TY - CHAP A1 - Maurer, Florian A1 - Miskiw, Kim K. A1 - Acosta, Rebeca Ramirez A1 - Harder, Nick A1 - Sander, Volker A1 - Lehnhoff, Sebastian ED - Jorgensen, Bo Norregaard ED - Pereira da Silva, Luiz Carlos ED - Ma, Zheng T1 - Market abstraction of energy markets and policies - application in an agent-based modeling toolbox T2 - EI.A 2023: Energy Informatics N2 - In light of emerging challenges in energy systems, markets are prone to changing dynamics and market design. Simulation models are commonly used to understand the changing dynamics of future electricity markets. However, existing market models were often created with specific use cases in mind, which limits their flexibility and usability. This can impose challenges for using a single model to compare different market designs. This paper introduces a new method of defining market designs for energy market simulations. The proposed concept makes it easy to incorporate different market designs into electricity market models by using relevant parameters derived from analyzing existing simulation tools, morphological categorization and ontologies. These parameters are then used to derive a market abstraction and integrate it into an agent-based simulation framework, allowing for a unified analysis of diverse market designs. Furthermore, we showcase the usability of integrating new types of long-term contracts and over-the-counter trading. To validate this approach, two case studies are demonstrated: a pay-as-clear market and a pay-as-bid long-term market. These examples demonstrate the capabilities of the proposed framework. KW - Energy market design KW - Agent-based simulation KW - Market modeling Y1 - 2023 SN - 978-3-031-48651-7 (Print) SN - 978-3-031-48652-4 (eBook) U6 - http://dx.doi.org/10.1007/978-3-031-48652-4_10 N1 - Energy Informatics Academy Conference, 6-8 December 23, Campinas, Brazil. N1 - Part of the Lecture Notes in Computer Science book series (LNCS,volume 14468). SP - 139 EP - 157 PB - Springer CY - Cham ER - TY - JOUR A1 - Hammer, Thorben A1 - Quitter, Julius A1 - Mayntz, Joscha A1 - Bauschat, J.-Michael A1 - Dahmann, Peter A1 - Götten, Falk A1 - Hille, S. A1 - Stumpf, E. T1 - Free fall drag estimation of small-scale multirotor unmanned aircraft systems using computational fluid dynamics and wind tunnel experiments JF - CEAS Aeronautical Journal N2 - New European Union (EU) regulations for UAS operations require an operational risk analysis, which includes an estimation of the potential danger of the UAS crashing. A key parameter for the potential ground risk is the kinetic impact energy of the UAS. The kinetic energy depends on the impact velocity of the UAS and, therefore, on the aerodynamic drag and the weight during free fall. Hence, estimating the impact energy of a UAS requires an accurate drag estimation of the UAS in that state. The paper at hand presents the aerodynamic drag estimation of small-scale multirotor UAS. Multirotor UAS of various sizes and configurations were analysed with a fully unsteady Reynolds-averaged Navier–Stokes approach. These simulations included different velocities and various fuselage pitch angles of the UAS. The results were compared against force measurements performed in a subsonic wind tunnel and provided good consistency. Furthermore, the influence of the UAS`s fuselage pitch angle as well as the influence of fixed and free spinning propellers on the aerodynamic drag was analysed. Free spinning propellers may increase the drag by up to 110%, depending on the fuselage pitch angle. Increasing the fuselage pitch angle of the UAS lowers the drag by 40% up to 85%, depending on the UAS. The data presented in this paper allow for increased accuracy of ground risk assessments. KW - Multirotor UAS KW - Drag estimation KW - CFD KW - Wind tunnel experiments KW - Wind milling Y1 - 2023 U6 - http://dx.doi.org/10.1007/s13272-023-00702-w SN - 1869-5590 (Online) SN - 1869-5582 (Print) N1 - Corresponding author: Thorben Hammer PB - Springer CY - Wien ER - TY - CHAP A1 - Büsgen, André A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Cuzzocrea, Alfredo ED - Gusikhin, Oleg ED - Hammoudi, Slimane ED - Quix, Christoph T1 - From cracked accounts to fake IDs: user profiling on German telegram black market channels T2 - Data Management Technologies and Applications N2 - Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling. KW - Clustering KW - Natural language processing KW - Information extraction KW - Profile extraction KW - Text mining Y1 - 2023 SN - 978-3-031-37889-8 (Print) SN - 978-3-031-37890-4 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-37890-4_9 N1 - 10th International Conference, DATA 2021, Virtual Event, July 6–8, 2021, and 11th International Conference, DATA 2022, Lisbon, Portugal, July 11-13, 2022 SP - 176 EP - 202 PB - Springer CY - Cham ER - TY - CHAP A1 - Kohl, Philipp A1 - Freyer, Nils A1 - Krämer, Yoka A1 - Werth, Henri A1 - Wolf, Steffen A1 - Kraft, Bodo A1 - Meinecke, Matthias A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - ALE: a simulation-based active learning evaluation framework for the parameter-driven comparison of query strategies for NLP T2 - Deep Learning Theory and