@article{Gaigall2023, author = {Gaigall, Daniel}, title = {On the applicability of several tests to models with not identically distributed random effects}, series = {Statistics : A Journal of Theoretical and Applied Statistics}, volume = {57}, journal = {Statistics : A Journal of Theoretical and Applied Statistics}, publisher = {Taylor \& Francis}, address = {London}, isbn = {0323-3944}, issn = {1029-4910}, doi = {10.1080/02331888.2023.2193748}, pages = {14 Seiten}, year = {2023}, abstract = {We consider Kolmogorov-Smirnov and Cram{\´e}r-von-Mises type tests for testing central symmetry, exchangeability, and independence. In the standard case, the tests are intended for the application to independent and identically distributed data with unknown distribution. The tests are available for multivariate data and bootstrap procedures are suitable to obtain critical values. We discuss the applicability of the tests to random effects models, where the random effects are independent but not necessarily identically distributed and with possibly unknown distributions. Theoretical results show the adequacy of the tests in this situation. The quality of the tests in models with random effects is investigated by simulations. Empirical results obtained confirm the theoretical findings. A real data example illustrates the application.}, 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} } @incollection{FreyerKempt2023, author = {Freyer, Nils and Kempt, Hendrik}, title = {AI-DSS in healthcare and their power over health-insecure collectives}, series = {Justice in global health}, booktitle = {Justice in global health}, editor = {Bhakuni, Himani and Miotto, Lucas}, publisher = {Routledge}, address = {London}, isbn = {9781003399933}, doi = {10.4324/9781003399933-4}, pages = {38 -- 55}, year = {2023}, abstract = {AI-based systems are nearing ubiquity not only in everyday low-stakes activities but also in medical procedures. To protect patients and physicians alike, explainability requirements have been proposed for the operation of AI-based decision support systems (AI-DSS), which adds hurdles to the productive use of AI in clinical contexts. This raises two questions: Who decides these requirements? And how should access to AI-DSS be provided to communities that reject these standards (particularly when such communities are expert-scarce)? This chapter investigates a dilemma that emerges from the implementation of global AI governance. While rejecting global AI governance limits the ability to help communities in need, global AI governance risks undermining and subjecting health-insecure communities to the force of the neo-colonial world order. For this, this chapter first surveys the current landscape of AI governance and introduces the approach of relational egalitarianism as key to (global health) justice. To discuss the two horns of the referred dilemma, the core power imbalances faced by health-insecure collectives (HICs) are examined. The chapter argues that only strong demands of a dual strategy towards health-secure collectives can both remedy the immediate needs of HICs and enable them to become healthcare independent.}, 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{ElBerguiAbouabdillahBouriougetal.2023, author = {El Bergui, Omnia and Abouabdillah, Aziz and Bourioug, Mohamed and Schmitz, Dominik and Biel, Markus and Aboudrare, Abdellah and Krauss, Manuel and Jomaa, Ahlem and Romuli, Sebastian and M{\"u}ller, Joachim and Fagroud, Mustapha and Bouabid, Rachid}, title = {Innovative solutions for drought: Evaluating hydrogel application on onion cultivation (Allium cepa) in Morocco}, series = {Water}, volume = {15}, journal = {Water}, number = {11}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/w15111972}, pages = {Artikel 1972}, year = {2023}, abstract = {Throughout the last decade, and particularly in 2022, water scarcity has become a critical concern in Morocco and other Mediterranean countries. The lack of rainfall during spring was worsened by a succession of heat waves during the summer. To address this drought, innovative solutions, including the use of new technologies such as hydrogels, will be essential to transform agriculture. This paper presents the findings of a study that evaluated the impact of hydrogel application on onion (Allium cepa) cultivation in Meknes, Morocco. The treatments investigated in this study comprised two different types of hydrogel-based soil additives (Arbovit® polyacrylate and Huminsorb® polyacrylate), applied at two rates (30 and 20 kg/ha), and irrigated at two levels of water supply (100\% and 50\% of daily crop