@inproceedings{LahrsKrisamHerrmann2023,
  author    = {Lahrs, Lennart and Krisam, Pierre and Herrmann, Ulf},
  title     = {Envisioning a collaborative energy system planning platform for the energy transition at the district level},
  series = {ECOS 2023. The 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems},
  booktitle = {ECOS 2023. The 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems},
  publisher = {Procedings of ECOS 2023},
  doi       = {10.52202/069564-0284},
  pages     = {3163 -- 3170},
  year      = {2023},
  abstract  = {Residential and commercial buildings account for more than one-third of global energy-related greenhouse gas emissions. Integrated multi-energy systems at the district level are a promising way to reduce greenhouse gas emissions by exploiting economies of scale and synergies between energy sources. Planning district energy systems comes with many challenges in an ever-changing environment. Computational modelling established itself as the state-of-the-art method for district energy system planning. Unfortunately, it is still cumbersome to combine standalone models to generate insights that surpass their original purpose. Ideally, planning processes could be solved by using modular tools that easily incorporate the variety of competing and complementing computational models. Our contribution is a vision for a collaborative development and application platform for multi-energy system planning tools at the district level. We present challenges of district energy system planning identified in the literature and evaluate whether this platform can help to overcome these challenges. Further, we propose a toolkit that represents the core technical elements of the platform. Lastly, we discuss community management and its relevance for the success of projects with collaboration and knowledge sharing at their core.},
  language  = {en}
}
@inproceedings{KueppersSchubaNeugebaueretal.2023,
  author    = {K{\"u}ppers, Malte and Schuba, Marko and Neugebauer, Georg and H{\"o}ner, Tim and Hack, Sacha},
  title     = {Security analysis of the KNX smart building protocol},
  series = {ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security},
  booktitle = {ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security},
  publisher = {ACM},
  doi       = {10.1145/3600160.3605167},
  pages     = {1 -- 7},
  year      = {2023},
  abstract  = {KNX is a protocol for smart building automation, e.g., for automated heating, air conditioning, or lighting. This paper analyses and evaluates state-of-the-art KNX devices from manufacturers Merten, Gira and Siemens with respect to security. On the one hand, it is investigated if publicly known vulnerabilities like insecure storage of passwords in software, unencrypted communication, or denialof-service attacks, can be reproduced in new devices. On the other hand, the security is analyzed in general, leading to the discovery of a previously unknown and high risk vulnerability related to so-called BCU (authentication) keys.},
  language  = {en}
}
@inproceedings{KohlFreyerKraemeretal.2023,
  author    = {Kohl, Philipp and Freyer, Nils and Kr{\"a}mer, Yoka and Werth, Henri and Wolf, Steffen and Kraft, Bodo and Meinecke, Matthias and Z{\"u}ndorf, Albert},
  title     = {ALE: a simulation-based active learning evaluation framework for the parameter-driven comparison of query strategies for NLP},
  series = {Deep Learning Theory and Applications},
  booktitle = {Deep Learning Theory and Applications},
  editor    = {Conte, Donatello and Fred, Ana and Gusikhin, Oleg and Sansone, Carlo},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-39058-6 (Print)},
  doi       = {10.1007/978-3-031-39059-3_16},
  pages     = {235 -- 253},
  year      = {2023},
  abstract  = {Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance. However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP. The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.},
  language  = {en}
}
@inproceedings{KloeserBuesgenKohletal.2023,
  author    = {Kl{\"o}ser, Lars and B{\"u}sgen, Andr{\´e} and Kohl, Philipp and Kraft, Bodo and Z{\"u}ndorf, Albert},
  title     = {Explaining relation classification models with semantic extents},
  series = {Deep Learning Theory and Applications},
  booktitle = {Deep Learning Theory and Applications},
  editor    = {Conte, Donatello and Fred, Ana and Gusikhin, Oleg and Sansone, Carlo},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-39058-6 (Print)},
  doi       = {10.1007/978-3-031-39059-3_13},
  pages     = {189 -- 208},
  year      = {2023},
