@inproceedings{ChristianMontagSchubaetal.2018,
  author    = {Christian, Esser and Montag, Tim and Schuba, Marko and Allhof, Manuel},
  title     = {Future critical infrastructure and security - cyberattacks on charging stations},
  series = {31st International Electric Vehicle Symposium \& Exhibition and International Electric Vehicle Technology Conference (EVS31 \& EVTeC 2018)},
  booktitle = {31st International Electric Vehicle Symposium \& Exhibition and International Electric Vehicle Technology Conference (EVS31 \& EVTeC 2018)},
  publisher = {Society of Automotive Engineers of Japan (JSAE)},
  address   = {Tokyo},
  isbn      = {978-1-5108-9157-9},
  pages     = {665 -- 671},
  year      = {2018},
  language  = {en}
}
@inproceedings{GaldiHartungDugelay2017,
  author    = {Galdi, Chiara and Hartung, Frank and Dugelay, Jean-Luc},
  title     = {Videos versus still images: Asymmetric sensor pattern noise comparison on mobile phones},
  series = {Electronic Imaging},
  booktitle = {Electronic Imaging},
  publisher = {Society for Imaging Science and Technology},
  address   = {Springfield, Virginia},
  issn      = {2470-1173},
  doi       = {10.2352/ISSN.2470-1173.2017.7.MWSF-331},
  pages     = {100 -- 103},
  year      = {2017},
  abstract  = {Nowadays, the most employed devices for recoding videos or capturing images are undoubtedly the smartphones. Our work investigates the application of source camera identification on mobile phones. We present a dataset entirely collected by mobile phones. The dataset contains both still images and videos collected by 67 different smartphones. Part of the images consists in photos of uniform backgrounds, especially collected for the computation of the RSPN. Identifying the source camera given a video is particularly challenging due to the strong video compression. The experiments reported in this paper, show the large variation in performance when testing an highly accurate technique on still images and videos.},
  language  = {en}
}
@inproceedings{HauggKreyerKemperetal.2020,
  author    = {Haugg, Albert Thomas and Kreyer, J{\"o}rg and Kemper, Hans and Hatesuer, Katerina and Esch, Thomas},
  title     = {Heat exchanger for ORC. adaptability and optimisation potentials},
  series = {IIR International Rankine 2020 Conference},
  booktitle = {IIR International Rankine 2020 Conference},
  doi       = {10.18462/iir.rankine.2020.1224},
  pages     = {10 Seiten},
  year      = {2020},
  abstract  = {The recovery of waste heat requires heat exchangers to extract it from a liquid or gaseous medium into another working medium, a refrigerant. In Organic Rankine Cycles (ORC) on Combustion Engines there are two major heat sources, the exhaust gas and the water/glycol fluid from the engine's cooling circuit. A heat exchanger design must be adapted to the different requirements and conditions resulting from the heat sources, fluids, system configurations, geometric restrictions, and etcetera. The Stacked Shell Cooler (SSC) is a new and very specific design of a plate heat exchanger, created by AKG, which allows with a maximum degree of freedom the optimization of heat exchange rate and the reduction of the related pressure drop. This optimization in heat exchanger design for ORC systems is even more important, because it reduces the energy consumption of the system and therefore maximizes the increase in overall efficiency of the engine.},
  language  = {en}
}
@inproceedings{ThomaStiemerBraunetal.2023,
  author    = {Thoma, Andreas and Stiemer, Luc and Braun, Carsten and Fisher, Alex and Gardi, Alessandro G.},
  title     = {Potential of hybrid neural network local path planner for small UAV in urban environments},
  series = {AIAA SCITECH 2023 Forum},
  booktitle = {AIAA SCITECH 2023 Forum},
