@inproceedings{Matcha2016, author = {Matcha, Heike}, title = {From Designing Buildings from Systems to Designing Systems for Buildings}, series = {Complexity \& Simplicity - Proceedings of the 34th eCAADe Conference - Volume 1}, booktitle = {Complexity \& Simplicity - Proceedings of the 34th eCAADe Conference - Volume 1}, editor = {Herneoja, Aulikki and {\"O}sterlund, Toni and Markkanen, Piia}, publisher = {ECAADe}, address = {Oulu, Finland}, doi = {10.52842/conf.ecaade.2016.1.237}, pages = {237 -- 240}, year = {2016}, abstract = {We study the novel possibilities computer aided design and production open up for the design of building systems. Such systems today can, via individualized mass production, consist of a larger number and more complex parts than previously and therefore be assembled into more complex wholes. This opens up the possibility of designing specialized systems specifically for single buildings. The common order of starting with a building system and designing a building using this system can be reversed to designing a building first and then developing a system specifically for that building. We present and discuss research that incorporates students design projects into research work and fosters links between research and teaching.}, language = {en} } @inproceedings{Huening2019, author = {H{\"u}ning, Felix}, title = {Complexity for heterogeneous classes: teaching embedded systems using an open project approach}, series = {Varietas delectat: Complexity is the new normality - 47th Annual Conference, Budapest, Hungary16th - 20th September 2019. SEFI 47th Annual Conference Proceedings}, booktitle = {Varietas delectat: Complexity is the new normality - 47th Annual Conference, Budapest, Hungary16th - 20th September 2019. SEFI 47th Annual Conference Proceedings}, isbn = {978-2-87352-018-2}, pages = {540 -- 549}, year = {2019}, language = {en} } @inproceedings{WiesenSchleser2019, author = {Wiesen, Andreas and Schleser, Markus}, title = {Entwicklung einer Qualit{\"a}tssicherung f{\"u}r das Laserstrahlschweißen im Vakuum mittels Bildverarbeitung}, series = {Große Schweißtechnische Tagung}, booktitle = {Große Schweißtechnische Tagung}, publisher = {DVS-Media}, address = {D{\"u}sseldorf}, isbn = {978-3-96144-066-5}, pages = {1 -- 6}, year = {2019}, language = {de} } @inproceedings{OttenGerhardsSchleseretal.2019, author = {Otten, Christian and Gerhards, Benjamin and Schleser, Markus and Schwarz, A. and Gebhardt, Andreas}, title = {Innovative Laserschweißtechnologie f{\"u}r additiv gefertigte Bauteile}, series = {Große Schweißtechnische Tagung}, booktitle = {Große Schweißtechnische Tagung}, publisher = {DVS-Media}, address = {D{\"u}sseldorf}, isbn = {978-3-96144-066-5}, pages = {150 -- 157}, year = {2019}, language = {de} } @inproceedings{PohleFroehlichDalitzRichteretal.2020, author = {Pohle-Fr{\"o}hlich, Regina and Dalitz, Christoph and Richter, Charlotte and Hahnen, Tobias and St{\"a}udle, Benjamin and Albracht, Kirsten}, title = {Estimation of muscle fascicle orientation in ultrasonic images}, series = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5}, booktitle = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5}, publisher = {SciTePress}, address = {Set{\´u}bal, Portugal}, isbn = {978-989-758-402-2}, doi = {10.5220/0008933900790086}, pages = {79 -- 86}, year = {2020}, abstract = {We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates.}, language = {en} } @inproceedings{DinghoferHartung2020, author = {Dinghofer, Kai and Hartung, Frank}, title = {Analysis of Criteria for the Selection of Machine Learning Frameworks}, series = {2020 International Conference on Computing, Networking and Communications (ICNC)}, booktitle = {2020 International Conference on Computing, Networking and Communications (ICNC)}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1109/ICNC47757.2020.9049650}, pages = {373 -- 377}, year = {2020}, abstract = {With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.}, language = {en} } @inproceedings{KreyerMuellerEsch2020, author = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas}, title = {A Map-Based Model for the Determination of Fuel Consumption for Internal Combustion Engines as a Function of Flight Altitude}, publisher = {DGLR}, address = {Bonn}, doi = {10.25967/490162}, pages = {13 Seiten}, year = {2020}, abstract = {In addition to very high safety and reliability requirements, the design of internal combustion engines (ICE) in aviation focuses on economic efficiency. The objective must be to design the aircraft powertrain optimized for a specific flight mission with respect to fuel consumption and specific engine power. Against this background, expert tools provide valuable decision-making assistance for the customer. In this paper, a mathematical calculation model for the fuel consumption of aircraft ICE is presented. This model enables the derivation of fuel consumption maps for different engine configurations. Depending on the flight conditions and based on these maps, the current and the integrated fuel consumption for freely definable flight emissions is calculated. For that purpose, an interpolation method is used, that has been optimized for accuracy and calculation time. The mission boundary conditions flight altitude and power requirement of the ICE form the basis for this calculation. The mathematical fuel consumption model is embedded in a parent program. This parent program presents the simulated fuel consumption by means of an example flight mission for a representative airplane. The focus of the work is therefore on reproducing exact consumption data for flight operations. By use of the empirical approaches according to Gagg-Farrar [1] the power and fuel consumption as a function of the flight altitude are determined. To substantiate this approaches, a 1-D ICE model based on the multi-physical simulation tool GT-Suite® has been created. This 1-D engine model offers the possibility to analyze the filling and gas change processes, the internal combustion as well as heat and friction losses for an ICE under altitude environmental conditions. Performance measurements on a dynamometer at sea level for a naturally aspirated ICE with a displacement of 1211 ccm used in an aviation aircraft has been done to validate the 1-D ICE model. To check the plausibility of the empirical approaches with respect to the fuel consumption and performance adjustment for the flight altitude an analysis of the ICE efficiency chain of the 1-D engine model is done. In addition, a comparison of literature and manufacturer data with the simulation results is presented.}, language = {en} } @inproceedings{HingleyDikta2019, author = {Hingley, Peter and Dikta, Gerhard}, title = {Finding a well performing box-jenkins forecasting model for annualised patent filings counts}, series = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019}, booktitle = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019}, pages = {24 Folien}, year = {2019}, language = {en} } @inproceedings{StrieganStruthDickhoffetal.2019, author = {Striegan, Constantin J. D. and Struth, Benjamin and Dickhoff, Jens and Kusterer, Karsten and Funke, Harald and Bohn, Dieter}, title = {Numerical Simulations of the Micromix DLN Hydrogen Combustion Technology with LES and Comparison to Results of RANS and Experimental Data}, series = {Proceedings of International Gas Turbine Congress 2019 Tokyo, November 17-22, 2019, Tokyo, Japan.}, booktitle = {Proceedings of International Gas Turbine Congress 2019 Tokyo, November 17-22, 2019, Tokyo, Japan.}, isbn = {978-4-89111-010-9}, pages = {1 -- 9}, year = {2019}, language = {en} } @inproceedings{UlmerBraunChengetal.2021, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Adapting augmented reality systems to the users' needs using gamification and error solving methods}, series = {Procedia CIRP - 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0}, volume = {104}, booktitle = {Procedia CIRP - 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2021.11.024}, pages = {140 -- 145}, year = {2021}, abstract = {Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users' preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.}, language = {en} }