TY - JOUR A1 - Azzam, Mohamed A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Evaluating the Aging-Induced Voltage Slippery as Cause for Float Currents of Lithium-ion Cells JF - Batteries N2 - This paper provides a comprehensive exploration of float current analysis in lithium-ion batteries, a promising new testing method to assess calendar aging. Float currents are defined as the steady-state trickle charge current after a transient part. In the literature, a correlation to capacity loss was reported. Assuming the float current compensates for the voltage decay over time and is linked to calendar aging, effects from voltage slippery must be considered. The dU/dQ analysis suggests solely a loss of active lithium. Therefore, we investigate the solid electrolyte interphase (SEI) growth as the general aging mechanism to explain the origin of float currents. Our results show that the voltage slippery theory holds true within the low to middle test voltage ranges. However, the theory’s explanatory power begins to diminish at higher voltage ranges, suggesting the existence of additional, yet unidentified, factors influencing the float current. A shuttle reaction or lithiation of the cathode by electrolyte decomposition are the most promising alternative aging mechanisms at high voltages. The paper proposes a unique voltage slippery model to check for correlations between aging mechanisms, the float current test and the check-up test. For a better understanding, test strategies are proposed to verify/falsify the aging mechanisms beyond SEI. UR - https://doi.org/10.3390/batteries10010003 Y1 - 2023 UR - https://doi.org/10.3390/batteries10010003 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-43157 SN - 2313-0105 VL - 10 IS - 1 PB - MDPI CY - Basel ER - TY - JOUR A1 - Obando-Leitón, Miguel A1 - Dietze, Anna A1 - Castañeda González, Carmen M. A1 - Saeedi, Ali A1 - Karg, Sonja A1 - Hemmert, Werner T1 - On the Effect of High Stimulation Rates on Temporal Loudness Integration in Cochlear Implant Users JF - Trends in Hearing N2 - Long stimuli have lower detection thresholds or are perceived louder than short stimuli with the same intensity, an effect known as temporal loudness integration (TLI). In electric hearing, TLI for pulse trains with a fixed rate but varying number of pulses, i.e. stimulus duration, has mainly been investigated at clinically used stimulation rates. To study the effect of an overall effective stimulation rate at 100% channel crosstalk, we investigated TLI with (a) a clinically used single-channel stimulation rate of 1,500 pps and (b) a high stimulation rate of 18,000 pps, both for an apical and a basal electrode. Thresholds (THR), a line of equal loudness (BAL), and maximum acceptable levels (MALs) were measured in 10 MED-EL cochlear implant users. Stimulus durations varied from a single pulse to 300 ms long pulse trains. At 18,000 pps, the dynamic range (DR) increased by [Formula: see text] dB for the 300 ms pulse train. Amplitudes at THR, BAL, and MAL decreased monotonically with increasing stimulus duration. The decline was fitted with high accuracy with a power law function ([Formula: see text]). Threshold slopes were [Formula: see text] and [Formula: see text] dB per doubling of duration for the low and high rate, respectively, and were shallower than for acoustic hearing. The electrode location did not affect the amplitudes or slopes of the TLI curves. THR, BAL, and MAL were always lower for the higher rate and the DR was larger at the higher rate at all measured durations. UR - https://doi.org/10.1177/23312165231207229 Y1 - 2023 UR - https://doi.org/10.1177/23312165231207229 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-43749 SN - 2331-2165 VL - 27 PB - SAGE CY - London ER - TY - JOUR A1 - Paula, Daniel A1 - Bauder, Maximilian A1 - Pfeilschifter, Claus A1 - Petermeier, Franziska A1 - Kubjatko, Tibor A1 - Böhm, Klaus A1 - Riener, Andreas A1 - Schweiger, Hans-Georg T1 - Impact of Partially Automated Driving Functions on Forensic Accident Reconstruction: A Simulator Study on Driver Reaction Behavior in the Event of a Malfunctioning System Behavior JF - Sensors N2 - Partially automated driving functions (SAE Level 2) can control a vehicle’s longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver’s ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The results show that none of the subjects could avoid