@article{Golland2024,
  author    = {Golland, Alexander},
  title     = {Datenschutz beim Einsatz k{\"u}nstlicher Intelligenz im Unternehmen},
  series = {NWB},
  journal   = {NWB},
  number    = {6},
  publisher = {NWB},
  address   = {Herne},
  issn      = {0028-3460},
  pages     = {425 -- 432},
  year      = {2024},
  abstract  = {Seit Ende 2022 pr{\"a}gt das Schlagwort „K{\"u}nstliche Intelligenz" (KI) nicht nur den rechtswissenschaftlichen Diskurs. Die allgemeine Verf{\"u}gbarkeit von generativen KI-Modellen, allen voran die großen Sprachmodelle (Large Language Models, kurz: LLM) wie ChatGPT von OpenAI oder Bing AI von Microsoft, erfreuen sich gr{\"o}ßter Beliebtheit: LLM sind in der Lage, auf Grundlage statistischer Methoden - eine entsprechende Schnittstelle (Interface) vorausgesetzt - auch technisch wenig versierten Nutzern verst{\"a}ndliche Antworten auf ihre Fragen zu liefern. Dabei werden nicht nur umfassend Nutzerdaten verarbeitet, sondern auch auf weitere personenbezogene Daten zugegriffen sowie neue Daten erzeugt. Der Beitrag geht der Frage nach, welche spezifischen datenschutzrechtlichen Herausforderungen sich f{\"u}r Unternehmen beim Einsatz solcher LLM stellen.},
  language  = {de}
}
@inproceedings{SchlemmerPorstBassametal.2017,
  author    = {Schlemmer, Katharina and Porst, Dariusz and Bassam, Rasha and Artmann, Gerhard and Digel, Ilya},
  title     = {Effects of nitric oxide (NO) and ATP on red blood cell phenotype and deformability},
  series = {2nd YRA MedTech Symposium 2017 : June 8th - 9th / 2017 / Hochschule Ruhr-West},
  booktitle = {2nd YRA MedTech Symposium 2017 : June 8th - 9th / 2017 / Hochschule Ruhr-West},
  editor    = {Erni, Daniel and Fischerauer, Alice and Himmel, J{\"o}rg and Seeger, Thomas and Thelen, Klaus},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-9814801-9-1},
  doi       = {10.17185/duepublico/43984},
  pages     = {100 -- 101},
  year      = {2017},
  language  = {en}
}
@inproceedings{FerreinBharatheeshaSchifferetal.2019,
  author    = {Ferrein, Alexander and Bharatheesha, Mukunda and Schiffer, Stefan and Corbato, Carlos Hernandez},
  title     = {TRROS 2018 : Teaching Robotics with ROS Workshop at ERF 2018; Proceedings of the Workshop on Teaching Robotics with ROS (held at ERF 2018), co-located with European Robotics Forum 2018 (ERF 2018), Tampere, Finland, March 15th, 2018},
  series = {CEUR Workshop Proceedings},
  booktitle = {CEUR Workshop Proceedings},
  number    = {Vol-2329},
  issn      = {1613-0073},
  pages     = {68 Seiten},
  year      = {2019},
  language  = {en}
}
@inproceedings{DerschGeyerHerrmannetal.2002,
  author    = {Dersch, J{\"u}rgen and Geyer, Michael and Herrmann, Ulf and Jones, Scott A. and Kelly, Bruce and Kistner, Rainer and Ortmanns, Winfried and Pitz-Paal, Robert and Price, Henry},
  title     = {Solar Trough Integration Into Combined Cycle Systems},
  series = {Solar engineering 2002 : proceedings of the International Solar Energy Conference ; presented at the 2002 International Solar Energy Conference, a part of Solar 2002 - Sunrise on the Reliable Energy Economy, June 15 - 20, 2002, Reno, Nevada},
  booktitle = {Solar engineering 2002 : proceedings of the International Solar Energy Conference ; presented at the 2002 International Solar Energy Conference, a part of Solar 2002 - Sunrise on the Reliable Energy Economy, June 15 - 20, 2002, Reno, Nevada},
  editor    = {Pearson, J. Boise},
  publisher = {ASME},
  isbn      = {0-7918-1689-3},
  doi       = {doi:10.1115/SED2002-1072},
  pages     = {351 -- 359},
  year      = {2002},
  language  = {en}
}
@inproceedings{FerreinSchollNeumannetal.2019,
  author    = {Ferrein, Alexander and Scholl, Ingrid and Neumann, Tobias and Kr{\"u}ckel, Kai and Schiffer, Stefan},
  title     = {A system for continuous underground site mapping and exploration},
  doi       = {10.5772/intechopen.85859},
  pages     = {16 Seiten},
