In this work we present a novel approach for unsupervised multi-graph matching, which applies to problems for which a Gaussian distribution of keypoint features can be assumed. We leverage cycle consistency as loss for self-supervised learning, and determine Gaussian parameters through Bayesian Optimization, yielding a highly efficient approach that scales to large datasets. Our fully unsupervised approach enables us to reach the accuracy of state-of-the-art supervised methodology for the biomedical use case of semantic cell annotation in 3D microscopy images of the worm C. elegans. To this end, our approach yields the first unsupervised atlas of C. elegans, i.e. a model of the joint distribution of all of its cell nuclei, without the need for any ground truth cell annotation. This advancement enables highly efficient semantic annotation of cells in large microscopy datasets, overcoming a current key bottleneck. Beyond C. elegans, our approach offers fully unsupervised construction of cell-level atlases for any model organism with a stereotyped body plan down to the level of unique semantic cell labels, and thus bears the potential to catalyze respective biomedical studies in a range of further species.

As digitalization advances, the number of cyberattacks on companies increases. To counteract, Cyber Security Culture (CSC) provides a holistic approach, shaping people’s values and beliefs in its process. The successful establishment of a CSC could be especially important for micro, small and medium-sized enterprises (SMEs) with limited resources. The objective of this research is to determine factors leading to the successful establishment and maintenance of a CSC in SMEs. A literature review was conducted, in which existing literature has been reviewed on the topic of CSC and associated determinants. A conceptual model including four main determinants and eight hypotheses was established. To further evaluate these factors, ten guided interviews with experts from German SMEs were conducted and evaluated by means of a qualitative content analysis according to Mayring. As a result, a research model with the determinants for the successful establishment of a CSC in SMEs was finalized. The four resulting main factors are: Awareness & knowledge, resources, support from top management and continuous development.

Uncertainty Quantification (UQ) is crucial for reliable image segmentation. Yet, while the field sees continual development of novel methods, a lack of agreed-upon benchmarks limits their systematic comparison and evaluation: Current UQ methods are typically tested either on overly simplistic toy datasets or on complex real-world datasets that do not allow to discern true uncertainty. To unify both controllability and complexity, we introduce Arctique, a procedurally generated dataset modeled after histopathological colon images. We chose histopathological images for two reasons: 1) their complexity in terms of intricate object structures and highly variable appearance, which yields challenging segmentation problems, and 2) their broad prevalence for medical diagnosis and respective relevance of high-quality UQ. To generate Arctique, we established a Blender-based framework for 3D scene creation with intrinsic noise manipulation. Arctique contains up to 50,000 rendered images with precise masks as well as noisy label simulations. We show that by independently controlling the uncertainty in both images and labels, we can effectively study the performance of several commonly used UQ methods. Hence, Arctique serves as a critical resource for benchmarking and advancing UQ techniques and other methodologies in complex, multi-object environments, bridging the gap between realism and controllability. All code is publicly available, allowing re-creation and controlled manipulations of our shipped images as well as creation and rendering of new scenes.

Following scientific contribution bundles results from the research project "CyberWuP", which is supported by the Ministerium des Inneren, für Digitalisierung und Kommunen Baden-Württemberg (Germany). Results on three research questions of related studies are presented. Key data on the current equipment and know-how regarding cybersecurity in SMEs as well as information on the required support of SMEs are provided. In addition, a structural equation model is used, which shows the significant positive influence of "motives for crime" and "lack of prevention" on cybercrime as a threat to SMEs.

For securing multicast traffic with IPSec mechanisms, a mandatory requirement is that each member of the communication group owns the group security parameters. For this purpose, a concept for multicast Internet key exchange is introduced for negotiation and controlled distribution of group security parameters and membership management. A daemon is presented for use in a military environment. Hence, its protocols are designed to be insensitive against packet loss and are able to deal with special military conditions.

In this note, we show that LR(k) testing of context free grammars with respect to random instances is many-one complete for Distributional NP. The same result holds for testing whether a context free grammar is LL(k), strong LL(k), SLR(k), LC(k) or strong LC(k), respectively.