leaving their lane and moving into the oncoming lane and, therefore, could not control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 s. The second scenario examined driver responses to phantom braking caused by AEBS. We found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered. UR - https://doi.org/10.3390/s23249785 Y1 - 2023 UR - https://doi.org/10.3390/s23249785 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-42766 SN - 1424-8220 VL - 23 IS - 24 PB - MDPI CY - Basel ER - TY - JOUR A1 - Song, Rui A1 - Xu, Runsheng A1 - Festag, Andreas A1 - Ma, Jiaqi A1 - Knoll, Alois T1 - FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems JF - IEEE Transactions on Intelligent Vehicles N2 - Bird's eye view (BEV) perception is becoming increasingly important in the field of autonomous driving. It uses multi-view camera data to learn a transformer model that directly projects the perception of the road environment onto the BEV perspective. However, training a transformer model often requires a large amount of data, and as camera data for road traffic are often private, they are typically not shared. Federated learning offers a solution that enables clients to collaborate and train models without exchanging data but model parameters. In this paper, we introduce FedBEVT, a federated transformer learning approach for BEV perception. In order to address two common data heterogeneity issues in FedBEVT: (i) diverse sensor poses, and (ii) varying sensor numbers in perception systems, we propose two approaches - Federated Learning with Camera-Attentive Personalization (FedCaP) and Adaptive Multi-Camera Masking (AMCM), respectively. To evaluate our method in real-world settings, we create a dataset consisting of four typical federated use cases. Our findings suggest that FedBEVT outperforms the baseline approaches in all four use cases, demonstrating the potential of our approach for improving BEV perception in autonomous driving. UR - https://doi.org/10.1109/TIV.2023.3310674 Y1 - 2023 UR - https://doi.org/10.1109/TIV.2023.3310674 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-42789 SN - 2379-8904 SN - 2379-8858 VL - 9 IS - 1 SP - 958 EP - 969 PB - IEEE CY - New York ER - TY - JOUR A1 - Moerkerken, Albert A1 - Duijndam, Sem A1 - Blasch, Julia A1 - van Beukering, Pieter A1 - van Well, Erik T1 - Which farmers adopt solar energy? A regression analysis to explain adoption decisions over time JF - Renewable Energy Focus N2 - Farmers can play an important role in the critical renewable energy transition by generating solar energy. Farmers' adoption of a solar photovoltaic (PV) system results from a complex and interdependent array of technical, political, social, and economic factors. Under the regime of a covenant on energy and greenhouse gas emissions, the evolution of perceptions and responses to solar PV was monitored for a panel of 279 Dutch farmers in a unique series of surveys in 2015, 2018, and 2020. We observed that the willingness to reduce greenhouse gas emissions steadily increased from 35% of the farmers in 2015 to 82% in 2020, while the perceptions toward solar PV adoption among Dutch farmers fluctuated over this period. We examined Dutch farmers’ determinants of solar PV uptake through multiple regression analyses. Consistent with the literature, our results indicate that behavioural intentions, the perceived importance of renewable energy, and farmers’ innovativeness are the most critical determinants for solar PV adoption. Many farmers mentioned the decreased payback time as the most crucial motive to adopt solar PV. We argue that a stable long-term policy for renewable energy, as implemented in the Netherlands, creates attractive economic conditions for solar PV adoption. At the same time, the payback time is a critical factor in shaping farmers’ intentions and behaviour. We recommend more extensive research using panel datasets of farmers, while we also acknowledge the difficulty of obtaining high-quality panel data, which underlines the uniqueness of our analysis. UR - https://doi.org/10.1016/j.ref.2023.04.001 KW - Solar PV adoption KW - farmer behaviour KW - behavioural intentions KW - renewable energy policy KW - panel data Y1 - 2023 UR - https://doi.org/10.1016/j.ref.2023.04.001 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-40444 SN - 1755-0084 SN - 1878-0229 VL - 2023 IS - 45 SP - 169 EP - 178 PB - Elsevier CY - Amsterdam ER - TY - THES A1 - Mayer, Kevin T1 - Unveiling Hidden Knowledge: On the Effectiveness in Automotive Digital Forensics N2 - The continuous introduction of new services in modern automotive systems increases their digital capabilities and growing significance for digital forensic investigations. Those investigations are necessary to reconstruct events of potential crimes, generate security learnings, or resolve insurance cases due to the increased attack surface resulting from the increasing digital capabilities of modern vehicles. Consequently, the acquisition of vehicle and vehicle ecosystem components, as well as analysis of the collected data, has become pivotal for investigators seeking to reconstruct events effectively. This dissertation proposes a novel approach to leverage a multi-layered model utilizing ontologies in automotive digital forensics investigations, facilitating more efficient and effective data analysis by combining information from diverse sources. By harnessing ontologies to reuse knowledge collected from past investigations, investigators can seamlessly combine data from multiple sources, unveil hidden knowledge, and establish connections that might have otherwise remained obscure, thereby aiding in the resolution of crimes and apprehending criminals. A multi-layered model is presented to showcase increased effectiveness achieved through knowledge reuse. The model comprises a query layer that serves as an interface between investigators and the knowledge layer, allowing automotive digital forensics stakeholders to pose forensic questions and hypotheses via SPARQL queries. These queries extract data from the knowledge layer, which consists of two ontologies developed for this study: the general vehicle ontology, offering comprehensive knowledge on modern vehicles, and the vehicle type ontology, containing vehicle-specific knowledge, such as information from a Tesla Autopilot. The knowledge is generated through the operational layer, which introduces digital forensics tools generating results in an ontology-ready format. Two real-world investigations were undertaken to validate the effectiveness of the proposed approach: a thorough examination of the Tesla Autopilot system and an in-depth inquiry involving a GM Airbag control module. Both investigations involved crucial evidence items highly relevant for event reconstruction. The results demonstrate a significant increase in the effectiveness of automotive digital forensics investigations using the multi-layered model. This improvement is validated through three evaluation criteria and twelve metrics to show the application proximity of the multi-layered model. N2 - Durch die kontinuierliche Einführung neuer Dienste in modernen Automobilsystemen steigen deren digitale Fähigkeiten und ihre Bedeutung für digitalforensische Untersuchungen. Diese Untersuchungen sind notwendig, um Ereignisse potenzieller Straftaten zu rekonstruieren, Sicherheitserkenntnisse zu gewinnen oder Versicherungsfälle zu klären, da sich die Angriffsfläche aufgrund der zunehmenden digitalen Fähigkeiten moderner Fahrzeuge vergrößert hat. Folglich ist die Erfassung von Fahrzeugkomponenten und Bestandteile des Fahrzeugökosystems, sowie die Analyse der gesammelten Daten für Ermittelnde, die die Ereignisse effektiv rekonstruieren wollen, von zentraler Bedeutung. In dieser Dissertation wird ein neuartiger Ansatz zur Nutzung eines mehrschichtigen Modells unter Verwendung von Ontologien bei digitalen fahrzeugforensischen Untersuchungen vorgeschlagen, der eine effizientere und effektivere Datenanalyse durch die Kombination von Informationen aus verschiedenen Quellen ermöglicht. Durch die Nutzung von Ontologien zur Wiederverwendung von Wissen aus früheren Ermittlungen können Ermittelnde Daten aus verschiedenen Quellen nahtlos kombinieren, verborgenes Wissen aufdecken und Verbindungen herstellen, die andernfalls möglicherweise im Dunkeln geblieben wären, und so bei der Aufklärung von Verbrechen und der Festnahme von Kriminellen helfen. Es wird ein mehrschichtiges Modell vorgestellt, um die durch die Wiederverwendung von Wissen erzielte höhere Effektivität zu demonstrieren. Das Modell umfasst eine Abfrageschicht, die als Schnittstelle zwischen Ermittelnde und der Wissensschicht dient und es den Beteiligten der digitalen Fahrzeugforensik ermöglicht, forensische Fragen und Hypothesen über SPARQL-Abfragen