evapotranspiration; ETc). Two control treatments were included, without hydrogel application and with both water amounts. The experiment was conducted in an open field using a completely randomized design. The results indicated a significant impact of both hydrogel-type dose and water dose on onion plant growth, as evidenced by various vegetation parameters. Among the hydrogels tested, Huminsorb® Polyacrylate produced the most favorable outcomes, with treatment T9 (100\%, HP, 30 kg/ha) yielding 70.55 t/ha; this represented an increase of 11 t/ha as compared to the 100\% ETc treatment without hydrogel application. Moreover, the combination of hydrogel application with 50\% ETc water stress showed promising results, with treatment T4 (HP, 30 kg, 50\%) producing almost the same yield as the 100\% ETc treatment without hydrogel while saving 208 mm of water.}, 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} } @incollection{EggertZaehlWolfetal.2023, author = {Eggert, Mathias and Z{\"a}hl, Philipp M. and Wolf, Martin R. and Haase, Martin}, title = {Applying leaderboards for quality improvement in software development projects}, series = {Software Engineering for Games in Serious Contexts}, booktitle = {Software Engineering for Games in Serious Contexts}, editor = {Cooper, Kendra M.L. and Bucchiarone, Antonio}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-33337-8 (Print)}, doi = {10.1007/978-3-031-33338-5_11}, pages = {243 -- 263}, year = {2023}, abstract = {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.}, language = {en} } @inproceedings{EggertWeber2023, author = {Eggert, Mathias and Weber, Jannik}, title = {What drives the purchase decision in Instagram stores?}, series = {ECIS 2023 Research Papers}, booktitle = {ECIS 2023 Research Papers}, pages = {17 Seiten}, year = {2023}, abstract = {The popularity of social media and particularly Instagram grows steadily. People use the different platforms to share pictures as well as videos and to communicate with friends. The potential of social media platforms is also being used for marketing purposes and for selling products. While for Facebook and other online social media platforms the purchase decision factors are investigated several times, Instagram stores remain mainly unattended so far. The present research work closes this gap and sheds light into decisive factors for purchasing products offered in Instagram stores. A theoretical research model, which contains selected constructs that are assumed to have a significant influence on Instagram user´s purchase intention, is developed. The hypotheses are evaluated by applying structural equation modelling on survey data containing 127 relevant participants. The results of the study reveal that 'trust', 'personal recommendation', and 'usability' significantly influences user's buying intention in Instagram stores.}, language = {en} } @article{DroopChenRadfordetal.2023, author = {Droop, Philipp and Chen, Shaohuang and Radford, Melissa J. and Paulßen, Elisabeth and Gates, Byron D. and Reilly, Raymond M. and Radchenko, Valery and Hoehr, Cornelia}, title = {Synthesis of 197m/gHg labelled gold nanoparticles for targeted radionuclide therapy}, series = {Radiochimica Acta}, volume = {111}, journal = {Radiochimica Acta}, number = {10}, publisher = {De Gruyter}, address = {Berlin [u.a.]}, issn = {2193-3405}, doi = {10.1515/ract-2023-0144}, pages = {773 -- 779}, year = {2023}, abstract = {Meitner-Auger-electron emitters have a promising potential for targeted radionuclide therapy of cancer because of their short range and the high linear energy transfer of Meitner-Auger-electrons (MAE). One promising MAE candidate is 197m/gHg with its half-life of 23.8 h and 64.1 h, respectively, and high MAE yield. Gold nanoparticles (AuNPs) that are labelled with 197m/gHg could be a helpful tool for radiation treatment of glioblastoma multiforme when infused into the surgical cavity after resection to prevent recurrence. To produce such AuNPs, 197m/gHg was embedded into pristine AuNPs. Two different syntheses were tested starting from irradiated gold containing trace amounts of 197m/gHg. When sodium citrate was used as reducing agent, no 197m/gHg labelled AuNPs were formed, but with tannic acid, 197m/gHg labeled AuNPs were produced. The method was optimized by neutralizing the pH (pH = 7) of the Au/197m/gHg solution, which led to labelled AuNPs with a size of 12.3 ± 2.0 nm as measured by transmission electron microscopy. The labelled AuNPs had a concentration of 50 μg (gold)/mL with an activity of 151 ± 93 kBq/mL (197gHg, time corrected to the end of bombardment).}, language = {en} }