  abstract  = {In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relation classification. State-of-the-art systems are highly accurate on scientific benchmarks. A lack of explainability is currently a complicating factor in many real-world applications. Comprehensible systems are necessary to prevent biased, counterintuitive, or harmful decisions. We introduce semantic extents, a concept to analyze decision patterns for the relation classification task. Semantic extents are the most influential parts of texts concerning classification decisions. Our definition allows similar procedures to determine semantic extents for humans and models. We provide an annotation tool and a software framework to determine semantic extents for humans and models conveniently and reproducibly. Comparing both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the reliability and security of natural language processing systems. Semantic extents are an essential step in enabling applications in critical areas like healthcare or finance. Moreover, our work opens new research directions for developing methods to explain deep learning models.},
  language  = {en}
}
@inproceedings{HueningMund2023,
  author    = {H{\"u}ning, Felix and Mund, Cindy},
  title     = {Integration of agile development in standard labs},
  series = {51st Annual Conference of the European Society for Engineering Education (SEFI)},
  booktitle = {51st Annual Conference of the European Society for Engineering Education (SEFI)},
  doi       = {10.21427/NK4Z-WS73},
  pages     = {11 Seiten},
  year      = {2023},
  abstract  = {In addition to the technical content, modern courses at university should also teach professional skills to enhance the competencies of students towards their future work. The competency driven approach including technical as well as professional skills makes it necessary to find a suitable way for the integration into the corresponding module in a scalable and flexible manner. Agile development, for example, is essential for the development of modern systems and applications and makes use of dedicated professional skills of the team members, like structured group dynamics and communication, to enable the fast and reliable development. This paper presents an easy to integrate and flexible approach to integrate Scrum, an agile development method, into the lab of an existing module. Due to the different role models of Scrum the students have an individual learning success, gain valuable insight into modern system development and strengthen their communication and organization skills. The approach is implemented and evaluated in the module Vehicle Systems, but it can be transferred easily to other technical courses as well. The evaluation of the implementation considers feedback of all stakeholders, students, supervisor and lecturers, and monitors the observations during project lifetime.},
  language  = {en}
}
@inproceedings{HuelsenMulsowDabrowskietal.2023,
  author    = {H{\"u}lsen, Benjamin and Mulsow, Niklas A. and Dabrowski, Adam and Brinkmann, Wiebke and G{\"u}tzlaff, Joel and Spies, Leon and Czupalla, Markus and Kirchner, Frank},
  title     = {Towards an autonomous micro rover with night survivability for lunar exploration},
  series = {Proceedings of the 74th International Astronautical Congress},
  booktitle = {Proceedings of the 74th International Astronautical Congress},
  publisher = {dfki},
  pages     = {12 Seiten},
  year      = {2023},
  abstract  = {In Europe, efforts are underway to develop key technologies that can be used to explore the Moon and to exploit the resources available. This includes technologies for in-situ resource utilization (ISRU), facilitating the possibility of a future Moon Village. The Moon is the next step for humans and robots to exploit the use of available resources for longer term missions, but also for further exploration of the solar system. A challenge for effective exploration missions is to achieve a compact and lightweight robot to reduce launch costs and open up the possibility of secondary payload options. Current micro rover concepts are primarily designed to last for one day of solar illumination and show a low level of autonomy. Extending the lifetime of the system by enabling survival of the lunar night and implementing a high level of autonomy will significantly increase potential mission applications and the operational range. As a reference mission, the deployment of a micro rover in the equatorial region of the Moon is being considered. An overview of mission parameters and a detailed example mission sequence is given in this paper. The mission parameters are based on an in-depth study of current space agency roadmaps, scientific goals, and upcoming flight opportunities. Furthermore, concepts of the ongoing international micro rover developments are analyzed along with technology solutions identified for survival of lunar nights and a high system autonomy. The results provide a basis of a concise requirements set-up to allow dedicated system developments and qualification measures in the future.},