  publisher = {AIAA},
  address   = {Reston, Va.},
  doi       = {10.2514/6.2023-2359},
  pages     = {13 Seiten},
  year      = {2023},
  abstract  = {This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17\%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance.},
  language  = {en}
}
@inproceedings{StarkRiepingEsch2023,
  author    = {Stark, Ralf and Rieping, Carla and Esch, Thomas},
  title     = {The impact of guide tubes on flow separation in rocket nozzles},
  series = {Aerospace Europe Conference 2023 - 10th EUCASS - 9th CEAS},
  booktitle = {Aerospace Europe Conference 2023 - 10th EUCASS - 9th CEAS},
  pages     = {8 Seiten},
  year      = {2023},
  abstract  = {Rocket engine test facilities and launch pads are typically equipped with a guide tube. Its purpose is to ensure the controlled and safe routing of the hot exhaust gases. In addition, the guide tube induces a suction that effects the nozzle flow, namely the flow separation during transient start-up and shut-down of the engine. A cold flow subscale nozzle in combination with a set of guide tubes was studied experimentally to determine the main influencing parameters.},
  language  = {en}
}
@inproceedings{StarkBartelDitscheetal.2023,
  author    = {Stark, Ralf and Bartel, Sebastian and Ditsche, Florian and Esch, Thomas},
  title     = {Design study of a 30kN LOX/LCH4 aerospike rocket engine for lunar lander application},
  series = {Aerospace Europe Conference 2023 - 10th EUCASS - 9th CEAS},
  booktitle = {Aerospace Europe Conference 2023 - 10th EUCASS - 9th CEAS},
  pages     = {9 Seiten},
  year      = {2023},
  abstract  = {Based on lunar lander concept EL3, various LOX/CH4 aerospike engines were studied. A distinction was made between single and cluster configurations as well as ideal and non-ideal contour concepts. It could be shown that non-ideal aerospike engines promise a significant payload gain.},
  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}
}
@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}
}
@inproceedings{ElsenHawariJohnen2010,
  author    = {Elsen, Ingo and Hawari, Asma and Johnen, Uwe},
  title     = {Produktkernel in der Systemintegration (Erfahrungsbericht aus der Praxis)},
  series = {Vom Projekt zum Produkt - Fachtagung des GI-Fachausschusses Management der Anwendungsentwicklung und -wartung im Fachbereich Wirtschaftsinformatik (WI-MAW), 1. - 3. Dezember 2010 in Aachen},
  booktitle = {Vom Projekt zum Produkt - Fachtagung des GI-Fachausschusses Management der Anwendungsentwicklung und -wartung im Fachbereich Wirtschaftsinformatik (WI-MAW), 1. - 3. Dezember 2010 in Aachen},
  editor    = {Pietsch, Wolfram and Krams, Benedikt},
  publisher = {Gesellschaft f{\"u}r Informatik eV},
  address   = {Bonn},
  isbn      = {9783885792727},
  issn      = {1617-5468},
  pages     = {93 -- 102},
  year      = {2010},
  abstract  = {In der Vergangenheit basierten große Systemintegrationsprojekte in der Regel auf Individualentwicklungen f{\"u}r einzelne Kunden. Getrieben durch Kostendruck steigt aber der Bedarf nach standardisierten L{\"o}sungen, die gleichzeitig die individuellen Anforderungen des jeweiligen Umfelds ber{\"u}cksichtigen. T-Systems GEI GmbH wird beiden Anforderungen mit Produktkerneln gerecht. Neben den technischen Aspekten der Kernelentwicklung spielen besonders organisatorische Aspekte eine Rolle, um Kernel effizient und qualitativ hochwertig zu entwickeln, ohne deren Funktionalit{\"a}ten ins Uferlose wachsen zu lassen. Umgesetzt hat T-Systems dieses Konzept f{\"u}r Flughafeninformationssysteme. Damit kann dem wachsenden Bedarf der Flughafenbetreiber nach einer effizienten und kosteng{\"u}nstigen Softwarel{\"o}sung zur Unterst{\"u}tzung Ihrer Gesch{\"a}ftsprozesse entsprochen werden.},
  language  = {de}
}