TY - JOUR A1 - Digel, Ilya A1 - Akimbekov, Nuraly S. A1 - Rogachev, Evgeniy A1 - Pogorelova, Natalia T1 - Bacterial cellulose produced by Medusomyces gisevii on glucose and sucrose: biosynthesis and structural properties JF - Cellulose N2 - In this work, the effects of carbon sources and culture media on the production and structural properties of bacterial cellulose (BC) synthesized by Medusomyces gisevii have been studied. The culture medium was composed of different initial concentrations of glucose or sucrose dissolved in 0.4% extract of plain green tea. Parameters of the culture media (titratable acidity, substrate conversion degree etc.) were monitored daily for 20 days of cultivation. The BC pellicles produced on different carbon sources were characterized in terms of biomass yield, crystallinity and morphology by field emission scanning electron microscopy (FE-SEM), atomic force microscopy and X-ray diffraction. Our results showed that Medusomyces gisevii had higher BC yields in media with sugar concentrations close to 10 g L−1 after a 18–20 days incubation period. Glucose in general lead to a higher BC yield (173 g L−1) compared to sucrose (163.5 g L−1). The BC crystallinity degree and surface roughness were higher in the samples synthetized from sucrose. Obtained FE-SEM micrographs show that the BC pellicles synthesized in the sucrose media contained densely packed tangles of cellulose fibrils whereas the BC produced in the glucose media displayed rather linear geometry of the BC fibrils without noticeable aggregates. KW - Bacterial cellulose KW - Medusomyces gisevi KW - Carbon sources KW - Culture media KW - Cellulose nanostructure Y1 - 2023 U6 - https://doi.org/10.1007/s10570-023-05592-z SN - 1572-882X (Online) SN - 0969-0239 (Print) N1 - Corresponding author: Ilya Digel PB - Springer Science + Business Media CY - Dordrecht ER - TY - JOUR A1 - Laarmann, Lukas A1 - Thoma, Andreas A1 - Misch, Philipp A1 - Röth, Thilo A1 - Braun, Carsten A1 - Watkins, Simon A1 - Fard, Mohammad T1 - Automotive safety approach for future eVTOL vehicles JF - CEAS Aeronautical Journal N2 - The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL’s crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented. KW - eVTOL development KW - eVTOL safety KW - Crashworthiness KW - Automotive safety approach KW - Full-vehicle crash test Y1 - 2023 U6 - https://doi.org/10.1007/s13272-023-00655-0 SN - 1869-5590 (Online) SN - 1869-5582 (Print) N1 - Corresponding author: Lukas Laarmann PB - Springer Nature ER - TY - JOUR A1 - Fayyazi, Mojgan A1 - Sardar, Paramjotsingh A1 - Thomas, Sumit Infent A1 - Daghigh, Roonak A1 - Jamali, Ali A1 - Esch, Thomas A1 - Kemper, Hans A1 - Langari, Reza A1 - Khayyam, Hamid T1 - Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles N2 - 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. KW - optimization system KW - intelligent control KW - fuel cell vehicle KW - machine learning KW - artificial intelligence KW - intelligent energy management Y1 - 2023 U6 - https://doi.org/10.3390/su15065249 N1 - This article belongs to the Special Issue "Circular Economy and Artificial Intelligence" VL - 15 IS - 6 SP - 38 PB - MDPI CY - Basel 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 - https://doi.org/10.1007/978-3-031-33338-5_11 SP - 243 EP - 263 PB - Springer CY - Cham ER - TY - CHAP A1 - Arndt, Tobias A1 - Conzen, Max A1 - Elsen, Ingo A1 - Ferrein, Alexander A1 - Galla, Oskar A1 - Köse, Hakan A1 - Schiffer, Stefan A1 - Tschesche, Matteo T1 - Anomaly detection in the metal-textile industry for the reduction of the cognitive load of quality control workers T2 - PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments N2 - This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products. KW - Datasets KW - Neural networks KW - Anomaly detection KW - Quality control KW - Process optimization Y1 - 2023 SN - 9798400700699 U6 - https://doi.org/10.1145/3594806.3596558 N1 - PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments, Corfu, Greece, July 5 - 7, 2023 SP - 535 EP - 542 PB - ACM ER - TY - JOUR A1 - Ayala, Rafael Ceja A1 - Harris, Isaac A1 - Kleefeld, Andreas A1 - Pallikarakis, Nikolaos T1 - Analysis of the transmission eigenvalue