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Tunable femtosecond optical parametric amplifier pumped by 1 kHz ultrafast thin-disk laser pulses for coherent anti-Stokes Raman scattering
No full textFrequency comb generation based on optical parametric oscillation with second-order nonlinear materials
No full textInvestigating the temporal dynamics and modelling of mid-level feature representations in humans
No full textScene perception is a key function of biological visual systems. According to the hierarchical processing view, scene perception in the human brain begins with low-level features, progresses to mid-level features, and ends with high-level features. While low- and high-level feature processing is well-studied, research on mid-level features remains limited. Here, we addressed this gap by investigating when mid-level features are processed in humans using a novel stimulus set of naturalistic scenes as images and videos, accompanied with ground-truth annotations for five mid-level features (reflectance, lighting, world normals, scene depth and skeleton position), and two framing features: one low-level (edges) and one high-level feature (action). To reveal when low-, mid- and high-level features are represented in the brain, we collected electroencephalography (EEG) data from human participants during stimulus presentation and trained encoding models to predict EEG data from ground-truth annotations. We revealed that mid-level features were best represented between ∼100 and ∼250 ms post-stimulus, between low- and high-level features. Moreover, we assessed scene- and action-trained convolutional neural networks (CNNs) as models of mid-level feature processing in humans. We found a comparable processing order for mid-but not low- or high-level features with humans. Overall, our results characterize mid-level feature processing in humans in the temporal domain and reveal CNNs as suitable models of the processing hierarchy of mid-level vision in humans
Highly Miniaturized in-ear MEMS Loudspeaker Featuring High SPL
No full text865868In this paper, simulation, fabrication, and measurement results of MEMS loudspeakers for in-ear applications are presented. The speakers are based on a novel design concept, enabling exceptionally high sound pressure levels (SPL) at very small sizes. Fabricated speakers mounted in a prototype earphone and attached to an IEC 60318-4 ear simulator generate 105 dB SPL within the whole audible frequency range. With a device area of only 2.4 x 2.4 mm2, this yields a normalized SPL of 89.7 dB/mm2, exceeding the previous generation by 9.4 dB/mm2</sup
How lightweight design and sustainable aviation fuels can change the European environmental impact of aviation - a simplified case study
No full textSkip Probabilities for Subprocesses
No full text129136Conformance checking techniques compare process models of organizational behavior with observed process executions to reveal their deviations. Traditional alignments concern individual activities and provide a single out of potentially infinitely many explanations for observed deviations. Skip alignments lift insights to subprocesses and provide all possible explanations. Though valuable for analysts and process mining tools, there exist no interpretations how likely these deviations are. In this paper, we introduce skip probabilities revealing how likely certain subprocesses deviate w.r.t. an event log of observed process executions. We show the formal derivation of this calculation and demonstrate the feasibility of its computation. By analyzing a realistic case, we empirically show that yet hidden process insights can be derived from skip probabilities and how they contribute to targeted process improvement
Ceramic micro-PEM fuel cell systems for self-sufficient supply of miniaturized systems below one watt (eMikro)
No full text6872The results presented were created in the publicly funded project "eMikro" within a consortium consisting of the partners balticFuelCells GmbH, VIA Electronic GmbH, Prignitz Mikrosystemtechnik GmbH, Fraunhofer IKTS and Fraunhofer IFAM and represents the current state of research on ceramic micro energy systems after 3 years of development. In the field of energy storage, new miniaturized metal hydride storage devices have been developed and optimized in terms of energy density and cycle stability. In the field of ceramic multilayer-based low-temperature fuel cells, a 4-cell stack was developed that works with an output of 150 mW/cm2 and a stack voltage of 2 volts. A novelty is the development of passive microvalves in LTCC, which do not require additional energy to supply the system with hydrogen and allow the integrated tank to be reloaded. The first characterizations of the individual components as well as the overall system are presented
Fast-paced quality assurance in the digital ecosystem for mobile services - From the really great pain, viral posts and the stay on the train Schnelllebige Qualitätssicherung im digitalen ökosystem für mobile Dienste - vom ganz großen Schmerz, viralen Posts und dem Aufenthalt in der Bahn
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SAFETY4RAILS Information System platform demonstration at Madrid Metro simulation exercise
No full text21512158SAFETY4RAILS is the acronym for the European Union Horizon 2020 co-funded innovation project entitled: “Data-based analysis for safety and security protection for detection, prevention, mitigation and response in transmodal metro and railway networks” which started in October 2020. Its focus is to support the increase of security and resilience against combined cyber-physical threats including natural hazards to railway and metro systems. Its objectives target capabilities to support the characteristics of resilient systems; resilience represented by cycles containing phases of identification, protection, detection, response and recovery (Department of Communications 2019) (or similarly named phases). An ESREL paper in 2021 introduced the SAFETY4RAILS project and the SAFETY4RAILS Information System platform as well as some of the tools that are included in the platform. This paper will describe the architectural solution implemented for the platform in the last year and the demonstration of representative capabilities from the first simulation exercise with Madrid Metro at the beginning of 2022
Fraunhofer SIT at CheckThat! 2023: Can LLMs Be Used for Data Augmentation & Few-Shot Classification? Detecting Subjectivity in Text Using ChatGPT
No full text329336The fight against the spread of misinformation and rumors on the Internet has become a difficult issue lately. In some cases, it is difficult to tell whether a news article published on the Internet contains opinions or was written objectively. This year’s CheckThat! 2023 Task 2 dealt with the recognition of such texts. Due to the recent rise of large language models, this work analyzed the extent to which large language models such as ChatGPT can be used to augment unbalanced data sets and whether they can serve as a reliable few-shot classifier. The proposed approaches were trained and evaluated on the English and German subtasks of the challenge. While the models trained with the augmented data were unable to outperform the BERT models trained without the additional data, the few-shot classification scheme was able to outperform across different data set splits, most notably with the English test set. On the private test sets, the proposed ChatGPT-based few-shot classifiers achieved an F1 value of 0.73 on the English data and an F1 value of 0.68 on the German data. However, they have not been shown to achieve stable performance over multiple data set splits