zu stellen. Diese Abfragen extrahieren Daten aus der Wissensschicht, die aus zwei für diese Studie entwickelten Ontologien besteht: der allgemeinen Fahrzeugontologie, die umfassendes Wissen über moderne Fahrzeuge bietet, und der Fahrzeugtypontologie, die fahrzeugspezifisches Wissen enthält, wie z. B. Informationen über einen Tesla Autopiloten. Das Wissen wird durch die operative Schicht generiert. Diese führt digitale Forensik-Tools ein, welche die Ergebnisse in einem Ontologie-kompatiblen Format erzeugen. Zwei reale Untersuchungen wurden durchgeführt, um die Wirksamkeit des vorgeschlagenen Ansatzes zu validieren: eine Untersuchung des Tesla-Autopilot-Systems und eine eingehende Untersuchung eines GM-Airbag-Steuermoduls. Beide Untersuchungen beinhalteten entscheidende Beweismittel, die für die Rekonstruktion von Ereignissen von großer Bedeutung sind. Die Ergebnisse zeigen eine signifikante Steigerung der Effektivität digitaler forensischer Untersuchungen im Automobilbereich, durch die Verwendung des mehrschichtigen Modells. Diese Verbesserung wird durch drei Bewertungskriterien und zwölf Metriken validiert, um die Anwendungsnähe des mehrschichtigen Modells aufzuzeigen. T2 - Enthüllung von verborgenem Wissen: Über die Effektivität der digitalen Fahrzeugforensik UR - https://doi.org/10.25593/open-fau-205 Y1 - 2024 UR - https://doi.org/10.25593/open-fau-205 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-44402 PB - Friedrich-Alexander-Universität Erlangen-Nürnberg CY - Erlangen ER - TY - JOUR A1 - Lacerda, Luis M. A1 - Sperl, Jonathan I. A1 - Menzel, Marion Irene A1 - Sprenger, Tim A1 - Barker, Gareth J. A1 - Dell'Acqua, Flavio T1 - Diffusion in realistic biophysical systems can lead to aliasing effects in diffusion spectrum imaging JF - Magnetic Resonance in Medicine N2 - Purpose Diffusion spectrum imaging (DSI) is an imaging technique that has been successfully applied to resolve white matter crossings in the human brain. However, its accuracy in complex microstructure environments has not been well characterized. Theory and Methods Here we have simulated different tissue configurations, sampling schemes, and processing steps to evaluate DSI performances' under realistic biophysical conditions. A novel approach to compute the orientation distribution function (ODF) has also been developed to include biophysical constraints, namely integration ranges compatible with axial fiber diffusivities. Results Performed simulations identified several DSI configurations that consistently show aliasing artifacts caused by fast diffusion components for both isotropic diffusion and fiber configurations. The proposed method for ODF computation showed some improvement in reducing such artifacts and improving the ability to resolve crossings, while keeping the quantitative nature of the ODF. Conclusion In this study, we identified an important limitation of current DSI implementations, specifically the presence of aliasing due to fast diffusion components like those from pathological tissues, which are not well characterized, and can lead to artifactual fiber reconstructions. To minimize this issue, a new way of computing the ODF was introduced, which removes most of these artifacts and offers improved angular resolution. UR - https://doi.org/10.1002/mrm.26080 Y1 - 2015 UR - https://doi.org/10.1002/mrm.26080 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-44426 SN - 1522-2594 SN - 0740-3194 VL - 76 IS - 6 SP - 1837 EP - 1847 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Koellisch, Ulrich A1 - Laustsen, Christoffer A1 - Nørlinger, Thomas S. A1 - Østergaard, Jakob A. A1 - Flyvbjerg, Allan A1 - Gringeri, Concetta V. A1 - Menzel, Marion Irene A1 - Schulte, Rolf F. A1 - Haase, Axel A1 - Stødkilde-Jørgensen, Hans T1 - Current state-of-the-art hyperpolarized 13C-acetate-to-acetylcarnitine imaging is not indicative of the alteredbalance between glucose and fatty acid utilizationassociated with diabetes JF - Physiological Reports UR - https://doi.org/10.14814/phy2.12975 Y1 - 2016 UR - https://doi.org/10.14814/phy2.12975 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-44633 SN - 2051-817X N1 - Erratum verfügbar unter DOI "https://doi.org/10.14814/phy2.12999" VL - 4 IS - 17 PB - Wiley CY - New York ER - TY - JOUR A1 - Koellisch, Ulrich A1 - Laustsen, Christoffer A1 - Nørlinger, Thomas S. A1 - Østergaard, Jakob Appel A1 - Flyvbjerg, Allan A1 - Gringeri, Concetta V. A1 - Menzel, Marion Irene A1 - Schulte, Rolf F. A1 - Haase, Axel A1 - Stødkilde-Jørgensen, Hans T1 - Investigation of metabolic changes in STZ-induced diabetic rats with hyperpolarized [1-13C]acetate JF - Physiological Reports N2 - In the metabolism of acetate several enzymes are involved, which play an important role in free fatty acid oxidation. Fatty acid metabolism is altered in diabetes patients and therefore acetate might serve as a marker for pathological changes in the fuel selection of cells, as these changes occur in diabetes patients. Acetylcarnitine is a metabolic product of acetate, which enables its transport into the mitochondria for energy production. This study investigates whether the ratio of acetylcarnitine to acetate, measured by noninvasive hyperpolarized [1-13C]acetate magnetic resonance spectroscopy, could serve as a marker for myocardial, hepatic, and renal metabolic changes in rats with Streptozotocin (STZ)-induced diabetes in vivo. We demonstrate that the conversion of acetate to acetylcarnitine could be detected and quantified in all three organs of interest. More interestingly, we found that the hyperpolarized acetylcarnitine to acetate ratio was independent of blood glucose levels and prolonged hyperglycemia following diabetes induction in a type-1 diabetes model. UR - https://doi.org/10.14814/phy2.12474 Y1 - 2015 UR - https://doi.org/10.14814/phy2.12474 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-44529 SN - 2051-817X VL - 3 IS - 8 PB - Wiley CY - Weinheim ER - TY - JOUR A1 - Mondal, Rahul A1 - Ignatova, Evelina A1 - Walke, Daniel A1 - Broneske, David A1 - Saake, Gunter A1 - Heyer, Robert T1 - Clustering graph data: the roadmap to spectral techniques JF - Discover Artificial Intelligence N2 - AbstractGraph data models enable efficient storage, visualization, and analysis of highly interlinked data, by providing the benefits of horizontal scalability and high query performance. Clustering techniques, such as K-means, hierarchical clustering, are highly beneficial tools in data mining and machine learning to find meaningful similarities and differences between data points. Recent developments in graph data models, as well as clustering algorithms for graph data, have shown promising results in image segmentation, gene data analysis, etc. This has been primarily achieved through research and development of algorithms in the field of spectral theory, leading to the conception of spectral clustering algorithms. Spectral clustering algorithms have been one of the most effective in grouping similar data points in graph data models. In this paper, we have compiled 16 spectral clustering algorithms and compared their computational complexities, after an overview of graph data models and graph database models. Furthermore, we provided a broad taxonomy to classify most existing clustering algorithms and discussed the taxonomy in detail. UR - https://doi.org/10.1007/s44163-024-00102-x Y1 - 2024 UR - https://doi.org/10.1007/s44163-024-00102-x UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-45082 SN - 2731-0809 VL - 4 IS - 1 PB - Springer International Publishing CY - Cham ER - TY - JOUR A1 - Schropp, Theresa Constanze A1 - Schwarz, Jan Oliver A1 - Buder, Fabian T1 - Corporate foresight in light of the COVID‐19 pandemic—The crisis as a driver? JF - Futures & Foresight Science N2 - AbstractOur study emphasizes the evolving nature and increasing relevance of corporate foresight (CF) in a volatile, uncertain, complex, and ambiguous world. This research, therefore, contributes to the foresight literature, concerned with the antecedents and motivators of CF as it investigates how external events that are characterized by great uncertainty influence the CF practice of large companies. On the example of the COVID‐19 pandemic and based on a study of 25 interviews, this empirical research reveals that such events provoke an intensified engagement with the future within companies as implied by a greater resource commitment and interest in foresight. Thereby, CF and especially the development of multiple future scenarios, are considered helpful in countering uncertainty and facilitating responsiveness. UR - https://doi.org/10.1002/ffo2.178 Y1 - 2024 UR - https://doi.org/10.1002/ffo2.178 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-45121 SN - 2573-5152 VL - 6 IS - 2 PB - Wiley CY - Hoboken ER -