  year      = {2019},
  language  = {en}
}
@article{ClaerFerreinSchiffer2019,
  author    = {Claer, Mario and Ferrein, Alexander and Schiffer, Stefan},
  title     = {Calibration of a Rotating or Revolving Platform with a LiDAR Sensor},
  series = {Applied Sciences},
  volume    = {Volume 9},
  journal   = {Applied Sciences},
  number    = {issue 11, 2238},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2076-3417},
  doi       = {10.3390/app9112238},
  pages     = {18 Seiten},
  year      = {2019},
  language  = {en}
}
@inproceedings{RitzStrauch2012,
  author    = {Ritz, Thomas and Strauch, Jakob},
  title     = {Strukturierte Ermittlung beeinflussender Faktoren f{\"u}r mobile Softwarel{\"o}sungen},
  series = {MMS 2012 : mobile und ubiquit{\"a}re Informationssysteme ; 7. Konferenz zur "Mobile und Ubiquit{\"a}re Informationssysteme" ; 01 - 02. M{\"a}rz 2012 in Braunschweig, Germany. - (GI-Edition lecture notes in informatics ; 202)},
  booktitle = {MMS 2012 : mobile und ubiquit{\"a}re Informationssysteme ; 7. Konferenz zur "Mobile und Ubiquit{\"a}re Informationssysteme" ; 01 - 02. M{\"a}rz 2012 in Braunschweig, Germany. - (GI-Edition lecture notes in informatics ; 202)},
  editor    = {Back, Andrea},
  publisher = {Ges. f{\"u}r Informatik},
  address   = {Bonn},
  isbn      = {978-3-88579-296-3 (CD-ROM-Ausg.)},
  year      = {2012},
  language  = {de}
}
@article{KahmannRauschPluemeretal.2022,
  author    = {Kahmann, Stephanie L. and Rausch, Valentin and Pl{\"u}mer, Jonathan and M{\"u}ller, Lars P. and Pieper, Martin and Wegmann, Kilian},
  title     = {The automized fracture edge detection and generation of three-dimensional fracture probability heat maps},
  series = {Medical Engineering \& Physics},
  volume    = {2022},
  journal   = {Medical Engineering \& Physics},
  number    = {110},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1350-4533},
  pages     = {7 Seiten},
  year      = {2022},
  abstract  = {With proven impact of statistical fracture analysis on fracture classifications, it is desirable to minimize the manual work and to maximize repeatability of this approach. We address this with an algorithm that reduces the manual effort to segmentation, fragment identification and reduction. The fracture edge detection and heat map generation are performed automatically. With the same input, the algorithm always delivers the same output. The tool transforms one intact template consecutively onto each fractured specimen by linear least square optimization, detects the fragment edges in the template and then superimposes them to generate a fracture probability heat map. We hypothesized that the algorithm runs faster than the manual evaluation and with low (< 5 mm) deviation. We tested the hypothesis in 10 fractured proximal humeri and found that it performs with good accuracy (2.5 mm ± 2.4 mm averaged Euclidean distance) and speed (23 times faster). When applied to a distal humerus, a tibia plateau, and a scaphoid fracture, the run times were low (1-2 min), and the detected edges correct by visual judgement. In the geometrically complex acetabulum, at a run time of 78 min some outliers were considered acceptable. An automatically generated fracture probability heat map based on 50 proximal humerus fractures matches the areas of high risk of fracture reported in medical literature. Such automation of the fracture analysis method is advantageous and could be extended to reduce the manual effort even further.},
  language  = {en}
}
@article{BiewendtBlaschkeBoehnert2020,
  author    = {Biewendt, Marcel and Blaschke, Florian and B{\"o}hnert, Arno},
  title     = {An evaluation of corporate sustainability in context of the Jevons paradox},
  series = {SocioEconomic Challenges},
  volume    = {4},
  journal   = {SocioEconomic Challenges},
  number    = {3},
  publisher = {ARMG Publishing},
  address   = {Sumy},
