@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} } @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} } @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{FayyaziSardarThomasetal.2023, author = {Fayyazi, Mojgan and Sardar, Paramjotsingh and Thomas, Sumit Infent and Daghigh, Roonak and Jamali, Ali and Esch, Thomas and Kemper, Hans and Langari, Reza and Khayyam, Hamid}, title = {Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles}, volume = {15}, number = {6}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/su15065249}, pages = {38}, year = {2023}, abstract = {Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.}, language = {en} } @article{ElsenHartungHornetal.2001, author = {Elsen, Ingo and Hartung, Frank and Horn, Uwe and Kampmann, Markus and Peters, Liliane}, title = {Streaming technology in 3G mobile communication systems}, series = {Computer : innovative technology for computer professionals}, volume = {34}, journal = {Computer : innovative technology for computer professionals}, number = {9 Seiten}, editor = {Voas, Jeffrey}, publisher = {IEEE}, address = {New York}, issn = {0018-9162}, pages = {46 -- 52}, year = {2001}, abstract = {Third-generation mobile communication systems will combine standardized streaming with a range of unique services to provide high-quality Internet content that meets the specific needs of the rapidly growing mobile market.}, language = {en} } @inproceedings{DeyElsenFerreinetal.2021, author = {Dey, Thomas and Elsen, Ingo and Ferrein, Alexander and Frauenrath, Tobias and Reke, Michael and Schiffer, Stefan}, title = {CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom}, series = {PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference}, booktitle = {PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference}, editor = {Makedon, Fillia}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {9781450387927}, doi = {10.1145/3453892.3462697}, pages = {292 -- 299}, year = {2021}, abstract = {In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.}, 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} } @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} } @article{UlmerBraunChengetal.2023, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation}, series = {International Journal of Production Research}, journal = {International Journal of Production Research}, publisher = {Taylor \& Francis}, issn = {0020-7543 (Print)}, doi = {10.1080/00207543.2023.2166140}, year = {2023}, abstract = {Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers' cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.}, language = {en} } @article{BergmannMoehrenBraunetal.2023, author = {Bergmann, Ole and M{\"o}hren, Felix and Braun, Carsten and Janser, Frank}, title = {On the influence of elasticity on swept propeller noise}, series = {AIAA SCITECH 2023 Forum}, journal = {AIAA SCITECH 2023 Forum}, publisher = {AIAA}, address = {Reston, Va.}, doi = {10.2514/6.2023-0210}, year = {2023}, abstract = {High aerodynamic efficiency requires propellers with high aspect ratios, while propeller sweep potentially reduces noise. Propeller sweep and high aspect ratios increase elasticity and coupling of structural mechanics and aerodynamics, affecting the propeller performance and noise. Therefore, this paper analyzes the influence of elasticity on forward-swept, backward-swept, and unswept propellers in hover conditions. A reduced-order blade element momentum approach is coupled with a one-dimensional Timoshenko beam theory and Farassat's formulation 1A. The results of the aeroelastic simulation are used as input for the aeroacoustic calculation. The analysis shows that elasticity influences noise radiation because thickness and loading noise respond differently to deformations. In the case of the backward-swept propeller, the location of the maximum sound pressure level shifts forward by 0.5 °, while in the case of the forward-swept propeller, it shifts backward by 0.5 °. Therefore, aeroacoustic optimization requires the consideration of propeller deformation.}, language = {en} } @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{SchubaHoefkenLinzbach2022, author = {Schuba, Marko and H{\"o}fken, Hans-Wilhelm and Linzbach, Sophie}, title = {An ICS Honeynet for Detecting and Analyzing Cyberattacks in Industrial Plants}, series = {2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)}, booktitle = {2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)}, publisher = {IEEE}, isbn = {978-1-6654-4231-2}, doi = {10.1109/ICECET52533.2021.9698746}, pages = {6 Seiten}, year = {2022}, abstract = {Cybersecurity of Industrial Control Systems (ICS) is an important issue, as ICS incidents may have a direct impact on safety of people or the environment. At the same time the awareness and knowledge about cybersecurity, particularly in the context of ICS, is alarmingly low. Industrial honeypots offer a cheap and easy to implement way to raise cybersecurity awareness and to educate ICS staff about typical attack patterns. When integrated in a productive network, industrial honeypots may not only reveal attackers early but may also distract them from the actual important systems of the network. Implementing multiple honeypots as a honeynet, the systems can be used to emulate or simulate a whole Industrial Control System. This paper describes a network of honeypots emulating HTTP, SNMP, S7communication and the Modbus protocol using Conpot, IMUNES and SNAP7. The nodes mimic SIMATIC S7 programmable logic controllers (PLCs) which are widely used across the globe. The deployed honeypots' features will be compared with the features of real SIMATIC S7 PLCs. Furthermore, the honeynet has been made publicly available for ten days and occurring cyberattacks have been analyzed}, language = {en} } @article{PfaffEnningSutter2022, author = {Pfaff, Raphael and Enning, Manfred and Sutter, Stefan}, title = {A risk‑based approach to automatic brake tests for rail freight service: incident analysis and realisation concept}, series = {SN Applied Sciences}, volume = {4}, journal = {SN Applied Sciences}, number = {4}, publisher = {Springer}, address = {Cham}, issn = {2523-3971}, doi = {10.1007/s42452-022-05007-x}, pages = {1 -- 14}, year = {2022}, abstract = {This study reviews the practice of brake tests in freight railways, which is time consuming and not suitable to detect certain failure types. Public incident reports are analysed to derive a reasonable brake test hardware and communication architecture, which aims to provide automatic brake tests at lower cost than current solutions. The proposed solutions relies exclusively on brake pipe and brake cylinder pressure sensors, a brake release position switch as well as radio communication via standard protocols. The approach is embedded in the Wagon 4.0 concept, which is a holistic approach to a smart freight wagon. The reduction of manual processes yields a strong incentive due to high savings in manual labour and increased productivity.}, language = {en} } @inproceedings{NikolovskiRekeElsenetal.2021, author = {Nikolovski, Gjorgji and Reke, Michael and Elsen, Ingo and Schiffer, Stefan}, title = {Machine learning based 3D object detection for navigation in unstructured environments}, series = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)}, booktitle = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)}, publisher = {IEEE}, isbn = {978-1-6654-7921-9}, doi = {10.1109/IVWorkshops54471.2021.9669218}, pages = {236 -- 242}, year = {2021}, abstract = {In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.}, 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{MerkensHebel2021, author = {Merkens, Torsten and Hebel, Christoph}, title = {Sharing mobility concepts - flexible, sustainable, smart}, series = {Proceedings of the 1st UNITED - Southeast Asia Automotive Interest Group (SAIG) International Conference}, booktitle = {Proceedings of the 1st UNITED - Southeast Asia Automotive Interest Group (SAIG) International Conference}, isbn = {978-3-902103-94-9}, pages = {43 -- 44}, year = {2021}, language = {en} } @article{GoettenFingerHavermannetal.2021, author = {G{\"o}tten, Falk and Finger, Felix and Havermann, Marc and Braun, Carsten and Marino, M. and Bil, C.}, title = {Full configuration drag estimation of short-to-medium range fixed-wing UAVs and its impact on initial sizing optimization}, series = {CEAS Aeronautical Journal}, volume = {12}, journal = {CEAS Aeronautical Journal}, publisher = {Springer}, address = {Berlin}, issn = {1869-5590 (Online)}, doi = {10.1007/s13272-021-00522-w}, pages = {589 -- 603}, year = {2021}, abstract = {The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV's parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft's total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft.}, language = {en} } @inproceedings{ThomaFisherBraun2020, author = {Thoma, Andreas and Fisher, Alex and Braun, Carsten}, title = {Improving the px4 avoid algorithm by bio-inspired flight strategies}, series = {DLRK2020 - „Luft- und Raumfahrt - Verantwortung in allen Dimensionen"}, booktitle = {DLRK2020 - „Luft- und Raumfahrt - Verantwortung in allen Dimensionen"}, doi = {10.25967/530183}, pages = {10 Seiten}, year = {2020}, language = {en} } @inproceedings{ThomaFisherBertrandetal.2020, author = {Thoma, Andreas and Fisher, Alex and Bertrand, Olivier and Braun, Carsten}, title = {Evaluation of possible flight strategies for close object evasion from bumblebee experiments}, series = {Living Machines 2020: Biomimetic and Biohybrid Systems}, booktitle = {Living Machines 2020: Biomimetic and Biohybrid Systems}, editor = {Vouloutsi, Vasiliki and Mura, Anna and Tauber, Falk and Speck, Thomas and Prescott, Tony J. and Verschure, Paul F. M. J.}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-64312-6}, doi = {10.1007/978-3-030-64313-3_34}, pages = {354 -- 365}, year = {2020}, language = {en} } @article{GoettenHavermannBraunetal.2020, author = {G{\"o}tten, Falk and Havermann, Marc and Braun, Carsten and Marino, Matthew and Bil, Cees}, title = {Improved Form Factor for Drag Estimation of Fuselages with Various Cross Sections}, series = {Journal of Aircraft}, journal = {Journal of Aircraft}, publisher = {AIAA}, address = {Reston, Va.}, issn = {1533-3868}, doi = {10.2514/1.C036032}, pages = {1 -- 13}, year = {2020}, abstract = {The paper presents an aerodynamic investigation of 70 different streamlined bodies with fineness ratios ranging from 2 to 10. The bodies are chosen to idealize both unmanned and small manned aircraft fuselages and feature cross-sectional shapes that vary from circular to quadratic. The study focuses on friction and pressure drag in dependency of the individual body's fineness ratio and cross section. The drag forces are normalized with the respective body's wetted area to comply with an empirical drag estimation procedure. Although the friction drag coefficient then stays rather constant for all bodies, their pressure drag coefficients decrease with an increase in fineness ratio. Referring the pressure drag coefficient to the bodies' cross-sectional areas shows a distinct pressure drag minimum at a fineness ratio of about three. The pressure drag of bodies with a quadratic cross section is generally higher than for bodies of revolution. The results are used to derive an improved form factor that can be employed in a classic empirical drag estimation method. The improved formulation takes both the fineness ratio and cross-sectional shape into account. It shows superior accuracy in estimating streamlined body drag when compared with experimental data and other form factor formulations of the literature.}, language = {en} }