the evaluation of form in virtual space : reflections in model theory},
  series = {Design and semantics of form and movement : DeSForM 2008 ; [Hochschule f{\"u}r Gestaltung Offenbach am Main, 6.-7.11.2008]},
  booktitle = {Design and semantics of form and movement : DeSForM 2008 ; [Hochschule f{\"u}r Gestaltung Offenbach am Main, 6.-7.11.2008]},
  editor    = {Feijs, Loe},
  publisher = {Philips},
  address   = {Eindhoven},
  isbn      = {978-90-809801-2-9},
  pages     = {31 -- 34},
  year      = {2008},
  language  = {en}
}
@article{AliaziziOezsoyluBakhshiSichanietal.2024,
  author    = {Aliazizi, Fereshteh and {\"O}zsoylu, Dua and Bakhshi Sichani, Soroush and Khorshid, Mehran and Glorieux, Christ and Robbens, Johan and Sch{\"o}ning, Michael Josef and Wagner, Patrick},
  title     = {Development and Calibration of a Microfluidic, Chip-Based Sensor System for Monitoring the Physical Properties of Water Samples in Aquacultures},
  series = {Micromachines},
  volume    = {15},
  journal   = {Micromachines},
  number    = {6},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-666X},
  doi       = {10.3390/mi15060755},
  year      = {2024},
  abstract  = {In this work, we present a compact, bifunctional chip-based sensor setup that measures the temperature and electrical conductivity of water samples, including specimens from rivers and channels, aquaculture, and the Atlantic Ocean. For conductivity measurements, we utilize the impedance amplitude recorded via interdigitated electrode structures at a single triggering frequency. The results are well in line with data obtained using a calibrated reference instrument. The new setup holds for conductivity values spanning almost two orders of magnitude (river versus ocean water) without the need for equivalent circuit modelling. Temperature measurements were performed in four-point geometry with an on-chip platinum RTD (resistance temperature detector) in the temperature range between 2 °C and 40 °C, showing no hysteresis effects between warming and cooling cycles. Although the meander was not shielded against the liquid, the temperature calibration provided equivalent results to low conductive Milli-Q and highly conductive ocean water. The sensor is therefore suitable for inline and online monitoring purposes in recirculating aquaculture systems.},
  language  = {en}
}