  issn      = {2520-6214},
  doi       = {10.21272/sec.4(3).46-65.2020},
  pages     = {46 -- 65},
  year      = {2020},
  abstract  = {The successful implementation and continuous development of sustainable corporate-level solutions is a challenge. These are endeavours in which social, environmental, and financial aspects must be weighed against each other. They can prove difficult to handle and, in some cases, almost unrealistic. Concepts such as green controlling, IT, and manufacturing look promising and are constantly evolving. This paper aims to achieve a better understanding of the field of corporate sustainability (CS). It will evaluate the hypothesis by which Corporate Sustainability thrives, via being efficient, increasing the performance, and raising the value of the input of the enterprises to the resources used. In fact, Corporate Sustainability on the surface could seem to contradict the idea, which supports the understanding that it encourages the reduction of the heavy reliance on the use of natural resources, the overall environmental impact, and above all, their protection. To understand how the contradictory notion of CS came about, in this part of the paper, the emphasis is placed on providing useful insight to this regard. The first part of this paper summarizes various definitions, organizational theories, and measures used for CS and its derivatives like green controlling, IT, and manufacturing. Second, a case study is given that combines the aforementioned sustainability models. In addition to evaluating the hypothesis, the overarching objective of this paper is to demonstrate the use of green controlling, IT, and manufacturing in the corporate sector. Furthermore, this paper outlines the current challenges and possible directions for CS in the future.},
  language  = {en}
}
@article{EngelmannSimsekShalabyetal.2024,
  author    = {Engelmann, Ulrich M. and Simsek, Beril and Shalaby, Ahmed and Krause, Hans-Joachim},
  title     = {Key contributors to signal generation in frequency mixing magnetic detection (FMMD): an in silico study},
  series = {Sensors},
  volume    = {24},
  journal   = {Sensors},
  number    = {6},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s24061945},
  pages     = {Artikel 1945},
  year      = {2024},
  abstract  = {Frequency mixing magnetic detection (FMMD) is a sensitive and selective technique to detect magnetic nanoparticles (MNPs) serving as probes for binding biological targets. Its principle relies on the nonlinear magnetic relaxation dynamics of a particle ensemble interacting with a dual frequency external magnetic field. In order to increase its sensitivity, lower its limit of detection and overall improve its applicability in biosensing, matching combinations of external field parameters and internal particle properties are being sought to advance FMMD. In this study, we systematically probe the aforementioned interaction with coupled N{\´e}el-Brownian dynamic relaxation simulations to examine how key MNP properties as well as applied field parameters affect the frequency mixing signal generation. It is found that the core size of MNPs dominates their nonlinear magnetic response, with the strongest contributions from the largest particles. The drive field amplitude dominates the shape of the field-dependent response, whereas effective anisotropy and hydrodynamic size of the particles only weakly influence the signal generation in FMMD. For tailoring the MNP properties and parameters of the setup towards optimal FMMD signal generation, our findings suggest choosing large particles of core sizes dc > 25 nm nm with narrow size distributions (σ < 0.1) to minimize the required drive field amplitude. This allows potential improvements of FMMD as a stand-alone application, as well as advances in magnetic particle imaging, hyperthermia and magnetic immunoassays.},
  language  = {en}
}