@article{HoffmannRohrbachUhletal.2022,
  author    = {Hoffmann, Andreas and Rohrbach, Felix and Uhl, Matthias and Ceblin, Maximilian and Bauer, Thomas and Mallah, Marcel and Jacob, Timo and Heuermann, Holger and Kuehne, Alexander J. C.},
  title     = {Atmospheric pressure plasma-jet treatment of polyacrylonitrile-nonwovens—Stabilization and roll-to-roll processing},
  series = {Journal of Applied Polymer Science},
  volume    = {139},
  journal   = {Journal of Applied Polymer Science},
  number    = {37},
  publisher = {Wiley},
  issn      = {0021-8995 (Print)},
  doi       = {10.1002/app.52887},
  pages     = {1 -- 9},
  year      = {2022},
  abstract  = {Carbon nanofiber nonwovens represent a powerful class of materials with prospective application in filtration technology or as electrodes with high surface area in batteries, fuel cells, and supercapacitors. While new precursor-to-carbon conversion processes have been explored to overcome productivity restrictions for carbon fiber tows, alternatives for the two-step thermal conversion of polyacrylonitrile precursors into carbon fiber nonwovens are absent. In this work, we develop a continuous roll-to-roll stabilization process using an atmospheric pressure microwave plasma jet. We explore the influence of various plasma-jet parameters on the morphology of the nonwoven and compare the stabilized nonwoven to thermally stabilized samples using scanning electron microscopy, differential scanning calorimetry, and infrared spectroscopy. We show that stabilization with a non-equilibrium plasma-jet can be twice as productive as the conventional thermal stabilization in a convection furnace, while producing electrodes of comparable electrochemical performance.},
  language  = {en}
}
@inproceedings{WalterElsenMuelleretal.1999,
  author    = {Walter, Peter and Elsen, Ingo and M{\"u}ller, Holger and Kraiss, Karl-Friedrich},
  title     = {3D object recognition with a specialized mixtures of experts architecture},
  series = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings},
  booktitle = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {0-7803-5529-6},
  issn      = {1098-7576},
  doi       = {10.1109/IJCNN.1999.836243},
  pages     = {3563 -- 3568},
  year      = {1999},
  abstract  = {Aim of the AXON2 project (Adaptive Expert System for Object Recogniton using Neuml Networks) is the development of an object recognition system (ORS) capable of recognizing isolated 3d objects from arbitrary views. Commonly, classification is based on a single feature extracted from the original image. Here we present an architecture adapted from the Mixtures of Eaqerts algorithm which uses multiple neuml networks to integmte different features. During tmining each neural network specializes in a subset of objects or object views appropriate to the properties of the corresponding feature space. In recognition mode the system dynamically chooses the most relevant features and combines them with maximum eficiency. The remaining less relevant features arz not computed and do therefore not decelerate the-recognition process. Thus, the algorithm is well suited for ml-time applications.},
  language  = {en}
}
@article{ElsenKraiss1999,
  author    = {Elsen, Ingo and Kraiss, Karl-Friedrich},
  title     = {System concept and realization of a scalable neurocomputing architecture},
  series = {Systems Analysis Modelling Simulation},
  volume    = {35},
  journal   = {Systems Analysis Modelling Simulation},
  number    = {4},
  publisher = {Gordon and Breach Science Publishers},
  address   = {Amsterdam},
  issn      = {0232-9298},
  pages     = {399 -- 419},
  year      = {1999},
  abstract  = {This paper describes the realization of a novel neurocomputer which is based on the concepts of a coprocessor. In contrast to existing neurocomputers the main interest was the realization of a scalable, flexible system, which is capable of computing neural networks of arbitrary topology and scale, with full independence of special hardware from the software's point of view. On the other hand, computational power should be added, whenever needed and flexibly adapted to the requirements of the application. Hardware independence is achieved by a run time system which is capable of using all available computing power, including multiple host CPUs and an arbitrary number of neural coprocessors autonomously. The realization of arbitrary neural topologies is provided through the implementation of the elementary operations which can be found in most neural topologies.},
  language  = {en}
}
@article{ElsenKraissKrumbiegeletal.1999,
  author    = {Elsen, Ingo and Kraiss, Karl-Friedrich and Krumbiegel, Dirk and Walter, Peter and Wickel, Jochen},
  title     = {Visual information retrieval for 3D product identification: a midterm report},
  series = {KI - K{\"u}nstliche Intelligenz},
  volume    = {13},
  journal   = {KI - K{\"u}nstliche Intelligenz},
  number    = {1},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1610-1987},
  pages     = {64 -- 67},
  year      = {1999},
  language  = {en}
}
@inproceedings{Elsen1998,
  author    = {Elsen, Ingo},
  title     = {A pixel based approach to view based object recognition with self-organizing neural networks},
  series = {IECON'98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society},
  booktitle = {IECON'98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {0-7803-4503-7},
  doi       = {10.1109/IECON.1998.724032},
  pages     = {2040 -- 2044},
  year      = {1998},
  abstract  = {This paper addresses the pixel based classification of three dimensional objects from arbitrary views. To perform this task a coding strategy, inspired by the biological model of human vision, for pixel data is described. The coding strategy ensures that the input data is invariant against shift, scale and rotation of the object in the input domain. The image data is used as input to a class of self organizing neural networks, the Kohonen-maps or self-organizing feature maps (SOFM). To verify this approach two test sets have been generated: the first set, consisting of artificially generated images, is used to examine the classification properties of the SOFMs; the second test set examines the clustering capabilities of the SOFM when real world image data is applied to the network after it has been preprocessed to be invariant against shift, scale and rotation. It is shown that the clustering capability of the SOFM is strongly dependant on the invariance coding of the images.},
