Open Access

Im Rahmen dieser Bachelorarbeit werden zwei Skelettierungsalgorithmen für Baum-Punktwolken implementiert und miteinander verglichen. Darüber hinaus werden zwei Erweiterungen für einen der beiden Algorithmen präsentiert.

During the Corona-Pandemic, information (e.g. from the analysis of balance sheets and payment behavior) traditionally used for corporate credit risk analysis became less valuable because it represents only past circumstances. Therefore, the use of currently published data from social media platforms, which have shown to contain valuable information regarding the financial stability of companies, should be evaluated. In this data e. g. additional information from disappointed employees or customers can be present. In order to analyze in how far this data can improve the information base for corporate credit risk assessment, Twitter data regarding the ten greatest insolvencies of German companies in 2020 and solvent counterparts is analyzed in this paper. The results from t-tests show, that sentiment before the insolvencies is significantly worse than in the comparison group which is in alignment with previously conducted research endeavors. Furthermore, companies can be classified as prospectively solvent or insolvent with up to 70% accuracy by applying the k-nearest-neighbor algorithm to monthly aggregated sentiment scores. No significant differences in the number of Tweets for both groups can be proven, which is in contrast to findings from studies which were conducted before the Corona-Pandemic. The results can be utilized by practitioners and scientists in order to improve decision support systems in the domain of corporate credit risk analysis. From a scientific point of view, the results show, that the information asymmetry between lenders and borrowers in credit relationships, which are principals and agents according to the principal-agent-theory, can be reduced based on user generated content from social media platforms. In future studies, it should be evaluated in how far the data can be integrated in established processes for credit decision making. Furthermore, additional social media platforms as well as samples of companies should be analyzed. Lastly, the authenticity of user generated contend should be taken into account in order to ensure, that credit decisions rely on truthful information only.

Unternehmen, die sich ernsthaft mit Nachhaltigkeit beschäftigen, müssen den Nachweis erbringen, dass sie positive Effekte für die Gesellschaft erzielen. Damit ist eine ganzheitliche Wirkungsmessung unabdingbar. Sozialunternehmen sollten als Vorbild für eine solche Wirkungsmessung dienen. Eine wissenschaftliche Studie auf Basis der sog. „Ergebnispyramide“ kommt jedoch zu dem Schluss, dass selbst diese ihre Wirkung bisher kaum ganzheitlich messen.

Music streaming platforms offer music listeners an overwhelming choice of music. Therefore, users of streaming platforms need the support of music recommendation systems to find music that suits their personal taste. Currently, a new class of recommender systems based on knowledge graph embeddings promises to improve the quality of recommendations, in particular to provide diverse and novel recommendations. This paper investigates how knowledge graph embeddings can improve music recommendations. First, it is shown how a collaborative knowledge graph can be derived from open music data sources. Based on this knowledge graph, the music recommender system EARS (knowledge graph Embedding-based Artist Recommender System) is presented in detail, with particular emphasis on recommendation diversity and explainability. Finally, a comprehensive evaluation with real-world data is conducted, comparing of different embeddings and investigating the influence of different types of knowledge.

The transfer of historically grown monolithic software architectures into modern service-oriented architectures creates a lot of loose coupling points. This can lead to an unforeseen system behavior and can significantly impede those continuous modernization processes, since it is not clear where bottlenecks in a system arise. It is therefore necessary to monitor such modernization processes with an adaptive monitoring concept to be able to correctly record and interpret unpredictable system dynamics. This contribution presents a generic QoS measurement framework for service-based systems. The framework consists of an XML-based specification for the measurement to be performed – the Information Model (IM) – and the QoS System, which provides an execution platform for the IM. The framework will be applied to a standard business process of the German insurance industry, and the concepts of the IM and their mapping to artifacts of the QoS System will be presented. Furtherm ore, design and implementation of the QoS System’s parser and generator module and the generated artifacts are explained in detail, e.g., event model, agents, measurement module and analyzer module.

Even for the more traditional insurance industry, the Microservices Architecture (MSA) style plays an increasingly important role in provisioning insurance services. However, insurance businesses must operate legacy applications, enterprise software, and service-based applications in parallel for a more extended transition period. The ultimate goal of our ongoing research is to design a microservice reference architecture in cooperation with our industry partners from the insurance domain that provides an approach for the integration of applications from different architecture paradigms. In Germany, individual insurance services are classified as part of the critical infrastructure. Therefore, German insurance companies must comply with the Federal Office for Information Security requirements, which the Federal Supervisory Authority enforces. Additionally, insurance companies must comply with relevant laws, regulations, and standards as part of the business’s compliance requirements. Note: Since Germany is seen as relatively ’tough’ with respect to privacy and security demands, fullfilling those demands might well be suitable (if not even ’over-achieving’) for insurances in other countries as well. The question raises thus, of how insurance services can be secured in an application landscape shaped by the MSA style to comply with the architectural and security requirements depicted above. This article highlights the specific regulations, laws, and standards the insurance industry must comply with. We present initial architectural patterns to address authentication and authorization in an MSA tailored to the requirements of our insurance industry partners.

In this paper the workflow of the project 'Untersuchungs-, Simulations- und Evaluationstool für Urbane Logistik` (USEfUL) is presented. Aiming to create a web-based decision support tool for urban logistics, the project needed to integrate multiple steps into a single workflow, which in turn needed to be executed multiple times. While a service-oriented system could not be created, the principles of service orientation was utilized to increase workflow efficiency and flexibility, allowing the workflow to be easily adapted to new concepts or research areas.

Microservices build a deeply distributed system. Although this offers significant flexibility for development teams and helps to find solutions for scalability or security questions, it also intensifies the drawbacks of a distributed system. This article offers a decision framework, which helps to increase the resiliency of microservices. A metamodel is used to represent services, resiliency patterns, and quality attributes. Furthermore, the general idea for a suggestion procedure is outlined.

The usage of microservices promises a lot of benefits concerning scalability and maintainability, rewriting large monoliths is however not always possible. Especially in scientific projects, pure microservice architectures are therefore not feasible in every project. We propose the utilization of microservice principles for the construction of microsimulations for urban transport. We present a prototypical architecture for the connection of MATSim and AnyLogic, two widely used simulation tools in the context of urban transport simulation. The proposed system combines the two tools into a singular tool supporting civil engineers in decision making on innovative urban transport concepts.

Microservices are meanwhile an established software engineering vehicle, which more and more companies are examining and adopting for their development work. Naturally, reference architectures based on microservices come into mind as a valuable thing to utilize. Initial results for such architectures are published in generic and in domain-specific form. Missing to the best of our knowledge however, is a domain-specific reference architecture based on microservices, which takes into account specifics of the insurance industry domain. Jointly with partners from the German insurance industry, we take initial steps to fill this gap in the present article. Thus, we aim towards a microservices-based reference software architecture for (at least German) insurance companies. As the main results of this article we thus provide an initial such reference architecture together with a deeper look into two important parts of it.