  language  = {en}
}
@inproceedings{GrundAltherr2023,
  author    = {Grund, Raphael M. and Altherr, Lena},
  title     = {Development of an open source energy disaggregation tool for the home automation platform Home Assistant},
  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       = {10.33968/2023.02},
  pages     = {11 -- 20},
  year      = {2023},
  abstract  = {In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.},
  language  = {en}
}
@inproceedings{FunkeBeckmannStefanetal.2023,
  author    = {Funke, Harald and Beckmann, Nils and Stefan, Lukas and Keinz, Jan},
  title     = {Hydrogen combustor integration study for a medium range aircraft engine using the dry-low NOx "Micromix" combustion principle},
  series = {Proceedings of the ASME Turbo Expo 2023: Turbomachinery Technical Conference and Exposition. Volume 1: Aircraft Engine.},
  booktitle = {Proceedings of the ASME Turbo Expo 2023: Turbomachinery Technical Conference and Exposition. Volume 1: Aircraft Engine.},
  publisher = {ASME},
  address   = {New York},
  isbn      = {978-0-7918-8693-9},
  doi       = {10.1115/GT2023-102370},
  pages     = {12 Seiten},
  year      = {2023},
  abstract  = {The feasibility study presents results of a hydrogen combustor integration for a Medium-Range aircraft engine using the Dry-Low-NOₓ Micromix combustion principle. Based on a simplified Airbus A320-type flight mission, a thermodynamic performance model of a kerosene and a hydrogen-powered V2530-A5 engine is used to derive the thermodynamic combustor boundary conditions. A new combustor design using the Dry-Low NOx Micromix principle is investigated by slice model CFD simulations of a single Micromix injector for design and off-design operation of the engine. Combustion characteristics show typical Micromix flame shapes and good combustion efficiencies for all flight mission operating points. Nitric oxide emissions are significant below ICAO CAEP/8 limits. For comparison of the Emission Index (EI) for NOₓ emissions between kerosene and hydrogen operation, an energy (kerosene) equivalent Emission Index is used. A full 15° sector model CFD simulation of the combustion chamber with multiple Micromix injectors including inflow homogenization and dilution and cooling air flows investigates the combustor integration effects, resulting NOₓ emission and radial temperature distributions at the combustor outlet. The results show that the integration of a Micromix hydrogen combustor in actual aircraft engines is feasible and offers, besides CO₂ free combustion, a significant reduction of NOₓ emissions compared to kerosene operation.},
  language  = {en}
}
@inproceedings{FreyerThewesMeinecke2023,
  author    = {Freyer, Nils and Thewes, Dustin and Meinecke, Matthias},
  title     = {GUIDO: a hybrid approach to guideline discovery \& ordering from natural language texts},
  series = {Proceedings of the 12th International Conference on Data Science, Technology and Applications DATA - Volume 1},
  booktitle = {Proceedings of the 12th International Conference on Data Science, Technology and Applications DATA - Volume 1},
  editor    = {Gusikhin, Oleg and Hammoudi, Slimane and Cuzzocrea, Alfredo},
  isbn      = {978-989-758-664-4},
  issn      = {2184-285X},
  doi       = {10.5220/0012084400003541},
  pages     = {335 -- 342},
  year      = {2023},
  abstract  = {Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better resul ts than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low.},
  language  = {en}
}
@inproceedings{EichenbaumNikolovskiMuelhensetal.2023,
  author    = {Eichenbaum, Julian and Nikolovski, Gjorgji and M{\"u}lhens, Leon and Reke, Michael and Ferrein, Alexander and Scholl, Ingrid},
  title     = {Towards a lifelong mapping approach using Lanelet 2 for autonomous open-pit mine operations},
  series = {2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)},
  booktitle = {2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)},
  publisher = {IEEE},
  isbn      = {979-8-3503-2069-5 (Online)},
  doi       = {10.1109/CASE56687.2023.10260526},
  pages     = {8 Seiten},
  year      = {2023},
  abstract  = {Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.},
  language  = {en}
}