  language  = {en}
}
@inproceedings{ElsenKraissKrumbiegel1997,
  author    = {Elsen, Ingo and Kraiss, Karl-Friedrich and Krumbiegel, Dirk},
  title     = {Pixel based 3D object recognition with bidirectional associative memories},
  series = {International Conference on Neural Networks 1997},
  booktitle = {International Conference on Neural Networks 1997},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {0-7803-4122-8},
  pages     = {1679 -- 1684},
  year      = {1997},
  abstract  = {This paper addresses the pixel based recognition of 3D objects with bidirectional associative memories. Computational power and memory requirements for this approach are identified and compared to the performance of current computer architectures by benchmarking different processors. It is shown, that the performance of special purpose hardware, like neurocomputers, is between one and two orders of magnitude higher than the performance of mainstream hardware. On the other hand, the calculation of small neural networks is performed more efficiently on mainstream processors. Based on these results a novel concept is developed, which is tailored for the efficient calculation of bidirectional associative memories. The computational efficiency is further enhanced by the application of algorithms and storage techniques which are matched to characteristics of the application at hand.},
  language  = {en}
}
@article{WiegnerVolkerMainzetal.2023,
  author    = {Wiegner, Jonas and Volker, Hanno and Mainz, Fabian and Backes, Andreas and Loeken, Michael and H{\"u}ning, Felix},
  title     = {Energy analysis of a wireless sensor node powered by a Wiegand sensor},
  series = {Journal of Sensors and Sensor Systems (JSSS)},
  volume    = {12},
  journal   = {Journal of Sensors and Sensor Systems (JSSS)},
  number    = {1},
  publisher = {Copernicus Publ.},
  address   = {G{\"o}ttingen},
  issn      = {2194-878X},
  doi       = {10.5194/jsss-12-85-2023},
  pages     = {85 -- 92},
  year      = {2023},
  abstract  = {This article describes an Internet of things (IoT) sensing device with a wireless interface which is powered by the energy-harvesting method of the Wiegand effect. The Wiegand effect, in contrast to continuous sources like photovoltaic or thermal harvesters, provides small amounts of energy discontinuously in pulsed mode. To enable an energy-self-sufficient operation of the sensing device with this pulsed energy source, the output energy of the Wiegand generator is maximized. This energy is used to power up the system and to acquire and process data like position, temperature or other resistively measurable quantities as well as transmit these data via an ultra-low-power ultra-wideband (UWB) data transmitter. A proof-of-concept system was built to prove the feasibility of the approach. The energy consumption of the system during start-up was analysed, traced back in detail to the individual components, compared to the generated energy and processed to identify further optimization options. Based on the proof of concept, an application prototype was developed.},
  language  = {en}
}
@inproceedings{ChircuCzarneckiFriedmannetal.2023,
  author    = {Chircu, Alina and Czarnecki, Christian and Friedmann, Daniel and Pomaskow, Johanna and Sultanow, Eldar},
  title     = {Towards a Digital Twin of Society},
  series = {Proceedings of the 56th Hawaii International Conference on System Sciences 2023},
  booktitle = {Proceedings of the 56th Hawaii International Conference on System Sciences 2023},
  publisher = {University of Hawai'i},
  address   = {Honolulu},
  isbn      = {978-0-9981331-6-4},
  pages     = {6748 -- 6757},
  year      = {2023},
  abstract  = {This paper describes the potential for developing a digital twin of society- a dynamic model that can be used to observe, analyze, and predict the evolution of various societal aspects. Such a digital twin can help governmental agencies and policy makers in interpreting trends, understanding challenges, and making decisions regarding investments or policies necessary to support societal development and ensure future prosperity. The paper reviews related work regarding the digital twin paradigm and its applications. The paper presents a motivating case study- an analysis of opportunities and challenges faced by the German federal employment agency, Bundesagentur f¨ur Arbeit (BA), proposes solutions using digital twins, and describes initial proofs of concept for such solutions.},
  language  = {en}
}
@misc{WiegnerVolkerMainzetal.2022,
  author    = {Wiegner, J. and Volker, H. and Mainz, F. and Backes, A. and L{\"o}ken, M. and H{\"u}ning, Felix},
  title     = {Wiegand-Effect-Powered Wireless IT Sensor Node},
  year      = {2022},
  abstract  = {With the growing interest in small distributed sensors for the "Internet of Things", more attention is being paid to energy harvesting techologies. Reducing or eliminating the need for external power sources or batteries make devices more self-sufficient, more reliable, and reduces maintenance requirements. The Wiegand effect is a proven technology for harvesting small amounts of electrical power from mechanical motion.},
  language  = {en}
}
@inproceedings{AltherrConzenElsenetal.2023,
  author    = {Altherr, Lena and Conzen, Max and Elsen, Ingo and Frauenrath, Tobias and Lyrmann, Andreas},
  title     = {Sensor retrofitting of existing buildings in an interdisciplinary teaching project at university level},
  series = {Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel},
  booktitle = {Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel},
  editor    = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Schwarz, Andr{\´e}},
  publisher = {le-tex publishing services GmbH},
  address   = {Leipzig},
  isbn      = {978-3-910103-01-6},
  doi       = {10.33968/2023.04},
  pages     = {31 -- 40},
  year      = {2023},
  abstract  = {Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems},
  language  = {en}
}