problem with two conductivity parameters JF - Applicable Analysis N2 - In this paper, we provide an analytical study of the transmission eigenvalue problem with two conductivity parameters. We will assume that the underlying physical model is given by the scattering of a plane wave for an isotropic scatterer. In previous studies, this eigenvalue problem was analyzed with one conductive boundary parameter whereas we will consider the case of two parameters. We prove the existence and discreteness of the transmission eigenvalues as well as study the dependence on the physical parameters. We are able to prove monotonicity of the first transmission eigenvalue with respect to the parameters and consider the limiting procedure as the second boundary parameter vanishes. Lastly, we provide extensive numerical experiments to validate the theoretical work. KW - Transmission Eigenvalues KW - Conductive Boundary Condition KW - Inverse Scattering Y1 - 2023 U6 - https://doi.org/10.1080/00036811.2023.2181167 SN - 0003-6811 PB - Taylor & Francis ER - TY - JOUR A1 - Maurer, Florian A1 - Rieke, Christian A1 - Schemm, Ralf A1 - Stollenwerk, Dominik T1 - Analysis of an urban grid with high photovoltaic and e-mobility penetration JF - Energies N2 - This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub. KW - distribution grid simulation KW - smart-charging KW - e-mobility Y1 - 2023 U6 - https://doi.org/10.3390/en16083380 SN - 1996-1073 N1 - This article belongs to the Special Issue "Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids" N1 - Corresponding author: Florian Maurer VL - 16 IS - 8 PB - MDPI CY - Basel ER - TY - JOUR A1 - Kowalewski, Paul A1 - Bragard, Michael A1 - Hüning, Felix A1 - De Doncker, Rik W. T1 - An inexpensive Wiegand-sensor-based rotary encoder without rotating magnets for use in electrical drives JF - IEEE Transactions on Instrumentation and Measurement N2 - This paper introduces an inexpensive Wiegand-sensor-based rotary encoder that avoids rotating magnets and is suitable for electrical-drive applications. So far, Wiegand-sensor-based encoders usually include a magnetic pole wheel with rotating permanent magnets. These encoders combine the disadvantages of an increased magnet demand and a limited maximal speed due to the centripetal force acting on the rotating magnets. The proposed approach reduces the total demand of permanent magnets drastically. Moreover, the rotating part is manufacturable from a single piece of steel, which makes it very robust and cheap. This work presents the theoretical operating principle of the proposed approach and validates its benefits on a hardware prototype. The presented proof-of-concept prototype achieves a mechanical resolution of 4.5 ° by using only 4 permanent magnets, 2Wiegand sensors and a rotating steel gear wheel with 20 teeth. KW - Rotary encoder KW - Wiegand sensor Y1 - 2023 U6 - https://doi.org/10.1109/TIM.2023.3326166 SN - 0018-9456 (Print) SN - 1557-9662 (Online) VL - 72 SP - 10 Seiten PB - IEEE CY - New York ER - TY - JOUR A1 - Gaigall, Daniel ED - AitSahlia, Farid T1 - Allocating and forecasting changes in risk JF - Journal of risk N2 - We consider time-dependent portfolios and discuss the allocation of changes in the risk of a portfolio to changes in the portfolio’s components. For this purpose we adopt established allocation principles. We also use our approach to obtain forecasts for changes in the risk of the portfolio’s components. To put the approach into practice we present an implementation based on the output of a simulation. Allocation is illustrated with an example portfolio in the context of Solvency II. The quality of the forecasts is investigated with an empirical study. KW - portfolio risk KW - allocation KW - forecast KW - covariance principle KW - conditional expectation principle Y1 - 2023 U6 - https://doi.org/10.21314/JOR.2022.048 SN - 1755-2842 SN - 1465-1211 VL - 25 IS - 3 SP - 1 EP - 24 PB - Infopro Digital Risk CY - London 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 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 - https://doi.org/10.1007/978-3-031-39059-3_16 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 235 EP - 253 PB - Springer CY - Cham ER -