Applications. DeLTA 2023. Communications in Computer and Information Science N2 - 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. KW - Active learning KW - Query learning KW - Natural language processing KW - Deep learning KW - Reproducible research Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/978-3-031-39059-3 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 235 EP - 253 PB - Springer CY - Cham ER - TY - CHAP A1 - Klöser, Lars A1 - Büsgen, André A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - Explaining relation classification models with semantic extents T2 - DeLTA 2023: Deep Learning Theory and Applications N2 - 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. KW - Relation classification KW - Natural language processing KW - Natural language understanding KW - Information extraction KW - Trustworthy artificial intelligence Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-39059-3_13 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 189 EP - 208 PB - Springer CY - Cham ER - TY - CHAP A1 - Baier, Ralph A1 - Brauner, Philipp A1 - Brillowski, Florian A1 - Dammers, Hannah A1 - Liehner, Luca A1 - Pütz, Sebastian A1 - Schneider, Sebastian A1 - Schollemann, Alexander A1 - Steuer-Dankert, Linda A1 - Vervier, Luisa A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Mertens, Alexander A1 - Nagel, Saskia K. A1 - Schuh, Günther A1 - Ziefle, Martina A1 - Nitsch, Verena ED - Brecher, Christian ED - Schuh, Günther ED - van der Alst, Wil ED - Jarke, Matthias ED - Piller, Frank T. ED - Padberg, Melanie T1 - Human-centered work design for the internet of production T2 - Internet of production - fundamentals, applications and proceedings N2 - Like all preceding transformations of the manufacturing industry, the large-scale usage of production data will reshape the role of humans within the sociotechnical production ecosystem. To ensure that this transformation creates work systems in which employees are empowered, productive, healthy, and motivated, the transformation must be guided by principles of and research on human-centered work design. Specifically, measures must be taken at all levels of work design, ranging from (1) the work tasks to (2) the working conditions to (3) the organizational level and (4) the supra-organizational level. We present selected research across all four levels that showcase the opportunities and requirements that surface when striving for human-centered work design for the Internet of Production (IoP). (1) On the work task level, we illustrate the user-centered design of human-robot collaboration (HRC) and process planning in the composite industry as well as user-centered design factors for cognitive assistance systems. (2) On the working conditions level, we present a newly developed framework for the classification of HRC workplaces. (3) Moving to the organizational level, we show how corporate data can be used to facilitate best practice sharing in production networks, and we discuss the implications of the IoP for new leadership models. Finally, (4) on the supra-organizational level, we examine overarching ethical dimensions, investigating, e.g., how the new work contexts affect our understanding of responsibility and normative values such as autonomy and privacy. Overall, these interdisciplinary research perspectives highlight the importance and necessary scope of considering the human factor in the IoP. KW - Responsibility KW - Privacy KW - Digital leadership KW - Best practice sharing KW - Cognitive assistance system KW - Human-robot collaboration KW - Human-centered work design Y1 - 2023 SN - 978-3-030-98062-7 U6 - http://dx.doi.org/10.1007/978-3-030-98062-7_19-1 N1 - Part of the book series: Interdisciplinary Excellence Accelerator Series (IDEAS) SP - 1 EP - 23 PB - Springer CY - Cham ER - TY - JOUR A1 - Eggert, Mathias A1 - Kling, Rene T1 - How to distribute charging requests of electronic vehicles? A reservation-based approach JF - International Journal of Intelligent Transportation Systems Research N2 - The number of electronic vehicles increase steadily while the space for extending the charging infrastructure is limited. In particular in urban areas, where parking spaces in attractive areas are famous, opportunities to setup new charging stations is very limited. This leads to an overload of some very attractive charging stations and an underutilization of less attractive ones. Against this background, the paper at hand presents the design of an e-vehicle reservation system that aims at distributing the utilization of the charging infrastructure, particularly in urban areas. By applying a design science approach, the requirements for a reservation-based utilization approach are elicited and a model for a suitable distribution approach and its instantiation are developed. The artefact is evaluated by simulating the distribution effects based on data of real charging station utilizations. KW - Simulation KW - Parking KW - Charging station KW - Utilization improvement KW - Reservation system KW - Electronic vehicle Y1 - 2023 U6 - http://dx.doi.org/10.1007/s13177-023-00367-z SN - 1868-8659 N1 - Corresponding author: Mathias Eggert VL - 21 IS - 2023 SP - 437 EP - 460 PB - Springer CY - Berlin, Heidelberg, New York ER - TY - JOUR A1 - Adels, Klaudia A1 - Elbers, Gereon A1 - Diehl, Bernd A1 - Monakhova, Yulia T1 - Multicomponent analysis of dietary supplements containing glucosamine and chondroitin: comparative low- and high-field NMR spectroscopic study JF - Analytical Sciences N2 - With the prevalence of glucosamine- and chondroitin-containing dietary supplements for people with osteoarthritis in the marketplace, it is important to have an accurate and reproducible analytical method for the quantitation of these compounds in finished products. NMR spectroscopic method based both on low- (80 MHz) and high- (500–600 MHz) field NMR instrumentation was established, compared and validated for the determination of chondroitin sulfate and glucosamine in dietary supplements. The proposed method was applied for analysis of 20 different dietary supplements. In the majority of cases, quantification results obtained on the low-field NMR spectrometer are similar to those obtained with high-field 500–600 MHz NMR devices. Validation results in terms of accuracy, precision, reproducibility, limit of detection and recovery demonstrated that the developed method is fit for purpose for the marketed products. The NMR method was extended to the analysis of methylsulfonylmethane, adulterant maltodextrin, acetate and inorganic ions. Low-field NMR can be a quicker and cheaper alternative to more expensive high-field NMR measurements for quality control of the investigated dietary supplements. High-field NMR instrumentation can be more favorable for samples with complex composition due to better resolution, simultaneously giving the possibility of analysis of inorganic species such as potassium and chloride. KW - Glucosamine KW - Chondroitin sulfate KW - Polysaccharides KW - Dietary supplements KW - High-field NMR Y1 - 2023 U6 - http://dx.doi.org/10.1007/s44211-023-00433-2 SN - 1348-2246 (Online) SN - 0910-6340 (Print) N1 - Corresponding author: Yulia Monakhova VL - 2023 PB - Springer Verlag CY - Cham ER - TY - CHAP A1 - Eggert, Mathias A1 - Zähl, Philipp M. A1 - Wolf, Martin R. A1 - Haase, Martin ED - Cooper, Kendra M.L. ED - Bucchiarone, Antonio T1 - Applying leaderboards for quality improvement in software development projects T2 - Software Engineering for Games in Serious Contexts N2 - Software development projects often fail because of insufficient code quality. It is now well documented that the task of testing software, for example, is perceived as uninteresting and rather boring, leading to poor software quality and major challenges to software development companies. One promising approach to increase the motivation for considering software quality is the use of gamification. Initial research works already investigated the effects of gamification on software developers and come to promising. Nevertheless, a lack of results from field experiments exists, which motivates the chapter at hand. By conducting a gamification experiment with five student software projects and by interviewing the project members, the chapter provides insights into the changing programming behavior of information systems students when confronted with a leaderboard. The results reveal a motivational effect as well as a reduction of code smells. KW - Leaderboard KW - Gamification KW - Software testing KW - Software development Y1 - 2023 SN - 978-3-031-33337-8 (Print) SN - 978-3-031-33338-5 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-33338-5_11 SP - 243 EP - 263 PB - Springer CY - Cham ER - TY - CHAP A1 - Zähl, Philipp M. A1 - Theis, Sabine A1 - Wolf, Martin A1 - Köhler, Klemens ED - Chen, Jessie Y. C. ED - Fragomeni, Gino T1 - Teamwork in software development and what personality has to do with it - an overview T2 - Virtual, Augmented and Mixed Reality N2 - Due to the increasing complexity of software projects, software development is becoming more and more dependent on teams. The quality of this teamwork can vary depending on the team composition, as teams are always a combination of different skills and personality types. This paper aims to answer the question of how to describe a software development team and what influence the personality of the team members has on the team dynamics. For this purpose, a systematic literature review (n=48) and a literature search with the AI research assistant Elicit (n=20) were conducted. Result: A person’s personality significantly shapes his or her thinking and actions, which in turn influences his or her behavior in software development teams. It has been shown that team performance and satisfaction can be strongly influenced by personality. The quality of communication and the likelihood of conflict can also be attributed to personality. KW - Teamwork KW - Software KW - Personality KW - Performance KW - Elicit Y1 - 2023 SN - 978-3-031-35633-9 (Print) SN - 978-3-031-35634-6 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-35634-6_10 N1 - Virtual, Augmented and Mixed Reality: 15th International Conference. VAMR 2023. Held as Part of the 25th HCI International Conference. HCII 2023. Copenhagen, Denmark. July 23–28, 2023. SP - 130 EP - 153 PB - Springer CY - Cham ER -